diff --git a/proys/InsectPopulation/AutomDiff_V2.jl b/proys/InsectPopulation/AutomDiff_V2.jl
new file mode 100644
index 0000000..0b99f5b
--- /dev/null
+++ b/proys/InsectPopulation/AutomDiff_V2.jl
@@ -0,0 +1,95 @@
+#Modulo de Diferenciacion Automatica
+#El siguiente modulo define la estructura de los objetos "duales" asi como las operaciones entre ellos.
+#Autores: Daniel (https://github.com/danmarurr) y Fernanda (https://github.com/FernandaPerez)
+
+
+__precompile__(true)
+
+module AD
+    import Base: +, -, *, /, ^, ==
+    
+    export Dual, xdual
+
+
+
+    type Dual{T<:Real}
+    # código: 
+    fun :: T
+    der :: T
+    end
+    
+    Dual(a, b) = Dual(promote(a, b) ...)
+    # Aqui se define un método que garantiza que el dual de un número cumple lo requerido
+    Dual(a) = Dual(a, zero(0))
+    # Aqui se define la función `xdual`, que se usará para identificar la variable independiente
+
+    function xdual(x0)
+        Dual(x0, one(x0))
+    end
+
+    # Definiendo operaciones cuando los argumentos son Duales
+    +(a::Dual, b::Dual) = Dual(a.fun + b.fun, a.der + b.der)
+    -(a::Dual, b::Dual) = Dual(a.fun - b.fun, a.der - b.der)
+    *(a::Dual, b::Dual) = Dual(a.fun * b.fun, a.der*b.fun + b.der*a.fun)
+    /(a::Dual, b::Dual) = Dual(a.fun / b.fun, (a.der - b.der*(a.fun/b.fun))/b.fun)
+    ^{T<:Int}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Float64}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Rational}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Irrational}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ==(a::Dual, b::Dual) = (a.fun == b.fun && a.der == b.der)
+
+
+    # Definiendo operaciones cuando el argumento de la derecha es un número
+    +{T<:Real}(a::Dual, γ::T) = +(a, Dual(γ))
+    -{T<:Real}(a::Dual, γ::T) = -(a, Dual(γ))
+    *{T<:Real}(a::Dual, γ::T) = *(a, Dual(γ))
+    /{T<:Real}(a::Dual, γ::T) = /(a, Dual(γ))
+
+    # Definiendo operaciones cuando el argumento de la izquierda es un número
+
+    +{T<:Real}(γ::T, a::Dual) = +(Dual(γ), a)
+    -{T<:Real}(γ::T, a::Dual) = -(Dual(γ), a)
+    *{T<:Real}(γ::T, a::Dual) = *(Dual(γ), a)
+    /{T<:Real}(γ::T, a::Dual) = /(Dual(γ), a)
+
+
+#Importamos todas las funciones para las cuales queremos definir su operacion 
+import Base: ^, exp, sqrt, cbrt, sin, cos, tan, cot, sec, csc, sinh, cosh, tanh, coth, sech, csch,
+asin,   acos,   atan,   acot,   asec,   acsc,
+asinh,  acosh,  atanh,  acoth,  asech,  acsch
+
+#Vector con todos los símbolos asociados a las funciones trigométricas, exponenciales, etc. y sus respectivas
+#derivadas
+Vec_Func = [(:sin, :cos), (:cos, :(x -> -sin(x))), (:tan, :(x -> (sec(x))^2)), (:cot, :(x -> -(csc(x))^2)), 
+    (:sec, :(x -> sec(x)*tan(x))), (:csc, :(x -> -csc(x)*cot(x))), (:sinh, :cosh), (:cosh, :sinh), 
+    (:tanh, :(x -> (sech(x))^2)), (:coth, :(x -> -(csch(x))^2)), (:asin, :(x -> 1/sqrt(1-x^2))), 
+    (:acos, :(x -> -1/sqrt(1-x^2))), (:atan, :(x -> 1/(1+x^2))), (:acot, :(x -> -1/(1+x^2))),
+    (:asec, :(x -> 1/(sqrt(x^2-1)*x))), (:acsc, :(x -> -1/(sqrt(x^2-1)*x))), (:asinh, :(x -> 1/sqrt(1+x^2))),
+    (:acosh, :(x -> 1/sqrt(x^2-1))), (:atanh, :(x -> 1/(1-x^2))), (:acoth, :(x -> 1/(1-x^2))),
+    (:asech, :(x -> 1/(x*sqrt(1-x^2)))), (:acsch, :(x -> -1/(x*sqrt(1+x^2)))), (:sqrt, :(x -> 1/(2*sqrt(x)))), (:exp, :exp),
+    (:cbrt, :(x -> 1/(3*x^(2/3))))]
+
+#Casos especiales: los logarítmos y a^x
+log(a::Dual) = Dual(log(a.fun), a.der/a.fun)
+log{T<:Real}(b::T, a::Dual) = Dual(log(b,a.fun), a.der/(log(b)*a.fun))
+^{T<:Real}(b::T, a::Dual) = Dual(b^a.fun, a.der*log(b)*b^a.fun)
+
+#Loop para crear los nuevos métodos a partir de los símbolos
+for r in 1:length(Vec_Func)
+    fn = Vec_Func[r][1] #El primer símbolo está asociado a la función
+    der = Vec_Func[r][2] #El segundo símbolo está asociado a la derivada de la función
+    ex = quote #Creamos una nueva expresión
+        function ($fn)(a::Dual) #Definimos fn(a::Dual)
+            fun = ($fn)(a.fun)
+            derv = ($der)(a.fun)
+            return Dual(fun, derv*a.der) #Aplicamos la regla de la cadena
+        end
+    end
+    @eval $ex #Evaluamos la expresión para crear el método
+end
+
+
+
+
+end
+
diff --git a/proys/InsectPopulation/DatosPlano/ccs1.csv b/proys/InsectPopulation/DatosPlano/ccs1.csv
new file mode 100644
index 0000000..109d8dc
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/ccs1.csv
@@ -0,0 +1,32670 @@
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diff --git a/proys/InsectPopulation/DatosPlano/ccs2.csv b/proys/InsectPopulation/DatosPlano/ccs2.csv
new file mode 100644
index 0000000..918854e
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/ccs2.csv
@@ -0,0 +1,32670 @@
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diff --git a/proys/InsectPopulation/DatosPlano/ccs3.csv b/proys/InsectPopulation/DatosPlano/ccs3.csv
new file mode 100644
index 0000000..d64d57f
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/ccs3.csv
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diff --git a/proys/InsectPopulation/DatosPlano/mms1.csv b/proys/InsectPopulation/DatosPlano/mms1.csv
new file mode 100644
index 0000000..7e9961d
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/mms1.csv
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diff --git a/proys/InsectPopulation/DatosPlano/mms2.csv b/proys/InsectPopulation/DatosPlano/mms2.csv
new file mode 100644
index 0000000..5dd4b3c
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/mms2.csv
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diff --git a/proys/InsectPopulation/DatosPlano/mms3.csv b/proys/InsectPopulation/DatosPlano/mms3.csv
new file mode 100644
index 0000000..babeba7
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/mms3.csv
@@ -0,0 +1,33660 @@
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diff --git a/proys/InsectPopulation/DatosPlano/rrs1.csv b/proys/InsectPopulation/DatosPlano/rrs1.csv
new file mode 100644
index 0000000..bd810dd
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/rrs1.csv
@@ -0,0 +1,32670 @@
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+21.1
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+24.1
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+25.1
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+28
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+32
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+34
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+35
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+37.1
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+38.1
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+39
+39.1
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+40.1
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+41.1
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+42
+42.1
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+43
+43.1
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+44.1
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+44.9
+45
+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56
+56.1
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+57.1
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+58.1
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+59.1
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+64.1
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+65.1
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+67.1
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+68.1
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+69.1
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+71.1
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+75.1
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+79.1
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+89.1
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+90.1
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+38.1
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+39.1
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+41.1
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+42.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+50.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+61.1
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+8.1
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+9.1
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+39.1
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+40.1
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+41.1
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+42.1
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+44.1
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+38.1
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+39.1
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+41.1
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+42.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
+47.2
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+48.1
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+48.7
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+49.1
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+50.1
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+54.1
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+55.1
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+56.1
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+57.1
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+69.1
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+81.1
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+97.1
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+98.1
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+48.1
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+88.1
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+89.1
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+99.1
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+32
+32.1
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+33
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+34
+34.1
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+35
+35.1
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+36.1
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+37
+37.1
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+38
+38.1
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+39
+39.1
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+40
+40.1
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+41
+41.1
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+41.6
+41.7
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+41.9
+42
+42.1
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+43
+43.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+56
+56.1
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+57.1
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+58.1
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+66.1
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+67.1
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+69
+69.1
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+38.1
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+39.1
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+40.1
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+41.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+65.1
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+66.1
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+67.1
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+68.1
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+69.1
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+38.1
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+39.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+43.1
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+44.1
+44.2
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+57.1
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+66.1
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+81.1
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+97.1
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+48.1
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+29
+29.1
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+31.1
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+32
+32.1
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+33
+33.1
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+34
+34.1
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+35
+35.1
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+36.1
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+37
+37.1
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+38
+38.1
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+39
+39.1
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+40
+40.1
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+41
+41.1
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+42
+42.1
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+43
+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+50.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+64.1
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+65.1
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+66
+66.1
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+67.1
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+68.1
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+69.1
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+79.1
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+80.1
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+81.1
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+38.1
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+39.1
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+41.1
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+44.1
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+47.1
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+48.1
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+49.1
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+65.1
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+66.1
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+67.1
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+69.1
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+70.1
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+39.1
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+48.1
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+49.1
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+65.1
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+38.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+50.1
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+54.1
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+55.1
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+56
+56.1
+56.2
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+57.1
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+58.1
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+59.1
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+60.1
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+64.1
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+65.1
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+66.1
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+97.1
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+98.1
+98.2
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+99.1
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+39.1
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+40.1
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+41
+41.1
+41.2
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+41.9
+42
+42.1
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+42.7
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+43.1
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+43.7
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+43.9
+44
+44.1
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+44.7
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+44.9
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+50.1
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+54.1
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+56.1
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+57.1
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+58.1
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+59.1
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+66.1
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+75.1
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+79.1
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+92.1
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+97.1
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+48.1
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+49.1
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+83.1
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+26
+26.1
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+27
+27.1
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+28
+28.1
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+29
+29.1
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+32
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+33
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+34
+34.1
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+35
+35.1
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+36.1
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+37.1
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+38
+38.1
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+39
+39.1
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+40.1
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+41.1
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+41.7
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+42
+42.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+57.1
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+58.1
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+59.1
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+63.1
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+64.1
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+65.1
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+66.1
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+67.1
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+69.1
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+75.1
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+79.1
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+90.1
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+91.1
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+38.1
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+39.1
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+41.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+56.1
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+57.1
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+58.1
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+64.1
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+65.1
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+66.1
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+67.1
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diff --git a/proys/InsectPopulation/DatosPlano/rrs2.csv b/proys/InsectPopulation/DatosPlano/rrs2.csv
new file mode 100644
index 0000000..bd810dd
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/rrs2.csv
@@ -0,0 +1,32670 @@
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+36.1
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+37.1
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+38.1
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+39
+39.1
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+40
+40.1
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+41
+41.1
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+41.7
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+42
+42.1
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+43.1
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+43.7
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+44.1
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+44.7
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+57.1
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+58.1
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+59.1
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+66.1
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+74.1
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+75.1
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+76.1
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+39.1
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+48.1
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+49.1
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+32
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+35
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+38.1
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+39.1
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+40.1
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+41.1
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+43.7
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+55.1
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+56
+56.1
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+57.1
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+58.1
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+59.1
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+64.1
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+65.1
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+69.1
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+38.1
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+39.1
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+44.1
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+45.1
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+46.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+41.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+69.1
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+38.1
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+39.1
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+41.1
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+42.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+58.1
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+59.1
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+89.1
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+99.1
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+33
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+34
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+35
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+38.1
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+39
+39.1
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+40
+40.1
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+41.1
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+42
+42.1
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+43.1
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+44.1
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+45.1
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+48.1
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+49.1
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+56.1
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+57.1
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+58.1
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+59.1
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+38.1
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+39.1
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+40.1
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+41.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+65.1
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+66.1
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+69.1
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+75.1
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+38.1
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+39.1
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+41.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+41.1
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+43.1
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+44.1
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+48.1
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+49.1
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+32
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+34
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+35
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+38.1
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+39
+39.1
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+40.1
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+41.1
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+42.1
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+44.1
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+47.1
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+49.1
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+55.1
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+56.1
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+57.1
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+58.1
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+65.1
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+68.1
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+69.1
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+48.1
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+49.1
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+69.1
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+71.1
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+38.1
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+39.1
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+40.1
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+41.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+56.1
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+57.1
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+39.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+66.1
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+98.1
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+99.1
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+41.1
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+48.1
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+49.1
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diff --git a/proys/InsectPopulation/DatosPlano/rrs3.csv b/proys/InsectPopulation/DatosPlano/rrs3.csv
new file mode 100644
index 0000000..ceddda0
--- /dev/null
+++ b/proys/InsectPopulation/DatosPlano/rrs3.csv
@@ -0,0 +1,33660 @@
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+32
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+34
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+35
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+39.1
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+40.1
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+41.1
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+42.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+56.1
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+57.1
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+58.1
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+59.1
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+48.1
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+49.1
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+57.1
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+65.1
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+66.1
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+38.1
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+39.1
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+41.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+58.1
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+69.1
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+38.1
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+39.1
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+41.1
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+42.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+50.1
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+51.1
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+38
+38.1
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+39.1
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+40
+40.1
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+41
+41.1
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+41.7
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+42
+42.1
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+43.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+57.1
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+58.1
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+59.1
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+75.1
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+48.1
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+32
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+38.1
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+39.1
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+40.1
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+41
+41.1
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+42
+42.1
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+43
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+69.1
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+39.1
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+47.1
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+48.1
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+49.1
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+56.1
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+57.1
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+58.1
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+59.1
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+63.1
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+38.1
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+41.1
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+44.1
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+45.1
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+48.1
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+38.1
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+39.1
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+41.1
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+43.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+34
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+34.7
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+35
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+38.1
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+39.1
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+40
+40.1
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+41
+41.1
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+44.1
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+49.1
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+57.1
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+69.1
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+19.1
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+32
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+35
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+36.1
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+38.1
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+39
+39.1
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+40.1
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+41.1
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+42
+42.1
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+43
+43.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56
+56.1
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+57.1
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+58.1
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+59.1
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+64.1
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+66.1
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+67.1
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+68.1
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+69.1
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+38.1
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+39.1
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+41.1
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+44.1
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+45.1
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+46.1
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+47.1
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+48.1
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+49.1
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+50.1
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+54.1
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+55.1
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+56.1
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+57.1
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+58.1
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+59.1
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+38.1
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+39.1
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+41.1
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+38.1
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+39.1
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+41.1
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+43.1
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+44.1
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+45.1
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+49.1
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+81.1
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+32
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+33
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+34
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+35
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+38.1
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+39
+39.1
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+40
+40.1
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+41
+41.1
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+41.7
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+42
+42.1
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+44.1
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+47.1
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+48.1
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+49.1
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+57.1
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+66.1
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+69.1
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+35
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+38.1
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+39.1
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+41.1
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+44.1
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+45.1
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+47.1
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+48.1
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+49.1
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+54.1
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+57.1
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+44.1
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+46.1
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+47.1
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+48.1
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+49.1
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+54.1
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+55.1
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+56.1
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+57.1
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diff --git a/proys/InsectPopulation/PabloProy/M1.csv b/proys/InsectPopulation/PabloProy/M1.csv
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index 0000000..c8ef9cc
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diff --git a/proys/InsectPopulation/PabloProy/finalpopulation.ipynb b/proys/InsectPopulation/PabloProy/finalpopulation.ipynb
new file mode 100644
index 0000000..52dbcc8
--- /dev/null
+++ b/proys/InsectPopulation/PabloProy/finalpopulation.ipynb
@@ -0,0 +1,908 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Control de Poblaciones de Insectos al Introducir Insectos Estériles\n",
+    "\n",
+    "$$\n",
+    "N_{t+1}=\\frac{R N_t^2}{(R-1)\\frac{N_t^2}{M}+N_t+S}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "En 1937, E. F. Knipling, propuso la Técnica de Insectos Estériles (SIT, en inglés). La técnica no fue implementada haste 1958 sobre una plaga de  `screwworm` en EEUU usando métodos físicos y químicos para causar esterilidad. El método ha sido implementado en México o otros países de Sudamérica con éxito.\n",
+    "\n",
+    "<img src=\"knipling.png\" width=\"200\">\n",
+    "<img src=\"worm.png\" width=\"200\">\n",
+    "\n",
+    "Hasta años recientes SIT sigue siendo una técnica usada y estudiada en genética de poblaciones\n",
+    "\n",
+    "* `Oliva, C., Damiens, D., Vreysen, M., Lempeiere, G., & Gilles, J. (2013). Reproductive strategies of aedes albopictus (diptera: Culicidae) and implications for the sterile insect technique. Plos One, 8(11), e78884. doi:10.1371/journal.pone.0078884`\n",
+    "\n",
+    "\n",
+    "* `Barnes, B. N., Hofmeyr, J. H., Groenewald, S., Conlong, D. E., & Wohlfarter, M. (2015). The sterile insect technique in agricultural crops in south africa: A metamorphosis …. but will it fly? African Entomology, 23(1), 1-18. doi:10.4001/003.023.0103`\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: No working GUI backend found for matplotlib.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PyPlotBackend()"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "using Plots, LaTeXStrings\n",
+    "\n",
+    "pyplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "f (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f(x,α,β,γ) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "iteramapeo (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "``` Este código nos permite iterar una función f n veces dada una condición inicial x0. \n",
+    "``` \n",
+    "\n",
+    "function iteramapeo(f, x0, n)\n",
+    "    xx = [x0]\n",
+    "    fx = [0.0]\n",
+    "    for it = 1:n\n",
+    "        x1 = f(x0)\n",
+    "        push!(xx, x0)\n",
+    "        push!(fx, x1)\n",
+    "        x0 = x1\n",
+    "        push!(xx,x1)\n",
+    "        push!(fx,x1)\n",
+    "    end\n",
+    "    xx, fx\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#1) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "``` Aquí definimos el valor de los parámetros que utilizamos con la convención \\alpha \\equiv R, \\beta \\equiv M,\n",
+    "``` \\gamma \\equiv S ```\n",
+    "α=500.0\n",
+    "β=10.0\n",
+    "γ=2.0\n",
+    "func = x -> f(x,α,β,γ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div id=\"interact-js-shim\">\n",
+       "    <script charset=\"utf-8\">\n",
+       "(function (IPython, $, _, MathJax) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    var OutputArea = IPython.version >= \"4.0.0\" ? require(\"notebook/js/outputarea\").OutputArea : IPython.OutputArea;\n",
+       "\n",
+       "    var redrawValue = function (container, type, val) {\n",
+       "\tvar selector = $(\"<div/>\");\n",
+       "\tvar oa = new OutputArea(_.extend(selector, {\n",
+       "\t    selector: selector,\n",
+       "\t    prompt_area: true,\n",
+       "\t    events: IPython.events,\n",
+       "\t    keyboard_manager: IPython.keyboard_manager\n",
+       "\t})); // Hack to work with IPython 2.1.0\n",
+       "\n",
+       "\tswitch (type) {\n",
+       "\tcase \"image/png\":\n",
+       "            var _src = 'data:' + type + ';base64,' + val;\n",
+       "\t    $(container).find(\"img\").attr('src', _src);\n",
+       "\t    break;\n",
+       "\tdefault:\n",
+       "\t    var toinsert = OutputArea.append_map[type].apply(\n",
+       "\t\toa, [val, {}, selector]\n",
+       "\t    );\n",
+       "\t    $(container).empty().append(toinsert.contents());\n",
+       "\t    selector.remove();\n",
+       "\t}\n",
+       "\tif (type === \"text/latex\" && MathJax) {\n",
+       "\t    MathJax.Hub.Queue([\"Typeset\", MathJax.Hub, toinsert.get(0)]);\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        //_.extend(comm_manager.targets, require(\"widgets/js/widget\"))\n",
+       "\t    comm_manager.register_target(\"Signal\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                //Widgets.log(\"message received\", msg);\n",
+       "                var val = msg.content.data.value;\n",
+       "                $(\".signal-\" + comm.comm_id).each(function() {\n",
+       "                var type = $(this).data(\"type\");\n",
+       "                if (val[type]) {\n",
+       "                    redrawValue(this, type, val[type], type);\n",
+       "                }\n",
+       "                });\n",
+       "                delete val;\n",
+       "                delete msg.content.data.value;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "\t    // coordingate with Comm and redraw Signals\n",
+       "\t    // XXX: Test using Reactive here to improve performance\n",
+       "\t    $([IPython.events]).on(\n",
+       "\t\t'output_appended.OutputArea', function (event, type, value, md, toinsert) {\n",
+       "\t\t    if (md && md.reactive) {\n",
+       "                // console.log(md.comm_id);\n",
+       "                toinsert.addClass(\"signal-\" + md.comm_id);\n",
+       "                toinsert.data(\"type\", type);\n",
+       "                // Signal back indicating the mimetype required\n",
+       "                var comm_manager = IPython.notebook.kernel.comm_manager;\n",
+       "                var comm = comm_manager.comms[md.comm_id];\n",
+       "                comm.then(function (c) {\n",
+       "                    c.send({action: \"subscribe_mime\",\n",
+       "                       mime: type});\n",
+       "                    toinsert.bind(\"destroyed\", function() {\n",
+       "                        c.send({action: \"unsubscribe_mime\",\n",
+       "                               mime: type});\n",
+       "                    });\n",
+       "                })\n",
+       "\t\t    }\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery, _, MathJax);\n",
+       "</script>\n",
+       "    <script>\n",
+       "        window.interactLoadedFlag = true\n",
+       "       $(\"#interact-js-shim\").bind(\"destroyed\", function () {\n",
+       "           if (window.interactLoadedFlag) {\n",
+       "               console.warn(\"JavaScript required by Interact will be removed if you remove this cell or run using Interact more than once.\")\n",
+       "           }\n",
+       "       })\n",
+       "       $([IPython.events]).on(\"kernel_starting.Kernel kernel_restarting.Kernel\", function () { window.interactLoadedFlag = false })\n",
+       "   </script>\n",
+       "</div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "using Interact "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "xfin,ffin = iteramapeo(func,200.0,10);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(100.0, nactions=0),\"γ\",100.0,0.0:1.0:200.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {
+      "comm_id": "dd5ad9fa-6638-4016-ab33-fd67ec618fa2",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 20.0\n",
+    "``` Este codigo genera 200 gráficas para distintos valores de \\gamma y luego hace un .gif almacenado temporalmente\n",
+    "```\n",
+    "@manipulate for γ in 0:1.0:200\n",
+    "    pobla(x)=f(x,α,β,γ)\n",
+    "    xfin,ffin = iteramapeo(pobla,10.0,16); #Añade la condición inicial con la que se analiza el mapeo y \n",
+    "    #su trayectoria, la función  definida un renglón arriba y el número de iteraciones.\n",
+    "    plot(-10:1/32:100, pobla, xaxis=(L\"x\", (-10.0, 100.0)), yaxis=(L\"F_\\alpha(x)\",(-10.0,20.0)) # Hace la gráfica\n",
+    "    #con especificaciones para ejees.\n",
+    "    title!(\"Analisis grafico para distintos valores de S\")\n",
+    "    plot!(-10:1/32:50, identity) #Grafica la identidad del análisis gráfico\n",
+    "    plot!(xfin, ffin, marker=(:dot, 3, 0.4)) #Señala dónde terminó la condición inicial dada\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Aquí mostrasmos una gráfica del comportamiento temporal del mapeo cuando $S_{c}=0$ y se varía la condición inicial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/pymodules/python2.7/matplotlib/font_manager.py:1236: UserWarning: findfont: Font family ['Helvetica'] not found. Falling back to Bitstream Vera Sans\n",
+      "  (prop.get_family(), self.defaultFamily[fontext]))\n",
+      "/usr/lib/pymodules/python2.7/matplotlib/font_manager.py:1246: UserWarning: findfont: Could not match :family=Bitstream Vera Sans:style=normal:variant=normal:weight=normal:stretch=normal:size=8.0. Returning /usr/share/matplotlib/mpl-data/fonts/ttf/cmb10.ttf\n",
+      "  UserWarning)\n",
+      "/usr/lib/pymodules/python2.7/matplotlib/font_manager.py:1246: UserWarning: findfont: Could not match :family=Bitstream Vera Sans:style=normal:variant=normal:weight=normal:stretch=normal:size=11.0. Returning /usr/share/matplotlib/mpl-data/fonts/ttf/cmb10.ttf\n",
+      "  UserWarning)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 25.0\n",
+    "g(x,α,β)=(α*(x)^2)/((((α-1.0)*(x^2))/β + x)) #Define el mapeo con \\gamma = 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(50.0, nactions=0),\"i\",50.0,0.0:1.0:100.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {
+      "comm_id": "3daa2a7b-cad3-4c69-b2fc-cbf3a2e563a6",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@manipulate for i in 0:1.0:100 #Este código realiza una gráfica interactiva que cambia la condición inicial\n",
+    "    # en cada paso entre 0 y 100 con los valores de \\alpha y \\beta dados anteriormente.\n",
+    "    poblaciones(i) = g(i,α,β)\n",
+    "    xfin,ffin = iteramapeo(poblaciones,i,20);\n",
+    "    plot(-10:1/32:100, poblaciones, xaxis=(L\"x\", (-10.0,100.0)), yaxis=(L\"F_\\alpha(x)\",(-100.0,100.0)))\n",
+    "    title!(\"Evolucion de la poblacion sin insectos infertiles\")\n",
+    "    plot!(-30:1/32:100, identity)\n",
+    "    plot!(xfin, ffin, marker=(:dot, 3, 0.4))\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Vemos que en éste caso, la población total nunca muere, tal como se esperaba, pues no hay insectos infértiles en este caso."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "Se resolvió la ecuación $N(x)-x=0$ para encontrar los puntos fijos del mapeo en términos de los parámetros R,S y M, obteniendo:\n",
+    "\n",
+    "$X_{0}= 0$\n",
+    "\n",
+    "\n",
+    "y    \n",
+    "\n",
+    "\n",
+    "\n",
+    "$X_{12}= \\frac{\\pm M(1-R)+\\sqrt{R-1}\\sqrt{M^{2}(1-R)-4MS}}{2(1-R)}$\n",
+    "\n",
+    "\n",
+    "\n",
+    "Por lo que, para encontrar poblaciones estáticas distintas de cero, tenemos que se deben cumplir las siguientes condiciones:\n",
+    "\n",
+    "$R> 1 $ ^ $M > \\frac{4S}{R-1}$\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Nothing to be done\n",
+      "INFO: METADATA is out-of-date — you may not have the latest version of Roots\n",
+      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.add(\"Roots\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "using Roots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "puntofijo (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function puntofijo(F::Function, range) #Este código calcula los puntos fijos de una función F en un rango range.\n",
+    "    pf= fzeros(x -> (F(x) - x) , range)\n",
+    "    return pf\n",
+    "end "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "F (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "\n",
+    "F(x) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x)) #Se define la función con nuevos parámetros arbitrarios, pero que\n",
+    "#cumplen las condiciones mencionadas.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3-element Array{Float64,1}:\n",
+       "  0.0    \n",
+       "  8.33333\n",
+       " 16.6667 "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pf=puntofijo(F,[0,20.0]) #Se calculan los puntos fijos de éste mapeo."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 2 methods)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g(x)= (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x)) -x  #Se define el mapeo que nos permite estudiar la localización \n",
+    "#de los puntos fijos al variar los parámetros."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#24) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "func=x -> g(x) #Se dan valores a los parámetros para realizar un ejemplo de sus puntos fijos."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A continuación se muestra una gráfica de los puntos fijos del mapeo en términos de los parámetros\n",
+    "$R=10$,$M=25$ y $S=50$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(-10:1/32:30, func,xticks=-10:0.5:100,yticks=-10:0.5:50) #Se grafica el mapeo N(X)-x\n",
+    "xlabel!(L\"x\")\n",
+    "ylabel!(L\"N(x)-x\")\n",
+    "title!(\"Puntos fijos de N(x)\")\n",
+    "plot!([8.3,8.3], [1, -1, 0]) #Se marcan los puntos fijos sobre la gráfica.\n",
+    "plot!([0,0], [1, -1,0])\n",
+    "plot!([16.66,  16.66], [1, -1, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A continuación se muestran graficas que relacionan los parámetros y el comportamiento de los puntos fijos dependiendo de éstos."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La función a estudiar es:\n",
+    "\n",
+    "$N(X)-X= \\frac{MRX^{2}}{(R-1)X^{2}+M(X+S)} -X $\n",
+    "\n",
+    " Nos interesa encontrar éste mapeo pues nos permite observar el comportamiento de los puntos fijos en función de los parámetros."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "En primer lugar, estudiemos a los puntos fijos para distintas $M$ en cada gráfica en función de $R$ y $S$ para una condición inicial fija $X_{0}=10.0$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb416613e50>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.5184747648677959>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código realiza una gráfica para cada valor de M entre 1 y 80\n",
+    "x = y = linspace(2.0, 40, 40) #Establece el paso entre cada x,y y sus valores máximo y mínimo.\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0 #Condición inicial arbitraria\n",
+    "@gif for i in linspace(1, 80, 100) #Creando el .gif, con 100 imágenes.\n",
+    "    G(x,y) = (x*(x0)^2)/((((x-1.0)*(x0^2))/i + y + x0))-x0\n",
+    "\n",
+    "\n",
+    "plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"R\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas M\")\n",
+    "        \n",
+    "   end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ahora estudiamos el comportamiento de los puntos fijos con un valor distinto de $R$ en cada gráfica que varía en función de $M$ y $S$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb41d8ea250>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.30877001457821573>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código realiza una gráfica para cada valor de R entre 1 y 100.\n",
+    "x = y = linspace(2.0, 40, 40)\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0\n",
+    "@gif for i in linspace(1,100,100) #Se genera el .gif con 100 imágenes. \n",
+    "    G(x,y) = (i*(x0)^2)/((((i-1.0)*(x0^2))/x + y + x0))-x0\n",
+    "    title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas R\")\n",
+    "        \n",
+    " end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finalmente, observemos la evolución de los puntos fijos para un valor distinto de $S$ en cada gráfica que se encuentra en\n",
+    "función de $M$ y $R$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb41d3a6dd0>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.32854563172234674>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código genera una gŕafica para cada valor de S en función de M y R.\n",
+    "x = y = linspace(2.0, 80, 90)\n",
+    "zs = zeros(0,90)\n",
+    "x0= 50.0 #Se utiliza otra condición inicial.\n",
+    "@gif for i in linspace(1, 100, 100) #Se construye el .gif con 100 imágenes también.\n",
+    "    G(x,y) = (y*(x0)^2)/((((y-1.0)*(x0^2))/x + i + x0))-x0\n",
+    "    title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0,100)),yaxis=(L\"R\",(-1.0, 100)),title=\"Puntos fijos del mapeo para distintas S\")\n",
+    "        \n",
+    "end"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "celltoolbar": "Slideshow",
+  "kernelspec": {
+   "display_name": "Julia 0.5.0",
+   "language": "julia",
+   "name": "julia-0.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "0.5.0"
+  },
+  "widgets": {
+   "state": {
+    "1a72896c-621a-4f4a-ad21-0358c2e061ba": {
+     "views": [
+      {
+       "cell_index": 13
+      }
+     ]
+    },
+    "c6205deb-bbae-450c-bb19-6cb88744793d": {
+     "views": [
+      {
+       "cell_index": 10
+      }
+     ]
+    }
+   },
+   "version": "1.2.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/proys/InsectPopulation/PabloProy/population.ipynb b/proys/InsectPopulation/PabloProy/population.ipynb
new file mode 100644
index 0000000..2b14d70
--- /dev/null
+++ b/proys/InsectPopulation/PabloProy/population.ipynb
@@ -0,0 +1,1127 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Nothing to be done\n",
+      "INFO: METADATA is out-of-date — you may not have the latest version of Plots\n",
+      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.add(\"Plots\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Updating cache of StatPlots...\n",
+      "INFO: Installing AxisAlgorithms v0.1.5\n",
+      "INFO: Installing Interpolations v0.3.6\n",
+      "INFO: Installing KernelDensity v0.3.0\n",
+      "INFO: Installing PlotRecipes v0.1.0\n",
+      "INFO: Installing Ratios v0.0.4\n",
+      "INFO: Installing StatPlots v0.1.1\n",
+      "INFO: Installing WoodburyMatrices v0.2.0\n",
+      "INFO: Building Rmath\n",
+      "INFO: Building Plots\n",
+      "INFO: Cannot find deps/plotly-latest.min.js... downloading latest version.\n",
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0curl: (77) error setting certificate verify locations:\n",
+      "  CAfile: /etc/pki/tls/certs/ca-bundle.crt\n",
+      "  CApath: none\n",
+      "================================[ ERROR: Plots ]================================\n",
+      "\n",
+      "LoadError: failed process: Process(`curl -o /home/sof9409/.julia/v0.5/Plots/deps/plotly-latest.min.js -L https://cdn.plot.ly/plotly-latest.min.js`, ProcessExited(77)) [77]\n",
+      "while loading /home/sof9409/.julia/v0.5/Plots/deps/build.jl, in expression starting on line 7\n",
+      "\n",
+      "================================================================================\n",
+      "\n",
+      "================================[ BUILD ERRORS ]================================\n",
+      "\n",
+      "WARNING: Plots had build errors.\n",
+      "\n",
+      " - packages with build errors remain installed in /home/sof9409/.julia/v0.5\n",
+      " - build the package(s) and all dependencies with `Pkg.build(\"Plots\")`\n",
+      " - build a single package by running its `deps/build.jl` script\n",
+      "\n",
+      "================================================================================\n",
+      "INFO: Package database updated\n",
+      "INFO: METADATA is out-of-date — you may not have the latest version of PlotRecipes\n",
+      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.add(\"PlotRecipes\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Nothing to be done\n",
+      "INFO: METADATA is out-of-date — you may not have the latest version of PyPlot\n",
+      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.add(\"PyPlot\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Updating METADATA...\n",
+      "INFO: Updating cache of Polynomials...\n",
+      "INFO: Updating cache of PlotRecipes...\n",
+      "INFO: Updating cache of PlotUtils...\n",
+      "INFO: Updating cache of Plots...\n",
+      "INFO: Updating cache of FixedSizeArrays...\n",
+      "INFO: Updating cache of NaNMath...\n",
+      "INFO: Updating cache of ForwardDiff...\n",
+      "INFO: Updating cache of Compat...\n",
+      "INFO: Updating cache of SHA...\n",
+      "INFO: Updating cache of PDMats...\n",
+      "INFO: Updating cache of PositiveFactorizations...\n",
+      "INFO: Updating Plotly master...\n",
+      "INFO: Computing changes...\n",
+      "INFO: Cloning cache of GeometryTypes from https://github.com/JuliaGeometry/GeometryTypes.jl.git\n",
+      "INFO: Cloning cache of NetworkLayout from https://github.com/JuliaGraphs/NetworkLayout.jl.git\n",
+      "INFO: Cloning cache of PlotThemes from https://github.com/JuliaPlots/PlotThemes.jl.git\n",
+      "INFO: Upgrading Blink: v0.4.3 => v0.4.4\n",
+      "INFO: Upgrading Compat: v0.9.3 => v0.9.5\n",
+      "INFO: Upgrading Conda: v0.3.2 => v0.4.0\n",
+      "INFO: Upgrading DataArrays: v0.3.9 => v0.3.10\n",
+      "INFO: Upgrading DataFrames: v0.8.4 => v0.8.5\n",
+      "INFO: Upgrading DocStringExtensions: v0.2.1 => v0.3.0\n",
+      "INFO: Upgrading FixedSizeArrays: v0.2.4 => v0.2.5\n",
+      "INFO: Installing GeometryTypes v0.2.1\n",
+      "INFO: Upgrading Juno: v0.2.3 => v0.2.5\n",
+      "INFO: Upgrading Media: v0.2.3 => v0.2.4\n",
+      "INFO: Upgrading NaNMath: v0.2.1 => v0.2.2\n",
+      "INFO: Installing NetworkLayout v0.0.1\n",
+      "INFO: Upgrading PDMats: v0.5.0 => v0.5.1\n",
+      "INFO: Upgrading PlotRecipes: v0.1.0 => v0.2.0\n",
+      "INFO: Installing PlotThemes v0.1.0\n",
+      "INFO: Upgrading PlotUtils: v0.1.1 => v0.2.0\n",
+      "INFO: Upgrading Plots: v0.9.4 => v0.10.1\n",
+      "INFO: Upgrading Polynomials: v0.1.0 => v0.1.1\n",
+      "INFO: Upgrading PositiveFactorizations: v0.0.2 => v0.0.3\n",
+      "INFO: Upgrading SHA: v0.2.1 => v0.3.0\n",
+      "INFO: Upgrading StatPlots: v0.1.1 => v0.2.0\n",
+      "INFO: Building HttpParser\n",
+      "INFO: Attempting to Create directory /home/sof9409/.julia/v0.5/HttpParser/deps/downloads\n",
+      "INFO: Directory /home/sof9409/.julia/v0.5/HttpParser/deps/downloads already created\n",
+      "INFO: Attempting to Create directory /home/sof9409/.julia/v0.5/HttpParser/deps/downloads\n",
+      "INFO: Directory /home/sof9409/.julia/v0.5/HttpParser/deps/downloads already created\n",
+      "INFO: Downloading file https://github.com/nodejs/http-parser/archive/v2.7.1.zip\n",
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0curl: (77) error setting certificate verify locations:\n",
+      "  CAfile: /etc/pki/tls/certs/ca-bundle.crt\n",
+      "  CApath: none\n",
+      "=============================[ ERROR: HttpParser ]==============================\n",
+      "\n",
+      "LoadError: failed process: Process(`curl -f -o /home/sof9409/.julia/v0.5/HttpParser/deps/downloads/v2.7.1.zip -L https://github.com/nodejs/http-parser/archive/v2.7.1.zip`, ProcessExited(77)) [77]\n",
+      "while loading /home/sof9409/.julia/v0.5/HttpParser/deps/build.jl, in expression starting on line 71\n",
+      "\n",
+      "================================================================================\n",
+      "INFO: Building MbedTLS\n",
+      "INFO: Attempting to Create directory /home/sof9409/.julia/v0.5/MbedTLS/deps/downloads\n",
+      "INFO: Directory /home/sof9409/.julia/v0.5/MbedTLS/deps/downloads already created\n",
+      "INFO: Downloading file https://cache.julialang.org/https://tls.mbed.org/download/mbedtls-2.1.1-apache.tgz\n",
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0curl: (77) error setting certificate verify locations:\n",
+      "  CAfile: /etc/pki/tls/certs/ca-bundle.crt\n",
+      "  CApath: none\n",
+      "===============================[ ERROR: MbedTLS ]===============================\n",
+      "\n",
+      "LoadError: failed process: Process(`curl -f -o /home/sof9409/.julia/v0.5/MbedTLS/deps/downloads/mbedtls-2.1.1-apache.tgz -L https://cache.julialang.org/https://tls.mbed.org/download/mbedtls-2.1.1-apache.tgz`, ProcessExited(77)) [77]\n",
+      "while loading /home/sof9409/.julia/v0.5/MbedTLS/deps/build.jl, in expression starting on line 74\n",
+      "\n",
+      "================================================================================\n",
+      "INFO: Building Conda\n",
+      "INFO: Building Plots\n",
+      "INFO: Cannot find deps/plotly-latest.min.js... downloading latest version.\n",
+      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
+      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
+      "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0curl: (77) error setting certificate verify locations:\n",
+      "  CAfile: /etc/pki/tls/certs/ca-bundle.crt\n",
+      "  CApath: none\n",
+      "================================[ ERROR: Plots ]================================\n",
+      "\n",
+      "LoadError: failed process: Process(`curl -o /home/sof9409/.julia/v0.5/Plots/deps/plotly-latest.min.js -L https://cdn.plot.ly/plotly-latest.min.js`, ProcessExited(77)) [77]\n",
+      "while loading /home/sof9409/.julia/v0.5/Plots/deps/build.jl, in expression starting on line 7\n",
+      "\n",
+      "================================================================================\n",
+      "INFO: Building Rmath\n",
+      "\n",
+      "================================[ BUILD ERRORS ]================================\n",
+      "\n",
+      "WARNING: HttpParser, Plots and MbedTLS had build errors.\n",
+      "\n",
+      " - packages with build errors remain installed in /home/sof9409/.julia/v0.5\n",
+      " - build the package(s) and all dependencies with `Pkg.build(\"HttpParser\", \"Plots\", \"MbedTLS\")`\n",
+      " - build a single package by running its `deps/build.jl` script\n",
+      "\n",
+      "================================================================================\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.update()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Recompiling stale cache file /home/sof9409/.julia/lib/v0.5/Plots.ji for module Plots.\n",
+      "WARNING: Module Compat with uuid 9309146622058 is missing from the cache.\n",
+      "This may mean module Compat does not support precompilation but is imported by a module that does.\n",
+      "ERROR: LoadError: Declaring __precompile__(false) is not allowed in files that are being precompiled.\n",
+      " in require(::Symbol) at ./loading.jl:385\n",
+      " in include_from_node1(::String) at ./loading.jl:488\n",
+      " in macro expansion; at ./none:2 [inlined]\n",
+      " in anonymous at ./<missing>:?\n",
+      " in eval(::Module, ::Any) at ./boot.jl:234\n",
+      " in process_options(::Base.JLOptions) at ./client.jl:239\n",
+      " in _start() at ./client.jl:318\n",
+      "while loading /home/sof9409/.julia/v0.5/FixedSizeArrays/src/FixedSizeArrays.jl, in expression starting on line 4\n",
+      "ERROR: LoadError: Failed to precompile FixedSizeArrays to /home/sof9409/.julia/lib/v0.5/FixedSizeArrays.ji.\n",
+      " in compilecache(::String) at ./loading.jl:593\n",
+      " in require(::Symbol) at ./loading.jl:393\n",
+      " in include_from_node1(::String) at ./loading.jl:488\n",
+      " in macro expansion; at ./none:2 [inlined]\n",
+      " in anonymous at ./<missing>:?\n",
+      " in eval(::Module, ::Any) at ./boot.jl:234\n",
+      " in process_options(::Base.JLOptions) at ./client.jl:239\n",
+      " in _start() at ./client.jl:318\n",
+      "while loading /home/sof9409/.julia/v0.5/Plots/src/Plots.jl, in expression starting on line 5\n"
+     ]
+    },
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: Failed to precompile Plots to /home/sof9409/.julia/lib/v0.5/Plots.ji.\nwhile loading In[5], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: Failed to precompile Plots to /home/sof9409/.julia/lib/v0.5/Plots.ji.\nwhile loading In[5], in expression starting on line 1",
+      "",
+      " in compilecache(::String) at ./loading.jl:593",
+      " in require(::Symbol) at ./loading.jl:393"
+     ]
+    }
+   ],
+   "source": [
+    "using Plots, LaTeXStrings\n",
+    "\n",
+    "pyplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "f (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f(x,α,β,γ) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "iteramapeo (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function iteramapeo(f, x0, n)\n",
+    "    xx = [x0]\n",
+    "    fx = [0.0]\n",
+    "    for it = 1:n\n",
+    "        x1 = f(x0)\n",
+    "        push!(xx, x0)\n",
+    "        push!(fx, x1)\n",
+    "        x0 = x1\n",
+    "        push!(xx,x1)\n",
+    "        push!(fx,x1)\n",
+    "    end\n",
+    "    xx, fx\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#1) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α=500.0\n",
+    "β=10.0\n",
+    "γ=2.0\n",
+    "func = x -> f(x,α,β,γ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "xfin,ffin = iteramapeo(func,10.0,14);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: @L_str not defined\nwhile loading In[10], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: @L_str not defined\nwhile loading In[10], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "plot(-10:1/32:10, func, xaxis=(L\"x\", (-1.0, 6.0)), yaxis=(L\"F_\\alpha(x)\",(-1.0,3.0)))\n",
+    "plot!(-10:1/32:10, identity)\n",
+    "plot!(xfin, ffin, marker=(:dot, 3, 0.4))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#3) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α=500.0\n",
+    "β=10.0\n",
+    "γ=2.0\n",
+    "func = x -> f(x,α,β,γ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "xfin,ffin = iteramapeo(func,200.0,10);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: @L_str not defined\nwhile loading In[13], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: @L_str not defined\nwhile loading In[13], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "plot(-10:1/32:10, func, xaxis=(L\"x\", (-1.0, 6.0)), yaxis=(L\"F_\\alpha(x)\",(-1.0,3.0)))\n",
+    "plot!(-10:1/32:10, identity)\n",
+    "plot!(xfin, ffin, marker=(:dot, 3, 0.4))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div id=\"interact-js-shim\">\n",
+       "    <script charset=\"utf-8\">\n",
+       "(function (IPython, $, _, MathJax) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    var OutputArea = IPython.version >= \"4.0.0\" ? require(\"notebook/js/outputarea\").OutputArea : IPython.OutputArea;\n",
+       "\n",
+       "    var redrawValue = function (container, type, val) {\n",
+       "\tvar selector = $(\"<div/>\");\n",
+       "\tvar oa = new OutputArea(_.extend(selector, {\n",
+       "\t    selector: selector,\n",
+       "\t    prompt_area: true,\n",
+       "\t    events: IPython.events,\n",
+       "\t    keyboard_manager: IPython.keyboard_manager\n",
+       "\t})); // Hack to work with IPython 2.1.0\n",
+       "\n",
+       "\tswitch (type) {\n",
+       "\tcase \"image/png\":\n",
+       "            var _src = 'data:' + type + ';base64,' + val;\n",
+       "\t    $(container).find(\"img\").attr('src', _src);\n",
+       "\t    break;\n",
+       "\tdefault:\n",
+       "\t    var toinsert = OutputArea.append_map[type].apply(\n",
+       "\t\toa, [val, {}, selector]\n",
+       "\t    );\n",
+       "\t    $(container).empty().append(toinsert.contents());\n",
+       "\t    selector.remove();\n",
+       "\t}\n",
+       "\tif (type === \"text/latex\" && MathJax) {\n",
+       "\t    MathJax.Hub.Queue([\"Typeset\", MathJax.Hub, toinsert.get(0)]);\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        //_.extend(comm_manager.targets, require(\"widgets/js/widget\"))\n",
+       "\t    comm_manager.register_target(\"Signal\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                //Widgets.log(\"message received\", msg);\n",
+       "                var val = msg.content.data.value;\n",
+       "                $(\".signal-\" + comm.comm_id).each(function() {\n",
+       "                var type = $(this).data(\"type\");\n",
+       "                if (val[type]) {\n",
+       "                    redrawValue(this, type, val[type], type);\n",
+       "                }\n",
+       "                });\n",
+       "                delete val;\n",
+       "                delete msg.content.data.value;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "\t    // coordingate with Comm and redraw Signals\n",
+       "\t    // XXX: Test using Reactive here to improve performance\n",
+       "\t    $([IPython.events]).on(\n",
+       "\t\t'output_appended.OutputArea', function (event, type, value, md, toinsert) {\n",
+       "\t\t    if (md && md.reactive) {\n",
+       "                // console.log(md.comm_id);\n",
+       "                toinsert.addClass(\"signal-\" + md.comm_id);\n",
+       "                toinsert.data(\"type\", type);\n",
+       "                // Signal back indicating the mimetype required\n",
+       "                var comm_manager = IPython.notebook.kernel.comm_manager;\n",
+       "                var comm = comm_manager.comms[md.comm_id];\n",
+       "                comm.then(function (c) {\n",
+       "                    c.send({action: \"subscribe_mime\",\n",
+       "                       mime: type});\n",
+       "                    toinsert.bind(\"destroyed\", function() {\n",
+       "                        c.send({action: \"unsubscribe_mime\",\n",
+       "                               mime: type});\n",
+       "                    });\n",
+       "                })\n",
+       "\t\t    }\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery, _, MathJax);\n",
+       "</script>\n",
+       "    <script>\n",
+       "        window.interactLoadedFlag = true\n",
+       "       $(\"#interact-js-shim\").bind(\"destroyed\", function () {\n",
+       "           if (window.interactLoadedFlag) {\n",
+       "               console.warn(\"JavaScript required by Interact will be removed if you remove this cell or run using Interact more than once.\")\n",
+       "           }\n",
+       "       })\n",
+       "       $([IPython.events]).on(\"kernel_starting.Kernel kernel_restarting.Kernel\", function () { window.interactLoadedFlag = false })\n",
+       "   </script>\n",
+       "</div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "using Interact "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "xfin,ffin = iteramapeo(func,200.0,10);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: @L_str not defined\nwhile loading In[16], in expression starting on line 3",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: @L_str not defined\nwhile loading In[16], in expression starting on line 3",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 20.0\n",
+    "@manipulate for γ in 0:1.0:200\n",
+    "    pobla(x)=f(x,α,β,γ)\n",
+    "    xfin,ffin = iteramapeo(pobla,10.0,16);\n",
+    "    plot(-10:1/32:100, pobla, xaxis=(L\"x\", (-10.0, 100.0)), yaxis=(L\"F_\\alpha(x)\",(-10.0,10.0)))\n",
+    "plot!(-10:1/32:50, identity)\n",
+    "plot!(xfin, ffin, marker=(:dot, 3, 0.4))\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 20.0\n",
+    "g(x)=(α*(x)^2)/((((α-1.0)*(x^2))/β + x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: @L_str not defined\nwhile loading In[18], in expression starting on line 2",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: @L_str not defined\nwhile loading In[18], in expression starting on line 2",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "@manipulate for i in 1:1.0:100\n",
+    "    funcion(i)=g(i)\n",
+    "    plot(-10:1/32:100, funcion, xaxis=(L\"x\", (-100.0, 100.0)), yaxis=(L\"F_\\alpha(x)\",(-100.0,100.0)))\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "Se resolvió la ecuación $N(x)-x=0$ para encontrar los puntos fijos del mapeo en términos de los parámetros R,S y M, obteniendo:\n",
+    "\n",
+    "$X_{0}= 0$\n",
+    "\n",
+    "\n",
+    "y    \n",
+    "\n",
+    "\n",
+    "\n",
+    "$X_{12}= \\frac{\\pm M(1-R)+\\sqrt{R-1}\\sqrt{M^{2}(1-R)-4MS}}{2(1-R)}$\n",
+    "\n",
+    "\n",
+    "\n",
+    "Por lo que, para encontrar poblaciones estáticas distintas de cero, tenemos que se deben cumplir las siguientes condiciones:\n",
+    "\n",
+    "$R> 1 $ ^ $M > \\frac{4S}{R-1}$\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Nothing to be done\n"
+     ]
+    }
+   ],
+   "source": [
+    "Pkg.add(\"Roots\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Recompiling stale cache file /home/sof9409/.julia/lib/v0.5/Polynomials.ji for module Polynomials.\n",
+      "WARNING: Module Compat with uuid 9309146622058 is missing from the cache.\n",
+      "This may mean module Compat does not support precompilation but is imported by a module that does.\n",
+      "ERROR: LoadError: Declaring __precompile__(false) is not allowed in files that are being precompiled.\n",
+      " in require(::Symbol) at ./loading.jl:385\n",
+      " in include_from_node1(::String) at ./loading.jl:488\n",
+      " in macro expansion; at ./none:2 [inlined]\n",
+      " in anonymous at ./<missing>:?\n",
+      " in eval(::Module, ::Any) at ./boot.jl:234\n",
+      " in process_options(::Base.JLOptions) at ./client.jl:239\n",
+      " in _start() at ./client.jl:318\n",
+      "while loading /home/sof9409/.julia/v0.5/Polynomials/src/Polynomials.jl, in expression starting on line 8\n"
+     ]
+    },
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: Failed to precompile Polynomials to /home/sof9409/.julia/lib/v0.5/Polynomials.ji.\nwhile loading In[20], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: Failed to precompile Polynomials to /home/sof9409/.julia/lib/v0.5/Polynomials.ji.\nwhile loading In[20], in expression starting on line 1",
+      "",
+      " in compilecache(::String) at ./loading.jl:593",
+      " in require(::Symbol) at ./loading.jl:393",
+      " in _include_from_serialized(::String) at ./loading.jl:150",
+      " in _require_from_serialized(::Int64, ::Symbol, ::String, ::Bool) at ./loading.jl:187",
+      " in _require_search_from_serialized(::Int64, ::Symbol, ::String, ::Bool) at ./loading.jl:217",
+      " in require(::Symbol) at ./loading.jl:371"
+     ]
+    }
+   ],
+   "source": [
+    "using Roots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "puntofijo (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function puntofijo(F::Function, range)\n",
+    "    pf= fzeros(x -> (F(x) - x) , range)\n",
+    "    return pf\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "F (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "\n",
+    "F(x) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: fzeros not defined\nwhile loading In[23], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: fzeros not defined\nwhile loading In[23], in expression starting on line 1",
+      "",
+      " in puntofijo(::#F, ::Array{Float64,1}) at ./In[21]:2"
+     ]
+    }
+   ],
+   "source": [
+    "pf=puntofijo(F,[0,20.0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Method definition g(Any) in module Main at In[17]:3 overwritten at In[24]:1.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g(x)= (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x)) -x "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#20) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "func=x -> g(x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A continuación se muestra una gráfica de los puntos fijos del mapeo en términos de los parámetros\n",
+    "$R=10$,$M=25$ y $S=50$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: plot not defined\nwhile loading In[26], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: plot not defined\nwhile loading In[26], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "plot(-10:1/32:30, func,xticks=-10:0.5:100,yticks=-10:0.5:50)\n",
+    "xlabel!(L\"x\")\n",
+    "ylabel!(L\"N(x)-x\")\n",
+    "title!(\"Puntos fijos de N(x)\")\n",
+    "plot!([8.3,8.3], [1, -1, 0])\n",
+    "plot!([0,0], [1, -1,0])\n",
+    "plot!([16.66,  16.66], [1, -1, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A continuación se muestran graficas que relacionan los parámetros y el comportamiento de los puntos fijos dependiendo de éstos."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La función a estudiar es:\n",
+    "\n",
+    "$N(X)-X= \\frac{MRX^{2}}{(R-1)X^{2}+M(X+S)} -X $\n",
+    "\n",
+    " Nos interesa encontrar éste mapeo pues nos permite observar el comportamiento de los puntos fijos en función de los parámetros."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "En primer lugar, estudiemos a los puntos fijos para distintas $M$ en cada gráfica en función de $R$ y $S$ para una condición inicial fija $X_{0}=10.0$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: pyplot not defined\nwhile loading In[27], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: pyplot not defined\nwhile loading In[27], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing)\n",
+    "x = y = linspace(2.0, 40, 40)\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0\n",
+    "@gif for i in linspace(1, 80, 5)\n",
+    "    G(x,y) = (x*(x0)^2)/((((x-1.0)*(x0^2))/i + y + x0))-x0\n",
+    "\n",
+    "    # create a plot with 3 subplots and a custom layout\n",
+    "   # l = @layout [a{0.9w}]\n",
+    "\n",
+    "    plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"R\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas M\")\n",
+    "        \n",
+    "   end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ahora estudiamos el comportamiento de los puntos fijos con un valor distinto de $R$ en cada gráfica que varía en función de $M$ y $S$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: pyplot not defined\nwhile loading In[28], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: pyplot not defined\nwhile loading In[28], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing)\n",
+    "x = y = linspace(2.0, 40, 40)\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0\n",
+    "@gif for i in linspace(1,100,5)\n",
+    "    G(x,y) = (i*(x0)^2)/((((i-1.0)*(x0^2))/x + y + x0))-x0\n",
+    "\n",
+    "    # create a plot with 3 subplots and a custom layout\n",
+    "    title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas R\")\n",
+    "        \n",
+    " end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finalmente, observemos la evolución de los puntos fijos para un valor distinto de $S$ en cada gráfica que se encuentra en\n",
+    "función de $M$ y $R$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: pyplot not defined\nwhile loading In[29], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: pyplot not defined\nwhile loading In[29], in expression starting on line 1",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing)\n",
+    "x = y = linspace(2.0, 60, 60)\n",
+    "zs = zeros(0,60)\n",
+    "x0= 10.0\n",
+    "@gif for i in linspace(1, 80, 5)\n",
+    "    G(x,y) = (y*(x0)^2)/((((y-1.0)*(x0^2))/x + i + x0))-x0\n",
+    "\n",
+    "    # create a plot with 3 subplots and a custom layout\n",
+    "       title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0, 50)),yaxis=(L\"R\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas S\")\n",
+    "        \n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Julia 0.5.0",
+   "language": "julia",
+   "name": "julia-0.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "0.5.0"
+  },
+  "widgets": {
+   "state": {
+    "5106949f-6478-4b30-8cc4-b23f3bf1b7bd": {
+     "views": [
+      {
+       "cell_index": 15
+      }
+     ]
+    },
+    "905096df-477a-4938-b280-991bbb9ae467": {
+     "views": [
+      {
+       "cell_index": 17
+      }
+     ]
+    },
+    "9ee57ccf-20b1-41c6-8a38-36d91604bc0f": {
+     "views": [
+      {
+       "cell_index": 15
+      }
+     ]
+    }
+   },
+   "version": "1.2.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/proys/InsectPopulation/ProyDaniel/AutomDiff_V2.jl b/proys/InsectPopulation/ProyDaniel/AutomDiff_V2.jl
new file mode 100755
index 0000000..ce810a1
--- /dev/null
+++ b/proys/InsectPopulation/ProyDaniel/AutomDiff_V2.jl
@@ -0,0 +1,95 @@
+#Modulo de Diferenciacion Automatica
+#El siguiente modulo define la estructura de los objetos "duales" asi como las operaciones entre ellos.
+#Autores: Daniel (https://github.com/danmarurr) y Fernanda (https://github.com/FernandaPerez)
+
+
+__precompile__(true)
+
+module AD
+    import Base: +, -, *, /, ^, ==
+    
+    export Dual, xdual
+
+
+
+    type Dual{T<:Real}
+    # código: 
+    fun :: T
+    der :: T
+    end
+    
+    Dual(a, b) = Dual(promote(a, b) ...)
+    # Aqui se define un método que garantiza que el dual de un número cumple lo requerido
+    Dual(a) = Dual(a, zero(0))
+    # Aqui se define la función `xdual`, que se usará para identificar la variable independiente
+
+    function xdual(x0)
+        Dual(x0, one(x0))
+    end
+
+    # Definiendo operaciones cuando los argumentos son Duales
+    +(a::Dual, b::Dual) = Dual(a.fun + b.fun, a.der + b.der)
+    -(a::Dual, b::Dual) = Dual(a.fun - b.fun, a.der - b.der)
+    *(a::Dual, b::Dual) = Dual(a.fun * b.fun, a.der*b.fun + b.der*a.fun)
+    /(a::Dual, b::Dual) = Dual(a.fun / b.fun, (a.der - b.der*(a.fun/b.fun))/b.fun)
+    ^{T<:Int}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Float64}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Rational}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ^{T<:Irrational}(a::Dual, α::T) = Dual(a.fun^α, α*a.fun^(α - 1)*a.der)
+    ==(a::Dual, b::Dual) = (a.fun == b.fun && a.der == b.der)
+
+
+    # Definiendo operaciones cuando el argumento de la derecha es un número
+    *{T<:Real}(β :: T, a :: Dual) = Dual(a.fun*β, a.der*β    )
+    +{T<:Real}(a::Dual, γ::T)= +(a::Dual, Dual(γ))
+    -{T<:Real}(a::Dual, γ::T)= -(a::Dual, Dual(γ))
+    *{T<:Real}(a::Dual, γ::T)= *(a::Dual, Dual(γ))
+    /{T<:Real}(a::Dual, γ::T)= /(a::Dual, Dual(γ))
+
+    # Definiendo operaciones cuando el argumento de la izquierda es un número
+
+    +{T<:Real}(γ::T, a::Dual)= +(Dual(γ), a)
+    -{T<:Real}(γ::T, a::Dual)= -(Dual(γ), a)
+    /{T<:Real}(γ::T, a::Dual)= /(Dual(γ), a)
+
+
+#Importamos todas las funciones para las cuales queremos definir su operacion 
+import Base: ^, exp, sqrt, cbrt, sin, cos, tan, cot, sec, csc, sinh, cosh, tanh, coth, sech, csch,
+asin,   acos,   atan,   acot,   asec,   acsc,
+asinh,  acosh,  atanh,  acoth,  asech,  acsch
+
+#Vector con todos los símbolos asociados a las funciones trigométricas, exponenciales, etc. y sus respectivas
+#derivadas
+Vec_Func = [(:sin, :cos), (:cos, :(x -> -sin(x))), (:tan, :(x -> (sec(x))^2)), (:cot, :(x -> -(csc(x))^2)), 
+    (:sec, :(x -> sec(x)*tan(x))), (:csc, :(x -> -csc(x)*cot(x))), (:sinh, :cosh), (:cosh, :sinh), 
+    (:tanh, :(x -> (sech(x))^2)), (:coth, :(x -> -(csch(x))^2)), (:asin, :(x -> 1/sqrt(1-x^2))), 
+    (:acos, :(x -> -1/sqrt(1-x^2))), (:atan, :(x -> 1/(1+x^2))), (:acot, :(x -> -1/(1+x^2))),
+    (:asec, :(x -> 1/(sqrt(x^2-1)*x))), (:acsc, :(x -> -1/(sqrt(x^2-1)*x))), (:asinh, :(x -> 1/sqrt(1+x^2))),
+    (:acosh, :(x -> 1/sqrt(x^2-1))), (:atanh, :(x -> 1/(1-x^2))), (:acoth, :(x -> 1/(1-x^2))),
+    (:asech, :(x -> 1/(x*sqrt(1-x^2)))), (:acsch, :(x -> -1/(x*sqrt(1+x^2)))), (:sqrt, :(x -> 1/(2*sqrt(x)))), (:exp, :exp),
+    (:cbrt, :(x -> 1/(3*x^(2/3))))]
+
+#Casos especiales: los logarítmos y a^x
+log(a::Dual) = Dual(log(a.fun), a.der/a.fun)
+log{T<:Real}(b::T, a::Dual) = Dual(log(b,a.fun), a.der/(log(b)*a.fun))
+^{T<:Real}(b::T, a::Dual) = Dual(b^a.fun, a.der*log(b)*b^a.fun)
+
+#Loop para crear los nuevos métodos a partir de los símbolos
+for r in 1:length(Vec_Func)
+    fn = Vec_Func[r][1] #El primer símbolo está asociado a la función
+    der = Vec_Func[r][2] #El segundo símbolo está asociado a la derivada de la función
+    ex = quote #Creamos una nueva expresión
+        function ($fn)(a::Dual) #Definimos fn(a::Dual)
+            fun = ($fn)(a.fun)
+            derv = ($der)(a.fun)
+            return Dual(fun, derv*a.der) #Aplicamos la regla de la cadena
+        end
+    end
+    @eval $ex #Evaluamos la expresión para crear el método
+end
+
+
+
+
+end
+
diff --git a/proys/InsectPopulation/ProyDaniel/Finding Sc.ipynb b/proys/InsectPopulation/ProyDaniel/Finding Sc.ipynb
new file mode 100644
index 0000000..a57e1fe
--- /dev/null
+++ b/proys/InsectPopulation/ProyDaniel/Finding Sc.ipynb	
@@ -0,0 +1,699 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:05:16.448219",
+     "start_time": "2016-12-05T19:05:16.375Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: replacing module AD\n",
+      "WARNING: ignoring conflicting import of AD.Dual into Main\n",
+      "WARNING: ignoring conflicting import of AD.xdual into Main\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PyPlotBackend()"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Paquetería necesaria\n",
+    "using Plots, Interact, LaTeXStrings\n",
+    "include(\"AutomDiff_V2.jl\")\n",
+    "import AD: Dual, xdual\n",
+    "pyplot(legend = :false, size = (500, 500))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:01:36.536930",
+     "start_time": "2016-12-05T19:01:36.383Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapins (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#El mapeo que estudiaremos\n",
+    "mapins(x, M, S, R) = (R*x^2)/((R - 1)*(x^2)/M + S + x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:02:01.631819",
+     "start_time": "2016-12-05T19:02:01.402Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapeo_liap_all"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Código para bifurcaciones y Lyapunov que usamos a lo largo del curso\n",
+    "\"\"\"\n",
+    "    ciclosestables!(xx, f, nit, nout, cc)\n",
+    "\n",
+    "Esta función itera el mapeo `f`, de una variable, `nit+nout` veces, \n",
+    "usando como condición inicial `x0=0`; los últimos `nout` iterados \n",
+    "actualizan al vector `xx` que tiene longitud `nout`. `cc` es el valor\n",
+    "del parámetro del mapeo `f`. El mapeo `f` debe ser definido de \n",
+    "tal manera que `f(x0,cc)` tenga sentido. La idea es los últimos \n",
+    "`nout` iterados reflejen los ciclos estables del mapeo `f`. \n",
+    "\"\"\"\n",
+    "function ciclosestables!(xx, f, nit, nout, cc)\n",
+    "    @assert nit > 0 && nout > 0\n",
+    "    \n",
+    "    # Primeros nit iterados\n",
+    "    x0 = 1000.0\n",
+    "    for it = 1:nit\n",
+    "        x0 = f(x0, cc)\n",
+    "    end\n",
+    "    \n",
+    "    # Se guardan los siguientes nout iterados\n",
+    "    for it = 1:nout\n",
+    "        x0 = f(x0, cc)\n",
+    "        @inbounds xx[it] = x0\n",
+    "    end\n",
+    "    \n",
+    "    nothing\n",
+    "end\n",
+    "\"\"\"\n",
+    "    diagbifurc(f, nit, nout, crange)\n",
+    "\n",
+    "Itera el mapeo `f` `nit+nout` veces y regresa una matriz\n",
+    "cuya columna `i` tiene los últimos `nout` iterados del mapeo\n",
+    "para el valor del parámetro del mapeo `crange[i]`.\n",
+    "\n",
+    "La función `f` debe ser definida de tal manera que `f(x0, c)` \n",
+    "tenga sentido.\n",
+    "\"\"\"\n",
+    "function diagbifurc(f, nit, nout, crange)\n",
+    "    xx = Vector{Float64}(nout)\n",
+    "    ff = Array{Float64,2}(nout, length(crange))\n",
+    "    \n",
+    "    for ic in eachindex(crange)\n",
+    "        c = crange[ic]\n",
+    "        ciclosestables!(xx, f, nit, nout, c)\n",
+    "        ff[:,ic] = xx\n",
+    "    end\n",
+    "    \n",
+    "    return ff\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    Lyapunov(y, F)\n",
+    "\n",
+    "Dado un punto un arreglo que contenga todas las iteraciones bajo $F$ de $x_0$, calcula \n",
+    "$\\frac{1}{n} \\sum_{i=1}^n \\log\\Big| \\, f'(x_i)\\, \\Big|.$\n",
+    "\"\"\"\n",
+    "function Lyapunov(y, F::Function)\n",
+    "    n = length(y)\n",
+    "    l = 0\n",
+    "   \n",
+    "    for i in 1:n\n",
+    "        x = abs((F(xdual(y[i]))).der)\n",
+    "        l = l + log(x)\n",
+    "       \n",
+    "    end\n",
+    "    l/n\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    iterado(F,x0,n)\n",
+    "\n",
+    "Dado un punto $x_0$, esta funció guarda a todas la iteraciones bajo $F$ en un arreglo.\n",
+    "\"\"\"\n",
+    "function iterado(F::Function,x0::Float64,n::Int)\n",
+    "    y = Float64[x0] ##El primer elemento es x_0\n",
+    "    x = x0\n",
+    "    for i in 1:n\n",
+    "        x=F(x) #El valor de x cambia con cada iteración\n",
+    "        push!(y,x) #Este nuevo valor se guarda en el arreglo\n",
+    "    end\n",
+    "    y\n",
+    "end\n",
+    "\n",
+    "\n",
+    "\n",
+    "doc\"\"\"\n",
+    "mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "\n",
+    "Calcula el exponente de Lyapunov para un mapeo paramétrico $Q_c = Q_c(x, c)$ en un rango de parámetros `crange`, un\n",
+    "valor inicial `x0` y `n` iteraciones.\n",
+    "\"\"\"\n",
+    "function mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100_000)\n",
+    "    mapeo = Float64[]\n",
+    "  \n",
+    "    for i in crange\n",
+    "        Qci(x) = Qc(x,i) \n",
+    "        y = iterado(Qci,x0,n)\n",
+    "        l = Lyapunov(y, Qci)\n",
+    "        if abs(l)<Inf #En algunos puntos labda diverge, por lo que si tiende a infinito, se la asigna el valor-2.5\n",
+    "            push!(mapeo,l)      \n",
+    "        else\n",
+    "            push!(mapeo,-2.5)       \n",
+    "        end\n",
+    "      \n",
+    "    end\n",
+    "    mapeo\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Primero, vamos a revisar el comportamiento del punto de bifurcación $S_c$ bifurcación del mapeo con respecto a $M$ y $R$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:05:37.468051",
+     "start_time": "2016-12-05T19:05:29.663Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(5.0, nactions=0),\"M\",5.0,0.1:0.1:10.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(5.5, nactions=0),\"R\",5.5,1.1:0.1:10.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {
+      "comm_id": "2a77854a-ac72-4f78-bfb1-098e709b222d",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@manipulate for M in 0.1:0.1:10, R in 1.1:0.1:10\n",
+    "    m1(x, s) = mapins(x, M, s, R)\n",
+    "    srange = 0:200.0\n",
+    "    map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "    ff = diagbifurc(m1, 300, 10, srange); \n",
+    "    cc = ones(size(ff)[1])*srange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "    ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "    cc = reshape(cc, size(ff));\n",
+    "    scatter(cc, ff, markersize= 0.5)\n",
+    "    ylims!(0, 10)\n",
+    "    title!(\"Diagrama de bifurcación para mapeo de poblaciones\")\n",
+    "    xlabel!(L\"S\")\n",
+    "    ylabel!(L\"x_n\")\n",
+    "    #for l in eachindex(ff)\n",
+    "    #    if ff[l] == 0\n",
+    "    #        @show cc[l]\n",
+    "    #    end\n",
+    "    #end\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ahora revisaremos el tiempo de cálculo usando iteraciones y exponentes de Lypunov y así decidir sobre el más eficiente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:19:12.677803",
+     "start_time": "2016-12-05T19:19:11.643Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "elapsed time: 0.86598408 seconds\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.86598408"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tic()\n",
+    "M, R = 200, 200\n",
+    "            m1(x, s) = mapins(x, M, s, R)\n",
+    "            srange = 0:9990.0\n",
+    "            #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "            ff = diagbifurc(m1, 300, 50, srange); \n",
+    "            cc = ones(size(ff)[1])*srange';\n",
+    "cs = 0\n",
+    "            # Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "            ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "            cc = reshape(cc, size(ff));\n",
+    "            for l in eachindex(ff)\n",
+    "                if ff[l] == 0\n",
+    "        cs = cc[l]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "cs\n",
+    "toc()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:24:41.424604",
+     "start_time": "2016-12-05T19:23:56.834Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "elapsed time: 44.580758861 seconds\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Method definition m1(Any, Any) in module Main at In[16]:3 overwritten at In[24]:3.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "44.580758861"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tic()\n",
+    "M, R = 200, 200\n",
+    "            m1(x, s) = mapins(x, M, s, R)\n",
+    "            srange = 0:1000.0\n",
+    "            map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "            #ff = diagbifurc(m1, 300, 50, srange); \n",
+    "            #cc = ones(size(ff)[1])*srange';\n",
+    "            cs = 0\n",
+    "            # Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "            #ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "            #cc = reshape(cc, size(ff));\n",
+    "            for l in eachindex(srange)\n",
+    "                if map1[l] == 0\n",
+    "                    cs = cc[l]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "cs\n",
+    "toc()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Vemos que el método de Lyapunov es mucho más lento, por lo que usaremos el primero, es decir, iterar muchas veces y buscar el primer valor de $S$ para el cual $x_n = 0$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-03T12:37:42.728256",
+     "start_time": "2016-12-03T18:37:42.714Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.1:0.1:200.0"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "M1 = 1:200\n",
+    "R1 = 1.1:0.1:200"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:12:44.375097",
+     "start_time": "2016-12-05T19:12:44.322Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Method definition iteram(Base.Range, Base.Range) in module Main at In[9]:8 overwritten at In[11]:11.\n",
+      "WARNING: replacing docs for 'iteram :: Tuple{Range,Range}' in module 'Main'.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "iteram"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "doc\"\"\"\n",
+    "`iteram` \n",
+    "\n",
+    "Calcula el valor de $S_c$ para el cual las iteraciones del mapeo \n",
+    "$x_{n + 1} = \\frac{R*x^2}{(R - 1)*(x^2)/M + S + x}$ tienden a cero. \n",
+    "\n",
+    "Esto se realiza para los rangos\n",
+    "$M1 = m_{min}:m_{step}:m_{max}$ y $R1 = r_{min}:r_{step}:r_{max}$. Es necesario que $r_{min} > 1$ y $r_{min} > 0$\n",
+    "\"\"\"\n",
+    "function iteram(M1::Range, R1::Range)\n",
+    "    P, Q = length(R1), length(M1)\n",
+    "    Mat1 = zeros(P, Q) \n",
+    "    K = Int(P*Q)\n",
+    "    n = 1\n",
+    "    #@show (P, Q)\n",
+    "    for j in 1:Q\n",
+    "        for i in 1:P\n",
+    "            if mod(100n/K, 10) == 0\n",
+    "                println(100n/K, \"%\")\n",
+    "            end\n",
+    "            #@show i, j\n",
+    "            M, R = M1[j], R1[i]\n",
+    "            m1(x, s) = mapins(x, M, s, R)\n",
+    "            srange = 0:2500.0\n",
+    "            #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "            ff = diagbifurc(m1, 300, 50, srange); \n",
+    "            cc = ones(size(ff)[1])*srange';\n",
+    "            \n",
+    "            # Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "            ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "            cc = reshape(cc, size(ff));\n",
+    "            for l in eachindex(ff)\n",
+    "                if ff[l] == 0\n",
+    "                    Mat1[i, j] = cc[l]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "            n += 1\n",
+    "        end\n",
+    "    end\n",
+    "\n",
+    "    mm = ones(size(Mat1)[1])*M1'\n",
+    "    rr = R1*ones(size(Mat1)[2])'\n",
+    "    A1 = reshape(Mat1, size(Mat1)[1]*size(Mat1)[2])\n",
+    "    mm1 = reshape(mm, size(A1)[1])\n",
+    "    rr1 = reshape(rr, size(A1)[1])\n",
+    "    return mm1, rr1, A1\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "En la siguiente celda se calcularán las $S_c$'s y se escribirán los datos en archivos `.csv`, pues los calculos son tardados"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-03T19:31:23.972848",
+     "start_time": "2016-12-03T18:37:54.166Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10.0%\n",
+      "20.0%\n",
+      "30.0%\n",
+      "40.0%\n",
+      "50.0%\n",
+      "60.0%\n",
+      "70.0%\n",
+      "80.0%\n",
+      "90.0%\n",
+      "100.0%\n"
+     ]
+    }
+   ],
+   "source": [
+    "mm1, rr1, A1 = iteram(M1, R1);\n",
+    "writecsv(\"mms1.csv\", mm1)\n",
+    "writecsv(\"rrs1.csv\", rr1)\n",
+    "writecsv(\"ccs1.csv\", A1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:26:44.762158",
+     "start_time": "2016-12-05T19:26:44.735Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "A1 = readcsv(\"../DatosPlano/ccs1.csv\")[:,1]\n",
+    "rr1 = readcsv(\"../DatosPlano/rrs1.csv\")[:,1];\n",
+    "mm1 = readcsv(\"../DatosPlano/mms1.csv\")[:,1];"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Primero veamos algunas proyecciones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:17:34.507645",
+     "start_time": "2016-12-05T19:17:34.102Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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\" />"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(rr1, A1)\n",
+    "title!(L\"$R$ vs $S_c$\")\n",
+    "xlabel!(L\"R\")\n",
+    "ylabel!(L\"S_c\")\n",
+    "#xlims!(80,83)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T13:26:48.498543",
+     "start_time": "2016-12-05T19:26:47.963Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(mm1, rr1, A1)\n",
+    "xlabel!(\"M\")\n",
+    "ylabel!(\"R\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dado a los tiempo de cálculo, se correrá el código en varias computadoras, el resutado final se mostrará en el trabajo final."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 0.5.0",
+   "language": "julia",
+   "name": "julia-0.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "0.5.0"
+  },
+  "latex_envs": {
+   "bibliofile": "biblio.bib",
+   "cite_by": "apalike",
+   "current_citInitial": 1,
+   "eqLabelWithNumbers": true,
+   "eqNumInitial": 0
+  },
+  "widgets": {
+   "state": {
+    "603df24a-55be-4de5-9dc3-6c3ba5bb6109": {
+     "views": [
+      {
+       "cell_index": 4
+      }
+     ]
+    },
+    "c97ef275-6cc8-4a79-8b7d-16118417efb9": {
+     "views": [
+      {
+       "cell_index": 4
+      }
+     ]
+    },
+    "fa235be2-b496-4991-bdbf-a7f81a5e6a15": {
+     "views": [
+      {
+       "cell_index": 4
+      }
+     ]
+    },
+    "ff137af8-77d1-40c6-bd59-184abfff0375": {
+     "views": [
+      {
+       "cell_index": 4
+      }
+     ]
+    }
+   },
+   "version": "1.2.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/proys/InsectPopulation/ProyDaniel/ProyDaniel.ipynb b/proys/InsectPopulation/ProyDaniel/ProyDaniel.ipynb
new file mode 100644
index 0000000..7a3c8dd
--- /dev/null
+++ b/proys/InsectPopulation/ProyDaniel/ProyDaniel.ipynb
@@ -0,0 +1,907 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:23.090617",
+     "start_time": "2016-12-05T05:37:15.429Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div id=\"interact-js-shim\">\n",
+       "    <script charset=\"utf-8\">\n",
+       "(function (IPython, $, _, MathJax) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    var OutputArea = IPython.version >= \"4.0.0\" ? require(\"notebook/js/outputarea\").OutputArea : IPython.OutputArea;\n",
+       "\n",
+       "    var redrawValue = function (container, type, val) {\n",
+       "\tvar selector = $(\"<div/>\");\n",
+       "\tvar oa = new OutputArea(_.extend(selector, {\n",
+       "\t    selector: selector,\n",
+       "\t    prompt_area: true,\n",
+       "\t    events: IPython.events,\n",
+       "\t    keyboard_manager: IPython.keyboard_manager\n",
+       "\t})); // Hack to work with IPython 2.1.0\n",
+       "\n",
+       "\tswitch (type) {\n",
+       "\tcase \"image/png\":\n",
+       "            var _src = 'data:' + type + ';base64,' + val;\n",
+       "\t    $(container).find(\"img\").attr('src', _src);\n",
+       "\t    break;\n",
+       "\tdefault:\n",
+       "\t    var toinsert = OutputArea.append_map[type].apply(\n",
+       "\t\toa, [val, {}, selector]\n",
+       "\t    );\n",
+       "\t    $(container).empty().append(toinsert.contents());\n",
+       "\t    selector.remove();\n",
+       "\t}\n",
+       "\tif (type === \"text/latex\" && MathJax) {\n",
+       "\t    MathJax.Hub.Queue([\"Typeset\", MathJax.Hub, toinsert.get(0)]);\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        //_.extend(comm_manager.targets, require(\"widgets/js/widget\"))\n",
+       "\t    comm_manager.register_target(\"Signal\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                //Widgets.log(\"message received\", msg);\n",
+       "                var val = msg.content.data.value;\n",
+       "                $(\".signal-\" + comm.comm_id).each(function() {\n",
+       "                var type = $(this).data(\"type\");\n",
+       "                if (val[type]) {\n",
+       "                    redrawValue(this, type, val[type], type);\n",
+       "                }\n",
+       "                });\n",
+       "                delete val;\n",
+       "                delete msg.content.data.value;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "\t    // coordingate with Comm and redraw Signals\n",
+       "\t    // XXX: Test using Reactive here to improve performance\n",
+       "\t    $([IPython.events]).on(\n",
+       "\t\t'output_appended.OutputArea', function (event, type, value, md, toinsert) {\n",
+       "\t\t    if (md && md.reactive) {\n",
+       "                // console.log(md.comm_id);\n",
+       "                toinsert.addClass(\"signal-\" + md.comm_id);\n",
+       "                toinsert.data(\"type\", type);\n",
+       "                // Signal back indicating the mimetype required\n",
+       "                var comm_manager = IPython.notebook.kernel.comm_manager;\n",
+       "                var comm = comm_manager.comms[md.comm_id];\n",
+       "                comm.then(function (c) {\n",
+       "                    c.send({action: \"subscribe_mime\",\n",
+       "                       mime: type});\n",
+       "                    toinsert.bind(\"destroyed\", function() {\n",
+       "                        c.send({action: \"unsubscribe_mime\",\n",
+       "                               mime: type});\n",
+       "                    });\n",
+       "                })\n",
+       "\t\t    }\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery, _, MathJax);\n",
+       "</script>\n",
+       "    <script>\n",
+       "        window.interactLoadedFlag = true\n",
+       "       $(\"#interact-js-shim\").bind(\"destroyed\", function () {\n",
+       "           if (window.interactLoadedFlag) {\n",
+       "               console.warn(\"JavaScript required by Interact will be removed if you remove this cell or run using Interact more than once.\")\n",
+       "           }\n",
+       "       })\n",
+       "       $([IPython.events]).on(\"kernel_starting.Kernel kernel_restarting.Kernel\", function () { window.interactLoadedFlag = false })\n",
+       "   </script>\n",
+       "</div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PyPlotBackend()"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "using Plots, Interact, LaTeXStrings\n",
+    "pyplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:23.190347",
+     "start_time": "2016-12-05T05:37:15.763Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "intermap (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function intermap(M, R)\n",
+    "    m1(x, s) = mapins(x, M, s, R)\n",
+    "    srange = 0:2500.0\n",
+    "    #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "    ff = diagbifurc(m1, 300, 10, srange); \n",
+    "    cc = ones(size(ff)[1])*srange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "    ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "    cc = reshape(cc, size(ff));\n",
+    "    return ff, cc\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:23.301461",
+     "start_time": "2016-12-05T05:37:16.323Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "iteram (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Código para generar las bifurcaciones\n",
+    "\"\"\"\n",
+    "    ciclosestables!(xx, f, nit, nout, cc)\n",
+    "\n",
+    "Esta función itera el mapeo `f`, de una variable, `nit+nout` veces, \n",
+    "usando como condición inicial `x0=0`; los últimos `nout` iterados \n",
+    "actualizan al vector `xx` que tiene longitud `nout`. `cc` es el valor\n",
+    "del parámetro del mapeo `f`. El mapeo `f` debe ser definido de \n",
+    "tal manera que `f(x0,cc)` tenga sentido. La idea es los últimos \n",
+    "`nout` iterados reflejen los ciclos estables del mapeo `f`. \n",
+    "\"\"\"\n",
+    "function ciclosestables!(xx, f, nit, nout, cc)\n",
+    "    @assert nit > 0 && nout > 0\n",
+    "    \n",
+    "    # Primeros nit iterados\n",
+    "    x0 = 1000.0\n",
+    "    for it = 1:nit\n",
+    "        x0 = f(x0, cc)\n",
+    "    end\n",
+    "    \n",
+    "    # Se guardan los siguientes nout iterados\n",
+    "    for it = 1:nout\n",
+    "        x0 = f(x0, cc)\n",
+    "        @inbounds xx[it] = x0\n",
+    "    end\n",
+    "    \n",
+    "    nothing\n",
+    "end\n",
+    "\"\"\"\n",
+    "    diagbifurc(f, nit, nout, crange)\n",
+    "\n",
+    "Itera el mapeo `f` `nit+nout` veces y regresa una matriz\n",
+    "cuya columna `i` tiene los últimos `nout` iterados del mapeo\n",
+    "para el valor del parámetro del mapeo `crange[i]`.\n",
+    "\n",
+    "La función `f` debe ser definida de tal manera que `f(x0, c)` \n",
+    "tenga sentido.\n",
+    "\"\"\"\n",
+    "function diagbifurc(f, nit, nout, crange)\n",
+    "    xx = Vector{Float64}(nout)\n",
+    "    ff = Array{Float64,2}(nout, length(crange))\n",
+    "    \n",
+    "    for ic in eachindex(crange)\n",
+    "        c = crange[ic]\n",
+    "        ciclosestables!(xx, f, nit, nout, c)\n",
+    "        ff[:,ic] = xx\n",
+    "    end\n",
+    "    \n",
+    "    return ff\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    Lyapunov(y, F)\n",
+    "\n",
+    "Dado un punto un arreglo que contenga todas las iteraciones bajo $F$ de $x_0$, calcula \n",
+    "$\\frac{1}{n} \\sum_{i=1}^n \\log\\Big| \\, f'(x_i)\\, \\Big|.$\n",
+    "\"\"\"\n",
+    "function Lyapunov(y, F::Function)\n",
+    "    n = length(y)\n",
+    "    l = 0\n",
+    "   \n",
+    "    for i in 1:n\n",
+    "        x = abs((F(xdual(y[i]))).der)\n",
+    "        l = l + log(x)\n",
+    "       \n",
+    "    end\n",
+    "    l/n\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    iterado(F,x0,n)\n",
+    "\n",
+    "Dado un punto $x_0$, esta funció guarda a todas la iteraciones bajo $F$ en un arreglo.\n",
+    "\"\"\"\n",
+    "function iterado(F::Function,x0::Float64,n::Int)\n",
+    "    y = Float64[x0] ##El primer elemento es x_0\n",
+    "    x = x0\n",
+    "    for i in 1:n\n",
+    "        x=F(x) #El valor de x cambia con cada iteración\n",
+    "        push!(y,x) #Este nuevo valor se guarda en el arreglo\n",
+    "    end\n",
+    "    y\n",
+    "end\n",
+    "\n",
+    "\n",
+    "\n",
+    "doc\"\"\"\n",
+    "mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "\n",
+    "Calcula el exponente de Lyapunov para un mapeo paramétrico $Q_c = Q_c(x, c)$ en un rango de parámetros `crange`, un\n",
+    "valor inicial `x0` y `n` iteraciones.\n",
+    "\"\"\"\n",
+    "function mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100_000)\n",
+    "    mapeo = Float64[]\n",
+    "  \n",
+    "    for i in crange\n",
+    "        Qci(x) = Qc(x,i) \n",
+    "        y = iterado(Qci,x0,n)\n",
+    "        l = Lyapunov(y, Qci)\n",
+    "        if abs(l)<Inf #En algunos puntos labda diverge, por lo que si tiende a infinito, se la asigna el valor-2.5\n",
+    "            push!(mapeo,l)      \n",
+    "        else\n",
+    "            push!(mapeo,-2.5)       \n",
+    "        end\n",
+    "      \n",
+    "    end\n",
+    "    mapeo\n",
+    "end\n",
+    "\n",
+    "function iteram(M1::Range, R1::Range)\n",
+    "    P, Q = length(R1), length(M1)\n",
+    "    Mat1 = zeros(P, Q) \n",
+    "    K = Int(P*Q)\n",
+    "    n = 1\n",
+    "    #@show (P, Q)\n",
+    "    for j in 1:Q\n",
+    "        for i in 1:P\n",
+    "            if mod(100n/K, 5) == 0\n",
+    "                println(100n/K, \"%\")\n",
+    "            end\n",
+    "            #@show i, j\n",
+    "            M, R = M1[j], R1[i]\n",
+    "            m1(x, s) = mapins(x, M, s, R)\n",
+    "            srange = 0:3_000.0\n",
+    "            #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "            ff = diagbifurc(m1, 300, 50, srange); \n",
+    "            cc = ones(size(ff)[1])*srange';\n",
+    "            \n",
+    "            # Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "            ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "            cc = reshape(cc, size(ff));\n",
+    "            for l in eachindex(ff)\n",
+    "                if ff[l] == 0\n",
+    "                    Mat1[i, j] = cc[l]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "            n += 1\n",
+    "        end\n",
+    "    end\n",
+    "\n",
+    "    mm = ones(size(Mat1)[1])*M1'\n",
+    "    rr = R1*ones(size(Mat1)[2])'\n",
+    "    A1 = reshape(Mat1, size(Mat1)[1]*size(Mat1)[2])\n",
+    "    mm1 = reshape(mm, size(A1)[1])\n",
+    "    rr1 = reshape(rr, size(A1)[1])\n",
+    "    return mm1, rr1, A1\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:23.303268",
+     "start_time": "2016-12-05T05:37:16.805Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapins (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Mapeo\n",
+    "mapins(x, M, S, R) = (R*x^2)/((R - 1)*(x^2)/M + S + x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Primero, decidimos ver el comportamiento de los diagramas de bifurcación con respecto a los parámetros $M$ y $R$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:41.485985",
+     "start_time": "2016-12-05T05:37:17.963Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Int64}(Signal{Int64}(50, nactions=0),\"M\",50,1:100,\"d\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(50.5, nactions=0),\"R\",50.5,1.1:0.1:100.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {
+      "comm_id": "ac7bd381-e049-4f9b-8b14-a25cc245ef7a",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@manipulate for M in 1:100, R in 1.1:0.1:100\n",
+    "    ff, cc = intermap(M, R)\n",
+    "    scatter(cc, ff, markersize= 0.5, legend = :false, title =\"Diagrama de bifurcacion\", xlabel =L\"s\", ylabel =L\"x_{300}\")\n",
+    "    xlims!(0, 2500)\n",
+    "    ylims!(0, 100)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:41.532978",
+     "start_time": "2016-12-05T05:37:18.995Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Parte de Sofia\n",
+    "#M1 = 1:67\n",
+    "\n",
+    "#Parte de Pablo\n",
+    "#M1 = 68:134\n",
+    "\n",
+    "#Parte de Daniel\n",
+    "#M1 = 67:100\n",
+    "\n",
+    "#R1 = 1.1:0.1:100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:41.536148",
+     "start_time": "2016-12-05T05:37:19.435Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Parte de Sofía\n",
+    "#mm1, rr1, A1 = iteram(M1, R1);\n",
+    "#writecsv(\"mms1.csv\", mm1)\n",
+    "#writecsv(\"rrs1.csv\", rr1)\n",
+    "#writecsv(\"ccs1.csv\", A1)\n",
+    "\n",
+    "\n",
+    "#Parte de Pablo\n",
+    "#mm2, rr2, A2 = iteram(M1, R1);\n",
+    "#writecsv(\"mms2.csv\", mm2)\n",
+    "#writecsv(\"rrs2.csv\", rr2)\n",
+    "#writecsv(\"ccs2.csv\", A2)\n",
+    "\n",
+    "#Parte de Daniel\n",
+    "\n",
+    "#mm3, rr3, A3 = iteram(M1, R1);\n",
+    "#writecsv(\"mms3.csv\", mm3)\n",
+    "#writecsv(\"rrs3.csv\", rr3)\n",
+    "#writecsv(\"ccs3.csv\", A3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Lo siguiente fue encotrar $S_c$ como función de $M$ y $R$, para esto empleamos el dominio $M\\times R = [1,100]\\times[1.1,100]$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:37:43.348339",
+     "start_time": "2016-12-05T05:37:25.044Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "mm = readcsv(\"DatosPlano/mms2.csv\")[:,1]\n",
+    "rr = readcsv(\"DatosPlano/rrs2.csv\")[:,1]\n",
+    "cs = readcsv(\"DatosPlano/ccs2.csv\")[:,1];\n",
+    "append!(mm, readcsv(\"DatosPlano/mms3.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs3.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs3.csv\")[:,1]);\n",
+    "append!(mm, readcsv(\"DatosPlano/mms1.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs1.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs1.csv\")[:,1]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:38:23.001597",
+     "start_time": "2016-12-05T05:37:52.090Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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yMjICEEQMDAwQF9f34TfgtML+76QPg/5fJ7u7m56e3vp6+ujp6eHrq4utNbZczc6OsrIyAgjIyMUi0XK5fKY4FePp1m0qiCpbBmGYUgul8tWKCqliOM4e98MDw8zODiYvcdHR0cpl8vZl03P3lFG3DzC6f5MfH43bdrEBRdcwFve8hb6+/s57LDDOOOMM3jyySfHbfv4449z0kknMW/ePBYsWMBZZ53Fjh07aj7uddddx/Lly+np6WHZsmV84xvfqLnd7t27Oe+881i0aBH9/f2sWrWKzZs3Z/f7CpZnQnzkwt5JkoRCoUAURQRBMOvt0spv3ulxpJWuyp+JzPQ+b8jTKNpReFT7tVJ8ZlcDkARMHTUdmXgV4Ve/+lXuv/9+1qxZw9ve9jZefPFFrrrqKlasWMGDDz7I8uXLAdi6dSt/+Id/yP7778/ll1/O0NAQ//AP/8Cvf/1rHnrooTHdgX/913/l/PPPZ82aNVx44YXce++9fOYzn6FYLHLRRRftOSwRPvCBD/Doo49y8cUXs2DBAq6++mpOOOEEHnnkEY444ggvsDzjmWrkQisHeja7glVpYNda09fXRz6fb8kLaqXoSpnITJ9mDwFj/Ci+PbJv+PPW3kw1s6tye5/Z1XwuvPBCbr755jECae3atbz1rW/l8ssv54YbbgDgK1/5CsVikV/+8pccfPDBALzrXe/iT/7kT7j++uv5xCc+AcDo6Ch/+7d/y6mnnsott9wCwLnnnkuSJHzpS1/ivPPOY2BgAIBbb72VjRs3sn79ek4//XQA1qxZw7Jly7jkkku48cYbfYvQs4e0YlUqlYiiaEwC+2QXhVYUWM1CRCgWi+zevZtSqURPTw8DAwN0dXVNeo5aTYxWfgCkXrG+vj56e3vp7u4mn88DZK+HQqHAyMgIhUKB0dFRoijy7ZEp0Mnnp1ExDa1KdYsxFVPplxFjDIODg+zevZuhoSGGhoYYHBzk8ccf55vf/GbnvTaM1P8zAccdd9w4b+qRRx7JUUcdxZYtW7Lbbr/9dk455ZRMXAH88R//McuWLeM73/lOdtvdd9/Nzp07+cu//Msxj/mpT32K4eFhfvjDH2a3rV+/noMOOigTVwALFy5k7dq1fP/73yeKIi+wPGMjF1JhNZV2YCtfOBtdwUpbA7t376ZYLJLP59lvv/2yFYLTPbZWJRVd+Xw+E119fX2Z6Ep9XaVSiWKxOEZ0eU+Kp9OpXAWcVozT91R6TdqyZQv//u//3tLXgaaQxjRM+2f615OXXnqJhQsXArBt2zZefvll3vnOd47bbuXKlWM8U+n/H3PMMWO2O+aYY9Baj9t2xYoVNR+zUCjwxBNP+BZhJ1MZuZCanafbBmqFvKlmE0URxWKROI7J5XLMmzdv3DLw6dJOF9fJVjBWtxgr96luMXo6j3Z6nTeL6ozAkZGRLA/P03huvPFGtm7dype//GUAtm/fDsDixYvHbbt48WJ27txJFEXkcjm2b99OEASZOEvJ5XIsWLCAbdu2Zbdt376d97znPTUfE6yw8wKrQ6k1jHkuXQzTEv2+kCRJtuKuFQzsrcRUzPSpj6+ayjmMneLr6oS/sZq5/sVrKtQ6B4ODg8yfP38WjmaWmYEcrMcff5wLLriA448/nrPOOguAYrEIQFdX17jtu7u7s21yuVzWnahFd3d39ljpPhM9Zmol8QKrw6glrPYlUG8uVrDSeWejo6MopRpiYG81D1YzmMxMn4qtJEmIoqhjzPRz+fmeCnPleayHiTxoQ0ND9Pf3z8YhzS578VNNut8UeOmllzj55JPZf//9ufXWW7Pz3tPTA0CpVBq3TzrCLN2mp6dnzArr6m3T7dJtJ3rMNGDaC6wOoVmRC3NJYIlI5i0SEXp6euju7u7oD4l9pXocUJIk9PX1jWsx+nFAc4+5cl2YPjGVCUi1BFZHVrCmwLfvK/Ptn48VOLsLe38dDQ4OctJJJzE4OMh9993HQQcdlN2XtuzSVmEl27dv54ADDsiq8IsXLyZJEnbs2DGmTRhFEa+++ipLliwZ87gTPSbAkiVLvMCa60w1cmGuMR3hly6zLhQK4xLYPY2n1gxG8OOAPO1OhNLPo3SCiZdNeP3p3Bbh3mcRfvj3Qz78+2NlySPPJKz8m5EJ9ymVSpxyyik89dRT3HnnnbzxjW8cc/+SJUs48MAD2bRp07h9H3roIY4++ujs30cffTQiwqZNmzjppJOy2x9++GGMMeO2ve+++8Y95gMPPEBvby/Lli3zqwjnKvVGLkyXdq9gxXHM0NAQw8PDaK2ZP3/+pAns+0o7n6tmk5rp02T6dAVjT0/PlFYwVgsyz+zSOeO0YpR+Ah0+gtIvYWJb5ZioRTg8PNyZAquuFYST+7aMMaxdu5YHH3yQ2267jZUrV9bc7kMf+hA/+MEP2Lp1a3bbnXfeyRNPPMHatWuz21atWsUBBxzANddcM2b/a665hr6+Pk4++eTsttWrV/PSSy9x++23Z7ft2LGD2267jdNOO81OBpj2SfK0NI1YGVjP72w19ib8qg3s/f395HK5pp2nzvigaTwT+bomM9NXLpNvlcG9/vmfi8TAMyj9MhAhJg9qAJjcX+VbhI3jc5/7HBs2bOC0005jx44d3HTTTWPuP/PMMwH44he/yG233cYJJ5zAZz/7WYaGhrjiiit4+9vfzsc//vFs++7ubr70pS9xwQUXsHbtWt73vvfxs5/9jP/8z//ksssuY7/99su2Xb16NVdeeSVnn302jz32GAsXLuTqq6/GGMOll14K+FE5c4bZEFbp72gn0tUdqRGxt7d3ryGhntZib2b6VhoH1IpfPmaSufm+MsCzoF5AkSAEaKVADCY5PNtqMpN7RwqsJpjcf/WrX6GUYsOGDWzYsGHc/anAev3rX88999zD5z73Of7mb/6GfD7PKaecwhVXXDFuZfj5559PPp/nH//xH9mwYQOHHHIIV155JZ/+9KfHbKe15o477uCiiy7iqquuolgssnLlSm644QaWLl0KeIE1J5jNyIVGxCE0g+oKVrWBvbu7u66QUE9rUsvXNd1xQN7X1VjmZovwGeC3gAExCDmQBKM0inlA37g9vMByTMGDNeF+E3D33XdP+WHe/OY3c8cdd0xp23PPPZdzzz13r9sNDAxw7bXXcu2119a83wusNqbRkQtzkdTAXiwWSZIkSyifreDLym+1nV7daDaVoqsyKLVWe9Gb6ZvDnDlv5hlQzwAFUOm1IwAMKAUIIkeM2aXW+1tEOldgdSBeYLUhlZEL6bfE2coOamWhkF7M4jgmDEPmz58/LpF8ppgzHzRzgFpfRKorXdXJ9JUVrsoW41To1Oe+Va8L08I8C7IFZASCPKCwLUIBNBCB5IEDqPZe+RZhFU3OwWpFvMBqI2pFLrRCKGOrXUgr/TfGmKYb2D3tz97M9FMdB1T9Gmu194ZnikQvgDwKDFtNpXJgYlAhkLgqVpp3ZYClNR+m1jVnaGiIgYGBph16qyIyrVD2Mfu1K15gtQGtnGXVCseQIiKMjo6OGWcwMDDQUsfYybSb2KhnHFC1mT71gXUibenBil+E5BHgNXeDE9wqsUUrlYAorOoClAALgN5xDzXR896xFawOxAusFia9mKc5VkDLCKuUVmgRigjlcplCoZAZ2LXWFAqFWT2uSjphVE4nMNUVjNVm+mKxOGfHAc0Jkh1QehjkZdv5Q4MObMlFhWAS0Ol/A5DEVbMM8MaaD1lLYKaZbR0psMT91LNfm+IFVgtSGblQKBQolUrst99+LXtBnk3RkCawVxvYa82I8niawWQrGEulUrbKtpPGAU3kP2o5ol1QehB4DnDL9U3a/nPPpyT2/02qEAwQQGDAvA70+JWDKbX8V2lwbsdh3E89+7UpXmC1GNUrA9MKUateqGbruJIkoVAoEEVRTQN7ZcWoVc+dZ+5SKbrSuZYw9XFA9ZjpPdMg3g2l+53XSiDQQAxBCBKD0hVVKgESW80KAru9FkiA4KgJf0WtL55DQ0PMmzevWX+Vp8XwAqtFmChyIf1W3KpCYaaFjDGGYrFIqVRCa+0N7J6WpvpDNh0HVL3NZCsYp2Kmb1Va7jjjYRi5B6LnQRkrpDRglP1vkoDWri2l7DaJcSsIDSSyx4/F60GN916lpNfxSlKB1XLnZSZIi3/17NemeIE1y6SRC+kFtXploK/EWCoN7Eopenp66O7u3us5aRXPUy0PVqc/px5Lo8YBtZKvq1XedxlJAYbvg/gJ2+rTqVFdnLgygHbL3LSrYgGJstua2HqviIG8vT18y7QPY3BwsHMFlm8RemaKVo1cmC7NFoCpgb1YLGKMoauri56enr0GqrbbefR4KmmncUAtjUQw8nMY+hXoBBDQOZcoHjhhFVREW4kzsivbClQCogGz54M+SIDXQ9Az+a+ucU30LcLOwgusGWa6kQvtsvqsGcdXaWDP5XLMmzdv1hLYPZ56aZTAqXcc0GyY6Wfd5C4Ghu6HwUcgGLUiSSlItG37iataiXJRC8q1/gJ7v9Gg0pwrcfmizoNlFOSPntJheIFVgakvB8tXsDx7pdYw5qlc6FpdYDXjAlppYA+CgHnz5o0byDnV42rV8+bpDJr9+pvKOKDJzPRzchzQ0CYYvh/MMKCsWArEdvcCcZUpjRVOOVuxCtJVgrHdB+fNEuNahMp5swzI60FPXr2CiU3uHRnRAN6D5Wk8tYTVdMr2rS4UGnl81Qb2vr4+8vn8nLnwt0JmmKczmOlxQBMxo+/doV/C8L1Q3AW5wH4wB1hxlM4MFCFLXzfathDTFYP2gG21S6cxDelIHCeuTAC9x+z1UCYbk9OxFawOxAusJlJrZeB0LzitLrBS9uX4UgP76OhotqR9Kgb2yWiX8+bxzBSNGAc01YHyM/q+G/pf2HUPKtkJKCRUEMXQpa0ZPXCtv7S9Fya2VRg4QzvY6pWCbOVg5bhBwW4rGoLDQXdP+dCqr2GDg4OdW8HyJndPI5gocqEeWl0o7IsIqtfA7vG0E61cgW3EOKDJzPRN/duHH0Pt+B/E7IBYkK48KhYIQCmNpCsA08pV4qpYcQJBzlWzFHa2YM6tHFRObKVVrNSTFdoWYf5dUzq0ia7Xw8PDHHzwwQ07BW2FF1iefWFvkQtzkXoFYBRFFItF4jhuioG9VYVpurJoLr8mPHtoxyiOyVYwTmamr6x0pXaIpjDyNGrnj5DRbfa9hEZyIOUI8oH1qofGVa80xAGEArGBXFrVckGhobgZg857la0adPEN2XwXA+FSCLqmdIgTtQgHBwd585vf3Lhz4WlpvMBqAM2MXGhVoVAvSZJQLBYpl8t1G9jblfS5TM8BMDdNxp45Ry0zfaXoqqx0VV6risVi41YwFrfCKz9ADf4WuhQqBhMqlNF2BSDKrvQTUKJt9SoWRItrCSqIYwgDu50OXHCodkb30Fa3NNiyibZVK+Pai91Tq15Vn7dKhoeHO7ZFKGhEpt+daOdPPi+w9oHpRi7USyubo6cqAI0xmc9KKTXnDOxTQUSIoig7B0BNk7EXXZ52oFZsBJDNYIzjGK31vo8DGn0ZXt6AHn4cUPZTKwEJQRnjqlPYUYJlg3SFqEiQtFqVw4WLYmMZAGKBnHFjcuzjodMHFevZ0mqPDyt4E+ipzw+c6HrY0asIDa4qWMd+bYoXWHWQfmuLoih7IzXzw7CVBVbKRMeXXmyLxWLDDOxToZUqf+k5SAV5OpA6FeVTWdnlRVf70mnPV6Xo6u62hvDpmumDIEBFO1Fbf4CMPAZJBHmFRAHkNGJABU4AJRHo0IktjSKBUKHEILkgu53IIHkNkdhVhnEMYWj/qwMr0sIEkgAb2uRmEeou6J1e9WqyFmHHCqwOxAusabCvkQv10soCa6K/Pa3WFAqFjjawV4alAuTzeXp6esZUPSda2eVFl6ddqfaeTctMH+0i98oPyY38xi4SCkAF2uqdnOyZF1g2kAuQWEHeeqZUYCByKwmNQWl37ZT0WuV8VZLYapakJSpjq1eCHYsTuGgGgHD5tKpXk52ToaEhBgYG9vmx2hKj6qxgte+1zQtZZEjYAAAgAElEQVSsKdKIyIW5SrUAjOOYQqFAHMeEYUh/f/+4AbczcUwwexWs6rDU+fPnMzIyMqXjqmc5vRddrUmrfjFqBca9zpNR+N13Ua8+hCGxgiqApCyovEHKGpVPQGkCNKgAbQwqAImMy75SEChUIkgY2riGXIgqGyQf2H9rDbHdjsRVtxIDoanwZMX2l+vuaVevYOIK1vDwcMfmYAkKkelfk4T2vY55gbUXGhm5UC+tXMGqpNrA3t/fTy6X66gPehGhWCw23Gu2twrAZKKrkcGRHs9UmfJrLSnB1g3oVzYilOxrXQTygfVO5QJEKaQbTGyT1U1kkBDiWKPy2BzRRFCJQuVDUBpl+4go7HBnJUJ2GVW4+AW3mhDsg4hLfZfAbpN/i51d2KC/v6MrWB2IF1gT0EqRC+0gsNI8K6UUvb29dHV1zfqH+UyetzTTq1AoICJ0d3fT09PT1HPgRZenVZnS+04S1O9+hNpxD4wOITkbBGo0NnpBDBoFCvtfBJ0PrVDKB5CAyWskSZBQI+UEEwZQHIWuHKok0BWiS9j4hjiA0K4sJBRrhHetRBvnYOwnoou/QvdB/3EN+/vjOGZkZKRzBZZvEXqaGblQL6kRutWoNm/PhKhoRdILZ5IkmcdqokyvmZhN50VXa+HPZRUisP0u2P5jGN2NhBoVBKjErvTTRpAgQBllC0miMCQ2LgH3pUkJGI3SglYBohUqVBitUYHGCBilUYkhToCyzbLSRkDlIUnQBKg02kFjq1ZJOvhZIP922yas608cn382NDREGIb09Ox9juGcRNSeVZzT3a9N8QLLMVORC/XQahWs1MBeLBZJkgSlFLlcjt7e3tk+tHE087wZYygUClPO9Jqt15IXXbNHK71vZ5KaAasiqG13wrafoKLXwBgktBlUEiqUBNnIPzDWeWMClBZbtQoEktgKssSt/EuU9V6V7WMpxK4gJCAM7e/UucCOEXTVKdEREkMSGNSotqsRowRCIYi1rXapHug/dp/OwURzCP37qHPorCVdNUiFValUymIXvEl4YuI4ZmhoiOHhYZRSzJ8/v6EJ7I2kWc9f6rPatWsXURTR29vL/PnzpxWYOtuvrVR05XI5uru76e3tpa+vj56eHrq6urI07rT1OzIyQqFQYHR0lHK5nHkS6/m9ng5k+72oh7+IPPMdpLTThkcqjRZBKY1OsGnqsbYFixhMIhDHGBGMCRAExHqpQFvzswISgw4Dl+oOGEGpBEjH5hi0hlCEMJ8jF4bkwxx5pQk0KCUulSEmNhFxFDFqjqI4Ws7yvIwx03q919p2aGiI/v7+jn0PiIAYNf2fvZz2kZERLrnkEt7//vezYMECtNbccMMN47arnqdZ+fO+971vStt+7WtfG/e4u3fv5rzzzmPRokX09/ezatUqNm/eDHRwBWu2IhfqoRUqWJXVGq31OAP7bB/fTFAdPdHd3U13d/eciZ7wlS5Po0i/qPLyI6jnvgfFF0EptAhGK0hkTwp7KK4NpFHagBjbMtQKQdBxYkffRIFNZY8ElQ9QsQsTNSDK2JWD+QBigwS5Pe2+xFjvldhqmQIbIpqAzgc2yLJLQwSSU6D7MAPHIsKk44CCIJjwMyP7+ytIK1gdS5M8WDt27OBLX/oShx12GEcffTQ//elPa2534403jrvt4Ycf5l/+5V/GCSyA9773vZx11lljbnvHO94x5t8iwgc+8AEeffRRLr74YhYsWMDVV1/NCSecwCOPPNK5AitJkjEVq1b+UJhNgSUijI6OTmpgb9Vz18jzVhk9Ue/sxFYQytOlHtFVGRrpRVfrvj+aidr1BMEL/wVD2xCdYM1VdjWfdvP9VCyI1qgYJFAQKyRIUEZhQkHFCsLAtgaNQinXNgwDSBIbIioGFWiQyPm27CgcZZI9SeyhQnDbmQRxtyvciBzc6By03b7vOLq699gdamV11UqmrxRfULtFOH/+/LpeD6VSiQ9/+MNs2bKFnp4eFi1axNVXX80RRxzBK6+8wllnncXTTz9Nd3c369at4w//8A8BO6ro3HPP5eGHHyYIAr7yla/woQ99CLDv48985jPccccdaK357Gc/y6c+9alpH9tss2TJEl588UUWLVrEL37xC971rtqxGh/5yEfG3XbXXXehlOLDH/7wuPuWLVtWc59Kbr31VjZu3Mj69es5/fTTAVizZg3Lli3jkksu6VyBNdGYh1ZkNj6Ya62Km6ha06om/EZgjKFYLFIqlbLKXT6/76GD7fyhO63QyIp90tdxkiQdIbraTUw3hMHn4P9uI7fjMVuFCgCMzZxyc5TFKJu47rzqKEGbJDOsSKhQSYyEtkpFqCDRmJzYKpVKUAYQQRJli19RYENIJbAxC1GC5EMbw6CARCFEdoVg3q5WlNBGO4g2KBMggUEF85B5Y71XtaJ50tdx5Wu+8vWebqOUYtu2bRxwwAEMDg7uUwXrk5/8JCeddBIA69at4xOf+AR33303X/jCF3j3u9/NHXfcwaZNmzj99NN59tlnCYKAK664gu7ubp588kmeffZZjj32WFatWsX+++/Pf/zHf/D444/z1FNP8dprr/GOd7yDVatWNW0YtUidOVh72SeXy7Fo0aJpP265XOb222/nhBNOYMmSJTW3SeN2urpqD/lev349Bx10UCauABYuXMjatWu56aabOteD1U4X+Jluw0VRxODgICMjI+RyOQYGBujt7W0LMVrJvgjT1Ge1e/duyuUyvb29DAwMNERczUUqPV1dXV3jPF1hGGbPRerpGhkZ2WdPl6dFGPwdbPo6PPT/wmtPWFFjjK0WETrneoJObI6VioxdVAaIEowoDOI+hAWlNUqUNaAngDZoAUK79g+tULFBayvOVC71XJks6V2LASUoI6gAlAgqVG4uodgqlwGFsanvIkjvcTCFzwWlFGEYks/na3oYU8rlMn/1V3/FIYccwt///d/z9NNP89WvfpX//u//5pVXXpny6e3q6srEFcBxxx3Hc889B9gqyl/8xV8A8M53vpODDz6Ye+65B4Bbbrklu+/www/nhBNO4Lvf/S4A3/nOd/jzP/9zAPbff3/OOOMMbr755ikf07QRDaaOnzoGRE+FH/7wh+zatYszzzyz5v3XX3999pweddRRNc/N5s2bWbFixbjbV65cSaFQ6NwKVjtRKbCaKQor08fDMGT+/PlTSmBvx9bXZKSVu2aO+BGROXXOalGd1K2Uolwu09PTM2mlq5bPxdOiDL8Iv/kOvPa4HT+jralckgSVy9lVewEQa5sthTWpKy12RiBYD5QyKKNtBlasrD8rNpi8RqkAtHHTbYTEhLZKZYwb1KwRZUNClbYiDW1jHNAgibLHFSvr2RIXMIq26e2RQF6jgv2Q+fXlXsHY13upVCKXy5HL5bjsssvYtGkT//M//8PGjRv58pe/zPDwMACvf/3r2bx5MwsXLpzW7/r617/On/3Zn7Fz507iOB5TwTnssMN4/vnnAXj++ec57LDDsvsOP/zwSe978MEH6/77242bbrqJ7u7urGVayfHHH88ZZ5zB4YcfzrZt21i3bh1nnnkmg4ODfPKTn8y22759O+95z3vG7b948WKgg03unj3UaoNNN4G9FcXCdIVftcBs9IifudxKnSp7GwM0F0VXOx3rlCnugsdvhW3/Czq2pSgtQIAoQXSIVukKPYNom6guKrHtutSnpG3mlBIAV3XS2g1oVqjE2AJGIigNSqzfyla1tItXMOjE6ikSZR8zTiCn0LGxw6FjrN/LGNCuoubmFNrrRILpO35K1au9UTkmRynF8uXLWb58OS+88AKHHnoo//zP/8zTTz/N5s2b+fWvf82CBQum9fiXXXYZTz/9NNdeey2FQmGfj3emEOPaw3Xs12iGhob40Y9+xMknn1xz+Pa999475t/nnHMOK1as4Itf/CIf//jHsyplsVis2T7s7u5GRDpXYLXTRa9ZLcJqA3tPTw/d3d3TPjftdC5r0QiB6amfThRdbUt5BH7zXXj+AVv9SY3h2q7mQwvELrczVkheWzM5toWnXXsPI9bYbgTR4nLaDZIIhAkqxgqgRIE2KAnscn33KxFtxZDGrv9X2rUlFaLEJsFnBnbXFgxdNUsZe5sWVGSsKV7th+w3/ZmDk1HL5H7AAQegtWbp0qUsXbqUtWvXTusxr7jiCr73ve9x5513Zr7YMAx5+eWXsyrWs88+y6GHHgrYatZzzz3H6173uuy+dMXcoYceynPPPcexxx47br+m0EJJ7rfddhulUmnC9mA1YRhywQUXcP755/OLX/yC3//93wegp6eHUqk0bvvUu9WxAgvap7XVaIGVGtiLxWJD2mDtch6rSZPoi8UiIlK3wPRMjem8RiYSXZXm4lYXXe34npiQJIItG+CFn0O5YE3rsYIwsQILcTP87Pk2UYLuSttytgQhSmeCSisrepRWzuiODQUNta0+hRoxBh1oiAQJIxc6qpAYVM4g6cBmsXEOYCtmqTFeicKWthQE2lXDUg+WXYmoCDFikP3Gt3nqZaLnfWhoiMMPP7zux/2nf/onvv3tb3PnnXeOMcuvWbOGa665hksuuYSHH36Ybdu2ZW2r1atX881vfpOVK1fyzDPPcM8993DNNddk+/3bv/0bq1evZteuXdxyyy388Ic/rPv4GsF3Hhvl1sdGx9y2e7Tx76ObbrqJgYEBTj755Cnvc8ghhwCwc+fO7LbFixezffv2cdumt3W0wGoXGimw0hynJEnqjhuoRSt+mEzWkqs8D/l8fsZM/K14ntqFWit/2010tR1JDFt+DC/cC8Vhm1ml3XTlILZ9uZA9c/wMdvVfGNgxM8q25USDLieYfOj+batIRsmewcwoJLHBo9acrt1YHIDACjEj1viOLZaJGLKPsViQILHVLJRNeRdX8tICZZC8q6IoY+MgggSVW4gMvLNhp6yyRVhJGtNQD1u3buXzn/88RxxxBH/0R3+UrezeuHEjl19+OR/96EdZtmwZXV1d3HTTTdk1/aKLLuKcc87hyCOPJAxD1q1bxwEHHADARz/6UTZt2sTSpUvRWvP5z3+eo446ah/+8r2hkb0Y1tcs72XN8rETQX75YsQf/PurDTuKF198kZ/+9Kecc8450wqHfvrppwE48MADs9uOPvpo7rvvvnHbPvDAA/T29nqB1Q40QmBV+oumMtalnuNrB+o18jeCdjpP7UK9oqsyt8iLrhqYGB7/CTx9L8SDuInLtmqVc1UrVwUiwlavEmW1TuTyquIEyWFbeEYhgasaKRf6GRhbZcJAAiowiLFhosppN5UYCAIbu5BzswIVkJB5swj2hIfqWGECg/W8O38VCSrRkBPXKnThotoa7s28P2rKKWykwDr44IMn/LK4aNEifvzjH9e8r7e3l29/+9s179Nac9VVV3HVVVfVdUzTJU1mr2e/RnLzzTcjIhO2B3fs2DFu0cHQ0BBXXnklCxcu5JhjjsluX716NevXr+f222/ngx/8YLb/bbfdxmmnndbZAqtdW1vTodpf1NfXRz6fb+gHykytcpwulc9vGruQ9sabcR6me2ye5jBV0VUul8fs0yzR1VbPtQj830/h/+6CeMgKkiCwKwTD0FWtnI8pUnt6IMpViVwEgkQG8nknuozzRhlQGqOt4BGlbZ6VsrEMts1nUFhDOyJWgIk7BmMg0Ijr8NlcLVulUtiRKoLzYzkBJUZBgBu3YoWdGLtiEQx0LYT9j6l1JvbhFE7cIqxXYHkmZ926dezatYutW7cC8F//9V+88MILAHzmM58Z01K96aabWLJkSc3Vf+ljfe973+PUU0/l0EMPZdu2bXzrW9/ihRde4MYbbxzzhXz16tVceeWVnH322Tz22GMsXLiQq6++GmMMl156aWcLrHahngpWamAfHR3taH9R6rOqDEzt6enpuPPQ6cyG6Gq3L2/mtw/AYz9Bj+7cY1wPYuurUiFuKR5ucKAVVIl2wZ7Ktg9RVvQEoVsJGAJuCLMIaFutkkChTIJSzryOseNzctjWoJ00iAkEHYsdlZMoyNu0UmOcmAsgXblIDOQEXTaYvP1Vol2rUBsruhBU4o5dINnvxIafx1otQhFhaGiIgYGBhv++tsEot9Szjv32whVXXJHFTyil+O53v5vlfX30ox/NBNYTTzzB5s2bufDCCyd8rOOPP56NGzdy3XXX8eqrr9LX18exxx7L9ddfP06Uaa254447uOiii7jqqqsoFousXLmSG264gaVLl3qB1Q5MR2A12sA+3eNrJeGSrkQbGRkhn8/T09PTsoOpPTPPVERXOvC6cp+51l5Mnn8U9esfweArLkfKVpQwxgorXAwD7r3jQkTJh9ajJU6IYb1TRABuDA4CqbkcbatS2NDP1NiuXJdQaY02BjAo0QgJOgnsw6L2ZF8p3EBnm3Ul2s0h1DqLgFAmrV67YcEidiFjTiFpuGj362D/8SGRzaLTZxEKdSa5s/d9nnnmmSk91rJly0iSZNJtTjzxRE48cerCe2BggGuvvZZrr7123H0dLbDa6cI4lXZmFEUUi8V9mpe3L7TKN/bKwdRAQ/1m+0Llc9hOr71OohGiq9ZolVYkfvm38MgP4JXfQQ4rXrRCB4GrDrlZfYHrx6UeoEhBTkHZVZAULk10z2tbRLnZf2JzrRJjq1YIqMAGNoi4SpVGjGSdR0LX6tMBEokdgRMpyGmIQeXc4pXApb2LYESjlB2dowKBOEYCjUrsSkWMQekAEYNSGkFhDhg/4LcRTGZy7+gKVgfS0QKrnZhMYCVJQrFYpFwuN9zAPtVjawWqc73CMMxWS7YirXLePJNTr+hKn19jTEvNPY12boVNP4QXn4IAlE6QSNsxMrEgAXYln4tLsJlRrsUWiptvg70t1u62tMKkSLDeKclag8ZWlURsdpURlI6tmtIKTIIKFAqDUjiRpBETu7gFrJBLBZ4YAqUQY+xKRVcMs9s50aa0rYyJIMpGSogCYoGcQeWWwMDbm3J+a1Xy0xZhR3uwWigHa6bwAquNqBZYxpjMZzWbxu2ZnpVYjYhksQvGmCyAr1Qq7bUc7PHUw1Q9XUAWRDjbla7o1e2YX/x/sP1J0LE1ihtABShiF6sgCMYax5VyIos9KwRjrOiK3ZiaEBf0qVzYpyGQhDKGMNK20iU2BFSMWEElVpApQuu7cp1FxLb7QKwRXdkDFNGIdlUhrTIPlzW/W++V5Aza+cDsikJBRWBC2y60KxbFJsqLEB849fyjRjAyMoIxhv7+/hn9va2EXUU4/dd7o1cRziQdLbDaqYJQbZhsxYDM2RBYcRxTKBRmrS06XVqljeppPNWiK45jRkdH6e7uBsiE10y3F+PdO4gf/BFsfRKlymCUbZMlggpsZUoCKzwkUei8wrmXXMWJzBSeVqCscHLmqdR7ZVJfVeCiq9SeEFLcYyQKpY1rKSY25V0MKhYkp1BJYIWbGDuMWSsksKNwJHQtRlEoEyFBznmvBB1rJLB+K62UGyStXKK8yeZNCwZ6DoaB5uU91apgDQ8PN3z0lqf18c92m5CGZs7EIOJ6jm2mqTXeJp/PjzuuVhI0sy2APbNDKprSD9e00pVWuSYSXdXCa7qYkSFKD/0AeeY3KBJrCieAIEEkRKsIiWzhyrbSAptFhcY1+rLQT1t1SkM/lc2fSiMRSGzrLXRJ7Qo7QNmtKrSizLUZtSAS2FagM72LaLtIMTW8SwJom5vlfo3Y3qGtgASCkEeZBCOBOyZjzesimECjygoJxM0wVIhb7aiUkCw6ZV+ezilRy381b968jr4GNNPk3qp0tMBqpxd72npo1iDifWEmW4SV8RNgg/S6urra6rn0dDaVla7JRFcURURRlO1TLboqfV6VmNIohQfvgCd/jaJkRYu2FSMxCSqwkeuiQlSYIEbsKj0TgdY2/FyFKCLEOLO64ARTWsnCzQHE/sM9vhVjGvIKZcRWsdI4hQRU6PKqlLjqk7ViCVjfVmBsjEIgqNhgggBtlN3OPTTGoFX6u2NnXrdmd7S27UZt/yZxKx/FiLVrdR0O85c354l11LoODg4OdvQKQsBmoXkPlqeVSA3sqZ+jUwcRV/usplK9a9X4CE9nMZXXXiNEl5iE6OG7SZ7YBEmEUjZbKlUjgpvll4gVOnEMoUZpF2EQBLYKpMkGJqMhKyMZtaeaBS5fSrAtwsQ9BhgRl5zufFLaKTE3EFqlD6mUraqlcQ2BdqNvlKtauZWG2qViiXZCLLAtQLErBo3BJcnj/mbcJ1uARpDEOJEomIOaX70SkXHXJV/B6ky8wGpRqpPHwzDEGDOuDdYKNLuCVT3eppWqd9Oh1VqWnuayr8/1VEVXeXSU+Jc/Rz31KygMoQPngQrFaRXrs1KBbdepAEhszIGd06eskDKxi2aIUVmOlWu9Bbh5g8oJIvasLEynNTuPFRiMYB8rAbtRAIGxAkq7VYcKG7sQCBgw2qAT7cJFDZIL0HGMyQWoJLErHhNtk9krcrC0ciGkygowKyhxKyKtR0zEoHqPgIE37dNzMp3nrpKOX0FIanKvo0XoK1jtSSt+m6g2sKfJ42kSeSvT6OOr5bOaTvXOV7A8c41K0aWVYnjTvSS/2YQaHbFZT0oj4lbOxta3pHJYgSEB6axd5cbXECRIrLJPAoXzOynbahOl0WJsAndebPZVzkYr2JWD2P8miWsT2uR3pa34QdtjQtLhgulvsf+VEIhtRU0ZQUJxCeyBi3cI7OOpIPPL26BQZYWj834JVripBPdf21a0QaaCEogX/9mMPEe+RTgRbkVpPfu1KR0tsFqJtAWWtgOrk8dbufrRaPHSqqskPZ5WQEQY+dUDlH75IBR2uwV+ChVqEG3bZGK9SdYyZdAqwBjj5v3ZFp4WgxaF0omtJGmVValshQi7wtA6z1Gxciv8sO2+2NjwT+MqW+ncwtjmWaWtOklcaGkiNtcqFjdDUNzfE9hMK5Q1vwug7MpCEyobUhriVj/ivF3axTQoKtPg0+qauNBUSYC8QnrfAPOPnLHnZyKTu6ez8AKrBaiMGgjDkPnz549rgbWywILGHV/qs0pFZm9v76yvkvR49oVGfjEoPPZLhh+6DzWyG6Vja05XgiKx1QGDjS3QIeJElnIxCjrQSGLQLtxTQojFWI+Sq/ZoDTp2OiqwYk10DiWRE1ZOwRiXe2VwFSzn9TIuWDQ1Wrmxhcoot4LQziq0Kxqta13lEruSEOOiHtLWpbEWMKWdET8Ve9jfZ5QVdqnQSuyQaCUGCV0AaaBRJiE5+IMNew4mY7IUd98i9C3CjmK2KyKVI1321gJrdYG1r1T7rGqJzOky2wGo1bTa8XiaSyOf59GnnmT3A3ejXn05M55LEthMKW1bZCrNq8KZwdE2sDNwKeaJFRwoUFqjjEYHxlaLlNhxNcYQY0hwtyeCMgZlhCAXoBPlRIxA4AZAZ2UjQClEKVTiRA82GkJU6p53NwGSBpvGCoVy1Srn5RLXiow0hFZ42RmDthWpsFUtq+PExXEpGwWARqVtTS3I/GUw/w0Ney7qYXBw0AssL7A6j9kQLtUjXaYSNdDqfqJ6z2OlmV9rPWtp9DNNkiTEcTxmyb3HU03huWcY/Pk9yMvbbbUK5apWiZvl5wzcKhi7os+Z15Wyw421VllKOqJsnIEG3DgbMaCVRgcu5kAloMDEiS1CKSGOI+dvcm1Ik6BDjU4MKseeAdGxQoIETOCqWu73ptU2F7eQyi/lYhx0jDWwi84CUNGJ9Vwp57myxirbdlSBXbGoXc6Wss4sqVzxqCA5ZGaqVzBxBWt4eJjXve51M3Ycntag4wXWTCIiWVBoamDv7u6eEy2w6QqsWueip6enoUKjVStGhUIhG5+SUitY0ouuzmX0hecZvvdnjL74O7vYT2lQsfVauWV9ogVlYpfCbtyXLxcmqgyI2ByrdCWhKGsKD1wYqLKVKFHaRTO49loSWz+XMQTdIUFsUEFgYw4CMJH9nSJ2pE0iBiLQFY+tcFU1XTEoWrnqmgZUgjilJc4rhgseRYyNZSgLhFjDeg5UjM3HSrRtM5rEvkec3964mYdIGkUB0v9mmPd7s/Y8pvgKFu7LQB2jcmjfz0cvsGaIam9RpYF9KrR6BWs67Ou5aEfSRQxgZ9NVmvYrl9zHcZztUym4giCYMFjS07pM9/ka3baVXff8jPL251GiCJTGGIOWxAqqUO/xNYmLWkhiTKDQaAwGrWKXeG6Flj0C154LFCIJimCPbypJkNBFMihQoRtSqEBctUqcAV2LIswFdtVgLsAYa0QnNhglSNnYkTaJELkROIQ2RDRwoaM6tB+0SsS2/tK8LLIkUTdSx/1b24AtcUUpo5Rt/yG2XZpWtwwoSfbkbonGHPahBj6be2eyClanCywMdQ57bviRzBgdL7Ca3SJslLeoVasxKVM5j5WesyAImDdvHrlcrqnHBLN/zioXMQDMnz8frXXmvQuCIDsP1RlHcRyPOX4vuuYm5Z2vsevuuyk++1srilwKuiGxWeTKmcAlce01sV4nIxAG7ju+W3GnNVpsm0yhEBNBaEfK2FQFJ0ACydpvpKvu0nZcGgJqxJrdcZUpEyOBaz8SoHWMlsCJOSAnlOPIRkmoACMJJELi5hyKhsAlxmutbZvQiA0ERaGMQcIQlTjhJvb1nf5dxAaVs+1JAuV8Z2ArY8qJQqxLf/5R0H/obDyd3uTuAbzAahr7muFUTauIhcmY6NiqPWed4rOqfA0EQUB3d3fmNZsIpRRBEIyp6KVjklLhVS26KgXXZCNUWoFWPa5mMJX3ajw0zMt33U35yScxYsVUGIYkJM7rbc3fWtxoGxHQrh0otjqE0RgStHYVqMSutrMdOIUOQ8QYWznKxtfE1jMluPajEzhZG9IGmiqNaysqF04a2LajFsTEe55PjQ2oSpwpWWsCpQncfEKj0/iFGJNo+5qOYhtgGtkxNlph9xNxHpSiWmcAACAASURBVC+VtRXTSpwE7iaXi2W9WE5ouoHU9pgUyeGrG/+k7oVaz7mIeIEFtnVbxyxC6tmnReh4gdWMDKdKMdGoDKdWF1i1/r7UZ1UsFjHGNMVnNRVmYxFDZY5XuoghbRFOlzTJvxJjTPaTiq7qESrVlS5P65AURnn1np8x9Nhv0MZgVEJOKdAQRzFBaD1FWb5TZm4HYhdDgEG55YF2NZ22VafQuA8zUCaxFafAjYzR1hSvdehmDlrzuXIeKVFpS9ClJdhfbUVX4OpMKrEtuhAXq+DiGEKroqy80XZHl02lcW1AFRDkAGwmlmCzuUSLrXZJgim52AhsOxEBFWJXNLp0CDvD0NiWJxqlDZLssXKx39ug/+CZeTIrmCymodNzsPwqQk/dVIuJqczKq/f3tCJKKYzZ0yyvbIvlcjnmzZs34z6r2RAVcRwzMjLS9Byv1AifUnOESrmc3e9FV2sQF0fZ/dP72fmbLYRxmVRihDogTiICAlSgMWKs/wq7gs+IDV/QKAhD6zVStoIjSqGVXT2nA1CxjTZQaassBnKBXZGHFSm2FZhknid7u4Y4QXIalbgRM0rc6kBbDQNl0+JVjBJnZHerA62ny63iEyew0vgGo+y8wDQM1GgIBWVs7ANK2wiJREhyzqCPJkkMYFBlEJfltSf5XVnhJcYa5pUTmEqTvGHtbDy9EzI0NMTAwMBsH4ZnhvECqwFUmrabJSba5cOwui3WbJ9VqzCVv7t6oULqW2vEczvZ3LrK9mK16KrVXvQ0jvR8JqWI137+EK/+8lcwWiQnQjnU5HSA1glxkhAo5YYdixNX7r9JhFZWzIhKUEYjyq4cRItdMIhGSWKn/mlrApfQiRstNqk9VDbSQOyqPgkD660ScSJpT+YUgfVLqT3xVmBsy9AY0EGARHa1oRhxhnSskErExixIaH+XDmzf0rXzbMtHINEondiqmYuPEK1ctcvYzqAKEO1am1qQOLG7R2CUQGSrYqG25n2d08j+b4eeRbPyfPug0Ynxqwg7kH35QKk0sDdbTLR6ixDs+di1a9eUs72azUycs8p2IDCtv7vZK0IrRVfl76zl6UrxcRGNQ0QwScIr9zzA7s2/pDQySs7FIcQ6IK8gNjE6MYRakWhFqDRCgkkSVBiQqBilQ8TErkplxYnOAjtdlcm5vbVO3IeYNahrtIu9UkgSkUYhqMBFGWRtwACJjV2lqA0iCpUkNtxTXIuQ2PqvAvehp9wYr6wvZ5wSC2xbUtJVim6UTjoQWsiUm4hdzSiBsWnvgakYV6icmd6NwsEa+tP2oCjBGFvJiyMbP59EOYoHfQBdKMzKYpBa7+lSqUSpVPICy9TX7hO/irCzqDawz4Rpu1UFVho/EEURItK01mgrUlm5bJe/eyLRVennqhUX4UXX9Nm56VGGHv4lpdECQSLktSISIReEhGKIgJxWICExMXk0SRKhg9AKHwOBsisJVahs5ch130SJNXarxGZUJQoCjRFnjldOhOjADlHWglKhvV0Z6+9yJnpbVEpXHLrhzEpcVcz9MUkCudBWvkRsm067mYXiVh9qN28QQUXpnEJrUCcSCJ1Xy/m+0K5fGGDzsJxItN4wg00dtX4vpZOK46t4HQfWt4bL5TIHvoP8/CWzugK3VkRDV1cX3d3dDf9dntbGC6xpkBrYR0dHZ2UIcauNy6n0WaUf2H19fbN8VONp9DmrjpuYbvRGq2WZVa5cnCguolaly8dF1ObVzVvYed/DFF7biZiEnq4cEti5f11aEbncqrxoEkkIBLRSRAh5pW1VS9l2XhKnq//swGaIUYkgAbYYpQKUcQWfJHYZVmnLzw17DtKByWJ9WYgVZQEgEUJoR9CIi3DQaSvPvm9E0nZ22irEmubd61iUcUGnGhsS6gR46sNSGnJuVWDqyRLIJkenVS0CVBzbTC6jbP6VM/ELASRxFtUgOe1M7hqVJKAFrfPIsjPI5/PZc1FZrd2b6GrEl4da15rBwcGON7iDfR3Vs4qwrpWHLULHC6yptnJmwsC+N1pFYNWKoIjjeFw6+WzTjBWipVKJQqFQVxu0nQTIRHERk2V0tVNcRDN47Vf/x8v3bcK89hoxgDHkdEAsyrYBA00EBEGIwlA2CV2hJjZCqEAZIdaKUIUkkqBFMIG1tqderCBQ1rMkgl1F6M6/kizHymiNti52Gx4qVqxJouxqO3Gr+4xBhSFiEtsydKvyEJcWb1wsAsoGgxqbRWUjFFx8AmkqfM5FPwQ2bDRwS/10bE32rmhlhZSy1aw9QwndnRVJ7Ol2uBiGxOVeifV7Sex8XwmIsnN35MBjoGfhmOek1grcZoquWl+eUoHVSe+Fmkh9qwh9TMMcJooiisXirK6GaxWq4wcqK3hJkrSE+KumUaK00e3AdrzYTjWjqzouIv3AasXXRyN47fHfsv1/HqL86g4bMWVTEVBaERlDj9JIoEiMkAMiDIFSBBqi2BAqiBFCZcMNYkkIlc22CpUmMTFGBRDamIQAG+EAyrX8sF6n2AkkEgwB2sRIzrbZRGsUCWLsSru0GpUa2LPbjVtlKKE1qifGthfTxHSDM7QrFw4fODuVccOlE5R2GV1KrEJLW4EILunUaau056lcS9DerlyquyTWK5YOLhSRdBMn+twTEAAqjyydWmr7TIsuH9HQubS2YWQGmOhNkiQJw8PDDA0NISLMmzdv1sXVbFawoihicHCQQqFALpdjv/32G5Np1Y6CYSoYY7LXgVKK+fPn09fX15Dq5Vw4Z+mHVTryqK+vj97eXrq7u7MPsSiKGB0dJY7jrPpZLpfHfYi1G4PPbOX/rl3Pc7f8mPjVVxFsAnoOhVEgiSKnFFGUgFEEgSZS0KVC6zcyQhjkMFqRCwKM1ohAqAISgYCA2IgVLkqhjcaIJjGgdOhW2aWGdoUETqhIYCtYWkHZZVYlcbaCyxaMxI6UMYKowLb2nGld0IiJrIDJ0tFde0cEkcAVFWwVTcB5qNzqRdFWWKWVsmzGoFNHxoCJ7f/H7DG0G9tOFJSVkUpVtJWs+V2JoIzO0tvtLEKFLFwB3fvX/VxWvo67u7vp6+ujr6+P7u5u8vk8WuusSl8sFhkZGclmikZRlH3BrFXBSlcQ1vt+/+xnP8vv/d7vobXmf//3f7PbTzjhBN7whjewYsUKVqxYwde//vXsvmKxyEc+8hGWLl3Km970JtavX5/dJyJ8+tOf5sgjj2TZsmWsW7euruOaLiK67p/JGBkZ4ZJLLuH9738/CxYsQGvNDTfcMG67s88+e4xATn+WL19e83Gvu+46li9fTk9PD8uWLeMb3/hGze12797Neeedx6JFi+jv72fVqlVs3rwZ8BWscRhjMp9Vq6WOz4bAmuqon7k0KxH2+O0amT7fqgsVGk164aqOixgdHc2y0to5LmLkxR387o772PXsdroDjRZFpCCvNEjijOyaWGsiEnqDHLGKMQbyCOVQyLkk8kRiutCU4oS81iRgF+MFEEcRQWi3C4BErPQwqck8BJQVYCSxCx9NTeJpurkbcyPaFokga7nYlqBtsykduAHJbpVhNv3ZHo9dWZhWuVxLUZwJXpsKX5UVUkq51mTaBsxKTzrbJjO7Jza7ykY54DqPLt4B4/xj9vhtFpfNz7JxW4IK88gbG5/aPlGla7I2eUoURezcuZP9999/nytYa9as4Qtf+AJ/8Ad/MO74vv7/s/fuwZaW1bnvb4z3/ebqK81FUTDSpLZ08LhNBAPGrXvLZp8TIgYTqhAKE2MC0ahRUymvldLShDJlLJPSogCjx5SXREUlHM1mq4lBvCSo3AxIvBEFjKCCTdO9+rLm975jnD/G+81e3XQ33avXWr0a1qC6mp7Xb841L88a4xm/593v5pxzznnIdd75zneyYsUKvve973HnnXfyjGc8gzPPPJOjjjqKD3/4w3z729/mjjvu4IEHHuCUU07hzDPP5MlPfvKcj3F/aqFAo/fffz+XXHIJ69ev52lPexrXXXfdXi+7YsUK3v/+9+/yM9sTn+yv//qvefnLX84LXvACXvOa1/DlL3+ZV7/61Wzfvp3Xve51O4/NnbPPPpvbbruN17/+9RxzzDFcfvnlnHHGGdx8883LAmuofY2/lkotpsByd7Zv3z6JdllKQvNAai7P2Xg8Ztu2bYfUb/dIqt03F1euXLnfuIilJLq23v8A937ueh74/t14X+k0YxbKIqcEVKw6U5IoVFycDqGK0UnCJMZPI2Ds0BHTsplaGeVE8RojRq+kApIz1Z0uxQZhFg/9odpETca9RlcppbbxF/4p1/BSRROqdcFaOHSc3wRLOwazGhgIHyJ2dgqaEFuD16uN6yzo6XFlwdWbiT3htUCKjcWhSyaD/0qagkpEJ2voXnltz/LA04KW7Bxe+eq4NpSDNht/M977safD1OIgEB7OmzgejzEzZmZmeMUrXsGXvvQlNmzYQK2V97///Tz96U/nKU95ygHhfAZhtafPsdlw59l15ZVX8jd/8zcAnHjiiZxxxhlcffXVXHTRRXz84x/nJS95CQBHHXUUF1xwAR/96Ef5sz/7s/0+pqVUxx9/PD/+8Y859thjuemmmzjttNP2etmcMxdeeOE+b2/Hjh286U1v4pxzzuHKK68E4OKLL6bWyiWXXMJLX/rSiSj7xCc+wfXXX89VV13FueeeC4Qg3rBhA295y1uWR4QQX6gPPvgg27ZtYzQaPWT8tVRqMQTWIDQ3bdrEjh07WLlyJevWrXtYM/cjoTtTa2XLli1MT0+jqvM6DlyuXWsQXF3XMTU1xapVq1i9ejUrV65kamoKVZ3Q6GePZHbs2LHLSGYxasfGzXzvo5/nW5dfxf3fvgufcTrJFK+YVbKClYqZoK7MUNp4zKgYnQszHuRzFaU3o7MgKwgJzUKpJUDnmsiaGvC8bRI2lEJBUQV3izGZBJwU9Z2dIo8R29BREm8eJmsep1pj5FabH6rW1qESnBwjOQ1GltO6XLTOg7QuRBvZ4doEpjTgZ7z/o/EUxnWv3jYLB4XV3ksTY3tDObi0J2Qwxw+XgcZlAOlwzyHujBBuaQp+4dxFeR3srQbRNWwvjkYjVq9ezRvf+Ebe/OY38/jHP5577rmHl7zkJZxyyimsXbuW008/fcLOO5h6wxvewC/90i9x4YUX8oMf/GBy+t1338369esn/z7xxBO5++67H/a8hSz3nZuEB/Zn37fbdR3HHrv/YFkzY8uWLXs9/wtf+AIbN27kFa94xS6n/+Ef/iHT09Ncc801k9OuuuoqHv/4x0/EFcBjHvMYzj//fD71qU8td7DcnenpaXLOrFmz5oDW7Q9FLeSXymwj9+CpOVDP2VITWPsjSh+tYdRLrfaFi9gXo2uhcBEzD27lzs99lQe/dSdWDMcYaZj1e4xOMqoWgkkCwGnuJM1ULyRV0MoOq6zMmR1WyQIdQhEjm4ahPSuelFIrakZvMFKhWCUD3sZ2iFCrTLpcWBDSsyZqLaSkOIWJ5ymFMBKioyVNPIUB3TBJO7tWNcZtSjSTwk7vzRCvtHU9dnaYpJnfpU3+mkhyp3oiJ21e9ib+2rhyovwmrTMaFiK1ceTQ1RoQDrSwaaDU0F9NrLkIHPcMmFozLz/vg63ZFHcR4bTTTuO0007jgQce4KlPfSp/+qd/yje+8Q1uuukmvv/977Ny5cqDur+//du/5QlPiLzFyy67jF//9V/n9ttvP+jHsVDlzBHTwPx9Dm/bto0jjjiCbdu2cdRRR3HhhRfyF3/xF7vghQb/1NOf/vRdrvv0pz8dVeWWW27hhS984eSyp5566kPu5/TTT+d973vfssBSVY488sjDYqV8oY6v1joxHs+VSL/Un7u91exx4EKHUT8SunyLXfvD6JpvoGS/Y4Y7P/tV7rvlP1AqtRmjprJSakEROlUKhU46OiGibkqEGtdaGWlmu43pUKZUmXFnRQokQ3Uhe1Dcu1FHb4WRKNZlpBTEneIem4TiZITiTieOiYT0cUVT6KhSHNVEbWZ30fZc1DC9m7dYneE0BaQLMrtrYA9cEalY+9vJMc7ziO+RFlcjScFqM9TPMq6L7lwSrALJsNIyElMTS7WhJXI78Ek3y5uwal4sCyTDJKdHW6fLa3zZVg+hmKbwX/iNg3h1LU5t2bKF448/njVr1vDsZz/7IV6qudYgriC6K6997Wt54IEHOOqoo1i/fj133XUXj3vc4wC48847OeusswA44YQTuOuuu3jGM54xOe+EE06Yl2NaynX88cfz+te/nlNPPRUz47Of/SyXX345t956K9ddd91kUnHvvfeSUuIxj9kV+dF1Hccccwz33HPP5LR7772X5zznOQ+5r+OOOw5YNrkDHDYr5PM9IpztszrYzs1SFQ97e852N+8f6g3R5dr/2l9cxIEyumpf+OE/3sh/fv07SCnQulNTKYMIxcZ0ogga3SWN7bs6dKHaYK8zoUplSsOY3rvTOYyrRlROMkoBzQkbCO/mrBKhF0F1EBeOilCqkVOMEbusFIHOleKF5Bpkd5jldWrvRbGW69dOy42GEO56PA0+rIZVIINbUNHxFubsjaBOY2q193r1+PYwD7aWhLcrtgmHlGlCiFmY5t0rkppQm4Cxgt4e2T86/IDj9pMEekIJkaUySeNxFH/Cf4PR0gEbL2YOYa2Vn/3sZ5PR2DCqOuqo2KQ877zzeM973sPpp5/OD37wA774xS9yxRVXAOERet/73sd5553Hpk2buPLKK3cZey1UuQm2ACb3/a23ve1tu/z7/PPP56STTuJNb3oTn/zkJzn//AgI3759+y6w2tm1YsWKXUa727dvZ2pqao+Xc/dlgQWHFn9wIDVfx7k7OHU+OzdL/Xnc3by/Zs0auq47bDtwyxW1p42vYbS4L0ZXSgkB7vnS7fzw67dTp3eQk1LF0FrIkij0ZFNEEgUj0bpKVskS+IXqEbLs7pjEct6O6kypIJqoVDpxioXxvbjhEgHF4spIhRm32BY0p1NlbIWRBkfKqqMp0Vcna3S0sgqGkJUQeUBVJTXRlFAMa74tn2CpIsdPY3tw4nQfPFQQRvkAiIoOBPfarlMbm8qhxOMN77q1kWQzq5dw8XuVNmYUROIXWaG2LMPwoGGVnSnShIJqJv3gevnEJ0bsUUKagpN/fVFeWwda8y2wXvayl3HNNdfwk5/8hLPOOou1a9fyb//2bzzvec9jPB4jIjz2sY/l05/+9OQ6r3vd67jooot40pOeRM6Zyy67jKOPPhqAF73oRdx4442cdNJJqCqvfe1recpTnjLn49vf2h/kwt6ut1D1x3/8x7z5zW/m85///ERgrVy5cpct59k1+JKHWrly5R4B20PTYllgHUY1HwJrdrzNfIJTl7pAGTITF2scuFyHvoYtxKGGzcVBcNW+8IPrbuWeG79Dv2kzXc7QkAvZnZwypRpaFU2CJSeZomKMBTpLkBxzyGJUc0YiGFC8BCQUZ0SMvooZOUHR5sPyIdzZqG1Tr3oIsDHOqMuU0pNVqQgjIjc5IOpOqQErLdUQCdGl4tRmXYpUHMFqhZywWlFSMLhEEAuhExiHvHM014NnAvMAIQJzkN5VNeCihFANAZSYCJ/m1/ImXHEPYWatIzUJfiY6XsP7z2Z1sCqQWmdrAsqq8cQN3vgT/jt0qxbmhTPH2ttn88FiGt7znvfs8fQbbrhhr9dZtWoVH/vYx/Z4nqpy6aWXcumll875mBaqPv3D+/mHH/5sl9O29GUvlz74WrFiBccccwwbN26cnHbcccdRa+X+++/fZUzY9z0/+9nPOP7443e57L333vuQ2x1OWxZYh2HNhTW1e37eXHxW+6qlPCIctkYONY1/9+focOmcPlJqGAuKCPdc/x3u+sptzGzeSqqVqdFKivQxQis9Yzdq1eYhUvoKaoIlw4qyIkX3SGvBxSkesThjC/p6J5mZUuimBBNFvKDquAVItKcycoKf5Ylq4d8SnHBAKePqjDRhAh1OX42sQhUJzlbtcdo4z0Cyt3DlpnOsmdC1iSkRvI+8QknSjOWtuzRgr5xov7ng7TxNqUXT0NhWESKNeRsLMgGnioBYICu8DpE+7XVvLSOxtpO0sbQGc7taHL8GmHUyNrTGxGqEd7o1sOG5h+Q1tK9azBHh4VjDFuG+6pyfeyzn/Nxjdzntmw9M8xtfuG1Bjml6epr777+fxz52530+7WlPw9258cYb+bVf+7XJ6TfccANmxtOe9rRdLvuVr3zlIbf71a9+lVWrVi1jGmDpd1+GmstxDiOxTZs20fc9q1at4ogjjphXcbVUa/DlDATxNWvWLHutHuX1nzd+j6++4+/53v/5Kts3byMj5C5jCiNJTI0yqUtMrejoVBsxQPBamXGjVnAK28Zj8Ipp+Is0SRNZMV50HMlCbbyr2qjkRticMsK4VrJFYyZLdK80ddRmKE8qlGYc711IohR3RhIRO50kzCvZI58wSO+QRfBqKOHjSg1zkKXDUw7hVNqI0sINNdDXHcGa9wraONHaeEe0/T94qU2c7aSq40Gidyw6YgPyoW1AAqCKNURDIB8CG+EIjZzKhALvvhMnMZjdJcH6Z0K3YtFfO3Mpd2fLli17hFk+2spbFuEB/5mHLMKZmRmmp6cfcvrA/nruc3cK9jPPPJOjjz564lkb6oorrmD16tU873nPm5x23nnn8ZOf/IS///u/n5x2//3388lPfpLnP//5yx2sw6kOhJa++0hsoYGZS6mDNXjMtm3bFlweVdatW3fYCOnlmv/6yb//kO//n5vZcv9GgjSuZAkqugNqsYlnZmQUMaFmZ4XHJp+QWKmCSUEcuiTM9DvovKNKjxSjS5nSO5Kg1zCXJxV2lMIoGj6TIOcsSkqRKZgJk3sWobeeTKKIMwX0qojV8ESlECalxu2GH0zo3UiqIcYUSo1uk3mwtGqNTlapJUzmNcznWq2FORPeqYaamHSd2hJfPF++s3sFQX5v+AUh4ZSd9HcSEw97JcaL7rPyA2USRShJZnXHHMHiQVSfkNyDkVWhE+hWwpPPXvwX0H7U3jpY09PTy1mEC1yXXXYZmzZt4kc/+hEAn/70p/nhD38IwKtf/Wo2btzIKaecwoUXXsjJJ58MwGc/+1k+85nPcPbZZ/P85z9/clsrVqzgkksu4ZWvfCXnn38+Z511Fl/60pf4yEc+wp//+Z9z5JFHTi573nnn8a53vYvf+73f4/bbb+cxj3kMl19+OWbGW9/61mWBdTjV/oqY2T6rxd6QO9QCa3eP2XBMy+Lq0Vkb/+PHfPszNzH9n/eh6pjHZl1ujCYkkaxg6gEFTYFZwGGkmWKFrELKYTAfpakJ9XwqK9WMJAlrKAVxg1LoUmZM0EQ1hf8qJY2NQhH6hl/AhephRAfIHnE5gX5wsgRZIcaPRqdCxRihlIGgjoKFDzyZ4hKeLDdrnKombhoDKwQlYTJv3QERncThNPcWwaEayO7eeFRhRheJkZ8qmPngP590nHZ2HWZBTrUdZOuwhahSJHmY3m1QiMOmIkQgtEyI8Jz4LEh73vBaqrXcwWrlc+xG7cd13vnOd05gqSLC1VdfzdVXXw2Eqf/II4/knHPO4fOf/zwf+tCHqLXypCc9ibe//e285jWvecjtvfzlL2c0GvGXf/mX/MM//ANPfOITede73sWrXvWqXS6nqnzmM5/hda97HZdeeinbt2/n9NNP50Mf+hAnnXTSssCCw29EuDcRMwTpzszMLPqG3KF+Dnd/7IPHbOvWrbuAKQ9lLaUu3yO9HvzxJr756a8y/f2fBmKpASs7kRjnSaXz8OeVtnGXRRhXQ2qMC8dW6dqmnlkJ8VUCyRB08iC6G8YohVldVVFZyYyNmZLMuFQSRvFKKc4oCzNmjLJQCDZWjzSKe9iflIJ7+KOKh6V8bCXYWzXGkGOcLh4SI6AncA/VjYxTDToN2rxKdK20CRmhGf5FkQGZ0LAQ4hb4BgcXRwp4csRS62I5mmIUiCRcvHGxtCEUpG0U0mRdxT3FFqLHxqAoQPC12lojQLv95k3UGBGKpIZsALrV8OSl570aak8drFor09PTywILJmT2uVzv4Wo2xX5v9cEPfvCA7vfiiy/m4osvftjLrVu3jve+9728973vfch5ywLrMKq9fUEvlRzFQ2Ha3n0cuBQzJJdr8WrzjzfxnX+8hZ9+6+6GIRC0Ax8XVDNVDCvOKCmIkMRRSWDQp9gCdEmYhBgzj+5MlkRfK6Pmg0oanihzaziEQibFNMuNFdoxLj2jrHgSOgOTMLkrMC5GEmFr7ZnKytiNUUr0InQkKs1L5TFQSy0+J+UUnm8CzaACRZTkTiVEXvHYDOzdYpRnFRGnmoAY2t4b0mjo4jH+Sy6YeHjcveUXDm8jtwm2Kgz0BKDUGpjUBi6oNDVLeLKGjEINUSrNiybRFpt0u+KQGiOrAy+OpuEyrQP2X/4HpKX7lbWnTvkQu7Vq1dLaeFyuxaml+2pdxDqcv4xnx9s82oKJSyls3bp1Eu2zatWqPT725Y7RI7+m79/C7dfczI+/dRepxBe5YFScztJENCVJaOcxliO+90utwcRyqNXRJAhCXyqjLmFWKKJ0KQKZO1XcLFBPySlWGHWZvla6wb7kIUBMhRFKVWEkUKSSNKPmwaCqSl8cVWE8rmgKHlZOEluEOTF2j25bErIZpkJ2oUj8bQ6uirVxphHir0p4tEyFhFAlbqeItiicgjpYo8LHdM+oraskFmM8GUCPHpt9Eb/ThJEZLq27JeC9NeElSGriCm/eK21rirKTf6XNxE6wvkS15T4L3nIORSWAok/+fxb/hXWAtacNwrVr1z5qPpP3VdHBmgsH6/D9fl4WWIdRze5g7U4iP+KIIw55juJidbBmjwMfDjmxFMXzsuCbv9q+eRu3fupG7r39LhgXOk14ii9na94lLz2eM8msdXIC0jnk7+XWcXEga3ShCBm7ewAAIABJREFUvBpJBfNCktRi8sJv1de4H5HAeY7U6YuRRSjqdIS4wQR1pyYnm1MEMrHpl5JQ3eM9qyE58BrhyqoR8ExlXMNU3zskc4omOjd6YCpFPE7yEHtZU7C2MCqgSagWI70ioFbpDVRqSwgUvEqwvCqotvaUFEKCaTPK18gaJDpKASFtiYDDKI9mZE+xsegY4il8YCkM89KeZKGGAFOdUOTdm/hSCahqE2m055GTnoPo0t7+3dP7evPmzaxdu3ZJfg4tdpnPjeRuywJruRajhjfpzMwMfd+jqksqmHihBdbsUSgETG9qampJPPb9rd2PddmAP7cqM2Nu/fQt3HXDHRQbk5wYcaUwUgvKCEAq1ZXssbEW2cIC5rhWOlGKBOU8ofRS6SyRtSEuPYKZOw1fEkAmY15JGgIGVbIa5kbnygyVKRF2FEijhNQYvalBMSdlpbfKqBnXV0h4rFaQ6VNwOCNsJkZ+yZw+OWYejK7WnZupgUhQGTxOA88qhIuZIDqQ2uM5sRxdJZNKh1Al+J/GgGIIFld8qVkTfuGv8twM796ib8xBY5Rog5G+xmtZu0A6wHDjggePNHxXePOxKUIN/ALeulfavF0WY8qVa5Ff+J+L9+KaY+3pvbzMwHp017LAYml2OXavQVxAjAUfbV6j/R0H7l7LMM9HVu2Y3sHt19zKD2+5A6l9m1oFEV2TYQ3S6Tg9Tq7KKENtkM/URlnVKlM5UUqIiGBODdE0heJheu+LkxPUaqREGLMltVBnJym4CLU4uVN6c6aS0NfYSCxujHKiViUTockodB5k9U6EYtC1zljOUKrGdSl0KfxZKzQx4z1T3RTj0tPpiFL6MMfLGFLCrJKqUjNkp8XzDF2uML5nh+Kx0Via8KqFIKe7gER0j4tHF8vbxiAgNTCooFC8gU3bdVv8oGsbH0p0qLAWpSNEJ8rrTiN7i8txUkNBNDEmFS+KNBwWJz0HXeLdq6H2NiJ8tHxO77MWcItwqdaywDoMarbPCph4rZZaLYSYWWgC/XIdHrV9y3Zu+9+3cPctd4GV6H44jHIYqN0Mz46axhd6hikXDKVYIXl4gqqFsT2lzLgvTKVM8Z4qSvYcIzUEFae3JryqMeraOCtMW1QNo3sFOg9flAMJp1bInpixnhHaul2J6kIWwYqDGKbQOUGWcg38k1l0zyzI8NU8tgTNmEod1Qqj1OHu5KkRZk6WnYHJZjVSZTDA6Af6uYaRvCKQQEUptZJToqbgwRtBYY+QaDD3aG95+KiENiYUQBzz1LIMpSkox2ttCTcOqcb9WmwmxpZiszlIuymziV8tRoIQCW4NGTG1lnTy/1jkV9vcak8drGFEuFwLu0W4VGtZYC3hqrWyffv2XcTF9PT0kv5taL4E1nyNA5daB2upHc9SrzLuue2z/8Z/fPUO6o4eamyXmcUmoBfH1UliCBmRHkHRKhSCNh6dEaNqbAlWF8RrwDkpqGeyxJZfp9BbBEFjJWJr8sCmkpYnGFIDcZIH8FNl6GgJIhadHxOQFKiDWFpso0Ghd2dKNXIJRSmlkrNgVfDIm8FcduIU1AM3kQLwOTSOYsMw01s8HgFyu/2OjiKOmmNlBjTjEgJs3EjzpRRQqBoDSXdrZPdYAFDae1pjvErrPtHCohsQC9JgZG/dq6xxvR7IaadPi+bTskGopegKAlRHMjt9W+bw5DOa/2vp1/KIcLl2r2WBxdIbEQ7xNkMi92yf1VI71tk1X8f2aN6MXK4oq8Ztn7+N737x25QdPSklRIPV5EDXwLmenU4FsUyt4UfqFCqGQETXBE+U7E4vTifRwTGFXFLDJwgoAfNMgksluaBpAGmGcb3TTLGehKAenbMk0f/JqhSvZBJWS4jpAEoBhkpGaIZ0EsUcBXoqSWBcjZFqdKtUKDKEQnuM9tRia1AS6iVM8kmZafDSavHYghivFAuxZQoprWhk9toEZ43xnYcXiupUDcGmTYi5K7UIKVWsWFDeIR6PCyRrz1sKBEPb+qM4DeMVCToMKAgPQWZAbQiJZmyLrUNpx9iYXKuPJP3Cfz8Er775q4MNen4k1XIH61FcS6GzMDCdtm/fjpmxYsUKVq5cuYtwWQrHubcagpXnWruPA+djM/JA4oUWswYRCZBzDkxASkvqGBei9ufxffML3+S7136XLdObSZ4ZJcHqOCKfdIqcSxi+cdSVMjY0BZpBVekpZOKXkd4rOYAMVKsNYwBeIaXY8EsGJmGoToTAGSExv6sanqDGgZqpPaMWU5MbaDM1v1KxSkoxSkwpUfrKSEPIdS17cErD8D7J2tPgTiFCMgdzMsQoE6dK/O3B7mxk9fZYZcBTGTUl1Gv4mrxG+0lC5Ejb1CsNjFrF6XKi4KjVlifoUA0Xo3qPuFOTxggPjV9w3Brnirhjs/BrDQb3MF9F28tSOw6igyfRElMGhEM8fKxhGNokcxBhbsDJZxxW74flDta+KzqjcxBY838oi1bLAmuJ1O4RL3uLt1nKAmuu5e7s2LGD7du3P6Rj90irQUTv2LFj0pUbj8eT80WElNJEcKnqI/J52L3cnW994dt860vfYuuDW1F3upRI1fACEL4pUmE8Dip5ElAMS4IOXh9zkrYNNmkm9FgrbNt5MSYkO4aGqNHYg6Mt3GWUSiVZoie27TQJZt7gooR3yyzQCC6o18l7U1GqB5OquDMynUBMx1YZ5RSwUhmic1omoWqLzUkR6SMh5KY003uN+BwJgnvvzkgT/cTfFV22QmAnguQeAdJZhN4jtLqIkYiuXFKaNyq6ayYFJUSjeAQxkxTvHUs1ukoZpDb6eiXsXV0ju1OhGNK1LcEGSiUR3Cu36GJgDfWg6OAfG1hZHoNE1hxNd/KzDsVLcU61txzCLVu27JJdt1yPrloWWIe4DtTEvZQF1lyOre97tm7duiiB1IeyBk+Zt1HJ6tWrJx2/4XmrtWJm1Fp3ifeZLbaGLtcjSXR95/o7uPWzt7J10+YGmjRyVtQkxI8AtY2O4juflOI1UkrPKI8ahyrsPrWNxtSdYjBKCRMLHhUpsA5phLo1Envk+2VNSONnKUrtKzknKj14DssQimilWEVIzJQxnXbAwMWyiRm+jCtdZ1Rti3YCWTOlRpyNCXRAdSeJ0LcQ5+rGiDC8dznicbLA2JhkEeak9G6TDMBu5yIfzcdO9cYDyzGZSwSFXtp9dB4srrishahK0gKXh+desREBjPA+UA4eo03MQI06JrIMk4c3y2FCYPdQrV4tfFnEAXojzHsLdhZt1xmAD/916WMZ9qe2bNnCE5/4xEN9GEuilkeEj+JabOGye9fmQEzcS1Vgwf4f22wDf86ZNWvWLAgodSmMCGcjJkSEruuYmpqi7/vJMQ7jraHcHTPbRXDNfm5373IdjqL0ztvu5sZPfYMHN24kWY4v73FlNOoQEyQZbXEWbSMmscinq1ZJDlk7egsiueY02YxznKot448KZmTN9G50KTdPkccWnRWyJCrR3ZE2ktOk9F4YSaJ6JTffljioZ1ycqRRG8gT0NTIGzcL/ZUlQSVQHGDprQY23Jmy8dZzcIVMRD8yBqSOumAtJiQ6cDRvrilUQsYj/sUqSIQsxMSaI8iZx3SpKNqNIE5i1kkQo1WNURwKtqCm1idvJ3xbirxLbfQKIxiZmzdZo7iVGgOMwzntxsB0hmIaDT3kyBhSpePN0uUnLIIyRqQiw9mhGG05f5FfjwdW+OljLI8Iod5kTNHRZYC3Xfpe7T/w3c+naLPUO1sPVo20cuG3btl2I89u2bduvxzqMClNKk47mnrpcs0XanjpdS7HuueNerv/kzWy+dyNew1RNi3XRLkfjQyq40HWAEZex6KwYY5Ln+GJWZ0QKUzYx9hKrVKt0XY4xlAMtS7CTwC50Eht+tZQgnVslJ6V6jAYRMAuOVO+VqZQoWsnedEKDk5qEfQmP7lngFZRSC111eoFRUgo1RnPNh2REk6hUJ2uAPTtNAf4EzGvbaIzMwt4sBJ55hD17OzYrZA1waadCX2t4tkRRi42+VI3qDjmyFQHwITonhOXIE33LWKwOqoJVmLTIKBG/YxGmWA0kNSBoaluCXYwVJQkMj9Idn+mRFBmPQ0xhtMAaFZ5w5ou2jcn/+r8W8+U4r7UssJZrdi0LrEWs/fVZ7auWusDa17ENocx7M/Av1DHB4nb99jeAei7Iid27fLO7XGa2i59r6GzN7nIdStH1s3s2cv3Hb+H+H22kAxBpX8M9yRTRCE92ic3AMIJHxh7uE154al/4JqmN3mK8FXBNISUhaQzrFMXU0OqkFN6okWaKFToESQmjnYdHVI5bBMVICmaUhcBRj65YMKIaAd2Caj4Y7lUCczBsKSY3eovHU91RM0wgW/y707iNThoDSxLW6OsBKw3TfVZtEFUYWwnjv0ESgWIBGg3jGYJQRcg4vRFGe2rcp1W6JHEMLq2j1rpZEDBI4jFVieeh1kArFAtflbpgYhFu3bpgNowV+wK5MSmSxHMjGSgxKmybi+LgfYwrJWaU0eVacxQrNpx6aF6gB1F7+3xZFlg7a3lE+CiuhfzimZ2dp6qsWbOGruvmdJ9LWWDBnj9ods9NnIuwPFyq1srWrVsnInrVqlW7PNbZP7/5+DkOwmkQXoPHq9Y6EV2H2s+16acP8pVPfp0f3Ho3nSRkKsUKv0MRYxSOpIiryTEGxB1XQwyyamybpYxKmKEFR1uMzQoSRm1bchLIATe61OHJSBabgGIVkeaB0hSiwCQ6QdKTXCkSnaEi0QmiRmdQ3agO2YJHpY3SnjS6XiNiY3FE/FsgumG5a/8fhvwqSsKCcgC4J1QrBSFrC6H2iI+xFEHO0rYVqY4pqGTcLcaWJMYURiKYaYRXe2UkSqnxfDggmjGrcVt4E3MSHTaEqkQQdC3krBHp40TnSR316K6pBgU/aWAmRFqEjwIWjysSogOeSmNoiaf4W53G05hsI1of25T0PWz4b2zfvv0hSx5LtRs71J5GhO7Oli1bWLdu3aE6rCVVywJruea1dodlzke8zVIWWHvK2Rt4XgcrLA/2mBb6OdvTYx2NRgt6n3uq2X6u2aPF2V2uffm55nO0uOn+ab72qRv5j1vuRqqjhG+pK4JTcBU6iUiUJBEdo56pXkhdiqiWEggAVQcMq9H1IimuMCUZJwKRkziFMGZnDdGWXDHGqHQYinhF1ZsXq8N8TCW6OTaM4TCySpjlk7fo5IRK+KNSdrxGhA7udMQYcZQSvcdtxKiuiZwcnSInhZeMhElFJTbqEgnzEv0pqbGgJ07y6CIlWsyNtm6bG9WFRKICU5pD5LhjNRAR5tHBSwjFoZPYPOxU27/byLTlM0Y+ocTz6u1LTZViRmrdqyREx6oxFpyg3huDWBSGXB2XgfsuaMjhllXo7dS4rKsiyaLLte5oupOfvtfx9+HgOdxbVM5yPTprWWC1mu8v/dnjsPncjjscBNbwJb7Y48BDVbM3IZfiY53t5xpqdz9X3/e7fKEdDCpiy6ZtfOWTX+eOm++OsaYmJFmYx4vhuSBVJp0rryEAowvn5JShN1IyiijaMAZuTtciV8KzA9V7lPBjVSrZgvQe+XuxaddJRK+oOKoNGOoBM5UGyUQayLSBLyttI7FYCBaiW1TFUHM86WQDzzVEVa0xWjNxsgf1fZSC8J4lY80MX62SU8Z9DKL0pdBlxUqM6yoVbVgDBVxCmJkPyIkWbCMCbRBqCFmMHhD39m+luJGJkOnJcydNdKvghOeqE6cQRvoIgJZ20QYJleg4mUccUJmQ2dvWoQvmFUwCweXRfUMNa8iMCI4G2hh24HRFJwu6p5+1yy8lu4+/d3+NLiXP4d4+k6enp5c7WK2WOVjLddC1+zhsobbjlho4c3ZNT08flM9sPmshO1izERuH2+hzdz/X7NHi3lARD+fn2rFthn/51I3c/i/fQ4lJUbbI3ksZKCU6OJbJo9ihU1Oq9c0wbagYUhMu0NfouCCxlaeqYaJWJUnGtEKvuIZISzk1fmd4e6wanYaxO6f4oDYDldhmUmUyZrNqqIIRPK2UNAzsSWMrUFMwqEypUsju1CYMavNjiTb/kivegqEdCbEi0U0SD7BmnJMRh9yF2ZvUyO6SAzHh0GmOY3ShF6Mj4nW0xmafujRB5BNPVzwJBqJt608nP2Pz5gcbkA8WFPniIWSlbVOqN5RDkvCQCVjffFraHo/E48iNvyVEh8tTmxgiJIIbJt4eczj4QRp0VMIQL0c+ltHP/1+7vJ72Nv7em+fwUDLklkeED1/LW4TLNecyM3bs2LHg47ClKqoGYzfEc3EoxoGLVcPod9gIPJBNyKXagdwfVMTe/Fw4XH/Nrdz+L99lPD0OQZGhk4xhjHKYm8dAshwdoRpDI8RIoqTW1RDPiBiiikjGtQUEO1QNErli1DKmyx2W+vY17iFENPxJaoqnMHt3Eh0tdXAJsSTmkf+nOeJzNHhTXSilRhkPrZI0hViw2jpYEa+T8hCNE92sTsI8Lh4do0Rs6iURigHquBjJJbpoKFUqnQcOQVXprQTOAVBNwaciAKnZo5NGCbO5NC+XewjCoL+36BxNO0GoFl2siMJpaKpB9GgKlIV7hEy7B4yhCUKzYH85ISizeHC4CPAq4lTiuVKJeB9pogrxBnyd9TqzFh8UUAnE27boL//fB/Qa3ZPncF+/GBwK0bV9+3ZKKcsjwkdxLQusVnN90832We1rY2y+ailwnWbX7vE+wIJ17ZZCzWZaPZLBqLB3VMTOsWLhX//3Ldz2le9Rto1jRKZhALde6DoPLlTrKHWm4X9OTJhWqtKi8Aoj7ZAWyhxf7oXkwUFwlfBJeUGSoikxrrWNvSreCV1VzAs6jKBc4kvfEskrpkYejNf4TizDgCxoMTtd21dMElBNV4ihoSJueOs0eYngZ3fI6s2v1HhaLhScqebDyioTT1g1Jp0dlQiSVhG8Gkmlddl2QjvjMtEdYzIyLSTJlIHkXmujzDsdHsM7bWHREF2nRnvvmwCbKT2jFJ6zRCAgTKSNKY1huU8lPF8xwI0ywrMVgishlEA3oAjtMblF10qauVlq83e1LUsJh5Ye8zhGJz55zq/RufxiMN/btXuLyVm9evUj9rPwQGvZ5L5cB1SzQ4lHoxGrVq1a8C/bQ4Ed2Fvtjp1YuXIlW7duXRLCb6j5er5mb4LOd07i4VSD6PrGF7/D1//p39i2aQY3J6uGLLGIthERyrjQS9DQU0MZuDjVhBEB7/QKU7kDhNKYTskCzZBSBvUYMQpIF9gGN6HS0+Uwd2eNrcRqQTYv7qQGsDSrJI1xX/JE8UpHoqX2kUiIKuqVggV6wStJYjTXSWT2hcG8kHygWOXgNrWumBGjP7cYYdLyBt0EUQsjuWuMDFNByFQKqTG8RCKj0Ac8gmp7bDBTnVGLvUkenSg1bXE6YR6vTmAZHLos9B4RObV1pPoa4i9GmNF1yhKMqwiHjtM6aF6yEFcigZ/osSb0dnavFDAN4SQiWPNklcbuGsRVM98ER8sLImni13JR8mkP372ay2t0T78YPFw39mC2a/dmcD8c3+cLUcsCa7n2q2ZTyPcn3mY+aykIrL1tzA0fWEtB/M1XzWZaAQdE3N/XbR6udcuXv8MNn7uNB+7bTE6xsScZRJQuZ7yv0aJSCRyBC2ohHkQIEjtOkUC0K0Ithksld207TYgNP204BY1RnVnDBNSeUeqwGl/k3sKauyQUhK75o9SjM2HFo6sGpJQpXppwalmGZkBANt2UJAOKIcCaamEW7xraQckBEk0hODpPVGmdMHc6g17Ck1S8kqWjek9ukTzqimsNfEQbgUY2YTzGLmuY+N0xE7qWPiMtVLp3SEnoa2FKnLFDlkQhngOvdeI9i3Gjt33CoLpHt6yxrhySDvE2FZPgaXUq8fxIGNq1bQYmbz+LrCSzyYZiabmEWMTteNscTBJU+JQCQSGS25gyodnRY45ndMJJC/66fbhu7J62aw9EdO3pPb158+bl8eCjvJYFVqv9pZAPwuJQU8gPxZf0/gI0l5KAOBhBOrtDN18dytkerMPpN9tv3nAHX7z6Rqbv3xodnxQ+Jk2B9Q7+kaO5QxrlXBFEO7yL3D4bF7JGzE2uMfKyxrXKOUOtWBUkB1xzhFD6iiSQ0niV5g0UWgOloNBZ3F9pI8CikEywZKhFUHNk3xAjtyZSIrdQ6JJQKzGWVMdMIYPX1ogikAq1dW0KlS4RfSwXLDlqQtVm+HYhmdC7MSUJL30Q0q2Qu1CLUtrosWVRCjFqdI3f8o3otI1raSgFaWHOYWmqtYTnC6UTa6b96PBVCU5YvMyiM5UExjWCot2sGfKb8PUImU6SQgxJUNwDtq7QHv9gaO9rJbdNRZWKewpvmWhsXTbivGh471xbxmBAvPCBm1WF7hlnLvpreaj92a7d34iqvY0IlztYO+vRaHJ/ZJpH5rkGn9WmTZvYsWMHK1as4MgjjzzoTsZc6lDm6W3ZsoWtW7fSdR3r1q17CI7gkfJBMkTcbN68GTNj7dq1rFmz5hHrtdpX3fHvP+SKt36cv3/vP7Hlga1tIwxShSwg1UnizUhOGK8NVH2CNxDX8CupIAJTXUfXdYy6SCFOOToKtVgAQ/sx5pW+1Bi5VZAsEy9PlcHrBJkYlYkIUtOEku7qLSy6xS+Lk9rHnZiRxLASG3S1toiYsF1TUxtfQXChpImR6CM1rlOY+yPmJZADSnTA8IjQidVHwcmN95QwCwO9aIudaRt40LYBHcYlHvMQ5lzMgxBvIZRUwpPmSSgYND6WNCxF8ta1kxZ7gwwTS9ygEMdYbaC5W6PTD+/fWA4QaX4pz5Ofe6QVRXeqqCA0H5gpFncWpHcCNFpMokvoIRIBXMILpo/7Oaae+F8W8dX88DVs145GI1auXMnq1atZtWoVK1asmCAkSins2LGDbdu2sXXr1on/dDDcD3UwDKw/+qM/4ud//udRVW699dbJ6ffddx/Pfe5z2bBhA7/4i7/Il7/85cl527dv54UvfCEnnXQSJ598MlddddXkPHfnVa96FU960pPYsGEDl1122ZyO62BqwDQc8J9FP9L5q+UOVqu9iYPdfUa7k7kXuxZ7RLg7hX5f49ClML7cW+3vMc3mly30wsJSrh/d+RM++9F/5T/vvI9kSsojcJpIakwkheSCkEgqqMVYTDDclVr71qmo5BzeHKlNoHjcRpfyTgRDhAZGuHAfLRQzpzImWVisu6Rx282cbql1x3A0J6RWipeIcXEQ0+BJTSJoBFJCPHbjqlXyLPhm/DszhDAHRypgnUmje9NpjNEUIlDaQiRlaGiDxNgaKNQFVWv+sDDYqxB+Ko3tQ9VGVRhEVhYGzJVqwgihYxqjuhLI0ugSWYwhk4QvKmm8VmvbDnRvG4AO3RC3Y9E9cyJkudIM7Kok9yamQjB7Csi6tcsUb50+98g61BBbg84EYVzDbxVIBwdr3q2GzpDWpeueMb/eq4Wq3cGme8JFDKdt3bqVv/qrv+I73/kOj3vc41BVHnzwwQNGNbzgBS/gDW94A89+9rN3Of2Nb3wjz3zmM/nMZz7DjTfeyLnnnsudd95JSol3vvOdrFixgu9973vceeedPOMZz+DMM8/kqKOO4sMf/jDf/va3ueOOO3jggQc45ZRTOPPMM3nyk+e2XLBc+1ePvl/J97PMjOnpaTZv3oy7s3bt2iXBOVpMMvnMzAwPPvggMzMzrFy5knXr1i2a12y+an/FUa2VLVu2MD09TUppjx26+Tqe2VE5S02M/vhH9/HBd1/D//sXV/OjO+8jE1/M2UE8IQhZhKwSWX0qkKFSg8wNkd+nwYXKnlBJuCtaE7mR24XGcHIPirs3PlbuwIWcEl1OpJQZ5RWIRkemYNS+x6vRl0KdcXqvYFC8CbrU8AZaqQ1oac3rVNuI0NzCKgZhwEbCXyVt69Gg1ILgrbMVJvqUWhdMUvSdvGUPthGfSmq+rbZ32FpZ4m0MiFPbb+Yi2hhVsVGnhCDDYdzwDObhW4v7ahuLAxW9ibY2cA5cAoMAC/RCalDWRp2gOpBaFI4ofQ0oqolGhI2HV00QUEEtRG626M6pxHF72zYcsiHNopsnreMgbfNRaiO+iwQtXmPLUB//c0z93PqFf0EvQM1GRQybxMDk30cffTT33XcfH/nIR/jCF77AkUceycknn8xv//Zv8+53v3sXdtfe6tnPfjbHH3/8Qz4fPv7xj/Oyl70MgF/+5V/mCU94Al/84hcBuPLKKyfnnXjiiZxxxhlcffXVk+u95CUvAeCoo47iggsu4KMf/ej8PCH7WdZGhHP5s6/aunUrb3nLW3juc5/LMcccg6ryoQ99aJfLuDsf+MAH+I3f+A1OOOEE1qxZw1Of+lTe9ra3MTMz85DbnI33mP3nHe94x0Mu++CDD/LSl76UY489ljVr1nDmmWdyyy23AMsdrF1KRCY8q+3btyMi82JqXohayC/m2SiCA/EeLeUO1t7K3Xf5eT+S+V37qgcf2MxnP3E9/37T95Ghw+NBVa+1MpKMmaEpVEntjZQlmFLVEc+4V5JmKIbmoIuLECwrho6Rk73DNZDhSaLDog0GaqWiKboeAJoNr0YnCjk1tlQfAkOji5CqMG48qTEziCdSTiEMhuxCHzKRhbHXiMTxJmqECIq2GHtWIrOPpIQ4CiBmEkF8iJwOk7g4zfgeJnAa5V3c8EhUxj34VNWc5KlhHgLgmXSgowu91TDaewjaIKFDtJtqIBZk4FQZ6inM8bRtwSTU5ukCpxdhJLQOVRjmMxHeHL8ohvnfXVo2oTazfetQOUAI6NjcDDFWrZISOzuJ0vIXG709uezMJ5RErU6XaZuOcZsrn/m/DsGrfOFqMMB3XccrX/lKXvnKV/KOd7yD7373u5x99tnceOON3HDDDVx33XW8+tWvntN9bNy4kVIKxx577OS09evXc/cvogyjAAAgAElEQVTddwNw9913s379TtF64okn7vO8r33ta3M6jrnWQm0R3n///VxyySWsX7+epz3taVx33XUPucy2bdu46KKLeOYzn8nLX/5yjj32WK6//nre8pa3cO211/LP//zPD7nOr/7qr/I7v/M7u5x2yimn7HZsztlnn81tt93G61//eo455hguv/xyzjjjDG6++eZlgTXUbHjkfMfbzGcNb+SFIpPPRhHMdTtyqQmsvT1fszEbSzHiZjFq65ZtXHPVl7jt6z8gVaXzAdQZHapilVFSfAg9ppm/M4gHgVxTkI+saJieB75UVfoWnoxYfHkP21imDWtQcM+o5hA2Gl/2qXVrzJ2cM6Z9fHHTCOUShqKpnAIzMBEqXeTwlR6jbeel6L4EVkGC71QrnSo1x7itStvmkxCAxXo6ghYf+YQVXLFEA3MGFyvM9gP+QXAVksF4ECpVIubG2uhUExoJziRxvAgSqcqtM+LBqUoawcvxzE5ArOphEtccI1Zp/1VvlPX27xBeTiEQFCSdcLTMQT2wDyE0g3mFtI5qSpRaIzYHY9TEqLTnniSYBUw2D56yNhIMP9ysOCKJUadb+LLUhHT8CXTHPfGQveYXovZmcl+/fj0vfvGLefGLXwzEZ+yj7TNmoev444/nxz/+Mcceeyw33XQTp5122kMuMxqN+Nd//Vd+5Vd+ZXLaxRdfzPr163nrW9/Ktddey5ln7rpwsWHDBl74whfu874/8YlPcP3113PVVVdx7rnnAjHe3bBhA295y1uWR4Sza/v27ZPx0OrVq5ecuFqoGro4Dz74IOPxmFWrVnHEEUccsLg6XD44hvHvli1bEBGOOOIIVq1addgc/3zU1untfPyD/8jb3/RBvvm1/0AlBcVclewJUkZcWMEIKYlOJTbnvJI8wn1VIlzYTfEaENFiHtuFApYihkbCxNPGiuFXESKmRlQRKl5tMkbL0gWQVIWUM1hBLWCa0sZQ0MZQLiGgnOj+qNCljjyKPzpK7XJGX4xSxuEFE6dQ8BJBytK23tQbxFMThRoMKK8RyGwg1eIxNiy6SAp/ExE/4xPhkpplPkZj7tHtQ6x1usK7ZAnwTKkxEuxNSB75fUkz7ho+t/bbv0psTjpKb60zh6N4eLIadb313qgWo9viYTYvxVAbgJ/RcRpGgsWjo2glulkiGuPUFgStxEhRrWEYSox9igjq0JfSxsTRGXSCLi8tK1HMcUmsfNYjq3u1t63g6elpjjjiiF1OO5jvlKOPPpqcMz/96U8np915552ccMIJQHSz7rrrrj2ed8IJJ+z1vMWq1ved0599Vdd1u3T19naZ2eJqqHPPPRd351vf+tYer7djx449jhCHuuqqq3j84x8/EVcAj3nMYzj//PP51Kc+tSywhhIR1q1btyR8Vg9X89nB6vuezZs3s23btsl24MEYu5diFMxwTLOFZN/3rFq1irVr1y46aflQPj8zM2P+v49dx1/8yfu5+V++DTsqXtp8rAQXSqqSeoKYLo40ARPeGgGN7pWZNRK7IV3brdNgIYiBWsaT4T2ohreHIpCkEcgDWaAaJnnzMGPTukmBRXBElb4MnCgDjbGdSsv1q80kD4hFWLIQnKhOEySYyko3ynRpitwShs1ClJR+hr5WxjM9ZgXzRj33hFs8JquGZsKHhASbq4Jo8L2IIw1BomAmlJZJU4nLlFrjtqGNN8PjFHFB7QfUlgaqRCfI2u5ijSwaao0NPKsxGnSP+/TGAwPCx0UK0npqsT8Ybim2GTVThvEfg1AlTOvuVBHwIeswfu7J4zGKEjBUj9BnF0HdJkZ3dcE8xc+hGrndTyXEaDr+BEaPP35hX+RLpDZv3vwQgXWw9YIXvIArrrgCgBtuuIF77rmH5zznOQCcd955vOc97wHgBz/4AV/84hf5zd/8zcn13ve+92FmbNy4kSuvvJILLrhgXo/t4WrANBzon4XENNx7771AiKLd6wMf+ACrV69m5cqVPOUpT9mjZ+2WW27h1FNPfcjpp59+Otu2bVseEc6uoCfboT6Mh635EDGzg4rni0y+lMvM2Lx586JS9/dUh6pLVmvlc9d8hX+59hbGW6FLiU4DPimSSB5ma0FCNKBYrRRNTKWMSw3PVMoxynLDTAM06oaPQzAljc07AYoYI41sQXePLpBUtNSGNIjxHWLgg8iqAQ5NASiNbpOSs1KojERxCXCmNyEFsRxIy/sTBbPKyFMEFbtSmkkeN1RH9N4zkhGGIZ6ojfXUFyelipUmC8TbqLCxq4QQTUpwujzo5zGSI2Jx0hA145gqatZEaWpdnCZShXgcLX9wZ66hkE3oKTH6JPxwAydr2CRstCsy8RRKG/cNZnozSKIUM7oYEJLF24jQUA0PVxaJbUiaT8pj1OcqMCwgEEHRufm7kjRQaRm2AsOEX2ECmK0anTezeG4kKWv++6HjXi1U7a2DtWXLljkLrJe97GVcc801/OQnP+Gss85i7dq1fPe73+Xtb387L3rRi9iwYQNTU1P83d/93aQh8LrXvY6LLrqIJz3pSeScueyyyzj66KMBeNGLXsSNN97ISSedhKry2te+lqc85SkH8agfGfWOd7yDdevW8dznPneX05/1rGdxwQUXcOKJJ3LPPfdw2WWX8Vu/9Vts3ryZP/iDP5hc7t57750I3Nl13HHHAcsm913qcBkRHYzAmp2dCPNDJp+vY1uIGjpXh4K6/3C1WK+3L33ha1x7zU3s2LoD8xSxMw7SBziRNrKSTkk0JmcVVOKXjuIlxFUzfA+qQhCSGqUKOSvmNbhYKdhSuVPcKt7o572PUZHYGpTaQpy9/WYbO3AZxcSQAqqGSwapTUgIxSophfhLSREMyQIWFK5k4U1yD8J8skAp5IYdkGbIzpLaKC8AoWoZTU7SMOJrokE3lb72CMqYRo53QZUISoYIdKZFw+gwIIsgZbcy8T0looHXMXSi2sg1afNqRaTP4NUKmeTN/ySBgJBEpTQWlzT6fHSdErG5OJKWIegetPsUI0VXY0BaJM3hiRLaZXYuqLhGFyw7VLEJMkJSjBRdlGQ1iPKte2cELqNidKZBw7CIDPK2XZqeeCL5sY9flNf8oaj9GRHubw2dqN3r2GOP5XOf+9wez1u1ahUf+9jH9nieqnLppZdy6aWXzul45qOGsfRcrrcQ9ed//udce+21XHHFFQ/5Oc3miwFcdNFFnHrqqfzJn/wJv/u7v8vU1BQQtqLh/2fXihUrogu+MIe+XAtZcxUxs8eBo9HooMeB83ls812z4bDezNVz8ZUdznXD177BJW+6gk9+5Dq2b9uKpBG5JnLz2qRRIBEoxogUnZbaTNxWyd0I8YjyzSIxomthw5DRJK1jE2Z3aYys6j7papgVknaoepjkRZq3KXLxvHl2RMIMXjX4UdIJNeAIDPl5xS3M8A6awJt7qNQQNWaRjVednYZrmmAhRUSMhzuprbiF/8rbqC+aQpGrqMpUzqgqI+nIuUNTxCiLhvdspo4ptVB6o9TwTYknejMcpziIZErznI2rtbic4YPXoyPoLfhYYoyq5EnWX7U6Oa6EtuDpnZ1CQwJE2jpcnRMkehpOQQNLEQHUaWJwdyM6fh5QUSemxIrGyHXYmHRFUmZsjtY2LywlvDGhuujb8109xJgr1PaRUjzGhoKy+tn/czFe9otee/u8O5gO1iOxjDliGh7GgzWXuvLKK3nzm9/M7//+7/PSl770YS+fc+aVr3wlmzZt4qabbpqcvnLlyj16tIa0l+UO1qOgHm3jwForW7duncBha62T7bVDXYsRlfONm2/nmqu/wI9/spGpboqpNApflYcJXFQZpYSPU3RshsBea68JcVIe4a4hqApIFlxAiuG5GZYbLHMQAJjHaM+Dyp6smcD70m42xk6dhrdJJbovgrR4nUAgGE6q0Ukj0QjiQsrN31VjhJiF1tFKUBvywKIrVdzpJGNiqKXAQpggGsysoePiKbYDh982nWFLN8QLAuSMe4mtwJTjfukZaeRvZhWqhyG+WiXYWXFVb8LJJfxs8SXTzkTIXilI25Bs3rMWnhwu+ugwViqJGPclhFID3Dk87lCcjhFBylmFvp8VdC2xnVmBkQbQdDKmFWLdrx1XEaGz8JmpOXhsSjoeFjpv4FWPsWNqZn/D6DTCuDUMahOLcj7xRLrH7tuIfLjWnt7P7r4ssOZQ197/Q6792Q93OW269PN6H//0T//Ei1/8Ys4555yJn21/6olPjM3XjRs3Tk477rjjJj6u2TWc9sj9lp1DLYUv4P2pgdf1cLU742kxshMPZQdrbyHUmzdvPiTHs9j1zVu/xdWf/Bw/u+9BxBMjXYH3jbL+/7P39sG63lV992et3++69zknJ4QmAeWlggrpU1seYgPhEYtCSqtt0akS+aMzaNXWGW1LO3XCYOuMzjB26DR1UiAgjBSIYAEJyJtUalUKPoDgy/NYKSrI20MCGDDJIefk7Pv6rfX88V3Xvc852QnJyTk5+4S9hkzI3ve+7+t+vb73Wt/1+brTbCJzFj9pO5kcxjyzWh0g50EQrLyRLjEU81rdo6YWuGVozqVtfzzKSIQ6X9GSaSThMl73CW0HeiEZ5qiuSOEBEA+qjGASWfJyS/541vp7w9tMhhWI3cmIze1EiY0I23RSmotP1cxqRGmbSBdriUeT+JJVW1twMZjaxPBRo8alczYES9UunBAUZaKauvL12nAZ+SMUkDzPuDvHY5uextqK3B7GShhQ0pSF6L5MaXX8sztTUhR5Gd09JJR86clFZ/JgNujZNgZ3SqwJq9HBkGDNeuwIhrRP3ZbI+iLRC77VqeWBosvPrs5YJvR6PqI6fovQkv1NXcvZFD49Cmaabg/a7tWJtduI8L4S3B/UdS8M68+45Bt4xiUnbzf+2R1/yY//r7tyqk6nPvShD/H93//9XHnllbzxjW+8Tz7cT3ziEwA87GEP2/zs8ssv5/3vf/9dLvvBD36QQ4cO7Qus87HujYhZr9fccccd54TpdS4E1on393xiWp2JY/zkJ/8/fuk1N3LrLUeYZ2i+otkkJ1A6Fk1ZdJ4YvUwNMqe3tmKsRUBv2UlzGLO4SK2Dl0hCXCzLAX1pwCQs0SzAyiZoGiVZ10jA0rSKZhIMzaAzMVtoFGnLppoJuWAaoTWSMFcny4NsDR8DwhXi7OoEmRnN2fFFpbbslEUYNY4z1lGsp0yYvSJgKhC5mje9dXWcFio58htZalkcFjCpkb1BVBcsy1ifErKZGpuqW9R1H0eoa0eyTQVcL4HRwIxGk5Hgs7IGxS2VsT7dWcdgVY9PbylxZoNh8qI58pPZsPKFUdyvMtYveIj6GBgWtJFkaxtA6jyCydUBdISc8CFMQ7gXQkKkegnChBpXYvKWTaZ8REUeGluP+UZWJ5yUHmy1PyK8d3VvqOx393dnov73//7fPOtZz+KbvumbeMc73rGrdwoELj11q/DIkSNcd911XHrppVxxxRWbn1999dXceOONvOUtb+H7v//7N3//5je/me/93u/dF1gn1vlwQoZ7FlhjDI4ePcp6vab3zuHDhx/QceAD/RieOP7sve+K2dgrvrAzXTfd9Hn+6+vexmc+9Xk8DbKrYzA0asqAaerKuXOHkXgTGkF5csFkxggvZEJitV22+JiYtXGIJXPONBwbaNWMxKPo7M01GJt9yZ9RNmE3rHAEvXUsk5gD6/LpTCZBIu/OUKQOEmytxnSejYgad43EwgUErc6PkAADn5roSybEwyioqACeupxZkhkyuCMavO6PSKWRiXvbiTMqD9kYg9YFFG1pEOrMxcL8qn8vsTAjHcuB+yTCfetEmeG1uRfCPNhgDIBgDCdb0sJZm2KG0oZGcakFgCx/28ZZVsiEFS7WVg7lBkZlO1qNDTfUeNncMSOiALCbsWOqY7agMGrbkZHV/TPCNe7svkQHLRiH4oC1RpoQDXqpGYefdtctqwdT7TYi3N7e5tixY/sdrAeorr/+em699VY+97nPAfD2t7+dz35Wo8bnPe95mBnf9V3fxa233srzn/983vnOd57099/8zd+84WRdf/31/Oqv/irf8z3fwzd8wzdw00038epXv5rPfvazvO51rzvpfHr11Vdz3XXX8cM//MP88R//MZdeeikve9nLiAh+9md/dl9gnY+1m2A4F+PAuzu2BwJ1cSJ5/1ze3/taZ0Ls3XrrrfzSa2/kT/7kk/TYEiW7QKHNOzYMctLWzqyxUPMt5ejZEK0pDbMV2JBJ3Yw2deZ5VmBwmc+3Wsdy1Ip/q/y5NS0mwih/TmeggGX3UOcptJ1mK22ShUNsB2ZqbhDKM5xH0CdBpRptQTPhrk6TWZC2xrOxHjO9S/y0rOibrBib3pVriHAHja6tuZRPq7dGujYXNSrrrHOmDwlDdWQE0Rwx6CVgundiCOEgkdL0+jaj42Az0PBWQdKiGDCGQqTXI+kV6rzp2BVHTFGOYl55CLzaosChI1gv9PQmJEUvlpiHVUh0oRiq27eMAmev0Wdt/6VVBy6d8NxE2ZjtICAMPS44jGwaJcbGKoa7uqBhyxJEwURHMpNMXqHRQ/NjicBk65u/mWkXxtCDrXYbD65WKw4cOHCOjmjv1b2Bht7d3321uvbaazexQGbGW9/61k0O43Of+1wycyO+XvCCF9zl73/oh35oI7C+/du/nQ984AO86lWv4ktf+hIXXHABT3nKU3jNa15zFySDu/Pud7+ba665hpe85CUcO3aMK6+8khtuuIHHP/7x+wLrfK0TT9Lb29ubiJ/zaTx2unViVuK9GX8+UKLvbNfRo0d53Q1v5qN/9CfaUJu15dboQFNHZJ7UNUqZlBleK/nQrIzeNXYyUx6gCJONiJmVdY0AI0rwmAw7xaeSaGnQ1fkxVwbhVD6grCydNLAO81jTre+AQesfDMJC4iOCjro1Xt0W8aIUU7Ns/Ll3IqNAmzO9F9ySElsbMeFEzvq3GY6iX5q34lPpvjYMLPA+Meb1xhdmYWRfol+G/u0uN1QOcPHCZquYnRx4jShBDCw3Z05jq/nCTCDQmHRFq/zC2igcEjcdw7q6rw1ETTdjneowHV+vN5uE0Yw+jPBg8s4Yc4lfZyrRuYxLhaXQSNXLkZZevrTQZuMa6LkclUbCcwS9qVtmoW5i1iLDSGMy6rmTYMwaM44SYXjjwqc/+L1Xu31huv3227nwwgvPwdF8bdYnP/nJr3qZMcZXvQzAM5/5TJ75zGfe69u+6KKLeOUrX8krX/nKu/xuX2CdUOeLKFmOc55njh07thkH7gUK/dkcx52alfhg34Zc6tixY9x449v50Af+H1HT84BM5FsTY1uZd3iyohPhTEMiyobTGhiNFiGzeJmUzQ1SI0NBKYNuTWOlWYZlbxBj3uAV0sBpDBsyuDM0aksJF02T5HWK5lgk3SYBQVO0ca/XrpvXpt4ylkq8NTKHcu3Cih+l7DYrJIOUme4L5c3QqCq1cbf4pdzF88oAd4nFlGnbCguxYCIYWSZ2WbRaR2NWM9Il4mKecS+GVEv50syqiwcgojyUmd2BlO9qbRKgc85MZkSNajM1yhUrSs/TTNYoDiYZ4bBoeAMbEnlzjV/nCDyT9byuOCIjLGghAdVNm5itaWtzZDJNrTp0EkStDO2MmajxXstlVOpFkVf0T5aBP0aJWSCtVexQbthcXs/L6nGPZ3roQx+w98m5rFPPHYvAOl/OKQ9EZZ6en+p8dnc8+M9OD+K6/fbbN9ty0zTtmTfzmRZYCyj06NGjwH2Ho+5FD9a9OZ7jx4/zpje9lQ998PchXMHAttKIr0GuQ7l9YfRoZBqTmczSkQXilCjxyckB3rpMyinUghWs082x6tKkVvUkpHCwIEbSJ3WefG6FDRDRO71iWtzpURzxEC8rQ8RvKB5TzlgFSqcpQmeMnTia3hbvkLYTrXhL0g+jjPhBa8IROIbV2T4zamtu0KLRCs0gK7m6axohVhBzLUUOxib+ZoOOMCNiLU9bSoRkhR1HlLk/gTDlFtoiaPRai+pqqTOl0WePJsP6SNJC1PQ6Lo3fDCsdqRiiGi02mNdB70A2JnT70YZI7SM23iuLYOQof5cWAqawui0jh0Z7yiBMuhvbI5lcW38S0uqsTSybhCWmqJgctM0YGYrJKWP/iaOc9MZFz3hwe6+W2u29fOTIkf0O1imVpxl7czajcs527Qus86gyk/V6vaGwb21t7bmQ4jN9LPM8c/ToUeZ5PqcRN2eq7s3jExG8/e3v4j2//l48jePDmbzTm+M2kSaCuCSLE0w0kjkcmwSKtHSwhtNxm7W2j5Epz1AzI7yD5NrGmG7RsRYylQ9oHuRstMkYs4JQekOxL8WL8jq1ZjjZQqNDstb01aGpARut/k5rjWJfWZmxC2eFh0tEhTETTAbrBlM2ogKY55jxLPBmprxNNeKb6IJwhoSRm0SiRTIsa/SncOiYy+9l6vpFGq2FeFo1WhVEtbxd6aR75e/pb+dU18kaEjpKqqYQqkJHzIPW1OWS0V4QwkW4WY3wGjKLd9Po1E2dJm/qDkU9ltSx4KZg5qZuXzdnnUWWj8BGMs/icqUr2PpAbf31Apsur0mdx5KYk9YlrgSBRePmQmy0CLLJ9+fo/rsJijq1jiVsPe7x9K+RDTqhRE5+Xy8bhHvps3m/HvjaF1gn1F5+M5wIz2ytMcY44xT2M1Fnqlt0KtNqL0XcnM367//9v/POd/4Gx4/NmDXmkRxaHRClHKcx4QGeTSOrYkDNQ7l+bWmHpAkOGWvIVpBNnSCn7jDAm8ZjNDT+cQcPYmi7L7oEFN2Ioe7NYow2EhuD3hvmg4iO+SyMgqxNGmtRUTgeGvflznjQ3JnHjJs2B9MWH5U6T8MUVRMkPpe4KKClV9i0kAISK5EDL8SA/nsRKMV1Kp6VVx5f4lgXzVSZhBJ2pKJeRup1KG9TiZ6hrhcmPnomJVBLUHqTMCnz9yoVd7M89mY7z4P5go/IE7pYEm1jgcJm7vDCxtjQ2TVarK1GK0REGrOZvHYmQdZdJPkpE5DIXI9Z2YpDIrR5sg7Duzpspfzq8SoAasjbNso3l1k4C1Nvy9DxWDrpExdd9R3n6B10bmq3EeHhw4fP0dHszVpI7qfzd+dr7QusU2qvjZN2g2e6O7fffvueOs4T6/4e14mm/YMHD95vIbnXntPd6v3vfz/v/rXf4JZb/hJS0SwRTusT28ed1arRZiM8ydDGXw5l7+UIvLfyyZQlPLsMyUy4Ja0LztmyYWvRwqfRKvZFYitTna9myexJS42ich5467CAQL3W05ozRmibDHm3YMhf5GxW5sxi03Xq3mS6rqgctwYe8gqZSegs2XdolOjpuEuQjVkjRzeJFvGvUmKKBsVjD9PjFKM6VEN+KluM5Uv3bTG2pyJ8elrlBSap9OZiYckT1uq+bwzkFvSg2F1GpNNM/C2dF1y+MncihthSQ6O5GBWZ4zuiWKb8wMr8bkWCJyumyK2EnMKgW8E9lfcjnxQmn1VbWGE03EJ5hSbOvMCjUXwvY82gj6zRoHARWV25MAnYDGjeNN5tjvS5cBcjKC+ac+CvXcb0NTQeu6cO1n7tVJ4mB2t/RLhfZ7xO9B1l5klCY57nc314d1v3RwidyPCapmlPmPbPVi2C78tf/jIvecnLuPnmLzN1J8eENcOi0XHmOdhaTWDO7MaKXkbkps0uM6Y2aSS4mIwxbRKWGdrNsZBQ6S6mlHsjLUkTUBJkSgd1tLyYUWJZrZjHmlWfiDZ04k0UY9MagcZ1VqPbZWMQX7xIzrBR3ahglZNO6wONBtN1LBjlpNdJPKvLVnl5Ho71dUXqqIuzdKXSRmUf1ugrojpP+vvZgp7lv6oOkicKetYToi3COvYYJpCoS+SZVdC0OzmGhKl34SisLGMprlakMzejh21o7Lmg1k25jmlU7qA2IlulE1rop2EhvpY7Xs+zyThFq01JTFj9dSRb1VXClLuoKazVRl8wYwsTVs+1C9Uweddz0gtolVHXKRG2nrM2JgU97XWcHouzTZ3AUcsJ2TsPfcbfPltvmz1Zdyew9j1Y+7UvsPZgneg7mqaJQ4cOnSQ0Np6JPdiVOfHY7q3YOpXhdaZN+3upg3Xi4/Nf/+sb+M3f/G3uvBNWU2eeO9bkIUrrmHUma2IkxUxvBzG6OlWpzb/VagubdZKfTN/2zJyYZ6wVeJMgmtECGdddAE51ZoQdSKzGQdAWRlJSZm4hDubY1mjS1EkjISkcQvmrJJSytgutvEXJ1DrbsRYyIYVfyPITjdruA3WnEuUH0gZUpA3phM348MrIkzjq2cSpar3EpUaDpDMDE8WXquOwZhUCrRGcggnLg2ZW4FLK2b3E4+yY9KtBhKHbTbeN92nOoM/yl9ksYvrC6dq5hztcHy9/U7YGi78qXZuYhjYzwzYROjKtQ0t1DkWLN3WqIhgEK+sl6orG7tToTrDSQZHzkxK8ZYA3k++uGWmNKcVGm8cQMiJmusEYWbwwsM1rSnyzTDj41y+jfw2OxvY7WF+9lkWJ0/m787X2BdYpdS5PxidiCE7M0ju19rLAuq+1Xq85evToxlP2YGd4AXz605/mda97A3/55SMcP97ZWgFji+YNt07kmqlOw27qRrRwGA3KJ9Oia3tvG2ylUaENwyaXP6ngka0M3G2YzEMhXAIlUsINry2+ZMi7UyKqubqKU+skM52VIAEVDaOnqUZ9KOi4W8PM6ZW118rEPUq0kdD6EvbsRThQB03jQGXchUcxpgTwdNMYL2orMa3QDwgnUO8IeYhCl/dm2qZrXccsNaAmmYlh4CYB1yivV+yYvaE6dVkazCiKlLPOYGWi4nvuYB3CHLfAvCJ/rCkiiEViRfm/QkKJMrYTm7Fd9bIw69TuIpYa37UhthclgIMU+oGCpy7Edrx+Rnm/ogSoPF14x3KWeGaZMCoDaaSQHbYO3NgAACAASURBVIH8VoaVeT0YzFqpGMk8D20zpqKAfNU59G1PZr1eC+3h/qB/L8PdbxF+3dd93Tk4mr1b5zoq51zUvsDaA3VP48Ddai8LrHvbwTo14uZsMq32SgdrjMGrX/0afuu3PsjWaiLmYGvrEAx1pDKrM5Wd9EbLiWDAMLxv0RJs1uireka0yZQvFwGxhQ0YlnSvrsUM02SsC3XQi/+0bO/1cIaLduQpSpS7tsS4M/EtIRlsdobN8mLloKUI5ItfKoISaQDJSAUE4+qUgY4lfcDQiXcUSiKGxmFuSyTP2GAUNtwsUp2cbtgsIeWtxmmxsK8U/bIQzy3K6J5l1g8dm2NiZ5UIsgqKxhKKC0bobxrGmqBXhp/Xc9Rw0ry2MvVsdJq2FMOY58HUvCauFZCc6vKFJ57VSXP5l8TF0uPYG2xHsjJt/+khKFREZnW4FBjt6O+yulwZdoKAE3KhpLbGrothuEZ6EWAuQ764s1oQyPLfgcacS7fNo0MTCqPrkrQ6vtVfezx2YIvjx49vXvPuTmtt8+8NaPZBUrvF5IAE1uMf//hzcUj7tYdqX2Cd47o/GIK9IBruru7u2JaImwU1cV+ZVudr/f7v/wGvefUN3HrrV9RhiIn1mOH4jLkztYnJFPey1SQD0oDRmdrEmIUF6O4QFGV7AgYWorU3L95TOtZMJviGOl3rwHsHQhiEPiTsLOTPsgnzGsUF+Eh86vIhqYWGeZcPJxfiefGq0jaoBUokNDOylffIaguuoJ1myj2sGWNdRxT/quOxeKckoJpLqblL0IUvhvYykjfwELfLQh2epePT3dWpqs3HqC6XVRDx4nkaDIlNU7dp1PbgyAJolojxkWSTH2ouCKtVt1BQ/EI+NFd8jcm3NArSuQBZMxvZNX4czCW4soRnWfVdaIzuVuHYrdxyTbdv0kBz4RxmdBtGsbvMtFhgTV0mq+egfFZz3bf1kDjWY1YsMETqT9PI2Ta3o6fOvRdYdoiIv9V4yHf8Xxw6dAjQF6gxBhHBPM8nCZHdRNf5Xvsjwq9emadnWN/Dp7mvWvsC65R6oN7sp1LJ7wuGYC9/IN3TsZ0YcfNAMq1Oxxd2pur222/nla/8Rf7wDz/K1moLckUzne4PbV2AZjLSCce3Z1qb2E7kX+pOc435LI3mK43Pcuhxi1C3K4NVBsNkfO9u5HrGaFDYgFWrxzka0XLTiZA40M9aaIuv2YJaGMrBqxN4ROIpgZKw6T5hOuGrs1HjxhxQl+1hFQ4dhCnHDpPoWTYT08BHZ22zEBGprg4Fu0wP2tDm3MomIuT9GlFm9RohgpAS5tCsVbSNoXwZCRBl9Gk8t2QOegkbSxhueJPgoLhZaUkbpt8N8at8cY03KHQ7mGmZMrMM/QLAukxvMq9nCbmhJYOuOWl1wUxdpLQd8GdKVJGCuqqbJ9q+Fvcq1gc2G4QKnEbcNKoTJpT2xqsGemiG5c5mZAVfa9MyRbl3yKblCUeic2GKORq5XvAt/wftwBag91tr7STfaEScJLq2t7c3v1suf6Lw2sufcSfW3X2R3BdYdy0la56GwNrHNOzXva0z1cHZK2OvU2u38WVmcvTo0dMSk+dz/c7v/A6vfe0buOMrx2i9E+n01uheQcmjqUMxdcy2WB1E46VRImdoxDUSGIZNA+/QvUElEI45FV9D0kLfENdjTUN8qlwn6S7IZYKhmBubEpvl5o5UZ0bCravPo8ZOjZIQ4mDhOIWEU4REhqFRF7GYzMWDyhGYq7PUojHK5J5NY7tAoq6Q7wybaenK+Av5knpt1LXFU2QVy7NE4ZQw0SagZIa3ygOkBHUITWBWKXslnED+Dlso5E4Z9jXGTFdnKhaBWeNF84qSobYjS1xZKnTZUsywNLXKosaii1DO5bg2CIdWQc+NcPT4FrereWdhpEuXytsWWR65GsUOxgY9ITVXXbgI3ORJSxZCe+UnLmKpxohpDWtRXTsAqzOECcfR9NqU9UzhzmbQpomHfudTuKfd5sWTtdgANBLPjeAaY5y0Hb1cfhFqe3W0eE8jwn2BtV/7AuuUOptv4jPZwdmrAmup5QP0vnjLHix166238uIXv4yP/9mnwJKpr2g20WxSGHELcnYaLoO6TThJbw2Kjt3bpNb4kIepNdHDx7Yhv1Qyt1beJTGjWq9OUibkjM1OTg0L2I5BK6FimcS2EAvuQV86PwG4RkMbb5R7jRFlPk+XWd5CziPCaoPMsCaMgGd5n1oRssyqa6XXetZ2orIIKzfRfNPRqoU+dUfYia9J2Nwe0k0bon2ajNxWHqRmttmYo0z5Uf/2Oo6O+FVmFccTIYI8lUEYQ76nJoTBhjdVHSfSJIQX03/WY4EAqlNvzFGPucOIrHDrxCy17ecVkmxCPKSjTUmiPFJiVaVpy7DhYlYZgp46elyL+L5gHdS9qjEnCFFRvqxRnjDK49UWsVsbj8ECaJ03ywvW1EELc3X9irOVwAX/51/Ht1awvX2v39uLYDrx82/ZjD11vLjUqV2uvZrokJl85Stf4aKLLjrXh7Knaj8qZ7/OSp1o6D5THZy9KrCWD9iI4MiRI3eLmjgXx/RAjAjf9ra38a53voc77jiOt6DbQcCho40368xrZ9WqwxGGWZP4Klhja1MBPTveBhHGNDnrNUyrFW1EiR8j1lRnZZsRGuK4pcKNp4YlGhmmOj5hsMTUTKm/zzawYfSuD0DzINIFmVw6Yz3U1YkKX27iPWFFA7cgh2MeG2M1WaiBdLwVW4pcdJa6OZ7yhFFbci5ZNUJdvBEz3tqmmSJvlLOOGiWqZybjlynaxk8wcyeG9wEx1eahbUz0M2xCrKEyFRHOwBArbB6zRp6WGyGp1xQ7nS7LzUYj9Rway2OpcWvGDirCawtwIcSrQ9fUuVy6SlndQPRcrlMQ1MiguVY4hXWopYDCTngCtQFoSNQJSVG3m/WYpDY7vVndF+Eg1IlDXrkmE3u0Jpjq0gkLyqjvtNXEpc/4v+6xe3Vv68TR4vL5uFuXa71eby5/rv1c99TB2udgnVyRhX45jb87X2tfYJ3FOpuG7r0qsJa644477hE18WCrL37xi1x77XXcfPMXIDu9dTDXODCAMRFp9AatdeXuRZ0QArwnNnzhbDIwJgLLzlRju2ZOr6287uKEtalGgJbkLJN7zMkswhGr1kpUTTQl5rDCGBnaDmuOjQHmjNkUe2OdltvM5hIxlrSQL6fViEsES+UORo3SyBDcMtW1oSU+GvQsg2vFzozEm6gTIqRLkEQOnbxDImomCuypTs9c3jM9Fk39rYzyQlXMS5m854jKQYSMIpubTPGWTaiCBeugg5MPrbxOhAKZMd8IDq1EDnV56pjk0bfixwtYEcWFGjmYWEz2uo8zgSfqSi1AfNMYEBAw1gvaCfiA9Mp0RKDUnnX7TcfkJihrDohuENrsWyKCSG0lTvpViUV17SxhJqsLqrtu1jfYCGUP1qJEHfCI2vgEDn/r38C3VuTx42dF3JjZXbaL742f68Qu1wMhunYTWPsdrP3aF1in1Jl6M57Id9ra2uLgwYNnvKW91wTWer3mjjvuAGCaJg4fPrwnxoFnE2sREbzpTb/Cr/+33+TosW3cO83AurpS2MSI42x1gZRGJK035gHNgrBGT8fCtRWW4khNpo7MsCRt4EMdrZjla7IOzFGjMNPJ2h0Lo686Q80lmZED0tbEDNaNdTM8Gs0NDxOaIIzmi3NpMFLG6bny/UYJCiEgtI/Xasus4TohuzonLZo6dkNg04aTMSSiDCZTR6YVzDIsyaE4H5nb9eXBUYCxL+T1jbARVWqNOFOLqTtLvIyAyY11akToVqgDK1O917gtC9fQysAfS3AM4jsJC8bsSWcRZXJpSejt8LhGmfYXn9Z2wtSaukgL/DUXuCcb265GfxQXjIrtqRF709Kf4iKXMGftEVpvRKZ8YgOqZwZDx7BAx6zoFM0L2WDlf1tgsjVvNSS0Wr1P9HjqZ5MvTC0TX8s1OsytFZd855PP+Hvqq9Xp+LnOFipit8+UMcb+iHCXSk4zKmff5L5fS506DjxbfKe9IFyWOpVpJcL4ak8d49moP/3TP+Vl1/8Cf/mXX2E9G6vpgPxULbCcUDqd0dqWAnqjbWLnQB8cbXTaSn6nyabiG8HIRl86EcNo3pnnbaa2wrKpW1SQz5bgHWLtmC1Ayq4MPtfoz9KIKWAW0ypzZljRvofM6pldnrCsqJYal+mUHhKFLsZT84k5583GoNmSbaeNv5yVY9cqNdlNPCkPBT97CQ1Hxn5hnRY/l0Zk1gyrDcv0CjSurlHach3LeAxxtopjFWY0NBJMoyClNVYtrtMokzxBBU4b2VIw1kyNQeeku4QPmdWZWuCgQ6HSaJMxsDKAS4hlqGNl1rAMdbgWz1aZ6XsUCoEEK2wGzhiDnmWe92TTocsucTgooSb1mLVFuYRG151WZzKCFiXqTKa9kcnktXGJcg7Ns06CoYxLYMLK4zXQzLhGjgYXP+lv0E7oTp+r9/s9+bl2Q0XAmfNz7TYiXL5kXnDBBad1nQ/WEq1uX2Dt12nUqXEvF1xwwVkVGWY6YZzLWkagR48e3dznaZq49dZb91R37Ux3sI4fP84rXvFKPvzh/5d5PTNNB9mampa3AjInbeNlEJF072i5HsCx5rRRFu6Oxm0FspwrxqW3SXTwFDIgY8b7RLU78Nlk6va28fwUCUA/K29Ub2wQC8IlTEDQcmtnTIa2045znHanaOTNvajkvmMMN3XKPBXgjDljzBUAnIslHaqTM9XDrfFfLhgsja3K3J6ZhYHQdmDP6mIVRX4hrFt1o+Q9itrG02O1MLm0WThIlzF76fq4gGK1LUdxuNC40JYuFsQYm5ElZHmo0HPTsgzzO/+t51SoBVIRPpa6DssgrdXjpq5aMwknGcijxoC5WQhQGHSNAc1ltC/hNGrMuHjBAjZ8IMPkQcMK2qqOoltjZBYWRDR6IlmvNV6MUa8X80oHMNYj6V1d0chgak2h1NVpjMp0bAcOcMl37HSv9tL7HU4eFS711fxcp4uKuDv/1V414e/XA1f7AuuUOh1BtIzGIuKsjQNPrXPtwTpxI/KBus97oT760Y/yn//zSzl2bBto9GklQnaA+YqRRm9GDIEwnY6nFwbAaTSNxrqR24nZRBTGwF20b7Ne2IQNHxwqvsaXURdBZlvaEtisBkO5oWA4vWUlEWtOlKjb2FwiJc3wNJo73o0+JsKHsA+pTcU1gW8H0aBnx7qgkyApxaTYm5QdSsIrJT3mNHXgMnV/1zqRW8hIvyAbrECcrQzhjjALVl0iq0UAWgoMarAM8xJ0w9kIDxHq0wqhUJuI4aQLbzFyLQZWaANxriBnjSZ1ryROrBxVIpnbUKdI4zZn5Cy4Z4qlNRJsDImuJnElPSbxY4no+GMxqOupi+X5CjsBnlo09rH4yypmiCXkutqKJvL+SIVQz1HZh2iQaWSJKgiZrbTZ2UtaZxZLS56zcMdalpF/QW5IhIXJQO815r3kiicUuHan9nrH+lQ/1zJaXATXPaEi7s7Ptdtn8O23386FF1645x+PB7pkcr/vj8m+yf1rtMYYHDt2bDMaO3z48FmLezm1zpXAOhWQutsI9FyLv7NRx44d4xWveCV/8Af/iwgJntabDOljwryVid1lwHZo2TFrgjSmuFbpznoEfTRaX4meHY02lSAzjREVPTOVh6cxuTNGYi74qEZF0GaNstLbTkfDtaI/p9cITposA7YmiSfCN8ZmOcGdVlmFZsHKJrBZXZAxyOGscw3bDa8NsmTGrQKq2yQiuTVirKFEmoWwAH2uOJlU98YTZp9pcyM9ipZexHezoohry8+bfGEWC++rbYjrZKX5ebJMxtwWJ5Tu2zDd3vF52TysO+4a4kZamdfV8WrYDmi+vjNkGdRb+iYOJ73iaWrz0lIdIx8a3ZKa0mWN35ZOUC5njPKyOY1g1GNg1QNcNj6NETOtRKLuUsXslGndi76PSdgtXLDMYpahjpe7sS4yfLJ0IWVeN/dCaWhkuXjgtFFJiV2J0nbwAJd8x7ee9P44H9/vJ44WT/Rz3RMq4lQ/V9RW7Yl1JjcIH/vYx56Et/mpn/opfuAHfoC/+Iu/4Ad/8Af5xCc+wYEDB7j++ut52tOeBuiz6kd/9Ef58Ic/TGuNn/u5n+PZz372GTme+1vn36vk/tW+wDqNeqDHgbvVAy1iTmRawfkVcXN/R4S/8Ru/wRvfeCPHjs1A0nxLNPMwsBWrqf4/ta7fjBzBKBikW2MeydRMhO1ZHSyiNuq8cvcw3GFnTz5lPk8YHrTu2uwKMEt1RqamcdkceEtIZc6RTSNEaxsDeGsSO0nHfOCVi2dZK/0ndEWSWYIBbQTmZEy5KqWWMklHE00+4Lhv61cmPnqaTN6ZyYRp/GYKEm7eNuHPmQNGHVPT/Z5jTfOOWdZCn5TOmjXd5PEz36FCu4WAoTTd/nDWhEKQS6RRIcjJToCzRmolUFMcKVtGodUViky8TqQeKTRCIEI+Q9mOGVgI1+BpmCmSp2dR2ReflYl6nwx1h6Ied4vyNalj52GCrdrCD+tgxuwzU4qjtYRHL0iHzRIAbJANJ4VE111umy9D2mLMRT5FbQyyRPbo8unI/F8zyWzGQ6/8m3g/N8iVs113h4q4Jz8XwPb2Nl/84hc5ePDgRmCdic9Gd+dNb3oTT3jCE076+Qte8AK+7du+jXe/+9185CMf4fu+7/v41Kc+RWuNa6+9lgMHDvBnf/ZnfOpTn+IpT3kKV111FX/lr/yV+308+3Xfal9gnVJf7U2xiIyI4MCBAxw8ePC8EBn3p8YY3HHHHfc6L/HB0sG65ZZbeOlLX87H/+zPcZ+ATm8DUnwgT23nkQc2JyqdzDV2i9Fw64xIVt7U3cncUM9Hzkx9Um7fIjIABkxmjLBiOjm2dqxTfiGd8Lp7CbTy9PTGiBo6eRneY8a8k3ViNhJi1GbewFLG6kxdXuZshTqPHHRr8jpliZUSd+aOd68MPTmuR2pEN0IyTtEz8hlZGjY1iRyrbboMYuMxmrG5omSqa7P4l6wM2y37hmW2EWvm1YER/LJnBUHnIimytu2gL3E/tWGXYeWfsuoYabQ5Kh5mLPiCsjqa7TxWEVEZfzKHLUZ8aipLGNk1Ro3FhL7pLknEYMXJiuVny6aeVZcyRWxPRQy1aItjTluOJa7SdqJvskbGioAMdh4GCTvmuozZDp2+uFbqqJX3CmEx2rDN0kCnYQdXPOxvn9y9gho3PkgtAvcU/XP8+PHNl8//8B/+A6997Wt5zGMeg7vz4he/mCuvvJLLL7+cAwcOnNZtL2PMU+tNb3oTn/jEJwB40pOexKMe9Sje+973ctVVV/HGN76R//Jf/gugDtgznvEM3vrWt/IjP/Ijp3UMZ6r2QaP7BewuEMYYHD16lPV6/YCPA3er5RjPJjwzMzl27Bh33nkn7n6vAal7TWDd1w5WZvJrv/bf+JVfuZExG611xkj65DgTWDCiV7epY97w0LTKesOZmMcsnIAZKzdsuECbFjrRs0S2qEOT1sQpQht1IQ85OdoGdJkYk/UNZHTpJmUMfCX2U7dWHRiKn1RX5qK+J1bYhSFyPMBwRlNQsTbWJPiaN5grHLkECcXh8vJVa6Uf0o1uEoi9OFMxz6TlDtByyFnlro05qMAfod/ruhpjzEI1gH7uUWbvcsknldMHOqDyCiWEtdpqbCKlm+CrWfBRWZrKw2ZeAE6xEBZIezoasqU259YMenmRSC9+lG9wCB5lQs/leUuZ5l3HLBP6wtWq+2WFoYjF70XNEyWEM3fWBbDGbDMThXyAHWREk0m/XH54Frajtiwzd/ARhkzz8pbpMdQf+SYeJ8rFpy8CrR5/jRrxwaXffrnAr1/jtXiylm3xra0tfvInf5KnPvWpvOc97+G3f/u3ef7zn8/x48fpvfPEJz6R973vfRw8ePA+39Zzn/tcAK688kpe9KIXYWbM88zDH/7wzWUe85jH8JnPfAaAz3zmMzzmMY/Z9XfnsqL+OZ2/O19rX2B9ldoL48Dd6mzf/omduq+ViBuAm2++mZe+5OV89rOf06nGGxHJtJqY14PWJ8w6rXfW69B4sFbmu8tgPTPrseo6+ecw6I02vLLvZEDuvYt/RCtskQRAzlnjrhqBuUaQvmTIdVNAtPlie2aMmcm3yHKzDwbT3KDpW2OGOjmtujebEY853mdiFp0956yNuSJ6u5eg1IZc4sWIqq4UlZS3dHqabmeeA7NkmrZoVmbyhBHzpkuy+YKAuicLoqJNTf6fiuKZGfgahg88l9BhicUl1sUYO+iHLGFRIk3+phqdYrV+p8eypWTMKJr6SBHcMxdPFNoQLBNbMzZZiHMkxY7fjBmjVZ7imJno0GHkDN5Fc1+wEZTxHH1Dj5wVTk2R8tMrX7CxLmhqGBUrRHmjsvIYgfJxLbT4thDn6wU0UhmUC1dL41zxtTZiLnMTMxSGwLV68WFu2AUXcOm3nTyqOrG+Fj4f7q7MjMc+9rE89rGP5Utf+hKHDh3iF3/xF/mjP/ojPvShD/Hxj3/8tMTV+973Ph796EczxuDf/bt/xw/90A9xww037KkvsPt19/Xg7Onez1o6MNvb29x2220cO3aMAwcO8NCHPnTP+I7OFjxzjMGRI0f4yle+QmuNiy666D6PQc/HDtYYg1/6pdfx/Gt+ms989ubauNNYb7VaEQNWJUpaE3izNae1idYbzRRxk7Vp5N5EwA6Apm7OCSdts6axXnbBMgcQwVgn3q2gjxo5znMi0vqQeJoTa0aOsViJcJtIZl13ymCfHvI3ufxH5s4oj9WGPB4zMQqLEA7daCkYY3qq81NjTW9efigkCps2Ec1NXSuD+fjgzuNr6bLWq9sif5mlM00TU+v03ln5Cm8Na+rKRczcuT7OenvNenubGMGwYKK6hAgbkZYEGpfmCEbMjDXMY8gbZ4a1ErekxqDUiAI00jOYmvxWw8HpG+FEaAyYWaM9aqvRfPP4kjuernWOErEywZe/XcJmgNGwIVyCsv4GiaCzi3/KrGmEOAqrkQKzkjKnm+vxXQzrUIIOIOv9FohTVZeba+Q7z4KzanptBWctoz4atUJBL0p4Jew83zgEPOypT7zbMeBeer8/kLXbBGEJel6tVlxxxRX8xE/8BD//8z9/Wtf/6Ec/GhC361//63/N+973Pi6++GJ673zxi1/cXO5Tn/oU3/AN3wCoY/XpT39619+dy1pGhKfzzz3VHXfcwc/8zM/w9//+3+eSSy7B3bnhhht2vezHPvYxvvu7v5sLL7yQSy65hB/8wR/klltu2fWyr3rVq/iWb/kWDh48yGWXXcZLX/rSXS9322238WM/9mM8/OEP5/Dhw1x11VX8wR/8AbAvsHathcR7osg4dOjQnhBWS51pgbWMA2+77Tbmeebw4cMcPnz4tPMDz6cP3E9/+tP85E9ew3ve8168NW3T0UqUiBdkQGTXSTYajUbHiaHtPi8QZM5JzEA46wo4FmG8lYFcY66MmQgDT+XdtcbsGvkwG1NtmxlGd2AkrakLY00n880GWFiR0tuON2cqkdC9RlFav1efg6JUlgepxmweOkmPYj8tJFDLMvCbqXuWKTPWsLovsB0z8zwzx2A1rfCp0bEazeVmZEks0ToullTTbWxtreirFdM00VqH2mrLGKzHzMiZhRllrvFc86bOCq7jbA4jWOdMxGCOUSb5kJE/a0yHKO9Z5m0bsRm5UQ/HstVYTvHaFlQW4kL8EvjKagSJPEymjpuVQV25i9pAzCwuF722RCW45mJYbcdc5n3qdVPiJ3KTU6kRYxJxAl4B9DyaMTbeLY0L01wm/Sxqe9pGpFlBSA0nFrFG00Zi1ONTXwj6hYd52FP/5j2+j/bS5+MDWXcnsO5vHT16lNtuu23z37/8y7/Mt36r/G/Pec5zePnLXw7Ahz/8YW666Sa+8zu/E4Crr76aX/iFXwDgk5/8JO9973v5R//oH93v47m/lbmgGu7bP1/tVHLLLbfwwhe+kI997GNcfvnld/s6/NznPsfTnvY0/vzP/5wXvehFXHPNNbzrXe/i7/29v3fSpijAK17xCv7ZP/tnPOEJT+ClL30pT33qU3ne857Hf/yP//GU+5T8g3/wD3jDG96w+f1f/MVf8PSnP51PfOIT+yPC3erIkSNEBIcPH2aapgf9B8eJsT5nwri/Vx+vU0Xfer3mda97Pb/1m+/XSWcEvW/V6jU02yoYtpOp7Ds34RHwIK2DhVAFVGcDpzf1PJzO5JOM1Q1yLKOrCVLA0RwDzxUxkr54qkyiKMthHTU6jAhFfWTQ6Myz/EPDRjGexEEyc3KdBT5dvD8dj1HU8kVURW0ShmJ9qA5QhIzxBhbKFGRO5i7qu6W6OYPAA+Y5SNMYq22tZLofccIWmsZZy+vChqP2nvxAZq3GhWVaL+9YxChYpmChYx36XaTGh3X93dVFc6I6NF4bckiIpDYFB0mbtdnnureAwKq28LBIbQSisZi+QcvzNg8xxBYMlZeB3kuLWsj7ZVHf1l1dpjl1f7L8TRJj1YGKZRMxN7cXWYT51DKBulU7nSnCNuBP6voa8sfJKO9FdNf2G/UcBBqDijyvUeXSHYiokapBuG+CpS0T3Ln0bz/xHt/X59MXqjNZu93vI0eO8KhHPep+X/cXvvAFnv3sZxOhLvI3fdM3bTozL3rRi3juc5/LZZddxtbWFq9//es3X4avueYafuRHfoTHPe5x9N65/vrrufjii+/38ezVeuQjH8nnP/95Hv7wh/N7v/d7PPnJu8c3/dzP/RzHjh3jD//wDzfPz5Of/GT+7t/9u7zmNa/hn/7TfwrAnXfeyU//9E/zPd/zPbzxjW8E4Ed/9EcZY/DCF76QH/uxH9vEIP3Kr/wKH/jAB7jxxhv5vu/7PgB+4Ad+gMsuspnBKgAAIABJREFUu4yf+Zmf2RdYu9VDHvKQs2oePxN1JjpYp0bcnKlYn71AmT+xdnsef+/3fo9Xv/o13HqrYi0yk9ZXrNdJb1usejIPbQzGSLLJxNyaVXSNQm+7TfITmbF0vQSycswGOa/pbVUGYsg2YRHy+YykheCezbsM1CHAZ9riT3JoMsI3b0IXRGdd9G85vF2BvRizU4bsJIdYRxmGe5RXqrboPMjQ5qCFM7MW8dx0O/LsmMaMoQGSo625jjxKEeq+uRnNlW2IF0vKtA+n/2UZ+2MzllqYV466aBFDWYue2DCGDRYXUUOdKj+wdJKCpJHzUFjx9pqapdFacaTMac3lN4pkRMXYaKaGmekxTI3FlridxVSeUeyqjfCB1r0EqyKMli4R9ZQviAx1hNb43LDuhOs4B7p8EPKJeaJsaeElPGrxwcvZZlbxQAYMGeBz0K3r+d5sN0pojSGRO0fSteiqrEirjYRFwNVrYNmSBMOaOrAxBrXkCmaENQ489AK+7tv+xll4Z57ftVtMDpy5DtY3fuM38vu///u7/u7hD384v/7rv77r7w4dOsQb3vCG+337Z7rOVlTONE0nGf7vrt7ylrfwrGc96yTx+3f+zt/hsssu401vetNGYP3Wb/0WX/7yl/mJn/iJk/7+n//zf87rX/963vWud/GP//E/BuDGG2/k67/+6zfiCuDSSy/lOc95Dq9//ev3R4S71RIIupfr/gisxbh/2223sV6vOXToEBdeeOE53Yp8oOr222/n2mt/nmuv/c986Uu3E2GYrZimAyh5Td2MkYblSmO1PjGl02xiPS+r8bJhZ6z1eilXEzix1jwnwzDb0iZdbcB5JQhnjYho6G9Ta/Wt6UNoNIkahd1FGa1zczLurTIAU50LN7UpWko8aWZW7ifXZay24EbWHNB1nGYL4JM67lnjJqLGciXKhjbf5hwcH6O2GZ2+mjbG6yif2XqsN39rZcUnyuBdI0KQ4MlhuJUJfeh58mzyHRG1ubiTi6h4acNXjdY77cBEnyb61CCN4yOY58H2eibnqOvITVfQmjxZU0UBaRSXzCPINMWnWGg84YtgSjJS3Ckgwje+riDZ8YnoNtIda+JUeflIDG1kRvWyhhDpGgWn6bVjUm45amtz49XaiUSSiMvyc2l5QID7WnkwI4Y6Z4Zea7ODhZICljzBSEgaM2UWrG4t5sxpFdWUfN13PPEe31N3JzS+VupsCawHWwX6wnCf/zkNUXZq3XTTTXzxi1/kSU960l1+d+WVV248U8Dm/19xxRUnXe6KK67A3e9y2b/1t/7Wrtd59OjR/Q7W+VqnK7BOjLi5N0yr0z22vTYyMDM++MHf5Q1veAO3334nvW+xfC7K9q0RYGsdcCLUlUka5CBSBHWrTTfFlXSsN41sNCQEFMmijDwNoiyaxnYmrlEXZKk8PKkuxxwbpEJrLh9Xa4z1oPtUt+kF0jR1RWzZZDNYtt9YTtbiZ2WBQm3Uth+DRtfYcFhxqLTR1nDN3GQ2kqeJZRQm/9VYz5vRUW9d4m3xIVlgAcOzHjuwVqKgIm7cdeIOH9WZKsZWiQfKQ7R0uRqdMQ9akw9secwWAGpY0lI0eEvDe5bR3AmbdTyzuk7DtgsE65tOlTu0cIanEoWSTecocyifzyRoNsdvbLqLUSNZMjWiNdgeQyM5E/Yi0xmCTdWY2et1N6tDyhCCoujsC8rBLNVRal4G99xZkiijfVLGedeznfV6Tl+OT2wvT3UXPepLQOjVqZetl9cqNxgLr9ubHnohD3vyXz+bb83ztu7uM+4rX/nKvsDaY3XzzTcD8IhHPOIuv3vEIx7Bl7/8ZdbrNdM0cfPNN9Na49JLLz3pctM0cckll3DTTTeddL2L9+3U64R9TMOudT58EzsdttPRo0c3ETf3lml1urWXBNatt97Kdde9mI9+9E+YJsXXKIx5ZgxjmiSOvJhJ1oHRsQq23ZDR3YniQ2WFC1NelVbhzp4dSugoFNnKeD423hhykTpBty4fljUYoYDfAO9OrmemXnBNNB5cIk9A3YjJl5DhurNRDCRaUb2rU1QGHgm/8hvFTMuJQGPMMYZEnjJoyqez+JSSsT0zmOls0XpU1yrwcGEOytPTMNi8PoMoKrz+v8sDFoV/SIoDpaDjzNrEo2JlMpSxKHMRVBeoZ5fASCEpllHjIpclIxzrBUQ1k5E7jDHWtDTmITO6kdBcRH2T8CM1xiXV4bPUSJgM5hCVv9qPdQzLbp/TzZkJ3AK3Sb4oBSOS5X3TwFa3Y94xYgdUWqT2AKw3NnI5a3SYkF4+MdPlddvSxxR13Wr8OZYlixGbsOg0q4jKykksW17Uc95SHbFHPuOu387vrs6Hz80zWbt17jJzv4N1D3WuzgrHjh0DYGtr6y6/WyCwx44dY5omjh07xmq12vV6Dhw4sLmu5W/u7jozc19gne/11YTMiRE3mfmAMK32ygdtZvK2t72TX/u1d3HkyJ1srbYUcwFkCJ5qdLGEXBtWGBthYQuo0RvW1Ulx1wm85lZsGEGZYF1CZ6hzEZ50C3mGxlSU8gWBoCHZHDMdMZLMly5YQgyaT4wRmKu7xpBxXT6kIdFQnZdlzU2GfDZ8qCy6uiJigrH4jTJxn8rbNckD1RzxIkzjJFeXY06N2gwTA44Emq7T84SuWWUC1hlbvi0v39VCnM9CH4gQLySBInDSZaLHrLbtNMZUDE3lAJK0UIeGTIUcDyVdRwwFbZMScVliMypShiZuVV/V60P3NTKxkcwpwTVsLtq8zOTLONMdLAfmMBA41axe79X5GiWAILGYNOatWB8tQmTZxYq/FWt6ZpnkTd0kH7VxWHE7C3TWJDRbM2JOZTRW1qBnyuM1S9APczq52RJMC73mapPRalyrNUdj5JoW+lJByI+2dcmFPOyKx9+r99l+7dS+wNq9lpHf6fzd/a2FQXb8+PG7/O7OO+886TIHDx5ke3t71+u58847T+KZHTx48G6v08z2Bdb5WvdGxJwYcTNNE4cOHTpt7MJ9PbZz/aH7+c9/npe85Ho++9nPMUayWk0a+/VWxt5eY6mZMVecScA0dTI7RGBNm36EOindC7GAonAGg1axOWNAn5KkqRNmRk8q8mUS2Xs0NWFiZwPMzJkzcGcHhpmpVX4k8lqou5GuEOQwBQuLqVDipdb3mUf5rRbMQ42qNHtSJl3KBJ5A86z/Rl8vu0z8YQMbyfGh7pA3Vz4gZRYfCPJSxngr4zwJMesKrZARS5QPqZEhUeBLtzJVN+ZMvMKsw2QCHznThivuJWoc58tYbMg2FOp8YUIixOa+aGDmc8XBLAKlhG0GIpKnvFn1xECaQqpTpvFw+d+obED9vV4HdC94agE+Y+wI3ETbiomeM7I6jyXeU8b+qanzmeWaX+dgVQLHifLcFY09YkektkXYGF4K22q8NzJoQ90ybxW1ki5MxTLKtvKHjaz/lIhfNioz4RFX3fvuFeydL1YPVN2TyX3ZMtuv+1Yfvv3jfPj2j5/0s2Oxu9i5L7WM7JZR4Yl18803c/HFF28mOo94xCMYY3DLLbecNCZcr9d86Utf4pGPfORJ13t31wn7I8Jd63z5oLg7IXMifd7dOXz48N22PM9WnSuBFRHceONbeMc7fo15re5Sa1tsbw9a0/p+W22R6fTayBOVfdC6kwOOr9c6+c6DRuCrqczXDetNgcs56N51wnJYtUaOxUMTZLTq1Ew16kq6O3NCbxRDqkaH7lj0IqULUrpUtyJv4zRLCRNbYTUWAwo6Wq/bnlCGaJaMwaWjskTwmBXcSydbaxBzdXuG4ZYyh5eKapM6cxufVXm3WqANOwoPMGd5eqzwAtpqWzZyayqo66COuThb6eqCzWUKjwVRUN77NHmPPIx5rMvQXmKxWYndVmLHiwsFy5ffxY+m/21+qA5ek/G/1Xixu+5vTurkpQGzOpHzujqHSXXLjI5iU+YGjGAmyhcnBtdCQ2dBRpj8dN7EykrA19qC7KYIn6jOoy8NTdQpJIqvpbRnKH8ctrxQdrqYybJpqPuut2TdewNrrcaVFMXdhOQw58ClD+FhT/zme/WeO9dfps517Y8I710lX31E+KSHPI4nPeRxJ/3sM3fewos+/Zb7dduPfOQjedjDHsZHPvKRu/zud3/3d7n88ss3/3355ZeTmXzkIx/hu7/7uzc///CHP0xE3OWy73//++9ynR/84Aflb75fR71f57R2E1jr9fok+vxFF130gIurcyFQM5OPf/zjPP/5L+Btv/qOGq057isyYequbT/vGr00bdC1ps2zqa2Y+oo2HeDggQMcWE1MrYE35m05bOYxM7a3GfM2sc4K1NVJeJ5rbZ8UqBF1hpo3LIZy/bI6GKQwD9V5slCgr5mrcxMV8Fzmb22aGWNO3OU9ClfXJ7DKCCz4JRJU6rzYxnpvUBE8VK6cjPlzBLmWJ6uVsFuvZyK1STj1LmM9FNpBnRovYbls0JmBdd9sK44xbwTTggbP8kxZPQ5eG5QzQQ7bbOgZSXYqBHoQo0aOIf/V8pzVdGsTMg3Qre8IRyBisNDoCf3BxldWhvOcUzmM5adbujuWvoko8t5oWyu2VgforbNqTUb6DOYcHF3fSayHaAg43rv8dKZAbDm9ioGF2GVjwBwCv0aT0T7SNp4qs7Kq1ZapMBCQ3YmEOaqTaJA5g4nUn5VlSHXMxkLj1zyTZNkkjRMM885AOnBE8Khn3rfu1ddi7SYs77zzTtbr9b7A2qXU2b3vW4RnSr8/+9nP5p3vfCef+9znNj/7H//jf/Cnf/qnPOc5z9n87KqrruLiiy/egFyXevnLX84FF1zAP/yH/3Dzs6uvvpovfOELvOUtOwLwlltu4c1vfjPf+73fu9/B2q3Oxw7WqUyrCy+88AEZB97dcQE7H+pnuY4fP85rXvNa3ve+DwDyFplbIRg6xgDrijbxYhk1B6ZiVq11MqM8LqvGvA68T+U0amS2jSl7HYNmyfH1cSyd3jV/clsxzPDesGH0Vh4rn3S9Vh2TFP198dKkG9EktAYzjUmw02XNv3d8hEKncyzxgBprxZDYCMNaCZkKGcYlXKjxocz71dlAoE1zV1fJg1gnI9Yy1E8TU40sPTvpg8gyfXfxsHwx48cSHhwbI7a3GlUVORwT3wpPmc1z0Et2OItYKnFoQzBSQxDXZGc7jgW4mad8HRZWQht61emBDYaBpYuWEph675g4VG1hgVUA8xgaxSVkW4jsjs1DG3vNNpmIjSZcRS0OLPT3OdZofKfOna5PG6JkjScHLHyLMYviTprAr+GbZIB0IR2aaRzJrNGytdiIPLN6buq+DYM2sqKM9JhEtRB0O22DeWh6oDZC/NDXX8ylT/jGe/3++1rFNOx2v48cOcLBgwfP6gLRft21rr/+em699daNeHr729/OZz/7WQCe97znceGFF/Jv/+2/5c1vfjNPf/rT+Vf/6l9x5MgRrr32Wp74xCfyT/7JP9lc14EDB3jhC1/Iv/gX/4LnPOc5fNd3fRf/83/+T375l3+Zf//v/z0PfehDN5e9+uqrue666/jhH/5h/viP/5hLL72Ul73sZUQEP/uzP7svsM7nWoCed955J0ePHmUvhVE/EJWZfOxjf8KLX/xSbr/9iKjm5bOKoVOy6OStTnpOZjL1xthOWhs0C6IEkCM0wVwbglEjo9Y680iZ3UNA0rSooF0jZoFG57EWx2gMJvcyz6+05ZbGMOXAzbEYlGPjCcusoF1vm/X5DAFNSXlw1EczxawY5BCeAJzwxbgs/5JRgNE2yNAWnZUBGnIDGWVoCy+35Reb+iTBGDXSS4cIvGtr0cvf5J4wtO5vwRKnrEDi2lBbxnQRg2ZCQywB0d1N4mA57pQ40sab1d/VzywkVMgSk5WNWJ0qMsu3VQKnIVI6AdE2RvOaqImvtXjAQub/zSjRJZ5qmgiUDxx1tubQqHcZwYqdlUJpuESQUX4sNLq0gHkdBX9V7pKHazxa/jZ1Q4sbFl5iv7pp81zwV/m4bNnuHLbJStwsNlCQ0PKB2SJIw7QNac7InTBo3XAr+KkE6KOeuTMC2a97rt38VxdeeOHXxOfvfa0l+uZ0/u6r1bXXXstnPvMZQM/JW9/6Vt761rcC8NznPpcLL7yQRz/60bz3ve/l3/ybf8NP/dRPsVqteNaznsW11157F0H84z/+46xWK/7Tf/pPvOMd7+Cv/tW/ynXXXce//Jf/8qTLuTvvfve7ueaaa3jJS17CsWPHuPLKK7nhhht4/OMfvy+wzufKTMYYrNdrtra2OHjw4BlnWp1OPRAdrGPHjvGqV72a3/md/5vmE72tqL4GOouGtuNSvqppWpVJWN/2e72fxuxlEC8/Exr9ZW94UbnXazGmvPwtMRS9Yj5hGNMKdcVcIxwjC+gIYxwns9EbCtktj8/G/F0dj5SZSE6bVAi0zMbq6qwpe0yd9dPBemwM8xJlKUBnS3LWhh9oM0xGdiEHMkRZV/Tg/P+z97bBlmZlleB6nr3fkx9VZQFVthY22GLxIR+K4AxOMD86tAXUKab9ARFIhAJlFKJoaDAaMxNER4woQWho4AdCVVGlVHchnxqKNt8hUI2KKIa0PS3MYCB2UwRWFSNW5s173r2fZ36std9zMyszKzMrs/Jm1dkRKeW999z7nve85+z1rrWetSA1EFM9sJjQyVBtypwjFQ8AQ2aDB1sNqwzgZskYA9M5dIZj9t4BV8Clwk8zoQiLrgm9MWmn62WAs3TMPZbsqRGomsZk9BB4GAntCVOVDkGGiU1L43kL42QiQQwrY0JTou6cJAxb3PsEimI2PQhmqg+poyMa0+xXk8qoR6I6WPkDM0ww3ggVAr6UTyoy0DowAWjgB7W7kvWNnjEa8I2VTALgGGXONhgtXrnuDGsFEj1oyDeZrTJSQMo3jDd4PEXnA2ZIMxy+5pG4+in/6pzekw83UHEyifCrX/0qrrjiiotwNPt/Xagkd4Cdi2eyvuVbvgXvfe97z+hnr7/+elx//fX3+3NXXnklbrrpJtx00033+d4WYJ1k7fcPiojAzs4ONy/gvFXcnO91IcyvmYk77vhPeNvb3oGvfvVeTrYpLykScK/oAWRWeYoMpSYCHaUaTFN/3LTkXRqTZDDFFrgM65t4AUNHjwo3o2c5uaEmBLgq08XROeFnigJAJqLRWNx6B6IgbBfm/PtWKE1N9QAiGuVIc9blKE8LBlR09CxgWws374whsXGjLWJOimmCDmOSUFNjpgpANIGXGZaA14qVmcggFhObDzv08CUBEGApmrhkxALRiyUYiNkTPQO1UFI1rwI5exgm28hu3k0mcIIAswHCRpQEVO1DNm1MWYaO1zKXypcISmQ8P4y36K7Kn5TEaMofKwLU+jvRwePRJGGqm7D3YGr+AHFJRimzo5SCAwcdjoIWDZHMKhtgJdEZi8DD57W3UrAqAgdU8szpz8S694UBg7ObksdagHBUT3neGPTakiCaGV1krzxV2wMWP7uAMW8VlNmmkVFLPq/IQNFQxjc+9+y9Vw9Xk/vJbiC3DNZ27V37b1feJ2s/RA2cuPZmWgFYPFb7DVxdqA+Xe+65B2984434r//1b4EsMJtoxlZXXfbh1UnUWhlxAMlPSbuSu/Ku3ZfU9AQknTAyIK0QMAimcHNl115GwMqE6Ezhpl7HDkGzihaOqQAZncdlHV4qN05b0ZQMFjhHT0QjINrtxxaP0WpydCso6hHkJlgVQ2BwT2RLpZ6LzRglvooSWPg4T9FdlOLCeR56X6OYCwgZZSWYqnYGyxEKKqVsZdq4aWpPhZeSmSKASgBBI75AL5K5Vx4FLTumQm+TayqQieOjYofhqK6pODNKZHPvqEmpzwycsnT6rHo2uJU9Q5GOpdQ4cuPJEkjrweGHWBg9fp2VPfSOGQC4kz30kOmcxvHWOtITq7pS/AHQBMYMWABZDzJvpNgoJ/M8EEvCwIELKMphSmaBhfK4AkuC/ByNbJaz9siMoahdoawjfBSmYdcAkJ2eO+Y9LDEew2wfA2yrYgcGXHbN1XjUEx9zQd67D9V14mfdlsE69bqQEuF+XftrZ96uU669mVaj4mZnZwettYt9aPdZ56OIeu/KTHzwgx/G29/+dqx3u1geTgEmTBlTkMTiwzcsbw0lroyEl8rJvsJ4BCtMSXeV+FYZmyU+IZIbGVmgAcQke6GiR2A1NnAU9ABKBcflnYxDjzFPL9ZGvqGpVHRrWPkKPTlL1xvglphnMkLdCBA8FY+QBVlHvAF7Cek9YgK8i6Wx6BjFKUm385IrletEhGEqjF/IBP1QGuMPT7EuDZ4jasLFOilewVg8POYWh5QF8Fw7gIgGUUxkWIxVQGkEcNlTHqui8mQlzoOAkYiBXytOcJdugBgy65TeHBUWIJgYCeYgOBzXokgzMo2Lh0mMmCvKwCDDuSGywTByzugVW8cuPIE0x6pUwMCKnsTiH6PcqA3XAGShB4sXDhTJSjC6sHim55wKqwWmOsEUyIoYMQyNnYLrBncGrpr5YqCHaaq1GhDBaUYltXsDQgXSx7FYrngKWtvw2Od++zm/P8e5fjitk32+bSMaTrfOTSLEOT1mf6wtwNrnKzOxs7ODY8eYPL634mY/smx71wM9tszEl7/8ZbzxjTfh//1/PkfmozhGCrmZqWZEbITTAF7dyXJEYz+fZKhIbeTpm0TuUFp2B6y6io5ZXiyCCJOpVsUroZSRASmlMkh0YVeKypdZuxNBMFONYZfVjRNnVpARqH5AXrEAesWBiceDMbkGIBvQs5Hxso5pdkShb8y1UVODUjWK08COwg0XhcBs3ZrqfYDpgG9qYIYHBzqvEMMy5FKRMDFS1oElaDMVAzGCQcM6SvpSxQOQ2Uu3JT0+E7CWS8m1WgfplUNSGtU0pCXT8C0ZJ+FBdm4YtHs2VJm2vRtSU4huhiyANUp8Dh7/AACcnGNUQgnf9A6OQFT4AoR6N/S+JmtUfeOPQsjEzySszBB76rwmXEGwpMN4HCZvGfQ3wfR02Ii6MJ6vHhqwkIyKBLLCisHLBENymhCMeYAM9WmGMrPy2SeXB42AKgU8U8MClkC2xtcRBZd9w9W46onf8IDerw+3lWIV964twNquvWsLsE6x9gN4GXJgRDwoFTfna52PY4wIvP1t78T73v9+TUCRPTIAXioAQ28qRh6j52zBo4emB0qZuHGpy66AwY2RCZ8mZAOmWsR+SZbyCRaBUlZAZ/DnLGZmyEApRsI8OaVmRslSRuKeLJKBM5KhoaOClS5l1NOYI7KJ7XFOM4ZzpD446WhhiBXluOiJmgAykNHQ01n4HJxAm5LTdoYJ5g3eCz1UkVi3GW6BOlUUcxiYoG5WZbiW4dxMPXcBAz1UCU329eFXI7CCKnFG52JPQoJALn4pSlOFWVZWUCwpt3GoUxCiM2LCQNZqONZhSy1OgOXDboYwAr+wDlcIKNXNwfIZ5uwo3VgxZIO3Ac3z4/oQ00TfeGwkSyMj1LMj1kEGyAsnB4uJnQQw/FwBsK45lqlGL1UWclPQJ+SVIuguDvQcgajkYT1M0451CWIlQB1k3ki45/mnMd9Qjf4xgixyrz2BXPel8qm6q3S7ALGHLTQCwkDiMf/mW5d6EDLBYgjPYGjmwYpj2Y/rVB6s7brvCpyjRHjej+TBW1uAtQ9X7x1Hjx5d2r1PlWm1H0DgydYDkQgzE5/73N/hDW94E/7xH/8RI1By1NMknCXFPqFOFRmO4lDmlSQqN/qMwthll8xT6poo9MmRmgwkeSM5qnG2qjh77bxWYG7MYgKN3YAm/DzRg1UkBQq7NHAyywrBU2ecQw0TUyWmi70ssMLqv6Kkb6aac+MLgbtqyqJyZ2RDLxDBxKDQ3gEE1r3B0wFbA3BUp4QanaP9pSgbLEcVsn4vHDAyIGYFQFcPIRPVIaM54EslTHdDkS+JpnRJspDPKIuYI/nfClPXaUbXhGJSMEAp9CWVUDxBjHRNet4k2WKkvCts1CQ3DvBK4CfLURJEcmCPrJNJJ+yauIyBpgybwFINBLS5kSFKoK4q2Tkk0KCKJDJ28FGIvZngC6gbMsBpznFORrin8TVwsZoM+RRdygNDawEXS8mBDCPjmkDKf2by8Jl+d9YC65SYCfOAhg7vjtaD4D9zMcXzhoKDGVd+07/A1U/4BjGM/Bex2dZOBFv7YVJ5P6xTTRFuGayTr4BtWhTO8nGX6toCrH209lbcmBkuv/xyTNN0yrvD/QqwznX13nH77W/Dhz/8YbQ5Uas2rXTUQvTRW4ebmCnJSwnFO2GwD8BqqtysW2VWlCt2IWlAr6UiGNq0TN3BDQXyccGA3jTFxqoRij6GdAVoZiC8KES0osWMWvj1YnUxFcMB80JJQY9LTQJ6MhvJgcU0bs5d35J5S2GaAOtQKGeHJ8M+V6WglUIJLlLmemOSugzqmczoKjkxSkAbZKSmzBTNgBzesy6QQhO6owiY0LNkkWKxFNY5zPXD4yMpMgGgOCf7PODh+j2JNJ4P6/RneRP7BZr7rezJdkqCCg8ARdEMwTgCM2evY0l4lzyZI6ahA1aWyp/skuzMFS465DKjJ8yZ6dV6Qy2FIGd4y+Qib63xZsdSXjj+fQ95mwb4mIyDCDw96MqgImPZF5aIZCDztcZL41U+sU0yKC/wYAZYIOVLS2T60uM4phehOiK3Cp9Yq40MRBglcOfgQElOll7zr78F8zyjlMK2gyGlRixAa+9/j/fZAF7Aw89/BZycubv33nvx2Mc+9iId0Xbtt7UFWKdYD/YHxjzPOHr0KHrvOHDgAA4fPny/x/BgJ6af6TpbBisz8Z//89/g1lvfgi996U5UsS09EsU5WRVGOa4W0zSKLZ4ZU76S24TW2C1Hz0mBV0OibGptCmWw3ljmTGali3VKmFXJN2IaNCEY2rxcvyckJblRFgw0TGVS1hb5ZyHoAAAgAElEQVSZNASZFStgkJWiD6yMkmAWFCMTbpWsl7GehebylL3K4M6Ih6wqMPYGZEF4YMrCakMVN/feUFDoGQLQO71WvQUaOszYw2g2IQqYmi6Te4LPGQHla8m8DcUJdDqUwgOWExwNMHmQjBES5sNDhCWws4QzWgECO7ovJSAqyr0KlTkDoWwuDi0or8oKweiYApSvKsNgjaCCegL/TqIi0QfMZJVPGgKdcp3cVGas5Mk5FvDiZUImk9tJVmnYoWpoQVpxBmEh5wB4hx6dKfWLiU/SpDz0ZPyM1z2nC3muio28MSOAM0HkDKCzX5EDofSklUF68USRIUvj7wEnaHtPsadkW00S9VQ4kfg133g1HvW4a5Y8vbEG2Kq1Luz5AFl7Wa7MXAZtWmsPe5Zry2CdZuXwd5794y7VtQVYF3mdWHFzNplW+xVgjXV/ACszcfToUdx882/hzz/xCdRpQvEVSnV+WFtVCCI1HDI/hRstEQBc3XOGgh6GWgmSIjpKHW9oGpdL0eNQYN4pMw0/VFd9CTpBTk+UKlbICszo8IpKf9dklOqiu0qkEz2CBdKZ6M1QSmcmU9AHJlEMyK6UbTIhBY4WzFWiiiQJStJgWiIkn9VwdAc8dY0k0JN/26KjBzBZhU2UFyOBlTb1MACd+V0MyZyRs8O9w00p8m6ILsCa3PCZog7AyFBReiuAdUD1OYAp3YEZW1Tkhlxl6ISLlPPE6hB8CvAmwzkZraDpOsUfkGmToudFvrpOIDoQjBV5k/R7s2oyj2xgGKXcAYhMclwA6GiIrlwrLww9TQJRXsGEYmFdAw309JlBU4n0YpmbJhqN8nSCwROSrXPIgQKrljSx9x4cgBDAHflrg1E027PHqF7HFYMxJ/OyyOKK8SSZBU1kkKmTruwgeDMNNTzx+c/CoUOHlvdj7335N8/z4ssys+MA194WiUx2eu4FW+Mxg+l6qAGuU01Obk3up17bmIbtetBWZmJ3dxc7OzsAgMOHD+PAgQPnBJT2m0x4Js8hM/Fnf/YJ3HrrW3DkyBFmJ4k9IWCcKJMB4MDb2DUUjCj05G6IBpTisEy4TQQ6taA1STYqQ2ZkVUUHaaUAtLFpGmiULJeElQG+jObiLh8ONt6nUiqN4JLXilXyMzbkHVdcE1kaRGi6jN6gLnaq5976FZnGFdEQRnO0SWKjEd02OU4JzH2t8EpgVSaY5yIhhkneSmCkphsMPk30QSX4HJo6FsMQOcOMCVhelLNUHIAv0QLQRCDPGKMEBhwZhqxMCNi4/F6UpEwxE1GYjwUZ2PkfBGuLvAoQNGgqFFbIcnWCM04UsA+QQHmAswRcUmySLctRcj36+wIqQu4oXoHK1wI9UMq4eRkTkupMNN4UjbiN0VsomgxhgTKSRRPyDCaKwBSzEyhB0wJm8EKplcCQHjPWAyomIyjjZqa8XrE8fxfrlQNn+ngP0vPlQpOJvrluwCnLq659NB7x2K897n1baz3uBi8iFsDVWsOxY8fu815erVbHFcrvZbpGGPL4/Xv/PRRA14mfdUeOHNkCrO1a1hZgnWJdSEaotYYjR46g975kWp3Lh81+ZK3GOpU/LDPxz//8z3jzm38Lf/mXn0TxilqqdvpUppDAljOdG0HTdJ0ULZAFEQyTbHNDKRPH+NMxJ/0zvbO/LVWF0pPTW4HOSa2+JhjLhHtdevNoZGeXX+8EbiU50cZoAwDQBGGOBj6jiRlMFM/RNTic34pRIJlFg3dz9sFFp6dn9PwlZGLPEX/ASTtkYflzdDgcxRwtgXk9w4ujVJfhnEAyLQQsGMbqpSB7UDLtg/FQEng4YjKskoDRw5FpCDSgA+vsmJoDzlww11Rf6vrrmqwjKPBFUoPyw8I6p/msglMGHFZw9fIRGTCigIZywC0Qyhgz0Fvm7sx3ksl99P1x+JBAYwlfzcFwYrlWcoCeHFJqRxag2iT2SX6iQmA0YixyyIGmqT4BP1bv8BobzJRIJPRgvlTopiEygdgUQpOT9Y0pHgAKByn6GD7AxtAf8r2l8RqDGC9Ikk75tzJGcOuAqaOM2xlAW5hBZum49vufeb/v41HhM6JhRotEa20BSuv1Guv1emG5xr/BXvXeT2ugvxRZrlPd1G4lwlOvrcl9uy7oGpLY7u4uSinHZVqdyzrfgZ4XemUmPvCBD+Kd73w3jh49plobAilHUdmxc/S90M8DmaZXq0lBnXXJeurWUVUqaGKpSjJINKNyg7GigtwRCOowpbFD2VZAp48ogqCud3gp2qACffhpVDNjVshsdaeBXvJVSocbiefDbV0MyHQ+NkbIKTdmypaG4kCGAdaY5zQATCdoGIyYGTf+uc/o0VCmFaoZmBqvP2sG92DnYAbSHAhGVMj3DesEfIpOZzlzJlCG/AQUrOAFlPWCRcQZwLqvGRoKllG7FRg6gIlp+AIOGNlTYWQMM2jGh8F0fOpx2ZQW80qhl0uspcYYgJSxe8h88kI1Jc5nJixZkTMMTzmM7hF8vFHGIsAEqrH+KI3J+/SZUc50hYCGNIoRkzjksaLvk/0ks2pd59+KPGkdFqSWbFwSmoocUimsMDurbwqgAZn/Y/i1YmGrhosNyCXfbbQOaBJjYRjp5dK1mQqeNcMjn3ANrvyXV53V+3dMN0cEDh48uJTKD2lwMF27u7vLY9x9kRZPZMYG2NrLco3H7HeW62QS4bh5vPLKKy/WYe3vtfVgbddY55Md2ltxk5nnLdNqPwOsvQxWZuLOO+/EzTffgr/928+glgm1GuUb0J/SGk3pDZxAiyzI4IboxcHOYFmtw+AFgPoAuX/ROG5WF7mqh8OKoYUriUEzYQbexUNTdVkp+wSn5CBPlalWh7IQodaQLVsCXrUZ9nGXFZsNz1Qpo/0hk8XGkbF4o6DnYjLrc8OV1woykDnoIyqAZ6D1QLaODKDWSUXIzkDQ7EAy0jzT1WKTZG8kZaZ2bCqDlCFTPjcHK11igIsOpDsSFV5ZhRPRMdkBfVh2BAxzWxM42ZqgwwmWimSqantCTJVzZQ3A8Eu5wcDqIYIlgo8MQ7GRaE5jPFLnw+m76r2zsNgVeSA2cFTHMHoC6CVhLTD3GQWMXzB51XvmJs5h+J0UQsseRE4cDkDXg9JziGVEHyXKQ+IOyYgCtdBz1tSeYUjWuZGF5b8L0BOYKRYQRlY2XYwhQWsTwHNeMkgU9NZ4/lWI7QKMwzTfdV26GZ503Xec8Xt5fH6NsOPLL7/8uNgYM8M0TcvN4l7gNKTFEw30w8s1pMWTGej3/v79GhNxsinCLYO1XWNtAdYFXnsrbqZpwuHDh0+aaXUu61IAWJmJ97znD/G77/5drGcyTpQNHLVwUhCSnEYw5JA43BO9A3UCogV6K6jqYoseZCPmwqu4g16WHtq8xiRfYqqJ9Vpdbkk2yeRNihbwyYCZIMasiC2yhUGJlqiTk3EJjfonyPrwyTL72yvQaUxHH+CKjAPrSGTChtgUGFACTflFzOxucJv2hF/qMS1xrK+B5EY/rVbyYEmmkzG+OPkNdvPxugh0oHPi0YbZ2WjwDtC43bMR6KWOI/R4TTpmh0I4i2S/hMeEtMRUVvRbBcNK28xpyA4antMr4IkJBRmUK1smipE541QfIzlc4AogQOkAQ05Ncht4/oaPCpJFR8kykun57tALxJ+LzinJYhW1FmZ6+UaogxXWz0hWFGemaT0bQiVlXYwcrUGU6XqxUScEybWsM7IhgRoNaNk58UfwVsTmpQq09Z4GFMaaKAMkgiANyXaABCVjArZQ5ZNkziwYVeCZgZ68TjMTj3rio3HFNY88o/fxXklwtVqd0Y3hXqlwrL0G+tYa1uv18rk1WK6TxUQMsHW6mIiLAbhO9Zm7DRo99VI83Dk97lJdW4B1gdbeTKtx17fXCHo+1n4GWADwhS98Abfd9lb8wxe+ANOE2jBKyyetO37IOB30/iT9TjEkNDFWQywqzk2UuUOQzOXoDQAM1kwlzol0F0ijBwnySq2KghoLwUQOn3KGttyOYhVzD1QnYOGmr0rmhH5/pSyVQEbjlBsAFPqmErHxv4i9GMAsjRUvpv4/PpG6yGRkwAJtNsx9hsNRp8IB/JQ7SVOLJhDSksdJMzd/xjOZDi5Gx4ZPDPRrhfMYIzhRCCMrRyZHHXkCX4mRNZXottno4cr+SmCaKmRWQvak/DYDu8bz5ykArpyoVOcjzUgKNA1bjOUoAm/pmiwsMu8HEIne5UuyIJh1HqPLz9ST586d11kLxnKQfFShdSR8MdhDkp+Amzt6b6hW0IaPyni8S9yD0V83XmOaznWdm0uqhUCZqbKGrGM28JyrZLsHodVguThosTG9L99feiKh5+SLMm0azkCaYi0I/Nwd3/L8/+GM3r+ttaVY/vDhww/YzjBkwgMHDiw3X3ulxVPFRKxWq+Uzbq+f62Qs14MFuk4mEY6ona1EePKVCWSevWqzT7e3M1pbgHWK9UDku3meceTIkcWrcOjQoX1tSD+fa3xovv3t78BHPvJRrNcN01Q0zVRYtNwTXgy9JUot8j5NNHCreBgYYIDRDMWZSO3Dn2O2GIGNiIFTWhmopbA70AS0OCBIyQpqPOnMO2IWESMZoNF7etNVaaPOPochnRJl60BxgNUjHYaqiTBNvmXIrE4eJFNTYI3Hstg2w9DNYJ0SVwG/b5z5Z67ROtGShv3J6zgzCCjGIlg0zNF+iAHixhoJyn5G1os5XyFPuXKvzMRqAeZNXjGZ3xMIjkHCU313I0kdzFXKnohUjpgGFUy+N+ZGsZA5J0qH/PkBSAlS3RxzT/mhFE2hmAaCnQSSXwsYSo5wVnq4rNKTl+bwZG2NOdB7MJi2VEYYKCpj5IXRE6+E/sIPf8/UhCbZJgcZTR+RDUNjDsNIYE8wowwjqd2AoVF2XTvMSuvwIHtVJHdz/mHInzKyj9wtgDKqvFeITW4XBK71IqI4QTdlR03FSgKNLkBWgKuf/A244l+cHgCMm8MRHXPo0KHzDlgGENp703m2MRF7DfR72a69f+PBNNDfe++9y/naru0CtgDrvK4TM61OVXFzvtZ+Y7AyE3/913+N37r1LfjyP94Fd8dqKugBpHUYAuswZBagafqvdRQv6H2NUqpkn0kGcEMPJyPRgamSpSI4kVQHyh5mrqlDR1OMA0mERA4gB6iEWYbhEQpaxug9mRdHso8vkkDJTF17iltwdsEFQt4YGrUDDlcnHKwJGMp31CltWUqmlBvZQRDj2owHTIs+IxvBzFQm1FoZedCAtAaMZHil0Gd2/g5wytIcsCrDdqYYDXb7QaniXUCRNTRd0ZQAgt8YCeVk05ygzAgoMczgprDP4XnC+HkFZWYinOe8cCSO3XhwBGb2CYpd6X1mPEWIToQhraAYNGSgSUK9jmOqroT8fknAEpnAbicfOFWBPzJVwxDO6yYQQ5rsYukwng9fq2Q2KSdJBXAAQ0ej0V/+raQHnwnsTrmvgOd8hIoOa7rmFAhm2Rmk1w6aKlSEhyTT6KHHGJqM9jFESxOr1xj3QJbS0XtfmMLwGK8snvS/POO07+HeO3Z2dtB7P87I/mCss42JcPcFcO1l104VEzEecz5YrpMxWF/96ldxxRVXPGxups92idQ9p8ddqmsLsM7DGplWR48ehZnhsssue9A+mPZDXc4wwf6H/3A7PvLHH12Oq7gjrGCaHBEdqWwmSoGpKAVD7wVmheP+MJTC6b/eyby0uaFMBT3EgA0DMUboj+S6UFmxFfbFhVidMjw3BHBj6gtGAQ8xgiBz8WAN+DP8OCbTN2t0Oub1jGmqjIcYmVne6UUy9uuZczOkVUiVLZLBXJOElClDDAiNTrudcQVeDKtp4rnK0OQfjwMe2Dt1ZzCEg+AkGFGAYsukoPzyWgQWYxqTQK0OvEr5Muk3GlfWkGctygIKrDtQVTit+AksTJktqeXIFJADTfthiJKwqMz3Mk0IlkBPRnVIv8Ou0ZQ+GKSJaIQDEsaf60PTM2cRdqdvqkxFk3cA4DSzG4SEBAaNfX4ZtoBUJDg0IaC4VO/IBc96Hd988LuqbTQZaGnyEZJdSsMyrLDkmhlU6kz5jios86owHh98bFigMiaVWW/OAm12Req0ujFsNgngvPoY0KTsDuDrn/aYU7JXmYl5no+zNFzIm8MzXSfGROw10LfWFj8XcLz362xiIs7FQH+ycOctwDr92nqwtmtZZ/om2ZtpdeDAgQtCp59uXWyAlZn45Cf/Are95d/jnq/8f8uHFYt6O8wqWu+opSDCMdVC1kqp6b2lwJfM33CUXlAqpbtpKjCfgBw24yHDJVCH9DdAjNrwjHbpUVickq0iWKPD/2XMAkEFOw7LtGL1jgv4QPo/lUcQPDCvyiaO/hubpvk6jDgkJLLIb5ZQ0Ggu3hyTV8gSzCUKQ2SjIXnd4F5QivOc6RyTCePmDGMRMqvqCDYzJZgmxMhp2H/09UVKVtU0ITjVWIzHgMwFEBT9TaY8yTRvsbwnEhwAiNKVHTV2eRFNQe+QAUwSl2TaesOEEZ7K88nE8gHyJOmaAcHIggmMP6B5HWh9jZzlZXNdazKht3kNM6AW+eBieKWGYkcTe7cELFBQKdflANdYsr2gWAoryhbrY+iAXrbFqwWeswGc6FPja82Uet4QoAugFh57V0o95eRRB0QAP2RksmwKRhWTZtgcKwGl2FiDvHCUCb1BgWECvsXxlOefPPdqxMeMQZz9bGnYC6KGvHiil+tkBvpTxUTsNdGPda4s19bgvl0nri3AOs06HXgZ0zUj0+psKm7O57pYACsz8U//9E+45c234C8/9SnUuoK7UZqLgBWgNaaBV2U9mYm1KobeOurkqBMzqzI7SnH0PiPSEY1m63ndZD52RVHRb5LG4lvGCaTiBMhkMbhRniwnE2KewCSQ5UbjezExF5QQx+Qe0IFSF5CFJpBkvshcqegEBJZ08x4JK8y9YshnUk7sgoZp7C7MqglFTs9lAq0nMmZM04RSKmVKbQBlBFKaQFMBegdBzjCNZ0MEpcGMkd5OiTPA6AtCoSFyOdwoDRYZ7QHKUiMOABboC1Aj0ICxRJoSl9Cc0FWPRIBsTDX6o4Ycm5LoEoaFfALN/WnDF0WgWyXv2qBjQOasMmGU3rVg+U6fG3rZJKO7QAksSNkZfV+As5jZASRZtwGWIVAMxXQsbJ+5Mrr0HBDsaWyx+M2KapvG+TBJrpHB6UdPxVDwawgOWaQS7qPnnmuVjNZg4GAulmswYqObkNdNeMBMMufGVMZEew0/eALphm/41sfgsqvuu/kPI3tmPmAj+8VaDyQmYnxmn21MxMkYrFGTs1/B6cVeKZb3XB53qa4twDrLtTfTCnhgFTfn85ge7L/3oQ9+CO94x7tw7NiOzOj80GlzQ6kVvQG1OHoEe/QiUafCkE9MKIWddRGAl1iCLM1XmABYLegxxtw7MhoaXBsQQ5TcC8w6SpmAnrDqC7tiLm9NUn1DGqyl/DGczBqhiyZA4alqFTEV1ck0DCM2x+qBmGms5hCbJtgwohx0HQwDdBO4GwW+ctAMZ0GPht7IVqxqlTTV0VHgNj7M9ePGOpvaSaml0VmTNvKsGIrqmr4jmOoCR+NvCwQE0HosuUnG0CwBwVzM38McT4DGAQPX1CUBE19f+MZjZZbo4ERowSYqwI0TfN5oSIeRR8voSxeflUmlxcPUlZJlschvaUCtHCIIEEtZEaOUhnXfpQF+5msId3hRQv0eHx1U9BMKAnUbIBTH9/np3FmmYkAIfLwZmnWYgUDL+ZxJI5INM4MiRVxAi+8fDwFHVTwlqBCbyycowOaSWhn9xeNIK4jc+MQMBPYQW0ZA7UtMiZWCp/yvx7NXw9YwbhDPtU1iP66zjYkY3q/TxUQMlmysAcDo4+R5GxLhdp188Vbi3B53qa4twDqLtTfT6oFU3JzP9WACu8zEPffcgxtvvAl/8zd/i1p4l21L5YsjonJjUMaVgT16xSvvzL3S0F6rzLucIjRMw6KtzS9RnZvoVCfMc9U0FqgLwjC3mVla8y6sOObZmXEk6Yw9fw1eJmCYl4O/g3FZkvaUXZXpcEVdebKqJTNQS0UgBTgCGl6Tn0jARRNx5vSIGxLZgFJdIZmG6iAj5LQo9zkQScam1opoPO5IJYunqWoFQPjSgadwd5BlAhDDTO1wmf/ZiZiqlkkEVCljHdEZ1WBl4DYyVWNqDpHIUU4tdBf6U55AVpn2JUuNAT0pjACYIO8u2RHsxItkqCoAWAlkEyBzDT4odkFYlEyaL7+UrAF5K/Qg0Lak12p0DALAAYHnnoEAOEkor7O5s0xa5FjR+8fA93cR22TFFu/aSOdP9eCYzokVFxA19OwAyCZ2JEoKrAokRya8b8zp5oYOeuVohieLxTQQMbMCvTTmjywuMHZDbJUJLXfFbpj8YC3l4zPDNU97DA494rLlfTyGcYat4WLfID4Y61xjIoYUuTcmYp7nBVgN0GVm+MpXvoIDBw5clOe3XftzbQHWadbesMydnZ0lyfiBVtycz/VgSITjHPz+7/8B/uD334P1PMOMYKG4U+ryQj9UAUQwKfLAYGBvHGMFOsGEakuAhJeKUKwCkAJe3OBqMaz7kO7otwrnZGFxJaILd/UE1ruN0t9s6AWaDARKJT1tlouhuEeHBzc2TqYpeypzkdKKU1bE2Ihp8CLHFHXPyPzIOTLmRGluK2S0r55o2qjXc1CqBDCVFWwq6HNnynYasrgIFjIiGSkmR7ECAKCC6YRv+ukikNVgHVS8FNYJBXqmBQKMEygaEiBzEnq9yvK3MowVL8UkCXLiMhKUXJOgjWwNmSgMn1aQKWSWFFCK5BSX+T6w9DbCGzIcc86YzAkEy5AGB6hNpak7OgLRO7I3eC1kRc2X4y4AK5Y8+PoU/X3+Nqbgy++XoYJrY4AqigI01GsJ30inSLGVrtc3DV1slo0ssiUjjP4xTnQSIJn8UYMaS8i4b8lBCVJeyisbEujoQdR7MNQlCEeWFLgHQaqYthExUaywraAWPO0HNqnt6/V6MbJfdtllF8XWsB/WucZEDCmx1oqDBw8u7NY//MM/4Nd//de3GVinWZHnNkV4Lo/ZL+vh+e46izXkwIg4bxU353ON9OgLtTITn//853Hjm96M//bf/gHmhR4oiLGAqBCwTy86NvKcAU0dekzNHl6dRXvhJhNkvFpjB6G5M4DUA61ps0BfSpvdDb1LCisyAjvT1FFZDF0KYw9aX8OyYF6zo9CtKONJvX6LfOUKrwQWaUoRDGk+UgM4iYYB6AKucmp3iEnqS6glJMW5wi3NEm1NgDfVwk28SuJyMncdQIlYUr0N3JAjsURLGLjJF9d16Np8ZR9LYBnrJ6UiSUusSlG4apjkQ0le7Mzja5TRydCAEmeELYb/YepneOU4RjG5ioGAvG2m16dn57QgAFR24jVTd18kSiW4CnnCkKkKGA5LsKC6o88E337AUTAxgNRl+gbjJCIZ/WEFGMGxZNcSPk08e8H4/8GWzW2GZYHLfB7eYQ2SmQwxJMbARv51Ac2uInAjy+WWGmIgoFbXN5NFDAJQCn4duVdg7tloDxiTiZF7/IfGuIXIUFitAYUxJDToy8QfHUXG9n/5jG/Eoa85tNwkzvO8743sF2udLiZinufjGK7Pfe5zuOGGG/Ad3/EduPrqq3HzzTfjhhtuwGte85qLceiXxBpOh3N53KW6tgDrNOvee+/FsWPHME3TBc+0Otd1oRis4T24/fbfwQc/8EH6kEplvo4AlTvzdtj3xrJcAgGCqx7gZi4TeW8DVAES1Fis7AXRNwxScVfKt2kaURu4wkSjA17ECgD0TWUw9iAoKWYCBR1V6eLIMa3XEc1gYC5XMR5/H+P6qi5x4yRhlbxj7jRLKwRS3JEKqcf4IHv/WOaLZTwfvVFinFk8PB10mqwxMpz6wkJYkmXiIN2YxpNzq2/AUZHHJ7PBWgUrhriT5zKZNnibTsmrjbOukMrBkBgZmQZDlSzoxQEQpJqM7mk0aaemAl0eHwKLQDa9hgIZMChSQjESAKCaG5I5St6uuksVmEhlSSkNYrlOGLEhn8yS5yX2Jg0oG/9RxJjCcxRLoJABS3199F2yiLtjVQ9ychCdQDnoC+yZlJsFUmkiJwOVo6twYngu9b3EJpMCZPMwgDu/3/swSI9QUcj4DngWFUQDYRwaqEY/It8LtmEYDVBgFl+GRh+im3K4asHTrvv244zshw4dOu+NEg/lNW5g53lGKWUJEV2tVnjKU56Cj370o/i7v/s7AMDNN9+MT3/60/jO7/xOvPjFL8a11157MQ99u/bBemi4Gi/QWq1WuPzyy/dNJsyp1vkGWJmJz372s/g//49X4/3v/4DYKm4aAxx5MUQ0sShdAZ4dUx3SlTYASSetxXIO+b2Jnh4fWVUEVO6O1juZqRgmVHmOSqEOyIjxpSzX1D2TCNbopJgLc7iKn90rvBomVW+USpYMkmNan9HmzinGCPTGYNHoAQfvYkdIZU/GP/B4mT1VTOBCU2MZQRmqdax7RzYyQtOBCnSWL1s6U79HFEB2hCm6wAiUaJCXlOpQdABkDg/mUkEmaaPfaWRbwToiQD9VB9IT1ciKDFwYST2RPYkyjcs7xfBOXRMmec9pKDdt/gCB0mAh6UPSY8HjdxnV+XKSnYpCr1giEY3PMU0hr0b5C/LQrVvTMERBqZWfWs5LgccJlljLl8VaI19AcAafP4aZ3DbANQGiVS23ilILyjShThPci3LOgLl39LljXnfMc0cGy7djTdBmZrDCwY3h0Q8X3xjjVOo1z2SB+ACCvIARYixHrMiQcU0gqgcjPuCGGNe6mDE4GwyicZDjMc/8V8DKcOTIkcXasAVXZ75GfMWxY8ewWq1w2WWXLb6syy+/HH//93+Pr//6r8enP/1pvP/978dP/dRPwczwq7/6q/jCF+xZE6UAACAASURBVL5wsQ9/363MjUx4Nv9Ot7299KUvXbLSTvbvzjvvBAC85CUvOen3n/zkJ5/0995yyy148pOfjEOHDuEJT3gCfuM3fuOcnvOWwTrNOnDgwH2SgPfbOp80/5gsuu0tt+GOOz7Ou+bC1G4zgo06TQoE7cg0luF6YWyAV2ZcVUp4xcc4v1ii0JiUpugSANKU2E5PSo+g0TwBL5weWyxQQWYlA3AP9CCFX4p2XElgrtHByC4mZ6SF00ZfwFysIn9SUZcOIREjJMyAOYGCBvcqYzJ7EVGSm3iCzIzHErLJzdQWU3NXCnepE1O5I1GUKcouudwY7lEXrxDN6Tw/VCzJhHiBZDL19w1yr5MuypCB3UCfFjqyMxm8KK8JABkZjJBPgO4jMnORRepmX5gWU+ilYQCf0ZGXYpNURmwjt0m/OySXgdEdUNK+qfKQqfm6z0uXrwuAGdZtDQQHI8rEKIZYZDRJvZJLWeeTnChNeuSYgWbI0lmSHF2etMHkCYjyAIEiT71Amy8TpuAUoAVBTuOL3yKW39FU8gx31GpwGOZOr5u5o3EudLkpQFFfoq4JGDBUdMq3yliDjPEBGBwojRENgMCX5PYRe0EUDp8qHvdvnoDd3d2HjZH9fK5TxVdkJj7wgQ/g5S9/OX74h38Yr33tazFNE572tKfhOc95zvIzF9K2camuCxHT8KM/+qP4nu/5nhN+PvHyl78cj3vc43DNNdcA4D558OBB3HLLLccREifzzN144414xStegRe84AV41atehTvuuAM/+ZM/iZ2dHfzMz/zMWR37FmCdZl0KH0jnQyIcJva/+Iu/wG/dehu+8pV7cODgSncOYlJAwNNbqKDZUAtYEFy4KfK/gd65PQ/VJ9OR2eFeMSpwMqu8OwCS4AqWqAZkcKJsiGMGAAFYUbEvnEQWEu4TYkQqKNwyG5Bo8KqJRj1P1t2URQLLUL+eASjMD/IEUAtt6tERaWjR4CjItobBUUbsRCnyn4ETh5BPx0JMg6GuHBYc1xsNMNnF8OWQq1LxA9zpyfAF0ioGgdVlrud5AJCBnvS9mRicDIassvNOvirV5jDpfsAKoHtsJCYxKgBZLkdyKs1k4KYmy9crhnxHs7qJgUyMcmkARpkNZUy98feiuap2BOo8mdbvYm2SABg9Ea0ja2BVK1KBrQZJa2L7GD8BnkMYn1Mo7Vzm/AjlUcnInrreRzgoSrCuR+eHGnAHeyaXd5mCRE0hs5P+7CYB3vQe6nOTX0wxJejwLJJvJb+a4kncF6+ZdWaaIcmAtq5Cav7IhhUd0qizqBsZev/l8rwygEd/6zWYDk44fPjww9bIfi5rxPAcO3bsPvEVrTX8/M//PG699VbceuutuO666066RwxD/HZd+PWsZz0Lz3rWs4772sc//nEcPXoUL37xi4/7eq0VL3rRi077+44dO4ZXv/rVuO666/D2t78dAHD99dej947XvOY1uOGGG85qkGH7zrvE1wMFWJmJI0eO4KYb34xPfepT6BEotaK1YORBB9wZusk8H5U0F8fcAqsVGaUm4AUApajqBGAaeElEVtATY3uyr4K/OwBz+pgCvJMfeVKmaTJ6rxS1kNykx4j6Yv52R3Aunn6bYVjWJu7Dks0yQKQbGaIcz6uhTJo6DPqxVulA0YacgchEb4H0ROsJM1YAFWtwN8xBl7kDmKYCRKH7yIf0V5CKhg8BOh+GZUtmIRWIdcullmVsvLRBJaD8oxhenDGVOS4Fkx/dAbUqK0BUoaf6vbSvkWkZtTB6OEZwpsEVaspvliHtmdFMPeIuYItvyUeSfxptQmK5litVRnh3Azzkj+M1ltGBaph8pdiB1HGrHog6H2Cauksa5l0AKMyWjDIMAI1NUv0ofQaYR6UuaUYrZIeFGCJPgSVlqxkZW6c7nfEN8sKNqcMysa5m7g0RvLbmPlNKb031UamID1uM8Fk0wQka2MsIztVrQrVWUmuQxXNTcOpIiXdD0zX8tOuevq1tOcu1N9F+tVodN9D0xS9+ES972cuwXq/xyU9+Et/0Td90kY/20luBPfcsZ/m4s1m333473P2kYCoicOTIkVPmlf3xH/8x7rnnHvzYj/3YcV//8R//cdx+++34oz/6I/zgD/7gGR/L1oN1ia9zLXweNPYdd/wn/Mz/9r/jU3/1V6hTUXinaVKPo/mjPmaaeFfGUuWO4o6mqS5TZtQwKROQjSwmsTSMHGfEQwMATg7yv/R/bVBa1MgzuvwnibGvpTZZ+k7ICNGzFZxwS9bmYoQ+llj8L8PrMkbrU78ok6bg7AN8QaCG4lnS843qFasDFavKxHV6MhK9B1qjLwfaQHsHunVAnimMiU+TVJX8uZTUxqBN+p2IDeQZciG2DKBQtguEku3l+wIwt07/EooGO8U+Sb7MAiRCieI8zVCaeW6gD/OZjKA3Or1WbbBSiEXSMoQiCOTDsiBaFEGVyQqX8QozK0qgofDlCfA6yaD/LdGAYphK3bCLIwBVAD0tdC470CUn62d6jNfA0PVz47mNcFN+0ut5ZGoqj1Jdus4pclRDUor0lPxsy0Ri7gFtafKMhCHgqGVCrQXlQME01cXL1RPYbR3zuqG3hjk6Wu9ovQGSDMffhkBVAgzdHe9dhwA/lA1HRm/endF74HH/0zfjykdduQVXZ7F677j33nvRWsPhw4eXKcvMxIc//GE8+9nPxjOe8Qx87GMf24Krc1yJc/RgncXfaK3hne98J5797GfjsY997HHfO3r0KL7ma74GV155Ja666iq88pWvxJEjR477mb/6q78CADzzmccH8z7zmc+Euy/fP9O1ZbBOsy6FD6i9AOtMjzczcdddd+Gmm27G//1f/labpVN+ox1JuVOmD3lDRtMnOwAoNkGb3wjApLTVxT4ZajVEOEpNxi0U/kOGpgtV7BwuJobfS8UTJEDmp3dYqZu7+MTiP4KAUe8ETconILMgf1aPPWP85pIT6WtyARk+zPX8x9g70GS2GqP+hCgJrw7vtmzOOihGSlgA3TDnLiwmMhbcqfU8KMOZ8/kS/imtHKrPka+I53VTqdMFWimTKgahJ3p2lGnEEXSFeCaNXJIfrfOcu/phGM2AJQ0dThaEWErVNgJvGFU5g120pHG+bNLEOQSgYMwyUGpsgi+NU30EbsK+Tp9aS8qwU6lLbAQA4WQKxYzWCuQ4ByrZjgwWT7vvYUIlDWcii+s2eDCripBwox9M75vwhDWeH9MUJDDS2Z3PtSt6oTtvGvgSjncWp02NoLHofWUCkgagTEpIS0e2WABepAYCB6NlTuYS6lwE3ycj5T517fTOG4umG55Dhw/hmf/2Oy6Jz679sE6UBK+44orjJMHXve51uPHGG3HzzTfjB37gB7bndZ+v973vfbj77rvvIw8++tGPxs/+7M/iGc94BiIC73vf+/Cbv/mb+PSnP42PfOQjy2t+5513opSCq6+++rjHT9OEq666Cl/84hfP6ni2AOthtDaBob+PP/zD/4idoztYrQ5gPa+VYE5JxRUPQK/VnscDZEcsaKZ2+q44nSUw04GiPrdR98Fkc1eps23qX+jEJlhTGGkV8CKWCZgVRSQEzKsILk7HWeHBdXUBpuIbkJtoh5ZABuMWuqbyesci1YUiJUJG976ANwKenimzvnxmhcAsmpggEURlqvQsJSfAvBpqGCIdweJAgjUlrReTGR2DMYTSw0eevWIbPAmWFL5pGehiOoBkFgawSRkf0lch68fcpAagqHJF1TbWaEYX4LDhD2sCfqCUm6OqxgBYXyYUXVjWYuSHUTIj8yUQNkbpbHP9IJnbxAnOwDxzeGKpKVkS1AczxyZGxJh+pN8qFLNuAkoL+A4o0TwZqgpmaJkbJdIgRDaBRYAyXY7bZQEk6NrlRB+W13oMApiPl5InIj1hXcyirm0yUXrdjDA95o5aSd9FYZchovA9ExDjSCnSaLLSFG1RyOmIoeDXW+/IoF+reME3/8/XYjq4P0KQ9/s6nST4pS99CS972ctw5MgR/Pmf/zm++Zu/+SIf7aW/dD98To870/XWt74Vq9UKL3jBC477+i/8wi8c9/+/8IUvxOMf/3i8+tWvxrve9S688IUvBADs7OycctL24MGD2NnZOatj30qEp1mXwt3KmUqEmYk777wT/+7f/V/43Xf/HnaPreFe6NkolenEZeIG0skOtBb6GzLkavNmP2Bq0o/5UTS2cHIwojKYUn1rlLo0ZTUA17KJkdUasiTrVIYcoucWQLrKcrPRDOzJCa3kdJdlp3keAOMBtLErOykBVB/G5RHYSbATiic34irWzpDQRhUjAwR9Y5DMFYE2B9KSUpBJonQ+39aVFWWGaVqhThVTdUyTEqERCjHcRetrrNe7WO/OOuc8N2ENPVPSXoLGf4D5VSEyRmGoGWR3rAPKUEICoz3NJPlZJNxikbpgMc4y+wMdmsrT9CY2PzckNUE7bEqhh9RK8EKjdeh157lbUJYTnMx9xrzbCAJXBaUScBKYEwBZMjmbJdKJdE0QOn1Q/G8C6giCKxjZslAsw9CVWxe4RWo6EJwebONcD58cc/gZ4mmLHI3C7stweqwgg71p9C+bCYxurtthyM9kcGymwSdmxcWQPgMItRa4G3ya4FNBXU3wWhRgymDS3XmNNjf0uaH1hvXc9L6tKFNFPbzCt33ft532c2C7uE4nCX7kIx/Bs5/9bDz1qU/FHXfcsQVX52mdizx4NunvR44cwR/8wR/gec97Hh75yEfe78//9E//NMwMH/rQh5avHTp0aEnvP3EdO3ZsyUE707VlsC7xdX8Aa9Q/vOtd78b73vcBrNfz4rkZmwHBTVWQo4l1ChWfdgAVGQp11O/0IuYqB8tFI3XvQK2StrLRmxUqStao+5hqI1gDWk+UohgIxTDYkIgAoDhMIZ+ZrMgBIEmTm2tPbprFk1lELREGVKc3LFSEW9xEtDCqIcQoMZk8l+PksZFlYQ2JjEUBrNsMA7CqK7J8SE41yii+4ZEol7oPZqcKE6XCWh0WBE09E9k7uif6WmGilZIli5zpY4OM3CnJKUDplgw3d+6wpKkcMrrDgOhLdhdV0RFvwNekSOJlpZEYmUFCDWYHSZksXGBZ0Q2ZizfKGW8OK4yasEyE6mRGZhNaUIIsFV6wFDiHqZw7GK/BKh1nybFBBjWa61nVyOc7bPthvmG0wGsyg9OEZDZpwGcno4mBK2i9sRwZKoPWzYOJGY3egV6gsUkCR9U8hdhWg6Y0zRSyaooz0etmhmhM+WdSPPPTluk/K+jZaLTXJcjJQ7KiqIZqk3K+9N5QrMPcOjwT1/6Pj9d75MztAg+3tVcSdPfjMg577/jFX/xFvOENb8Cb3vQmvOAFL9iexwd5fXbnM/jssc8e97Xd2D2jx/7e7/0ednZ27iMPnmodPHgQV111Fe65557la9dccw1677jrrruOkwnnecbdd9+NRz/60Wf0u8faAqxLfJ0KYA058DOf+QxuueW38N//+xdRa5W3ip6f8b+9U25h5EFHnVg3ww/qgugESjY2GDCuoU4seXanF6aHwQuDQpGOUupwUolMUD2IKlMSmuwzU49hWYz1G0M6b2GsOGtAMlTJQ5DHzrYkeyUjcDZKYgWpnKyiiT9OmCEg+TMXmWgp9M2RQu8oGAGS6pbrjQGk1VDBnruR0VWMmy2Ucj7G8cxZ5Asw+pKskIDbmC60RLUCX7mm6LBEMcxthllByaRHxyb0aihBE7eb/FqLAXxM3QEYZcsCkAv3lGRVFKcu8LPx+8AYIZEyUk/DswV6lGjMHxlQTPAHCJSgrCiTxJoV7EY0+vh6o4V8KpXxAoGFObIY/i0H4yAag1QNGEn5iSTrZDpeYJGUPQkAkZv4A18YJEqLeip00nX+/6XwBiIslmuS9TWFPY2mqpoAPCkjs0ZIDPBedhema4S5aeb0TiE0RJGG1htKaErQjQASo6KHxzvKqdN5nhH0JqaeXnFFPxBlox4seNJ3PR5Hjx7lS++OUgpq5SCGuz/swcLeuqATJcEvf/nL+JEf+RHcfffd+MQnPoHHP/7xF/loH3pr2EZOt649+ERce/CJx33tH+cv4x33vO1+f//tt9+Oyy+/HNddd90ZHc+9996Lu+66C1/7tV+7fO3pT386RmTR8573vOXrn/zkJxERePrTn35Gv3usLcA6zboUPpBOBrDGB8ltt92Gj3/8T5EJ1DKht7ZM/DFDyshUqdA4xDhRTaEvqDVKEKkApgze6U2TyVguw7DqXWgsr0B2bTfMvmKOD2Wu3nLxaSUoGdIQPyIaKDvBbWGWEIwILZUbGJkr6lgjqHIAiEhDWcAPQZnLK2PaeGWpQR3RBR6LV6erXDqdBvLEjL7LDbBMlZEGEEBU2GXPBFS7Y6OEGQaOork2ekj9EyACUCzgkOQqZqJUgDJmwUrmfkt6qno0YE3pz80UUAqESU6SFBtIVeoQYIVYRocDOvd7cAtM/XkeQGSXJEwATmFNEQnjyFPFxnuKliE2kzU+wzxPYDa3XbiA2GqaAJm/OUhATxn7GwVIDMvwAEEpAR8ZQAGx4YcyQq2OQNGARShbbHQ3wpJlzt2W7scE2bLjAL/iMSyDUnFiOZ8oAJKgvvTOgYlJ74nktVhqIhwKFeU0qJujyzfocHjlxZk5CrXLZliiiwnVzcGIcegIhEZup1qXOiCDwYvhKd/zZDziUY9YuvN672itLf15I5tpL+i6FD7fztfqvS+dsicGh3784x/HS1/6Ulx33XV4z3vec9Yy0Had2dLH3zk97v7WXXfdhQ9/+MN48YtfjIMHDx73vd3dXczzjMsvv/y4r//cz/0cAOB7v/d7l69913d9Fx71qEfhjW9843EA641vfCMuu+wyfP/3f/9ZHfsWYD1E1mCsMhN/8zf/BTfd9Gbcc8/dACBfVEetjiZZzUzgqU6LuX00zHPzo8wwVUkOAEMb3WhIV2Boa0qgBpkbBlM2STyOiAYvBchQn1qBu6IdtLtTLqN8l2rGNYB+LGCR6Djhpw00OsxkeseCx+jpcQJIK45s8h6ZIcUcqaWXTEWM9GsxNBgNh6CkFKpeMWC1KkxMH8RBEgx2p1Q1zPtuQPYmSVTTd/JopY3ReqAmE9YtcrmzcwWWDjnK5b+BO0omUCYyYd20CeemWmaemarvkiOTvqoR4rpnNpMAyQaP6ehoKFk2ae0QuxcdMSRIeZVc7JT0RwVkGgrd3YxjSIKkjEBrjcCzGMrKWT6N4EQkxmQpr6EIU7VObjx8GIAtUUZahPH6WJhCnfiAQMvIqNIxIYGc9eKUwXoxxmEUV7vAL0F4ATrrjejTi42JfUyZJUNMB5NUamGJs4Jwx7UWuXnPZSQHE7IgrKOYI1pIAjUwd4KZWsPfNa9n9AxMU+W1l7YwuJnAgctW+LbnPu04ELX3c6G1toCu3d1d7O5ScnH3BWw9VFmu+5MEf+VXfgWvf/3r8YY3vAEvetGLHnLP/+Gy3va2t6H3flJ58Etf+hK+/du/HS960YvwpCc9CQCnDd/73vfi+77v+/D85z9/+dmDBw/iNa95DV75ylfihS98IZ773OfiYx/7GN761rfita99LR7xiEec1XFtAdb9rAtVpny+1l4Ga2dnB7/924O1GqXMvFsvPoqVfZFMapnQZvX+gSxUimZhfAIBy5j8c7EVhk45MTqn34yTeUUf+MbwKE080UDvBkyTQEaO0FAxCUo0D21wDspmnIBT/pAprsErMKLnFMswIga4kUlmQ4F3hkVSuhzyHWTKF4PjY2oP6kVMJYzTu+bJTYjKqtgfSNKyUe0SG9AlJgh7XpfESD4PgU3OorWUIRwVZh3VXJUrG6CXC8OSCFdUwQCV5liB8l7XcwWS5zbXGMFaZgVeEsUrTMwJPWHKekKnZ8ulN0EDBfLO2eI1SpiowYVxAUEBq5Dow3OvgLGnTwdG0FuMwZ0WCu6U1y1SgHyUIvP6JNghY4Uu0D2iGLqqZtI5GeoJD2CY/pGpvC5JboVmcqbt68UCPfI9hyytdPegQB0F5BYb4xfcCM6iic10U61NAt2UZGHLzQjcCaZLIkk5IkuqP5IyaohdM10rMGPXZKdhLZN+talOC1OngdbFyP/Ef/1ElHry5HAzwzRNxzE2g+VqraG1tph6H2os1+kkwbvuugs33HADvvjFL+JP//RPl413uy7cOhvD+omPu7/11re+FV/3dV+H7/7u777P9x7xiEfguuuuw4c+9CHcdttt6L3j2muvxete9zq86lWvus/Pv+IVr8BqtcIv//Iv4z3veQ8e85jH4PWvfz1+4id+4qyPfQuwHiLrYx/7GN75zndjZ+coZQ4mTbLAN1KbrIm1MkTntFat9CKVUrkhQl15Q55RNhYN4V1MTOEm7lXRC0x2T0U7xGLupQQ5mCeXzEOQQxaAMkiRSSsWicYxmBxsGAYrMqJD9JEMzTakKjIgcHqI5uyomPQ7CMCGoRoQgAsdH8R+wDDPDdE7aplQpoolIF1AatSdDF/Z8EyN3w8o2kBAxQUel9wmdJQsg1iBg3LqPOQsbAz3CmFg4IA8ZmT0lMfE5mBUVy6Ugf4d+XoIuTqiAWEz0BNeKwwN6EV1OGSIep9hJlDgA6QAUlcXCbhlLGbtBMFFyvjtVpbCbIC+OoergvL442cXH0DYEJpOBfp49cff6XtkN1MOlic2gxUjWkJRHAKoTFgX+5ViTBf2UUDeBYRHeKpATusMeUAZvi5WMWF4/zLZpyikxjDcLiYTGGRpIIEG3uBkImbiWHO1EvQx9CEgExzCyOyI3hnwWya+BwTUMzm96llw6IpD+LbnPfWMPyf2gqgxjr5XVjyR5Ro/O0DXhuXe32uvJHjo0KHluWYm/uzP/gwveclL8JznPAfvfve7cdlll13ko314rAspEf7Jn/zJKb935ZVX4i1vectZ/c3rr78e119//Vk95mRrC7DuZ+1XBmvIgXfffTd+7dd+HZ/5zGdl6K5ANrWFF7RITFNVHIOjFm7gXiRvRWdMgyaPXIwSQz8BOVPkyynKxwI/5GXwzmRIaSkF0Tv/N2hEp7wyfk6bke7y3Z0xTkO+Un6VGWRm9z2TWZIlnXfuTJwfAE2gLkxF0xy2r4Udc2ZMjreUDycoZ/UMTUFunus8rwEY6uoAExeGqGaGloyjAjoiWOI7QJ7FuNPqS8dcyEieoOw1ioodNL5XcHKzm8JToWk5oQAeu6Svpqwq4+sBmeHTKAFjmKd1XuAEdBECq5KsQmCVPqOGjtE5aPBSCFQtWTUk47Up1JVyquIIALBt0TncB1bvrPus6p3CKUi633jNirHCMmkZCMisnQnzYM2Opjs5qUr/kmu6juyfctoEorLE4mcaGV7whPcN2+NEshvQ6Eazeoa8fuxJzHQ4KHszIDWX6UsrSeZMNx3QM2BgvDMcFJwIdYDXrVjCUFKFSwbkDYymMDH8eXzd57nBwPdynZwsY/IJECw6xvjIU777iYtkea7L1ZpwIss1pMWTsVx7pcX9BLhOJwlGBH7t134Nv/RLv4TXv/71+KEf+qF9dezb9dBbW4B1Ca4RvfDRj34Uv/M778CxnaNYTQdgllivyUL0CEUQOHrfXaRBAFhNK8wzJ/qKzOJmDGUEqvwv/Fub/Ct6gcyA6C6zvPxZ8gqNhPauEmUjiqOPRRtbKYaIJvZrE6RotkkpNy8oRpYh4DTE967OwZRcSTErZdDmZCA3t8hEqb6xEUHj9mmwYHp8dABu8MowyNa7zM/00pAXGmEIpHgcXX9P3h/TpF0kypCMiKgWpi3TkYQxAmqQjFbQe2OWVBqKaTMPVQolzfss+IX8MXsM35KjXEZu+uZGZhcgvlDmfoBTiwo0BU94C0qDmTxH0VhVY2Go1TXNN5L1Abgv0Q4pc386gU3PRDaGXnpZLX4ePudUICkW/1umQmeNEluBo2N45ZiUnyPXQQMCgyGi10seLDSCLgNQh+QJWOegQ3ISY5FyOak3zjOfIwF55zlMMnEZTFZHEiBnUpZ0H2xYLrEmZra0BZhAU0ruRgOsio2Vb84LIyGid14OZgSXLdAbq5BKrRy4kDwJB6zTdO8lEd1x+MqDeNpznnzeP19O5uU60Tx/7Nix5XsnslwPFPCd6zqdJHjPPffg5S9/OT7/+c/jjjvuwFOfeuas33adn3UmU4Snetylui7OO2G7zmmNO8s77/wSfv7nfwG33PLb2Dl6lL4TzrtjdWAF94IDBw6h1BVqnRbmKYLeop2do5QgokmWGSZ4MgcZIzx0UzHDaUOooHmTkbQBbgz0jEyV1hrM6DkiU8bNiINyhVU1NnKsyFztHXdvkfIAqdNQRdKRBGX0+8QChBhSSqBmSnMnE0YpKcUquHdthnxktE7WKhI+GerwugiIJJj+niZ2xCtIDzE5fjwHVrY0moqT4/4kLciKGIjJXCxXZiejAf66ljESMMikwAkOoJ+JICuYmucTexcjmmKAKHUQMmiUoZl9hKMC9KIJGJNlKihTxVQKSp0Y+lqA1huOrdfYbR3r9Rrz3NFbJ/ulsNAEPWJzMPwyM1GnCWUqZNqE7ZDyKVkQWDEiXr+jE6DZ/8/eu0fdVZXXw/NZa583AQJiJChSpCDgjWK4agjaclEQ8KstouPTgVakDq0KKrW0HdTW4rWiww6rqFXozyEd4Cf6sw5Ah1oHCRcFEpQAhku4X4QgFxGSnLPXer4/5nzWOQEMSbgk4LvGsCXv+55z9tl7n7PnnnM+c0amPJ+zbwn1ZErdiibqDEUdjUjyZyXuK+8h6ZTb1/dkyICk/j7IX2UEiw6UEScYmBVG/xytXPSaNXbNJGNW+sLIToXMTdDTEuX78FJxW0sJZ77ywbQfc+Z2lFoxHI0I8pORhY69YYpm6IPdZM0Q4HjZQS9+ysBMMFwzZ87ErFmzsMUWW2DWrFmYcd29nQAAIABJREFUOXMmUkoYjUZYsWIFHnjgAfz2t7/FQw89hFWrVqHv+6dEAYjg0NFohE022WS14NBLLrkE++23H7baaiv8/Oc/f8rB1XHHHYcddtgBKSVcfvnl7efLly/H6173Ouyyyy7YbbfdsHDhwva7FStW4C1veQt23nlnvPjFL8ZZZ531lG7zk7Eqxj6sdfrfht7wx7GmGazHWBsLhRzTQN/97v/Fuef+ACtXDjE11aHvRw2chO+F3pweXRfyZsJgMMXARDDjqdBRDsdQQClj1aoRuq5rLINSJGHm6ATSYMpTEtMSUQ1kyghCUvhaHOwwtKRpNdrDYQnZKqrn5sEhEzRCTlOqC1GvmyekVDWdxS/6Gh6oAECmkXjjHX/KDM8kwyUpj1dBBZLS+F7LiOwQmN9l6qyjKV9eE6M05k6DNaySpanduJqxSixS/oNZbplXRSZxl9maoCurc9h1d+btPWQkMTMFORAHAjmKrUNBEfsDBONFBixXen9SHhvFk1ghd5eNjCwlxPbxHI+KpAzrnJEK1QRw2Js38hFSyco+SxoKYOFysoxuqgNLiDU2MDZAEZxqso9Do6ZtUWyGOSMU4ECm5NoLzORMRi72YURuIAG118U7J56yyu9KKtzmZCBBf0JidhjIDCag5ZSlSkAdAxClVjJPutkgWBRIgkvaluqYgdAiLUE3EgxNDS9hrapkKpRuSyn0mpmjLz3ME3LWuWrBmOm8EPsYMQ+WDZtusQleftATz16t7VoTyxXSYkREAMDDzfNPFDB09wbuHk0S/NKXvoRPfvKTOPnkk3H00UdvkO/zI488EieccAL222+/1X7+93//95g3bx7OPfdcXHrppfiLv/gL3Hjjjcg54+STT8bMmTNx7bXX4sYbb8QrXvEKHHDAAWuVUD69Np41DbA28hVeq2uuuQZf+9rX8etf34WkqcC+r0iKKvAGSJwXoZSb9ykmCMMv1eUMGxhKKfJbAdBFYDgc8ssvxs9LQtdx9D4njEFEVK0gvFVR4EzDeEQvpEzgUJ2TZIwWAEf7rQIK5XQA3WDAC0slHKNhmanmMMo7pfDvaukpBSHF4BtN64km/dLz4h/p6knGdzNqi6UfohTH1FRHOcZpOHajHwcOyWGGlOhit6BkjFU3NNtT3qHZXFOCiNSo4CGseXC4PQRaiDQDA+AslXZYA6zB1lHSU75VJMMrnR6gV8i8IgcYkoKJpEiB0p6FLE4uzQ+XNAnnVmX0FrNUJDXKX5ZnDFALQWNWbU6NLCfjvur7np4sTcIBSoaPQQRoglXdlCEzwp3HMcl8XiWbgUGdlKbjbyIwtcAL/82IBZMgKmmWjeWUSXWcWGBtDVQXncBkAF2+LgfAKJFaCJpqooQLj+MTnFf0MmqM1aCg3ISkvk7XZ0CfMD3GkLuE0apeAwMZearj56sSBEcIa3FmYUHADZUy6MsPedlGc/MX69G8XJPm+dFotJqXK8BWyIrr+n7WJAned999eM973oOrr74a5513Hnbbbbcn9s2uwwpg9XAm71vf+haWLVsGANhrr72w7bbb4rzzzsMBBxyAM888E6eeeioA4I//+I+x//7747vf/S6OPvrop3bjn8Dl+t/6PO7puqYB1ka84u7sjDO+hR/96Ef0+uTwZaj0Vr4oXn15px0SQym9WAb+nhlRLhmPRl7n7TdSyvQmVfFC1clOeMVwSF9U3xuSFbI9zsemyBmCJKzKkf0KeqZKu1CTFcgJgSh0wZLMWJ1+I3FdlOgAQJ4qS8rRcmZMOYFjqdTdzAV6clZauCHZYKK4N8zdnKhLOSF3xrJdeb0Y7hAmHtbaVDFt2hICLosEcV6YUyVLaNkZq5CMAEdZS8WZb5WypsZsIpMrJFhpXiZJz1o1EXWtmHCEwDCn5ATjisG6RECQaAjn+cP934RX05dVJRiFJFvzgoSOIrMXeMlC5k5bno8LtVMCyioNIeSMLmUUL7DC88ttCPQJGBEodpmsYQdDRU8fmCneXdljsLHkybxSGetDJsyUiy0KkXXOxJRedlOHYmnmfIiErXAyQeEDFAtV4fIDCmRZklleCf+9mDaBVXdH7RKsJ5jmNrhAoSmHC8xe86rQXE1xVgjk67jUglVDAvQ86JCQJ/wpHCIoxVoshFXTsAcPy+azN8XL/nSXJ+pr5klbAaK6bnyZeSyW6+G5XL9vrWlK8LLLLsNRRx2FfffdF5dccgk233zzJ+9Nrue655570Pc9tt566/az7bffHjfffDMA4Oabb8b222//qL97uq4/RA/WNMB6jLUh7hLDa3XllVfh618/FXfffTcnALuEvu8BMUSc3OsmTOVAq0GBJnzEoThYueJiDHI30SGIDHdNhIFj+6z7k4SlO/TiIwCG0YiG4Jw5TTcYdNoW13NAZmAyPiGtiCqDwVeT31pyJMQ8CPDBKZ9wKpF9eRrcJ1ipIX8BAIFN35dxKKZCI8m0FE53OchYQeGZUVSMii5RqkyZgCLBWsp9qwnSPqvgvmaWpMGck2HmjtrTW+NeWUhtTl9U7y2M1K2MQUBFk1VL6wyUYVrxAQSjITNJqtKEoifA+6qk8WDelDMl03VtfiLlUTm9PARejupF/YQBdgpo7B+DulKBflVPYDDVEcglR6oJaSCw5ByAiBTzYT9CNsNIoDpZB88936NAV66ZRvcAPA4ZwFU5VMYSJzdYKeZixhyK7Q82NIO5VIjaG0l9uhfw7Eqst7HMZw4vxp5D5kDwMY1hdKAvE8BzYpKR9Cm8xN+bmDV5FSEgVvkeSu2RZY43T0F+Qf3Yel/sTQw2bwz0gJcf/NKNjr1a27UmliumFYPpibqfh5vn1yQJfvWrX8VJJ52ET37yk3jXu961wQz302t6AdMAa6NaIQc+9NBDOO20/8LPfvYzXvCTogdqwZTATBjMq2uKKqlc16wBhpjiKqVHTl3z41DKcDFYCREUWZ2GX5rVq9gwQ9X0VMpTNMNbx9dFpERTwikKD+2y2K5ESSum88dsmi7GcVFEkdTESThLAl5QCrnrMcJoZJKANkEozxjlK4KIkD5rpZGZk2kydacE+qzJjGRjz18ESAbLkVOm2doiIdwlkwYAgvKvyFQkn5i2c4E/U5Bmi6oIrRB6D2Tg3HMbLPD4u5bvFOKho1a+1xQ5YiF/Gt+PeVKshZ7fClAUwwCa32tlanm2TLbMx8n9jsgcC/BVm1TFeIKELtMn5jLlQ1YryMfkYhTNwMEJAD4iYCvWo/QWAeywlAWSDD6qY3nRJZEWFnYXMFGe+1d5ZgphdYMSDiq7AxGZ9QxINZWMEyY7bMQJTUv0fZXwayVrIDyZAYkyrEFhuxFWWw1uCRW9gBjBP6MfKFfGoAQi2BWUOglkE5AHlPVd6rAKoV3ncWSRuTNLjow1sPlWm2PXP129q+3pvCZZrhkzZrTvwMn0+UmWK77fAnAFuLr//vvxvve9D0uWLMFPfvIT7LHHHhvqLa3Vmj17Nrquw1133dVYrBtvvBEveMELAJCxuummm/Dc5z63/e7ggw/eYNv7RKxpiXB6PWI9VXeKcSd3/vkX4Mwz/z/cf//9gFgW151rzpzWyV2nRHTdXZs3DwPvkhO7+CrT3HOwPZp2cwDwKoN6msi+AsFEpVvXKyWspCJlwGhCd+YcOVhzwu3r5csBhrUXGOAEVzJ6xfi8vBqnFAjFJwBioQRaCCe6JLAggGlGn1ktFblLIMliBEiFV3i3AZKS5eEFoxErgrKxXNgsmARe2HjpVqWNAiUByo/D0iNlwGoHwOGpolRr0l0DFUYmCcZkKEpukppahAL3qWK/mKguAGwemVBOxGYtdhLZKooqYyzTy2XVUVAYDQEAnlHLEJa7lixVicARxcWlVKTM8AYCRod7z21PTuAggChMx5iMAoXJAoOOOVmNmQm/UAPBlFShupuqXkEDkAbch5AHioGrnAQdjTRRaal5vpJl5ETQ0jvDaF3gMIfomdIYEAoUe05I7mPvlVnzY/EYFVjuGBSqSVaAkqDnDsnIXlXRXab9YGAeFVqRQEGq0ZTg8uAJmDla0n3wdKMh5c6UO3Rdbp9fJIMn7jNU5+HXe7JKwJU6DhkUA/Y87GVP2HfOxrgiyDQkPwDNKrFy5crGbvV9j9e+9rVYuXIldtttN5x//vnYfffd8fOf//xpYwQ/8sgjccopp+Cf//mfcckll+D222/Hn/7pnwIA3vjGN+LLX/4y9tlnH9xwww0477zzcMopp2zgLX5868lMct9Y1zTA2sAr7tgeeOABnHbaabj44sUAgK7rUMqIU3RmYhDCvM4LXIAveHzBB7MVd83yo9QkCYoXk3D2pJT1+prOSkneLGt+L5It8jlBPpl4XclJZK8yBoPUPGFMUeCEWz9ymK0Cs7bIUJmrxFjMVEqRkcVtyVkX8uToS4RLgsGQZuhHrM0xcxQP1o4VLZzQcnhf0Q1YgtymAuN+iAiBkhAc3g+R8gBBx/SFjAuqGDMZlMM/5h4J8tZ8Y6UCOYGeJMU8JAvTubeLA6fSkljEMIlrsxQL714BKyglAepurDVRitR7qeFhs4rUdZoyi+R+hnBScqPMah4mbAJrJNbs0KamCToSmmI+Oc2JZJhKGVBJOF+lMEdK8nJjGEEZryCqa3jOFSRGVCirwtyQJSfaQNUwlX9bi6NawbAHOsuwjkAypkcNhl5+KzNXZpo3idItmCbuu2Ada2ii5jwe+jRQcge88vNmYJwC/VwCvZJe09AUpcGi71IIpokuWQBtFmwl0McgSaYfDcodC7N8dYf1gOe4yaDsyBBbfbadvsdnbTULL9l3pyfle2hjXQ+fEtxss80QRdfHHnsszjnnHFx66aVYvnw5fvjDH2KHHXbAK17xChx22GE49thjN/TmAwDe/e534+yzz8add96Jgw8+GJtvvjmuueYafOpTn8JRRx2FXXbZBTNmzMDpp5/eGLkPf/jDOProo7HTTjuh6zp88YtfxOzZszfwO5le67qmAdYGXOG1+t///Sm+/e3v4MEHf6dJPCaKR1q5S7JgErZh0GX0krN4cS4tgJOEm8MsgE4EXrpeUz4o6XbWSpS5TaZJLijws8g3VIp6BxNlKq9MbA+ASLBWm8eoyw7PHeCV/hxPzOGqPcwNpe+RuywGJDeWBuZtH8AoMTLgqEPOCntwqOKEIaHesqgqainoK/1Eg0H4NgRIlL+kMTDACNwMrpH8ItCVmdhuASYk6wnwVVWkJNcFEpFu7vJp0b+TO47lO5xJ5JINWdkXwwJKL4/ACuVXFf1tOyaFbI+FBGpgcrnYyWJo7BJSIkPWM07BcmZqOZTCL7+eC5SHx6uETwtkCMw5DDBIqbGewlc6l0CZDEDkjtGuZ5IqZfCHpvNSpZwb+ioqejisGDozeCcjf8fny4WVMH3P/YGkEYAEev0S91cvGZDMKlAkm8dNRY39Jd8TOy3HcQiEVEn7jYMJUMF3TTLRS6RF5vsCVJWUUzu3TJ8/fpYMtSe4SjlPHEtDX0fokCUJMi+umdjFZcYUL/2APCp7Hf6HFY45OSU4GAxathUAPPTQQ/jxj3+MJUuW4Nvf/jZe8pKX4OKLL8ZFF12Eiy66aLW8qQ29vvzlLz/qz7feemv88Ic/fNTfbbrppjjjjDOezM16yte0RDi9HrGeDIkwgNWvf30nvvrV/8SyZdfBLAvIsOC16wYoRYZ23bFF/ELfMziz6qJZm9ShcXEQWHVdB5e8Q1aKnpWcE/qeJmJHZFnlNv0UieSld3SDhNIzU6sliZtPsCwy4Fhtz8E7c/peGNhIj1bKhlwrzDpmJSnUdOSFhvlCZofeitQuSkiJoKyVCQtYFnqiAkhWHwI1obOEPJXpX3FXTQ0vwhXalpThinoYU0iUkbJYjloTTPs0fE0eMifAmABz1NTDwMqQUvg+AUft5WFyTrNZ9hatkBRZUTxiGDC+ONvYP+dw+EhMV+bUX+7IrnmmV6cG8EKVbFlQjEXbXnuUkugRCnlPZFHiWw6iBNYB/ZAg02AYTHWQ6Ymgo8VCMK4hKVG9+aUQ0q/LzweGvlZ50uLPlZoOh2RgEHhrH2pygCDaEwaDAJhiPEtFReEAhKIbKF8nVKOHMKZSAaAqyy0wsylOxAUYazJ47WGFjNh4cMLFYPI4mMUASbyPkNvpO+PfGtwKyqjIo8cbA1cumoE5WLXEUAD4eTAm6CONuyHdXWG2hi2etwVe/Mo/HPbq900JAsAVV1yBo446CrvuuisuvfRSbLnllgCAAw44AAcccMCG2uTp9Rhreopwej2pK9ieWivOOus7OOecH6JWMgCU1kLGGucH8ULEnr9+xIuoJflKPDX2hhEJADAGYqVURK4Saz06uFcmRpsAUx2zP6WAmVea5MtpoPwsAjFeWxLCeDQGXAHQ4veQfOJISVSAHkfirOjufICclW9VlXjuFe496GuNfjyyTDkD7vTyhKEeIFgspQcrRhKyJbRewxTgwJWtlGAoZL5a1IWjucLDNRNj987ICbRsJlMGmCu00pDcUcqQo5eZzzkqBLPwmHgMUFGQjTUpUOUPwP3vAbQSkKqhQJlK0ERmVMIUbxOaLFmmabzI8B6gqGoyNBlaInqSV8ycpcKACSM7RqsKzB15MBCrQ9N8tSr+Jp5bMie8GbRp6BZLmK2BN1QBwDQ20MNBaJ+CVQRskIFi6h2k94oeQvrW0qChDljuglxEGVG+LZUTrTzmnP5MUK8h6GcCCIpoySJXZBO9h14ku8rc2OZTNWHJyDXuuxSnukNsI8H2qAxZAp0TbGDIVXVHBvryrLTICRi97ZwCJpCqoHwpgpWfKQP2+X/+5In4Ctro15qCQ90d3/jGN/CP//iP+Jd/+Re8//3vn54SnF4b9ZoGWE/RChP7bbfdjq9+9Wu44YbrV5MAAYylBpsI3fO4k60qWeYDaAimv6nraADmJFgCYxcmJMRaMegSRiMCK/q4elQHutw1kJVzEssV/i2V34YRWNlNtVQMuoHkR4IxAxPbY2KK+VphxCd4iSm0RvpaXLT1GgYAAzIgpTZze6mc3CqlIueK0kNgsWDlcIjqhhkzGL3A11S6uQVgi+R3sk8RAprFfHkNL1P4dLSdRraFEqAOlOmCWtNEHARgUZRcHL2NC5QLlKAOEy5l3lYBkOUncwEQOIBKszl7+ZotiUDMlWEmoJXNdEcY4MyadBisX4S4xhRjtdJ6AbNky1HtUXogZxaDB47y5qHCuD4pRSclgahlGtrJ7FWZtOlYYx0PJTcCMZ3X5iiizZj1VOGF4DdrN9faN0LW4egLz0gOVYhFrJrss4ycNIjgEHvVY1gJ9LWlfO2c1XRAMJ0N9KKp9gjJKBO6o4DDHMy6ApLHOcqU+ezG1HlzStN9Dxgw6Dqa7KPMMLKsdB5WSyh1RPBnpvw0Hv7o1azg65klzN5mS7xo7x2euC+jjXStSRL83e9+hw9+8IO48MILce655+IVr3jFk6IuTK8nb01LhNPrEevxfognx47PPPNb+MlPfoLhsBfQQQvizLmTJAhJdbqIRr+ZfFiUZmTq7ZlnFVNdgO7Gw8QMslIpZXYBMuWT5mXj1FbkFdUSDE7EBfBC77XQua2pOF6jWPXBlHYGIhJEKOCgZliKqcXJacbx/mC9Sxa7FP6YLEnLkDsai1NmKCbxjdLnUeH9sDFmXZYUmHjRtRyj9bWZmN18HP/gWeb5qu43xXl6+KL0WNXqBMCiiVz+q46VMS5Qa0Ixzboluc+0T4MRoqREwFTASABI3a2gpBpnnCuoNEkzchtPeloyjHoHEj125vTJZWRUlW9HL2QWWGTiPGBGADYqI9RCCblTuXAwkjDW3TiU1WSCcSXEM4Wdajs5deqN6YNuFPqoHWp+qDgiaODSi6NTSXitSec9UEGGlkeZ4GOkKcrcZYJ9mPxy+rwK9OSckVSUTWqXf9uPKF1mOdGrRQSCjlRVq2dikXbRY3Pqxt4rUAbmMGHleQQyjzl1gEXaPqXRuD+hR5CeK8sJKJQ+3bxlvXkPpC6mSBiu+4o/33Ap5E/VWpMkeNVVVzUz+KJFi6bN3k/TVXWDuD6Pe7quaYC1FmucLbVuK1irK6+8Eqee+n/wm9/cM8EQQeGcZI36fjSOUXBv8Qe1YiK6AM2QTikoo5ZCYGFkdKJ8Ofw8jGtw+br5Hiy5/FcTdR8JyB1lxTDM09fEmpCQXsigFfp5QgYzMV8AUpc1/ZgbwCIHIYmMYUlkm1IZA7uqXCEFfQatZ8GHSIJJCOM4eCFThEQZMSUcCUhuSJ5gKfNCLdORV4I4VgdpGrI31K6ytaeByKSgTcCUH8ZqlyJwxh5DTQTAlY5vbvIlpTYVmCT7JBmza/GWSE5ZSeP64LYl9fgZDFXyL6oz/iAm3FCZJZV40faa0FtB6kSyJRrckVKrKoIBfTWoJRFlNArUjoF1cJi2UeetjNU5KWG/sS/M0ypOBpAMFRFETdAEnCgYMBoCxdvfWGbJMkPsHZYNqMbeweqwjuCNmZ7sC6wRV1ANOZEhtKKk+ySmLT6rahYoPX+fOsBK13xqSUMc4dGqyWCj8U1OgL5qpvR9srHxuTURjUWvXzyS/yl507sHWAE88XPolRvpydRuUNFVY0DtWHVVTio9ZiI8sdV2s7HzHtuv83fP02kNh8PfKwmefvrpOOGEE3DiiSfigx/84LQkOL2eVmsaYD0JK0DSihUrcOqpp+HnP7+4SWVJhlyTHFWVuG2mnBz1CfLnlNmKpLVA8mGQhhdO4rkDkF+lTQti7EMSpdJLdoOmonjxJYADgNIXlOrouiRmzTEYsPOw65RfBAZwjpkLJ5PjuuAU3uXnHOxcEnNFBqLUACHMSILAB31VFTkpfd6UNB5+ouooeh3AWjGugYyFh8HYe73XHua8ULP7DUieYakHiqTZ6rDMiS1kk2SX4BEGacxTIgLqBYgiuDUAjouR4na5BWthAlJMt6fnu4gpY5hm8R7mWR5tAuMeQHaCK68CxykmDJUwnwLkjH1ZDIQlO1Iry6sD3JoMUe6O3gtcrBVzseTjA4FKA4aJAKsUeb2CqPcCTyHlUbozTfdFvCdqZrJ5rbDC7UuJ21erqnxsnPVEjyBjN1DV8ZiMMrYAsaPAkfn+jTEG1XksATKdiAob4zYCSf2SkPQHMrdIsE4hsApzddDH1xdHHlAmLE4mOCuUlHtTga/uGBa+50Hu9PoCklYR07po5zvIYikdvsY0o01OuIq5kwevmmPfv3z5+n4NbfTrsaYEP/ShD+G8887D2WefjXnz5k1Lgs+A9fTlotZvTQOsJ3gFa3X55ZfjtNP+C/fee99qv6N0VyiDZXqWIjsqgkJ5PSUqCeuP62Kqkhb+fTKUPszwjGsA6HPp+4KuU5ma2IOuS0pW17i8E6S5hQyZWgZWPCYAWMhdybKCFyekSkcrd2YyPCfX5MSZAD/eAGZMnfHCD12ExXAhoRTFJ1hCKT0rZFJCMjJjKXMKjUN9E3lSVeXXmiSDqdi4OPq6ildi7ymbpUQvlfKmyIBx34TXx52gzyNOIal02R0av0TyGAAg2KKdjBSiNym4KoqhIHlW3tHYj1ZqUSwCWrJ5ghLE5RFy1MYmFqimhUQm0/Q19ABn7yOSqZfQaSAHCEDd0HUZGR08ky/Tn+t8oDk/uvHC/O8aUnCxdnB54ZpXD+z0UyUMjehxIzFOqqffnMelMyP7mMnmKQqVx75jBU6JoFEeMr4d75nBlcBtLeFdJOvK/kpqurWnCd2T1G43ASvd3GQAPoB1+gz1kkNTRakV/ajQMJ8ykHo+1jjd2+lmoxSBbOfzs3idhYZ9KQKJ8XHk5zWRXkZEkliy8WBKBrZ+wXPwwt22ewK+lTa+tSZJcOnSpXjb296G7bffHosWLcJWW221Abd0ej1Rizfl6/e4p+uaBlhrsdZGIozpQAaG/h9ceukioHmH5IMqRUyVqjtabyAQQIPPxYta9bBja3rNoIthRcqd/n9GdAXCS0uVTim35yylYDAYiF1yxCg8ySCGi9IDRaCQu4So3QE6TTq6fEWlsVjjdHWCqxRyUUScQ8+TKrzSM5NSJ0CZybaUmJALJk+SpfbbqB+h9PSsWY687pDGQjIlwxNl0JYSRGTBUofkxv45ZTB5rSyJLiPuH8twFPqQKiXKipAIyaTAEkO869hHlCbBTlKqt4VnQEDYoXJuB7yXyV2/zpwYq84ICMsGDyCVQmasGI0YQUAPE8+RNMhACf9chSHTLK4UdUOA5go3RgT0ToDWTXX8feV0ZenpW6vxBuQbI4lH5oihtiHzgqxadZQ6QtTb1L4i2NkYYKAnkM73KpaT2IznW/EC65jNHnENuZ0b9LZZR99VlQcxanZ84mbDm0xNGS7CR1EdNjCYu465blwya3JSIli0aujFFEfMhtXMLLNESbLvixg5Bv/mChQ3WGcC+9bCcmmwYoREmNgBA3JVzQ+nUE2ao4mxMvVJegX2+4vdH+ur6Wm51iQJnnnmmTj++ONxwgkn4O/+7u+mJcHp9bRe0wDrca7J6IX//d//xbe//V08+OCDAFwyWXiIlE4utqpdqMRa8WfhycIEk0RpbQzwXDk68ncIhLlyh8LjEzPkZMbS2IdlwaRFGW1CykDfezPVl55MQ+pkiIcj5wH6np1gKcXoPXhV9CIDN6tL4JEZJDNwNaSkvsO2HVWBm/JXgQxKgMpSK03/XlUMmxCVOlS+xnJB7pQ/ZVCVTpFsxQult/clpixnymM2TiuvleGacIOPhvRvWaKsaEBEUnDiT0Z0Z1ddYxC9MCAyDNSR/5WS7P9QXEBtwJbvlsBksuMwpN6YLuydfiQpvPDSS5qkFFgwYnWLhg1cDKUlR99T6uxSQs5RskumJFuCdbyiW8rwQl9WccU6JAB9ZdK4gwxZcvQjoEtiHd0Fbghuo5anipVxnfMEpIYKSpQYOeo8AAAgAElEQVRZ+81BwGsy5xMUxkdEniY3JND756iKplD5deX7iePQlx5AksxZWb4dfj2Zyq24bnoc0BwHGxDEIIa/C65ke3qmUDnkkXT8+toDQ02dOjDqyUwnGtQYBquDytfVsIO8glFaHcddofh43g5bYYddt308X00b3VqTJLhixQqccMIJ+MEPfoDvfe97eNWrXjUtCT7D1nRVzvRapxVy4H333YcvfvEUXHvtNQh/0NhHZQByK0Tmd8b4Tj/yrxidUNpjAogwFFQZULoLZjp0GHnlC9FF3Rx6ThXVSqLi6+qC5lVG+AjHLGQ99IVmNs4HAmJqsG9eLl7QCsy6xshBFvr4TowJPHqQAMp+NO+mlAToJj85lJFgKsUtPcwyBoMBnzeYkfDA1JAFGbwa5vjS9w048OLM91LkfTEj4wMA1dST13XIkmNrBSoyrBbma6UiMMVJuK5jnY4HC5OgINMREjJSRyat1h5uifIeaTxoNwjcyEsUrFrUFRnZjZBLI3w+JRmgk7KnwMyvAMNhNq+oiojg6w6H9Ol1KUDBGLhZop/MFBdSVWytBCwCqp7bbgClPbF3OdUxm0S9uuWDpc5YiAznVF5KkgLpeXMPhs3GCfhJjC6MYNgrTAZyU4J/BZqHCa4MtsRzxk1l0MbzgB67ylLnSGIv9EdF5pVb1RQmjfdeaWqvQOuKjPOR7Kihm9Hx+FhG6hydZdReAFP1Q6UUsmFIHLqQbI8s71oFkpqYYIYa8mIHJbsDrzrimcVerUkSvPbaa3HUUUdhm222waJFi1rB8fR6Zi3d+q3X456ua5p/XYv18DupYKxKKai1Ysstt8TRR/8V3vSmN2P33efi2c/esnk0GLlAFsjlV2rgw9H+Lqb3+Py1veaYzaq8xBjoUyk0KbM+BgIh3kBRSmjVL5FAXVXYbKvlVfVimljeTIaAII2RBryIGyK2gIxNSpSNcu7aPgHkz0F4YRTdYModMkUGeBWIGwPOCEMdDkcYjXjRn5rq2nMCZLdqrYhiXVgS6+RIuaJX+GiXCU760jdfjlea6Gvr/+PF00FNhuXHRGDJyMQMZmTMmJKBWQxEPxphNFxF6bIMdR6QMTJz9NUFgDVh50BKPHYmpieZKXrBOeGYQElNrCKMniya1plWzxiMyNQiC1N6Hesc/h5v2V7DVUMMS49uMFDopk4mMVAh2UHATJiTxu/qOtfIZlWTOR41sj6V0xUP4nNXbYNLIs1iZrxW9H2hrTBiOYxgkP+3Er0ZGaFeE6myM3HqT6yVu/oRYZLDGTKa1AFYgw2sLj8aU99dfqxSgX7E/VcVq1Hg/L05al/VhcgstlWrRqjOGImcO7209pnkdyRGK1jHeIjBjAEGUwOgC2azokePfjjCaDRCRUFf+b7JBKvtsud5vs0L52D7l2yzrl9TG+0aDof43e9+BwCYNWtWA1fujm9/+9vYf//9ceSRR+Kcc86ZBlfT6xm1phmsdVwBrsZAhnenz3/+8/H85z8fwOsAAPfccw8WL74MS5dejVtuuRl33nmX+vwSJguWGysT4Ula48BRNBN4gKIwiDMcXNlYME6VUceRmV3ShC76poBRTi6NJcqceeEPPw+U3J4sTOes8YnajskQ08k6HyBymiAvELeZ+IhgrSolPgQ8bQT6vhcYYcVLeLHci2StKqmJ/pxSpacgEcDEtJaB7JEnSVDaJ21fVvRFAJECEqrLq+Y9LKUmuwGFU4+5Y9ZWdXXTZV4QawXKiGXTkPyYOPVWqsGMniBo9L5me5g3KiQs+a+cMiqc3iyGWCorSXENBgJc13E2VIEjnihlVBo7NhXsDsSCBWMKThvydGEWVDJDASf8WNeomBCdlSZDfeRbRUUPxKaS8aI05wCZHMVDdMq0qlWMUWbGWUR3JNXleKnIeiu1Enp1cSwSp+5yJ8kg0tWd7C7lh2B6wyen/K/IdBPwheIyWGZujVE0ZKQBgc6oZ5VTtozUZUV86G7atZGJn5VaquJBwDiNyuOcO0quFkydsYGg9AJzhWb7nGi0T+jg7vizN+75hHxXbei1Jklw5cqV+Id/+Ad8//vfx1lnnYU/+7M/m5YEn+FLVtv1etzTdU0DrLVY4SeqmvihcTet8Qth9uzZOOigA3HQQQcCAB588EFcdtkvcNVVv8INN1yPu+66C8NhaewUL858vqI4hcijiuobSpIxcbi6VweApJ2k7VWhrbw2SRfwFHJZK6wN1kzP0SpjoFBTmcJLXJRlgFa9zKT0KD2HLIMllRSLpRKYoEdr/GFzrzQ2axqLEpyAZCWALbXKH2OSvpiHxKymuHjSwxOJ5cyqGu8XQ/TnQQnnBX0xdRkaQuKsbCfWvk0wsOqkivHqFM6anNIiTI+xkIxHKMUao2KeUJSSLz6D4LczhnaaSTaEXsvhlpDFcBbnZF1SREapFV1m4BX7+8g6wgtKT0ZkqusQXZGRdgbtpyTQTWO8oSqcFQJlESZL472GDXpmiUVgaalkBpMmEWLKtRWF6wYi69ztK8F3Sjw+lPNMoMk1IWqKdtAxTYyQKDqg2Q1J8SFmY4aXhdLc18mqjOuGNiUBwnnAUL2H1cwjnVW3FNVCiuUoxcf+M8tIAya/k10rApdk4mrPmxPrOJxAyVLOPw9WTiC/Eml2nX5eoZBTtjGgOCz1+KMXzsGW22yGFStWoOs6+r2ehkbvNUmC119/Pd72trdh9uzZWLRoEbbZ5pnD1k2v378qsF4SYX3sP9lo1zTAWot14403Ys6cOYjMmscCV4+2NttsM+y333zst998AKTNL7/8clxxxVW4/vpluOOOX2M4HKJWb1M1ZFyK/FkEd2OjvMOs02QiZaJSKMcQ+PCqTcAFgQ1Twro8YqUgd7x6hPmdsqEuztkaQGLUQPhUxoAqSdpzD4AY9TgQW5baxcuB5r8xK6uFmkKJ7NaYEaAbKB5CTBhDH8mg1CrvDiB5TixWNsATvJJNydnFovE1Qz6yZDLrF6CQ3TFT8CXoozK4GBCC6pwj2TuyyAxAUS5VYuBo4uRbX2iyqV6BwhgIGP1FyRK8MLbAatRJQywbpUAykLr2e0GBpuMSOwYJYHhelH5E4DXpWRMgojG/KDKB+Wm1MGsqZZ4X3up0CPbYhefj18kZcEWCGCcO4ZAEmxVcq7qZlHn+iaGqljg1aAWu5PwKMYrOqTlHsKz0KBU4kqgzfszIZoXcXY0ToS7vWWwnnNJuX3tGWKSsrCmCotSxL7PWCoubFtB5a5bRe4864gk31Q2QkpHVLJpuBcFddYMnxm6UWpHAKUlvrGBquXXhUXMFtib59mpyAf2MwRSZPHfDAf/vnkgpYTQaYTgc6nvAGtjqum69vn+eyrWmKcHvfe97eP/734/3v//9+Kd/+qf2u+k1vZ6JaxpgrcV685vfjOuuuw777rsv9t13X8yfPx+77747BoPBen/RTU1NYa+99sJee+0FgF/6V111FZYsWYJly27AzTffjFWrhnCfnLwjgGmMi/ctLZ0SnzfARDlSDEOdZOEUrQAgkhfJwPAiQ3ZuIvxQ8hr9VIDEIiokpgkuMCtrNHL5l3KTu0oBch4DME7OFYxGDOtkH2PS60dBMXOEWGuSWs2Ke7Ba3IfcDcHYTXjQ6B7mBbKG50cxGA7AIm5AF3oAUCgoMNEF6ZH9xAt11BeZuh4xJvsor0k6ow+sE7FnClQlcOlLRY+K5Ny3SWDY5WlDTFYmsjchxSY9F6fOyB71fc+Yg+rIuvDyes791SsbKidD70DWiFqA6VLI7SWjN4nxDkm1QKq4sQSvAjAgixeDC0lAi4CF2WRRYm2xq+UZAxJqYmZYtegvJJuYjAwZpV+yQJ68ebOSKe9LvipuY7wHgmK3Ciuc5EwacEAtjWEtxrT+hIQ0ALxk5pqBp8KqlSsAN3SDDnmQgOL6PVFeETiCpPhUmKtVYyignZcBgJNyyRT8mkzDEIidrc9SRXHKqH/8kudhhxeNc6/C59n3PUopGLEBHQBWA1xZhegbeq1JEly1ahVOPPFEnHXWWTjjjDNw0EEHbRTbPL2eusVv1/V73O9b5513Hvbff/9H/NzMcNFFF2GfffZpP1u6dCk+8IEP4IILLsDU1BQOO+wwfO5zn3vUnLWvf/3r+OxnP4sbbrgB2223HY499li8733vW+dtnwZYa7EuvvhiLFu2DOeddx4WLFiA0047DXfeeSf23ntvzJ8/H/vttx/22muv1b5Q1nWllLDrrrti1113bT+77rrr8MtfLsHVVy/FzTffhgcffBBdl0ESJSQzgICqR85xh943lkoUDMKL1OWOoZZI9I9MDLixEqUCqbbpxgZMEFJf1J5keX+o9ZUeyCkhqkgCwPAG1RFThJHGnlKSHCgJR+CPRIuAjZliHgovYDkr7iEkOROo0vsRp+QgC8iAx04W9gh0HHuxWIoNWC7MXBJgq5Xery53qB6SGJmySM23qD3x8DRBoCTLvB1BqVn+KjI0g5QkX3JCsLhrWo6SpVVVFoExAmyaicRx7dZaMPQqMxI9YkmxBLWEyTzkr3FJkaXwwGHsJ0JFX3nsUGMyD5zcc6CWHl3KUrto4k8RpyCZK4U/rdQWBuojStQVYl2L2CeQLYzZa84rVLAcXDJjJfBPKdEorhgGE4CEgHSXDN6llggPAT7X411ZXPCQUsW2jnicLCXUvmCkWI+cOzKyvWs6NGFUKnKmpMhdTmk8zP4WgwKJQCoaElCVTm9hxndFP8TNgj4jqSI5wd6Bb9r7Ed8JKSXFlASgHAOu4XCIVatWtb+dBF3x2X2q1sMlwcmbzxtvvBFvf/vbsemmm2LRokXYdtsNGz9xzz334MADD2zb9+CDD+KGG27AXXfdhTe84Q24+eabseWWWwIA3v72t+O4447bkJv7jFlPpgfrAx/4QCMrYu20007tv2+77Ta86lWvwrOf/Wx86lOfwgMPPIDPfOYzuOKKK3DxxRej68ZQ6Ctf+Qre85734Mgjj8Txxx+PhQsX4thjj8WKFSvw4Q9/eJ22fRpgrcVKKWHnnXfGzjvvjGOOOQbujltvvRULFizAwoULcfzxx2PZsmXYY489MG/ePMyfPx/z5s3DFlts8bi+5HbaaadHnCS/+MUvsXQpAdd9992DwPcEV7qw2lhaC3+Ug1JJCZO5gbEPTtN8EouUswJLESxWUaxCVfwEnzMll2SUmqcn5WC04skJ7nhN5x14XAhMeUYAZa+Q5MK/Qk9P5H3xQu0yVZWWdt+OUPNCsRqRDB4lRNbT0BnD94bwgWkKjuxM4UVeLE8SOADECLmjUqjj83qAKwGK5n2mM7ylemP8egxiLYAS81PKel9ox7FYj9pHthnzuCxlZAQbSRDsxZG6DCDDMhChrQgGCLwgR+BmrQLQNgaDwW6NWcxglnSfaYbUsScw2JvVkv5TAmpBHXGCLsls7qUwCFV/12u4g0gp6ZzSeeGMy4jcAm+TrhqmqCEpZpTKnDJW14BVNk5QZ9D7g0JTvcBUnZM7Qz+ixJxsLBPWvtc5kzhpmSiReh/HQwb6oqlG+eiaQT4BXgy9UzpFdpY/9wldAtPuNYBgmT6sWmM/G8/jQgC248u2xfO2X3NieUiFcTGYnGbu+x593z+qrBj/e7IA15okwbPPPhvvec978O53vxsf/ehHV7uQbag1e/ZsXHbZZe3fn/3sZ7FgwQJsuSWnv//93/8dr3/96zfgFk6vdV377bcf/vIv//L3/v7jH/84VqxYgV/84hcN4O+99954zWteg//6r//CMcccA4DDFyeeeCJe//rX48wzzwQAvPOd70QpBSeddBLe9a534VnPetZab9eGP9ufhsvMsN122+Gtb30r3vrWt8LdsXz5cixcuBALFy7EJz7xCSxZsgQvfelLMX/+/CYtho9rfde2226LbbfdFocddigA4O67f4PFixdj6dKrcfPNN2P58rsIXFxXrnanPCGRgd6TOmHWT5IGLY0n3OAJyXShVwbQeLLR5BUbZ02lrAhqQF4ZVqgwtbpQYrGMrHF3esrAx/tYyiEhRrmpqGIEqE1eMTN0GRiNKnJHTxhT6RmYyotnZG+Zto/bH6/BOAZOJRIcJamFtT2KZdAKN9UhC5+WeyRFKUKg8KLOjmpFU4SMFdtihlILoxvEBpUin5tFFAcwGCgKwBmdQIJnhF4OfU6LktlLkuLgFb0m11L2sZfKbMwyairCgIkMMaAPYBvSISrZq+oEgzXJR1fbZCqrlrJCO1XODddwRqJZvRQqtYr2KCpLTiFL63xwD98SPU1VsjbPCXUAekRfJJniVXWERKav0P8G7W8OL2rqESzGTimh9IXTl5isJspknCD5rvd2s1FiG1hUwOc2yuF97WGV/rSsYQ4AOpZi+ibM9lU0oglkuk8MXAB4zcPYq7VZnAAmeAoT+ZpkxUlJMViux7PWJAkOh0N85CMfwRlnnIFvfvObOOSQQzZaSfDrX/86Pv3pT7d/B8s7vZ7YJR1hvR63Nut3v/sdNtlkk0f19X3nO9/B4Ycfvhp7euCBB2KXXXbBt771rQawfvrTn+Kee+7B3/zN36z2+Pe+9704/fTTcfbZZ+Mtb3nLWm/7NMB6ApaZYeutt8YRRxyBI444Au6O+++/HxdeeCEWLFiAL37xizj66KOxww47NMA1f/58/NEf/dHj+tLZaqvn4LWvfQ1e+9rXAOAJtnjxYlx11dJGeceEYnigakVjIEymZ3canlmtV2HoYNkxGpbVcra6nFYDZu15WpzDZMcgL8j9aKgLJTDoaAZmOjwn6xikHsnvE9NhteoiiibtJcQUJ1kJl1+JBnEXuEIDD7VWVLFFwizIycF+QoynszxYKL6O6z0kc/S1Kuk7TwDMEKrG4af0SotBkadJ8ZYNYHQ5Kz6goiIpX4sRAZEIzxkFgyOhS4Rx7kmTdwF8+ZLDVUMZniWrmqFW7msTUDaM/XdF+5StO/QVBYgpRdOKiYwN+C/mdNWi+ArwuLqOmaIJCIAcbpnP6ZjIpSKA04CsAjuhWhyFuKaChIRegFwcIVjAPPG6haymaaLSxSi6QlVN+0JxqzA3nSeSFAc06o+GPVLXoRt0lEnlL6S/TnEVpmGEWjRRmQjypczmlJlFVukbS1nTphWwnFVwrqT/bEReojljqACVTNgLX7Ytnrvdc9b7e2By/T5ZMUDXcDhETA5Pyooxrbi230drkgRvvvlm/NVf/RUGgwEWLVqE7bbbePsUL7zwQtx333047LDD2s9OOOEEfOQjH8FLX/pSfOITn8AOO+ywAbfwmbPcmzNgnR/3WOsd73gHHnjgAeSc8apXvQqf+cxnsOeejDu5/fbbcddddz1CQgSAffbZB+eee277dzCb8dhYe+7J4ZPLLrtsGmBt6GVm2HLLLXHooYfi0EMPbXd6P//5z7FgwQL893//N4499ljMmTOnga358+fjhS984eMayZ41axZe/epX49WvfjUA0p2XX74EV1xxFW688QbcdtvtqHUVGRvQhB6GZxY90ysVP8tdamxKXPwtzOg1+gIFiFRKHGGkfT/i5F1H+YV/o/2DsaQVeVeQkNdCVV0J25USZrbUcqMIggQCbPyYSK0nmxIXG/43oMqaWtsFM5izceYWJcTJwQEzTe7VCNaMlH1xZPK3MZoi09RdBVS5m7n9nTXWJHZGaYZ+mskjgqOqyzGOQ+1HgBm6nJEyXyNqkd3IjpRa0KXMWAMno5gtAeF/yownqACN5gLY5swUI1nHxPJkLL5udT2SZxm7RqYySTqDvEyslNE+so75aDkzFctiGlVMkjlSoT+NeV6OXsb+WnuCI2VlGAoKjXktt4xgRjcIyvVKmnj18L0ZUDGCe468VKwcFk4uTiVkSyi15/SnYi5cJc1ZUrrb2F/nXlAhEIuqqp1gt3RzIN9WYbAZoDBTFMnTAYTL+HyvFTjoTWMj7hO9JmXFGTNmPKasOMly/T5ZcU2S4A9+8AO8+93vxtFHH42PfexjDehtrOvUU0/F2972tva9+81vfrOxHF/84hdx+OGH48orr9yQmzi91rCmpqbwxje+EYceeii22morXHXVVTj55JPx6le/GhdeeCFe/vKX44477gCAR40D2WabbXDPPfc0FvaOO+5AzvkRxvfBYIDnPOc5uP3229dp+6YB1lOwzAybbrop9t9/f+y///5wd4xGIyxatAgLFizAueeeixNPPBEzZsxocuJ+++2Hl770pY9rjHnmzJnYZ5+9sc8+lB9KKViy5ApcccUVWLbsetx6621YuXJVM8QGIxV3uFKVxEHQEM0LsOQxBUnaBMiCAytXrULOQM4DdF2wUEA8k+Ws2IjwXBUAKvglPuAUnaYnk2VNZjGENJgAE4IhQAhTNoFjsB4lcpHEqsFMyehid1Ju3i5E110r21Y6ey+/UmaGWPTeEXvGXT8v9jBuOzAxYdkluKLSUxajAkYlUIIFPBWxcAYof6q6o/QsUBx0A0luYsnc4WLqBjmhVQZR60SpBX0dwQq9RdZzY3LUscS0IpR/pe2gcd8B75nS71VgjuZ3V85VidBZFA6jgiC8wCj3dRpOgMCXgGj1wum6DDUNAAqpQOS0MSKi6nBkdBmoPaXXJF+eu6NrErO3aUMOAfBnMUXb6+8Bg3Vgv2QySpSFPr3ofKy1jH1qjgYQCdh4IhtPShS4wJup2olsYNLxJjOs46vCcEuUhFH5u51f/kd47raz1/szvq5rTbJigK6VK1e2v58EXCklDIdDDIfDR0iCo9EI//qv/4pvfOMbOO2003DYYYdttJJgrAcffBDf+ta3cOmll7afTUpI733ve/G3f/u3uPfee/HsZz97Q2ziM2qpi2K9Hvf71rx58zBv3rz278MPPxxHHHEEdtttN/zDP/wDzjnnHKxYsQIAMGPGjEc8fubMmQDYhTkYDLBixYrVMtse/rfxXGu7pgHWBlhmhqmpqXZynHDCCej7HldccUUzzp988slYuXLlagzX3LlzH5d3IueMuXNfjrlzXw6Ad5ycVPwlli69FrfeeiseeughyWsBsJJ8MhEXoBH4MD0bOxRhBAOlUIYadB3odwqWZ+z9qaU0potS5QTD5XXMlrU4BsmCmRdA/ndMEPqER0hxFgkNhAGUG6vzMcC4osjBvCwWElMeKzWCXBVTEUyPKbXeDF2nmAaPFHDhB8VZJIxrhSxxv1Ay42RjPL87ULyQnXMHFJhZvGedCyq6bgqD3Kk+Rl4xC0lLEQdwyZiUyxjyPoDViuIRXeGMFRiNEOnpKRnI4ZhQbVbel4qoaw83ecvEClpS/lYAxsTyZjgY+MkjLYmUIZ2u6cScDSjKHnMBUfkCm5RZqzxqhN/Ve9TROL2+TLCKfWX9EKcYGQSaMCEpVhNjWZCQYV0CW5Rqk0eDrSwolE+BMcg3Zm65PgwZDsv0cuWUNRBApi9NeOdiYhKgjy7CXbmPBMoypdzXHvnksVdru9ZFVgT4PbJ06VJsuumm2GWXXXDHHXfgHe94B2qtuPTSS7H99ttvqLeyTuuMM87A3LlzscsuuwDgDehvfvMbbL311gCAs846C8973vOmwdUTtGrcDK3H49ZlvfCFL8Sf//mf47vf/S7cHZtssgkAtInbyRU3E/E3m2yySWN0H+1v4+/Wdk0DrI1kdV2HuXPnYu7cuTj22GNRa8W1116LBQsWYMGCBfja176G5cuXt2iI+fPnY++998bMmTPXG3CZWZuOjHXLLbdg0aLLsGzZdbjxxptw332/FQPkkrH6NkkWfYPVq1gFgo+UOjg4SRf9izCjobtyPJ0gI8bxARE16LKxCJrplC2SgtlaABwYDAylyIRtmWP6/CtKXbp4wipimC+ZQkzr+OIHZzE00Yq8NIlMHAt9x8xXgEO4o++LZD1MmO87ZXihPYYxElwMDx0iWUdgWCYnIbU9iTUqfe2RkdFNTVHC85FiBYxGcidTE7EWEUHgcEWbRcYXQVc3yEoarzBw1LNX1yGsYOQV2TpO2WVD7QssMyC0ypcGMV21Voyc3XzVFMgqhGnGr8KYOOzLCJ0bLHUEcwo45fFAA8DGF5J03UioNhxAT1vlJGWyBqZzSqhpPBGZBgkoBK2oDNKtMNbdDHj8+1I5aJAYfeEp9qByx5TLBfUYmot1cp7ruVDS7b1X5hkbDsjoQeBQ2XWZQbKtfUFvzgs/Ey+euyPmbLPxXbwfLiuuWrUKK1eubOxXrRUf/ehH8eMf/xjPfvazUWvFn/zJn+DjH//406pL8LTTTsO73vWu9u9Vq1bhsMMOw3A4hJlhzpw5+J//+Z8NuIV/eOvX/bX4dblutZ/1/uiAZ01ru+22w3A4xIMPPtikwZAKJ9cdd9yB2bNnt5uLbbbZBqUU3H333avJhKPRCL/5zW9Uh7f2axpgbaQrpYQXvehFeNGLXoS//uu/hrvj5ptvbgzXhz70Idxwww3YY489mqw4b948bL755o+Lmt9uu+1WM6UuX74cixYtxq9+dTVuv/1W3HnncprFs6nsum8sUtdlghIL0YeuH06JtespL6htjcFa1OKYgk6lzsgMH2NYFaWEV6yTQZ6+G0YtgDKiuvoawhHbNa4jKmNZ0SOtPmRSSmm1qGYIfJ5SKtPmkxLlEcEShlJGYqzGIa8hM8GNpudC2Sz8YDAmnsddXT8aSsZT92PsC49tjjwuXrjHrA/9aJbJJpqer8KRnDUublkxUQZYxlSaYiZZrepedPRlCO+D5QEA9ip6l9t2WiLwKnVcvWPGepkAgbWnNNh1iQC5Fp4TNgaebgwHRQUsIkV8MquMUmmR/y7lNO4+VCxGRW1erFIKLFjIfhwNMeiy9pEDVhSqKtN+FkANT1uif664a9pzHPdgSeee84xIzVdWaGJP0bkJmFe+z0K7vsXpWAWAEydMD37TK9f7c/pULHfHypUrH1USPPXUU/HpT6G1xWUAACAASURBVH8al19+Oe6//35cdtllOOCAAzAYDLDnnnvixz/+MTbbbLMN/A7WvM4///zV/r3pppvikksu2UBb88xfqqlf499s3e2ErbudVvvZA3U5Lln5nXV6rWXLlmHmzJmYNWsWZs2ahTlz5qwmBce6+OKLMXfu3PbvuXPnwt1x6aWX4pBDDmk/v+SSS1BrXe1v12ZNA6ynyTIzbL/99jjqqKNw1FFHwd1x1113YeHChViwYAFOOukkXHnllXjZy17WGK558+Zhq622elyAa86cOTjkkINxyCEHAwDuv/9+LFq0GEuWXInrr1+Gu+/+DbpO1TzQBVxRBWj+JJN/qjYjeXVW47DqJ6b+WG/TJvqCNQvWKVCaJz1nFERLsgMwzvrShBwmg1KNF/cYv5cvCDJB1xJyk7xg4Q2SLy0mCYOqcBtHX1gY6uXXAvQenGP7Uchs8oM50AJS+zKEF5q3uy7DLeRXa+xcCjYupE913vWjgkHHzK7aj1ouWYAVlzzltdL3laiheh3RBN91TVqFD5iejqpBgx5eE3zFCDl3BMZGEJ1zsIuqwwkmsfD4pWRNGg0Jrw1MZJM5HWHsauCkSym2AKmaipLZscik+ooirx/9e4CVgtQxGGs4HKFWV96SUufTmPGDoUWKxBADUoKXHqVkRScoZiEnhoo6Ze0uR4K8ktozgTfZSAOMJePeZEF61lh8nmDZUXqCst323BnPmbPFen8un+y1pinBkARXrVqFM844AzvssAP6vseSJUtwwQUXYOnSpRs9uJpeT/3Sbcd6Pe73rYczTQDwy1/+Et///vdXmww94ogj8I1vfAO33XZb89n95Cc/wTXXXIPjjz++/d0BBxyA2bNn45RTTlkNYJ1yyinYbLPNVnvOtVnmk+L69HraLnfHfffd16IhFi5ciMWLF2PHHXdczce17bbbPi7AVWvFihUr0Pc9e+/c8ctfLsFVV12B66+/Cb/+9a/FbFWMX4aAgX2BwTaFtKb0c7FIgLUMKvYuqi7HxvlWnGJktAQ77Ai+Qr4Axgn0kRrPj2nmFCJ0YdbFkyAsGDJ16hk0pUYwNvkhSUGhAJpIHMtUAP01pacE6JIlc1TiKNIgpQ619qryYW7YYDAYh6WaaTs0Lad+xgCsBhF01ZTtZLKix/5iQGfY0cyy9r3wWVIZtqZCCTCJd6JHj2Z/l69IMt1EZlROiTKdpj87Y0aXu2Q4cLutbbc3cGrK8KoOdEl5XROsI4ueXU1NnHZ0U4BDOxdSy6zyvnKbzZHB+qWc1UHpel6gMaMuY3/yyvMx0JpuCjgV6ZK2efxriZgPY+yCESqba+ChagijnecJDnUxeoVlMpa5y/i7Tx+FLbactd6fwydzTU4JbrrppqtNCf70pz/FMcccgze/+c349Kc/3UzC02t6/b61ePFi7Lnnnthz5l9i87TmMN1HWw/Uu7Fo5XewaNEi7LHHHqv97sADD8Qmm2yCfffdF1tvvTWuvPJK/Od//idmzJiBCy+8EC960YsAALfeeiv22GMPPOtZz8Jxxx2HBx54ACeffDJe8IIX4OKLL15t2vWUU07B+973PhxxxBE4+OCDsWDBAnzzm9/EJz7xCZxwwgnrtO3TAOsZutwdDz30EH72s581wHXxxRdj6623Xi2La8cdd1yraIiYfFyxYgXMrN3VPnzFneySJVdg2bJluO222zEa9QDGzNHklCJASSdnjbXX2ozHgMba3cZTYA3MyP8i+c6VkO0qjw5jvFlIN5FEL4bN0baFshs0SVZhqWsmboSR3OlBogQY20KpstZxhhS3M/LFxiGlOVFihBHkVVcwp1HSZPSAtSnDeK9kYWISUs9vhmyO6gQ7BHYEMO7jqUBIPqsy5MMo/7WoMmDsPQIkR3J6M5spTyuxDicBtY6zxyJNnq+fZVgXWOvyuLjI25ZxP0ABocZg0ZDvOABoTDQoKn7OBrqoKNNyu+KYMAy1osIL0Msv1XXj4FCvEdtBICqcz1gFU1aXM02LtiuTbKsJi/jbWpEHakqofH2T36/0kk2hIQ4LIJdQCmcoLfN9lp6Bt7u/cme8+a8PfszP3FO91iQJ9n2Pf/u3f8OXvvQlfOUrX8Eb3/jGx3WjNr3+cFYArD1m/sV6A6zFK7/7qADrP/7jP3D66afjuuuuw29/+1vMmTMHBx10ED7ykY9gxx13XO1vf/WrX+FDH/oQzj//fExNTeHwww/HySefjDlz5jziNR/eRRgF5eu6pgHWH8hydwyHwxYNsXDhQlx44YUN/Uen4otf/OJHREPceeed2GyzzVBKecQX79q87q9+tRSXX74Ey5Zdh1tuuQ0PPfTghHSojrrK3rjW1VbpiYlWlgYIDM37EwZ6/rfS3FNGreqe4yPgoGfMI6CyPQZjIKc/r2JtLOzaponKCLH0SGZPjbWKdPfYUDM0oEe2KtPorFT60Ygp8l2XYcYYBRZTu7ZFjEmEctJODTTZdRzYSUlUEuLYZc3GnyRgIxYo5YQyEjuYxtNyAeocsc0BzgACSAXDWgIk9xlcafvMyKo1pjqV5h4ARpIlFbPcWLWQMRF+pgrAyCYx0JNyYJdpGIdrWi8nxULwmThgQeDSDTpEiQEjHeSAkEQcuzBpatUAeGFyfYD4YPOivohMm6O2GAjWBUTzgbnkYuf0rHtEOxBks8kAZK9Ak/gJn34bnrWRsVdrkgTvvPNOvPOd78T999+PM888c7X6ruk1vR5rBcDafeYbMGs9ANbv6t24bOX/fVSAtbGvaYD1B7yCbQrAdf7552M4HDbANW/ePPzsZz/DSSedhK9+9as4/PDDn5DgwOuvvwG//OUvcM01y3DLLbfggQd+28zlMbEYMQfhnwokFEZyr1FX4/AIEpDvKDePDSfNGoCTTFUjy8jDJ0MJzayIhUgN01UBkKrOODJmSVIjQWL1iCxI8hoVyZWQd4uBqZaA4aroY8yUqCwyqCaSyB0Tr4MGLl0ZXC5QEuiP+0RsnCYMoV6+rFok9yp2JTePXGKJodLlYwLTyFjVSGKnhww+lvSS2MOi12sdhGIRAUwwXJR8kdh72HUChCkhm4H5YUXHNiv8NTfWi5EcWbJrlaeNk3m19HBLmMqdsse8yYtxvFMCShFiMmh4IAYEAHhChYJsUSX3BWMo83wCEjLQqoEoTUZPZsxSjLPFchjO5A/k+WvI2Gv+S/Cmd77mcX+Gnsi1Jklw4cKFOProo/GGN7wBn/3sZ9d5TH16Ta8/ZIA1bXL/A15d12H33XfH7rvvjuOOOw61Vlx99dVYsGABzjnnHHz0ox/FqlWrcMABB+BXv/oVttpqK+y1116PKxoCAHbccQfsuOMO7d933nkXFi9ejKuvvho33ngT7r33fhmQfUJS9HZh5VTdGIAxNZ3SXddlAOPexPBANSTFR7KvL+SnZM1gn5shW+xK+LRS9BsCBjI2pWqqUExciZDTlMfTiPKRjXpOsKWcVZkTlThVniSCAOJJynOMxBDzU6OEWhfsCCOVHayUoiDUHlZM2Uag0VzAjUCK5ddh5ieS1DBALQRlgIqwBQCdADB1GVZpgzcf74+ilPbcccAggRJeUawFS6krau8YDvs2aTlyVzdllheuInIcwtTeqbi5HxbkLgMOjPohEMArZbFhDAj1EqN8fI5SjH2WOleqO83pzVhfBRbF0iUycS5AzOy0sYcK4HBCaYxV4bmU1TEpVi11BKvFq3x07OE89Mj56/25eaLXmiTBUgpOPvlkfOELX8CXvvQlvPnNb56WBKfX41pPdhfhxrimAdb0aiulhF122QU/+MEP8KMf/QjbbrstPvaxj2E0GmHhwoU47rjjcNNNN2HPPfdsLNcrX/lKzJo163F9+T73uVvjda87BK97Hac27r33Xixe/AssXboUN954E5YvX75awGit0SPojeHqR1VMU2mTevBI9I5Yhgnp0yRJNpAGSl2IGhZdWDWNyMwpyk5V0RBdx4txX7wBNcqFNNTnBIxGfSsuJkCi2d1QEE51ExgA0Hr4OPHmADJ6pYST5aL3isZwGd+T4h5KaeDNAYINTbOVyqwri+qgiRLq2o9QU27ybGwJ0+wJIC2D+VgJLQ+LximyVO6uFH2yf32NiUXT8KdhakpsmjxmXiuKA/1wpJwyyFQ+QMRxUD4lSzQaKfDSCeboMuf+rg5kA/KAAwYAmSZzBpCaJTJb7nDtz6QYhgDrcbzdOajQlx7Qvo6U/ajwUUgEQWdfUXuVZCP6NmOKVZleXjF335di1habrvfn5Ilck5LgzJkzMTU11fbB8uXLccwxx2D58uW46KKLmlF4ek2vx7Mq1jwRuKbHPV3XtEQ4vVZbK1euxJ577onXvOY1+PjHP77auLW7484772zREOeffz6uuuoq7Lrrrq3eZ968eXjOc57zhN7tPvTQQ1i8+Be4+uqrcdNNnFRk8CHGk4LRjzgRSxBGeE54gddjXRx5UQ0fVZiS60S3YUiSZIyqh0l+nP8EQN4j+cUkS6kAiNOUjDRHlzsZ+cnCASEpunxcZGHCQM00BuYy8XXRgGBWGGvK4f+JCAoyQtEnyBXVOs3tDaNLqGVI5RgqiH4/MAOM03PGCInEWApUuZ9sApwKkNQ2eRfZU4ClAuaV1TbRaUDzrFlOLQTV4czsgtLuXeyUkXVkxldC1w3oG0Nss6TGianDKmYwNYYSAtXaD44GeMfgvYNNBsRasFmUaxP49rJALb85reW6jqVdsp9eXJU8CbnL+OeT34XNZm14iW00GuGhhx56VEnwwgsvxDve8Q4ceuih+PznP49NN904AOH0evqukAj/ZOafr7dEuGTl956WEuE0wJpej1grVqxYK6+Fu+Pee+/FBRdcgAULFuCCCy7A4sWLsdNOO2HevHnNOL/NNts84fLCtddeh1/84nJcd921uOWWW/Db3z4gOW48FQhAxnldJLUa6HLW75QSzJNIGV2Qc8QHyPxdSlHKd25TjS353UNSC8muH/uHUmRTucCC4iAq2ja37fJxfhdfeexH41WczNI4gZ5EWM4JfWGnY06RhB7eLIZQpdwRULq8Zcma78jyGNgBQLaEXuAwpyzjuDcjeOysMIWXnhIay46JurIlVO0bJqKjGc0hdqlUSm1IQO3HYaWll6Cg3K+2X+jcbz4oGug1PZod7uM4Crn8RRRO+uaAbFGMrdqaYDvFwDnAkFbtd6+qIoqp0xqdltq/0HFld5FAV0xIGub/2Vy88aiDntDPwLqux5IEP//5z+Nzn/scvvCFL+Ctb33rtCQ4vf7/9s48vKrqbPv3WntnYpIZCiQgGLABGUNICCIiVhFQLIJABRyoEyrO4gTFt+LwAXXCVF+xlksRsdhiS7X2RSVBBBkiGAgBQkIgQQKEQch09lrr++NZaydHxgwSQtbPi0tykn2yzknCufMM910tlAms61G/EgLruDyAH4o/rZUCy7YILSdwtoOsjDE0bdoUI0aMwIgRI2CsIb799lskJyfjr3/9K6ZMmYLWrVv71hADBgxAhw4dzsoa4nRER1+C6Oiybabc3Fxs2JCKrVszsGfPHhw+fMivMCgtbOgtPV/FSED524vlRJmprkhlRt2Zny9nKh7mGuqUKV1VkigJlDm1h4S4/uah8cKiSgsZjDLQC5uSSg+9K/2CrbSrONOu91R5oQqdEU/0mMxvRwFt6gkdXwSl57ukgFIOuGPc5jltFOoYIwYA3AxswxdyAeHB1dUsYR6vdqenHpqpDNKgObTbvmJSV3sYhI7cISd+bWUBQDGd1+doQcoUILRQYoqElsvBJEdxaamO+wkFlHHxpzanAD3XjkP/jEmPzF6Z3opkSuqFCDond8tCxqU/9M7gyQAcRbmJQotRhztQOs+QvFn1xqJScEDzVkKvuBr/NVok4P5wPhQ9ppAwjut+W7OzV6drCR48eBB33nkn9uzZg2+++QYxMTE1elbLhYmJm6rMdbUVK7As1QZjDPXr18eQIUMwZMgQKKVQUlKCdevWISUlBZ9++immTZuG+vXrn2ANUVXB1bZtW7Rt2xYjRgwHABw4cBAbN36PtLQt2LVrFwoKDlE0jG4ZCaFofkgLGkgalodyoCC0QCk3U1V+E1G3xrTrAhgDAqUB3yyV6WF0GlSndprrGm8tRVt3glpijHGKuDFVJt3qpK1F+JUyqSS440Dq+aGyUpD+fOW22qiqpVuDYAATWljQzqWQnr+xSFYNAq5LIkEqLbQcBwHdGmSMqldCSLjc8QfIuW6PSRoaIysMvbEo9dwWpIKAPjMT8ASJGsYVpKeH+3XFi/5Hbd5AIKCd9Snuxtg/cJfRvJNuHQoh4Xnks8a5QCBAwpk7ZIGhAh4cRwdbBzxd+dKRRbqtx7kDoTwwyf22JwlMB5xJ3XKlliwT2hMNADiDEIASnv66CW0l4YArCsFWjCNuQDfUq19zrcHyLcEGDRoEtQTXrFmDW2+9FUOGDMHf/vY368BusVQjtkVoOacEAgFs2rTJt4b45ptvIIRAQkKCX+Hq3r07XNet1hbFTz/95M9xZWbuQH7+Af3CrPzPQ5UrSdULHanDtX8W+R65+uPMfBe16+hFnqpSrsu127m2b1C8zEKBlYVNm8xGY22gp330aZXfaqOAadMuNJ05peNY6IVS+m1FpUUVoAfOIIUsJ17N5zIbhY6xdQqaY2Pax8lxKG+PZrtcXUGi54GOT5mDWnHpKqGu8ikFgNP9C5RtKzK6fyEdOIyuIQsL8gMTAQkhBRRTCHEc+D5ZKOuyOnpTj4bRHdq+1MVGsrJQKJtLo8frcAbO9SwYA1wWAnCKRDLzalIqMj81vmCq3CwbKzN89b+O5usKY7Kqq526WqnAER4WipmzpyAiIqzavpfPltO1BKWUeP311/Hyyy9j7ty5uPXWW21L0PKLYFqEvw4fjvq8WYWvPy4PIr34X7WyRWgFlqVGkVJi69atQV5chw4dQr9+/fy2YmxsLMLCwqr1BaC0tBSpqalIS0vHrl3Z2L17DzzPKye2pDYIFTQjpAfXqZLiUOtMiHIv5hyO44JzqSNnuO8Az1BW9dLOUnqmiypEnDF/Y87faDSCQefuOQ4JAKq46Pvynw9qmZkBffMi78fR6DUcqjDB33JkHGS/4HA9RE7nIysII+bo/sw6nOty3aYzNhMoay3q7UVT6WPmQfhmnbraBg4aiSMRBiX0YL1+LhUDd+n5lDqzkFqbEhAcijqhgN6sNKLRyEuTMymE0m0+qROEmP94GANcx0F5LzSHuZCgypaZm5PCOPgDkDobkpmhd0VRSdqugTZCqdXL9MLA4N/0xcgx5372SkqJwsJCCCFOaAkWFBTgnnvuQWZmJj766CNcdtll5/x8lrqDEViXhl+HepUQWIXyILYW/7tWCizbIrTUKJxzxMTEICYmBnfffTeUUsjOzkZycjKSk5Nx//33IycnB7GxsUHWEPXr16+S4AoNDUW/fv3Qr18/ACSW0tLStON8FvLy9qCwsIReqKXS7UNqPVEYtNIeSAqO68J1XAh9u6NbWp5+cVZ6G00XkACmyONKV0eEFjnkWG7qWGS1zjkNTktJ8wsON8amDK6+xthX0H1RqLYRYVIZB3mqb1GLtCw+xwg9chmH7+9Fy5gmO1FbXDCgNEBVPWYWBkEbdVJQZQh6IF8qaicqSfYNEorehoInqW1HAsajc3sBfTYHToijsxEFuKMglQNIT2dXMt0Z1bmUHIBUuirF4ZmBeEULCJ4EXO6ChZBTvtJtWqUYSkpL6XFzElqSlyDE5VBwfvYcSEgPfnuRxLCE4ma+znydASF04DbnCIsIw7XXX17p79HKcrqW4Pr16zFx4kRcfvnlWLNmDRo2bHjOz2ex1BVsBctyXqOUwt69e4OsIbZu3Yru3bsjISHBt4Zo2rRptbc4MjK2Y+PGjdixYwdycnbj2LFjAMxaP4kY13FhqlsECRnfad0M2cPvoOn7ID8oN8SFFApgtAHoLxsaGwS9YajMIL4UYNwBA73QO46xhZD6Ot3zYz/7sdYhxkLPHjk6H89U2BQ92bry5sDzPN0Oc/wNSeMNBoWyx6SrSFTxoTkkh7s6u1CXwRQAzqGEAHNMm1VX7KSirEolERoaRm03yv7xW4MwcT6qbKrfbEcy/dw4jMGTtLnIHZDXFzlGkHjS81xMkVM99CyYkAImGkgybfPAOIlX0Bk45RWZJVB/i1JJgGtzVYDBZdw/L2PA1cP644bfDq6eb8azoHxL0HVd1KtXL6glmJSUhFmzZuHll1/G5MmTbUvQck4wFazO4UNRjzet8PWFsgDbij+zFSyLpbphjKFNmza4+eabcfPNN0MphYKCAt8aYu7cufj+++8RHR3tV7gSExPRunXrKr+AdOkSjS5dogHQi1dWVhbWrPkOO3dmYe/ePBw5cgxgUs9kOb7oMjE35MVl5qnIj5gzp8w13tW5iZzT9ULqXEHd8FIoG8o3juy+XcTP/bqoYiOFKGddoGN19EyUiREyW5XGAgHMuMlzSKEgUApXf5yQAfixQpJaeswYP2nRR3qjbAtRSqGrfnoZwCEJZ7IYzTC/53kQ2m/L4WFaO+mWXznxB670/VE1TwkJLv2P1jYMtHQgpJ4L08+hFORRRtU5oYOZFWUqKgnHZYCiSqDLOZQEhPQQ8DxdvSTJzBwXIa4Rwzo+yCGBxssNxnNt1RBRLwxDh5+76tXpWoKHDx/Gvffei/T0dHz11Vfo2bPnOTuXxWJQ2su9MtfVVqzAstQqGGNo1qwZrr/+elx//fVQSuH48eNYtWoVUlJS8O677+Luu+9GmzZtgqwh2rdvX+lNRSklioqK0KxZM9xww/X+sHB+/n58//33SE/fgqysXTh06BCUYhDCA2NC+ybpYXk9GG18lBiDrhKRWDHD764DbUTKtBijWB7OTXWLrBrK5rTKfKk8j4xGmR8KzQAI2kg0gsN4RIHR4LYybTDo/EKpBaGgIXg9Z0XPvTkrZQc6jn6snFObkFKgwZhDppy6skV+V55vTaGUQqCkWM9ZmVxFmhnzh+y1gapUoAF4BnhawDDdJlXQJqxCkJcZZyRahQSk/jsoDJppR3savjcxPwrC0+anTOl4HkZbi0I/1yEk6ALCgygOUKuUczCh9N8pdok7jg4Up2dr4OC+CA2tem7n2WBagmaL13XL/llPTU3FhAkTEB8fj7Vr16JRo0bn5ExnokOHDoiIiPBjt5588kmMHj0a+/fvx8SJE5GZmYnw8HDMmzcPl19+7tusFkt1YFuElgsKYw2xdu1af3D+22+/RaNGjXzz08TExLO2hggEAigqKgJA/mCnC7s+cuQIUlNTkZ6+DTt3ZiE//0d/4FtqQ03TioO2gNCm7uWqQmVxQGYTzkT1MIBif/xgbA6TWGM2GqUAym8NmlksU4nhnHyayMXdhWkt0n2Vy0XUGX1U7NLh2caaAmX2ETTPBZhcR/L5knpmy7RGyyp6QsigYGtyT2fl7p8EC2NUiXIdh4bqGRmeGqFG3loKSghwV/uNSeW3Uv1KE+Ng3NGtVQaHk4GqMnNrxgmfPlhvDurtQ8b0Y6HzS0EC2WUMpUKQUz3Tg/pgMD5pDRrUx4tzH0VIyC/7++uZWoLvvPMOZs6ciVmzZuGuu+6qshVKddKxY0csXbr0hAH7O+64A+3bt8f06dOxbt063HjjjcjOzvbnyCy1D9MivCT8N4hwKt4iLBIF2FH8hW0RWiw1DWMM4eHhuPzyy3H55ZdDKQXP87Bx40YkJyfj66+/xh//+EcACBJc3bt3h+M4QZtWubm5iIqKguu6iIiIOOML1EUXXYRBgwZh0KBBAICSkhKkpm5EWloasrOzkZeXh9LSgN46oxd5Y+BpBuCVAnlWMeW3AM2QuZQePM9YE5Q3L6XwZDDAccuMTMEY5SQyY0WgqzTMoZkvJWgo33G0L5fZNJR6cJ6eT8/z4DqOb8tA1gc0rwUYc00Tyq3NPSEAqUt1TEF6nr9xCZDDPZTJiNSVLElD+VT5o0ocuezTPFeAunIAB4QnAA4yD5WCxI1DbUyK6NH+YVKAKQHuOFBSotSj55IbjzJOIlYoCS6ZH4LNlA5t1o72nBkPNMCTinzNlNJtYFpIkJJ8vvr174bi4iIEAg5c1/Xd/Ktz5ul0LcGjR4/ivvvuw8aNG7F8+fLz8kWp/PdCeRYvXozMzEwAQGxsLNq2bYsVK1Zg8OBzN8tm+WWg+njF23027NliOU9hjCEkJASxsbGIjY3Fww8/DCkltmzZ4g/Nv/HGGzh69KhvDdGoUSO8/PLLiIyMxBdffIGQkJBKvTiGhYUhPj4O8fFxAKgluHnzFj04n4kff/wRRUXFvq9WWTXK+EhR9UQKBilp61A5gFICDqdQZyHKWo5KKQjPg+M6OvCYxA4Zq1I70mEuDbqbAW5OAs5kGCozp8SUbmG6OpNQ6OF95Vs/mAFzJT1Q/iD87EXuULAy9ByYEB6UknCcUDghZfEyjkOO71IoOC4JTqFbkDQET6HK9HgFFf/o+CQytVu6kMZCg4xWFblh6K1L3YLVuYCmgmYELOfk5qWg4AkJh3EoZmbgFM1s6Xk45pAYlkqQMAVV8ByXg8NB/Qb1cP2NQ3xhHwgE/O9DxykTXOXFfEU5XUtw06ZNmDBhAnr16oV169bhoosuqtTnOBdMmDABABAXF4cXX3zRF/MtW7b0P6Z9+/bIycmpqSNaLFXCCixLnYNzjm7duqFbt2649957/QH2L774Aq+88goyMjLQrVs3NGnSBC+++CIGDBiAuLi4KltDuK6LHj26o0eP7gBIEGVkbMOmTZuwdWsG9u7Nw7FjhVDKuLXrMGpuhscVGCQ4d+FpR3eyjdDeTQ611zzPA2eO3x70POHPenmixJ/n8v2qQC/ajuuCgetBeegXbgo/BqC9spR2YgcAQefUVgZKV+M4AzyP134JRQAAIABJREFUKlFCKnheCc02hYZqXST9bUCpFByXa4FEUUH0OKQOaKbP7ImAbkfqGS09vA89Y0WeqzTvZjYepRLwFPfDsmk5wFhjeHAYh+s62qaibDtQKgHGyCfMLA34LVjPVO4UPI+ErsuVP9s15OoEhIeH+19zI7SEEPA8D8XFxf77yguuszHWPVNL8L333sOzzz6L5557DlOmTDmvWoI/JyUlBe3atYMQAk8//TQmTZqEBQsWnLSqZbkwkPq/ylxXW7ECy1LnoYH1fMyePRt5eXl44403MHLkSN8a4qmnnkJGRgZ69OjhbyomJCSgSZMmVRJcjDFcemkXXHppF/+27OxsbNiQioyM7dizZzd++uknPRtVJqCUENptXsHzSrWnlPasAnzRIBW5vXMFY8RQ5uukt/KoTQa9nSjBmdQzXwJCt+s4o81FZgbWPT3srW83j8V4eEnFwCBRWupBKSAklBzZldnw889Cf6WZMqbboqrMwgFkr8D0IL8ZoqetSA9C0lYlHBJ3HAxM5x4qBb/KJyW1CLmg9qdSAAeHgITwaIsREvBEgMxHGafwao5yTv7C3xCVnoDrkuGpJzxAO903atwAvxkaPJBtKqhmdk8pBSGEL7hKS0t9UcE5DxJc5QXS6VqCP/30E6ZOnYrvvvsO//nPfxAXF1fp78lzRbt27QCQyHzwwQfRpUsXNG3aFK7rIj8/369iZWdnIyoqqiaPaqk2KrdFCCuwLJbaTUFBAVq0aIHPPvsM0dFkzTB27FiMHTsWSikcPHgQK1euREpKCmbPno3vv/8eXbp0CbKGaNWqVZXnbDp06IAOHTr4b//44z4tuDKQnZ2Nw4ePaPsED4w5lCEoFBgTWmQJvRnnaI8nsooAK4vpYeXmpRwj2pTUlR4GT3g026XtJbj28xKeoHkuR4s507YE89uc5M/lwfMEQlwHCo6eLzMGVtpTyxdk2lxKSSjl0PyYnh2jShuZgkJnAUqpK2+OAyUk5RJyY9UgtW0FB4PwHy84hwh4ul2qW6FmKJ/px8WNMakAh7a8UAqeIH8raA8xDvLFkno5wGQ4CiVw9dX9zziMzRjlUrqui7CwMJggcCO4jOgCoGfTqJVobvt5S3Dz5s245ZZbEBMTg/Xr16NJkyZV+v47FxQWFiIQCPjty4ULF6JXr14AgDFjxiApKQkzZszA2rVrkZeXhyuuuKImj2uxVBq7RWixaPwZnjOglMKxY8ewatUqf1Nx3bp1aNeuHfr37x9kDVHdZo6HDx/G+vUbkJGxDTt37sT+/QeosqOrQjqXGgBVfZS+DXq2i/y1jHjRBpwcMDmMYAwMTlnLj5l4Hh2E7BufKi3UjGAiawcpzDwWiRlznRB6C9JxIIWAMVI1Xle0sWcqWdBzVUJbOHC9JWi8uqgNSLNhgBJmvor5lTmubSNoWF9/TRWjeSlt6wWpoBwHjlLaUsIBtH8YaE0AitFz47oMUtLn9h+TsaEA0LhxI7w4e1q1tOXKC65AIFDO1JXhnXfegZQS/fv3R0ZGBp555hlMnz4dU6dOPa9bguXJysrCqFGjfNuSjh074tVXX0VUVBTy8/MxYcIEZGVlISwsDPPmzcPAgQNr+siWKmC2CKMiBiHcaVzh64vFYeQUfV0rtwitwLJYqoiZjfm5NUTjxo19wZWYmIguXbpU+4tgUVER1q1bjy1b0pGdvQt5eXnah6ss19DRmYo0S2QGySl2R0gGxsgo1Zib0tgT8x3bzcyREWa0AWbumywkTC6jVIo2DvUMmJA6MFmLPrI/oCoTub47OgPR5DkymoliNIslPGksTcvEqn4MSk+yM11pY1D0eR2m56Pofb4A44AUVA0zXltG0DHoah2nvytoaw3X0bFAtFFoZuG43syU+rkYf8sNGDwksdq+ruVbgmFhYXAc+hreddddWLZsGYqKisAYQ69evTB06FAMHDgQ8fHx543PlcViMAKrXcTASgusPUXJVmBZLJaywebU1FR/U3HlypVgjPlia8CAAejWrVuVtslORiAQwMaNm/DDD2nIyspCXl4eiotLfGGlFPSAOgkcP28PzPfdMv8i+G08ZapiethdV7wYU7plJ/XGoYOQEBecO2XWDoyVte0Yg5Cejp9xac5LKISEkMgqqw6Z7Ujmizs6hOP7XQF6U1GY6o6D8p5egLFrYL6gNLNSULQuzpkDpv23wKgCBkWTIg4YlB8DREJMURgihVhzKoMxxnBRk0b4f3OerravY3nvtXr16gW1BNPT03HrrbciOjoavXr1woYNG7By5UocOHAAoaGhOHz4MCIiIqrlHBZLdVCXBZadwbqAKSkpwdixY5Geno6IiAi0bNkSSUlJ6NixIwYNGoScnBw0bkzf8JMmTcLUqVNr+MQXBmawOS4uDnFxcXj00UchpcTmzZv9Ctdrr72GY8eO+dYQiYmJ6N27d9DwcmUgS4o+iI3tA4DE3pYt6UhNTcXOnVnYsycXRUVF/qYibSmS+OCcwdPtO2p9CUhwcEdB6MgZ08pT2vaA4n2UNtV0dIuOcgxpe1Gbker8RsYdMMbhBTw4DuC65GnFOYcbQtcrQMcI0QwZZy6kEhQrBF3ZEtIPvyZBKPTj8fyqmdK2ERQxRO72Ugm/GkbROdA5iR4EyI2dKQlPMDiOjuOR5ARvrBs44zonkap6w4YPrhZx9fMtwfLea0opfPjhh3jsscfw1FNP4ZFHHgl637Zt27B582YrriznLaqSPliqFvtg2QrWBUxJSQm++uorXHvttQCAefPmYcmSJfjyyy9x5ZVX4uGHH8aIESNq+JR1EyklsrKysGLFCr/KtXfvXsTGxvqCKy4uLmgVv7rYuXMnNmxIxbZt27Fnzx4cPXoU5MpOG3NKt+uYbs6Zt6X2zzKbiJ4nwAASV9r+gGvRVrbNaExP9eM2AdXaV4oG4Cn6BoosKMDK7CBM2xLQ7UhyQ6Aqmu+Cr2fGdDuT/Li0U7uuzFFli+kFAQVHm5sKTw/nM+7Pg1FuIVXKmKPjfWTwcL4Eg8M4mrVoipf+39NV/pqcbkuwsLAQjz32GJYvX46FCxciMTGx2r8nLJZfClPBahPRH2FOxX3ZSsQR5BWtshUsy/lFWFiYL64AID4+HnPmzPHfpuFoS03AOUenTp3QqVMn3H777VBKITc3F8nJyUhOTsa0adOwffv2E6whGjduXOUX144dO6Jjx47+23l5e3XETzpycvbgyJHDFEMDEiLUbjPmphKBQCmgN+hIIxlfKwYJnVOoA6oBTtt9ugLmhnAtzDgY13mF4HCN0anxoAIZqirJ9YA+fINUABCegutwSMUhZUCbplIFS+r7k0rqViYApvS8GaP3SYVAQII7xj1faksGAU9wUBe1rFLH9ayZ1JU+KvpJDBt2VZW+FkBwS/DnW4IZGRmYNGkS2rVrhw0bNqB58+ZV/nwXOjNnzsTMmTP9t5s2bYpf//rXeOqppzB06NAaPJmlrlE71k4s1cKrr76KkSNH+m8/8cQT6NGjB8aNG4esrKwaPJmFMYZ27dph/Pjx+POf/4xNmzZh9+7dmDZtGgDgpZdeQseOHdG/f3888sgj+OSTT7Bv375qMWZs0+ZXGDbsOjz66CN47bU/4U9/moNbb52A+Pg4NGmqs8MYENAWAkxH8nCnrOoFZRzeJbUClNk2JMHlOtSGDJR60IuBZd5SXKJUO56DMW3uqStLXJjiF2UNanPUkBASe5SZCHjCtCBpG9LzhL5IkEgC5TgqKSCV1GdQ2h6C2qRSCXBHZ0TqViIJMwGhhN5uVJDKg2IKzVs1w8BB8ZV+3pVSKCoqQmFhIRzHQYMGDXxxpZTC4sWLMXjwYIwdOxb//Oc/rbiqAPXq1cOaNWuwevVqvPPOOyguLsaIESOwevXqmj5ancVE5VT8v1P/G7du3Trcd9996NatGxo0aID27dvj5ptvxvbt24M+7rbbbvO3msv/iYmJOen9zp8/HzExMYiIiEDnzp3xxhtvVOox2wpWHWHWrFnIzMzE22+/DQB4//330bZtWwDUOhw+fDg2b95ck0e0lIMxhhYtWuDGG2/EjTfeCKUUfvrpJ98a4q233sLvf/97REVFITEx0a9yRUVFVbnC1bRpUwwZchWGDKHqzLFjx7BmzXfYtOkH5OTsRkFBAc1A6Qoo50xbMXjaUsG05STFyUgFoZT2iJJ6WNyYnypd3QJ8A1LjqiCpmqWg56b8oGoBqbj/MWAcoaEuhKCwatel4XclBRzHpSF8IchEFIysJEDRNcoPmaYZLU8IOLpi5eklALJ8AMpS0cjM9IYbflPp5/h0LcGioiI88cQT+Oyzz/CPf/wDAwcOtC3BCsI5R9++ff234+LiEBkZib/+9a+Ij6+8KLZUBeH/wlXR607FSy+9hFWrVmH06NHo3r07fvzxR7z++uvo3bs31qxZEySgwsPDMX/+/KBfSk8WJfXWW2/hnnvuwejRo/HII48gJSUFDzzwAIqKivDYY49V6OR2BqsOMHv2bCxevBjLly9Hw4YNT/oxERERyMvLqxVGhZaygeg1a9b4M1yrV69GkyZNgsxPo6Ojq2QNIYRAUVGRbxcQFhYGKSW2bt2G9PQtyMjYgd27d+Gnn46bk5Wb36LZJ8dx6XdXIcG46/t2mY1BKK5zDmk7kWapHL29qP28dEVJgT5eSmrv0bUUnE1ROhKO9rOiTUmvzHNLKDgO94f7pVRwXAdKt/5McLbxQ6MoRQXuuNBJhICeS2vVujleeml6pZ7T020J7tixAxMnTkTLli2xYMECtG7dulKfoy4zc+ZMzJkzR88WltG6dWv06dMHy5Ytq6GT1U3MDFbriDiEOhW3ESkVR/Fj0XcnncFavXo1YmNjT/gZuuyyyzB69GgsWLAAAFWwlixZcsL3xM8pLi5GZGQk+vfvj6VLl/q3T5gwAUuXLsXu3bsrlO9pK1gXOHPnzsWiRYuCxJUQAgcPHvTjKJYsWYLWrVtbcVWLYIwhIiICgwYNwqBBg6CUQiAQ8K0hvvjiC8yYMQOu6yIhIeEEa4gzYe6vqKgInPOg2SDHcdC166/Rteuv/Y/fvXs3NmxIxfbt25GdvRuHDx/WwkbRth7jWjRJkI4pG2A3+YFkl6Dd3RX8qo0QJpqHqk+cMziujs5R2hzWoY0+xyFxRxE+5cxRuW5LKgFpqlkMEJ5HMTrQ3lmO61tLMAYyGFWm6lbmB3bjjddV+Gt2pi3Bv//973jggQfw0EMP4amnnjqrr5Pl7Dh27BgKCgqCZg8t5xbTIqzMdafiZNXISy65BF27dkV6evqJ9yUljh8/fspCw1dffYWCggLce++9QbdPmTIFH3zwAZYtW4bx48ef9dmtwLqAyc3NxaOPPopOnTrhyiuvhFIK4eHhWL58OYYNG6bnaagV9emnn9b0cS1VgDGG0NBQ9OvXD/369cNjjz0Gz/OwefNmP1PxT3/6E4qKihAfH++3FXv37o2QkJCgFtThw4fJZNNxEBISgoiIiDO2qCIjIxEZGem/vX//Aaxfvx5bt2YgJycH+/cfoLmn8k7pjOu2otncY+X8tphvS88ZOagz301eQILaeApStx3IFd5RHEKRO72QZETqOGVZimZoX0ihzTt1K5MzKMUgVcA3RqWgbFY2lyUkXJejTZtWiI+PrdDX53QtweLiYjz99NNYunQpPv74YwweXD22D3Udk5OZm5uLxx9/HI0aNcIDDzxQw6equ5zLsOd9+/ahW7duQbcVFhaiUaNGKCwsRJMmTTBu3Di89NJLqF+/vv8xqampAIA+ffoEXdunTx9wzpGammoFloVo27btKTcF165de45PYznXuK6LHj16oEePHrjvvvsgpURmZqZvDfHee+9h79696Nu3r1/hklLi7rvvxvDhw/HCCy8gNDS0Up+7RYvmuPbaa3DttdcAoEDitWvXIT19K7Kzs5Gfn6/9r0gYSaFd4x3dDgzKTySHdwp7pogcilkR2jaBNhmN3QNZQBindYqccRyXshm1+SgA7fZO13iCDFe5FmoAeYnSBiUjawkwCCHw21EVszY53Zbgzp07MWnSJFx00UVYv349fvWrX1Xq+bYEc+zYMT9gG6CfhaVLl/o5o5YLl/fffx+5ubn44x//6N/Wpk0bPP744+jduzeklPj888/x5ptvYtOmTfj666/9SvLevXvhOM4JCyUhISFo1qwZ8vLyKnQWK7AsljoC5xzR0dGIjo7G5MmToZTCnj17kJycjBUrVmDSpEk4cOAAYmJiEBYWhuXLlyM+Pr5arCEaNmyIwYOvxODBVwIgj7YNG1KRlpaGXbtykJubi9JSz59/kkIAnAw9hfCgeFlUjieEL35onItpx3YSWcp3o9dh1opElOM4/kYhYxxgElJJcBZClTBah/RnvaQCtSahEPDIpqJdZFv07dvrrB6zUgolJSUoKSk5aUvwn//8J6ZMmYIpU6Zg+vTpQcLLUjXq1auHlJQUCCGwfft2TJs2DRMnTkRaWhpatWpV08ero5hqc8WvO1u2bt2K++67D4mJiZg4caJ/+/PPPx/0cWPGjEF0dDSeeeYZ/O1vf8OYMWMA0ILJqX6pDA8P939ROlvsT7TFUkdhjCEyMhIDBgxAUlISDh48iIcffhj9+vXDN998gxdeeAE//PADYmJi/EzF/v37o2XLllUWXGFhYUhIiEdCAs1QCCHwww9p+P77jcjKykZeXi6Ki4v0IDrXQkqHQUNCSmrd0U0SSnEw3z2+LFeR0m24H1/EOf2T53kBuA4HA4dUAUCLKZq90pmLUmgrCZOR6GH0mOvP6vGdriVYWlqKZ599Fh9//DE+/PBDXH311bYlWM1wztGrFwnh2NhYdO7cGf369cNzzz2HefPm1fDp6iZSSW2tUvHrzoZ9+/Zh2LBhaNKkCT7++OMz/kw99NBDePbZZ/F///d/vsCKiIhAaWnpST++uLi4wkkJVmBZLHWct956C3v27MGKFSswYMAAAMDo0aOhlMKRI0d8a4g333wTkydPRvv27YOsISIjI6ssEBzHQc+ePdCzZw8AZfEv69enYseOHcjL24vjx4/TkLvjkj+VJ3Trjmsndwbu6OxCmExCCSUFOHOg/K1CPZclBRwHYIomuagdSeJMioCfbyi0aOvQIRK9evU442M5XUtw165dmDRpEiIiIrB+/XrfKsXyy9KnTx+MGzcOf/nLXzBjxgx/wcdyflHk7Uextz/oNlqCOT1Hjx7Ftddei6NHj2LlypVntX0bHh6OZs2aoaCgwL/tV7/6FYQQOHDgQFCbMBAI4ODBg2jTpk0FHo0VWBZLnWfGjBl4/PHH/VxKA2MMjRs3xnXXXYfrrrvON8b87rvvsGLFCnz44YeYOnUqmjdvHmQNcckll1TJGsJ87i5duqBLly7+bTk5Odiw4Xts3ZqO3NxcHDp0BEIqMFCViQKiKS5HKald2LUhqQqAcxcO5/ACAiEhgBPiwNNROVShUgB0uLNkNNcFDuaQp9aYMb897ZnP1BL897//jXvuuQd33nknnnvuOdsSPMc8++yzWLRoEV555RXMmjWrpo9T59C/xpz2Y8LdZgh3mwXdFhDHcKj4h1NeU1JSguHDh2PHjh1Yvnx50L8Zp+PYsWM4cOAAWrRo4d/Ws2dPKKWwbt26oBSUtWvXQkqJnj17ntV9G+xPuMVSxzH+VmeCMYZ69eqdYA2xYcMGJCcn4/PPP8ezzz6L0NBQv504YMAAdO3atVosB6KiohAVFQWA2nT5+flITf0emzdvxq5dOTh06LBe6hB+u48sImg7kbIUyYXeExJcWzFAKQgPvi+XFOZ6ekHgjOHijh3QvXu3U57tTC3BP/zhD1i4cCEWLFiAoUOH2pbgL8zJnt/OnTtj7NixSEpKwpNPPnnKVX3LL4PScc+Vue5USCkxZswYrFmzBp9++ini4uJO+JiSkhIEAgE0aNAg6PbnnnsOAILikwYPHoymTZsiKSkpSGAlJSWhfv36GDZsWIXObo1GLRZLteF5HtLS0pCcnIyUlBSsXLkSxcXFvhdXYmIievbseYI1RHVw5MgRbNiwAZs3b0Fm5k4UFBwkkSRZWdCz0L5XnOa6jAmp8uc8qPrFTACiomieJ6Y9iq5dTx6rcTrj0N27d+PWW2+F4zhYuHChFogWS93BGI02Du+GEKf+mS/4GQFxHIeL005qNPrggw/itddew/XXX4/Ro0efcO3vfvc77Nq1C7169cK4ceNw6aWXAgA+//xzfPbZZ7juuuvwr3/9K+iapKQk3HfffRg1ahSuueYaJCcn4/3338esWbPwxBNPVOjsVmBZLkg6dOiAiIgIhIeHgzGGJ598EqNHj8b+/fsxceJEZGZmIjw8HPPmzcPll19e08e9YJFSYseOHb41xDfffIP8/HzExcX5Fa7Y2Niz8tqqKMXFxdiwIRU//LAZmZmZyM/fB8/zwLQVA4MRVjQgbyJ+zP+lpGH36Es6YsYfnjnh/s/UEvzPf/6Du+66C7fddhuef/75INsAi6WuUCawfg2XV1xgefI4Dhenn1RgXXnllUhOTj7ltUIIHDlyBA888ABWr16NvLw8CCFwySWX4JZbbsEjjzxy0ur6/PnzMWfOHGRlZSEyMhL3338/7r///gqf3QosywVJx44dsXTpUlx22WVBt99xxx1o3749pk+fjnXr1uHGG29Edna2dc0+RyilsHv3br/ClZKSgp07d6J3795+lSshIQGNGjWqdsHleR42btyEtLQ0bNu2HXv35qGkRIdPw0TyQFs3UCK1UgrTpz+Fzp07B91X+ZagabGa8wYCAfzP//wP3nvvPbz77rsYMWLEedESLCkpwdixY5Geno6IiAi0bNkSSUlJ6NixIwYNGoScnBx/Dm/SpEmYOnVqDZ/YciFgBFaj8Evh8noVvt6ThThavPWkAut8x85gWS5IKGz4xN8dFi9ejMzMTAC0vt22bVusWLECgwcPPtdHrJMwxhAVFYVbbrkFt9xyC5RSyM/P993mn3/+eaSlpSEmJsZvKSYkJKBFixZVFimu66JPn97o04f+kVZKYcuWLdi0KQ0ZGRnIzc1FcXEpoEUWFNClS/QJ4up0W4K5ubm4/fbbEQgEsG7dOnTo0KFKZ65u7rrrLn+2ZN68eZg8eTK+/PJLMMbw6quvYsSIipmoWiyWU2MFluWCZcKECQCAuLg4vPjii2CMwfO8oBXt9u3bIycnp6aOWOdhjKFVq1a46aabcNNNN0EphcOHD/vWEK+//jpuu+02XHzxxb41xIABA9C2bdsqCy7GGLp27YquXbv6t+3cuROpqd9j27btyMnZjfHjx/rvO1NL8Msvv8TkyZMxfvx4vPTSS5V2wf+lCAsLCxrcjY+Px5w5c/y3T5X6YLFUB2ezRXiq62orVmBZLkhSUlLQrl07CCHw9NNPY9KkSViwYMFJq1qW8wfGGJo0aYJhw4Zh2LBhUEqhsLAQq1evRkpKCj744AM88MADaNGiRZAXV6dOnapsDQFQa/lkgcCnawl6nocXXngBb7/9Nt555x2MHDnyvGgJnolXX30VI0eO9N9+4oknMH36dMTExGDWrFm4+OKLa/B0lgsN8qqrhMCqxDXnC1ZgWS5I2rVrB4AMLB988EF06dIFTZs2heu6yM/P96tY2dnZdrPrPIYxhvr16+Oqq67CVVddBaUUSktLsX79eiQnJ2PZsmV45plnEBYWFuTFFRMTU21zdadrCf7444+4/fbbcfz4caxdu/ak4ux8ZNasWcjMzMTbb78NgPLbjOnpvHnzMHz4cGzevLkmj2ix1Hqq/iufxXKeUVhYiCNHjvhvL1y40I/NGDNmDJKSkgCQeVxeXh6uuOKKGjmnpeIwxnwxNW3aNCxbtgz5+fn497//jYEDB2LVqlW44YYbEBUVhdGjR+OVV17B2rVrEQgEKly9VEqhuLgYhYWFcBwHDRo08MWVUgpff/01EhMTcdlllyElJaXWiKvZs2fjH//4Bz7//HOEh4cDQJCj/JQpU7Bz504cOnSopo5ouSBRfpuwIn9wGh+s8x1bwbJccOzbtw+jRo0iDySl0LFjRyxYsAAA8OKLL2LChAno3LkzwsLC8MEHH9gNwlqO67ro1asXevXqhalTp0JKiYyMDH9L8X//939x4MAB3xoiMTERffv29S08TsbpWoJCCLz88suYN28e3nrrLdx00021oiUIAHPnzsWiRYuwfPly32hTCIGDBw/6Vd0lS5agdevWaNKkSU0e1XKBURdbhNamwWKxXNAopbBr164ga4hdu3ahd+/evuCKj49Hw4YNwRjDf//7X2RmZmL8+PEnGIfm5+fjjjvuwKFDh/DRRx8hOjq6Bh9ZxcjNzUVkZCQ6deqEhg0bQimF8PBwLF++HFdccQVKS0vBGEOLFi0wd+7cEyxOLJbKYGwa6odeDIdXLCwZAIQswvHSrFpp02AFlsViqVMopbBv3z7fGmLlypXYsmULYmJi0LJlS/z3v//F4MGD8cknnwS1BFeuXInbbrsNN9xwA+bOnYuIiIq/WFgsdQ0jsOqFtofDwyt8vZDFKCzdZQWWxWKx1DaUUkhPT8fYsWORlpaGgQMHYvXq1ejUqRMSEhKQkJCA9PR0zJ8/H2+++SbGjh1ba1qCFktNYwRWREhkpQVWUWB3rRRYdgbLYrHUaTZu3Ihrr70WjDF8+eWXuOKKK1BYWIhvv/0WycnJeOONN5CZmYnvvvvOzzKzWCyWM2ErWBaLpU5z9OhRPPTQQ5g1axZatWp1wvuVUvA8z2YJWiyVwFSwwkPaweFhFb5eyBIUB/bYCpbFYrHUNho1aoT58+ef8v2MMSuuLJaqogSUEpW6rrZifbAsFovFYrFYqhlbwbJYLiAKCgpw1VVX+UPYx48fR1ZWFvLz8zFy5Ejk5OSgcePGAIBJkyZh6tSpNXlci8VSR1CrqyfnAAAFF0lEQVTaaLQy19VWrMCyWC4gmjZtitTUVP/tOXPmIDk5GY0bNwZjDK+++ipGjBhRgye0WCx1EQkJVMI0VNbisGfbIrTUGmbOnAnOOSIjI0/6/sTERHDOcfvtt5/jk52/zJ8/H5MnT/bflrL2/mNlsVgstQkrsCy1ipCQEBw4cADJyclBt+fk5GD16tV+/IcFWLVqFQ4fPoxhw4b5tz3xxBPo0aMHxo0bh6ysrBo8ncViqUtUJoewLI+wdmIFlqVWERoaiqFDh+LDDz8Mun3RokXo1q0bOnXqVEMnO/949913MXHiRHBOP+bvv/8+tm7dio0bN2LAgAEYPnx4DZ/QYrHUGZSE0puEFflTmbbi+YIVWJZaBWMM48aNw8cffwwhytZ3Fy5ciPHjx8PauhHHjx/H4sWLg9qlbdu29f8+ZcoU7Ny5E4cOHaqJ41ksFssFjxVYllrHiBEjUFJSgi+++AIAsGXLFvzwww8YO3ZsDZ/s/GHRokXo2bMnOnfuDAAQQiA/P99//5IlS9C6dWs0adKkpo5osVjqEErJSv+prdgtQkutIzw8HDfccAMWLVrktwsTEhLQvn37mj7aecNf/vIX3Hnnnf7bJSUlGDZsGEpLS8EYQ4sWLfDpp5/W4AktFkvdQgGVmqeqvV0JK7AstZJx48bhd7/7HYqLi/HRRx/hwQcfrOkjnVesXLky6O169eph7dq1NXQai8ViqXtYgWWplVxzzTVwXRfTp09HdnY2xowZU9NHslgsFsspoG3AyhiN2hahxXJOcV0Xo0aNwty5c3H11VejefPmNX0ki8VisZwKVckWYS1eXLICy1JrmTx5Mvbv34/f//73NX0Ui8VisViCsALLUmvp27cvPvnkk5o+hsVisVjOiATAKnld7cQKLEutwoQYn+79Z/oYi8VisZxbVCUFVm2ewWLKOjNaLBaLxWL5BdiwYQP69OkDxsLBmFPh68nRvRjr169H7969f4ET/nLYCpbFYrFYLJZfljo45G6d3C0WS61m6tSpuPjii8E5x6ZNm/zb9+/fj6FDh6Jz587o3r07UlJS/PcVFRVh/PjxiI6OxqWXXoolS5bUxNEtljqDDXu2WCyWWsbo0aPxzTffoEOHDkG3T5s2DQkJCdi2bRveffddjB8/3s+vnD17NsLDw7F9+3Z8/vnnuPfee20uo8ViqVaswLJYLLWaAQMGoE2bNicEfS9evBh33303ACA2NhZt27bFihUrAAAfffSR/74OHTrgyiuvxN///vdze3CLpU6hACUr/sdG5VgsFsv5Q0FBATzPQ8uWLf3b2rdvj5ycHABATk5OUHZl+fdZLJZfAglVKZsGK7AsFovFYrFYgmjevDnq1auHwsLCSt9HvXr1amVahxVYFovlgqNp06ZwXRf5+fl+FSs7OxtRUVEAqGK1a9cutGrVyn/fNddcU2PntVguVKKiopCeno4DBw5U+j6aN2/u/+zWJqzAslgsFySjR49GUlISZsyYgbVr1yIvLw9XXHEFAOCmm27Cn//8Z8TFxSErKwsrVqxAUlJSDZ/YYrkwiYqKqpUCqapYo1GLxVKrufvuu7Fs2TLs27cPzZo1Q8OGDbFt2zbk5+djwoQJyMrKQlhYGObNm4eBAwcCAAoLC3H77bdj3bp1cF0Xzz//PEaNGlXDj8RisVxIWIFlsVgsFovFUs1YmwaLxWKxWCyWasYKLIvFYrFYLJZqxgosi8VisVgslmrm/wOWHuaew7TvCAAAAABJRU5ErkJggg==\" />"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(mm, rr, cs, st = :surface)\n",
+    "xlabel!(\"M\")\n",
+    "ylabel!(\"R\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:40:55.547125",
+     "start_time": "2016-12-05T05:40:52.909Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script charset=\"utf-8\" type='text/javascript'>\n",
+       "    // This script was adapted from\n",
+       "// https://github.com/JuliaLang/Interact.jl/blob/master/src/IJulia/ijulia.js\n",
+       "(function (IPython, $) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    function resolve_promises(comm, val) {\n",
+       "        val === undefined && (val = null);\n",
+       "        if (val && val.constructor == Promise) {\n",
+       "            val.then(function(val) {\n",
+       "                return resolve_promises(comm, val);\n",
+       "            })\n",
+       "        } else {\n",
+       "            return val;\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        console.log(\"plotly comm init\");\n",
+       "\t    comm_manager.register_target(\"plotlyjs_eval\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                // Call the code in the message\n",
+       "                eval(msg.content.data.code);\n",
+       "\n",
+       "                // Clean up\n",
+       "                delete msg.content.data.code;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "        comm_manager.register_target(\"plotlyjs_return\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                // Call the code in the message\n",
+       "                val = eval(msg.content.data.code);\n",
+       "\n",
+       "                // resolve any promises so we get a raw value\n",
+       "                val = resolve_promises(comm, val);\n",
+       "                console.log(\"About to send\", val);\n",
+       "\n",
+       "                // Send the value back to Julia\n",
+       "                comm.send({action: \"plotlyjs_ret_val\", ret: val});\n",
+       "\n",
+       "                // Clean up\n",
+       "                delete msg.content.data.code;  // clean up\n",
+       "                delete val;\n",
+       "            });\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "        console.log(e);\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery);\n",
+       "\n",
+       "</script>\n",
+       "\n",
+       " <script charset=\"utf-8\" type='text/javascript'>\n",
+       "     define('plotly', function(require, exports, module) {\n",
+       "         /**\n",
+       "* plotly.js v1.19.1\n",
+       "* Copyright 2012-2016, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
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t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,t|=t>>>16,t-(t>>>1)},r.parity=function(t){return t^=t>>>16,t^=t>>>8,t^=t>>>4,t&=15,27030>>>t&1};var a=new Array(256);!function(t){for(var e=0;e<256;++e){var r=e,n=e,i=7;for(r>>>=1;r;r>>>=1)n<<=1,n|=1&r,--i;t[e]=n<<i&255}}(a),r.reverse=function(t){return a[255&t]<<24|a[t>>>8&255]<<16|a[t>>>16&255]<<8|a[t>>>24&255]},r.interleave2=function(t,e){return t&=65535,t=16711935&(t|t<<8),t=252645135&(t|t<<4),t=858993459&(t|t<<2),t=1431655765&(t|t<<1),e&=65535,e=16711935&(e|e<<8),e=252645135&(e|e<<4),e=858993459&(e|e<<2),e=1431655765&(e|e<<1),t|e<<1},r.deinterleave2=function(t,e){return t=t>>>e&1431655765,t=858993459&(t|t>>>1),t=252645135&(t|t>>>2),t=16711935&(t|t>>>4),t=65535&(t|t>>>16),t<<16>>16},r.interleave3=function(t,e,r){return 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e?this.words[n]=this.words[n]|1<<i:this.words[n]=this.words[n]&~(1<<i),this.strip()},i.prototype.iadd=function(t){if(this.sign&&!t.sign){this.sign=!1;var e=this.isub(t);return this.sign=!this.sign,this._normSign()}if(!this.sign&&t.sign){t.sign=!1;var e=this.isub(t);return t.sign=!0,e._normSign()}var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++){var e=r.words[a]+n.words[a]+i;this.words[a]=67108863&e,i=e>>>26}for(;0!==i&&a<r.length;a++){var e=r.words[a]+i;this.words[a]=67108863&e,i=e>>>26}if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},i.prototype.add=function(t){if(t.sign&&!this.sign){t.sign=!1;var e=this.sub(t);return t.sign=!0,e}if(!t.sign&&this.sign){this.sign=!1;var e=t.sub(this);return this.sign=!0,e}return this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(t.sign){t.sign=!1;var e=this.iadd(t);return t.sign=!0,e._normSign()}if(this.sign)return this.sign=!1,this.iadd(t),this.sign=!0,this._normSign();var r=this.cmp(t);if(0===r)return this.sign=!1,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++){var e=n.words[o]-i.words[o]+a;a=e>>26,this.words[o]=67108863&e}for(;0!==a&&o<n.length;o++){var e=n.words[o]+a;a=e>>26,this.words[o]=67108863&e}if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.sign=!0),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)},i.prototype._smallMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0;n<e.length-1;n++){for(var i=r>>>26,a=67108863&r,o=Math.min(n,t.length-1),s=Math.max(0,n-this.length+1);s<=o;s++){var l=n-s,u=0|this.words[l],c=0|t.words[s],h=u*c,f=67108863&h;i=i+(h/67108864|0)|0,f=f+a|0,a=67108863&f,i=i+(f>>>26)|0}e.words[n]=a,r=i}return 0!==r?e.words[n]=r:e.length--,e.strip()},i.prototype._bigMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0,i=0;i<e.length-1;i++){var a=n;n=0;for(var o=67108863&r,s=Math.min(i,t.length-1),l=Math.max(0,i-this.length+1);l<=s;l++){var u=i-l,c=0|this.words[u],h=0|t.words[l],f=c*h,d=67108863&f;a=a+(f/67108864|0)|0,d=d+o|0,o=67108863&d,a=a+(d>>>26)|0,n+=a>>>26,a&=67108863}e.words[i]=o,r=a,a=n}return 0!==r?e.words[i]=r:e.length--,e.strip()},i.prototype.mulTo=function(t,e){var r;return r=this.length+t.length<63?this._smallMulTo(t,e):this._bigMulTo(t,e)},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.imul=function(t){if(0===this.cmpn(0)||0===t.cmpn(0))return this.words[0]=0,this.length=1,this;var e=this.length,r=t.length;this.sign=t.sign!==this.sign,this.length=this.length+t.length,this.words[this.length-1]=0;for(var n=this.length-2;n>=0;n--){for(var i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);s<=o;s++){var l=n-s,u=this.words[l],c=t.words[s],h=u*c,f=67108863&h;i+=h/67108864|0,f+=a,a=67108863&f,i+=f>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var d=this.words[l]+i;this.words[l]=67108863&d,i=d>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var o=this.length-1;o>=0;o--)this.words[o+n]=this.words[o];for(var o=0;o<n;o++)this.words[o]=0;this.length+=n}return this.strip()},i.prototype.ishrn=function(t,e,n){r(\"number\"==typeof t&&t>=0);var i;i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=n;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o){this.length-=o;for(var u=0;u<this.length;u++)this.words[u]=this.words[u+o]}else this.words[0]=0,this.length=1;for(var c=0,u=this.length-1;u>=0&&(0!==c||u>=i);u--){var h=this.words[u];this.words[u]=c<<26-a|h>>>a,c=h&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip(),this},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.testn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n)return!1;var a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),t<0?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),t<0)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(s===-1),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var h=n.clone()._ishlnsubmul(a,1,u);h.sign||(n=h,l&&(l.words[u]=1));for(var f=u-1;f>=0;f--){var d=67108864*n.words[a.length+f]+n.words[a.length+f-1];for(d=Math.min(d/o|0,67108863),n._ishlnsubmul(a,d,f);n.sign;)d--,n.sign=!1,n._ishlnsubmul(a,1,f),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[f]=d)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(t<=67108863);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(t<=67108863);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),h=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(h).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(h).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;a<n+1;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=t<0;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:n<t?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new f(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(h,s),h.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function t(e){if(v[e])return v[e];var t;if(\"k256\"===e)t=new l;else if(\"p224\"===e)t=new u;else if(\"p192\"===e)t=new c;else{if(\"p25519\"!==e)throw new Error(\"Unknown prime \"+e);t=new h}return v[e]=t,t},f.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},f.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},f.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},f.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},f.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},f.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},f.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},f.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},f.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},f.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},f.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},f.prototype.isqr=function(t){return this.imul(t,t)},f.prototype.sqr=function(t){return this.mul(t,t)},f.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),h=this.m.bitLength();for(h=new i(2*h*h).toRed(this);0!==this.pow(h,c).cmp(u);)h.redIAdd(u);for(var f=this.pow(h,o),a=this.pow(t,o.addn(1).ishrn(1)),d=this.pow(t,o),p=s;0!==d.cmp(l);){for(var g=d,m=0;0!==g.cmp(l);m++)g=g.redSqr();r(m<p);var v=this.pow(f,new i(1).ishln(p-m-1));a=a.redMul(v),f=v.redSqr(),d=d.redMul(f),p=m}return a},f.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},f.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},f.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},f.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new d(t)},n(d,f),d.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},d.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},d.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},d.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var 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S=0;S<3;++S)O[S]+=M*R[S]*this.tickPad[S]/r[5*S];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],O,this.tickColor[A])}if(this.labelEnable[A]){for(var S=0;S<3;++S)O[S]+=M*R[S]*this.labelPad[S]/r[5*S];O[A]+=.5*(s[0][A]+s[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],O,this.labelColor[A])}}},p.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":121,\"./lib/cube.js\":122,\"./lib/lines.js\":123,\"./lib/text.js\":125,\"./lib/ticks.js\":126}],121:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}function i(t){for(var e=[],r=[],i=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,h=[0,0,0],f=[0,0,0],d=-1;d<=1;d+=2){r.push(i,i+2,i+1,i+1,i+2,i+3),h[l]=d,f[l]=d;for(var p=-1;p<=1;p+=2){h[u]=p;for(var g=-1;g<=1;g+=2)h[c]=g,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),i+=1}var m=u;u=c,c=m}var v=a(t,new 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s=n(f);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},g.drawGrid=function(t,e,r,a,o,s){if(this.gridCount[t]){var l=n(h);l[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[e]+=r[0][e],this.shader.uniforms.offset=u;var p=n(c);p[t]=1,this.shader.uniforms.majorAxis=p;var g=n(f);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},g.drawZero=function(t,e,r,a,o,s){var l=n(h);this.shader.uniforms.majorAxis=l,l[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[t]+=r[0][t],this.shader.uniforms.offset=u;var c=n(f);c[e]=1,this.shader.uniforms.screenAxis=c,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,6)},g.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":124,\"gl-buffer\":128,\"gl-vao\":236}],124:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.line=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"}])};var o=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvoid main() {  \\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n  mat2 planeXform = scale * mat2(cos(angle), sin(angle),\\n                                -sin(angle), cos(angle));\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n  vec4 worldPosition = model * vec4(dataPosition, 1);\\n  \\n  //Compute clip position\\n  vec4 viewPosition = view * worldPosition;\\n  vec4 clipPosition = projection * viewPosition;\\n  clipPosition /= clipPosition.w;\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec4(viewOffset, 0, 0);\\n\\n  //Done\\n  gl_Position = clipPosition;\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.text=function(t){return n(t,o,s,null,[{name:\"position\",type:\"vec3\"}])};var l=\"#define GLSLIFY 1\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  if(dot(normal, enable) > 0.0) {\\n    vec3 nPosition = mix(bounds[0], bounds[1], 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n  colorChannel = abs(normal);\\n}\",u=\"precision mediump float;\\n#define 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g=[0,0,0];d.drawTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=g;a[0]=a[1]=a[2]=0,a[t]=1,this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}};var m=[0,0,0];d.drawLabel=function(t,e,r,n,i){this.labelCount[t]&&(this.shader.uniforms.axis=m,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},d.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this,t(\"_process\"))},{\"./shaders\":124,_process:445,\"gl-buffer\":128,\"gl-vao\":236,\"vectorize-text\":509}],126:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u=0|u);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var h=\"\"+u;h.length<i;)h=\"0\"+h;return c+\".\"+h}return c}function i(t,e){for(var r=[],i=0;i<3;++i){for(var a=[],o=(.5*(t[0][i]+t[1][i]),0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:n(e[i],o)});for(var o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:n(e[i],o)});r.push(a)}return r}function a(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}r.create=i,r.equal=a},{}],127:[function(t,e,r){\"use strict\";function n(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}function i(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=p,s=g,l=0;l<3;++l)s[l]=o[l]=r[l];s[3]=o[3]=1,s[a]+=1,h(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,h(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,c=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+c*c)}return t}function a(t,e,r,n,a){var h=e.model||f,p=e.view||f,g=e.projection||f,y=t.bounds,a=a||l(h,p,g,y),x=a.axis;a.edges;u(d,p,h),u(d,g,d);for(var b=m,_=0;_<3;++_)b[_].lo=1/0,b[_].hi=-(1/0),b[_].pixelsPerDataUnit=1/0;var w=o(c(d,d));c(d,d);for(var M=0;M<3;++M){var A=(M+1)%3,k=(M+2)%3,T=v;t:for(var _=0;_<2;++_){var E=[];if(x[M]<0!=!!_){T[M]=y[_][M];for(var S=0;S<2;++S){T[A]=y[S^_][A];for(var L=0;L<2;++L)T[k]=y[L^S^_][k],E.push(T.slice())}for(var S=0;S<w.length;++S){if(0===E.length)continue t;E=s.positive(E,w[S])}for(var S=0;S<E.length;++S)for(var k=E[S],z=i(v,d,k,r,n),L=0;L<3;++L)b[L].lo=Math.min(b[L].lo,k[L]),b[L].hi=Math.max(b[L].hi,k[L]),L!==M&&(b[L].pixelsPerDataUnit=Math.min(b[L].pixelsPerDataUnit,Math.abs(z[L])))}}}return b}e.exports=a;var o=t(\"extract-frustum-planes\"),s=t(\"split-polygon\"),l=t(\"./lib/cube.js\"),u=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/transpose\"),h=t(\"gl-vec4/transformMat4\"),f=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),d=new Float32Array(16),p=[0,0,0,1],g=[0,0,0,1],m=[new n(1/0,-(1/0),1/0),new n(1/0,-(1/0),1/0),new n(1/0,-(1/0),1/0)],v=[0,0,0]},{\"./lib/cube.js\":122,\"extract-frustum-planes\":103,\"gl-mat4/multiply\":151,\"gl-mat4/transpose\":159,\"gl-vec4/transformMat4\":242,\"split-polygon\":483}],128:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}function i(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function a(t,e){for(var r=l.malloc(t.length,e),n=t.length,i=0;i<n;++i)r[i]=t[i];return r}function o(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}function s(t,e,r,i){if(r=r||t.ARRAY_BUFFER,i=i||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(i!==t.DYNAMIC_DRAW&&i!==t.STATIC_DRAW&&i!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var a=t.createBuffer(),o=new n(t,r,a,0,i);return o.update(e),o}var l=t(\"typedarray-pool\"),u=t(\"ndarray-ops\"),c=t(\"ndarray\"),h=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"],f=n.prototype;f.bind=function(){this.gl.bindBuffer(this.type,this.handle)},f.unbind=function(){this.gl.bindBuffer(this.type,null)},f.dispose=function(){this.gl.deleteBuffer(this.handle)},f.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof 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:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},{}],130:[function(t,e,r){var n=t(\"./1.0/numbers\");e.exports=function(t){return n[t]}},{\"./1.0/numbers\":129}],131:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.plot=t,this.shader=e,this.bufferHi=r,this.bufferLo=n,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.color=[0,0,0,1]}function i(t,e){var r=a(t.gl,l.vertex,l.fragment),i=o(t.gl),s=o(t.gl),u=new n(t,r,i,s);return u.update(e),t.addObject(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"typedarray-pool\"),l=t(\"./lib/shaders\");e.exports=i;var u=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]],c=n.prototype;c.draw=function(){var t=new Float32Array([0,0]),e=new Float32Array([0,0]),r=new Float32Array([0,0]),n=new Float32Array([0,0]),i=[1,1];return function(){var a=this.plot,o=this.shader,s=this.bounds,l=this.numPoints;if(l){var 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h=0;h<3;++h)e.lineWidth(this.lineWidth[h]),r.capSize=this.capSize[h]*u,e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var f=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();h.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;u<3;++u){this.lineOffset[u]=l;t:for(var c=0;c<s;++c){for(var h=r[c],f=0;f<3;++f)if(isNaN(h[f])||!isFinite(h[f]))continue t;var d=n[c],p=e[u];if(Array.isArray(p[0])&&(p=e[c]),3===p.length&&(p=[p[0],p[1],p[2],1]),!isNaN(d[0][u])&&!isNaN(d[1][u])){if(d[0][u]<0){var g=h.slice();g[u]+=d[0][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,g[0],g[1],g[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,p,u)}if(d[1][u]>0){var g=h.slice();g[u]+=d[1][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,g[0],g[1],g[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,p,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":134,\"gl-buffer\":128,\"gl-vao\":236}],134:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":220}],135:[function(t,e,r){\"use strict\";function n(t){var e=t.getParameter(t.FRAMEBUFFER_BINDING),r=t.getParameter(t.RENDERBUFFER_BINDING),n=t.getParameter(t.TEXTURE_BINDING_2D);return[e,r,n]}function i(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function a(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);y=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(var a=n;a<r;++a)i[a]=t.NONE;y[n]=i}}function o(t){switch(t){case p:throw new Error(\"gl-fbo: Framebuffer unsupported\");case g:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case m:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case v:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function s(t,e,r,n,i,a){if(!n)return null;var o=d(t,e,r,i,n);return o.magFilter=t.NEAREST,o.minFilter=t.NEAREST,o.mipSamples=1,o.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,a,t.TEXTURE_2D,o.handle,0),o}function l(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function u(t){var e=n(t.gl),r=t.gl,a=t.handle=r.createFramebuffer(),u=t._shape[0],c=t._shape[1],h=t.color.length,f=t._ext,d=t._useStencil,p=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,a);for(var m=0;m<h;++m)t.color[m]=s(r,u,c,g,r.RGBA,r.COLOR_ATTACHMENT0+m);0===h?(t._color_rb=l(r,u,c,r.RGBA4,r.COLOR_ATTACHMENT0),f&&f.drawBuffersWEBGL(y[0])):h>1&&f.drawBuffersWEBGL(y[h]);var v=r.getExtension(\"WEBGL_depth_texture\");v?d?t.depth=s(r,u,c,v.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):p&&d?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(var m=0;m<t.color.length;++m)t.color[m].dispose(),t.color[m]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(x)}i(r,e)}function c(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var l=0;l<i;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,h=[0|e,0|r];Object.defineProperties(h,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=h,u(this)}function h(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(e<0||e>s||r<0||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function f(t,e,r,n){p||(p=t.FRAMEBUFFER_UNSUPPORTED,g=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,m=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,v=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);\n",
+       "if(e<0||e>o||r<0||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");n=n||{};var s=1;if(\"color\"in n){if(s=Math.max(0|n.color,0),s<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var h=!0;\"depth\"in n&&(h=!!n.depth);var f=!1;return\"stencil\"in n&&(f=!!n.stencil),new c(t,e,r,l,s,h,f,i)}var d=t(\"gl-texture2d\");e.exports=f;var p,g,m,v,y=null,x=c.prototype;Object.defineProperties(x,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return h(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t=0|t,h(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t=0|t,h(this,this._shape[0],t),t},enumerable:!1}}),x.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},x.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":232}],136:[function(t,e,r){function n(t,e,r){\"use strict\";var n=o(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===a.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=i(\"Error compiling %s shader %s:\\n\",l,n),c=i(\"%s%s\",u,t),h=t.split(\"\\n\"),f={},d=0;d<h.length;d++){var p=h[d];if(\"\"!==p){var g=parseInt(p.split(\":\")[2]);if(isNaN(g))throw new Error(i(\"Could not parse error: %s\",p));f[g]=p}}for(var m=s(e).split(\"\\n\"),d=0;d<m.length;d++)if(f[d+3]||f[d+2]||f[d+1]){var v=m[d];if(u+=v+\"\\n\",f[d+1]){var y=f[d+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),u+=i(\"^^^ %s\\n\\n\",y)}}return{long:u.trim(),short:c.trim()}}var i=t(\"sprintf-js\").sprintf,a=t(\"gl-constants/lookup\"),o=t(\"glsl-shader-name\"),s=t(\"add-line-numbers\");e.exports=n},{\"add-line-numbers\":29,\"gl-constants/lookup\":130,\"glsl-shader-name\":244,\"sprintf-js\":484}],137:[function(t,e,r){r.lineVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi, dLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvec2 project_2_1(vec2 scHi, vec2 scLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi\\n       + scLo * posHi\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 dir = project_2_1(scaleHi, scaleLo, dHi, dLo);\\n  vec2 n = 0.5 * width * normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(p + n, 0.0, 1.0);\\n}\",r.lineFragment=\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\",r.mitreVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo;\\nuniform float radius;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  gl_Position = vec4(p, 0.0, 1.0);\\n  gl_PointSize = radius;\\n}\",r.mitreFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\nattribute vec4 pick0, pick1;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 n = width * normalize(screenShape.yx * vec2(dHi.y, -dHi.x)) / screenShape.xy;\\n  gl_Position = vec4(p + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\",r.fillVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, projectAxis;\\nuniform float projectValue, depth;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  if(dHi.y < 0.0 || (dHi.y == 0.0 && dHi.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\",r.fillFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\"},{}],138:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l){this.plot=t,this.dashPattern=e,this.lineBufferHi=r,this.lineBufferLo=n,this.pickBuffer=i,this.lineShader=a,this.mitreShader=o,this.fillShader=s,this.pickShader=l,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=s(r),c=l(r,[1,1]),f=o(r,h.lineVertex,h.lineFragment),d=o(r,h.mitreVertex,h.mitreFragment),p=o(r,h.fillVertex,h.fillFragment),g=o(r,h.pickVertex,h.pickFragment),m=new n(t,c,i,a,u,f,d,p,g);return t.addObject(m),m.update(e),m}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),h=t(\"./lib/shaders\"),f=n.prototype;f.setProjectionModel=function(){var t={scaleHi:new Float32Array([0,0]),scaleLo:new Float32Array([0,0]),translateHi:new Float32Array([0,0]),translateLo:new Float32Array([0,0]),screenShape:[0,0]};return function(){var e=this.bounds,r=this.plot.viewBox,n=this.plot.dataBox,i=e[2]-e[0],a=e[3]-e[1],o=n[2]-n[0],s=n[3]-n[1],l=r[2]-r[0],u=r[3]-r[1],c=2*i/o,h=2*a/s,f=2*(e[0]-n[0])/o-1,d=2*(e[1]-n[1])/s-1;return t.scaleHi[0]=c,t.scaleHi[1]=h,t.scaleLo[0]=c-t.scaleHi[0],t.scaleLo[1]=h-t.scaleHi[1],t.translateHi[0]=f,t.translateHi[1]=d,t.translateLo[0]=f-t.translateHi[0],t.translateLo[1]=d-t.translateHi[1],t.screenShape[0]=l,t.screenShape[1]=u,t}}(),f.setProjectionUniforms=function(t,e){t.scaleHi=e.scaleHi,t.scaleLo=e.scaleLo,t.translateHi=e.translateHi,t.translateLo=e.translateLo,t.screenShape=e.screenShape},f.draw=function(){var t=[1,0],e=[-1,0],r=[0,1],n=[0,-1];return function(){var i=this.vertCount;if(i){var a=this.setProjectionModel(),o=this.plot,s=this.width,l=o.gl,u=o.pixelRatio,c=this.color,h=this.fillShader.attributes;this.lineBufferLo.bind(),h.aLo.pointer(l.FLOAT,!1,16,0),this.lineBufferHi.bind();var f=this.fill;if(f[0]||f[1]||f[2]||f[3]){var d=this.fillShader;d.bind();var p=d.uniforms;this.setProjectionUniforms(p,a),p.depth=o.nextDepthValue(),h.aHi.pointer(l.FLOAT,!1,16,0),h.dHi.pointer(l.FLOAT,!1,16,8),l.depthMask(!0),l.enable(l.DEPTH_TEST);var g=this.fillColor;f[0]&&(p.color=g[0],p.projectAxis=e,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[1]&&(p.color=g[1],p.projectAxis=n,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[2]&&(p.color=g[2],p.projectAxis=t,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[3]&&(p.color=g[3],p.projectAxis=r,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),l.depthMask(!1),l.disable(l.DEPTH_TEST)}var m=this.lineShader;m.bind(),this.lineBufferLo.bind(),m.attributes.aLo.pointer(l.FLOAT,!1,16,0),m.attributes.dLo.pointer(l.FLOAT,!1,16,8),this.lineBufferHi.bind();var v=m.uniforms;this.setProjectionUniforms(v,a),v.color=c,v.width=s*u,v.dashPattern=this.dashPattern.bind(),v.dashLength=this.dashLength*u;var y=m.attributes;if(y.aHi.pointer(l.FLOAT,!1,16,0),y.dHi.pointer(l.FLOAT,!1,16,8),l.drawArrays(l.TRIANGLES,0,i),s>2&&!this.usingDashes){var x=this.mitreShader;this.lineBufferLo.bind(),x.attributes.aLo.pointer(l.FLOAT,!1,48,0),this.lineBufferHi.bind(),x.bind();var b=x.uniforms;this.setProjectionUniforms(b,a),b.color=c,b.radius=s*u,x.attributes.aHi.pointer(l.FLOAT,!1,48,0),l.drawArrays(l.POINTS,0,i/3|0)}}}}(),f.drawPick=function(){var t=[0,0,0,0];return function(e){var r=this.vertCount,n=this.numPoints;if(this.pickOffset=e,!r)return e+n;var i=this.setProjectionModel(),a=this.plot,o=this.width,s=a.gl,l=a.pickPixelRatio,u=this.pickShader,c=this.pickBuffer;t[0]=255&e,t[1]=e>>>8&255,t[2]=e>>>16&255,t[3]=e>>>24,u.bind();var h=u.uniforms;this.setProjectionUniforms(h,i),h.width=o*l,h.pickOffset=t;var f=u.attributes;return this.lineBufferHi.bind(),f.aHi.pointer(s.FLOAT,!1,16,0),f.dHi.pointer(s.FLOAT,!1,16,8),this.lineBufferLo.bind(),f.aLo.pointer(s.FLOAT,!1,16,0),c.bind(),f.pick0.pointer(s.UNSIGNED_BYTE,!1,8,0),f.pick1.pointer(s.UNSIGNED_BYTE,!1,8,4),s.drawArrays(s.TRIANGLES,0,r),e+n}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(r<n||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},f.update=function(t){t=t||{};var e,r,n,a,o,s=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var h=t.dashes||[1],f=0;for(e=0;e<h.length;++e)f+=h[e];var d=c.mallocUint8(f);n=0;var p=255;for(e=0;e<h.length;++e){for(r=0;r<h[e];++r)d[n++]=p;p^=255}this.dashPattern.dispose(),this.usingDashes=h.length>1,this.dashPattern=l(s,u(d,[f,1,4],[1,0,0])),this.dashPattern.minFilter=s.NEAREST,this.dashPattern.magFilter=s.NEAREST,this.dashLength=f,c.free(d);var g=t.positions;this.data=g;var m=this.bounds;m[0]=m[1]=1/0,m[2]=m[3]=-(1/0);var v=this.numPoints=g.length>>>1;if(0!==v){for(e=0;e<v;++e)a=g[2*e],o=g[2*e+1],isNaN(a)||isNaN(o)||(m[0]=Math.min(m[0],a),m[1]=Math.min(m[1],o),m[2]=Math.max(m[2],a),m[3]=Math.max(m[3],o));m[0]===m[2]&&(m[2]+=1),m[3]===m[1]&&(m[3]+=1);var y=c.mallocFloat64(24*(v-1)),x=c.mallocFloat32(24*(v-1)),b=c.mallocFloat32(24*(v-1)),_=c.mallocUint32(12*(v-1)),w=x.length,M=_.length;n=v;for(var A=0;n>1;){var k=--n;a=g[2*n],o=g[2*n+1];var T=k-1,E=g[2*T],S=g[2*T+1];if(!(isNaN(a)||isNaN(o)||isNaN(E)||isNaN(S))){A+=1,a=(a-m[0])/(m[2]-m[0]),o=(o-m[1])/(m[3]-m[1]),E=(E-m[0])/(m[2]-m[0]),S=(S-m[1])/(m[3]-m[1]);var L=E-a,z=S-o,C=k|1<<24,I=k-1,P=k,D=k-1|1<<24;y[--w]=-z,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I,y[--w]=z,y[--w]=L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=-z,y[--w]=-L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=z,y[--w]=L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=-z,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I,y[--w]=z,y[--w]=L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I}}for(e=0;e<y.length;e++)x[e]=y[e],b[e]=y[e]-x[e];this.vertCount=6*A,this.lineBufferHi.update(x.subarray(w)),this.lineBufferLo.update(b.subarray(w)),this.pickBuffer.update(_.subarray(M)),c.free(y),c.free(x),c.free(b),c.free(_)}},f.dispose=function(){this.plot.removeObject(this),this.lineBufferLo.dispose(),this.lineBufferHi.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":137,\"gl-buffer\":128,\"gl-shader\":220,\"gl-texture2d\":232,ndarray:427,\"typedarray-pool\":496}],139:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":220}],140:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=m(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=d(new Array(1024),[256,1,4]),h=0;h<1024;++h)s.data[h]=255;var f=c(e,s);f.wrap=e.REPEAT;var p=new o(e,r,n,i,a,f);return p.update(t),p}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),h=t(\"glsl-read-float\"),f=t(\"binary-search-bounds\"),d=t(\"ndarray\"),p=t(\"./lib/shaders\"),g=p.createShader,m=p.createPickShader,v=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){var e,r;this.dirty=!0;var i=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var a=t.position||t.positions;if(a){var o=t.color||t.colors||[0,0,0,1],s=t.lineWidth||1,l=[],u=[],c=[],h=0,p=0,g=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],m=!1;t:for(e=1;e<a.length;++e){var v=a[e-1],y=a[e];for(u.push(h),c.push(v.slice()),r=0;r<3;++r){if(isNaN(v[r])||isNaN(y[r])||!isFinite(v[r])||!isFinite(y[r])){if(!i&&l.length>0){for(var x=0;x<24;++x)l.push(l[l.length-12]);p+=2,m=!0}continue t}g[0][r]=Math.min(g[0][r],v[r],y[r]),g[1][r]=Math.max(g[1][r],v[r],y[r])}var b,_;Array.isArray(o[0])?(b=o[e-1],_=o[e]):b=_=o,3===b.length&&(b=[b[0],b[1],b[2],1]),3===_.length&&(_=[_[0],_[1],_[2],1]);var w;w=Array.isArray(s)?s[e-1]:s;var M=h;if(h+=n(v,y),m){for(r=0;r<2;++r)l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,b[0],b[1],b[2],b[3]);p+=2,m=!1}l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,b[0],b[1],b[2],b[3],v[0],v[1],v[2],y[0],y[1],y[2],M,-w,b[0],b[1],b[2],b[3],y[0],y[1],y[2],v[0],v[1],v[2],h,-w,_[0],_[1],_[2],_[3],y[0],y[1],y[2],v[0],v[1],v[2],h,w,_[0],_[1],_[2],_[3]),p+=4}if(this.buffer.update(l),u.push(h),c.push(a[a.length-1].slice()),this.bounds=g,this.vertexCount=p,this.points=c,this.arcLength=u,\"dashes\"in t){var A=t.dashes,k=A.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var T=d(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)T.set(e,0,r,0);1&f.le(k,k[k.length-1]*e/255)?T.set(e,0,0,0):T.set(e,0,0,255)}this.texture.setPixels(T)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=h(t.value[0],t.value[1],t.value[2],0),r=f.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;u<3;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(o<.5?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":139,\"binary-search-bounds\":53,\"gl-buffer\":128,\"gl-texture2d\":232,\"gl-vao\":236,\"glsl-read-float\":243,ndarray:427}],141:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],142:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=c*o-s*u,f=-c*a+s*l,d=u*a-o*l,p=r*h+n*f+i*d;return p?(p=1/p,t[0]=h*p,t[1]=(-c*n+i*u)*p,t[2]=(s*n-i*o)*p,t[3]=f*p,t[4]=(c*r-i*l)*p,t[5]=(-s*r+i*a)*p,t[6]=d*p,t[7]=(-u*r+n*l)*p,t[8]=(o*r-n*a)*p,t):null}e.exports=n},{}],143:[function(t,e,r){function n(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}e.exports=n},{}],144:[function(t,e,r){function n(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],145:[function(t,e,r){function n(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],g=t[14],m=t[15],v=e*o-r*a,y=e*s-n*a,x=e*l-i*a,b=r*s-n*o,_=r*l-i*o,w=n*l-i*s,M=u*p-c*d,A=u*g-h*d,k=u*m-f*d,T=c*g-h*p,E=c*m-f*p,S=h*m-f*g;return v*S-y*E+x*T+b*k-_*A+w*M}e.exports=n},{}],146:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-m,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+g,t[7]=0,t[8]=f+m,t[9]=d-g,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],147:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,g=a*u,m=o*s,v=o*l,y=o*u;return t[0]=1-(d+g),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+g),t[6]=p+m,t[7]=0,t[8]=f+v,t[9]=p-m,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],148:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],149:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,A=c*g-h*p,k=c*m-f*p,T=c*v-d*p,E=h*m-f*g,S=h*v-d*g,L=f*v-d*m,z=y*L-x*S+b*E+_*T-w*k+M*A;return z?(z=1/z,t[0]=(s*L-l*S+u*E)*z,t[1]=(i*S-n*L-a*E)*z,t[2]=(g*M-m*w+v*_)*z,t[3]=(f*w-h*M-d*_)*z,t[4]=(l*T-o*L-u*k)*z,t[5]=(r*L-i*T+a*k)*z,t[6]=(m*b-p*M-v*x)*z,t[7]=(c*M-f*b+d*x)*z,t[8]=(o*S-s*T+u*A)*z,t[9]=(n*T-r*S-a*A)*z,t[10]=(p*w-g*b+v*y)*z,t[11]=(h*b-c*w-d*y)*z,t[12]=(s*k-o*E-l*A)*z,t[13]=(r*E-n*k+i*A)*z,t[14]=(g*x-p*_-m*y)*z,t[15]=(c*_-h*x+f*y)*z,t):null}e.exports=n},{}],150:[function(t,e,r){function n(t,e,r,n){var a,o,s,l,u,c,h,f,d,p,g=e[0],m=e[1],v=e[2],y=n[0],x=n[1],b=n[2],_=r[0],w=r[1],M=r[2];return 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r=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=e[0],c=e[1],h=e[2],f=e[3],d=e[4],p=e[5];return Math.abs(r-u)<=n.EPSILON*Math.max(1,Math.abs(r),Math.abs(u))&&Math.abs(i-c)<=n.EPSILON*Math.max(1,Math.abs(i),Math.abs(c))&&Math.abs(a-h)<=n.EPSILON*Math.max(1,Math.abs(a),Math.abs(h))&&Math.abs(o-f)<=n.EPSILON*Math.max(1,Math.abs(o),Math.abs(f))&&Math.abs(s-d)<=n.EPSILON*Math.max(1,Math.abs(s),Math.abs(d))&&Math.abs(l-p)<=n.EPSILON*Math.max(1,Math.abs(l),Math.abs(p))},e.exports=i},{\"./common.js\":162}],165:[function(t,e,r){var n=t(\"./common.js\"),i={};i.create=function(){var t=new n.ARRAY_TYPE(9);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=1,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},i.fromMat4=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[4],t[4]=e[5],t[5]=e[6],t[6]=e[8],t[7]=e[9],t[8]=e[10],t},i.clone=function(t){var e=new n.ARRAY_TYPE(9);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e},i.copy=function(t,e){return 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t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t[3]=e[3]+r[3],t[4]=e[4]+r[4],t[5]=e[5]+r[5],t[6]=e[6]+r[6],t[7]=e[7]+r[7],t[8]=e[8]+r[8],t},i.subtract=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t[3]=e[3]-r[3],t[4]=e[4]-r[4],t[5]=e[5]-r[5],t[6]=e[6]-r[6],t[7]=e[7]-r[7],t[8]=e[8]-r[8],t},i.sub=i.subtract,i.multiplyScalar=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t[3]=e[3]*r,t[4]=e[4]*r,t[5]=e[5]*r,t[6]=e[6]*r,t[7]=e[7]*r,t[8]=e[8]*r,t},i.multiplyScalarAndAdd=function(t,e,r,n){return t[0]=e[0]+r[0]*n,t[1]=e[1]+r[1]*n,t[2]=e[2]+r[2]*n,t[3]=e[3]+r[3]*n,t[4]=e[4]+r[4]*n,t[5]=e[5]+r[5]*n,t[6]=e[6]+r[6]*n,t[7]=e[7]+r[7]*n,t[8]=e[8]+r[8]*n,t},i.exactEquals=function(t,e){return t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]&&t[3]===e[3]&&t[4]===e[4]&&t[5]===e[5]&&t[6]===e[6]&&t[7]===e[7]&&t[8]===e[8]},i.equals=function(t,e){var r=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=t[6],c=t[7],h=t[8],f=e[0],d=e[1],p=e[2],g=e[3],m=e[4],v=e[5],y=t[6],x=e[7],b=e[8];return 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e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},i.copy=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.fromValues=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,g,m){var v=new n.ARRAY_TYPE(16);return v[0]=t,v[1]=e,v[2]=r,v[3]=i,v[4]=a,v[5]=o,v[6]=s,v[7]=l,v[8]=u,v[9]=c,v[10]=h,v[11]=f,v[12]=d,v[13]=p,v[14]=g,v[15]=m,v},i.set=function(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,g,m){return t[0]=e,t[1]=r,t[2]=n,t[3]=i,t[4]=a,t[5]=o,t[6]=s,t[7]=l,t[8]=u,t[9]=c,t[10]=h,t[11]=f,t[12]=d,t[13]=p,t[14]=g,t[15]=m,t},i.identity=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.scalar.transpose=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t},i.SIMD.transpose=function(t,e){var r,n,i,a,o,s,l,u,c,h;return r=SIMD.Float32x4.load(e,0),n=SIMD.Float32x4.load(e,4),i=SIMD.Float32x4.load(e,8),a=SIMD.Float32x4.load(e,12),o=SIMD.Float32x4.shuffle(r,n,0,1,4,5),s=SIMD.Float32x4.shuffle(i,a,0,1,4,5),l=SIMD.Float32x4.shuffle(o,s,0,2,4,6),u=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,0,l),SIMD.Float32x4.store(t,4,u),o=SIMD.Float32x4.shuffle(r,n,2,3,6,7),s=SIMD.Float32x4.shuffle(i,a,2,3,6,7),c=SIMD.Float32x4.shuffle(o,s,0,2,4,6),h=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,8,c),SIMD.Float32x4.store(t,12,h),t},i.transpose=n.USE_SIMD?i.SIMD.transpose:i.scalar.transpose,i.scalar.invert=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,A=c*g-h*p,k=c*m-f*p,T=c*v-d*p,E=h*m-f*g,S=h*v-d*g,L=f*v-d*m,z=y*L-x*S+b*E+_*T-w*k+M*A;return z?(z=1/z,t[0]=(s*L-l*S+u*E)*z,t[1]=(i*S-n*L-a*E)*z,t[2]=(g*M-m*w+v*_)*z,t[3]=(f*w-h*M-d*_)*z,t[4]=(l*T-o*L-u*k)*z,t[5]=(r*L-i*T+a*k)*z,t[6]=(m*b-p*M-v*x)*z,t[7]=(c*M-f*b+d*x)*z,t[8]=(o*S-s*T+u*A)*z,t[9]=(n*T-r*S-a*A)*z,t[10]=(p*w-g*b+v*y)*z,t[11]=(h*b-c*w-d*y)*z,t[12]=(s*k-o*E-l*A)*z,t[13]=(r*E-n*k+i*A)*z,t[14]=(g*x-p*_-m*y)*z,t[15]=(c*_-h*x+f*y)*z,t):null},i.SIMD.invert=function(t,e){var r,n,i,a,o,s,l,u,c,h,f=SIMD.Float32x4.load(e,0),d=SIMD.Float32x4.load(e,4),p=SIMD.Float32x4.load(e,8),g=SIMD.Float32x4.load(e,12);return o=SIMD.Float32x4.shuffle(f,d,0,1,4,5),n=SIMD.Float32x4.shuffle(p,g,0,1,4,5),r=SIMD.Float32x4.shuffle(o,n,0,2,4,6),n=SIMD.Float32x4.shuffle(n,o,1,3,5,7),o=SIMD.Float32x4.shuffle(f,d,2,3,6,7),a=SIMD.Float32x4.shuffle(p,g,2,3,6,7),i=SIMD.Float32x4.shuffle(o,a,0,2,4,6),a=SIMD.Float32x4.shuffle(a,o,1,3,5,7),o=SIMD.Float32x4.mul(i,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.mul(n,o),l=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(SIMD.Float32x4.mul(n,o),s),l=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),l),l=SIMD.Float32x4.swizzle(l,2,3,0,1),o=SIMD.Float32x4.mul(n,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),s),c=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),o=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(n,2,3,0,1),a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),i=SIMD.Float32x4.swizzle(i,2,3,0,1),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),s),u=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),u),u=SIMD.Float32x4.swizzle(u,2,3,0,1),o=SIMD.Float32x4.mul(r,n),o=SIMD.Float32x4.swizzle(o,1,0,3,2),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(i,o),c),o=SIMD.Float32x4.swizzle(o,2,3,0,1),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(i,o)),o=SIMD.Float32x4.mul(r,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),u),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),l),u=SIMD.Float32x4.sub(u,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.mul(r,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),l),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),c),h=SIMD.Float32x4.mul(r,s),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,2,3,0,1),h),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,1,0,3,2),h),o=SIMD.Float32x4.reciprocalApproximation(h),h=SIMD.Float32x4.sub(SIMD.Float32x4.add(o,o),SIMD.Float32x4.mul(h,SIMD.Float32x4.mul(o,o))),(h=SIMD.Float32x4.swizzle(h,0,0,0,0))?(SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(h,s)),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(h,l)),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(h,u)),SIMD.Float32x4.store(t,12,SIMD.Float32x4.mul(h,c)),t):null},i.invert=n.USE_SIMD?i.SIMD.invert:i.scalar.invert,i.scalar.adjoint=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15];return t[0]=s*(f*v-d*m)-h*(l*v-u*m)+g*(l*d-u*f),t[1]=-(n*(f*v-d*m)-h*(i*v-a*m)+g*(i*d-a*f)),t[2]=n*(l*v-u*m)-s*(i*v-a*m)+g*(i*u-a*l),t[3]=-(n*(l*d-u*f)-s*(i*d-a*f)+h*(i*u-a*l)),t[4]=-(o*(f*v-d*m)-c*(l*v-u*m)+p*(l*d-u*f)),t[5]=r*(f*v-d*m)-c*(i*v-a*m)+p*(i*d-a*f),t[6]=-(r*(l*v-u*m)-o*(i*v-a*m)+p*(i*u-a*l)),t[7]=r*(l*d-u*f)-o*(i*d-a*f)+c*(i*u-a*l),t[8]=o*(h*v-d*g)-c*(s*v-u*g)+p*(s*d-u*h),t[9]=-(r*(h*v-d*g)-c*(n*v-a*g)+p*(n*d-a*h)),t[10]=r*(s*v-u*g)-o*(n*v-a*g)+p*(n*u-a*s),t[11]=-(r*(s*d-u*h)-o*(n*d-a*h)+c*(n*u-a*s)),t[12]=-(o*(h*m-f*g)-c*(s*m-l*g)+p*(s*f-l*h)),t[13]=r*(h*m-f*g)-c*(n*m-i*g)+p*(n*f-i*h),t[14]=-(r*(s*m-l*g)-o*(n*m-i*g)+p*(n*l-i*s)),t[15]=r*(s*f-l*h)-o*(n*f-i*h)+c*(n*l-i*s),t},i.SIMD.adjoint=function(t,e){var r,n,i,a,o,s,l,u,c,h,f,d,p,r=SIMD.Float32x4.load(e,0),n=SIMD.Float32x4.load(e,4),i=SIMD.Float32x4.load(e,8),a=SIMD.Float32x4.load(e,12);return c=SIMD.Float32x4.shuffle(r,n,0,1,4,5),s=SIMD.Float32x4.shuffle(i,a,0,1,4,5),o=SIMD.Float32x4.shuffle(c,s,0,2,4,6),s=SIMD.Float32x4.shuffle(s,c,1,3,5,7),c=SIMD.Float32x4.shuffle(r,n,2,3,6,7),u=SIMD.Float32x4.shuffle(i,a,2,3,6,7),l=SIMD.Float32x4.shuffle(c,u,0,2,4,6),u=SIMD.Float32x4.shuffle(u,c,1,3,5,7),c=SIMD.Float32x4.mul(l,u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),h=SIMD.Float32x4.mul(s,c),f=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(SIMD.Float32x4.mul(s,c),h),f=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),f),f=SIMD.Float32x4.swizzle(f,2,3,0,1),c=SIMD.Float32x4.mul(s,l),c=SIMD.Float32x4.swizzle(c,1,0,3,2),h=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),h),p=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(h,SIMD.Float32x4.mul(u,c)),p=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),p),p=SIMD.Float32x4.swizzle(p,2,3,0,1),c=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,2,3,0,1),u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),l=SIMD.Float32x4.swizzle(l,2,3,0,1),h=SIMD.Float32x4.add(SIMD.Float32x4.mul(l,c),h),d=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(h,SIMD.Float32x4.mul(l,c)),d=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),d),d=SIMD.Float32x4.swizzle(d,2,3,0,1),c=SIMD.Float32x4.mul(o,s),c=SIMD.Float32x4.swizzle(c,1,0,3,2),d=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),d),p=SIMD.Float32x4.sub(SIMD.Float32x4.mul(l,c),p),c=SIMD.Float32x4.swizzle(c,2,3,0,1),d=SIMD.Float32x4.sub(SIMD.Float32x4.mul(u,c),d),p=SIMD.Float32x4.sub(p,SIMD.Float32x4.mul(l,c)),c=SIMD.Float32x4.mul(o,u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),f=SIMD.Float32x4.sub(f,SIMD.Float32x4.mul(l,c)),d=SIMD.Float32x4.add(SIMD.Float32x4.mul(s,c),d),c=SIMD.Float32x4.swizzle(c,2,3,0,1),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(l,c),f),d=SIMD.Float32x4.sub(d,SIMD.Float32x4.mul(s,c)),c=SIMD.Float32x4.mul(o,l),c=SIMD.Float32x4.swizzle(c,1,0,3,2),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),f),p=SIMD.Float32x4.sub(p,SIMD.Float32x4.mul(s,c)),c=SIMD.Float32x4.swizzle(c,2,3,0,1),f=SIMD.Float32x4.sub(f,SIMD.Float32x4.mul(u,c)),p=SIMD.Float32x4.add(SIMD.Float32x4.mul(s,c),p),SIMD.Float32x4.store(t,0,h),SIMD.Float32x4.store(t,4,f),SIMD.Float32x4.store(t,8,d),SIMD.Float32x4.store(t,12,p),t},i.adjoint=n.USE_SIMD?i.SIMD.adjoint:i.scalar.adjoint,i.determinant=function(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],g=t[14],m=t[15],v=e*o-r*a,y=e*s-n*a,x=e*l-i*a,b=r*s-n*o,_=r*l-i*o,w=n*l-i*s,M=u*p-c*d,A=u*g-h*d,k=u*m-f*d,T=c*g-h*p,E=c*m-f*p,S=h*m-f*g;return v*S-y*E+x*T+b*k-_*A+w*M},i.SIMD.multiply=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4.load(r,0),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,3,3,3,3),o))));SIMD.Float32x4.store(t,0,l);var u=SIMD.Float32x4.load(r,4),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,3,3,3,3),o))));SIMD.Float32x4.store(t,4,c);var h=SIMD.Float32x4.load(r,8),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,3,3,3,3),o))));SIMD.Float32x4.store(t,8,f);var d=SIMD.Float32x4.load(r,12),p=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,3,3,3,3),o))));return SIMD.Float32x4.store(t,12,p),t},i.scalar.multiply=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*h+w*g,t[1]=x*i+b*l+_*f+w*m,t[2]=x*a+b*u+_*d+w*v,t[3]=x*o+b*c+_*p+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*h+w*g,t[5]=x*i+b*l+_*f+w*m,t[6]=x*a+b*u+_*d+w*v,t[7]=x*o+b*c+_*p+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*h+w*g,t[9]=x*i+b*l+_*f+w*m,t[10]=x*a+b*u+_*d+w*v,t[11]=x*o+b*c+_*p+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*h+w*g,t[13]=x*i+b*l+_*f+w*m,t[14]=x*a+b*u+_*d+w*v,t[15]=x*o+b*c+_*p+w*y,t},i.multiply=n.USE_SIMD?i.SIMD.multiply:i.scalar.multiply,i.mul=i.multiply,i.scalar.translate=function(t,e,r){var n,i,a,o,s,l,u,c,h,f,d,p,g=r[0],m=r[1],v=r[2];return e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=u,t[7]=c,t[8]=h,t[9]=f,t[10]=d,t[11]=p,t[12]=n*g+s*m+h*v+e[12],t[13]=i*g+l*m+f*v+e[13],t[14]=a*g+u*m+d*v+e[14],t[15]=o*g+c*m+p*v+e[15]),t},i.SIMD.translate=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4(r[0],r[1],r[2],0);e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11]),n=SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(s,0,0,0,0)),i=SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(s,1,1,1,1)),a=SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(s,2,2,2,2));var l=SIMD.Float32x4.add(n,SIMD.Float32x4.add(i,SIMD.Float32x4.add(a,o)));return SIMD.Float32x4.store(t,12,l),t},i.translate=n.USE_SIMD?i.SIMD.translate:i.scalar.translate,i.scalar.scale=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.SIMD.scale=function(t,e,r){var n,i,a,o=SIMD.Float32x4(r[0],r[1],r[2],0);return n=SIMD.Float32x4.load(e,0),SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(o,0,0,0,0))),i=SIMD.Float32x4.load(e,4),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(o,1,1,1,1))),a=SIMD.Float32x4.load(e,8),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(o,2,2,2,2))),t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.scale=n.USE_SIMD?i.SIMD.scale:i.scalar.scale,i.rotate=function(t,e,r,i){var a,o,s,l,u,c,h,f,d,p,g,m,v,y,x,b,_,w,M,A,k,T,E,S,L=i[0],z=i[1],C=i[2],I=Math.sqrt(L*L+z*z+C*C);return Math.abs(I)<n.EPSILON?null:(I=1/I,L*=I,z*=I,C*=I,a=Math.sin(r),o=Math.cos(r),s=1-o,l=e[0],u=e[1],c=e[2],h=e[3],f=e[4],d=e[5],p=e[6],g=e[7],m=e[8],v=e[9],y=e[10],x=e[11],b=L*L*s+o,_=z*L*s+C*a,w=C*L*s-z*a,M=L*z*s-C*a,A=z*z*s+o,k=C*z*s+L*a,T=L*C*s+z*a,E=z*C*s-L*a,S=C*C*s+o,t[0]=l*b+f*_+m*w,t[1]=u*b+d*_+v*w,t[2]=c*b+p*_+y*w,t[3]=h*b+g*_+x*w,t[4]=l*M+f*A+m*k,t[5]=u*M+d*A+v*k,t[6]=c*M+p*A+y*k,t[7]=h*M+g*A+x*k,t[8]=l*T+f*E+m*S,t[9]=u*T+d*E+v*S,t[10]=c*T+p*E+y*S,t[11]=h*T+g*E+x*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)},i.scalar.rotateX=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],h=e[10],f=e[11];return e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[4]=a*i+u*n,t[5]=o*i+c*n,t[6]=s*i+h*n,t[7]=l*i+f*n,t[8]=u*i-a*n,t[9]=c*i-o*n,t[10]=h*i-s*n,t[11]=f*i-l*n,t},i.SIMD.rotateX=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,4),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,4,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateX=n.USE_SIMD?i.SIMD.rotateX:i.scalar.rotateX,i.scalar.rotateY=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],h=e[10],f=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-h*n,t[3]=l*i-f*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+h*i,t[11]=l*n+f*i,t},i.SIMD.rotateY=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,n),SIMD.Float32x4.mul(o,i))),t},i.rotateY=n.USE_SIMD?i.SIMD.rotateY:i.scalar.rotateY,i.scalar.rotateZ=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],h=e[6],f=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+h*n,t[3]=l*i+f*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=h*i-s*n,t[7]=f*i-l*n,t},i.SIMD.rotateZ=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,4);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,4,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateZ=n.USE_SIMD?i.SIMD.rotateZ:i.scalar.rotateZ,i.fromTranslation=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t},i.fromScaling=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromRotation=function(t,e,r){var i,a,o,s=r[0],l=r[1],u=r[2],c=Math.sqrt(s*s+l*l+u*u);return Math.abs(c)<n.EPSILON?null:(c=1/c,s*=c,l*=c,u*=c,i=Math.sin(e),a=Math.cos(e),o=1-a,t[0]=s*s*o+a,t[1]=l*s*o+u*i,t[2]=u*s*o-l*i,t[3]=0,t[4]=s*l*o-u*i,t[5]=l*l*o+a,t[6]=u*l*o+s*i,t[7]=0,t[8]=s*u*o+l*i,t[9]=l*u*o-s*i,t[10]=u*u*o+a,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t)},i.fromXRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromYRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromZRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromRotationTranslation=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,g=a*u,m=o*s,v=o*l,y=o*u;return t[0]=1-(d+g),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+g),t[6]=p+m,t[7]=0,t[8]=f+v,t[9]=p-m,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.getTranslation=function(t,e){return t[0]=e[12],t[1]=e[13],t[2]=e[14],t},i.getRotation=function(t,e){var r=e[0]+e[5]+e[10],n=0;return r>0?(n=2*Math.sqrt(r+1),t[3]=.25*n,t[0]=(e[6]-e[9])/n,t[1]=(e[8]-e[2])/n,t[2]=(e[1]-e[4])/n):e[0]>e[5]&e[0]>e[10]?(n=2*Math.sqrt(1+e[0]-e[5]-e[10]),t[3]=(e[6]-e[9])/n,t[0]=.25*n,t[1]=(e[1]+e[4])/n,t[2]=(e[8]+e[2])/n):e[5]>e[10]?(n=2*Math.sqrt(1+e[5]-e[0]-e[10]),t[3]=(e[8]-e[2])/n,t[0]=(e[1]+e[4])/n,t[1]=.25*n,t[2]=(e[6]+e[9])/n):(n=2*Math.sqrt(1+e[10]-e[0]-e[5]),t[3]=(e[1]-e[4])/n,t[0]=(e[8]+e[2])/n,t[1]=(e[6]+e[9])/n,t[2]=.25*n),t},i.fromRotationTranslationScale=function(t,e,r,n){var i=e[0],a=e[1],o=e[2],s=e[3],l=i+i,u=a+a,c=o+o,h=i*l,f=i*u,d=i*c,p=a*u,g=a*c,m=o*c,v=s*l,y=s*u,x=s*c,b=n[0],_=n[1],w=n[2];return t[0]=(1-(p+m))*b,t[1]=(f+x)*b,t[2]=(d-y)*b,t[3]=0,t[4]=(f-x)*_,t[5]=(1-(h+m))*_,t[6]=(g+v)*_,t[7]=0,t[8]=(d+y)*w,t[9]=(g-v)*w,t[10]=(1-(h+p))*w,t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.fromRotationTranslationScaleOrigin=function(t,e,r,n,i){var a=e[0],o=e[1],s=e[2],l=e[3],u=a+a,c=o+o,h=s+s,f=a*u,d=a*c,p=a*h,g=o*c,m=o*h,v=s*h,y=l*u,x=l*c,b=l*h,_=n[0],w=n[1],M=n[2],A=i[0],k=i[1],T=i[2];return t[0]=(1-(g+v))*_,t[1]=(d+b)*_,t[2]=(p-x)*_,t[3]=0,t[4]=(d-b)*w,t[5]=(1-(f+v))*w,t[6]=(m+y)*w,t[7]=0,t[8]=(p+x)*M,t[9]=(m-y)*M,t[10]=(1-(f+g))*M,t[11]=0,t[12]=r[0]+A-(t[0]*A+t[4]*k+t[8]*T),t[13]=r[1]+k-(t[1]*A+t[5]*k+t[9]*T),t[14]=r[2]+T-(t[2]*A+t[6]*k+t[10]*T),t[15]=1,t},i.fromQuat=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-m,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+g,t[7]=0,t[8]=f+m,t[9]=d-g,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.frustum=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),u=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*u,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*u,t[15]=0,t},i.perspective=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t},i.perspectiveFromFieldOfView=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),u=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=u,t[6]=0,t[7]=0,t[8]=-((o-s)*l*.5),t[9]=(i-a)*u*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t},i.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},i.lookAt=function(t,e,r,a){var o,s,l,u,c,h,f,d,p,g,m=e[0],v=e[1],y=e[2],x=a[0],b=a[1],_=a[2],w=r[0],M=r[1],A=r[2];return Math.abs(m-w)<n.EPSILON&&Math.abs(v-M)<n.EPSILON&&Math.abs(y-A)<n.EPSILON?i.identity(t):(f=m-w,d=v-M,p=y-A,g=1/Math.sqrt(f*f+d*d+p*p),f*=g,d*=g,p*=g,o=b*p-_*d,s=_*f-x*p,l=x*d-b*f,g=Math.sqrt(o*o+s*s+l*l),g?(g=1/g,o*=g,s*=g,l*=g):(o=0,s=0,l=0),u=d*l-p*s,c=p*o-f*l,h=f*s-d*o,g=Math.sqrt(u*u+c*c+h*h),g?(g=1/g,u*=g,c*=g,h*=g):(u=0,c=0,h=0),t[0]=o,t[1]=u,t[2]=f,t[3]=0,t[4]=s,t[5]=c,t[6]=d,t[7]=0,t[8]=l,t[9]=h,t[10]=p,t[11]=0,t[12]=-(o*m+s*v+l*y),t[13]=-(u*m+c*v+h*y),t[14]=-(f*m+d*v+p*y),t[15]=1,t)},i.str=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\";\n",
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 , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution_2_0(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n  \\n  if(!gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = cookTorranceSpecular_1_1(L, V, N, roughness, fresnel);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\",l=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5,0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",u=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\",c=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(f_position, clipBounds[0])) || \\n     any(greaterThan(f_position, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\",h=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\",f=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\",d=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\";r.meshShader={vertex:n,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:a,fragment:o,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:s,fragment:l,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:f,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{}],173:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,g,m,v,y,x,b,_,w,M,A,k,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=u,this.triangleVAO=d,this.triangleCount=0,this.lineWidth=1,this.edgePositions=p,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=w,this.pointSizes=M,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=k,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this._model=R,this._view=R,this._projection=R,this._resolution=[1,1]}function i(t){for(var e=A({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return M(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;for(var a=t.length,i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}function s(t){var e=m(t,L);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=m(t,z);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=m(t,C);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function c(t){var e=m(t,I);return e.attributes.position.location=0,e.attributes.id.location=1,e}function h(t){var e=m(t,P);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function f(t){var e=m(t,D);return e.attributes.position.location=0,e}function d(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),d=h(e),p=f(e),g=x(e,M(new Uint8Array([255,255,255,255]),[1,1,4]));g.generateMipmap(),g.minFilter=e.LINEAR_MIPMAP_LINEAR,g.magFilter=e.LINEAR;var m=v(e),b=v(e),_=v(e),w=v(e),A=v(e),k=y(e,[{buffer:m,type:e.FLOAT,size:3},{buffer:A,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:b,type:e.FLOAT,size:4},{buffer:_,type:e.FLOAT,size:2},{buffer:w,type:e.FLOAT,size:3}]),T=v(e),E=v(e),S=v(e),L=v(e),z=y(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:L,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:E,type:e.FLOAT,size:4},{buffer:S,type:e.FLOAT,size:2}]),C=v(e),I=v(e),P=v(e),D=v(e),R=v(e),O=y(e,[{buffer:C,type:e.FLOAT,size:3},{buffer:R,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:e.FLOAT,size:4},{buffer:P,type:e.FLOAT,size:2},{buffer:D,type:e.FLOAT,size:1}]),F=v(e),j=y(e,[{buffer:F,type:e.FLOAT,size:3}]),N=new n(e,g,r,i,a,o,d,p,m,A,b,_,w,k,T,L,E,S,z,C,R,I,P,D,O,F,j);return N.update(t),N}var p=1e-6,g=1e-6,m=t(\"gl-shader\"),v=t(\"gl-buffer\"),y=t(\"gl-vao\"),x=t(\"gl-texture2d\"),b=t(\"normals\"),_=t(\"gl-mat4/multiply\"),w=t(\"gl-mat4/invert\"),M=t(\"ndarray\"),A=t(\"colormap\"),k=t(\"simplicial-complex-contour\"),T=t(\"typedarray-pool\"),E=t(\"./lib/shaders\"),S=t(\"./lib/closest-point\"),L=E.meshShader,z=E.wireShader,C=E.pointShader,I=E.pickShader,P=E.pointPickShader,D=E.contourShader,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=n.prototype;O.isOpaque=function(){return this.opacity>=1},O.isTransparent=function(){return this.opacity<1},O.pickSlots=1,O.setPickBase=function(t){this.pickId=t},O.highlight=function(t){if(!t||!this.contourEnable)return void(this.contourCount=0);for(var e=k(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=T.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var h=u[0];2===u.length&&(h=u[c]);for(var f=n[h][0],d=n[h][1],p=i[h],g=1-p,m=this.positions[f],v=this.positions[d],y=0;y<3;++y)o[s++]=p*m[y]+g*v[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),T.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=x(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),\n",
+       "this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],h=[],f=[],d=[],m=[],v=[],y=[],_=[],w=[],M=[],A=[];this.cells=r,this.positions=n;var k=t.vertexNormals,T=t.cellNormals,E=void 0===t.vertexNormalsEpsilon?p:t.vertexNormalsEpsilon,S=void 0===t.faceNormalsEpsilon?g:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=b.faceNormals(r,n,S)),T||k||(k=b.vertexNormals(r,n,E));var L=t.vertexColors,z=t.cellColors,C=t.meshColor||[1,1,1,1],I=t.vertexUVs,P=t.vertexIntensity,D=t.cellUVs,R=t.cellIntensity,O=1/0,F=-(1/0);if(!I&&!D)if(P)for(var j=0;j<P.length;++j){var N=P[j];O=Math.min(O,N),F=Math.max(F,N)}else if(R)for(var j=0;j<R.length;++j){var N=R[j];O=Math.min(O,N),F=Math.max(F,N)}else for(var j=0;j<n.length;++j){var N=n[j][2];O=Math.min(O,N),F=Math.max(F,N)}P?this.intensity=P:R?this.intensity=a(r,n.length,R):this.intensity=o(n);var B=t.pointSizes,U=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var j=0;j<n.length;++j)for(var V=n[j],q=0;q<3;++q)!isNaN(V[q])&&isFinite(V[q])&&(this.bounds[0][q]=Math.min(this.bounds[0][q],V[q]),this.bounds[1][q]=Math.max(this.bounds[1][q],V[q]));var H=0,G=0,X=0;t:for(var j=0;j<r.length;++j){var Y=r[j];switch(Y.length){case 1:for(var W=Y[0],V=n[W],q=0;q<3;++q)if(isNaN(V[q])||!isFinite(V[q]))continue t;y.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?_.push(Z[0],Z[1],Z[2],1):_.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],w.push(Q[0],Q[1]),B?M.push(B[W]):M.push(U),A.push(j),X+=1;break;case 2:for(var q=0;q<2;++q)for(var W=Y[q],V=n[W],K=0;K<3;++K)if(isNaN(V[K])||!isFinite(V[K]))continue t;for(var q=0;q<2;++q){var W=Y[q],V=n[W];f.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?d.push(Z[0],Z[1],Z[2],1):d.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],m.push(Q[0],Q[1]),v.push(j)}G+=1;break;case 3:for(var q=0;q<3;++q)for(var W=Y[q],V=n[W],K=0;K<3;++K)if(isNaN(V[K])||!isFinite(V[K]))continue t;for(var q=0;q<3;++q){var W=Y[q],V=n[W];s.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?l.push(Z[0],Z[1],Z[2],1):l.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],c.push(Q[0],Q[1]);var $;$=k?k[W]:T[j],u.push($[0],$[1],$[2]),h.push(j)}H+=1}}this.pointCount=X,this.edgeCount=G,this.triangleCount=H,this.pointPositions.update(y),this.pointColors.update(_),this.pointUVs.update(w),this.pointSizes.update(M),this.pointIds.update(new Uint32Array(A)),this.edgePositions.update(f),this.edgeColors.update(d),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(v)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(h))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);_(l,s.view,s.model),_(l,s.projection,l),w(l,l);for(var o=0;o<3;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;o<3;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;o<3;++o){for(var c=l[12+o],h=0;h<3;++h)c+=l[4*h+o]*this.lightPosition[h];s.lightPosition[o]=c/u}if(this.triangleCount>0){var f=this.triShader;f.bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var f=this.lineShader;f.bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var f=this.pointShader;f.bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var f=this.contourShader;f.bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=S(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=d},{\"./lib/closest-point\":171,\"./lib/shaders\":172,colormap:80,\"gl-buffer\":128,\"gl-mat4/invert\":149,\"gl-mat4/multiply\":151,\"gl-shader\":220,\"gl-texture2d\":232,\"gl-vao\":236,ndarray:427,normals:429,\"simplicial-complex-contour\":474,\"typedarray-pool\":496}],174:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[0,0,0,1,1,0,1,1]),i=o(e,s.boxVert,s.lineFrag);return new n(t,r,i)}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawBox=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o){var s=this.plot,l=this.shader,u=s.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,l.uniforms.lo=t,l.uniforms.hi=e,l.uniforms.color=o,u.drawArrays(u.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"gl-buffer\":128,\"gl-shader\":180}],175:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function i(t,e){return t-e}function a(t){var e=t.gl,r=o(e),i=s(e,u.gridVert,u.gridFrag),a=s(e,u.tickVert,u.gridFrag),l=new n(t,r,i,a);return l}e.exports=a;var o=t(\"gl-buffer\"),s=t(\"gl-shader\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.draw=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){for(var n=this.plot,i=this.vbo,a=this.shader,o=this.ticks,s=n.gl,l=n._tickBounds,u=n.dataBox,c=n.viewBox,h=n.gridLineWidth,f=n.gridLineColor,d=n.gridLineEnable,p=n.pixelRatio,g=0;g<2;++g){var m=l[g],v=l[g+2],y=v-m,x=.5*(u[g+2]+u[g]),b=u[g+2]-u[g];e[g]=2*y/b,t[g]=2*(m-x)/b}a.bind(),i.bind(),a.attributes.dataCoord.pointer(),a.uniforms.dataShift=t,a.uniforms.dataScale=e;for(var _=0,g=0;g<2;++g){r[0]=r[1]=0,r[g]=1,a.uniforms.dataAxis=r,a.uniforms.lineWidth=h[g]/(c[g+2]-c[g])*p,a.uniforms.color=f[g];var w=6*o[g].length;d[g]&&w&&s.drawArrays(s.TRIANGLES,_,w),_+=w}}}(),c.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,h=this.ticks,f=s.gl,d=s._tickBounds,p=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var M=d[w],A=d[w+2],k=A-M,T=.5*(p[w+2]+p[w]),E=p[w+2]-p[w];e[w]=2*k/E,t[w]=2*(M-T)/E}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var L=s.tickMarkLength,z=s.tickMarkWidth,C=s.tickMarkColor,I=0,P=6*h[0].length,D=Math.min(l.ge(h[0],(p[0]-d[0])/(d[2]-d[0]),i),h[0].length),R=Math.min(l.gt(h[0],(p[2]-d[0])/(d[2]-d[0]),i),h[0].length),O=I+6*D,F=6*Math.max(0,R-D),j=Math.min(l.ge(h[1],(p[1]-d[1])/(d[3]-d[1]),i),h[1].length),N=Math.min(l.gt(h[1],(p[3]-d[1])/(d[3]-d[1]),i),h[1].length),B=P+6*j,U=6*Math.max(0,N-j);a[0]=2*(g[0]-L[1])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=L[1]*m/y,o[1]=z[1]*m/x,U&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,U)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-L[0])/x-1,o[0]=z[0]*m/y,o[1]=L[0]*m/x,F&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,F)),a[0]=2*(g[2]+L[3])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=L[3]*m/y,o[1]=z[3]*m/x,U&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,U)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+L[2])/x-1,o[0]=z[2]*m/y,o[1]=L[2]*m/x,F&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,F))}}(),c.update=function(){var t=[1,1,-1,-1,1,-1],e=[1,-1,1,1,-1,-1];return function(r){for(var n=r.ticks,i=r.bounds,a=new Float32Array(18*(n[0].length+n[1].length)),o=(this.plot.zeroLineEnable,0),s=[[],[]],l=0;l<2;++l)for(var u=s[l],c=n[l],h=i[l],f=i[l+2],d=0;d<c.length;++d){var p=(c[d].x-h)/(f-h);u.push(p);for(var g=0;g<6;++g)a[o++]=p,a[o++]=t[g],a[o++]=e[g]}this.ticks=s,this.vbo.update(a)}}(),c.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":177,\"binary-search-bounds\":179,\"gl-buffer\":128,\"gl-shader\":180}],176:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[-1,-1,-1,1,1,-1,1,1]),i=o(e,s.lineVert,s.lineFrag),l=new n(t,r,i);return l}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawLine=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o,s){var l=this.plot,u=this.shader,c=l.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,u.uniforms.start=t,u.uniforms.end=e,u.uniforms.width=o*l.pixelRatio,u.uniforms.color=s,c.drawArrays(c.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"gl-buffer\":128,\"gl-shader\":180}],177:[function(t,e,r){\"use strict\";var n=\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\";e.exports={lineVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\",lineFrag:n,textVert:\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\",textFrag:n,gridVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\",gridFrag:n,boxVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\",tickVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"}},{}],178:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}function i(t){var e=t.gl,r=a(e),i=o(e,u.textVert,u.textFrag),s=new n(t,r,i);return s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,h=i.dataBox,f=i.screenBox,d=i.pixelRatio,p=i.tickEnable,g=i.tickPad,m=i.tickColor,v=i.tickAngle,y=i.labelEnable,x=i.labelPad,b=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],M=this.labelCount[n],A=l.lt(o,h[n]),k=l.le(o,h[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(f[2+n]-f[n])-1;var T=2/f[2+(1^n)]-f[1^n];e[1^n]=T*c[1^n]-1,p[n]&&(e[1^n]-=T*d*g[n],A<k&&s[k]>s[A]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=m[n],a.uniforms.angle=v[n],u.drawArrays(u.TRIANGLES,s[A],s[k]-s[A]))),y[n]&&M&&(e[1^n]-=T*d*x[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=b[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,M)),e[1^n]=T*c[2+(1^n)]-1,p[n+2]&&(e[1^n]+=T*d*g[n+2],A<k&&s[k]>s[A]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=m[n+2],a.uniforms.angle=v[n+2],u.drawArrays(u.TRIANGLES,s[A],s[k]-s[A]))),y[n+2]&&M&&(e[1^n]+=T*d*x[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=b[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,M))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;u<2;++u){var c=a[u],h=a[u+2],f=h-c,d=.5*(o[u+2]+o[u]),p=o[u+2]-o[u],g=l[u],m=l[u+2],v=m-g,y=s[u],x=s[u+2],b=x-y;e[u]=2*f/p*v/b,t[u]=2*(c-d)/p*v/b}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){var e,r,n,i,a,o=[],l=t.ticks,u=t.bounds;for(a=0;a<2;++a){var c=[Math.floor(o.length/3)],h=[-(1/0)],f=l[a];for(e=0;e<f.length;++e){var d=f[e],p=d.x,g=d.text,m=d.font||\"sans-serif\";i=d.fontSize||12;for(var v=1/(u[a+2]-u[a]),y=u[a],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=s(m,x[b]).data,r=0;r<n.length;r+=2)o.push(n[r]*i,-n[r+1]*i-b*i*1.2,(p-y)*v);c.push(Math.floor(o.length/3)),h.push(p)}this.tickOffset[a]=c,this.tickX[a]=h}for(a=0;a<2;++a){for(this.labelOffset[a]=Math.floor(o.length/3),n=s(t.labelFont[a],t.labels[a],{textAlign:\"center\"}).data,i=t.labelSize[a],e=0;e<n.length;e+=2)o.push(n[e]*i,-n[e+1]*i,0);this.labelCount[a]=Math.floor(o.length/3)-this.labelOffset[a]}for(this.titleOffset=Math.floor(o.length/3),n=s(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)o.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(o.length/3)-this.titleOffset,this.vbo.update(o)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"binary-search-bounds\":179,\"gl-buffer\":128,\"gl-shader\":180,\"text-cache\":488}],179:[function(t,e,r){arguments[4][72][0].apply(r,arguments)},{dup:72}],180:[function(t,e,r){\"use strict\";function n(t){this.gl=t,this.gl.lastAttribCount=0,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}function i(t,e){return t.name<e.name?-1:1}function a(t,e,r,i,a){var o=new n(t);return o.update(e,r,i,a),o}var o=t(\"./lib/create-uniforms\"),s=t(\"./lib/create-attributes\"),l=t(\"./lib/reflect\"),u=t(\"./lib/shader-cache\"),c=t(\"./lib/runtime-reflect\"),h=t(\"./lib/GLError\"),f=n.prototype;f.bind=function(){this.program||this._relink();var t,e=this.gl.getProgramParameter(this.program,this.gl.ACTIVE_ATTRIBUTES),r=this.gl.lastAttribCount;if(e>r)for(t=r;t<e;t++)this.gl.enableVertexAttribArray(t);else if(r>e)for(t=e;t<r;t++)this.gl.disableVertexAttribArray(t);this.gl.lastAttribCount=e,this.gl.useProgram(this.program)},f.dispose=function(){for(var t=this.gl.lastAttribCount,e=0;e<t;e++)this.gl.disableVertexAttribArray(e);this.gl.lastAttribCount=0,this._fref&&this._fref.dispose(),this._vref&&this._vref.dispose(),this.attributes=this.types=this.vertShader=this.fragShader=this.program=this._relink=this._fref=this._vref=null},f.update=function(t,e,r,n){function a(){d.program=u.program(p,d._vref,d._fref,_,w);for(var t=0;t<r.length;++t)S[t]=p.getUniformLocation(d.program,r[t].name)}if(!e||1===arguments.length){var f=t;t=f.vertex,e=f.fragment,r=f.uniforms,n=f.attributes}var d=this,p=d.gl,g=d._vref;d._vref=u.shader(p,p.VERTEX_SHADER,t),g&&g.dispose(),d.vertShader=d._vref.shader;var m=this._fref;if(d._fref=u.shader(p,p.FRAGMENT_SHADER,e),m&&m.dispose(),d.fragShader=d._fref.shader,!r||!n){var v=p.createProgram();if(p.attachShader(v,d.fragShader),p.attachShader(v,d.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var y=p.getProgramInfoLog(v);throw new h(y,\"Error linking 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p=0;p<2;++p)if(h[p]&&n[p]<=0&&n[p+2]>=0){\n",
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e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}}(),f.pick=function(){return function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var h=u[c].pick(a,o,l);if(h)return h}return null}}}(),f.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},f.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},f.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},f.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;u<2;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},f.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},f.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},f.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},f.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},f.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":174,\"./lib/grid\":175,\"./lib/line\":176,\"./lib/text\":178,\"gl-select-static\":219}],188:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":220}],189:[function(t,e,r){\"use strict\";function n(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function i(t,e){var r=null;try{r=t.getContext(\"webgl\",e),r||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}function a(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){var r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function o(t){return\"boolean\"!=typeof t||t}function s(t){function e(){if(!_&&H.autoResize){var t=w.parentNode,e=1,r=1;t&&t!==document.body?(e=t.clientWidth,r=t.clientHeight):(e=window.innerWidth,r=window.innerHeight);var n=0|Math.ceil(e*H.pixelRatio),i=0|Math.ceil(r*H.pixelRatio);if(n!==w.width||i!==w.height){w.width=n,w.height=i;var a=w.style;a.position=a.position||\"absolute\",a.left=\"0px\",a.top=\"0px\",a.width=e+\"px\",a.height=r+\"px\",j=!0}}}function r(){for(var t=D.length,e=F.length,r=0;r<e;++r)O[r]=0;t:for(var r=0;r<t;++r){var n=D[r],i=n.pickSlots;if(i){for(var a=0;a<e;++a)if(O[a]+i<255){R[r]=a,n.setPickBase(O[a]+1),O[a]+=i;continue t}var o=f(A,q);R[r]=e,F.push(o),O.push(i),n.setPickBase(1),e+=1}else R[r]=-1}for(;e>0&&0===O[e-1];)O.pop(),F.pop().dispose()}function s(){return!!H.contextLost||void(A.isContextLost()&&(H.contextLost=!0,H.mouseListener.enabled=!1,H.selection.object=null,H.oncontextloss&&H.oncontextloss()))}function y(){if(!s()){A.colorMask(!0,!0,!0,!0),A.depthMask(!0),A.disable(A.BLEND),A.enable(A.DEPTH_TEST);for(var t=D.length,e=F.length,r=0;r<e;++r){var n=F[r];n.shape=G,n.begin();for(var i=0;i<t;++i)if(R[i]===r){var a=D[i];a.drawPick&&(a.pixelRatio=1,a.drawPick(V))}n.end()}}}function x(){if(!s()){e();var t=H.camera.tick();V.view=H.camera.matrix,j=j||t,N=N||t,C.pixelRatio=H.pixelRatio,P.pixelRatio=H.pixelRatio;var r=D.length,n=W[0],i=W[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-(1/0);for(var o=0;o<r;++o){var l=D[o];l.pixelRatio=H.pixelRatio,l.axes=H.axes,j=j||!!l.dirty,N=N||!!l.dirty;var u=l.bounds;if(u)for(var h=u[0],f=u[1],d=0;d<3;++d)n[d]=Math.min(n[d],h[d]),i[d]=Math.max(i[d],f[d])}var g=H.bounds;if(H.autoBounds)for(var d=0;d<3;++d){if(i[d]<n[d])n[d]=-1,i[d]=1;else{n[d]===i[d]&&(n[d]-=1,i[d]+=1);var v=.05*(i[d]-n[d]);n[d]=n[d]-v,i[d]=i[d]+v}g[0][d]=n[d],g[1][d]=i[d]}for(var x=!1,d=0;d<3;++d)x=x||Z[0][d]!==g[0][d]||Z[1][d]!==g[1][d],Z[0][d]=g[0][d],Z[1][d]=g[1][d];if(x){for(var b=[0,0,0],o=0;o<3;++o)b[o]=a((g[1][o]-g[0][o])/10);C.autoTicks?C.update({bounds:g,tickSpacing:b}):C.update({bounds:g})}N=N||x,j=j||x;var _=A.drawingBufferWidth,w=A.drawingBufferHeight;q[0]=_,q[1]=w,G[0]=0|Math.max(_/H.pixelRatio,1),G[1]=0|Math.max(w/H.pixelRatio,1),m(B,H.fovy,_/w,H.zNear,H.zFar);for(var o=0;o<16;++o)U[o]=0;U[15]=1;for(var M=0,o=0;o<3;++o)M=Math.max(M,g[1][o]-g[0][o]);for(var o=0;o<3;++o)H.autoScale?U[5*o]=H.aspect[o]/(g[1][o]-g[0][o]):U[5*o]=1/M,H.autoCenter&&(U[12+o]=.5*-U[5*o]*(g[0][o]+g[1][o]));for(var o=0;o<r;++o){var l=D[o];l.axesBounds=g,H.clipToBounds&&(l.clipBounds=g)}if(T.object&&(H.snapToData?P.position=T.dataCoordinate:P.position=T.dataPosition,P.bounds=g),N&&(N=!1,y()),j){H.axesPixels=c(H.axes,V,_,w),H.onrender&&H.onrender(),A.bindFramebuffer(A.FRAMEBUFFER,null),A.viewport(0,0,_,w);var k=H.clearColor;A.clearColor(k[0],k[1],k[2],k[3]),A.clear(A.COLOR_BUFFER_BIT|A.DEPTH_BUFFER_BIT),A.depthMask(!0),A.colorMask(!0,!0,!0,!0),A.enable(A.DEPTH_TEST),A.depthFunc(A.LEQUAL),A.disable(A.BLEND),A.disable(A.CULL_FACE);var L=!1;C.enable&&(L=L||C.isTransparent(),C.draw(V)),P.axes=C,T.object&&P.draw(V),A.disable(A.CULL_FACE);for(var o=0;o<r;++o){var l=D[o];l.axes=C,l.pixelRatio=H.pixelRatio,l.isOpaque&&l.isOpaque()&&l.draw(V),l.isTransparent&&l.isTransparent()&&(L=!0)}if(L){E.shape=q,E.bind(),A.clear(A.DEPTH_BUFFER_BIT),A.colorMask(!1,!1,!1,!1),A.depthMask(!0),A.depthFunc(A.LESS),C.enable&&C.isTransparent()&&C.drawTransparent(V);for(var o=0;o<r;++o){var l=D[o];l.isOpaque&&l.isOpaque()&&l.draw(V)}A.enable(A.BLEND),A.blendEquation(A.FUNC_ADD),A.blendFunc(A.ONE,A.ONE_MINUS_SRC_ALPHA),A.colorMask(!0,!0,!0,!0),A.depthMask(!1),A.clearColor(0,0,0,0),A.clear(A.COLOR_BUFFER_BIT),C.isTransparent()&&C.drawTransparent(V);for(var o=0;o<r;++o){var l=D[o];l.isTransparent&&l.isTransparent()&&l.drawTransparent(V)}A.bindFramebuffer(A.FRAMEBUFFER,null),A.blendFunc(A.ONE,A.ONE_MINUS_SRC_ALPHA),A.disable(A.DEPTH_TEST),S.bind(),E.color[0].bind(0),S.uniforms.accumBuffer=0,p(A),A.disable(A.BLEND)}j=!1;for(var o=0;o<r;++o)D[o].dirty=!1}}}function b(){_||H.contextLost||(requestAnimationFrame(b),x())}t=t||{};var _=!1,w=(t.pixelRatio||parseFloat(window.devicePixelRatio),t.canvas);if(!w)if(w=document.createElement(\"canvas\"),t.container){var M=t.container;M.appendChild(w)}else document.body.appendChild(w);var A=t.gl;if(A||(A=i(w,t.glOptions||{premultipliedAlpha:!0,antialias:!0})),!A)throw new Error(\"webgl not supported\");var k=t.bounds||[[-10,-10,-10],[10,10,10]],T=new n,E=d(A,[A.drawingBufferWidth,A.drawingBufferHeight],{preferFloat:!0}),S=v(A),L=t.camera||{eye:[2,0,0],center:[0,0,0],up:[0,1,0],zoomMin:.1,zoomMax:100,mode:\"turntable\"},z=t.axes||{},C=u(A,z);C.enable=!z.disable;var I=t.spikes||{},P=h(A,I),D=[],R=[],O=[],F=[],j=!0,N=!0,B=new Array(16),U=new Array(16),V={view:null,projection:B,model:U},N=!0,q=[A.drawingBufferWidth,A.drawingBufferHeight],H={gl:A,contextLost:!1,pixelRatio:t.pixelRatio||parseFloat(window.devicePixelRatio),canvas:w,selection:T,camera:l(w,L),axes:C,axesPixels:null,spikes:P,bounds:k,objects:D,shape:q,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:o(t.autoResize),autoBounds:o(t.autoBounds),autoScale:!!t.autoScale,autoCenter:o(t.autoCenter),clipToBounds:o(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:V,oncontextloss:null,mouseListener:null},G=[A.drawingBufferWidth/H.pixelRatio|0,A.drawingBufferHeight/H.pixelRatio|0];H.autoResize&&e(),window.addEventListener(\"resize\",e),H.update=function(t){_||(t=t||{},j=!0,N=!0)},H.add=function(t){_||(t.axes=C,D.push(t),R.push(-1),j=!0,N=!0,r())},H.remove=function(t){if(!_){var e=D.indexOf(t);e<0||(D.splice(e,1),R.pop(),j=!0,N=!0,r())}},H.dispose=function(){if(!_&&(_=!0,window.removeEventListener(\"resize\",e),w.removeEventListener(\"webglcontextlost\",s),H.mouseListener.enabled=!1,!H.contextLost)){C.dispose(),P.dispose();for(var t=0;t<D.length;++t)D[t].dispose();E.dispose();for(var t=0;t<F.length;++t)F[t].dispose();S.dispose(),A=null,C=null,P=null,D=[]}};var X=!1,Y=0;H.mouseListener=g(w,function(t,e,r){if(!_){var n=F.length,i=D.length,a=T.object;T.distance=1/0,T.mouse[0]=e,T.mouse[1]=r,T.object=null,T.screen=null,T.dataCoordinate=T.dataPosition=null;var o=!1;if(t&&Y)X=!0;else{X&&(N=!0),X=!1;for(var s=0;s<n;++s){var l=F[s].query(e,G[1]-r-1,H.pickRadius);if(l){if(l.distance>T.distance)continue;for(var u=0;u<i;++u){var c=D[u];if(R[u]===s){var h=c.pick(l);h&&(T.buttons=t,T.screen=l.coord,T.distance=l.distance,T.object=c,T.index=h.distance,T.dataPosition=h.position,T.dataCoordinate=h.dataCoordinate,T.data=h,o=!0)}}}}}a&&a!==T.object&&(a.highlight&&a.highlight(null),j=!0),T.object&&(T.object.highlight&&T.object.highlight(T.data),j=!0),o=o||T.object!==a,o&&H.onselect&&H.onselect(T),1&t&&!(1&Y)&&H.onclick&&H.onclick(T),Y=t}}),w.addEventListener(\"webglcontextlost\",s);var W=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],Z=[W[0].slice(),W[1].slice()];return b(),H.redraw=function(){_||(j=!0,x())},H}e.exports=s;var l=t(\"3d-view-controls\"),u=t(\"gl-axes3d\"),c=t(\"gl-axes3d/properties\"),h=t(\"gl-spikes3d\"),f=t(\"gl-select-static\"),d=t(\"gl-fbo\"),p=t(\"a-big-triangle\"),g=t(\"mouse-change\"),m=t(\"gl-mat4/perspective\"),v=t(\"./lib/shader\")},{\"./lib/shader\":188,\"3d-view-controls\":26,\"a-big-triangle\":28,\"gl-axes3d\":120,\"gl-axes3d/properties\":127,\"gl-fbo\":135,\"gl-mat4/perspective\":152,\"gl-select-static\":219,\"gl-spikes3d\":229,\"mouse-change\":413}],190:[function(t,e,r){r.pointVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\",r.pointFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\",r.pickVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],191:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{\"./lib/GLError\":192,\"./lib/create-attributes\":193,\"./lib/create-uniforms\":194,\"./lib/reflect\":195,\"./lib/runtime-reflect\":196,\"./lib/shader-cache\":197,dup:180}],192:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],193:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":192,dup:182}],194:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":192,\"./reflect\":195,dup:183}],195:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],196:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],197:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":192,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],198:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}function i(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}function a(t,e){var r=t.gl,i=s(r),a=s(r),l=o(r,u.pointVertex,u.pointFragment),c=o(r,u.pickVertex,u.pickFragment),h=new n(t,i,a,l,c);return h.update(e),t.addObject(h),h}var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"typedarray-pool\"),u=t(\"./lib/shader\");e.exports=a;var c=n.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){function e(e,r){return e in t?t[e]:r}var r;t=t||{},this.sizeMin=e(\"sizeMin\",.5),this.sizeMax=e(\"sizeMax\",20),this.color=e(\"color\",[1,0,0,1]).slice(),this.areaRatio=e(\"areaRatio\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.blend=e(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,a=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,o=t.positions,s=i?o:l.mallocFloat32(o.length),u=a?t.idToIndex:l.mallocInt32(n);if(i||s.set(o),!a)for(s.set(o),r=0;r<n;r++)u[r]=r;this.points=o,this.offsetBuffer.update(s),this.pickBuffer.update(u),i||l.free(s),a||l.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=void 0!==r,a=n?this.pickShader:this.shader,o=this.plot.gl,s=this.plot.dataBox;if(0===this.pointCount)return r;var l=s[2]-s[0],u=s[3]-s[1],c=i(this.points,s),h=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(c,.33333)));t[0]=2/l,t[4]=2/u,t[6]=-2*s[0]/l-1,t[7]=-2*s[1]/u-1,this.offsetBuffer.bind(),a.bind(),a.attributes.position.pointer(),a.uniforms.matrix=t,a.uniforms.color=this.color,a.uniforms.borderColor=this.borderColor,a.uniforms.pointCloud=h<5,a.uniforms.pointSize=h,a.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),n&&(e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,this.pickBuffer.bind(),a.attributes.pickId.pointer(o.UNSIGNED_BYTE),a.uniforms.pickOffset=e,this.pickOffset=r);var f=o.getParameter(o.BLEND),d=o.getParameter(o.DITHER);return f&&!this.blend&&o.disable(o.BLEND),d&&o.disable(o.DITHER),o.drawArrays(o.POINTS,0,this.pointCount),f&&!this.blend&&o.enable(o.BLEND),d&&o.enable(o.DITHER),r+this.pointCount}}(),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":190,\"gl-buffer\":128,\"gl-shader\":191,\"typedarray-pool\":496}],199:[function(t,e,r){function n(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],h=e[2],f=e[3],d=r[0],p=r[1],g=r[2],m=r[3];return a=u*d+c*p+h*g+f*m,a<0&&(a=-a,d=-d,p=-p,g=-g,m=-m),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*d,t[1]=s*c+l*p,t[2]=s*h+l*g,t[3]=s*f+l*m,t}e.exports=n},{}],200:[function(t,e,r){\"use strict\";e.exports={vertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo, pixelScale;\\n\\nvarying vec4 fragColor;\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo, vec2 screenScale, vec2 screenOffset) {\\n  return vec4(scHi * posHi + trHi\\n            + scLo * posHi + trLo\\n            + scHi * posLo\\n            + scLo * posLo\\n            + screenScale * screenOffset, 0, 1);\\n}\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo,\\n    pixelScale, offset);\\n}\\n\",fragment:\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo, pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo, vec2 screenScale, vec2 screenOffset) {\\n  return vec4(scHi * posHi + trHi\\n            + scLo * posHi + trLo\\n            + scHi * posLo\\n            + scLo * posLo\\n            + screenScale * screenOffset, 0, 1);\\n}\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo,\\n    pixelScale, offset);\\n}\\n\",pickFragment:\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],201:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{\"./lib/GLError\":202,\"./lib/create-attributes\":203,\"./lib/create-uniforms\":204,\"./lib/reflect\":205,\"./lib/runtime-reflect\":206,\"./lib/shader-cache\":207,dup:180}],202:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],203:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":202,dup:182}],204:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":202,\"./reflect\":205,dup:183}],205:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],206:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],207:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":202,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],208:[function(t,e,r){\"use strict\";function n(t){if(t in f)return f[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var h=s[0]-o[0],f=s[1]-o[1],d=Math.sqrt(h*h+f*f);h/=d,f/=d,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-f,h),r.push(o[0],o[1]+1.4),n.push(-f,h),r.push(a[0],a[1]+1.4),n.push(f,-h),r.push(o[0],o[1]+1.4),n.push(f,-h)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;o<2;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return f[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o,s){this.plot=t,this.shader=e,this.pickShader=r,this.posHiBuffer=n,this.posLoBuffer=i,this.offsetBuffer=a,this.colorBuffer=o,this.idBuffer=s,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,h.vertex,h.fragment),a=o(r,h.pickVertex,h.pickFragment),l=s(r),u=s(r),c=s(r),f=s(r),d=s(r),p=new i(t,n,a,l,u,c,f,d);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),h=t(\"./lib/shaders\"),f={},d=i.prototype;!function(){function t(){var t=this.plot,o=this.bounds,s=t.viewBox,l=t.dataBox,u=t.pixelRatio,c=o[2]-o[0],h=o[3]-o[1],f=l[2]-l[0],d=l[3]-l[1],p=2*c/f,g=2*h/d,m=2*(o[0]-l[0])/f-1,v=2*(o[1]-l[1])/d-1;e[0]=p,r[0]=p-e[0],e[1]=g,r[1]=g-e[1],n[0]=m,i[0]=m-n[0],n[1]=v,i[1]=v-n[1];var y=s[2]-s[0],x=s[3]-s[1];a[0]=2*u/y,a[1]=2*u/x}var e=new Float32Array([0,0]),r=new Float32Array([0,0]),n=new Float32Array([0,0]),i=new Float32Array([0,0]),a=[0,0],o=[0,0,0,0];d.drawPick=function(s){var l=void 0!==s,u=this.plot,c=this.numVertices;if(!c)return s;t.call(this);var h=u.gl,f=l?this.pickShader:this.shader;if(f.bind(),l){this.pickOffset=s;for(var d=0;d<4;++d)o[d]=s>>8*d&255;f.uniforms.pickOffset=o,this.idBuffer.bind(),f.attributes.id.pointer(h.UNSIGNED_BYTE,!1)}else this.colorBuffer.bind(),f.attributes.color.pointer(h.UNSIGNED_BYTE,!0);return this.posHiBuffer.bind(),f.attributes.positionHi.pointer(),this.posLoBuffer.bind(),f.attributes.positionLo.pointer(),this.offsetBuffer.bind(),f.attributes.offset.pointer(),f.uniforms.pixelScale=a,f.uniforms.scaleHi=e,f.uniforms.scaleLo=r,f.uniforms.translateHi=n,f.uniforms.translateLo=i,h.drawArrays(h.TRIANGLES,0,c),l?s+this.numPoints:void 0}}(),d.draw=d.drawPick,d.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},d.update=function(t){t=t||{};var e,r,i=t.positions||[],a=t.colors||[],o=t.glyphs||[],s=t.sizes||[],c=t.borderWidths||[],h=t.borderColors||[];this.points=i;var f,d,p=this.bounds=[1/0,1/0,-(1/0),-(1/0)],g=0,m=[],v=[];for(e=0;e<o.length;++e)for(f=l(\"sans-serif\",o[e]),d=n(o[e]),m.push(f),v.push(d),g+=f.data.length+d.coords.length>>1,r=0;r<2;++r)p[r]=Math.min(p[r],i[2*e+r]),p[2+r]=Math.max(p[2+r],i[2*e+r]);p[0]===p[2]&&(p[2]+=1),p[3]===p[1]&&(p[3]+=1);var y=1/(p[2]-p[0]),x=1/(p[3]-p[1]),b=p[0],_=p[1],w=u.mallocFloat64(2*g),M=u.mallocFloat32(2*g),A=u.mallocFloat32(2*g),k=u.mallocFloat32(2*g),T=u.mallocUint8(4*g),E=u.mallocUint32(g),S=0;for(e=0;e<o.length;++e){f=m[e],d=v[e];var L=y*(i[2*e]-b),z=x*(i[2*e+1]-_),C=s[e],I=255*a[4*e],P=255*a[4*e+1],D=255*a[4*e+2],R=255*a[4*e+3],O=.5*(d.bounds[0]+d.bounds[2]),F=.5*(d.bounds[1]+d.bounds[3]);for(r=0;r<f.data.length;r+=2)w[2*S]=L,w[2*S+1]=z,k[2*S]=-C*(f.data[r]-O),k[2*S+1]=-C*(f.data[r+1]-F),T[4*S]=I,T[4*S+1]=P,T[4*S+2]=D,T[4*S+3]=R,E[S]=e,S+=1;var j=c[e];for(I=255*h[4*e],P=255*h[4*e+1],D=255*h[4*e+2],R=255*h[4*e+3],r=0;r<d.coords.length;r+=2)w[2*S]=L,w[2*S+1]=z,k[2*S]=-(C*(d.coords[r]-O)+j*d.normals[r]),k[2*S+1]=-(C*(d.coords[r+1]-F)+j*d.normals[r+1]),T[4*S]=I,T[4*S+1]=P,T[4*S+2]=D,T[4*S+3]=R,E[S]=e,S+=1}for(this.numPoints=o.length,this.numVertices=g,M.set(w),e=0;e<w.length;e++)A[e]=w[e]-M[e];this.posHiBuffer.update(M),this.posLoBuffer.update(A),this.offsetBuffer.update(k),this.colorBuffer.update(T),this.idBuffer.update(E),u.free(w),u.free(M),u.free(A),u.free(k),u.free(T),u.free(E)},d.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.posHiBuffer.dispose(),this.posLoBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":200,\"gl-buffer\":128,\"gl-shader\":201,\"text-cache\":488,\"typedarray-pool\":496,\"vectorize-text\":509}],209:[function(t,e,r){r.pointVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute float weight;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4(scaleHi * positionHi + translateHi\\n            + scaleLo * positionHi + translateLo\\n            + scaleHi * positionLo\\n            + scaleLo * positionLo, 0.0, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\",r.pointFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4(scaleHi * positionHi + translateHi\\n            + scaleLo * positionHi + translateLo\\n            + scaleHi * positionLo\\n            + scaleLo * positionLo, 0.0, 1.0);\\n}\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec4 pickId;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragId = id;\\n}\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\"},{}],210:[function(t,e,r){arguments[4][72][0].apply(r,arguments)},{dup:72}],211:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){a<=4*f?i(0,a-1,t,e,r,n):h(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;o<=e;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],h=a[o],f=o;f>t;){var d=r[f-1],p=n[2*(f-1)];if((d-s||l-p)>=0)break;r[f]=d,n[2*f]=p,n[2*f+1]=n[2*f-1],i[f]=i[f-1],a[f]=a[f-1],f-=1}r[f]=s,n[2*f]=l,n[2*f+1]=u,i[f]=c,a[f]=h}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],h=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=h}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0;\n",
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if(!c(it,D,R,O,F,r,n,d))for(;;){if(c(E,D,R,O,F,r,n,d)){c(E,L,z,C,I,r,n,d)?(s(it,T,E,r,n,d,p),++T,--E):(a(it,E,r,n,d,p),--E);break}if(--E<it)break}l(t,T-1,L,z,C,I,P,r,n,d,p),l(e,E+1,D,R,O,F,j,r,n,d,p),T-2-t<=f?i(t,T-2,r,n,d,p):h(t,T-2,r,n,d,p),e-(E+2)<=f?i(E+2,e,r,n,d,p):h(E+2,e,r,n,d,p),E-T<=f?i(T,E,r,n,d,p):h(T,E,r,n,d,p)}e.exports=n;var f=32},{}],212:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;u<n;++u){var c=t[2*u],h=t[2*u+1],f=e[u];i<=c&&c<=o&&a<=h&&h<=s&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=h,e[l]=f,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var h=.5*o,f=s+1,d=u-s;r[_]=d,b[_++]=c;for(var p=0;p<2;++p)for(var g=0;g<2;++g){var m=i+p*h,v=a+g*h,y=n(t,e,f,u,m,v,m+h,v+h);if(y!==f){if(y-f>=Math.max(.9*d,32)){var x=u+s>>>1;l(m,v,h,f,x,c+1),f=x}l(m,v,h,f,y,c+1),f=y}}}var u=t.length>>>1;if(u<1)return[];for(var c=1/0,h=1/0,f=-(1/0),d=-(1/0),p=0;p<u;++p){var g=t[2*p],m=t[2*p+1];c=Math.min(c,g),f=Math.max(f,g),h=Math.min(h,m),d=Math.max(d,m),e[p]=p}c===f&&(f+=1+Math.abs(f)),h===d&&(d+=1+Math.abs(f));var v=1/(f-c),y=1/(d-h),x=Math.max(f-c,d-h);a=a||[0,0,0,0],a[0]=c,a[1]=h,a[2]=f,a[3]=d;var b=o.mallocInt32(u),_=0;l(c,h,x,0,u,0),s(b,t,e,r,u);for(var w=[],M=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*v,t[2*_+1]=(t[2*_+1]-h)*y;var k=b[_];k!==M&&(w.push(new i(x*Math.pow(.5,k),_+1,A-(_+1))),A=_+1,M=k)}return w.push(new i(x*Math.pow(.5,k+1),0,A)),o.free(b),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":211,\"typedarray-pool\":496}],213:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o){this.plot=t,this.positionBufferHi=e,this.positionBufferLo=r,this.pickBuffer=n,this.weightBuffer=i,this.shader=a,this.pickShader=o,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=o(r),h=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),d=new n(t,i,s,l,u,h,f);return d.update(e),t.addObject(d),d}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var h=n.prototype,f=new Float32Array(2),d=new Float32Array(2),p=new Float32Array(2),g=new 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h=0,f=0;h<r;h++,f+=2)c[f]=a[f]-s[f],c[f+1]=a[f+1]-s[f+1],o[h]=a[f];this.positionBufferHi.update(s),this.positionBufferLo.update(c),this.pickBuffer.update(n),this.weightBuffer.update(i),u.free(n),u.free(a),u.free(s),u.free(c),u.free(i),this.xCoords=o,this.pointCount=r,this.pickOffset=0},h.draw=function(t){var e=void 0!==t,r=this.plot,n=e?this.pickShader:this.shader,i=this.scales,a=this.positionBufferHi,o=this.positionBufferLo,l=this.pickBuffer,u=this.bounds,c=this.size,h=this.borderSize,v=r.gl,y=e?r.pickPixelRatio:r.pixelRatio,x=r.viewBox,b=r.dataBox;if(0===this.pointCount)return t;var _=u[2]-u[0],w=u[3]-u[1],M=b[2]-b[0],A=b[3]-b[1],k=(x[2]-x[0])*y/r.pixelRatio,T=(x[3]-x[1])*y/r.pixelRatio,E=Math.min(M/k,A/T),S=2*_/M,L=2*w/A;f[0]=S,f[1]=L,d[0]=S-f[0],d[1]=L-f[1];var z=2*(u[0]-b[0])/M-1,C=2*(u[1]-b[1])/A-1;p[0]=z,p[1]=C,g[0]=z-p[0],g[1]=C-p[1],n.bind(),n.uniforms.scaleHi=f,n.uniforms.scaleLo=d,n.uniforms.translateHi=p,n.uniforms.translateLo=g,n.uniforms.color=this.color,n.uniforms.borderColor=this.borderColor,n.uniforms.pointSize=y*(c+h),n.uniforms.centerFraction=0===this.borderSize?2:c/(c+h+1.25),a.bind(),n.attributes.positionHi.pointer(),o.bind(),n.attributes.positionLo.pointer(),e?(this.pickOffset=t,m[0]=255&t,m[1]=t>>8&255,m[2]=t>>16&255,m[3]=t>>24&255,n.uniforms.pickOffset=m,l.bind(),n.attributes.pickId.pointer(v.UNSIGNED_BYTE)):(n.uniforms.useWeight=1,this.weightBuffer.bind(),n.attributes.weight.pointer());for(var I=this.xCoords,P=(b[0]-u[0]-E*c*y)/_,D=(b[2]-u[0]+E*c*y)/_,R=!0,O=i.length-1;O>=0;O--){var F=i[O];if(!(F.pixelSize<E&&O>1)){var j=F.offset,N=F.count+j,B=s.ge(I,P,j,N-1),U=s.lt(I,D,B,N-1)+1;U>B&&v.drawArrays(v.POINTS,B,U-B),!e&&R&&(R=!1,n.uniforms.useWeight=0)}}},h.drawPick=h.draw,h.pick=function(t,e,r){var n=r-this.pickOffset;return n<0||n>=this.pointCount?null:{object:this,pointId:n,dataCoord:[this.points[2*n],this.points[2*n+1]]}}},{\"./lib/shader\":209,\"binary-search-bounds\":210,\"gl-buffer\":128,\"gl-shader\":220,\"snap-points-2d\":212,\"typedarray-pool\":496}],214:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;c<2;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":509}],215:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],h={vertex:a,fragment:l,attributes:c},f={vertex:o,fragment:l,attributes:c},d={vertex:s,fragment:l,attributes:c},p={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},m={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,h)},r.createOrtho=function(t){return n(t,f)},r.createProject=function(t){return n(t,d)},r.createPickPerspective=function(t){return n(t,p)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,m)}},{\"gl-shader\":220}],216:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,h,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=h,this.pickProjectShader=f,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=L,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function h(t,e,r,n,a){var o,h=e.axesProject,f=e.gl,d=t.uniforms,p=r.model||b,g=r.view||b,m=r.projection||b,y=e.axesBounds,x=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/f.drawingBufferWidth,w[1]=2/f.drawingBufferHeight,t.bind(),d.view=g,d.projection=m,d.screenSize=w,d.highlightId=e.highlightId,d.highlightScale=e.highlightScale,d.clipBounds=x,d.pickGroup=e.pickId/255,d.pixelRatio=e.pixelRatio;for(var _=0;_<3;++_)if(h[_]&&e.projectOpacity[_]<1===n){d.scale=e.projectScale[_],d.opacity=e.projectOpacity[_];for(var L=E,z=0;z<16;++z)L[z]=0;for(var z=0;z<4;++z)L[5*z]=1;L[5*_]=0,o[_]<0?L[12+_]=y[0][_]:L[12+_]=y[1][_],v(L,p,L),d.model=L;var C=(_+1)%3,I=(_+2)%3,P=s(M),D=s(A);P[C]=1,D[I]=1;var R=i(m,g,p,l(k,P)),O=i(m,g,p,l(T,D));if(Math.abs(R[1])>Math.abs(O[1])){var F=R;R=O,O=F,F=P,P=D,D=F;var j=C;C=I,I=j}R[0]<0&&(P[C]=-1),O[1]>0&&(D[I]=-1);for(var N=0,B=0,z=0;z<4;++z)N+=Math.pow(p[4*C+z],2),B+=Math.pow(p[4*I+z],2);P[C]/=Math.sqrt(N),D[I]/=Math.sqrt(B),d.axes[0]=P,d.axes[1]=D,d.fragClipBounds[0]=u(S,x[0],_,-1e8),d.fragClipBounds[1]=u(S,x[1],_,1e8),e.vao.draw(f.TRIANGLES,e.vertexCount),e.lineWidth>0&&(f.lineWidth(e.lineWidth),e.vao.draw(f.LINES,e.lineVertexCount,e.vertexCount))}}function f(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||b,s.view=n.view||b,s.projection=n.projection||b,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=I,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}h(e,r,n,i,a),r.vao.unbind()}function d(t){var 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w=[0,0],M=[0,0,0],A=[0,0,0],k=[0,0,0,1],T=[0,0,0,1],E=b.slice(),S=[0,0,0],L=[[0,0,0],[0,0,0]],z=[-1e8,-1e8,-1e8],C=[1e8,1e8,1e8],I=[z,C];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;f(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;f(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;f(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in 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U=Math.cos(B),V=Math.sin(B),b=n[y],_=0;_<3;++_)s[_]=Math.max(s[_],b[_]),o[_]=Math.min(o[_],b[_]);a[0]<0?C[0]=a[0]*(1+k[1][0]):a[0]>0&&(C[0]=-a[0]*(1+k[0][0]));for(var q=M.cells,H=M.positions,_=0;_<q.length;++_)for(var G=q[_],X=0;X<3;++X){for(var Y=0;Y<3;++Y)E[3*I+Y]=b[Y];for(var Y=0;Y<4;++Y)S[4*I+Y]=D[Y];z[I]=d;var W=H[G[X]];L[2*I]=N*(U*W[0]-V*W[1]+C[0]),L[2*I+1]=N*(V*W[0]+U*W[1]+C[1]),I+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],X=0;X<2;++X){for(var Y=0;Y<3;++Y)E[3*P+Y]=b[Y];for(var Y=0;Y<4;++Y)S[4*P+Y]=R[Y];z[P]=d;var W=H[G[X]];L[2*P]=N*(U*W[0]-V*W[1]+C[0]),L[2*P+1]=N*(V*W[0]+U*W[1]+C[1]),P+=1}d+=1}this.vertexCount=p,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(S),this.glyphBuffer.update(L),this.idBuffer.update(new Uint32Array(z)),m.free(E),m.free(S),m.free(L),m.free(z),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":214,\"./lib/shaders\":215,\"gl-buffer\":128,\"gl-mat4/multiply\":151,\"gl-vao\":236,\"typedarray-pool\":496}],217:[function(t,e,r){\"use strict\";r.boxVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],218:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,h=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],f=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],d=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],p=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(h=Math.max(h,u[0]),f=Math.max(f,u[1]),d=Math.min(d,u[2]),p=Math.min(p,u[3]),!(d<h||p<f)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,f,i),o.drawBox(0,f,h,p,i),o.drawBox(0,p,g,m,i),o.drawBox(d,f,g,p,i)),this.innerFill&&o.drawBox(h,f,d,p,n),r>0){var v=r*c;o.drawBox(h-v,f-v,d+v,f+v,a),o.drawBox(h-v,p-v,d+v,p+v,a),o.drawBox(h-v,f-v,h+v,p+v,a),o.drawBox(d-v,f-v,d+v,p+v,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":217,\"gl-buffer\":128,\"gl-shader\":220}],219:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(_inline_46_arg0_<255||_inline_46_arg1_<255||_inline_46_arg2_<255||_inline_46_arg3_<255){var 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this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){s.free(this.buffer);for(var n=this.buffer=s.mallocUint8(u(r*e*4)),i=0;i<r*e*4;++i)n[i]=255}return t}}}),h.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},h.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},h.query=function(t,e,r){if(!this.gl)return null;var i=this.fbo.shape.slice();t=0|t,e=0|e,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),i[0]),o=0|Math.min(Math.max(t+r,0),i[0]),s=0|Math.min(Math.max(e-r,0),i[1]),u=0|Math.min(Math.max(e+r,0),i[1]);if(o<=a||u<=s)return null;var 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v=p.createProgram();if(p.attachShader(v,d.fragShader),p.attachShader(v,d.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var y=p.getProgramInfoLog(v);throw new h(y,\"Error linking program:\"+y)}r=r||c.uniforms(p,v),n=n||c.attributes(p,v),p.deleteProgram(v)}n=n.slice(),n.sort(i);for(var x=[],b=[],_=[],w=0;w<n.length;++w){var M=n[w];if(M.type.indexOf(\"mat\")>=0){for(var A=0|M.type.charAt(M.type.length-1),k=new Array(A),T=0;T<A;++T)k[T]=_.length,b.push(M.name+\"[\"+T+\"]\"),\"number\"==typeof M.location?_.push(M.location+T):Array.isArray(M.location)&&M.location.length===A&&\"number\"==typeof M.location[T]?_.push(0|M.location[T]):_.push(-1);x.push({name:M.name,type:M.type,locations:k})}else x.push({name:M.name,type:M.type,locations:[_.length]}),b.push(M.name),\"number\"==typeof M.location?_.push(0|M.location):_.push(-1)}for(var E=0,w=0;w<_.length;++w)if(_[w]<0){for(;_.indexOf(E)>=0;)E+=1;_[w]=E}var S=new Array(r.length);a(),d._relink=a,d.types={uniforms:l(r),attributes:l(n)},d.attributes=s(p,d,x,_),Object.defineProperty(d,\"uniforms\",o(p,d,r,S))},e.exports=a},{\"./lib/GLError\":221,\"./lib/create-attributes\":222,\"./lib/create-uniforms\":223,\"./lib/reflect\":224,\"./lib/runtime-reflect\":225,\"./lib/shader-cache\":226}],221:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],222:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":221,dup:182}],223:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":221,\"./reflect\":224,dup:183}],224:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],225:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],226:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":221,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],227:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}function i(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r}e.exports=i;var a=n.prototype;a.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map(function(t){return t.slice()}),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},a.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],228:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":220}],229:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}function i(t,e){function r(t,e,r,n,a,o){var s=[t,e,r,0,0,0,1];s[n+3]=1,s[n]=a,i.push.apply(i,s),s[6]=-1,i.push.apply(i,s),s[n]=o,i.push.apply(i,s),i.push.apply(i,s),s[6]=1,i.push.apply(i,s),s[n]=a,i.push.apply(i,s)}var i=[];r(0,0,0,0,0,1),r(0,0,0,1,0,1),r(0,0,0,2,0,1),r(1,0,0,1,-1,1),r(1,0,0,2,-1,1),r(0,1,0,0,-1,1),r(0,1,0,2,-1,1),r(0,0,1,0,-1,1),r(0,0,1,1,-1,1);var l=a(t,i),u=o(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),c=s(t);c.attributes.position.location=0,c.attributes.color.location=1,c.attributes.weight.location=2;var h=new n(t,l,u,c);return h.update(e),h}var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders/index\");e.exports=i;var l=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],u=n.prototype,c=[0,0,0],h=[0,0,0],f=[0,0];u.isTransparent=function(){return!1},u.drawTransparent=function(t){},u.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||l,o=t.view||l,s=t.projection||l;this.axes&&(i=this.axes.lastCubeProps.axis);for(var u=c,d=h,p=0;p<3;++p)i&&i[p]<0?(u[p]=this.bounds[0][p],d[p]=this.bounds[1][p]):(u[p]=this.bounds[1][p],d[p]=this.bounds[0][p]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=o,\n",
+       "n.uniforms.projection=s,n.uniforms.coordinates=[this.position,u,d],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(var p=0;p<3;++p)n.uniforms.lineWidth=this.lineWidth[p]*this.pixelRatio,this.enabled[p]&&(r.draw(e.TRIANGLES,6,6*p),this.drawSides[p]&&r.draw(e.TRIANGLES,12,18+12*p));r.unbind()},u.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},u.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":228,\"gl-buffer\":128,\"gl-vao\":236}],230:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor = step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) + step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  vec4 worldPosition = model * vec4(dataCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z = clipPosition.z + zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f;\\n  kill = -1.0;\\n  worldCoordinate = dataCoordinate;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":220}],231:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=b([y({colormap:t,nshades:O,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return x.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,h,f,d,p){this.gl=t,this.shape=e,this.bounds=r,this.intensityBounds=[],this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=f,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=p,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(v.mallocFloat(1024),[0,0]),_(v.mallocFloat(1024),[0,0]),_(v.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}function o(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||j,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=N.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],M(l,t.model,l);var u=N.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return N.showSurface=o,N.showContour=s,N}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||P,n.view=t.view||P,n.projection=t.projection||P,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],s=0;s<3;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V,n.vertexColor=this.vertexColor;var l=U;for(M(l,n.view,n.model),M(l,n.projection,l),A(l,l),i=0;i<3;++i)n.eyePosition[i]=l[12+i]/l[15];var u=l[15];for(i=0;i<3;++i)u+=this.lightPosition[i]*l[4*i+3];for(i=0;i<3;++i){var c=l[12+i];for(s=0;s<3;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var h=o(n,this);if(h.showSurface&&e===this.opacity<1){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=h.projections[i],this._shader.uniforms.clipBounds=h.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(h.showContour&&!e){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var d=this._contourVAO;for(d.bind(),i=0;i<3;++i)for(f.uniforms.permutation=R[i],r.lineWidth(this.contourWidth[i]),s=0;s<this.contourLevels[i].length;++s)this._contourCounts[i][s]&&(s===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==s&&s-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),f.uniforms.height=this.contourLevels[i][s],d.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s]));for(i=0;i<3;++i)for(f.uniforms.model=h.projections[i],f.uniforms.clipBounds=h.clipBounds[i],s=0;s<3;++s)if(this.contourProject[i][s]){f.uniforms.permutation=R[s],r.lineWidth(this.contourWidth[s]);for(var p=0;p<this.contourLevels[s].length;++p)p===this.highlightLevel[s]?(f.uniforms.contourColor=this.highlightColor[s],f.uniforms.contourTint=this.highlightTint[s]):0!==p&&p-1!==this.highlightLevel[s]||(f.uniforms.contourColor=this.contourColor[s],f.uniforms.contourTint=this.contourTint[s]),f.uniforms.height=this.contourLevels[s][p],d.draw(r.LINES,this._contourCounts[s][p],this._contourOffsets[s][p])}for(d=this._dynamicVAO,d.bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=R[i],r.lineWidth(this.dynamicWidth[i]),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),s=0;s<3;++s)this.contourProject[s][i]&&(f.uniforms.model=h.projections[s],f.uniforms.clipBounds=h.clipBounds[s],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));d.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();x.assign(t.lo(1,1).hi(r[0],r[1]),e),x.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),x.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),x.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),x.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function h(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function f(t){var e=t.gl,r=S(e),n=z(e),i=L(e),o=C(e),s=p(e),l=g(e,[{buffer:s,size:4,stride:I,offset:0},{buffer:s,size:3,stride:I,offset:16},{buffer:s,size:3,stride:I,offset:28}]),u=p(e),c=g(e,[{buffer:u,size:4,stride:20,offset:0},{buffer:u,size:1,stride:20,offset:16}]),h=p(e),f=g(e,[{buffer:h,size:2,type:e.FLOAT}]),d=m(e,1,O,e.RGBA,e.UNSIGNED_BYTE);d.minFilter=e.LINEAR,d.magFilter=e.LINEAR;var v=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,d,i,o,u,c,h,f),y={levels:[[],[],[]]};for(var x in t)y[x]=t[x];return y.colormap=y.colormap||\"jet\",v.update(y),v}e.exports=f;var d=t(\"bit-twiddle\"),p=t(\"gl-buffer\"),g=t(\"gl-vao\"),m=t(\"gl-texture2d\"),v=t(\"typedarray-pool\"),y=t(\"colormap\"),x=t(\"ndarray-ops\"),b=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),M=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),k=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),E=t(\"./lib/shaders\"),S=E.createShader,L=E.createContourShader,z=E.createPickShader,C=E.createPickContourShader,I=40,P=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],D=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],R=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;t<3;++t){var e=R[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var O=256,F=a.prototype;F.isTransparent=function(){return this.opacity<1},F.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},F.pickSlots=1,F.setPickBase=function(t){this.pickId=t};var j=[0,0,0],N={showSurface:!1,showContour:!1,projections:[P.slice(),P.slice(),P.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:P,view:P,projection:P,inverseModel:P.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},U=P.slice(),V=[1,0,0,0,1,0,0,0,1];F.draw=function(t){return s.call(this,t,!1)},F.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:P,view:P,projection:P,inverseModel:P,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};F.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||P,r.view=t.view||P,r.projection=t.projection||P,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;for(u.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=R[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){l.uniforms.permutation=R[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}u.unbind()}},F.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var h=c?a:1-a,f=0;f<2;++f)for(var d=f?l:1-l,p=i+c,g=s+f,m=h*d,v=0;v<3;++v)u[v]+=this._field[v].get(p,g)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=k.le(this.contourLevels[x],u[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},F.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=h(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=h(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0);var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var n=(e.shape[0]+2)*(e.shape[1]+2);n>this._field[2].data.length&&(v.freeFloat(this._field[2].data),this._field[2].data=v.mallocFloat(d.nextPow2(n))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(v.freeFloat(this._field[o].data),this._field[o].data=v.mallocFloat(this._field[2].size)),this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var s=t.coords;if(!Array.isArray(s)||3!==s.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=s[o];for(y=0;y<2;++y)if(c.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[o],c)}}else if(t.ticks){var f=t.ticks;if(!Array.isArray(f)||2!==f.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=f[o];if((Array.isArray(p)||p.length)&&(p=_(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var g=_(p.data,a);g.stride[o]=p.stride[0],g.stride[1^o]=0,l(this._field[o],g)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var x=this._field,b=_(v.mallocFloat(3*x[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)T(b.pick(o),x[o],\"mirror\");var M=_(v.mallocFloat(3*x[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var A=b.get(0,o,y,0),k=b.get(0,o,y,1),E=b.get(1,o,y,0),S=b.get(1,o,y,1),L=b.get(2,o,y,0),z=b.get(2,o,y,1),C=E*z-S*L,I=L*k-z*A,P=A*S-k*E,R=Math.sqrt(C*C+I*I+P*P);R<1e-8?(R=Math.max(Math.abs(C),Math.abs(I),Math.abs(P)),R<1e-8?(P=1,I=C=0,R=1):R=1/R):R=1/Math.sqrt(R),M.set(o,y,0,C*R),M.set(o,y,1,I*R),M.set(o,y,2,P*R)}v.free(b.data);var O=[1/0,1/0,1/0],F=[-(1/0),-(1/0),-(1/0)],j=1/0,N=-(1/0),B=(a[0]-1)*(a[1]-1)*6,U=v.mallocFloat(d.nextPow2(10*B)),V=0,q=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var H=0;H<2;++H)for(var G=0;G<2;++G)for(var X=0;X<3;++X){var Y=this._field[X].get(1+o+H,1+y+G);if(isNaN(Y)||!isFinite(Y))continue t}for(X=0;X<6;++X){var W=o+D[X][0],Z=y+D[X][1],Q=this._field[0].get(W+1,Z+1),K=this._field[1].get(W+1,Z+1);Y=this._field[2].get(W+1,Z+1);var $=Y;C=M.get(W+1,Z+1,0),I=M.get(W+1,Z+1,1),P=M.get(W+1,Z+1,2),t.intensity&&($=t.intensity.get(W,Z)),U[V++]=W,U[V++]=Z,U[V++]=Q,U[V++]=K,U[V++]=Y,U[V++]=0,U[V++]=$,U[V++]=C,U[V++]=I,U[V++]=P,O[0]=Math.min(O[0],Q),O[1]=Math.min(O[1],K),O[2]=Math.min(O[2],Y),j=Math.min(j,$),F[0]=Math.max(F[0],Q),F[1]=Math.max(F[1],K),F[2]=Math.max(F[2],Y),N=Math.max(N,$),q+=1}}for(t.intensityBounds&&(j=+t.intensityBounds[0],N=+t.intensityBounds[1]),o=6;o<V;o+=10)U[o]=(U[o]-j)/(N-j);this._vertexCount=q,this._coordinateBuffer.update(U.subarray(0,V)),v.freeFloat(U),v.free(M.data),this.bounds=[O,F],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===j&&this.intensityBounds[1]===N||(r=!0),this.intensityBounds=[j,N]}if(\"levels\"in t){var J=t.levels;for(J=Array.isArray(J[0])?J.slice():[[],[],J],o=0;o<3;++o)J[o]=J[o].slice(),J.sort(function(t,e){return t-e});t:for(o=0;o<3;++o){if(J[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<J[o].length;++y)if(J[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=J}if(r){x=this._field,a=this.shape;for(var tt=[],et=0;et<3;++et){J=this.contourLevels[et];var rt=[],nt=[],it=[0,0,0];for(o=0;o<J.length;++o){var at=w(this._field[et],J[o]);rt.push(tt.length/5|0),q=0;t:for(y=0;y<at.cells.length;++y){var ot=at.cells[y];for(X=0;X<2;++X){var st=at.positions[ot[X]],lt=st[0],ut=0|Math.floor(lt),ct=lt-ut,ht=st[1],ft=0|Math.floor(ht),dt=ht-ft,pt=!1;e:for(var gt=0;gt<3;++gt){it[gt]=0;var mt=(et+gt+1)%3;for(H=0;H<2;++H){var vt=H?ct:1-ct;for(W=0|Math.min(Math.max(ut+H,0),a[0]),G=0;G<2;++G){var yt=G?dt:1-dt;if(Z=0|Math.min(Math.max(ft+G,0),a[1]),Y=gt<2?this._field[mt].get(W,Z):(this.intensity.get(W,Z)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(Y)||isNaN(Y)){pt=!0;break e}var xt=vt*yt;it[gt]+=xt*Y}}}if(pt){if(X>0){for(var bt=0;bt<5;++bt)tt.pop();q-=1}continue t}tt.push(it[0],it[1],st[0],st[1],it[2]),q+=1}}nt.push(q)}this._contourOffsets[et]=rt,this._contourCounts[et]=nt}var _t=v.mallocFloat(tt.length);for(o=0;o<tt.length;++o)_t[o]=tt[o];this._contourBuffer.update(_t),v.freeFloat(_t)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},F.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)v.freeFloat(this._field[t].data)},F.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=v.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],h=this._field[l],f=(this.intensity,w(u,r[o])),d=f.cells,p=f.positions;for(this._dynamicOffsets[o]=n,e=0;e<d.length;++e)for(var g=d[e],m=0;m<2;++m){var y=p[g[m]],x=+y[0],b=0|x,_=0|Math.min(b+1,i[0]),M=x-b,A=1-M,k=+y[1],T=0|k,E=0|Math.min(T+1,i[1]),S=k-T,L=1-S,z=A*L,C=A*S,I=M*L,P=M*S,D=z*c.get(b,T)+C*c.get(b,E)+I*c.get(_,T)+P*c.get(_,E),R=z*h.get(b,T)+C*h.get(b,E)+I*h.get(_,T)+P*h.get(_,E);if(isNaN(D)||isNaN(R)){m&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=R,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),v.freeFloat(a)}}},{\"./lib/shaders\":230,\"binary-search-bounds\":53,\"bit-twiddle\":54,colormap:80,\"gl-buffer\":128,\"gl-mat4/invert\":149,\"gl-mat4/multiply\":151,\"gl-texture2d\":232,\"gl-vao\":236,ndarray:427,\"ndarray-gradient\":418,\"ndarray-ops\":421,\"ndarray-pack\":422,\"surface-nets\":487,\"typedarray-pool\":496}],232:[function(t,e,r){\"use strict\";function n(t){m=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],v=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],y=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function i(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function a(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var 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n=t(\"./literals\");e.exports=n.slice().concat([\"layout\",\"centroid\",\"smooth\",\"case\",\"mat2x2\",\"mat2x3\",\"mat2x4\",\"mat3x2\",\"mat3x3\",\"mat3x4\",\"mat4x2\",\"mat4x3\",\"mat4x4\",\"uint\",\"uvec2\",\"uvec3\",\"uvec4\",\"samplerCubeShadow\",\"sampler2DArray\",\"sampler2DArrayShadow\",\"isampler2D\",\"isampler3D\",\"isamplerCube\",\"isampler2DArray\",\"usampler2D\",\"usampler3D\",\"usamplerCube\",\"usampler2DArray\",\"coherent\",\"restrict\",\"readonly\",\"writeonly\",\"resource\",\"atomic_uint\",\"noperspective\",\"patch\",\"sample\",\"subroutine\",\"common\",\"partition\",\"active\",\"filter\",\"image1D\",\"image2D\",\"image3D\",\"imageCube\",\"iimage1D\",\"iimage2D\",\"iimage3D\",\"iimageCube\",\"uimage1D\",\"uimage2D\",\"uimage3D\",\"uimageCube\",\"image1DArray\",\"image2DArray\",\"iimage1DArray\",\"iimage2DArray\",\"uimage1DArray\",\"uimage2DArray\",\"image1DShadow\",\"image2DShadow\",\"image1DArrayShadow\",\"image2DArrayShadow\",\"imageBuffer\",\"iimageBuffer\",\"uimageBuffer\",\"sampler1DArray\",\"sampler1DArrayShadow\",\"isampler1D\",\"isampler1DArray\",\"usampler1D\",\"usampler1DArray\",\"isampler2DRect\",\"usampler2DRect\",\"samplerBuffer\",\"isamplerBuffer\",\"usamplerBuffer\",\"sampler2DMS\",\"isampler2DMS\",\"usampler2DMS\",\"sampler2DMSArray\",\"isampler2DMSArray\",\"usampler2DMSArray\"])},{\"./literals\":249}],249:[function(t,e,r){e.exports=[\"precision\",\"highp\",\"mediump\",\"lowp\",\"attribute\",\"const\",\"uniform\",\"varying\",\"break\",\"continue\",\"do\",\"for\",\"while\",\"if\",\"else\",\"in\",\"out\",\"inout\",\"float\",\"int\",\"void\",\"bool\",\"true\",\"false\",\"discard\",\"return\",\"mat2\",\"mat3\",\"mat4\",\"vec2\",\"vec3\",\"vec4\",\"ivec2\",\"ivec3\",\"ivec4\",\"bvec2\",\"bvec3\",\"bvec4\",\"sampler1D\",\"sampler2D\",\"sampler3D\",\"samplerCube\",\"sampler1DShadow\",\"sampler2DShadow\",\"struct\",\"asm\",\"class\",\"union\",\"enum\",\"typedef\",\"template\",\"this\",\"packed\",\"goto\",\"switch\",\"default\",\"inline\",\"noinline\",\"volatile\",\"public\",\"static\",\"extern\",\"external\",\"interface\",\"long\",\"short\",\"double\",\"half\",\"fixed\",\"unsigned\",\"input\",\"output\",\"hvec2\",\"hvec3\",\"hvec4\",\"dvec2\",\"dvec3\",\"dvec4\",\"fvec2\",\"fvec3\",\"fvec4\",\"sampler2DRect\",\"sampler3DRect\",\"sampler2DRectShadow\",\"sizeof\",\"cast\",\"namespace\",\"using\"]},{}],250:[function(t,e,r){e.exports=[\"<<=\",\">>=\",\"++\",\"--\",\"<<\",\">>\",\"<=\",\">=\",\"==\",\"!=\",\"&&\",\"||\",\"+=\",\"-=\",\"*=\",\"/=\",\"%=\",\"&=\",\"^^\",\"^=\",\"|=\",\"(\",\")\",\"[\",\"]\",\".\",\"!\",\"~\",\"*\",\"/\",\"%\",\"+\",\"-\",\"<\",\">\",\"&\",\"^\",\"|\",\"?\",\":\",\"=\",\",\",\";\",\"{\",\"}\"]},{}],251:[function(t,e,r){function 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Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},n.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=i+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var a=new Int32Array(e+r+this.keys.length+this.bboxes.length);a[0]=this.extent,a[1]=this.n,a[2]=this.padding;for(var o=e,s=0;s<t.length;s++){var l=t[s];a[i+s]=o,a.set(l,o),o+=l.length}return a[i+t.length]=o,a.set(this.keys,o),o+=this.keys.length,a[i+t.length+1]=o,a.set(this.bboxes,o),o+=this.bboxes.length,a.buffer}},{}],253:[function(t,e,r){r.read=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,u=l>>1,c=-7,h=r?i-1:0,f=r?-1:1,d=t[e+h];for(h+=f,a=d&(1<<-c)-1,d>>=-c,c+=s;c>0;a=256*a+t[e+h],h+=f,c-=8);for(o=a&(1<<-c)-1,a>>=-c,c+=n;c>0;o=256*o+t[e+h],h+=f,c-=8);if(0===a)a=1-u;else{if(a===l)return o?NaN:(d?-1:1)*(1/0);o+=Math.pow(2,n),a-=u}return(d?-1:1)*o*Math.pow(2,a-n)},r.write=function(t,e,r,n,i,a){var o,s,l,u=8*a-i-1,c=(1<<u)-1,h=c>>1,f=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,d=n?0:a-1,p=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=c):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),e+=o+h>=1?f/l:f*Math.pow(2,1-h),e*l>=2&&(o++,l/=2),o+h>=c?(s=0,o=c):o+h>=1?(s=(e*l-1)*Math.pow(2,i),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,i),o=0));i>=8;t[r+d]=255&s,d+=p,s/=256,i-=8);for(o=o<<i|s,u+=i;u>0;t[r+d]=255&o,d+=p,o/=256,u-=8);t[r+d-p]|=128*g}},{}],254:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;r<=t;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function 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This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\nuniform mediump float u_blur;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_blur;\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_fade;\\nuniform float u_opacity;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float x_a = mod(v_linesofar / u_pattern_size_a.x, 1.0);\\n    float x_b = mod(v_linesofar / u_pattern_size_b.x, 1.0);\\n    float y_a = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_a.y);\\n    float y_b = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_b.y);\\n    vec2 pos_a = mix(u_pattern_tl_a, u_pattern_br_a, vec2(x_a, y_a));\\n    vec2 pos_b = mix(u_pattern_tl_b, u_pattern_br_b, vec2(x_b, y_b));\\n\\n    vec4 color = mix(texture2D(u_image, pos_a), texture2D(u_image, pos_b), u_fade);\\n\\n    alpha *= u_opacity;\\n\\n    gl_FragColor = color * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n    v_linesofar = a_linesofar;\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linesdfpattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\n\\nuniform float u_blur;\\nuniform sampler2D u_image;\\nuniform float u_sdfgamma;\\nuniform float u_mix;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float sdfdist_a = texture2D(u_image, v_tex_a).a;\\n    float sdfdist_b = texture2D(u_image, v_tex_b).a;\\n    float sdfdist = mix(sdfdist_a, sdfdist_b, u_mix);\\n    alpha *= smoothstep(0.5 - u_sdfgamma, 0.5 + u_sdfgamma, sdfdist);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform vec2 u_patternscale_a;\\nuniform float u_tex_y_a;\\nuniform vec2 u_patternscale_b;\\nuniform float u_tex_y_b;\\nuniform float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    v_tex_a = vec2(a_linesofar * u_patternscale_a.x, normal.y * u_patternscale_a.y + u_tex_y_a);\\n    v_tex_b = vec2(a_linesofar * u_patternscale_b.x, normal.y * u_patternscale_b.y + u_tex_y_b);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},outline:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    gl_FragColor = outline_color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},outlinepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    // find distance to outline for alpha interpolation\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    \\n\\n    gl_FragColor = mix(color1, color2, u_mix) * alpha * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},pattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    gl_FragColor = mix(color1, color2, u_mix) * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n}\\n\"},raster:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity0;\\nuniform float u_opacity1;\\nuniform sampler2D u_image0;\\nuniform sampler2D u_image1;\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nuniform float u_brightness_low;\\nuniform float u_brightness_high;\\n\\nuniform float u_saturation_factor;\\nuniform float u_contrast_factor;\\nuniform vec3 u_spin_weights;\\n\\nvoid main() {\\n\\n    // read and cross-fade colors from the main and parent tiles\\n    vec4 color0 = texture2D(u_image0, v_pos0);\\n    vec4 color1 = texture2D(u_image1, v_pos1);\\n    vec4 color = color0 * u_opacity0 + color1 * u_opacity1;\\n    vec3 rgb = color.rgb;\\n\\n    // spin\\n    rgb = vec3(\\n        dot(rgb, u_spin_weights.xyz),\\n        dot(rgb, u_spin_weights.zxy),\\n        dot(rgb, u_spin_weights.yzx));\\n\\n    // saturation\\n    float average = (color.r + color.g + color.b) / 3.0;\\n    rgb += (average - rgb) * u_saturation_factor;\\n\\n    // contrast\\n    rgb = (rgb - 0.5) * u_contrast_factor + 0.5;\\n\\n    // brightness\\n    vec3 u_high_vec = vec3(u_brightness_low, u_brightness_low, u_brightness_low);\\n    vec3 u_low_vec = vec3(u_brightness_high, u_brightness_high, u_brightness_high);\\n\\n    gl_FragColor = vec4(mix(u_high_vec, u_low_vec, rgb), color.a);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_tl_parent;\\nuniform float u_scale_parent;\\nuniform float u_buffer_scale;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos0 = (((a_texture_pos / 32767.0) - 0.5) / u_buffer_scale ) + 0.5;\\n    v_pos1 = (v_pos0 * u_scale_parent) + u_tl_parent;\\n}\\n\"},icon:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp float u_opacity;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    lowp float alpha = texture2D(u_fadetexture, v_fade_tex).a * u_opacity;\\n    gl_FragColor = texture2D(u_texture, v_tex) * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n    if (u_rotate_with_map) {\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    } else {\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},sdf:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\nuniform lowp float u_buffer;\\nuniform lowp float u_gamma;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    lowp float dist = texture2D(u_texture, v_tex).a;\\n    lowp float fade_alpha = texture2D(u_fadetexture, v_fade_tex).a;\\n    lowp float gamma = u_gamma * v_gamma_scale;\\n    lowp float alpha = smoothstep(u_buffer - gamma, u_buffer + gamma, dist) * fade_alpha;\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nconst float PI = 3.141592653589793;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform bool u_pitch_with_map;\\nuniform mediump float u_pitch;\\nuniform mediump float u_bearing;\\nuniform mediump float u_aspect_ratio;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    // pitch-alignment: map\\n    // rotation-alignment: map | viewport\\n    if (u_pitch_with_map) {\\n        lowp float angle = u_rotate_with_map ? (a_data[1] / 256.0 * 2.0 * PI) : u_bearing;\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, asin, -1.0 * asin, acos);\\n        vec2 offset = RotationMatrix * a_offset;\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: map\\n    } else if (u_rotate_with_map) {\\n        // foreshortening factor to apply on pitched maps\\n        // as a label goes from horizontal <=> vertical in angle\\n        // it goes from 0% foreshortening to up to around 70% foreshortening\\n        lowp float pitchfactor = 1.0 - cos(u_pitch * sin(u_pitch * 0.75));\\n\\n        lowp float lineangle = a_data[1] / 256.0 * 2.0 * PI;\\n\\n        // use the lineangle to position points a,b along the line\\n        // project the points and calculate the label angle in projected space\\n        // this calculation allows labels to be rendered unskewed on pitched maps\\n        vec4 a = u_matrix * vec4(a_pos, 0, 1);\\n        vec4 b = u_matrix * vec4(a_pos + vec2(cos(lineangle),sin(lineangle)), 0, 1);\\n        lowp float angle = atan((b[1]/b[3] - a[1]/a[3])/u_aspect_ratio, b[0]/b[3] - a[0]/a[3]);\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, -1.0 * asin, asin, acos);\\n\\n        vec2 offset = RotationMatrix * (vec2((1.0-pitchfactor)+(pitchfactor*cos(angle*2.0)), 1.0) * a_offset);\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: viewport\\n    } else {\\n        vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_gamma_scale = (gl_Position.w - 0.5);\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},collisionbox:{\n",
+       "fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_zoom;\\nuniform float u_maxzoom;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n\\n    float alpha = 0.5;\\n\\n    gl_FragColor = vec4(0.0, 1.0, 0.0, 1.0) * alpha;\\n\\n    if (v_placement_zoom > u_zoom) {\\n        gl_FragColor = vec4(1.0, 0.0, 0.0, 1.0) * alpha;\\n    }\\n\\n    if (u_zoom >= v_max_zoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 0.0, 1.0) * alpha * 0.25;\\n    }\\n\\n    if (v_placement_zoom >= u_maxzoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 1.0, 1.0) * alpha * 0.2;\\n    }\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_extrude;\\nattribute vec2 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform float u_scale;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos + a_extrude / u_scale, 0.0, 1.0);\\n\\n    v_max_zoom = a_data.x;\\n    v_placement_zoom = a_data.y;\\n}\\n\"}},e.exports.util=\"float evaluate_zoom_function_1(const vec4 values, const float t) {\\n    if (t < 1.0) {\\n        return mix(values[0], values[1], t);\\n    } else if (t < 2.0) {\\n        return mix(values[1], values[2], t - 1.0);\\n    } else {\\n        return mix(values[2], values[3], t - 2.0);\\n    }\\n}\\nvec4 evaluate_zoom_function_4(const vec4 value0, const vec4 value1, const vec4 value2, const vec4 value3, const float t) {\\n    if (t < 1.0) {\\n        return mix(value0, value1, t);\\n    } else if (t < 2.0) {\\n        return mix(value1, value2, t - 1.0);\\n    } else {\\n        return mix(value2, value3, t - 2.0);\\n    }\\n}\\n\"},{path:434}],265:[function(t,e,r){\"use strict\";function n(t,e){this.message=(t?t+\": \":\"\")+i.apply(i,Array.prototype.slice.call(arguments,2)),null!==e&&void 0!==e&&e.__line__&&(this.line=e.__line__)}var i=t(\"util\").format;e.exports=n},{util:504}],266:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1;e<arguments.length;e++){var r=arguments[e];for(var n in r)t[n]=r[n]}return t}},{}],267:[function(t,e,r){\"use strict\";e.exports=function(t){return t instanceof Number?\"number\":t instanceof String?\"string\":t instanceof Boolean?\"boolean\":Array.isArray(t)?\"array\":null===t?\"null\":typeof t}},{}],268:[function(t,e,r){\"use strict\";e.exports=function(t){return t instanceof Number||t instanceof String||t instanceof Boolean?t.valueOf():t}},{}],269:[function(t,e,r){\"use strict\";var n=t(\"../error/validation_error\"),i=t(\"../util/get_type\"),a=t(\"../util/extend\");e.exports=function(e){var 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this.paintVertexArrays)t.push(this.paintVertexArrays[e].arrayBuffer)}},{\"../util/util\":403}],290:[function(t,e,r){\"use strict\";function n(t){if(this.zoom=t.zoom,this.overscaling=t.overscaling,this.layer=t.layer,this.childLayers=t.childLayers,this.type=this.layer.type,this.features=[],this.id=this.layer.id,this.index=t.index,this.sourceLayer=this.layer.sourceLayer,this.sourceLayerIndex=t.sourceLayerIndex,this.minZoom=this.layer.minzoom,this.maxZoom=this.layer.maxzoom,this.paintAttributes=i(this),t.arrays){var e=this.programInterfaces;this.bufferGroups=c.mapObject(t.arrays,function(r,n){var i=e[n],a=t.paintVertexArrayTypes[n];return r.map(function(t){return new u(t,{layoutVertexArrayType:i.layoutVertexArrayType.serialize(),elementArrayType:i.elementArrayType&&i.elementArrayType.serialize(),elementArrayType2:i.elementArrayType2&&i.elementArrayType2.serialize(),paintVertexArrayTypes:a})})})}}function i(t){var e={};for(var r in t.programInterfaces){for(var n=e[r]={},i=0;i<t.childLayers.length;i++){var s=t.childLayers[i];n[s.id]={attributes:[],uniforms:[],defines:[],vertexPragmas:{define:{},initialize:{}},fragmentPragmas:{define:{},initialize:{}}}}var l=t.programInterfaces[r];if(l.paintAttributes)for(var u=\"{precision}\",h=\"{type}\",d=0;d<l.paintAttributes.length;d++){var p=l.paintAttributes[d];p.multiplier=p.multiplier||1;for(var g=0;g<t.childLayers.length;g++){var m=t.childLayers[g],v=n[m.id],y=p.name;f(\"a_\"===p.name.slice(0,2));var x,b=p.name.slice(2);if(v.fragmentPragmas.initialize[b]=\"\",m.isPaintValueFeatureConstant(p.paintProperty))v.uniforms.push(p),v.fragmentPragmas.define[b]=v.vertexPragmas.define[b]=[\"uniform\",u,h,y].join(\" \")+\";\",v.fragmentPragmas.initialize[b]=v.vertexPragmas.initialize[b]=[u,h,b,\"=\",y].join(\" \")+\";\\n\";else if(m.isPaintValueZoomConstant(p.paintProperty)){v.attributes.push(c.extend({},p,{name:y})),x=[\"varying\",u,h,b].join(\" \")+\";\\n\";var _=[v.fragmentPragmas.define[b],\"attribute\",u,h,y].join(\" \")+\";\\n\";v.fragmentPragmas.define[b]=x,v.vertexPragmas.define[b]=x+_,v.vertexPragmas.initialize[b]=[b,\"=\",y,\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\"}else{for(var w=\"u_\"+y.slice(2)+\"_t\",M=m.getPaintValueStopZoomLevels(p.paintProperty),A=0;A<M.length&&M[A]<t.zoom;)A++;for(var k=Math.max(0,Math.min(M.length-4,A-2)),T=[],E=0;E<4;E++)T.push(M[Math.min(k+E,M.length-1)]);x=[\"varying\",u,h,b].join(\" \")+\";\\n\",v.vertexPragmas.define[b]=x+[\"uniform\",\"lowp\",\"float\",w].join(\" \")+\";\\n\",v.fragmentPragmas.define[b]=x,v.uniforms.push(c.extend({},p,{name:w,getValue:o(p,k),components:1}));var S=p.components;if(1===S)v.attributes.push(c.extend({},p,{getValue:a(p,T),isFunction:!0,components:4*S})),v.vertexPragmas.define[b]+=[\"attribute\",u,\"vec4\",y].join(\" \")+\";\\n\",v.vertexPragmas.initialize[b]=[b,\"=\",\"evaluate_zoom_function_1(\"+y+\", \"+w+\")\",\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\";else{for(var L=[],z=0;z<4;z++)L.push(y+z),v.attributes.push(c.extend({},p,{getValue:a(p,[T[z]]),isFunction:!0,name:y+z})),v.vertexPragmas.define[b]+=[\"attribute\",u,h,y+z].join(\" \")+\";\\n\";v.vertexPragmas.initialize[b]=[b,\" = \",\"evaluate_zoom_function_4(\"+L.join(\", \")+\", \"+w+\")\",\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\"}}}}}return e}function a(t,e){return function(r,n,i){if(1===e.length)return t.getValue(r,c.extend({},n,{zoom:e[0]}),i);for(var a=[],o=0;o<e.length;o++){var s=e[o];a.push(t.getValue(r,c.extend({},n,{zoom:s}),i)[0])}return a}}function o(t,e){return function(r,n){var i=r.getPaintInterpolationT(t.paintProperty,n.zoom);return[Math.max(0,Math.min(4,i-e))]}}var s=t(\"feature-filter\"),l=t(\"./array_group\"),u=t(\"./buffer_group\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"assert\");e.exports=n,n.create=function(e){var r={fill:t(\"./bucket/fill_bucket\"),line:t(\"./bucket/line_bucket\"),circle:t(\"./bucket/circle_bucket\"),symbol:t(\"./bucket/symbol_bucket\")};return new r[e.layer.type](e)},n.EXTENT=8192,n.prototype.populateArrays=function(){this.createArrays(),this.recalculateStyleLayers();for(var t=0;t<this.features.length;t++)this.addFeature(this.features[t]);this.trimArrays()},n.prototype.prepareArrayGroup=function(t,e){var r=this.arrayGroups[t],n=r.length&&r[r.length-1];return n&&n.hasCapacityFor(e)||(n=new l({layoutVertexArrayType:this.programInterfaces[t].layoutVertexArrayType,elementArrayType:this.programInterfaces[t].elementArrayType,elementArrayType2:this.programInterfaces[t].elementArrayType2,paintVertexArrayTypes:this.paintVertexArrayTypes[t]}),n.index=r.length,r.push(n)),n},n.prototype.createArrays=function(){this.arrayGroups={},this.paintVertexArrayTypes={};for(var t in this.programInterfaces){this.arrayGroups[t]=[];var e=this.paintVertexArrayTypes[t]={},r=this.paintAttributes[t];for(var i in r)e[i]=new n.VertexArrayType(r[i].attributes)}},n.prototype.destroy=function(t){for(var e in this.bufferGroups)for(var r=this.bufferGroups[e],n=0;n<r.length;n++)r[n].destroy(t)},n.prototype.trimArrays=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)e[r].trim()},n.prototype.isEmpty=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)if(!e[r].isEmpty())return!1;return!0},n.prototype.getTransferables=function(t){for(var e in this.arrayGroups)for(var r=this.arrayGroups[e],n=0;n<r.length;n++)r[n].getTransferables(t)},n.prototype.setUniforms=function(t,e,r,n,i){for(var a=this.paintAttributes[e][n.id].uniforms,o=0;o<a.length;o++){var s=a[o],l=r[s.name];t[\"uniform\"+s.components+\"fv\"](l,s.getValue(n,i))}},n.prototype.serialize=function(){return{layerId:this.layer.id,zoom:this.zoom,arrays:c.mapObject(this.arrayGroups,function(t){return t.map(function(t){return t.serialize()})}),paintVertexArrayTypes:c.mapObject(this.paintVertexArrayTypes,function(t){return c.mapObject(t,function(t){return t.serialize()})}),childLayerIds:this.childLayers.map(function(t){return t.id})}},n.prototype.createFilter=function(){this.filter||(this.filter=s(this.layer.filter))};var d={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};n.prototype.recalculateStyleLayers=function(){for(var t=0;t<this.childLayers.length;t++)this.childLayers[t].recalculate(this.zoom,d)},n.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a=0;a<this.childLayers.length;a++)for(var o=this.childLayers[a],s=this.arrayGroups[t],l=n.index;l<s.length;l++){var u=s[l],c=u.layoutVertexArray.length,h=u.paintVertexArrays[o.id];h.resize(c);for(var f=this.paintAttributes[t][o.id].attributes,d=0;d<f.length;d++)for(var p=f[d],g=p.getValue(o,e,r),m=p.multiplier||1,v=p.components||1,y=l===n.index?i:0,x=y;x<c;x++)for(var b=h.get(x),_=0;_<v;_++){var w=v>1?p.name+_:p.name;b[w]=g[_]*m}}},n.VertexArrayType=function(t){return new h({members:t,alignment:4})},n.ElementArrayType=function(t){return new h({members:[{type:\"Uint16\",name:\"vertices\",components:t||3}]})}},{\"../util/struct_array\":401,\"../util/util\":403,\"./array_group\":289,\"./bucket/circle_bucket\":291,\"./bucket/fill_bucket\":292,\"./bucket/line_bucket\":293,\"./bucket/symbol_bucket\":294,\"./buffer_group\":296,assert:34,\"feature-filter\":105}],291:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addCircleVertex=function(t,e,r,n,i){return t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)},n.prototype.programInterfaces={circle:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType,paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"circle-color\",e,r)},multiplier:255,paintProperty:\"circle-color\"},{name:\"a_radius\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-radius\",e,r)]},multiplier:10,paintProperty:\"circle-radius\"},{name:\"a_blur\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-blur\",e,r)]},multiplier:10,paintProperty:\"circle-blur\"},{name:\"a_opacity\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-opacity\",e,r)]},multiplier:255,paintProperty:\"circle-opacity\"}]}},n.prototype.addFeature=function(t){for(var e={zoom:this.zoom},r=o(t),n=this.prepareArrayGroup(\"circle\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)for(var l=0;l<r[a].length;l++){var u=r[a][l].x,c=r[a][l].y;if(!(u<0||u>=s||c<0||c>=s)){var h=this.prepareArrayGroup(\"circle\",4),f=h.layoutVertexArray,d=this.addCircleVertex(f,u,c,-1,-1);this.addCircleVertex(f,u,c,1,-1),this.addCircleVertex(f,u,c,1,1),this.addCircleVertex(f,u,c,-1,1),h.elementArray.emplaceBack(d,d+1,d+2),h.elementArray.emplaceBack(d,d+3,d+2)}}this.populatePaintArrays(\"circle\",e,t.properties,n,i)}},{\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298}],292:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=t(\"earcut\"),l=t(\"../../util/classify_rings\"),u=500;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.programInterfaces={fill:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType(1),elementArrayType2:new i.ElementArrayType(2),paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-color\",e,r)},multiplier:255,paintProperty:\"fill-color\"},{name:\"a_outline_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-outline-color\",e,r)},multiplier:255,paintProperty:\"fill-outline-color\"},{name:\"a_opacity\",components:1,type:\"Uint8\",getValue:function(t,e,r){return[t.getPaintValue(\"fill-opacity\",e,r)]},multiplier:255,paintProperty:\"fill-opacity\"}]}},n.prototype.addFeature=function(t){for(var e=o(t),r=l(e,u),n=this.prepareArrayGroup(\"fill\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)this.addPolygon(r[a]);this.populatePaintArrays(\"fill\",{zoom:this.zoom},t.properties,n,i)},n.prototype.addPolygon=function(t){for(var e=0,r=0;r<t.length;r++)e+=t[r].length;for(var n=this.prepareArrayGroup(\"fill\",e),i=[],a=[],o=n.layoutVertexArray.length,l=0;l<t.length;l++){var u=t[l];l>0&&a.push(i.length/2);for(var c=0;c<u.length;c++){var h=u[c],f=n.layoutVertexArray.emplaceBack(h.x,h.y);c>=1&&n.elementArray2.emplaceBack(f-1,f),i.push(h.x),i.push(h.y)}}for(var d=s(i,a),p=0;p<d.length;p++)n.elementArray.emplaceBack(d[p]+o)}},{\"../../util/classify_rings\":391,\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298,earcut:99}],293:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT,l=63,u=Math.cos(37.5*(Math.PI/180)),c=15,h=15,f=.5,d=Math.pow(2,h-1)/f;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addLineVertex=function(t,e,r,n,i,a,o){return t.emplaceBack(e.x<<1|n,e.y<<1|i,Math.round(l*r.x)+128,Math.round(l*r.y)+128,(0===a?0:a<0?-1:1)+1|(o*f&63)<<2,o*f>>6)},n.prototype.programInterfaces={line:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),elementArrayType:new i.ElementArrayType}},n.prototype.addFeature=function(t){for(var e=o(t,h),r=0;r<e.length;r++)this.addLine(e[r],this.layer.layout[\"line-join\"],this.layer.layout[\"line-cap\"],this.layer.layout[\"line-miter-limit\"],this.layer.layout[\"line-round-limit\"])},n.prototype.addLine=function(t,e,r,n,i){for(var a=t.length;a>2&&t[a-1].equals(t[a-2]);)a--;if(!(t.length<2)){\"bevel\"===e&&(n=1.05);var o=c*(s/(512*this.overscaling)),l=t[0],h=t[a-1],f=l.equals(h);if(this.prepareArrayGroup(\"line\",10*a),2!==a||!f){this.distance=0;var d,p,g,m,v,y,x,b=r,_=f?\"butt\":r,w=!0;this.e1=this.e2=this.e3=-1,f&&(d=t[a-2],v=l.sub(d)._unit()._perp());for(var M=0;M<a;M++)if(g=f&&M===a-1?t[1]:t[M+1],!g||!t[M].equals(g)){v&&(m=v),d&&(p=d),d=t[M],v=g?g.sub(d)._unit()._perp():m,m=m||v;var A=m.add(v)._unit(),k=A.x*v.x+A.y*v.y,T=1/k,E=k<u&&p&&g;if(E&&M>0){var S=d.dist(p);if(S>2*o){var L=d.sub(d.sub(p)._mult(o/S)._round());this.distance+=L.dist(p),this.addCurrentVertex(L,this.distance,m.mult(1),0,0,!1),p=L}}var z=p&&g,C=z?e:g?b:_;if(z&&\"round\"===C&&(T<i?C=\"miter\":T<=2&&(C=\"fakeround\")),\"miter\"===C&&T>n&&(C=\"bevel\"),\"bevel\"===C&&(T>2&&(C=\"flipbevel\"),T<n&&(C=\"miter\")),p&&(this.distance+=d.dist(p)),\"miter\"===C)A._mult(T),this.addCurrentVertex(d,this.distance,A,0,0,!1);else if(\"flipbevel\"===C){if(T>100)A=v.clone();else{var I=m.x*v.y-m.y*v.x>0?-1:1,P=T*m.add(v).mag()/m.sub(v).mag();A._perp()._mult(P*I)}this.addCurrentVertex(d,this.distance,A,0,0,!1),this.addCurrentVertex(d,this.distance,A.mult(-1),0,0,!1)}else if(\"bevel\"===C||\"fakeround\"===C){var D=m.x*v.y-m.y*v.x>0,R=-Math.sqrt(T*T-1);if(D?(x=0,y=R):(y=0,x=R),w||this.addCurrentVertex(d,this.distance,m,y,x,!1),\"fakeround\"===C){for(var O,F=Math.floor(8*(.5-(k-.5))),j=0;j<F;j++)O=v.mult((j+1)/(F+1))._add(m)._unit(),this.addPieSliceVertex(d,this.distance,O,D);this.addPieSliceVertex(d,this.distance,A,D);for(var N=F-1;N>=0;N--)O=m.mult((N+1)/(F+1))._add(v)._unit(),this.addPieSliceVertex(d,this.distance,O,D)}g&&this.addCurrentVertex(d,this.distance,v,-y,-x,!1)}else\"butt\"===C?(w||this.addCurrentVertex(d,this.distance,m,0,0,!1),g&&this.addCurrentVertex(d,this.distance,v,0,0,!1)):\"square\"===C?(w||(this.addCurrentVertex(d,this.distance,m,1,1,!1),this.e1=this.e2=-1),g&&this.addCurrentVertex(d,this.distance,v,-1,-1,!1)):\"round\"===C&&(w||(this.addCurrentVertex(d,this.distance,m,0,0,!1),this.addCurrentVertex(d,this.distance,m,1,1,!0),this.e1=this.e2=-1),g&&(this.addCurrentVertex(d,this.distance,v,-1,-1,!0),this.addCurrentVertex(d,this.distance,v,0,0,!1)));if(E&&M<a-1){var B=d.dist(g);if(B>2*o){var U=d.add(g.sub(d)._mult(o/B)._round());this.distance+=U.dist(d),this.addCurrentVertex(U,this.distance,v.mult(1),0,0,!1),d=U}}w=!1}}}},n.prototype.addCurrentVertex=function(t,e,r,n,i,a){var o,s=a?1:0,l=this.arrayGroups.line[this.arrayGroups.line.length-1],u=l.layoutVertexArray,c=l.elementArray;o=r.clone(),n&&o._sub(r.perp()._mult(n)),this.e3=this.addLineVertex(u,t,o,s,0,n,e),this.e1>=0&&this.e2>=0&&c.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,o=r.mult(-1),i&&o._sub(r.perp()._mult(i)),this.e3=this.addLineVertex(u,t,o,s,1,-i,e),this.e1>=0&&this.e2>=0&&c.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,e>d/2&&(this.distance=0,this.addCurrentVertex(t,this.distance,r,n,i,a))},n.prototype.addPieSliceVertex=function(t,e,r,n){var i=n?1:0;r=r.mult(n?-1:1);var a=this.arrayGroups.line[this.arrayGroups.line.length-1],o=a.layoutVertexArray,s=a.elementArray;this.e3=this.addLineVertex(o,t,r,0,i,0,e),this.e1>=0&&this.e2>=0&&s.emplaceBack(this.e1,this.e2,this.e3),n?this.e2=this.e3:this.e1=this.e3}},{\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298}],294:[function(t,e,r){\"use strict\";function n(t){o.apply(this,arguments),this.showCollisionBoxes=t.showCollisionBoxes,this.overscaling=t.overscaling,this.collisionBoxArray=t.collisionBoxArray,this.symbolQuadsArray=t.symbolQuadsArray,this.symbolInstancesArray=t.symbolInstancesArray,this.sdfIcons=t.sdfIcons,this.iconsNeedLinear=t.iconsNeedLinear,this.adjustedTextSize=t.adjustedTextSize,this.adjustedIconSize=t.adjustedIconSize,this.fontstack=t.fontstack}function i(t,e,r,n,i,a,o,s,l,u,c){return t.emplaceBack(e,r,Math.round(64*n),Math.round(64*i),a/4,o/4,10*(u||0),c,10*(s||0),10*Math.min(l||25,25))}var a=t(\"point-geometry\"),o=t(\"../bucket\"),s=t(\"../../symbol/anchor\"),l=t(\"../../symbol/get_anchors\"),u=t(\"../../util/token\"),c=t(\"../../symbol/quads\"),h=t(\"../../symbol/shaping\"),f=t(\"../../symbol/resolve_text\"),d=t(\"../../symbol/mergelines\"),p=t(\"../../symbol/clip_line\"),g=t(\"../../util/util\"),m=t(\"../load_geometry\"),v=t(\"../../symbol/collision_feature\"),y=h.shapeText,x=h.shapeIcon,b=c.getGlyphQuads,_=c.getIconQuads,w=o.EXTENT;e.exports=n,n.MAX_QUADS=65535,n.prototype=g.inherit(o,{}),n.prototype.serialize=function(){var t=o.prototype.serialize.apply(this);return t.sdfIcons=this.sdfIcons,t.iconsNeedLinear=this.iconsNeedLinear,t.adjustedTextSize=this.adjustedTextSize,t.adjustedIconSize=this.adjustedIconSize,t.fontstack=this.fontstack,t};var M=new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_offset\",components:2,type:\"Int16\"},{name:\"a_texture_pos\",components:2,type:\"Uint16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),A=new o.ElementArrayType;n.prototype.addCollisionBoxVertex=function(t,e,r,n,i){return t.emplaceBack(e.x,e.y,Math.round(r.x),Math.round(r.y),10*n,10*i)},n.prototype.programInterfaces={glyph:{layoutVertexArrayType:M,elementArrayType:A},icon:{layoutVertexArrayType:M,elementArrayType:A},collisionBox:{layoutVertexArrayType:new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_extrude\",components:2,type:\"Int16\"},{name:\"a_data\",components:2,type:\"Uint8\"}])}},n.prototype.populateArrays=function(t,e,r){var n={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};this.adjustedTextMaxSize=this.layer.getLayoutValue(\"text-size\",{zoom:18,zoomHistory:n}),this.adjustedTextSize=this.layer.getLayoutValue(\"text-size\",{zoom:this.zoom+1,zoomHistory:n}),this.adjustedIconMaxSize=this.layer.getLayoutValue(\"icon-size\",{zoom:18,zoomHistory:n}),this.adjustedIconSize=this.layer.getLayoutValue(\"icon-size\",{zoom:this.zoom+1,zoomHistory:n});var i=512*this.overscaling;this.tilePixelRatio=w/i,this.compareText={},this.iconsNeedLinear=!1,this.symbolInstancesStartIndex=this.symbolInstancesArray.length;var a=this.layer.layout,o=this.features,s=this.textFeatures,l=.5,c=.5;switch(a[\"text-anchor\"]){case\"right\":case\"top-right\":case\"bottom-right\":l=1;break;case\"left\":case\"top-left\":case\"bottom-left\":l=0}switch(a[\"text-anchor\"]){case\"bottom\":case\"bottom-right\":case\"bottom-left\":c=1;break;case\"top\":case\"top-right\":case\"top-left\":c=0}for(var h=\"right\"===a[\"text-justify\"]?1:\"left\"===a[\"text-justify\"]?0:.5,f=24,p=a[\"text-line-height\"]*f,v=\"line\"!==a[\"symbol-placement\"]?a[\"text-max-width\"]*f:0,b=a[\"text-letter-spacing\"]*f,_=[a[\"text-offset\"][0]*f,a[\"text-offset\"][1]*f],M=this.fontstack=a[\"text-font\"].join(\",\"),A=[],k=0;k<o.length;k++)A.push(m(o[k]));if(\"line\"===a[\"symbol-placement\"]){var T=d(o,s,A);A=T.geometries,o=T.features,s=T.textFeatures}for(var E,S,L=0;L<o.length;L++)if(A[L]){if(E=s[L]?y(s[L],e[M],v,p,l,c,h,b,_):null,a[\"icon-image\"]){var z=u(o[L].properties,a[\"icon-image\"]),C=r[z];S=x(C,a),C&&(void 0===this.sdfIcons?this.sdfIcons=C.sdf:this.sdfIcons!==C.sdf&&g.warnOnce(\"Style sheet warning: Cannot mix SDF and non-SDF icons in one buffer\"),1!==C.pixelRatio?this.iconsNeedLinear=!0:0===a[\"icon-rotate\"]&&this.layer.isLayoutValueFeatureConstant(\"icon-rotate\")||(this.iconsNeedLinear=!0))}else S=null;(E||S)&&this.addFeature(A[L],E,S,o[L])}this.symbolInstancesEndIndex=this.symbolInstancesArray.length,this.placeFeatures(t,this.showCollisionBoxes),this.trimArrays()},n.prototype.addFeature=function(t,e,r,n){var i=this.layer.layout,a=24,o=this.adjustedTextSize/a,u=void 0!==this.adjustedTextMaxSize?this.adjustedTextMaxSize:this.adjustedTextSize,c=this.tilePixelRatio*o,h=this.tilePixelRatio*u/a,f=this.tilePixelRatio*this.adjustedIconSize,d=this.tilePixelRatio*i[\"symbol-spacing\"],g=i[\"symbol-avoid-edges\"],m=i[\"text-padding\"]*this.tilePixelRatio,v=i[\"icon-padding\"]*this.tilePixelRatio,y=i[\"text-max-angle\"]/180*Math.PI,x=\"map\"===i[\"text-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],b=\"map\"===i[\"icon-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],_=i[\"text-allow-overlap\"]||i[\"icon-allow-overlap\"]||i[\"text-ignore-placement\"]||i[\"icon-ignore-placement\"],M=\"line\"===i[\"symbol-placement\"],A=d/2;M&&(t=p(t,0,0,w,w));for(var k=0;k<t.length;k++){var T,E=t[k];T=M?l(E,d,y,e,r,a,h,this.overscaling,w):[new s(E[0].x,E[0].y,0)];for(var S=0,L=T.length;S<L;S++){var z=T[S];if(!(e&&M&&this.anchorIsTooClose(e.text,A,z))){var C=!(z.x<0||z.x>w||z.y<0||z.y>w);if(!g||C){var I=C||_;this.addSymbolInstance(z,E,e,r,this.layer,I,this.symbolInstancesArray.length,this.collisionBoxArray,n.index,this.sourceLayerIndex,this.index,c,m,x,f,v,b,{zoom:this.zoom},n.properties)}}}}},n.prototype.anchorIsTooClose=function(t,e,r){var n=this.compareText;if(t in n){for(var i=n[t],a=i.length-1;a>=0;a--)if(r.dist(i[a])<e)return!0}else n[t]=[];return n[t].push(r),!1},n.prototype.placeFeatures=function(t,e){this.recalculateStyleLayers(),this.createArrays();var r=this.layer.layout,n=t.maxScale,i=\"map\"===r[\"text-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"],a=\"map\"===r[\"icon-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"],o=r[\"text-allow-overlap\"]||r[\"icon-allow-overlap\"]||r[\"text-ignore-placement\"]||r[\"icon-ignore-placement\"];if(o){var s=this.symbolInstancesArray.toArray(this.symbolInstancesStartIndex,this.symbolInstancesEndIndex),l=t.angle,u=Math.sin(l),c=Math.cos(l);this.sortedSymbolInstances=s.sort(function(t,e){var r=u*t.anchorPointX+c*t.anchorPointY|0,n=u*e.anchorPointX+c*e.anchorPointY|0;return r-n||e.index-t.index})}for(var h=this.symbolInstancesStartIndex;h<this.symbolInstancesEndIndex;h++){var f=this.sortedSymbolInstances?this.sortedSymbolInstances[h-this.symbolInstancesStartIndex]:this.symbolInstancesArray.get(h),d={boxStartIndex:f.textBoxStartIndex,boxEndIndex:f.textBoxEndIndex},p={boxStartIndex:f.iconBoxStartIndex,boxEndIndex:f.iconBoxEndIndex},g=!(f.textBoxStartIndex===f.textBoxEndIndex),m=!(f.iconBoxStartIndex===f.iconBoxEndIndex),v=r[\"text-optional\"]||!g,y=r[\"icon-optional\"]||!m,x=g?t.placeCollisionFeature(d,r[\"text-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale,b=m?t.placeCollisionFeature(p,r[\"icon-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale;v||y?!y&&x?x=Math.max(b,x):!v&&b&&(b=Math.max(b,x)):b=x=Math.max(b,x),g&&(t.insertCollisionFeature(d,x,r[\"text-ignore-placement\"]),x<=n&&this.addSymbols(\"glyph\",f.glyphQuadStartIndex,f.glyphQuadEndIndex,x,r[\"text-keep-upright\"],i,t.angle)),m&&(t.insertCollisionFeature(p,b,r[\"icon-ignore-placement\"]),b<=n&&this.addSymbols(\"icon\",f.iconQuadStartIndex,f.iconQuadEndIndex,b,r[\"icon-keep-upright\"],a,t.angle))}e&&this.addToDebugBuffers(t)},n.prototype.addSymbols=function(t,e,r,n,a,o,s){for(var l=this.prepareArrayGroup(t,4*(r-e)),u=l.elementArray,c=l.layoutVertexArray,h=this.zoom,f=Math.max(Math.log(n)/Math.LN2+h,0),d=e;d<r;d++){var p=this.symbolQuadsArray.get(d).SymbolQuad,g=(p.anchorAngle+s+Math.PI)%(2*Math.PI);if(!(a&&o&&(g<=Math.PI/2||g>3*Math.PI/2))){var m=p.tl,v=p.tr,y=p.bl,x=p.br,b=p.tex,_=p.anchorPoint,w=Math.max(h+Math.log(p.minScale)/Math.LN2,f),M=Math.min(h+Math.log(p.maxScale)/Math.LN2,25);if(!(M<=w)){w===f&&(w=0);var A=Math.round(p.glyphAngle/(2*Math.PI)*256),k=i(c,_.x,_.y,m.x,m.y,b.x,b.y,w,M,f,A);i(c,_.x,_.y,v.x,v.y,b.x+b.w,b.y,w,M,f,A),i(c,_.x,_.y,y.x,y.y,b.x,b.y+b.h,w,M,f,A),i(c,_.x,_.y,x.x,x.y,b.x+b.w,b.y+b.h,w,M,f,A),u.emplaceBack(k,k+1,k+2),u.emplaceBack(k+1,k+2,k+3)}}}},n.prototype.updateIcons=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"icon-image\"];if(e)for(var r=0;r<this.features.length;r++){var n=u(this.features[r].properties,e);n&&(t[n]=!0)}},n.prototype.updateFont=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"text-font\"],r=t[e]=t[e]||{};this.textFeatures=f(this.features,this.layer.layout,r)},n.prototype.addToDebugBuffers=function(t){for(var e=this.prepareArrayGroup(\"collisionBox\",0),r=e.layoutVertexArray,n=-t.angle,i=t.yStretch,o=this.symbolInstancesStartIndex;o<this.symbolInstancesEndIndex;o++){var s=this.symbolInstancesArray.get(o);s.textCollisionFeature={boxStartIndex:s.textBoxStartIndex,boxEndIndex:s.textBoxEndIndex},s.iconCollisionFeature={boxStartIndex:s.iconBoxStartIndex,boxEndIndex:s.iconBoxEndIndex};for(var l=0;l<2;l++){var u=s[0===l?\"textCollisionFeature\":\"iconCollisionFeature\"];if(u)for(var c=u.boxStartIndex;c<u.boxEndIndex;c++){var h=this.collisionBoxArray.get(c),f=h.anchorPoint,d=new a(h.x1,h.y1*i)._rotate(n),p=new a(h.x2,h.y1*i)._rotate(n),g=new a(h.x1,h.y2*i)._rotate(n),m=new a(h.x2,h.y2*i)._rotate(n),v=Math.max(0,Math.min(25,this.zoom+Math.log(h.maxScale)/Math.LN2)),y=Math.max(0,Math.min(25,this.zoom+Math.log(h.placementScale)/Math.LN2));this.addCollisionBoxVertex(r,f,d,v,y),this.addCollisionBoxVertex(r,f,p,v,y),this.addCollisionBoxVertex(r,f,p,v,y),this.addCollisionBoxVertex(r,f,m,v,y),this.addCollisionBoxVertex(r,f,m,v,y),this.addCollisionBoxVertex(r,f,g,v,y),this.addCollisionBoxVertex(r,f,g,v,y),this.addCollisionBoxVertex(r,f,d,v,y)}}}},n.prototype.addSymbolInstance=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,m,y,x,w,M){var A,k,T,E,S,L,z,C;if(r&&(z=o?b(t,r,f,e,a,p):[],S=new v(l,e,t,u,c,h,r,f,d,p,!1)),A=this.symbolQuadsArray.length,z&&z.length)for(var I=0;I<z.length;I++)this.addSymbolQuad(z[I]);k=this.symbolQuadsArray.length;var P=S?S.boxStartIndex:this.collisionBoxArray.length,D=S?S.boxEndIndex:this.collisionBoxArray.length;i&&(C=o?_(t,i,m,e,a,x,r,w,M):[],L=new v(l,e,t,u,c,h,i,m,y,x,!0)),T=this.symbolQuadsArray.length,C&&1===C.length&&this.addSymbolQuad(C[0]),E=this.symbolQuadsArray.length;var R=L?L.boxStartIndex:this.collisionBoxArray.length,O=L?L.boxEndIndex:this.collisionBoxArray.length;return E>n.MAX_QUADS&&g.warnOnce(\"Too many symbols being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),k>n.MAX_QUADS&&g.warnOnce(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),this.symbolInstancesArray.emplaceBack(P,D,R,O,A,k,T,E,t.x,t.y,s)},n.prototype.addSymbolQuad=function(t){return this.symbolQuadsArray.emplaceBack(t.anchorPoint.x,t.anchorPoint.y,t.tl.x,t.tl.y,t.tr.x,t.tr.y,t.bl.x,t.bl.y,t.br.x,t.br.y,t.tex.h,t.tex.w,t.tex.x,t.tex.y,t.anchorAngle,t.glyphAngle,t.maxScale,t.minScale)}},{\"../../symbol/anchor\":352,\"../../symbol/clip_line\":354,\"../../symbol/collision_feature\":356,\"../../symbol/get_anchors\":358,\"../../symbol/mergelines\":361,\"../../symbol/quads\":362,\"../../symbol/resolve_text\":363,\"../../symbol/shaping\":364,\"../../util/token\":402,\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298,\"point-geometry\":442}],295:[function(t,e,r){\"use strict\";function n(t,e,r){this.arrayBuffer=t.arrayBuffer,\n",
+       "this.length=t.length,this.attributes=e.members,this.itemSize=e.bytesPerElement,this.type=r,this.arrayType=e}e.exports=n,n.prototype.bind=function(t){var e=t[this.type];this.buffer?t.bindBuffer(e,this.buffer):(this.buffer=t.createBuffer(),t.bindBuffer(e,this.buffer),t.bufferData(e,this.arrayBuffer,t.STATIC_DRAW),this.arrayBuffer=null)};var i={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\"};n.prototype.setVertexAttribPointers=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],a=e[n.name];void 0!==a&&t.vertexAttribPointer(a,n.components,t[i[n.type]],!1,this.arrayType.bytesPerElement,n.offset)}},n.prototype.destroy=function(t){this.buffer&&t.deleteBuffer(this.buffer)},n.BufferType={VERTEX:\"ARRAY_BUFFER\",ELEMENT:\"ELEMENT_ARRAY_BUFFER\"}},{}],296:[function(t,e,r){\"use strict\";function n(t,e){this.layoutVertexBuffer=new a(t.layoutVertexArray,e.layoutVertexArrayType,a.BufferType.VERTEX),t.elementArray&&(this.elementBuffer=new a(t.elementArray,e.elementArrayType,a.BufferType.ELEMENT));var r,n=this.vaos={};t.elementArray2&&(this.elementBuffer2=new a(t.elementArray2,e.elementArrayType2,a.BufferType.ELEMENT),r=this.secondVaos={}),this.paintVertexBuffers=i.mapObject(t.paintVertexArrays,function(i,s){return n[s]=new o,t.elementArray2&&(r[s]=new o),new a(i,e.paintVertexArrayTypes[s],a.BufferType.VERTEX)})}var i=t(\"../util/util\"),a=t(\"./buffer\"),o=t(\"../render/vertex_array_object\");e.exports=n,n.prototype.destroy=function(t){this.layoutVertexBuffer.destroy(t),this.elementBuffer&&this.elementBuffer.destroy(t),this.elementBuffer2&&this.elementBuffer2.destroy(t);for(var e in this.paintVertexBuffers)this.paintVertexBuffers[e].destroy(t);for(var r in this.vaos)this.vaos[r].destroy(t);for(var n in this.secondVaos)this.secondVaos[n].destroy(t)}},{\"../render/vertex_array_object\":318,\"../util/util\":403,\"./buffer\":295}],297:[function(t,e,r){\"use strict\";function n(t,e,r){if(t.grid){var n=t,i=e;t=n.coord,e=n.overscaling,this.grid=new p(n.grid),this.featureIndexArray=new A(n.featureIndexArray),this.rawTileData=i,this.bucketLayerIDs=n.bucketLayerIDs}else this.grid=new p(h,16,0),this.featureIndexArray=new A;this.coord=t,this.overscaling=e,this.x=t.x,this.y=t.y,this.z=t.z-Math.log(e)/Math.LN2,this.setCollisionTile(r)}function i(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function a(t,e){return e-t}function o(t){return t[\"line-gap-width\"]>0?t[\"line-gap-width\"]+2*t[\"line-width\"]:t[\"line-width\"]}function s(t,e,r,n,i){if(!e[0]&&!e[1])return t;e=u.convert(e),\"viewport\"===r&&e._rotate(-n);for(var a=[],o=0;o<t.length;o++){for(var s=t[o],l=[],c=0;c<s.length;c++)l.push(s[c].sub(e._mult(i)));a.push(l)}return a}function l(t,e){for(var r=[],n=new u(0,0),i=0;i<t.length;i++){for(var a=t[i],o=[],s=0;s<a.length;s++){var l=a[s-1],c=a[s],h=a[s+1],f=0===s?n:c.sub(l)._unit()._perp(),d=s===a.length-1?n:h.sub(c)._unit()._perp(),p=f._add(d)._unit(),g=p.x*d.x+p.y*d.y;p._mult(1/g),o.push(p._mult(e)._add(c))}r.push(o)}return r}var u=t(\"point-geometry\"),c=t(\"./load_geometry\"),h=t(\"./bucket\").EXTENT,f=t(\"feature-filter\"),d=t(\"../util/struct_array\"),p=t(\"grid-index\"),g=t(\"../util/dictionary_coder\"),m=t(\"vector-tile\"),v=t(\"pbf\"),y=t(\"../util/vectortile_to_geojson\"),x=t(\"../util/util\").arraysIntersect,b=t(\"../util/intersection_tests\"),_=b.multiPolygonIntersectsBufferedMultiPoint,w=b.multiPolygonIntersectsMultiPolygon,M=b.multiPolygonIntersectsBufferedMultiLine,A=new d({members:[{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"}]});e.exports=n,n.prototype.insert=function(t,e,r,n){var i=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(e,r,n);for(var a=c(t),o=0;o<a.length;o++){for(var s=a[o],l=[1/0,1/0,-(1/0),-(1/0)],u=0;u<s.length;u++){var h=s[u];l[0]=Math.min(l[0],h.x),l[1]=Math.min(l[1],h.y),l[2]=Math.max(l[2],h.x),l[3]=Math.max(l[3],h.y)}this.grid.insert(i,l[0],l[1],l[2],l[3])}},n.prototype.setCollisionTile=function(t){this.collisionTile=t},n.prototype.serialize=function(){var t={coord:this.coord,overscaling:this.overscaling,grid:this.grid.toArrayBuffer(),featureIndexArray:this.featureIndexArray.serialize(),bucketLayerIDs:this.bucketLayerIDs};return{data:t,transferables:[t.grid,t.featureIndexArray.arrayBuffer]}},n.prototype.query=function(t,e){this.vtLayers||(this.vtLayers=new m.VectorTile(new v(new Uint8Array(this.rawTileData))).layers,this.sourceLayerCoder=new g(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"]));var r={},n=t.params||{},s=h/t.tileSize/t.scale,l=f(n.filter),c=0;for(var d in e){var p=e[d],y=p.paint,x=0;\"line\"===p.type?x=o(y)/2+Math.abs(y[\"line-offset\"])+i(y[\"line-translate\"]):\"fill\"===p.type?x=i(y[\"fill-translate\"]):\"circle\"===p.type&&(x=y[\"circle-radius\"]+i(y[\"circle-translate\"])),c=Math.max(c,x*s)}for(var b=t.queryGeometry.map(function(t){return t.map(function(t){return new u(t.x,t.y)})}),_=1/0,w=1/0,M=-(1/0),A=-(1/0),k=0;k<b.length;k++)for(var T=b[k],E=0;E<T.length;E++){var S=T[E];_=Math.min(_,S.x),w=Math.min(w,S.y),M=Math.max(M,S.x),A=Math.max(A,S.y)}var L=this.grid.query(_-c,w-c,M+c,A+c);L.sort(a),this.filterMatching(r,L,this.featureIndexArray,b,l,n.layers,e,t.bearing,s);var z=this.collisionTile.queryRenderedSymbols(_,w,M,A,t.scale);return z.sort(),this.filterMatching(r,z,this.collisionTile.collisionBoxArray,b,l,n.layers,e,t.bearing,s),r},n.prototype.filterMatching=function(t,e,r,n,i,a,u,h,f){for(var d,p=0;p<e.length;p++){var g=e[p];if(g!==d){d=g;var m=r.get(g),v=this.bucketLayerIDs[m.bucketIndex];if(!a||x(a,v)){var b=this.sourceLayerCoder.decode(m.sourceLayerIndex),A=this.vtLayers[b],k=A.feature(m.featureIndex);if(i(k))for(var T=null,E=0;E<v.length;E++){var S=v[E];if(!(a&&a.indexOf(S)<0)){var L=u[S];if(L){var z;if(\"symbol\"!==L.type){T||(T=c(k));var C=L.paint;if(\"line\"===L.type){z=s(n,C[\"line-translate\"],C[\"line-translate-anchor\"],h,f);var I=o(C)/2*f;if(C[\"line-offset\"]&&(T=l(T,C[\"line-offset\"]*f)),!M(z,T,I))continue}else if(\"fill\"===L.type){if(z=s(n,C[\"fill-translate\"],C[\"fill-translate-anchor\"],h,f),!w(z,T))continue}else if(\"circle\"===L.type){z=s(n,C[\"circle-translate\"],C[\"circle-translate-anchor\"],h,f);var P=C[\"circle-radius\"]*f;if(!_(z,T,P))continue}}var D=new y(k,this.z,this.x,this.y);D.layer=L.serialize({includeRefProperties:!0});var R=t[S];void 0===R&&(R=t[S]=[]),R.push(D)}}}}}}}},{\"../util/dictionary_coder\":393,\"../util/intersection_tests\":398,\"../util/struct_array\":401,\"../util/util\":403,\"../util/vectortile_to_geojson\":404,\"./bucket\":290,\"./load_geometry\":298,\"feature-filter\":105,\"grid-index\":252,pbf:436,\"point-geometry\":442,\"vector-tile\":505}],298:[function(t,e,r){\"use strict\";function n(t){return{min:-1*Math.pow(2,t-1),max:Math.pow(2,t-1)-1}}var i=t(\"../util/util\"),a=t(\"./bucket\").EXTENT,o=t(\"assert\"),s={15:n(15),16:n(16)};e.exports=function(t,e){var r=s[e||16];o(r);for(var n=a/t.extent,l=t.loadGeometry(),u=0;u<l.length;u++)for(var c=l[u],h=0;h<c.length;h++){var f=c[h];f.x=Math.round(f.x*n),f.y=Math.round(f.y*n),(f.x<r.min||f.x>r.max||f.y<r.min||f.y>r.max)&&i.warnOnce(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\")}return l}},{\"../util/util\":403,\"./bucket\":290,assert:34}],299:[function(t,e,r){\"use strict\";function n(t,e,r){this.column=t,this.row=e,this.zoom=r}e.exports=n,n.prototype={clone:function(){return new n(this.column,this.row,this.zoom)},zoomTo:function(t){return this.clone()._zoomTo(t)},sub:function(t){return this.clone()._sub(t)},_zoomTo:function(t){var e=Math.pow(2,t-this.zoom);return this.column*=e,this.row*=e,this.zoom=t,this},_sub:function(t){return t=t.zoomTo(this.zoom),this.column-=t.column,this.row-=t.row,this}}},{}],300:[function(t,e,r){\"use strict\";function n(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")}e.exports=n;var i=t(\"../util/util\").wrap;n.prototype.wrap=function(){return new n(i(this.lng,-180,180),this.lat)},n.prototype.toArray=function(){return[this.lng,this.lat]},n.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},n.convert=function(t){return t instanceof n?t:Array.isArray(t)?new n(t[0],t[1]):t}},{\"../util/util\":403}],301:[function(t,e,r){\"use strict\";function n(t,e){t&&(e?this.extend(t).extend(e):4===t.length?this.extend([t[0],t[1]]).extend([t[2],t[3]]):this.extend(t[0]).extend(t[1]))}e.exports=n;var i=t(\"./lng_lat\");n.prototype={extend:function(t){var e,r,a=this._sw,o=this._ne;if(t instanceof i)e=t,r=t;else{if(!(t instanceof n))return t?this.extend(i.convert(t)||n.convert(t)):this;if(e=t._sw,r=t._ne,!e||!r)return this}return a||o?(a.lng=Math.min(e.lng,a.lng),a.lat=Math.min(e.lat,a.lat),o.lng=Math.max(r.lng,o.lng),o.lat=Math.max(r.lat,o.lat)):(this._sw=new i(e.lng,e.lat),this._ne=new i(r.lng,r.lat)),this},getCenter:function(){return new i((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},getSouthWest:function(){return this._sw},getNorthEast:function(){return this._ne},getNorthWest:function(){return new i(this.getWest(),this.getNorth())},getSouthEast:function(){return new i(this.getEast(),this.getSouth())},getWest:function(){return this._sw.lng},getSouth:function(){return this._sw.lat},getEast:function(){return this._ne.lng},getNorth:function(){return this._ne.lat},toArray:function(){return[this._sw.toArray(),this._ne.toArray()]},toString:function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"}},n.convert=function(t){return!t||t instanceof n?t:new n(t)}},{\"./lng_lat\":300}],302:[function(t,e,r){\"use strict\";function n(t,e){this.tileSize=512,this._minZoom=t||0,this._maxZoom=e||22,this.latRange=[-85.05113,85.05113],this.width=0,this.height=0,this._center=new i(0,0),this.zoom=0,this.angle=0,this._altitude=1.5,this._pitch=0,this._unmodified=!0}var i=t(\"./lng_lat\"),a=t(\"point-geometry\"),o=t(\"./coordinate\"),s=t(\"../util/util\").wrap,l=t(\"../util/interpolate\"),u=t(\"../source/tile_coord\"),c=t(\"../data/bucket\").EXTENT,h=t(\"gl-matrix\"),f=h.vec4,d=h.mat4,p=h.mat2;e.exports=n,n.prototype={get minZoom(){return this._minZoom},set minZoom(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},get maxZoom(){return this._maxZoom},set maxZoom(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},get worldSize(){return this.tileSize*this.scale},get centerPoint(){return this.size._div(2)},get size(){return new a(this.width,this.height)},get bearing(){return-this.angle/Math.PI*180},set bearing(t){var e=-s(t,-180,180)*Math.PI/180;this.angle!==e&&(this._unmodified=!1,this.angle=e,this._calcMatrices(),this.rotationMatrix=p.create(),p.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},get pitch(){return this._pitch/Math.PI*180},set pitch(t){var e=Math.min(60,t)/180*Math.PI;this._pitch!==e&&(this._unmodified=!1,this._pitch=e,this._calcMatrices())},get altitude(){return this._altitude},set altitude(t){var e=Math.max(.75,t);this._altitude!==e&&(this._unmodified=!1,this._altitude=e,this._calcMatrices())},get zoom(){return this._zoom},set zoom(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._calcMatrices(),this._constrain())},get center(){return this._center},set center(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._calcMatrices(),this._constrain())},coveringZoomLevel:function(t){return(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize))},coveringTiles:function(t){var e=this.coveringZoomLevel(t),r=e;if(e<t.minzoom)return[];e>t.maxzoom&&(e=t.maxzoom);var n=this,i=n.locationCoordinate(n.center)._zoomTo(e),o=new a(i.column-.5,i.row-.5);return u.cover(e,[n.pointCoordinate(new a(0,0))._zoomTo(e),n.pointCoordinate(new a(n.width,0))._zoomTo(e),n.pointCoordinate(new a(n.width,n.height))._zoomTo(e),n.pointCoordinate(new a(0,n.height))._zoomTo(e)],t.reparseOverscaled?r:e).sort(function(t,e){return o.dist(t)-o.dist(e)})},resize:function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._calcMatrices(),this._constrain()},get unmodified(){return this._unmodified},zoomScale:function(t){return Math.pow(2,t)},scaleZoom:function(t){return Math.log(t)/Math.LN2},project:function(t,e){return new a(this.lngX(t.lng,e),this.latY(t.lat,e))},unproject:function(t,e){return new i(this.xLng(t.x,e),this.yLat(t.y,e))},get x(){return this.lngX(this.center.lng)},get y(){return this.latY(this.center.lat)},get point(){return new a(this.x,this.y)},lngX:function(t,e){return(180+t)*(e||this.worldSize)/360},latY:function(t,e){var r=180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360));return(180-r)*(e||this.worldSize)/360},xLng:function(t,e){return 360*t/(e||this.worldSize)-180},yLat:function(t,e){var r=180-360*t/(e||this.worldSize);return 360/Math.PI*Math.atan(Math.exp(r*Math.PI/180))-90},panBy:function(t){var e=this.centerPoint._add(t);this.center=this.pointLocation(e)},setLocationAtPoint:function(t,e){var r=this.locationCoordinate(t),n=this.pointCoordinate(e),i=this.pointCoordinate(this.centerPoint),a=n._sub(r);this._unmodified=!1,this.center=this.coordinateLocation(i._sub(a))},locationPoint:function(t){return this.coordinatePoint(this.locationCoordinate(t))},pointLocation:function(t){return this.coordinateLocation(this.pointCoordinate(t))},locationCoordinate:function(t){var e=this.zoomScale(this.tileZoom)/this.worldSize,r=i.convert(t);return new o(this.lngX(r.lng)*e,this.latY(r.lat)*e,this.tileZoom)},coordinateLocation:function(t){var e=this.zoomScale(t.zoom);return new i(this.xLng(t.column,e),this.yLat(t.row,e))},pointCoordinate:function(t){var e=0,r=[t.x,t.y,0,1],n=[t.x,t.y,1,1];f.transformMat4(r,r,this.pixelMatrixInverse),f.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],s=r[0]/i,u=n[0]/a,c=r[1]/i,h=n[1]/a,d=r[2]/i,p=n[2]/a,g=d===p?0:(e-d)/(p-d),m=this.worldSize/this.zoomScale(this.tileZoom);return new o(l(s,u,g)/m,l(c,h,g)/m,this.tileZoom)},coordinatePoint:function(t){var e=this.worldSize/this.zoomScale(t.zoom),r=[t.column*e,t.row*e,0,1];return f.transformMat4(r,r,this.pixelMatrix),new a(r[0]/r[3],r[1]/r[3])},calculatePosMatrix:function(t,e){void 0===e&&(e=1/0),t instanceof u&&(t=t.toCoordinate(e));var r=Math.min(t.zoom,e),n=this.worldSize/Math.pow(2,r),i=new Float64Array(16);return d.identity(i),d.translate(i,i,[t.column*n,t.row*n,0]),d.scale(i,i,[n/c,n/c,1]),d.multiply(i,this.projMatrix,i),new Float32Array(i)},_constrain:function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var t,e,r,n,i,o,s,l,u=this.size,c=this._unmodified;this.latRange&&(t=this.latY(this.latRange[1]),e=this.latY(this.latRange[0]),i=e-t<u.y?u.y/(e-t):0),this.lngRange&&(r=this.lngX(this.lngRange[0]),n=this.lngX(this.lngRange[1]),o=n-r<u.x?u.x/(n-r):0);var h=Math.max(o||0,i||0);if(h)return this.center=this.unproject(new a(o?(n+r)/2:this.x,i?(e+t)/2:this.y)),this.zoom+=this.scaleZoom(h),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var f=this.y,d=u.y/2;f-d<t&&(l=t+d),f+d>e&&(l=e-d)}if(this.lngRange){var p=this.x,g=u.x/2;p-g<r&&(s=r+g),p+g>n&&(s=n-g)}void 0===s&&void 0===l||(this.center=this.unproject(new a(void 0!==s?s:this.x,void 0!==l?l:this.y))),this._unmodified=c,this._constraining=!1}},_calcMatrices:function(){if(this.height){var t=Math.atan(.5/this.altitude),e=Math.sin(t)*this.altitude/Math.sin(Math.PI/2-this._pitch-t),r=Math.cos(Math.PI/2-this._pitch)*e+this.altitude,n=new Float64Array(16);if(d.perspective(n,2*Math.atan(this.height/2/this.altitude),this.width/this.height,.1,r),d.translate(n,n,[0,0,-this.altitude]),d.scale(n,n,[1,-1,1/this.height]),d.rotateX(n,n,this._pitch),d.rotateZ(n,n,this.angle),d.translate(n,n,[-this.x,-this.y,0]),this.projMatrix=n,n=d.create(),d.scale(n,n,[this.width/2,-this.height/2,1]),d.translate(n,n,[1,-1,0]),this.pixelMatrix=d.multiply(new Float64Array(16),n,this.projMatrix),n=d.invert(new Float64Array(16),this.pixelMatrix),!n)throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=n}}}},{\"../data/bucket\":290,\"../source/tile_coord\":330,\"../util/interpolate\":397,\"../util/util\":403,\"./coordinate\":299,\"./lng_lat\":300,\"gl-matrix\":161,\"point-geometry\":442}],303:[function(t,e,r){\"use strict\";var n={\" \":[16,[]],\"!\":[10,[5,21,5,7,-1,-1,5,2,4,1,5,0,6,1,5,2]],'\"':[16,[4,21,4,14,-1,-1,12,21,12,14]],\"#\":[21,[11,25,4,-7,-1,-1,17,25,10,-7,-1,-1,4,12,18,12,-1,-1,3,6,17,6]],$:[20,[8,25,8,-4,-1,-1,12,25,12,-4,-1,-1,17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],\"%\":[24,[21,21,3,0,-1,-1,8,21,10,19,10,17,9,15,7,14,5,14,3,16,3,18,4,20,6,21,8,21,10,20,13,19,16,19,19,20,21,21,-1,-1,17,7,15,6,14,4,14,2,16,0,18,0,20,1,21,3,21,5,19,7,17,7]],\"&\":[26,[23,12,23,13,22,14,21,14,20,13,19,11,17,6,15,3,13,1,11,0,7,0,5,1,4,2,3,4,3,6,4,8,5,9,12,13,13,14,14,16,14,18,13,20,11,21,9,20,8,18,8,16,9,13,11,10,16,3,18,1,20,0,22,0,23,1,23,2]],\"'\":[10,[5,19,4,20,5,21,6,20,6,18,5,16,4,15]],\"(\":[14,[11,25,9,23,7,20,5,16,4,11,4,7,5,2,7,-2,9,-5,11,-7]],\")\":[14,[3,25,5,23,7,20,9,16,10,11,10,7,9,2,7,-2,5,-5,3,-7]],\"*\":[16,[8,21,8,9,-1,-1,3,18,13,12,-1,-1,13,18,3,12]],\"+\":[26,[13,18,13,0,-1,-1,4,9,22,9]],\",\":[10,[6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"-\":[26,[4,9,22,9]],\".\":[10,[5,2,4,1,5,0,6,1,5,2]],\"/\":[22,[20,25,2,-7]],0:[20,[9,21,6,20,4,17,3,12,3,9,4,4,6,1,9,0,11,0,14,1,16,4,17,9,17,12,16,17,14,20,11,21,9,21]],1:[20,[6,17,8,18,11,21,11,0]],2:[20,[4,16,4,17,5,19,6,20,8,21,12,21,14,20,15,19,16,17,16,15,15,13,13,10,3,0,17,0]],3:[20,[5,21,16,21,10,13,13,13,15,12,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],4:[20,[13,21,3,7,18,7,-1,-1,13,21,13,0]],5:[20,[15,21,5,21,4,12,5,13,8,14,11,14,14,13,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],6:[20,[16,18,15,20,12,21,10,21,7,20,5,17,4,12,4,7,5,3,7,1,10,0,11,0,14,1,16,3,17,6,17,7,16,10,14,12,11,13,10,13,7,12,5,10,4,7]],7:[20,[17,21,7,0,-1,-1,3,21,17,21]],8:[20,[8,21,5,20,4,18,4,16,5,14,7,13,11,12,14,11,16,9,17,7,17,4,16,2,15,1,12,0,8,0,5,1,4,2,3,4,3,7,4,9,6,11,9,12,13,13,15,14,16,16,16,18,15,20,12,21,8,21]],9:[20,[16,14,15,11,13,9,10,8,9,8,6,9,4,11,3,14,3,15,4,18,6,20,9,21,10,21,13,20,15,18,16,14,16,9,15,4,13,1,10,0,8,0,5,1,4,3]],\":\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,5,2,4,1,5,0,6,1,5,2]],\";\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"<\":[24,[20,18,4,9,20,0]],\"=\":[26,[4,12,22,12,-1,-1,4,6,22,6]],\">\":[24,[4,18,20,9,4,0]],\"?\":[18,[3,16,3,17,4,19,5,20,7,21,11,21,13,20,14,19,15,17,15,15,14,13,13,12,9,10,9,7,-1,-1,9,2,8,1,9,0,10,1,9,2]],\"@\":[27,[18,13,17,15,15,16,12,16,10,15,9,14,8,11,8,8,9,6,11,5,14,5,16,6,17,8,-1,-1,12,16,10,14,9,11,9,8,10,6,11,5,-1,-1,18,16,17,8,17,6,19,5,21,5,23,7,24,10,24,12,23,15,22,17,20,19,18,20,15,21,12,21,9,20,7,19,5,17,4,15,3,12,3,9,4,6,5,4,7,2,9,1,12,0,15,0,18,1,20,2,21,3,-1,-1,19,16,18,8,18,6,19,5]],A:[18,[9,21,1,0,-1,-1,9,21,17,0,-1,-1,4,7,14,7]],B:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,-1,-1,4,11,13,11,16,10,17,9,18,7,18,4,17,2,16,1,13,0,4,0]],C:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5]],D:[21,[4,21,4,0,-1,-1,4,21,11,21,14,20,16,18,17,16,18,13,18,8,17,5,16,3,14,1,11,0,4,0]],E:[19,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11,-1,-1,4,0,17,0]],F:[18,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11]],G:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,18,8,-1,-1,13,8,18,8]],H:[22,[4,21,4,0,-1,-1,18,21,18,0,-1,-1,4,11,18,11]],I:[8,[4,21,4,0]],J:[16,[12,21,12,5,11,2,10,1,8,0,6,0,4,1,3,2,2,5,2,7]],K:[21,[4,21,4,0,-1,-1,18,21,4,7,-1,-1,9,12,18,0]],L:[17,[4,21,4,0,-1,-1,4,0,16,0]],M:[24,[4,21,4,0,-1,-1,4,21,12,0,-1,-1,20,21,12,0,-1,-1,20,21,20,0]],N:[22,[4,21,4,0,-1,-1,4,21,18,0,-1,-1,18,21,18,0]],O:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21]],P:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,14,17,12,16,11,13,10,4,10]],Q:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21,-1,-1,12,4,18,-2]],R:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,4,11,-1,-1,11,11,18,0]],S:[20,[17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],T:[16,[8,21,8,0,-1,-1,1,21,15,21]],U:[22,[4,21,4,6,5,3,7,1,10,0,12,0,15,1,17,3,18,6,18,21]],V:[18,[1,21,9,0,-1,-1,17,21,9,0]],W:[24,[2,21,7,0,-1,-1,12,21,7,0,-1,-1,12,21,17,0,-1,-1,22,21,17,0]],X:[20,[3,21,17,0,-1,-1,17,21,3,0]],Y:[18,[1,21,9,11,9,0,-1,-1,17,21,9,11]],Z:[20,[17,21,3,0,-1,-1,3,21,17,21,-1,-1,3,0,17,0]],\"[\":[14,[4,25,4,-7,-1,-1,5,25,5,-7,-1,-1,4,25,11,25,-1,-1,4,-7,11,-7]],\"\\\\\":[14,[0,21,14,-3]],\"]\":[14,[9,25,9,-7,-1,-1,10,25,10,-7,-1,-1,3,25,10,25,-1,-1,3,-7,10,-7]],\"^\":[16,[6,15,8,18,10,15,-1,-1,3,12,8,17,13,12,-1,-1,8,17,8,0]],_:[16,[0,-2,16,-2]],\"`\":[10,[6,21,5,20,4,18,4,16,5,15,6,16,5,17]],a:[19,[15,14,15,0,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],b:[19,[4,21,4,0,-1,-1,4,11,6,13,8,14,11,14,13,13,15,11,16,8,16,6,15,3,13,1,11,0,8,0,6,1,4,3]],c:[18,[15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],d:[19,[15,21,15,0,-1,-1,15,11,13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a,o,s,l,u,c,h,f,d=[];for(a=0,o=t.length;a<o;a++)if(u=n[t[a]]){for(f=null,s=0,l=u[1].length;s<l;s+=2)u[1][s]===-1&&u[1][s+1]===-1?f=null:(c=e+u[1][s]*i,h=r-u[1][s+1]*i,f&&d.push(f.x,f.y,c,h),f={x:c,y:h});e+=u[0]*i}return d}},{}],304:[function(t,e,r){\"use strict\";var n=e.exports={};n.version=t(\"../package.json\").version,n.Map=t(\"./ui/map\"),n.Control=t(\"./ui/control/control\"),n.Navigation=t(\"./ui/control/navigation\"),n.Geolocate=t(\"./ui/control/geolocate\"),n.Attribution=t(\"./ui/control/attribution\"),n.Popup=t(\"./ui/popup\"),n.Marker=t(\"./ui/marker\"),n.Style=t(\"./style/style\"),n.LngLat=t(\"./geo/lng_lat\"),n.LngLatBounds=t(\"./geo/lng_lat_bounds\"),n.Point=t(\"point-geometry\"),n.Evented=t(\"./util/evented\"),n.util=t(\"./util/util\"),n.supported=t(\"./util/browser\").supported;var i=t(\"./util/ajax\");n.util.getJSON=i.getJSON,n.util.getArrayBuffer=i.getArrayBuffer;var a=t(\"./util/config\");n.config=a,Object.defineProperty(n,\"accessToken\",{get:function(){return a.ACCESS_TOKEN},set:function(t){a.ACCESS_TOKEN=t}})},{\"../package.json\":405,\"./geo/lng_lat\":300,\"./geo/lng_lat_bounds\":301,\"./style/style\":339,\"./ui/control/attribution\":370,\"./ui/control/control\":371,\"./ui/control/geolocate\":372,\"./ui/control/navigation\":373,\"./ui/map\":382,\"./ui/marker\":383,\"./ui/popup\":384,\"./util/ajax\":386,\"./util/browser\":387,\"./util/config\":392,\"./util/evented\":395,\"./util/util\":403,\"point-geometry\":442}],305:[function(t,e,r){\"use strict\";var n=t(\"assert\");e.exports=function(t){for(var e={define:{},initialize:{}},r=0;r<t.length;r++){var i=t[r];n(\"u_\"===i.name.slice(0,2));var a=\"{precision} \"+(1===i.components?\"float\":\"vec\"+i.components);e.define[i.name.slice(2)]=\"uniform \"+a+\" \"+i.name+\";\\n\",e.initialize[i.name.slice(2)]=a+\" \"+i.name.slice(2)+\" = \"+i.name+\";\\n\"}return e}},{assert:34}],306:[function(t,e,r){\"use strict\";function n(t,e,r){var n,s=t.gl,l=t.transform,u=r.paint[\"background-color\"],c=r.paint[\"background-pattern\"],h=r.paint[\"background-opacity\"],f=c?t.spriteAtlas.getPosition(c.from,!0):null,d=c?t.spriteAtlas.getPosition(c.to,!0):null;if(t.setDepthSublayer(0),f&&d){if(t.isOpaquePass)return;n=t.useProgram(\"pattern\"),s.uniform1i(n.u_image,0),s.uniform2fv(n.u_pattern_tl_a,f.tl),s.uniform2fv(n.u_pattern_br_a,f.br),s.uniform2fv(n.u_pattern_tl_b,d.tl),s.uniform2fv(n.u_pattern_br_b,d.br),s.uniform1f(n.u_opacity,h),s.uniform1f(n.u_mix,c.t),s.uniform2fv(n.u_pattern_size_a,f.size),s.uniform2fv(n.u_pattern_size_b,d.size),s.uniform1f(n.u_scale_a,c.fromScale),s.uniform1f(n.u_scale_b,c.toScale),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),t.tileExtentPatternVAO.bind(s,n,t.tileExtentBuffer)}else{if(t.isOpaquePass!==(1===u[3]))return;var p=a([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]);n=t.useProgram(\"fill\",[],p,p),s.uniform4fv(n.u_color,u),s.uniform1f(n.u_opacity,h),t.tileExtentVAO.bind(s,n,t.tileExtentBuffer)}s.disable(s.STENCIL_TEST);for(var g=l.coveringTiles({tileSize:o}),m=0;m<g.length;m++){var v=g[m];if(f&&d){var y={coord:v,tileSize:o};s.uniform1f(n.u_tile_units_to_pixels,1/i(y,1,t.transform.tileZoom));var x=y.tileSize*Math.pow(2,t.transform.tileZoom-y.coord.z),b=x*(y.coord.x+v.w*Math.pow(2,y.coord.z)),_=x*y.coord.y;s.uniform2f(n.u_pixel_coord_upper,b>>16,_>>16),s.uniform2f(n.u_pixel_coord_lower,65535&b,65535&_)}s.uniformMatrix4fv(n.u_matrix,!1,t.transform.calculatePosMatrix(v)),s.drawArrays(s.TRIANGLE_STRIP,0,t.tileExtentBuffer.length)}s.stencilMask(0),s.stencilFunc(s.EQUAL,128,128)}var i=t(\"../source/pixels_to_tile_units\"),a=t(\"./create_uniform_pragmas\"),o=512;e.exports=n},{\"../source/pixels_to_tile_units\":324,\"./create_uniform_pragmas\":305}],307:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;t.setDepthSublayer(0),t.depthMask(!1),a.disable(a.STENCIL_TEST);for(var o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.circle;if(c){var h=u.paintAttributes.circle[r.id],f=t.useProgram(\"circle\",h.defines,h.vertexPragmas,h.fragmentPragmas);\"map\"===r.paint[\"circle-pitch-scale\"]?(a.uniform1i(f.u_scale_with_map,!0),a.uniform2f(f.u_extrude_scale,t.transform.pixelsToGLUnits[0]*t.transform.altitude,t.transform.pixelsToGLUnits[1]*t.transform.altitude)):(a.uniform1i(f.u_scale_with_map,!1),a.uniform2fv(f.u_extrude_scale,t.transform.pixelsToGLUnits)),a.uniform1f(f.u_devicepixelratio,i.devicePixelRatio),a.uniformMatrix4fv(f.u_matrix,!1,t.translatePosMatrix(s.posMatrix,l,r.paint[\"circle-translate\"],r.paint[\"circle-translate-anchor\"])),u.setUniforms(a,\"circle\",f,r,{zoom:t.transform.zoom});for(var d=0;d<c.length;d++){var p=c[d];p.vaos[r.id].bind(a,f,p.layoutVertexBuffer,p.elementBuffer,p.paintVertexBuffers[r.id]),a.drawElements(a.TRIANGLES,3*p.elementBuffer.length,a.UNSIGNED_SHORT,0)}}}}}}var i=t(\"../util/browser\");e.exports=n},{\"../util/browser\":387}],308:[function(t,e,r){\"use strict\";function n(t,e,r,n){var i=t.gl;i.enable(i.STENCIL_TEST);for(var a=t.useProgram(\"collisionbox\"),o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.collisionBox;if(c&&c.length){var h=c[0];0!==h.layoutVertexBuffer.length&&(i.uniformMatrix4fv(a.u_matrix,!1,s.posMatrix),t.enableTileClippingMask(s),t.lineWidth(1),i.uniform1f(a.u_scale,Math.pow(2,t.transform.zoom-l.coord.z)),i.uniform1f(a.u_zoom,10*t.transform.zoom),i.uniform1f(a.u_maxzoom,10*(l.coord.z+1)),h.vaos[r.id].bind(i,a,h.layoutVertexBuffer),i.drawArrays(i.LINES,0,h.layoutVertexBuffer.length))}}}}e.exports=n},{}],309:[function(t,e,r){\"use strict\";function n(t,e,r){if(!t.isOpaquePass&&t.options.debug)for(var n=0;n<r.length;n++)i(t,e,r[n])}function i(t,e,r){var n=t.gl;n.disable(n.STENCIL_TEST),t.lineWidth(1*o.devicePixelRatio);var i=r.posMatrix,h=t.useProgram(\"debug\");n.uniformMatrix4fv(h.u_matrix,!1,i),n.uniform4f(h.u_color,1,0,0,1),t.debugVAO.bind(n,h,t.debugBuffer),n.drawArrays(n.LINE_STRIP,0,t.debugBuffer.length);for(var f=a(r.toString(),50,200,5),d=new t.PosArray,p=0;p<f.length;p+=2)d.emplaceBack(f[p],f[p+1]);var g=new u(d.serialize(),t.PosArray.serialize(),u.BufferType.VERTEX),m=new c;m.bind(n,h,g),n.uniform4f(h.u_color,1,1,1,1);for(var v=e.getTile(r).tileSize,y=l/(Math.pow(2,t.transform.zoom-r.z)*v),x=[[-1,-1],[-1,1],[1,-1],[1,1]],b=0;b<x.length;b++){var _=x[b];n.uniformMatrix4fv(h.u_matrix,!1,s.translate([],i,[y*_[0],y*_[1],0])),n.drawArrays(n.LINES,0,g.length)}n.uniform4f(h.u_color,0,0,0,1),n.uniformMatrix4fv(h.u_matrix,!1,i),n.drawArrays(n.LINES,0,g.length)}var a=t(\"../lib/debugtext\"),o=t(\"../util/browser\"),s=t(\"gl-matrix\").mat4,l=t(\"../data/bucket\").EXTENT,u=t(\"../data/buffer\"),c=t(\"./vertex_array_object\");e.exports=n},{\"../data/bucket\":290,\"../data/buffer\":295,\"../lib/debugtext\":303,\"../util/browser\":387,\"./vertex_array_object\":318,\"gl-matrix\":161}],310:[function(t,e,r){\"use strict\";function n(t,e,r,n){var o=t.gl;o.enable(o.STENCIL_TEST);var s;if(s=!r.paint[\"fill-pattern\"]&&(r.isPaintValueFeatureConstant(\"fill-color\")&&r.isPaintValueFeatureConstant(\"fill-opacity\")&&1===r.paint[\"fill-color\"][3]&&1===r.paint[\"fill-opacity\"]),t.isOpaquePass===s){t.setDepthSublayer(1);for(var l=0;l<n.length;l++)i(t,e,r,n[l])}if(!t.isOpaquePass&&r.paint[\"fill-antialias\"]){t.lineWidth(2),t.depthMask(!1);var u=r.getPaintProperty(\"fill-outline-color\");(u||!r.paint[\"fill-pattern\"])&&u?t.setDepthSublayer(2):t.setDepthSublayer(0);for(var c=0;c<n.length;c++)a(t,e,r,n[c])}}function i(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s=a.bufferGroups.fill;if(s){var l,u=t.gl,c=r.paint[\"fill-pattern\"];if(c)l=t.useProgram(\"pattern\"),o(c,r.paint[\"fill-opacity\"],i,n,t,l),u.activeTexture(u.TEXTURE0),t.spriteAtlas.bind(u,!0);else{var h=a.paintAttributes.fill[r.id];l=t.useProgram(\"fill\",h.defines,h.vertexPragmas,h.fragmentPragmas),a.setUniforms(u,\"fill\",l,r,{zoom:t.transform.zoom})}u.uniformMatrix4fv(l.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),t.enableTileClippingMask(n);for(var f=0;f<s.length;f++){var d=s[f];d.vaos[r.id].bind(u,l,d.layoutVertexBuffer,d.elementBuffer,d.paintVertexBuffers[r.id]),u.drawElements(u.TRIANGLES,d.elementBuffer.length,u.UNSIGNED_SHORT,0)}}}}function a(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s,l=t.gl,u=a.bufferGroups.fill,c=r.paint[\"fill-pattern\"],h=r.paint[\"fill-opacity\"],f=r.getPaintProperty(\"fill-outline-color\");if(c&&!f)s=t.useProgram(\"outlinepattern\"),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight);else{var d=a.paintAttributes.fill[r.id];s=t.useProgram(\"outline\",d.defines,d.vertexPragmas,d.fragmentPragmas),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight),l.uniform1f(s.u_opacity,h),a.setUniforms(l,\"fill\",s,r,{zoom:t.transform.zoom})}l.uniformMatrix4fv(s.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),\n",
+       "c&&o(c,h,i,n,t,s),t.enableTileClippingMask(n);for(var p=0;p<u.length;p++){var g=u[p];g.secondVaos[r.id].bind(l,s,g.layoutVertexBuffer,g.elementBuffer2,g.paintVertexBuffers[r.id]),l.drawElements(l.LINES,2*g.elementBuffer2.length,l.UNSIGNED_SHORT,0)}}}function o(t,e,r,n,i,a){var o=i.gl,l=i.spriteAtlas.getPosition(t.from,!0),u=i.spriteAtlas.getPosition(t.to,!0);if(l&&u){o.uniform1i(a.u_image,0),o.uniform2fv(a.u_pattern_tl_a,l.tl),o.uniform2fv(a.u_pattern_br_a,l.br),o.uniform2fv(a.u_pattern_tl_b,u.tl),o.uniform2fv(a.u_pattern_br_b,u.br),o.uniform1f(a.u_opacity,e),o.uniform1f(a.u_mix,t.t),o.uniform1f(a.u_tile_units_to_pixels,1/s(r,1,i.transform.tileZoom)),o.uniform2fv(a.u_pattern_size_a,l.size),o.uniform2fv(a.u_pattern_size_b,u.size),o.uniform1f(a.u_scale_a,t.fromScale),o.uniform1f(a.u_scale_b,t.toScale);var c=r.tileSize*Math.pow(2,i.transform.tileZoom-r.coord.z),h=c*(r.coord.x+n.w*Math.pow(2,r.coord.z)),f=c*r.coord.y;o.uniform2f(a.u_pixel_coord_upper,h>>16,f>>16),o.uniform2f(a.u_pixel_coord_lower,65535&h,65535&f),o.activeTexture(o.TEXTURE0),i.spriteAtlas.bind(o,!0)}}var s=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":324}],311:[function(t,e,r){\"use strict\";var n=t(\"../util/browser\"),i=t(\"gl-matrix\").mat2,a=t(\"../source/pixels_to_tile_units\");e.exports=function(t,e,r,o){if(!t.isOpaquePass){t.setDepthSublayer(0),t.depthMask(!1);var s=t.gl;if(s.enable(s.STENCIL_TEST),!(r.paint[\"line-width\"]<=0)){var l=1/n.devicePixelRatio,u=r.paint[\"line-blur\"]+l,c=r.paint[\"line-color\"],h=t.transform,f=i.create();i.scale(f,f,[1,Math.cos(h._pitch)]),i.rotate(f,f,t.transform.angle);var d,p,g,m,v,y=Math.sqrt(h.height*h.height/4*(1+h.altitude*h.altitude)),x=h.height/2*Math.tan(h._pitch),b=(y+x)/y-1,_=r.paint[\"line-dasharray\"],w=r.paint[\"line-pattern\"];if(_)d=t.useProgram(\"linesdfpattern\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),p=t.lineAtlas.getDash(_.from,\"round\"===r.layout[\"line-cap\"]),g=t.lineAtlas.getDash(_.to,\"round\"===r.layout[\"line-cap\"]),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.lineAtlas.bind(s),s.uniform1f(d.u_tex_y_a,p.y),s.uniform1f(d.u_tex_y_b,g.y),s.uniform1f(d.u_mix,_.t),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f);else if(w){if(m=t.spriteAtlas.getPosition(w.from,!0),v=t.spriteAtlas.getPosition(w.to,!0),!m||!v)return;d=t.useProgram(\"linepattern\"),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform2fv(d.u_pattern_tl_a,m.tl),s.uniform2fv(d.u_pattern_br_a,m.br),s.uniform2fv(d.u_pattern_tl_b,v.tl),s.uniform2fv(d.u_pattern_br_b,v.br),s.uniform1f(d.u_fade,w.t),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f)}else d=t.useProgram(\"line\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]);for(var M=0;M<o.length;M++){var A=o[M],k=e.getTile(A),T=k.getBucket(r);if(T){var E=T.bufferGroups.line;if(E){t.enableTileClippingMask(A);var S=t.translatePosMatrix(A.posMatrix,k,r.paint[\"line-translate\"],r.paint[\"line-translate-anchor\"]);s.uniformMatrix4fv(d.u_matrix,!1,S);var L=1/a(k,1,t.transform.zoom);if(_){var z=p.width*_.fromScale,C=g.width*_.toScale,I=[1/a(k,z,t.transform.tileZoom),-p.height/2],P=[1/a(k,C,t.transform.tileZoom),-g.height/2],D=t.lineAtlas.width/(256*Math.min(z,C)*n.devicePixelRatio)/2;s.uniform1f(d.u_ratio,L),s.uniform2fv(d.u_patternscale_a,I),s.uniform2fv(d.u_patternscale_b,P),s.uniform1f(d.u_sdfgamma,D)}else w?(s.uniform1f(d.u_ratio,L),s.uniform2fv(d.u_pattern_size_a,[a(k,m.size[0]*w.fromScale,t.transform.tileZoom),v.size[1]]),s.uniform2fv(d.u_pattern_size_b,[a(k,v.size[0]*w.toScale,t.transform.tileZoom),v.size[1]])):s.uniform1f(d.u_ratio,L);for(var R=0;R<E.length;R++){var O=E[R];O.vaos[r.id].bind(s,d,O.layoutVertexBuffer,O.elementBuffer),s.drawElements(s.TRIANGLES,3*O.elementBuffer.length,s.UNSIGNED_SHORT,0)}}}}}}}},{\"../source/pixels_to_tile_units\":324,\"../util/browser\":387,\"gl-matrix\":161}],312:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;a.enable(a.DEPTH_TEST),t.depthMask(!0),a.depthFunc(a.LESS);for(var o=n.length&&n[0].z,s=0;s<n.length;s++){var l=n[s];t.setDepthSublayer(l.z-o),i(t,e,r,l)}a.depthFunc(a.LEQUAL)}}function i(t,e,r,n){var i=t.gl;i.disable(i.STENCIL_TEST);var u=e.getTile(n),c=t.transform.calculatePosMatrix(n,e.maxzoom),h=t.useProgram(\"raster\");i.uniformMatrix4fv(h.u_matrix,!1,c),i.uniform1f(h.u_brightness_low,r.paint[\"raster-brightness-min\"]),i.uniform1f(h.u_brightness_high,r.paint[\"raster-brightness-max\"]),i.uniform1f(h.u_saturation_factor,s(r.paint[\"raster-saturation\"])),i.uniform1f(h.u_contrast_factor,o(r.paint[\"raster-contrast\"])),i.uniform3fv(h.u_spin_weights,a(r.paint[\"raster-hue-rotate\"]));var f,d,p=u.source&&u.source.findLoadedParent(n,0,{}),g=l(u,p,r,t.transform);i.activeTexture(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,u.texture),i.activeTexture(i.TEXTURE1),p?(i.bindTexture(i.TEXTURE_2D,p.texture),f=Math.pow(2,p.coord.z-u.coord.z),d=[u.coord.x*f%1,u.coord.y*f%1]):(i.bindTexture(i.TEXTURE_2D,u.texture),g[1]=0),i.uniform2fv(h.u_tl_parent,d||[0,0]),i.uniform1f(h.u_scale_parent,f||1),i.uniform1f(h.u_buffer_scale,1),i.uniform1f(h.u_opacity0,g[0]),i.uniform1f(h.u_opacity1,g[1]),i.uniform1i(h.u_image0,0),i.uniform1i(h.u_image1,1);var m=u.boundsBuffer||t.rasterBoundsBuffer,v=u.boundsVAO||t.rasterBoundsVAO;v.bind(i,h,m),i.drawArrays(i.TRIANGLE_STRIP,0,m.length)}function a(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}function o(t){return t>0?1/(1-t):1+t}function s(t){return t>0?1-1/(1.001-t):-t}function l(t,e,r,n){var i=[1,0],a=r.paint[\"raster-fade-duration\"];if(t.source&&a>0){var o=(new Date).getTime(),s=(o-t.timeAdded)/a,l=e?(o-e.timeAdded)/a:-1,c=n.coveringZoomLevel(t.source),h=!!e&&Math.abs(e.coord.z-c)>Math.abs(t.coord.z-c);!e||h?(i[0]=u.clamp(s,0,1),i[1]=1-i[0]):(i[0]=u.clamp(1-l,0,1),i[1]=1-i[0])}var f=r.paint[\"raster-opacity\"];return i[0]*=f,i[1]*=f,i}var u=t(\"../util/util\"),c=t(\"../util/struct_array\");e.exports=n,n.RasterBoundsArray=new c({members:[{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]})},{\"../util/struct_array\":401,\"../util/util\":403}],313:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=!(r.layout[\"text-allow-overlap\"]||r.layout[\"icon-allow-overlap\"]||r.layout[\"text-ignore-placement\"]||r.layout[\"icon-ignore-placement\"]),o=t.gl;a?o.disable(o.STENCIL_TEST):o.enable(o.STENCIL_TEST),t.setDepthSublayer(0),t.depthMask(!1),o.disable(o.DEPTH_TEST),i(t,e,r,n,!1,r.paint[\"icon-translate\"],r.paint[\"icon-translate-anchor\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-size\"],r.paint[\"icon-halo-width\"],r.paint[\"icon-halo-color\"],r.paint[\"icon-halo-blur\"],r.paint[\"icon-opacity\"],r.paint[\"icon-color\"]),i(t,e,r,n,!0,r.paint[\"text-translate\"],r.paint[\"text-translate-anchor\"],r.layout[\"text-rotation-alignment\"],r.layout[\"text-pitch-alignment\"],r.layout[\"text-size\"],r.paint[\"text-halo-width\"],r.paint[\"text-halo-color\"],r.paint[\"text-halo-blur\"],r.paint[\"text-opacity\"],r.paint[\"text-color\"]),o.enable(o.DEPTH_TEST),e.map.showCollisionBoxes&&s(t,e,r,n)}}function i(t,e,r,n,i,o,s,l,u,c,h,f,d,p,g){for(var m=0;m<n.length;m++){var v=e.getTile(n[m]),y=v.getBucket(r);if(y){var x=y.bufferGroups,b=i?x.glyph:x.icon;b.length&&(t.enableTileClippingMask(n[m]),a(t,r,n[m].posMatrix,v,y,b,i,i||y.sdfIcons,!i&&y.iconsNeedLinear,i?y.adjustedTextSize:y.adjustedIconSize,y.fontstack,o,s,l,u,c,h,f,d,p,g))}}}function a(t,e,r,n,i,a,s,u,c,h,f,d,p,g,m,v,y,x,b,_,w){var M,A,k,T=t.gl,E=t.transform,S=\"map\"===g,L=\"map\"===m,z=s?24:1,C=v/z;if(L?(A=l(n,1,t.transform.zoom)*C,k=1/Math.cos(E._pitch),M=[A,A]):(A=t.transform.altitude*C,k=1,M=[E.pixelsToGLUnits[0]*A,E.pixelsToGLUnits[1]*A]),s||t.style.sprite.loaded()){var I=t.useProgram(u?\"sdf\":\"icon\");if(T.uniformMatrix4fv(I.u_matrix,!1,t.translatePosMatrix(r,n,d,p)),T.uniform1i(I.u_rotate_with_map,S),T.uniform1i(I.u_pitch_with_map,L),T.uniform2fv(I.u_extrude_scale,M),T.activeTexture(T.TEXTURE0),T.uniform1i(I.u_texture,0),s){var P=f&&t.glyphSource.getGlyphAtlas(f);if(!P)return;P.updateTexture(T),T.uniform2f(I.u_texsize,P.width/4,P.height/4)}else{var D=t.options.rotating||t.options.zooming,R=1!==C||o.devicePixelRatio!==t.spriteAtlas.pixelRatio||c,O=L||t.transform.pitch;t.spriteAtlas.bind(T,u||D||R||O),T.uniform2f(I.u_texsize,t.spriteAtlas.width/4,t.spriteAtlas.height/4)}var F=Math.log(v/h)/Math.LN2||0;T.uniform1f(I.u_zoom,10*(t.transform.zoom-F)),T.activeTexture(T.TEXTURE1),t.frameHistory.bind(T),T.uniform1i(I.u_fadetexture,1);var j;if(u){var N=8,B=1.19,U=6,V=.105*z/v/o.devicePixelRatio;if(y){T.uniform1f(I.u_gamma,(b*B/C/N+V)*k),T.uniform4fv(I.u_color,x),T.uniform1f(I.u_opacity,_),T.uniform1f(I.u_buffer,(U-y/C)/N);for(var q=0;q<a.length;q++)j=a[q],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}T.uniform1f(I.u_gamma,V*k),T.uniform4fv(I.u_color,w),T.uniform1f(I.u_opacity,_),T.uniform1f(I.u_buffer,.75),T.uniform1f(I.u_pitch,E.pitch/360*2*Math.PI),T.uniform1f(I.u_bearing,E.bearing/360*2*Math.PI),T.uniform1f(I.u_aspect_ratio,E.width/E.height);for(var H=0;H<a.length;H++)j=a[H],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}else{T.uniform1f(I.u_opacity,_);for(var G=0;G<a.length;G++)j=a[G],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}}}var o=t(\"../util/browser\"),s=t(\"./draw_collision_debug\"),l=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":324,\"../util/browser\":387,\"./draw_collision_debug\":308}],314:[function(t,e,r){\"use strict\";function n(){this.changeTimes=new Float64Array(256),this.changeOpacities=new Uint8Array(256),this.opacities=new Uint8ClampedArray(256),this.array=new Uint8Array(this.opacities.buffer),this.fadeDuration=300,this.previousZoom=0,this.firstFrame=!0}e.exports=n,n.prototype.record=function(t){var e=Date.now();this.firstFrame&&(e=0,this.firstFrame=!1),t=Math.floor(10*t);var r;if(t<this.previousZoom)for(r=t+1;r<=this.previousZoom;r++)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];else for(r=t;r>this.previousZoom;r--)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];for(r=0;r<256;r++){var n=e-this.changeTimes[r],i=n/this.fadeDuration*255;r<=t?this.opacities[r]=this.changeOpacities[r]+i:this.opacities[r]=this.changeOpacities[r]-i}this.changed=!0,this.previousZoom=t},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.changed&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,256,1,t.ALPHA,t.UNSIGNED_BYTE,this.array),this.changed=!1)):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,256,1,0,t.ALPHA,t.UNSIGNED_BYTE,this.array))}},{}],315:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.nextRow=0,this.bytes=4,this.data=new Uint8Array(this.width*this.height*this.bytes),this.positions={}}var i=t(\"../util/util\");e.exports=n,n.prototype.setSprite=function(t){this.sprite=t},n.prototype.getDash=function(t,e){var r=t.join(\",\")+e;return this.positions[r]||(this.positions[r]=this.addDash(t,e)),this.positions[r]},n.prototype.addDash=function(t,e){var r=e?7:0,n=2*r+1,a=128;if(this.nextRow+n>this.height)return i.warnOnce(\"LineAtlas out of space\"),null;for(var o=0,s=0;s<t.length;s++)o+=t[s];for(var l=this.width/o,u=l/2,c=t.length%2===1,h=-r;h<=r;h++)for(var f=this.nextRow+r+h,d=this.width*f,p=c?-t[t.length-1]:0,g=t[0],m=1,v=0;v<this.width;v++){for(;g<v/l;)p=g,g+=t[m],c&&m===t.length-1&&(g+=t[0]),m++;var y,x=Math.abs(v-p*l),b=Math.abs(v-g*l),_=Math.min(x,b),w=m%2===1;if(e){var M=r?h/r*(u+1):0;if(w){var A=u-Math.abs(M);y=Math.sqrt(_*_+A*A)}else y=u-Math.sqrt(_*_+M*M)}else y=(w?1:-1)*_;this.data[3+4*(d+v)]=Math.max(0,Math.min(255,y+a))}var k={y:(this.nextRow+r+.5)/this.height,height:2*r/this.height,width:o};return this.nextRow+=n,this.dirty=!0,k},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.RGBA,t.UNSIGNED_BYTE,this.data))):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width,this.height,0,t.RGBA,t.UNSIGNED_BYTE,this.data))}},{\"../util/util\":403}],316:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.transform=e,this.reusableTextures={},this.preFbos={},this.frameHistory=new o,this.setup(),this.numSublayers=s.maxUnderzooming+s.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.lineWidthRange=t.getParameter(t.ALIASED_LINE_WIDTH_RANGE)}var i=t(\"../util/browser\"),a=t(\"gl-matrix\").mat4,o=t(\"./frame_history\"),s=t(\"../source/source_cache\"),l=t(\"../data/bucket\").EXTENT,u=t(\"../source/pixels_to_tile_units\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"../data/buffer\"),d=t(\"./vertex_array_object\"),p=t(\"./draw_raster\").RasterBoundsArray,g=t(\"./create_uniform_pragmas\");e.exports=n,c.extend(n.prototype,t(\"./painter/use_program\")),n.prototype.resize=function(t,e){var r=this.gl;this.width=t*i.devicePixelRatio,this.height=e*i.devicePixelRatio,r.viewport(0,0,this.width,this.height)},n.prototype.setup=function(){var t=this.gl;t.verbose=!0,t.enable(t.BLEND),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.enable(t.STENCIL_TEST),t.enable(t.DEPTH_TEST),t.depthFunc(t.LEQUAL),this._depthMask=!1,t.depthMask(!1);var e=this.PosArray=new h({members:[{name:\"a_pos\",type:\"Int16\",components:2}]}),r=new e;r.emplaceBack(0,0),r.emplaceBack(l,0),r.emplaceBack(0,l),r.emplaceBack(l,l),this.tileExtentBuffer=new f(r.serialize(),e.serialize(),f.BufferType.VERTEX),this.tileExtentVAO=new d,this.tileExtentPatternVAO=new d;var n=new e;n.emplaceBack(0,0),n.emplaceBack(l,0),n.emplaceBack(l,l),n.emplaceBack(0,l),n.emplaceBack(0,0),this.debugBuffer=new f(n.serialize(),e.serialize(),f.BufferType.VERTEX),this.debugVAO=new d;var i=new p;i.emplaceBack(0,0,0,0),i.emplaceBack(l,0,32767,0),i.emplaceBack(0,l,0,32767),i.emplaceBack(l,l,32767,32767),this.rasterBoundsBuffer=new f(i.serialize(),p.serialize(),f.BufferType.VERTEX),this.rasterBoundsVAO=new d},n.prototype.clearColor=function(){var t=this.gl;t.clearColor(0,0,0,0),t.clear(t.COLOR_BUFFER_BIT)},n.prototype.clearStencil=function(){var t=this.gl;t.clearStencil(0),t.stencilMask(255),t.clear(t.STENCIL_BUFFER_BIT)},n.prototype.clearDepth=function(){var t=this.gl;t.clearDepth(1),this.depthMask(!0),t.clear(t.DEPTH_BUFFER_BIT)},n.prototype._renderTileClippingMasks=function(t){var e=this.gl;e.colorMask(!1,!1,!1,!1),this.depthMask(!1),e.disable(e.DEPTH_TEST),e.enable(e.STENCIL_TEST),e.stencilMask(248),e.stencilOp(e.KEEP,e.KEEP,e.REPLACE);var r=1;this._tileClippingMaskIDs={};for(var n=0;n<t.length;n++){var i=t[n],a=this._tileClippingMaskIDs[i.id]=r++<<3;e.stencilFunc(e.ALWAYS,a,248);var o=g([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]),s=this.useProgram(\"fill\",[],o,o);e.uniformMatrix4fv(s.u_matrix,!1,i.posMatrix),this.tileExtentVAO.bind(e,s,this.tileExtentBuffer),e.drawArrays(e.TRIANGLE_STRIP,0,this.tileExtentBuffer.length)}e.stencilMask(0),e.colorMask(!0,!0,!0,!0),this.depthMask(!0),e.enable(e.DEPTH_TEST)},n.prototype.enableTileClippingMask=function(t){var e=this.gl;e.stencilFunc(e.EQUAL,this._tileClippingMaskIDs[t.id],248)},n.prototype.prepareBuffers=function(){},n.prototype.bindDefaultFramebuffer=function(){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,null)};var m={symbol:t(\"./draw_symbol\"),circle:t(\"./draw_circle\"),line:t(\"./draw_line\"),fill:t(\"./draw_fill\"),raster:t(\"./draw_raster\"),background:t(\"./draw_background\"),debug:t(\"./draw_debug\")};n.prototype.render=function(t,e){this.style=t,this.options=e,this.lineAtlas=t.lineAtlas,this.spriteAtlas=t.spriteAtlas,this.spriteAtlas.setSprite(t.sprite),this.glyphSource=t.glyphSource,this.frameHistory.record(this.transform.zoom),this.prepareBuffers(),this.clearColor(),this.clearDepth(),this.showOverdrawInspector(e.showOverdrawInspector),this.depthRange=(t._order.length+2)*this.numSublayers*this.depthEpsilon,this.renderPass({isOpaquePass:!0}),this.renderPass({isOpaquePass:!1})},n.prototype.renderPass=function(t){var e=this.style._groups,r=t.isOpaquePass;this.currentLayer=r?this.style._order.length:-1;for(var n=0;n<e.length;n++){var i,a=e[r?e.length-1-n:n],o=this.style.sources[a.source],s=[];if(o){for(s=o.getVisibleCoordinates(),i=0;i<s.length;i++)s[i].posMatrix=this.transform.calculatePosMatrix(s[i],o.maxzoom);this.clearStencil(),o.prepare&&o.prepare(),o.isTileClipped&&this._renderTileClippingMasks(s)}for(r?(this._showOverdrawInspector||this.gl.disable(this.gl.BLEND),this.isOpaquePass=!0):(this.gl.enable(this.gl.BLEND),this.isOpaquePass=!1,s.reverse()),i=0;i<a.length;i++){var l=a[r?a.length-1-i:i];this.currentLayer+=r?-1:1,this.renderLayer(this,o,l,s)}o&&m.debug(this,o,s)}},n.prototype.depthMask=function(t){t!==this._depthMask&&(this._depthMask=t,this.gl.depthMask(t))},n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||n.length)&&(this.id=r.id,m[r.type](t,e,r,n))},n.prototype.setDepthSublayer=function(t){var e=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon,r=e-1+this.depthRange;this.gl.depthRange(r,e)},n.prototype.translatePosMatrix=function(t,e,r,n){if(!r[0]&&!r[1])return t;if(\"viewport\"===n){var i=Math.sin(-this.transform.angle),o=Math.cos(-this.transform.angle);r=[r[0]*o-r[1]*i,r[0]*i+r[1]*o]}var s=[u(e,r[0],this.transform.zoom),u(e,r[1],this.transform.zoom),0],l=new Float32Array(16);return a.translate(l,t,s),l},n.prototype.saveTexture=function(t){var e=this.reusableTextures[t.size];e?e.push(t):this.reusableTextures[t.size]=[t]},n.prototype.getTexture=function(t){var e=this.reusableTextures[t];return e&&e.length>0?e.pop():null},n.prototype.lineWidth=function(t){this.gl.lineWidth(c.clamp(t,this.lineWidthRange[0],this.lineWidthRange[1]))},n.prototype.showOverdrawInspector=function(t){if(t||this._showOverdrawInspector){this._showOverdrawInspector=t;var e=this.gl;if(t){e.blendFunc(e.CONSTANT_COLOR,e.ONE);var r=8,n=1/r;e.blendColor(n,n,n,0),e.clearColor(0,0,0,1),e.clear(e.COLOR_BUFFER_BIT)}else e.blendFunc(e.ONE,e.ONE_MINUS_SRC_ALPHA)}}},{\"../data/bucket\":290,\"../data/buffer\":295,\"../source/pixels_to_tile_units\":324,\"../source/source_cache\":328,\"../util/browser\":387,\"../util/struct_array\":401,\"../util/util\":403,\"./create_uniform_pragmas\":305,\"./draw_background\":306,\"./draw_circle\":307,\"./draw_debug\":309,\"./draw_fill\":310,\"./draw_line\":311,\"./draw_raster\":312,\"./draw_symbol\":313,\"./frame_history\":314,\"./painter/use_program\":317,\"./vertex_array_object\":318,\"gl-matrix\":161}],317:[function(t,e,r){\"use strict\";function n(t,e){return t.replace(/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,function(t,r,n,i,a){return e[r][a].replace(/{type}/g,i).replace(/{precision}/g,n)})}var i=t(\"assert\"),a=t(\"../../util/util\"),o=t(\"mapbox-gl-shaders\"),s=o.util;e.exports._createProgram=function(t,e,r,l){for(var u=this.gl,c=u.createProgram(),h=o[t],f=\"#define MAPBOX_GL_JS;\\n\",d=0;d<e.length;d++)f+=\"#define \"+e[d]+\";\\n\";var p=u.createShader(u.FRAGMENT_SHADER);u.shaderSource(p,n(f+h.fragmentSource,l)),u.compileShader(p),i(u.getShaderParameter(p,u.COMPILE_STATUS),u.getShaderInfoLog(p)),u.attachShader(c,p);var g=u.createShader(u.VERTEX_SHADER);u.shaderSource(g,n(f+s+h.vertexSource,r)),u.compileShader(g),i(u.getShaderParameter(g,u.COMPILE_STATUS),u.getShaderInfoLog(g)),u.attachShader(c,g),u.linkProgram(c),i(u.getProgramParameter(c,u.LINK_STATUS),u.getProgramInfoLog(c));for(var m={},v=u.getProgramParameter(c,u.ACTIVE_ATTRIBUTES),y=0;y<v;y++){var x=u.getActiveAttrib(c,y);m[x.name]=u.getAttribLocation(c,x.name)}for(var b={},_=u.getProgramParameter(c,u.ACTIVE_UNIFORMS),w=0;w<_;w++){var M=u.getActiveUniform(c,w);b[M.name]=u.getUniformLocation(c,M.name)}return a.extend({program:c,definition:h,attributes:m,numAttributes:v},m,b)},e.exports._createProgramCached=function(t,e,r,n){this.cache=this.cache||{};var i=JSON.stringify({name:t,defines:e,vertexPragmas:r,fragmentPragmas:n});return this.cache[i]||(this.cache[i]=this._createProgram(t,e,r,n)),this.cache[i]},e.exports.useProgram=function(t,e,r,n){var i=this.gl;e=e||[],this._showOverdrawInspector&&(e=e.concat(\"OVERDRAW_INSPECTOR\"));var a=this._createProgramCached(t,e,r,n),o=this.currentProgram;return o!==a&&(i.useProgram(a.program),this.currentProgram=a),a}},{\"../../util/util\":403,assert:34,\"mapbox-gl-shaders\":264}],318:[function(t,e,r){\"use strict\";function n(){this.boundProgram=null,this.boundVertexBuffer=null,this.boundVertexBuffer2=null,this.boundElementBuffer=null,this.vao=null}var i=t(\"assert\");e.exports=n,n.prototype.bind=function(t,e,r,n,i){void 0===t.extVertexArrayObject&&(t.extVertexArrayObject=t.getExtension(\"OES_vertex_array_object\"));var a=!this.vao||this.boundProgram!==e||this.boundVertexBuffer!==r||this.boundVertexBuffer2!==i||this.boundElementBuffer!==n;!t.extVertexArrayObject||a?this.freshBind(t,e,r,n,i):t.extVertexArrayObject.bindVertexArrayOES(this.vao)},n.prototype.freshBind=function(t,e,r,n,a){var o,s=e.numAttributes;if(t.extVertexArrayObject)this.vao&&this.destroy(t),this.vao=t.extVertexArrayObject.createVertexArrayOES(),t.extVertexArrayObject.bindVertexArrayOES(this.vao),o=0,this.boundProgram=e,this.boundVertexBuffer=r,this.boundVertexBuffer2=a,this.boundElementBuffer=n;else{o=t.currentNumAttributes||0;for(var l=s;l<o;l++)i(0!==l),t.disableVertexAttribArray(l)}for(var u=o;u<s;u++)t.enableVertexAttribArray(u);r.bind(t),r.setVertexAttribPointers(t,e),a&&(a.bind(t),a.setVertexAttribPointers(t,e)),n&&n.bind(t),t.currentNumAttributes=s},n.prototype.unbind=function(t){var e=t.extVertexArrayObject;e&&e.bindVertexArrayOES(null)},n.prototype.destroy=function(t){var e=t.extVertexArrayObject;e&&this.vao&&(e.deleteVertexArrayOES(this.vao),this.vao=null)}},{assert:34}],319:[function(t,e,r){\"use strict\";function n(t,e,r){e=e||{},this.id=t,this.dispatcher=r,this._data=e.data,void 0!==e.maxzoom&&(this.maxzoom=e.maxzoom),e.type&&(this.type=e.type);var n=s/this.tileSize;this.workerOptions=a.extend({source:this.id,cluster:e.cluster||!1,geojsonVtOptions:{buffer:(void 0!==e.buffer?e.buffer:128)*n,tolerance:(void 0!==e.tolerance?e.tolerance:.375)*n,extent:s,maxZoom:this.maxzoom},superclusterOptions:{maxZoom:Math.min(e.clusterMaxZoom,this.maxzoom-1)||this.maxzoom-1,extent:s,radius:(e.clusterRadius||50)*n,log:!1}},e.workerOptions),this._updateWorkerData(function(t){return t?void this.fire(\"error\",{error:t}):void this.fire(\"load\")}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"resolve-url\"),s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype=a.inherit(i,{type:\"geojson\",minzoom:0,maxzoom:18,tileSize:512,isTileClipped:!0,reparseOverscaled:!0,onAdd:function(t){this.map=t},setData:function(t){return this._data=t,this._updateWorkerData(function(t){return t?this.fire(\"error\",{error:t}):void this.fire(\"change\")}.bind(this)),this},_updateWorkerData:function(t){var e=a.extend({},this.workerOptions),r=this._data;\"string\"==typeof r?e.url=\"undefined\"!=typeof window?o(window.location.href,r):r:e.data=JSON.stringify(r),this.workerID=this.dispatcher.send(this.type+\".loadData\",e,function(e){this._loaded=!0,t(e)}.bind(this))},loadTile:function(t,e){var r=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,n={type:this.type,uid:t.uid,coord:t.coord,zoom:t.coord.z,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,overscaling:r,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID=this.dispatcher.send(\"load tile\",n,function(r,n){if(t.unloadVectorData(this.map.painter),!t.aborted)return r?e(r):(t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null))}.bind(this),this.workerID)},abortTile:function(t){t.aborted=!0},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},function(){},t.workerID)},serialize:function(){return{type:this.type,data:this._data}}})},{\"../data/bucket\":290,\"../util/evented\":395,\"../util/util\":403,\"resolve-url\":458}],320:[function(t,e,r){\"use strict\";function n(t,e,r){r&&(this.loadGeoJSON=r),h.call(this,t,e)}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"geojson-rewind\"),s=t(\"./geojson_wrapper\"),l=t(\"vt-pbf\"),u=t(\"supercluster\"),c=t(\"geojson-vt\"),h=t(\"./vector_tile_worker_source\");e.exports=n,n.prototype=i.inherit(h,{_geoJSONIndexes:{},loadVectorData:function(t,e){var r=t.source,n=t.coord;if(!this._geoJSONIndexes[r])return e(null,null);var i=this._geoJSONIndexes[r].getTile(Math.min(n.z,t.maxZoom),n.x,n.y);if(!i)return e(null,null);var a=new s(i.features);a.name=\"_geojsonTileLayer\";var o=l({layers:{_geojsonTileLayer:a}});0===o.byteOffset&&o.byteLength===o.buffer.byteLength||(o=new Uint8Array(o)),e(null,{tile:a,rawTileData:o.buffer})},loadData:function(t,e){var r=function(r,n){return r?e(r):\"object\"!=typeof n?e(new Error(\"Input data is not a valid GeoJSON object.\")):(o(n,!0),void this._indexData(n,t,function(r,n){return r?e(r):(this._geoJSONIndexes[t.source]=n,void e(null))}.bind(this)))}.bind(this);this.loadGeoJSON(t,r)},loadGeoJSON:function(t,e){if(t.url)a.getJSON(t.url,e);else{if(\"string\"!=typeof t.data)return e(new Error(\"Input data is not a valid GeoJSON object.\"));try{return e(null,JSON.parse(t.data))}catch(t){return e(new Error(\"Input data is not a valid GeoJSON object.\"))}}},_indexData:function(t,e,r){try{e.cluster?r(null,u(e.superclusterOptions).load(t.features)):r(null,c(t,e.geojsonVtOptions))}catch(t){return r(t)}}})},{\"../util/ajax\":386,\"../util/util\":403,\"./geojson_wrapper\":321,\"./vector_tile_worker_source\":332,\"geojson-rewind\":110,\"geojson-vt\":114,supercluster:485,\"vt-pbf\":511}],321:[function(t,e,r){\"use strict\";function n(t){this.features=t,this.length=t.length,this.extent=s}function i(t){if(this.type=t.type,1===t.type){this.rawGeometry=[];for(var e=0;e<t.geometry.length;e++)this.rawGeometry.push([t.geometry[e]])}else this.rawGeometry=t.geometry;this.properties=t.tags,this.extent=s}var a=t(\"point-geometry\"),o=t(\"vector-tile\").VectorTileFeature,s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype.feature=function(t){return new i(this.features[t])},i.prototype.loadGeometry=function(){var t=this.rawGeometry;this.geometry=[];for(var e=0;e<t.length;e++){for(var r=t[e],n=[],i=0;i<r.length;i++)n.push(new a(r[i][0],r[i][1]));this.geometry.push(n)}return this.geometry},i.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var t=this.geometry,e=1/0,r=-(1/0),n=1/0,i=-(1/0),a=0;a<t.length;a++)for(var o=t[a],s=0;s<o.length;s++){var l=o[s];e=Math.min(e,l.x),r=Math.max(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.y)}return[e,n,r,i]},i.prototype.toGeoJSON=o.prototype.toGeoJSON},{\"../data/bucket\":290,\"point-geometry\":442,\"vector-tile\":505}],322:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,this.url=e.url,this.coordinates=e.coordinates,u.getImage(e.url,function(t,r){return t?this.fire(\"error\",{error:t}):(this.image=r,this.image.addEventListener(\"load\",function(){this.map._rerender()}.bind(this)),this._loaded=!0,this.fire(\"load\"),void(this.map&&this.setCoordinates(e.coordinates)))}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,onAdd:function(t){this.map=t,this.image&&this.setCoordinates(this.coordinates)},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=32767,r=new h;r.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),r.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,e,0),r.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,e),r.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,e,e),this.tile.buckets={},this.tile.boundsBuffer=new f(r.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(this._loaded&&this.image&&this.image.complete&&this.tile){var t=this.map.painter,e=t.gl;this._prepared?(e.bindTexture(e.TEXTURE_2D,this.tile.texture),e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,this.image)):(this.tile.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.tile.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,this.image))}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"image\",urls:this.url,coordinates:this.coordinates}}})},{\"../data/bucket\":290,\"../data/buffer\":295,\"../geo/lng_lat\":300,\"../render/draw_raster\":312,\"../render/vertex_array_object\":318,\"../util/ajax\":386,\"../util/evented\":395,\"../util/util\":403,\"./tile_coord\":330,\"point-geometry\":442}],323:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/ajax\"),a=t(\"../util/browser\"),o=t(\"../util/mapbox\").normalizeSourceURL;e.exports=function(t,e){var r=function(t,r){if(t)return e(t);var i=n.pick(r,[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\"]);r.vector_layers&&(i.vectorLayers=r.vector_layers,i.vectorLayerIds=i.vectorLayers.map(function(t){return t.id})),e(null,i)};t.url?i.getJSON(o(t.url),r):a.frame(r.bind(null,null,t))}},{\"../util/ajax\":386,\"../util/browser\":387,\"../util/mapbox\":400,\"../util/util\":403}],324:[function(t,e,r){\"use strict\";var n=t(\"../data/bucket\");e.exports=function(t,e,r){return e*(n.EXTENT/(t.tileSize*Math.pow(2,r-t.coord.z)))}},{\"../data/bucket\":290}],325:[function(t,e,r){\"use strict\";function n(t,e){var r=t.coord,n=e.coord;return r.z-n.z||r.y-n.y||r.w-n.w||r.x-n.x}function i(t){for(var e=t[0]||{},r=1;r<t.length;r++){var n=t[r];for(var i in n){var a=n[i],o=e[i];if(void 0===o)o=e[i]=a;else for(var s=0;s<a.length;s++)o.push(a[s]);\n",
+       "}}return e}var a=t(\"./tile_coord\");r.rendered=function(t,e,r,a,o,s){var l=t.tilesIn(r);l.sort(n);for(var u=[],c=0;c<l.length;c++){var h=l[c];h.tile.featureIndex&&u.push(h.tile.featureIndex.query({queryGeometry:h.queryGeometry,scale:h.scale,tileSize:h.tile.tileSize,bearing:s,params:a},e))}return i(u)},r.source=function(t,e){for(var r=t.getRenderableIds().map(function(e){return t.getTileByID(e)}),n=[],i={},o=0;o<r.length;o++){var s=r[o],l=new a(Math.min(s.sourceMaxZoom,s.coord.z),s.coord.x,s.coord.y,0).id;i[l]||(i[l]=!0,s.querySourceFeatures(n,e))}return n}},{\"./tile_coord\":330}],326:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,i.extend(this,i.pick(e,[\"url\",\"scheme\",\"tileSize\"])),s(e,function(t,e){return t?this.fire(\"error\",t):(i.extend(this,e),void this.fire(\"load\"))}.bind(this))}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"../util/evented\"),s=t(\"./load_tilejson\"),l=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=i.inherit(o,{minzoom:0,maxzoom:22,roundZoom:!0,scheme:\"xyz\",tileSize:512,_loaded:!1,onAdd:function(t){this.map=t},serialize:function(){return{type:\"raster\",url:this.url,tileSize:this.tileSize}},loadTile:function(t,e){function r(r,n){if(delete t.request,!t.aborted){if(r)return e(r);var i=this.map.painter.gl;t.texture=this.map.painter.getTexture(n.width),t.texture?(i.bindTexture(i.TEXTURE_2D,t.texture),i.texSubImage2D(i.TEXTURE_2D,0,0,0,i.RGBA,i.UNSIGNED_BYTE,n)):(t.texture=i.createTexture(),i.bindTexture(i.TEXTURE_2D,t.texture),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MIN_FILTER,i.LINEAR_MIPMAP_NEAREST),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MAG_FILTER,i.LINEAR),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_S,i.CLAMP_TO_EDGE),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_T,i.CLAMP_TO_EDGE),i.pixelStorei(i.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0),i.texImage2D(i.TEXTURE_2D,0,i.RGBA,i.RGBA,i.UNSIGNED_BYTE,n),t.texture.size=n.width),i.generateMipmap(i.TEXTURE_2D),this.map.animationLoop.set(this.map.style.rasterFadeDuration),t.state=\"loaded\",e(null)}}var n=l(t.coord.url(this.tiles,null,this.scheme),this.url,this.tileSize);t.request=a.getImage(n,r.bind(this))},abortTile:function(t){t.request&&(t.request.abort(),delete t.request)},unloadTile:function(t){t.texture&&this.map.painter.saveTexture(t.texture)}})},{\"../util/ajax\":386,\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./load_tilejson\":323}],327:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i={vector:t(\"../source/vector_tile_source\"),raster:t(\"../source/raster_tile_source\"),geojson:t(\"../source/geojson_source\"),video:t(\"../source/video_source\"),image:t(\"../source/image_source\")};r.create=function(t,e,r){if(e=new i[e.type](t,e,r),e.id!==t)throw new Error(\"Expected Source id to be \"+t+\" instead of \"+e.id);return n.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],e),e},r.getType=function(t){return i[t]},r.setType=function(t,e){i[t]=e}},{\"../source/geojson_source\":319,\"../source/image_source\":322,\"../source/raster_tile_source\":326,\"../source/vector_tile_source\":331,\"../source/video_source\":333,\"../util/util\":403}],328:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r;var n=this._source=o.create(t,e,r).on(\"load\",function(){this.map&&this._source.onAdd&&this._source.onAdd(this.map),this._sourceLoaded=!0,this.tileSize=n.tileSize,this.minzoom=n.minzoom,this.maxzoom=n.maxzoom,this.roundZoom=n.roundZoom,this.reparseOverscaled=n.reparseOverscaled,this.isTileClipped=n.isTileClipped,this.attribution=n.attribution,this.vectorLayerIds=n.vectorLayerIds,this.fire(\"load\")}.bind(this)).on(\"error\",function(t){this._sourceErrored=!0,this.fire(\"error\",t)}.bind(this)).on(\"change\",function(){this.reload(),this.transform&&this.update(this.transform,this.map&&this.map.style.rasterFadeDuration),this.fire(\"change\")}.bind(this));this._tiles={},this._cache=new c(0,this.unloadTile.bind(this)),this._isIdRenderable=this._isIdRenderable.bind(this)}function i(t,e,r){var n=r.zoomTo(Math.min(t.z,e));return{x:(n.column-(t.x+t.w*Math.pow(2,t.z)))*d,y:(n.row-t.y)*d}}function a(t,e){return t%32-e%32}var o=t(\"./source\"),s=t(\"./tile\"),l=t(\"../util/evented\"),u=t(\"./tile_coord\"),c=t(\"../util/lru_cache\"),h=t(\"../geo/coordinate\"),f=t(\"../util/util\"),d=t(\"../data/bucket\").EXTENT;e.exports=n,n.maxOverzooming=10,n.maxUnderzooming=3,n.prototype=f.inherit(l,{onAdd:function(t){this.map=t,this._source&&this._source.onAdd&&this._source.onAdd(t)},loaded:function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},getSource:function(){return this._source},loadTile:function(t,e){return this._source.loadTile(t,e)},unloadTile:function(t){if(this._source.unloadTile)return this._source.unloadTile(t)},abortTile:function(t){if(this._source.abortTile)return this._source.abortTile(t)},serialize:function(){return this._source.serialize()},prepare:function(){if(this._sourceLoaded&&this._source.prepare)return this._source.prepare()},getIds:function(){return Object.keys(this._tiles).map(Number).sort(a)},getRenderableIds:function(){return this.getIds().filter(this._isIdRenderable)},_isIdRenderable:function(t){return this._tiles[t].isRenderable()&&!this._coveredTiles[t]},reload:function(){this._cache.reset();for(var t in this._tiles){var e=this._tiles[t];\"loading\"!==e.state&&(e.state=\"reloading\"),this.loadTile(this._tiles[t],this._tileLoaded.bind(this,this._tiles[t]))}},_tileLoaded:function(t,e){return e?(t.state=\"errored\",this.fire(\"tile.error\",{tile:t,error:e}),void this._source.fire(\"tile.error\",{tile:t,error:e})):(t.source=this,t.timeAdded=(new Date).getTime(),this.fire(\"tile.load\",{tile:t}),void this._source.fire(\"tile.load\",{tile:t}))},getTile:function(t){return this.getTileByID(t.id)},getTileByID:function(t){return this._tiles[t]},getZoom:function(t){return t.zoom+t.scaleZoom(t.tileSize/this.tileSize)},findLoadedChildren:function(t,e,r){var n=!1;for(var i in this._tiles){var a=this._tiles[i];if(!(r[i]||!a.isRenderable()||a.coord.z<=t.z||a.coord.z>e)){var o=Math.pow(2,Math.min(a.coord.z,this.maxzoom)-Math.min(t.z,this.maxzoom));if(Math.floor(a.coord.x/o)===t.x&&Math.floor(a.coord.y/o)===t.y)for(r[i]=!0,n=!0;a&&a.coord.z-1>t.z;){var s=a.coord.parent(this.maxzoom).id;a=this._tiles[s],a&&a.isRenderable()&&(delete r[i],r[s]=!0)}}}return n},findLoadedParent:function(t,e,r){for(var n=t.z-1;n>=e;n--){t=t.parent(this.maxzoom);var i=this._tiles[t.id];if(i&&i.isRenderable())return r[t.id]=!0,i;if(this._cache.has(t.id))return this.addTile(t),r[t.id]=!0,this._tiles[t.id]}},updateCacheSize:function(t){var e=Math.ceil(t.width/t.tileSize)+1,r=Math.ceil(t.height/t.tileSize)+1,n=e*r,i=5;this._cache.setMaxSize(Math.floor(n*i))},update:function(t,e){if(this._sourceLoaded){var r,i,a;this.updateCacheSize(t);var o=(this.roundZoom?Math.round:Math.floor)(this.getZoom(t)),s=Math.max(o-n.maxOverzooming,this.minzoom),l=Math.max(o+n.maxUnderzooming,this.minzoom),c={},h=(new Date).getTime();this._coveredTiles={};var d=this.used?t.coveringTiles(this._source):[];for(r=0;r<d.length;r++)i=d[r],a=this.addTile(i),c[i.id]=!0,a.isRenderable()||this.findLoadedChildren(i,l,c)||this.findLoadedParent(i,s,c);for(var p={},g=Object.keys(c),m=0;m<g.length;m++){var v=g[m];i=u.fromID(v),a=this._tiles[v],a&&a.timeAdded>h-(e||0)&&(this.findLoadedChildren(i,l,c)&&(c[v]=!0),this.findLoadedParent(i,s,p))}var y;for(y in p)c[y]||(this._coveredTiles[y]=!0);for(y in p)c[y]=!0;var x=f.keysDifference(this._tiles,c);for(r=0;r<x.length;r++)this.removeTile(+x[r]);this.transform=t}},addTile:function(t){var e=this._tiles[t.id];if(e)return e;var r=t.wrapped();if(e=this._tiles[r.id],e||(e=this._cache.get(r.id),e&&this._redoPlacement&&this._redoPlacement(e)),!e){var n=t.z,i=n>this.maxzoom?Math.pow(2,n-this.maxzoom):1;e=new s(r,this.tileSize*i,this.maxzoom),this.loadTile(e,this._tileLoaded.bind(this,e))}return e.uses++,this._tiles[t.id]=e,this.fire(\"tile.add\",{tile:e}),this._source.fire(\"tile.add\",{tile:e}),e},removeTile:function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this.fire(\"tile.remove\",{tile:e}),this._source.fire(\"tile.remove\",{tile:e}),e.uses>0||(e.isRenderable()?this._cache.add(e.coord.wrapped().id,e):(e.aborted=!0,this.abortTile(e),this.unloadTile(e))))},clearTiles:function(){for(var t in this._tiles)this.removeTile(t);this._cache.reset()},tilesIn:function(t){for(var e={},r=this.getIds(),n=1/0,a=1/0,o=-(1/0),s=-(1/0),l=t[0].zoom,c=0;c<t.length;c++){var f=t[c];n=Math.min(n,f.column),a=Math.min(a,f.row),o=Math.max(o,f.column),s=Math.max(s,f.row)}for(var p=0;p<r.length;p++){var g=this._tiles[r[p]],m=u.fromID(r[p]),v=[i(m,g.sourceMaxZoom,new h(n,a,l)),i(m,g.sourceMaxZoom,new h(o,s,l))];if(v[0].x<d&&v[0].y<d&&v[1].x>=0&&v[1].y>=0){for(var y=[],x=0;x<t.length;x++)y.push(i(m,g.sourceMaxZoom,t[x]));var b=e[g.coord.id];void 0===b&&(b=e[g.coord.id]={tile:g,coord:m,queryGeometry:[],scale:Math.pow(2,this.transform.zoom-g.coord.z)}),b.queryGeometry.push(y)}}var _=[];for(var w in e)_.push(e[w]);return _},redoPlacement:function(){for(var t=this.getIds(),e=0;e<t.length;e++){var r=this.getTileByID(t[e]);r.redoPlacement(this)}},getVisibleCoordinates:function(){return this.getRenderableIds().map(u.fromID)}})},{\"../data/bucket\":290,\"../geo/coordinate\":299,\"../util/evented\":395,\"../util/lru_cache\":399,\"../util/util\":403,\"./source\":327,\"./tile\":329,\"./tile_coord\":330}],329:[function(t,e,r){\"use strict\";function n(t,e,r){this.coord=t,this.uid=a.uniqueId(),this.uses=0,this.tileSize=e,this.sourceMaxZoom=r,this.buckets={},this.state=\"loading\"}function i(t,e){if(e){for(var r={},n=0;n<t.length;n++){var i=e.getLayer(t[n].layerId);if(i){var s=o.create(a.extend({layer:i,childLayers:t[n].childLayerIds.map(e.getLayer.bind(e)).filter(function(t){return t})},t[n]));r[s.id]=s}}return r}}var a=t(\"../util/util\"),o=t(\"../data/bucket\"),s=t(\"../data/feature_index\"),l=t(\"vector-tile\"),u=t(\"pbf\"),c=t(\"../util/vectortile_to_geojson\"),h=t(\"feature-filter\"),f=t(\"../symbol/collision_tile\"),d=t(\"../symbol/collision_box\"),p=t(\"../symbol/symbol_instances\"),g=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype={loadVectorData:function(t,e){this.state=\"loaded\",t&&(this.collisionBoxArray=new d(t.collisionBoxArray),this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.symbolInstancesArray=new p(t.symbolInstancesArray),this.symbolQuadsArray=new g(t.symbolQuadsArray),this.featureIndex=new s(t.featureIndex,t.rawTileData,this.collisionTile),this.rawTileData=t.rawTileData,this.buckets=i(t.buckets,e))},reloadSymbolData:function(t,e,r){if(\"unloaded\"!==this.state){this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.featureIndex.setCollisionTile(this.collisionTile);for(var n in this.buckets){var o=this.buckets[n];\"symbol\"===o.type&&(o.destroy(e.gl),delete this.buckets[n])}a.extend(this.buckets,i(t.buckets,r))}},unloadVectorData:function(t){for(var e in this.buckets){var r=this.buckets[e];r.destroy(t.gl)}this.collisionBoxArray=null,this.symbolQuadsArray=null,this.symbolInstancesArray=null,this.collisionTile=null,this.featureIndex=null,this.rawTileData=null,this.buckets=null,this.state=\"unloaded\"},redoPlacement:function(t){function e(e,r){this.reloadSymbolData(r,t.map.painter,t.map.style),t.fire(\"tile.load\",{tile:this}),this.state=\"loaded\",this.redoWhenDone&&(this.redoPlacement(t),this.redoWhenDone=!1)}return\"loaded\"!==this.state||\"reloading\"===this.state?void(this.redoWhenDone=!0):(this.state=\"reloading\",void t.dispatcher.send(\"redo placement\",{uid:this.uid,source:t.id,angle:t.map.transform.angle,pitch:t.map.transform.pitch,showCollisionBoxes:t.map.showCollisionBoxes},e.bind(this),this.workerID))},getBucket:function(t){return this.buckets&&this.buckets[t.ref||t.id]},querySourceFeatures:function(t,e){if(this.rawTileData){this.vtLayers||(this.vtLayers=new l.VectorTile(new u(new Uint8Array(this.rawTileData))).layers);var r=this.vtLayers._geojsonTileLayer||this.vtLayers[e.sourceLayer];if(r)for(var n=h(e.filter),i={z:this.coord.z,x:this.coord.x,y:this.coord.y},a=0;a<r.length;a++){var o=r.feature(a);if(n(o)){var s=new c(o,this.coord.z,this.coord.x,this.coord.y);s.tile=i,t.push(s)}}}},isRenderable:function(){return\"loaded\"===this.state||\"reloading\"===this.state}}},{\"../data/bucket\":290,\"../data/feature_index\":297,\"../symbol/collision_box\":355,\"../symbol/collision_tile\":357,\"../symbol/symbol_instances\":366,\"../symbol/symbol_quads\":367,\"../util/util\":403,\"../util/vectortile_to_geojson\":404,\"feature-filter\":105,pbf:436,\"vector-tile\":505}],330:[function(t,e,r){\"use strict\";function n(t,e,r,n){l(!isNaN(t)&&t>=0&&t%1===0),l(!isNaN(e)&&e>=0&&e%1===0),l(!isNaN(r)&&r>=0&&r%1===0),isNaN(n)&&(n=0),this.z=+t,this.x=+e,this.y=+r,this.w=+n,n*=2,n<0&&(n=n*-1-1);var i=1<<this.z;this.id=32*(i*i*n+i*this.y+this.x)+this.z,this.posMatrix=null}function i(t,e,r){for(var n,i=\"\",a=t;a>0;a--)n=1<<a-1,i+=(e&n?1:0)+(r&n?2:0);return i}function a(t,e){if(t.row>e.row){var r=t;t=e,e=r}return{x0:t.column,y0:t.row,x1:e.column,y1:e.row,dx:e.column-t.column,dy:e.row-t.row}}function o(t,e,r,n,i){var a=Math.max(r,Math.floor(e.y0)),o=Math.min(n,Math.ceil(e.y1));if(t.x0===e.x0&&t.y0===e.y0?t.x0+e.dy/t.dy*t.dx<e.x1:t.x1-e.dy/t.dy*t.dx<e.x0){var s=t;t=e,e=s}for(var l=t.dx/t.dy,u=e.dx/e.dy,c=t.dx>0,h=e.dx<0,f=a;f<o;f++){var d=l*Math.max(0,Math.min(t.dy,f+c-t.y0))+t.x0,p=u*Math.max(0,Math.min(e.dy,f+h-e.y0))+e.x0;i(Math.floor(p),Math.ceil(d),f)}}function s(t,e,r,n,i,s){var l,u=a(t,e),c=a(e,r),h=a(r,t);u.dy>c.dy&&(l=u,u=c,c=l),u.dy>h.dy&&(l=u,u=h,h=l),c.dy>h.dy&&(l=c,c=h,h=l),u.dy&&o(h,u,n,i,s),c.dy&&o(h,c,n,i,s)}var l=t(\"assert\"),u=t(\"whoots-js\"),c=t(\"../geo/coordinate\");e.exports=n,n.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y},n.prototype.toCoordinate=function(t){var e=Math.min(this.z,t),r=Math.pow(2,e),n=this.y,i=this.x+r*this.w;return new c(i,n,e)},n.fromID=function(t){var e=t%32,r=1<<e,i=(t-e)/32,a=i%r,o=(i-a)/r%r,s=Math.floor(i/(r*r));return s%2!==0&&(s=s*-1-1),s/=2,new n(e,a,o,s)},n.prototype.url=function(t,e,r){var n=u.getTileBBox(this.x,this.y,this.z),a=i(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",Math.min(this.z,e||this.z)).replace(\"{x}\",this.x).replace(\"{y}\",\"tms\"===r?Math.pow(2,this.z)-this.y-1:this.y).replace(\"{quadkey}\",a).replace(\"{bbox-epsg-3857}\",n)},n.prototype.parent=function(t){return 0===this.z?null:this.z>t?new n(this.z-1,this.x,this.y,this.w):new n(this.z-1,Math.floor(this.x/2),Math.floor(this.y/2),this.w)},n.prototype.wrapped=function(){return new n(this.z,this.x,this.y,0)},n.prototype.children=function(t){if(this.z>=t)return[new n(this.z+1,this.x,this.y,this.w)];var e=this.z+1,r=2*this.x,i=2*this.y;return[new n(e,r,i,this.w),new n(e,r+1,i,this.w),new n(e,r,i+1,this.w),new n(e,r+1,i+1,this.w)]},n.cover=function(t,e,r){function i(t,e,i){var s,l,u;if(i>=0&&i<=a)for(s=t;s<e;s++)l=(s%a+a)%a,u=new n(r,l,i,Math.floor(s/a)),o[u.id]=u}var a=1<<t,o={};return s(e[0],e[1],e[2],0,a,i),s(e[2],e[3],e[0],0,a,i),Object.keys(o).map(function(t){return o[t]})}},{\"../geo/coordinate\":299,assert:34,\"whoots-js\":521}],331:[function(t,e,r){\"use strict\";function n(t,e,r){if(this.id=t,this.dispatcher=r,a.extend(this,a.pick(e,[\"url\",\"scheme\",\"tileSize\"])),this._options=a.extend({type:\"vector\"},e),512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");o(e,function(t,e){return t?void this.fire(\"error\",t):(a.extend(this,e),void this.fire(\"load\"))}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"./load_tilejson\"),s=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=a.inherit(i,{minzoom:0,maxzoom:22,scheme:\"xyz\",tileSize:512,reparseOverscaled:!0,isTileClipped:!0,onAdd:function(t){this.map=t},serialize:function(){return a.extend({},this._options)},loadTile:function(t,e){function r(r,n){if(!t.aborted){if(r)return e(r);t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null),t.reloadCallback&&(this.loadTile(t,t.reloadCallback),t.reloadCallback=null)}}var n=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,i={url:s(t.coord.url(this.tiles,this.maxzoom,this.scheme),this.url),uid:t.uid,coord:t.coord,zoom:t.coord.z,tileSize:this.tileSize*n,source:this.id,overscaling:n,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID?\"loading\"===t.state?t.reloadCallback=e:(i.rawTileData=t.rawTileData,this.dispatcher.send(\"reload tile\",i,r.bind(this),t.workerID)):t.workerID=this.dispatcher.send(\"load tile\",i,r.bind(this))},abortTile:function(t){this.dispatcher.send(\"abort tile\",{uid:t.uid,source:this.id},null,t.workerID)},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},null,t.workerID)}})},{\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./load_tilejson\":323}],332:[function(t,e,r){\"use strict\";function n(t,e,r){this.actor=t,this.styleLayers=e,r&&(this.loadVectorData=r),this.loading={},this.loaded={}}var i=t(\"../util/ajax\"),a=t(\"vector-tile\"),o=t(\"pbf\"),s=t(\"./worker_tile\");e.exports=n,n.prototype={loadTile:function(t,e){function r(t,r){return delete this.loading[n][i],t?e(t):r?(a.data=r.tile,a.parse(a.data,this.styleLayers.getLayerFamilies(),this.actor,r.rawTileData,e),this.loaded[n]=this.loaded[n]||{},void(this.loaded[n][i]=a)):e(null,null)}var n=t.source,i=t.uid;this.loading[n]||(this.loading[n]={});var a=this.loading[n][i]=new s(t);a.abort=this.loadVectorData(t,r.bind(this))},reloadTile:function(t,e){var r=this.loaded[t.source],n=t.uid;if(r&&r[n]){var i=r[n];i.parse(i.data,this.styleLayers.getLayerFamilies(),this.actor,t.rawTileData,e)}},abortTile:function(t){var e=this.loading[t.source],r=t.uid;e&&e[r]&&e[r].abort&&(e[r].abort(),delete e[r])},removeTile:function(t){var e=this.loaded[t.source],r=t.uid;e&&e[r]&&delete e[r]},loadVectorData:function(t,e){function r(t,r){if(t)return e(t);var n=new a.VectorTile(new o(new Uint8Array(r)));e(t,{tile:n,rawTileData:r})}var n=i.getArrayBuffer(t.url,r.bind(this));return function(){n.abort()}},redoPlacement:function(t,e){var r=this.loaded[t.source],n=this.loading[t.source],i=t.uid;if(r&&r[i]){var a=r[i],o=a.redoPlacement(t.angle,t.pitch,t.showCollisionBoxes);o.result&&e(null,o.result,o.transferables)}else n&&n[i]&&(n[i].angle=t.angle)}}},{\"../util/ajax\":386,\"./worker_tile\":335,pbf:436,\"vector-tile\":505}],333:[function(t,e,r){\"use strict\";function n(t,e){this.id=t,this.urls=e.urls,this.coordinates=e.coordinates,u.getVideo(e.urls,function(t,r){if(t)return this.fire(\"error\",{error:t});this.video=r,this.video.loop=!0;var n;this.video.addEventListener(\"playing\",function(){n=this.map.style.animationLoop.set(1/0),this.map._rerender()}.bind(this)),this.video.addEventListener(\"pause\",function(){this.map.style.animationLoop.cancel(n)}.bind(this)),this.map&&(this.video.play(),this.setCoordinates(e.coordinates)),this.fire(\"load\")}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,roundZoom:!0,getVideo:function(){return this.video},onAdd:function(t){this.map||(this.map=t,this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=32767,r=new h;r.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),r.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,e,0),r.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,e),r.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,e,e),this.tile.buckets={},this.tile.boundsBuffer=new f(r.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(!(this.video.readyState<2)&&this.tile){var t=this.map.painter.gl;this._prepared?(t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texSubImage2D(t.TEXTURE_2D,0,0,0,t.RGBA,t.UNSIGNED_BYTE,this.video)):(this._prepared=!0,this.tile.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,this.video)),this._currentTime=this.video.currentTime}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}}})},{\"../data/bucket\":290,\"../data/buffer\":295,\"../geo/lng_lat\":300,\"../render/draw_raster\":312,\"../render/vertex_array_object\":318,\"../util/ajax\":386,\"../util/evented\":395,\"../util/util\":403,\"./tile_coord\":330,\"point-geometry\":442}],334:[function(t,e,r){\"use strict\";function n(t){this.self=t,this.actor=new a(t,this);var e={getLayers:function(){return this.layers}.bind(this),getLayerFamilies:function(){return this.layerFamilies}.bind(this)};this.workerSources={vector:new l(this.actor,e),geojson:new u(this.actor,e)},this.self.registerWorkerSource=function(t,r){if(this.workerSources[t])throw new Error('Worker source with name \"'+t+'\" already registered.');this.workerSources[t]=new r(this.actor,e)}.bind(this)}function i(t){var e={};for(var r in t){var n=t[r],i=n.ref||n.id,a=t[i];a.layout&&\"none\"===a.layout.visibility||(e[i]=e[i]||[],r===i?e[i].unshift(n):e[i].push(n))}return e}var a=t(\"../util/actor\"),o=t(\"../style/style_layer\"),s=t(\"../util/util\"),l=t(\"./vector_tile_worker_source\"),u=t(\"./geojson_worker_source\");e.exports=function(t){return new n(t)},s.extend(n.prototype,{\"set layers\":function(t){function e(t){var e=o.create(t,t.ref&&r.layers[t.ref]);e.updatePaintTransitions({},{transition:!1}),r.layers[e.id]=e}this.layers={};for(var r=this,n=[],a=0;a<t.length;a++){var s=t[a];\"fill\"!==s.type&&\"line\"!==s.type&&\"circle\"!==s.type&&\"symbol\"!==s.type||(s.ref?n.push(a):e(s))}for(var l=0;l<n.length;l++)e(t[n[l]]);this.layerFamilies=i(this.layers)},\"update layers\":function(t){function e(t){var e=a.layers[t.ref];a.layers[t.id]?a.layers[t.id].set(t,e):a.layers[t.id]=o.create(t,e),a.layers[t.id].updatePaintTransitions({},{transition:!1})}var r,n,a=this;for(r in t)n=t[r],n.ref&&e(n);for(r in t)n=t[r],n.ref||e(n);this.layerFamilies=i(this.layers)},\"load tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].loadTile(t,e)},\"reload tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].reloadTile(t,e)},\"abort tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].abortTile(t)},\"remove tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].removeTile(t)},\"redo placement\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].redoPlacement(t,e)},\"load worker source\":function(t,e){try{this.self.importScripts(t.url),e()}catch(t){e(t)}}})},{\"../style/style_layer\":342,\"../util/actor\":385,\"../util/util\":403,\"./geojson_worker_source\":320,\"./vector_tile_worker_source\":332}],335:[function(t,e,r){\"use strict\";function n(t){this.coord=t.coord,this.uid=t.uid,this.zoom=t.zoom,this.tileSize=t.tileSize,this.source=t.source,this.overscaling=t.overscaling,this.angle=t.angle,this.pitch=t.pitch,this.showCollisionBoxes=t.showCollisionBoxes}function i(t){return!t.isEmpty()}function a(t){return t.serialize()}function o(t){var e=[];for(var r in t)t[r].getTransferables(e);return e}function s(t){return t.id}var l=t(\"../data/feature_index\"),u=t(\"../symbol/collision_tile\"),c=t(\"../data/bucket\"),h=t(\"../symbol/collision_box\"),f=t(\"../util/dictionary_coder\"),d=t(\"../util/util\"),p=t(\"../symbol/symbol_instances\"),g=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype.parse=function(t,e,r,n,m){function v(t,e){for(var r=0;r<t.length;r++){var n=t.feature(r);n.index=r;for(var i in e)e[i].filter(n)&&e[i].features.push(n)}}function y(t){if(t)return m(t);if(N++,2===N){for(var e=D.length-1;e>=0;e--)x(S,D[e]);b()}}function x(t,e){if(e.populateArrays(k,j,F),\"symbol\"!==e.type)for(var r=0;r<e.features.length;r++){var n=e.features[r];T.insert(n,n.index,e.sourceLayerIndex,e.index)}e.features=null}function b(){S.status=\"done\",S.redoPlacementAfterDone&&(S.redoPlacement(S.angle,S.pitch,null),S.redoPlacementAfterDone=!1);var t=T.serialize(),e=k.serialize(),r=S.collisionBoxArray.serialize(),s=S.symbolInstancesArray.serialize(),l=S.symbolQuadsArray.serialize(),u=[n].concat(t.transferables).concat(e.transferables),c=P.filter(i);m(null,{buckets:c.map(a),featureIndex:t.data,collisionTile:e.data,collisionBoxArray:r,symbolInstancesArray:s,symbolQuadsArray:l,rawTileData:n},o(c).concat(u))}this.status=\"parsing\",this.data=t,this.collisionBoxArray=new h,this.symbolInstancesArray=new p,this.symbolQuadsArray=new g;var _,w,M,A,k=new u(this.angle,this.pitch,this.collisionBoxArray),T=new l(this.coord,this.overscaling,k,t.layers),E=new f(t.layers?Object.keys(t.layers).sort():[\"_geojsonTileLayer\"]),S=this,L={},z={},C=0;for(var I in e)w=e[I][0],w.source===this.source&&(w.ref||w.minzoom&&this.zoom<w.minzoom||w.maxzoom&&this.zoom>=w.maxzoom||w.layout&&\"none\"===w.layout.visibility||t.layers&&!t.layers[w.sourceLayer]||(A=c.create({layer:w,index:C++,childLayers:e[I],zoom:this.zoom,overscaling:this.overscaling,showCollisionBoxes:this.showCollisionBoxes,collisionBoxArray:this.collisionBoxArray,symbolQuadsArray:this.symbolQuadsArray,symbolInstancesArray:this.symbolInstancesArray,sourceLayerIndex:E.encode(w.sourceLayer||\"_geojsonTileLayer\")}),A.createFilter(),L[w.id]=A,t.layers&&(M=w.sourceLayer,z[M]=z[M]||{},z[M][w.id]=A)));if(t.layers)for(M in z)1===w.version&&d.warnOnce('Vector tile source \"'+this.source+'\" layer \"'+M+'\" does not use vector tile spec v2 and therefore may have some rendering errors.'),w=t.layers[M],w&&v(w,z[M]);else v(t,L);var P=[],D=this.symbolBuckets=[],R=[];T.bucketLayerIDs={};for(var O in L)A=L[O],0!==A.features.length&&(T.bucketLayerIDs[A.index]=A.childLayers.map(s),P.push(A),\"symbol\"===A.type?D.push(A):R.push(A));var F={},j={},N=0;if(D.length>0){for(_=D.length-1;_>=0;_--)D[_].updateIcons(F),D[_].updateFont(j);for(var B in j)j[B]=Object.keys(j[B]).map(Number);F=Object.keys(F),r.send(\"get glyphs\",{uid:this.uid,stacks:j},function(t,e){j=e,y(t)}),F.length?r.send(\"get icons\",{icons:F},function(t,e){F=e,y(t)}):y()}for(_=R.length-1;_>=0;_--)x(this,R[_]);if(0===D.length)return b()},n.prototype.redoPlacement=function(t,e,r){if(\"done\"!==this.status)return this.redoPlacementAfterDone=!0,this.angle=t,{};for(var n=new u(t,e,this.collisionBoxArray),s=this.symbolBuckets,l=s.length-1;l>=0;l--)s[l].placeFeatures(n,r);var c=n.serialize(),h=s.filter(i);return{result:{buckets:h.map(a),collisionTile:c.data},transferables:o(h).concat(c.transferables)}}},{\"../data/bucket\":290,\"../data/feature_index\":297,\"../symbol/collision_box\":355,\"../symbol/collision_tile\":357,\"../symbol/symbol_instances\":366,\"../symbol/symbol_quads\":367,\"../util/dictionary_coder\":393,\"../util/util\":403}],336:[function(t,e,r){\"use strict\";function n(){this.n=0,this.times=[]}e.exports=n,n.prototype.stopped=function(){return this.times=this.times.filter(function(t){return t.time>=(new Date).getTime()}),!this.times.length},n.prototype.set=function(t){return this.times.push({id:this.n,time:t+(new Date).getTime()}),this.n++},n.prototype.cancel=function(t){this.times=this.times.filter(function(e){return e.id!==t})}},{}],337:[function(t,e,r){\"use strict\";function n(t){this.base=t,this.retina=s.devicePixelRatio>1;var e=this.retina?\"@2x\":\"\";o.getJSON(l(t,e,\".json\"),function(t,e){return t?void this.fire(\"error\",{error:t}):(this.data=e,void(this.img&&this.fire(\"load\")))}.bind(this)),o.getImage(l(t,e,\".png\"),function(t,e){if(t)return void this.fire(\"error\",{error:t});for(var r=e.getData(),n=e.data=new Uint8Array(r.length),i=0;i<r.length;i+=4){var a=r[i+3]/255;n[i+0]=r[i+0]*a,n[i+1]=r[i+1]*a,n[i+2]=r[i+2]*a,n[i+3]=r[i+3]}this.img=e,this.data&&this.fire(\"load\")}.bind(this))}function i(){}var a=t(\"../util/evented\"),o=t(\"../util/ajax\"),s=t(\"../util/browser\"),l=t(\"../util/mapbox\").normalizeSpriteURL;e.exports=n,n.prototype=Object.create(a),n.prototype.toJSON=function(){return this.base},n.prototype.loaded=function(){return!(!this.data||!this.img)},n.prototype.resize=function(){if(s.devicePixelRatio>1!==this.retina){var t=new n(this.base);t.on(\"load\",function(){this.img=t.img,this.data=t.data,this.retina=t.retina}.bind(this))}},i.prototype={x:0,y:0,width:0,height:0,pixelRatio:1,sdf:!1},n.prototype.getSpritePosition=function(t){if(!this.loaded())return new i;var e=this.data&&this.data[t];return e&&this.img?e:new i}},{\"../util/ajax\":386,\"../util/browser\":387,\"../util/evented\":395,\"../util/mapbox\":400}],338:[function(t,e,r){\"use strict\";var n=t(\"csscolorparser\").parseCSSColor,i=t(\"../util/util\"),a=t(\"./style_function\"),o={};e.exports=function t(e){if(a.isFunctionDefinition(e))return i.extend({},e,{stops:e.stops.map(function(e){return[e[0],t(e[1])]})});if(\"string\"==typeof e){if(!o[e]){var r=n(e);if(!r)throw new Error(\"Invalid color \"+e);o[e]=[r[0]/255*r[3],r[1]/255*r[3],r[2]/255*r[3],r[3]]}return o[e]}throw new Error(\"Invalid color \"+e)}},{\"../util/util\":403,\"./style_function\":341,csscolorparser:89}],339:[function(t,e,r){\"use strict\";function n(t,e,r){this.animationLoop=e||new g,this.dispatcher=new p(r||1,this),this.spriteAtlas=new l(1024,1024),this.lineAtlas=new u(256,512),this._layers={},this._order=[],this._groups=[],this.sources={},this.zoomHistory={},c.bindAll([\"_forwardSourceEvent\",\"_forwardTileEvent\",\"_forwardLayerEvent\",\"_redoPlacement\"],this),this._resetUpdates();var n=function(t,e){if(t)return void this.fire(\"error\",{error:t});if(!m.emitErrors(this,m(e))){this._loaded=!0,this.stylesheet=e,this.updateClasses();var r=e.sources;for(var n in r)this.addSource(n,r[n]);e.sprite&&(this.sprite=new o(e.sprite),this.sprite.on(\"load\",this.fire.bind(this,\"change\"))),this.glyphSource=new s(e.glyphs),this._resolve(),this.fire(\"load\")}}.bind(this);\"string\"==typeof t?h.getJSON(f(t),n):d.frame(n.bind(this,null,t)),this.on(\"source.load\",function(t){var e=t.source;if(e&&e.vectorLayerIds)for(var r in this._layers){var n=this._layers[r];n.source===e.id&&this._validateLayer(n)}})}var i=t(\"../util/evented\"),a=t(\"./style_layer\"),o=t(\"./image_sprite\"),s=t(\"../symbol/glyph_source\"),l=t(\"../symbol/sprite_atlas\"),u=t(\"../render/line_atlas\"),c=t(\"../util/util\"),h=t(\"../util/ajax\"),f=t(\"../util/mapbox\").normalizeStyleURL,d=t(\"../util/browser\"),p=t(\"../util/dispatcher\"),g=t(\"./animation_loop\"),m=t(\"./validate_style\"),v=t(\"../source/source\"),y=t(\"../source/query_features\"),x=t(\"../source/source_cache\"),b=t(\"./style_spec\"),_=t(\"./style_function\");e.exports=n,n.prototype=c.inherit(i,{_loaded:!1,_validateLayer:function(t){var e=this.sources[t.source];t.sourceLayer&&e&&e.vectorLayerIds&&e.vectorLayerIds.indexOf(t.sourceLayer)===-1&&this.fire(\"error\",{error:new Error('Source layer \"'+t.sourceLayer+'\" does not exist on source \"'+e.id+'\" as specified by style layer \"'+t.id+'\"')})},loaded:function(){if(!this._loaded)return!1;if(Object.keys(this._updates.sources).length)return!1;for(var t in this.sources)if(!this.sources[t].loaded())return!1;return!(this.sprite&&!this.sprite.loaded())},_resolve:function(){var t,e;this._layers={},this._order=this.stylesheet.layers.map(function(t){return t.id});for(var r=0;r<this.stylesheet.layers.length;r++)e=this.stylesheet.layers[r],\n",
+       "e.ref||(t=a.create(e),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent));for(var n=0;n<this.stylesheet.layers.length;n++)if(e=this.stylesheet.layers[n],e.ref){var i=this.getLayer(e.ref);t=a.create(e,i),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent)}this._groupLayers(),this._updateWorkerLayers()},_groupLayers:function(){var t;this._groups=[];for(var e=0;e<this._order.length;++e){var r=this._layers[this._order[e]];t&&r.source===t.source||(t=[],t.source=r.source,this._groups.push(t)),t.push(r)}},_updateWorkerLayers:function(t){this.dispatcher.broadcast(t?\"update layers\":\"set layers\",this._serializeLayers(t))},_serializeLayers:function(t){t=t||this._order;for(var e=[],r={includeRefProperties:!0},n=0;n<t.length;n++)e.push(this._layers[t[n]].serialize(r));return e},_applyClasses:function(t,e){if(this._loaded){t=t||[],e=e||{transition:!0};var r=this.stylesheet.transition||{},n=this._updates.allPaintProps?this._layers:this._updates.paintProps;for(var i in n){var a=this._layers[i],o=this._updates.paintProps[i];if(this._updates.allPaintProps||o.all)a.updatePaintTransitions(t,e,r,this.animationLoop);else for(var s in o)this._layers[i].updatePaintTransition(s,t,e,r,this.animationLoop)}}},_recalculate:function(t){for(var e in this.sources)this.sources[e].used=!1;this._updateZoomHistory(t),this.rasterFadeDuration=300;for(var r in this._layers){var n=this._layers[r];n.recalculate(t,this.zoomHistory),!n.isHidden(t)&&n.source&&(this.sources[n.source].used=!0)}var i=300;Math.floor(this.z)!==Math.floor(t)&&this.animationLoop.set(i),this.z=t,this.fire(\"zoom\")},_updateZoomHistory:function(t){var e=this.zoomHistory;void 0===e.lastIntegerZoom&&(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=0,e.lastZoom=t),Math.floor(e.lastZoom)<Math.floor(t)?(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=Date.now()):Math.floor(e.lastZoom)>Math.floor(t)&&(e.lastIntegerZoom=Math.floor(t+1),e.lastIntegerZoomTime=Date.now()),e.lastZoom=t},_checkLoaded:function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},update:function(t,e){if(!this._updates.changed)return this;if(this._updates.allLayers)this._groupLayers(),this._updateWorkerLayers();else{var r=Object.keys(this._updates.layers);r.length&&this._updateWorkerLayers(r)}var n,i=Object.keys(this._updates.sources);for(n=0;n<i.length;n++)this._reloadSource(i[n]);for(n=0;n<this._updates.events.length;n++){var a=this._updates.events[n];this.fire(a[0],a[1])}return this._applyClasses(t,e),this._updates.changed&&this.fire(\"change\"),this._resetUpdates(),this},_resetUpdates:function(){this._updates={events:[],layers:{},sources:{},paintProps:{}}},addSource:function(t,e){if(this._checkLoaded(),void 0!==this.sources[t])throw new Error(\"There is already a source with this ID\");if(!e.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(e)+\".\");var r=[\"vector\",\"raster\",\"geojson\",\"video\",\"image\"],n=r.indexOf(e.type)>=0;return n&&this._handleErrors(m.source,\"sources.\"+t,e)?this:(e=new x(t,e,this.dispatcher),this.sources[t]=e,e.style=this,e.on(\"load\",this._forwardSourceEvent).on(\"error\",this._forwardSourceEvent).on(\"change\",this._forwardSourceEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.load\",this._forwardTileEvent).on(\"tile.error\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.add\",{source:e}]),this._updates.changed=!0,this)},removeSource:function(t){if(this._checkLoaded(),void 0===this.sources[t])throw new Error(\"There is no source with this ID\");var e=this.sources[t];return delete this.sources[t],delete this._updates.sources[t],e.off(\"load\",this._forwardSourceEvent).off(\"error\",this._forwardSourceEvent).off(\"change\",this._forwardSourceEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.load\",this._forwardTileEvent).off(\"tile.error\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.remove\",{source:e}]),this._updates.changed=!0,this},getSource:function(t){return this.sources[t]&&this.sources[t].getSource()},addLayer:function(t,e){if(this._checkLoaded(),!(t instanceof a)){if(this._handleErrors(m.layer,\"layers.\"+t.id,t,!1,{arrayIndex:-1}))return this;var r=t.ref&&this.getLayer(t.ref);t=a.create(t,r)}return this._validateLayer(t),t.on(\"error\",this._forwardLayerEvent),this._layers[t.id]=t,this._order.splice(e?this._order.indexOf(e):1/0,0,t.id),this._updates.allLayers=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.events.push([\"layer.add\",{layer:t}]),this.updateClasses(t.id)},removeLayer:function(t){this._checkLoaded();var e=this._layers[t];if(void 0===e)throw new Error(\"There is no layer with this ID\");for(var r in this._layers)this._layers[r].ref===t&&this.removeLayer(r);return e.off(\"error\",this._forwardLayerEvent),delete this._layers[t],delete this._updates.layers[t],delete this._updates.paintProps[t],this._order.splice(this._order.indexOf(t),1),this._updates.allLayers=!0,this._updates.events.push([\"layer.remove\",{layer:e}]),this._updates.changed=!0,this},getLayer:function(t){return this._layers[t]},getReferentLayer:function(t){var e=this.getLayer(t);return e.ref&&(e=this.getLayer(e.ref)),e},setLayerZoomRange:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return n.minzoom===e&&n.maxzoom===r?this:(null!=e&&(n.minzoom=e),null!=r&&(n.maxzoom=r),this._updateLayer(n))},setFilter:function(t,e){this._checkLoaded();var r=this.getReferentLayer(t);return null!==e&&this._handleErrors(m.filter,\"layers.\"+r.id+\".filter\",e)?this:c.deepEqual(r.filter,e)?this:(r.filter=c.clone(e),this._updateLayer(r))},getFilter:function(t){return this.getReferentLayer(t).filter},setLayoutProperty:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return c.deepEqual(n.getLayoutProperty(e),r)?this:(n.setLayoutProperty(e,r),this._updateLayer(n))},getLayoutProperty:function(t,e){return this.getReferentLayer(t).getLayoutProperty(e)},setPaintProperty:function(t,e,r,n){this._checkLoaded();var i=this.getLayer(t);if(c.deepEqual(i.getPaintProperty(e,n),r))return this;var a=i.isPaintValueFeatureConstant(e);i.setPaintProperty(e,r,n);var o=!(r&&_.isFunctionDefinition(r)&&\"$zoom\"!==r.property&&void 0!==r.property);return o&&a||(this._updates.layers[t]=!0,i.source&&(this._updates.sources[i.source]=!0)),this.updateClasses(t,e)},getPaintProperty:function(t,e,r){return this.getLayer(t).getPaintProperty(e,r)},updateClasses:function(t,e){if(this._updates.changed=!0,t){var r=this._updates.paintProps;r[t]||(r[t]={}),r[t][e||\"all\"]=!0}else this._updates.allPaintProps=!0;return this},serialize:function(){return c.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:c.mapObject(this.sources,function(t){return t.serialize()}),layers:this._order.map(function(t){return this._layers[t].serialize()},this)},function(t){return void 0!==t})},_updateLayer:function(t){return this._updates.layers[t.id]=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.changed=!0,this},_flattenRenderedFeatures:function(t){for(var e=[],r=this._order.length-1;r>=0;r--)for(var n=this._order[r],i=0;i<t.length;i++){var a=t[i][n];if(a)for(var o=0;o<a.length;o++)e.push(a[o])}return e},queryRenderedFeatures:function(t,e,r,n){e&&e.filter&&this._handleErrors(m.filter,\"queryRenderedFeatures.filter\",e.filter,!0);var i={};if(e&&e.layers)for(var a=0;a<e.layers.length;a++){var o=e.layers[a];i[this._layers[o].source]=!0}var s=[];for(var l in this.sources)if(!e.layers||i[l]){var u=this.sources[l],c=y.rendered(u,this._layers,t,e,r,n);s.push(c)}return this._flattenRenderedFeatures(s)},querySourceFeatures:function(t,e){e&&e.filter&&this._handleErrors(m.filter,\"querySourceFeatures.filter\",e.filter,!0);var r=this.sources[t];return r?y.source(r,e):[]},addSourceType:function(t,e,r){return v.getType(t)?r(new Error('A source type called \"'+t+'\" already exists.')):(v.setType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"load worker source\",{name:t,url:e.workerSourceURL},r):r(null,null))},_handleErrors:function(t,e,r,n,i){var a=n?m.throwErrors:m.emitErrors,o=t.call(m,c.extend({key:e,style:this.serialize(),value:r,styleSpec:b},i));return a.call(m,this,o)},_remove:function(){this.dispatcher.remove()},_reloadSource:function(t){this.sources[t].reload()},_updateSources:function(t){for(var e in this.sources)this.sources[e].update(t)},_redoPlacement:function(){for(var t in this.sources)this.sources[t].redoPlacement&&this.sources[t].redoPlacement()},_forwardSourceEvent:function(t){this.fire(\"source.\"+t.type,c.extend({source:t.target.getSource()},t))},_forwardTileEvent:function(t){this.fire(t.type,c.extend({source:t.target},t))},_forwardLayerEvent:function(t){this.fire(\"layer.\"+t.type,c.extend({layer:{id:t.target.id}},t))},\"get sprite json\":function(t,e){var r=this.sprite;r.loaded()?e(null,{sprite:r.data,retina:r.retina}):r.on(\"load\",function(){e(null,{sprite:r.data,retina:r.retina})})},\"get icons\":function(t,e){var r=this.sprite,n=this.spriteAtlas;r.loaded()?(n.setSprite(r),n.addIcons(t.icons,e)):r.on(\"load\",function(){n.setSprite(r),n.addIcons(t.icons,e)})},\"get glyphs\":function(t,e){function r(t,r,n){t&&console.error(t),a[n]=r,i--,0===i&&e(null,a)}var n=t.stacks,i=Object.keys(n).length,a={};for(var o in n)this.glyphSource.getSimpleGlyphs(o,n[o],t.uid,r)}})},{\"../render/line_atlas\":315,\"../source/query_features\":325,\"../source/source\":327,\"../source/source_cache\":328,\"../symbol/glyph_source\":360,\"../symbol/sprite_atlas\":365,\"../util/ajax\":386,\"../util/browser\":387,\"../util/dispatcher\":394,\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./animation_loop\":336,\"./image_sprite\":337,\"./style_function\":341,\"./style_layer\":342,\"./style_spec\":349,\"./validate_style\":351}],340:[function(t,e,r){\"use strict\";function n(t,e){this.value=s.clone(e),this.isFunction=a.isFunctionDefinition(e),this.json=JSON.stringify(this.value);var r=\"color\"===t.type&&this.value?o(this.value):e;if(this.calculate=a[t.function||\"piecewise-constant\"](r),this.isFeatureConstant=this.calculate.isFeatureConstant,this.isZoomConstant=this.calculate.isZoomConstant,\"piecewise-constant\"===t.function&&t.transition&&(this.calculate=i(this.calculate)),!this.isFeatureConstant&&!this.isZoomConstant){this.stopZoomLevels=[];for(var n=[],l=this.value.stops,u=0;u<this.value.stops.length;u++){var c=l[u][0].zoom;this.stopZoomLevels.indexOf(c)<0&&(this.stopZoomLevels.push(c),n.push([c,n.length]))}this.calculateInterpolationT=a.interpolated({stops:n,base:e.base})}}function i(t){return function(e,r){var n,i,a,o=e.zoom,s=e.zoomHistory,l=e.duration,u=o%1,c=Math.min((Date.now()-s.lastIntegerZoomTime)/l,1),h=1,f=1;return o>s.lastIntegerZoom?(n=u+(1-u)*c,h*=2,i=t({zoom:o-1},r),a=t({zoom:o},r)):(n=1-(1-c)*u,a=t({zoom:o},r),i=t({zoom:o+1},r),h/=2),void 0===i||void 0===a?void 0:{from:i,fromScale:h,to:a,toScale:f,t:n}}}var a=t(\"./style_function\"),o=t(\"./parse_color\"),s=t(\"../util/util\");e.exports=n},{\"../util/util\":403,\"./parse_color\":338,\"./style_function\":341}],341:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl-function\");r.interpolated=function(t){var e=n.interpolated(t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r[\"piecewise-constant\"]=function(t){var e=n[\"piecewise-constant\"](t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r.isFunctionDefinition=n.isFunctionDefinition},{\"mapbox-gl-function\":263}],342:[function(t,e,r){\"use strict\";function n(t,e){this.set(t,e)}function i(t){return t.value}var a=t(\"../util/util\"),o=t(\"./style_transition\"),s=t(\"./style_declaration\"),l=t(\"./style_spec\"),u=t(\"./validate_style\"),c=t(\"./parse_color\"),h=t(\"../util/evented\");e.exports=n;var f=\"-transition\";n.create=function(e,r){var n={background:t(\"./style_layer/background_style_layer\"),circle:t(\"./style_layer/circle_style_layer\"),fill:t(\"./style_layer/fill_style_layer\"),line:t(\"./style_layer/line_style_layer\"),raster:t(\"./style_layer/raster_style_layer\"),symbol:t(\"./style_layer/symbol_style_layer\")};return new n[(r||e).type](e,r)},n.prototype=a.inherit(h,{set:function(t,e){this.id=t.id,this.ref=t.ref,this.metadata=t.metadata,this.type=(e||t).type,this.source=(e||t).source,this.sourceLayer=(e||t)[\"source-layer\"],this.minzoom=(e||t).minzoom,this.maxzoom=(e||t).maxzoom,this.filter=(e||t).filter,this.paint={},this.layout={},this._paintSpecifications=l[\"paint_\"+this.type],this._layoutSpecifications=l[\"layout_\"+this.type],this._paintTransitions={},this._paintTransitionOptions={},this._paintDeclarations={},this._layoutDeclarations={},this._layoutFunctions={};var r,n;for(var i in t){var a=i.match(/^paint(?:\\.(.*))?$/);if(a){var o=a[1]||\"\";for(r in t[i])this.setPaintProperty(r,t[i][r],o)}}if(this.ref)this._layoutDeclarations=e._layoutDeclarations;else for(n in t.layout)this.setLayoutProperty(n,t.layout[n]);for(r in this._paintSpecifications)this.paint[r]=this.getPaintValue(r);for(n in this._layoutSpecifications)this._updateLayoutValue(n)},setLayoutProperty:function(t,e){if(null==e)delete this._layoutDeclarations[t];else{var r=\"layers.\"+this.id+\".layout.\"+t;if(this._handleErrors(u.layoutProperty,r,t,e))return;this._layoutDeclarations[t]=new s(this._layoutSpecifications[t],e)}this._updateLayoutValue(t)},getLayoutProperty:function(t){return this._layoutDeclarations[t]&&this._layoutDeclarations[t].value},getLayoutValue:function(t,e,r){var n=this._layoutSpecifications[t],i=this._layoutDeclarations[t];return i?i.calculate(e,r):n.default},setPaintProperty:function(t,e,r){var n=\"layers.\"+this.id+(r?'[\"paint.'+r+'\"].':\".paint.\")+t;if(a.endsWith(t,f))if(this._paintTransitionOptions[r||\"\"]||(this._paintTransitionOptions[r||\"\"]={}),null===e||void 0===e)delete this._paintTransitionOptions[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintTransitionOptions[r||\"\"][t]=e}else if(this._paintDeclarations[r||\"\"]||(this._paintDeclarations[r||\"\"]={}),null===e||void 0===e)delete this._paintDeclarations[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintDeclarations[r||\"\"][t]=new s(this._paintSpecifications[t],e)}},getPaintProperty:function(t,e){return e=e||\"\",a.endsWith(t,f)?this._paintTransitionOptions[e]&&this._paintTransitionOptions[e][t]:this._paintDeclarations[e]&&this._paintDeclarations[e][t]&&this._paintDeclarations[e][t].value},getPaintValue:function(t,e,r){var n=this._paintSpecifications[t],i=this._paintTransitions[t];return i?i.calculate(e,r):\"color\"===n.type&&n.default?c(n.default):n.default},getPaintValueStopZoomLevels:function(t){var e=this._paintTransitions[t];return e?e.declaration.stopZoomLevels:[]},getPaintInterpolationT:function(t,e){var r=this._paintTransitions[t];return r.declaration.calculateInterpolationT({zoom:e})},isPaintValueFeatureConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isFeatureConstant},isLayoutValueFeatureConstant:function(t){var e=this._layoutDeclarations[t];return!e||e.isFeatureConstant},isPaintValueZoomConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isZoomConstant},isHidden:function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||(\"none\"===this.layout.visibility||0===this.paint[this.type+\"-opacity\"]))},updatePaintTransitions:function(t,e,r,n){for(var i=a.extend({},this._paintDeclarations[\"\"]),o=0;o<t.length;o++)a.extend(i,this._paintDeclarations[t[o]]);var s;for(s in i)this._applyPaintDeclaration(s,i[s],e,r,n);for(s in this._paintTransitions)s in i||this._applyPaintDeclaration(s,null,e,r,n)},updatePaintTransition:function(t,e,r,n,i){for(var a=this._paintDeclarations[\"\"][t],o=0;o<e.length;o++){var s=this._paintDeclarations[e[o]];s&&s[t]&&(a=s[t])}this._applyPaintDeclaration(t,a,r,n,i)},recalculate:function(t,e){for(var r in this._paintTransitions)this.paint[r]=this.getPaintValue(r,{zoom:t,zoomHistory:e});for(var n in this._layoutFunctions)this.layout[n]=this.getLayoutValue(n,{zoom:t,zoomHistory:e})},serialize:function(t){var e={id:this.id,ref:this.ref,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom};for(var r in this._paintDeclarations){var n=\"\"===r?\"paint\":\"paint.\"+r;e[n]=a.mapObject(this._paintDeclarations[r],i)}return(!this.ref||t&&t.includeRefProperties)&&a.extend(e,{type:this.type,source:this.source,\"source-layer\":this.sourceLayer,filter:this.filter,layout:a.mapObject(this._layoutDeclarations,i)}),a.filterObject(e,function(t,e){return void 0!==t&&!(\"layout\"===e&&!Object.keys(t).length)})},_applyPaintDeclaration:function(t,e,r,n,i){var l=r.transition?this._paintTransitions[t]:void 0,u=this._paintSpecifications[t];if(null!==e&&void 0!==e||(e=new s(u,u.default)),!l||l.declaration.json!==e.json){var c=a.extend({duration:300,delay:0},n,this.getPaintProperty(t+f)),h=this._paintTransitions[t]=new o(u,e,l,c);h.instant()||(h.loopID=i.set(h.endTime-Date.now())),l&&i.cancel(l.loopID)}},_updateLayoutValue:function(t){var e=this._layoutDeclarations[t];e&&e.isFunction?this._layoutFunctions[t]=!0:(delete this._layoutFunctions[t],this.layout[t]=this.getLayoutValue(t))},_handleErrors:function(t,e,r,n){return u.emitErrors(this,t.call(u,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:l,style:{glyphs:!0,sprite:!0}}))}})},{\"../util/evented\":395,\"../util/util\":403,\"./parse_color\":338,\"./style_declaration\":340,\"./style_layer/background_style_layer\":343,\"./style_layer/circle_style_layer\":344,\"./style_layer/fill_style_layer\":345,\"./style_layer/line_style_layer\":346,\"./style_layer/raster_style_layer\":347,\"./style_layer/symbol_style_layer\":348,\"./style_spec\":349,\"./style_transition\":350,\"./validate_style\":351}],343:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],344:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],345:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValue.call(this,\"fill-color\",e,r):a.prototype.getPaintValue.call(this,t,e,r)},getPaintValueStopZoomLevels:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValueStopZoomLevels.call(this,\"fill-color\"):a.prototype.getPaintValueStopZoomLevels.call(this,arguments)},getPaintInterpolationT:function(t,e){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintInterpolationT.call(this,\"fill-color\",e):a.prototype.getPaintInterpolationT.call(this,t,e)},isPaintValueFeatureConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueFeatureConstant.call(this,\"fill-color\"):a.prototype.isPaintValueFeatureConstant.call(this,t)},isPaintValueZoomConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueZoomConstant.call(this,\"fill-color\"):a.prototype.isPaintValueZoomConstant.call(this,t)}}),e.exports=n},{\"../../util/util\":403,\"../style_layer\":342}],346:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){var n=a.prototype.getPaintValue.apply(this,arguments);if(n&&\"line-dasharray\"===t){var i=Math.floor(e.zoom);this._flooredZoom!==i&&(this._flooredZoom=i,this._flooredLineWidth=this.getPaintValue(\"line-width\",e,r)),n.fromScale*=this._flooredLineWidth,n.toScale*=this._flooredLineWidth}return n}})},{\"../../util/util\":403,\"../style_layer\":342}],347:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],348:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{isHidden:function(){if(a.prototype.isHidden.apply(this,arguments))return!0;var t=0===this.paint[\"text-opacity\"]||!this.layout[\"text-field\"],e=0===this.paint[\"icon-opacity\"]||!this.layout[\"icon-image\"];return!(!t||!e)},getLayoutValue:function(t,e,r){return(\"text-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"text-rotation-alignment\"))&&(\"icon-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"icon-rotation-alignment\"))?\"text-pitch-alignment\"!==t||this.getLayoutProperty(\"text-pitch-alignment\")?a.prototype.getLayoutValue.apply(this,arguments):this.getLayoutValue(\"text-rotation-alignment\"):\"map\"}})},{\"../../util/util\":403,\"../style_layer\":342}],349:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/reference/latest.min\")},{\"mapbox-gl-style-spec/reference/latest.min\":286}],350:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.declaration=e,this.startTime=this.endTime=(new Date).getTime(),\"piecewise-constant\"===t.function&&t.transition?this.interp=i:this.interp=o[t.type],this.oldTransition=r,this.duration=n.duration||0,this.delay=n.delay||0,this.instant()||(this.endTime=this.startTime+this.duration+this.delay,this.ease=a.easeCubicInOut),r&&r.endTime<=this.startTime&&delete r.oldTransition}function i(t,e,r){return void 0===(t&&t.to)||void 0===(e&&e.to)?void 0:{from:t.to,fromScale:t.toScale,to:e.to,toScale:e.toScale,t:r}}var a=t(\"../util/util\"),o=t(\"../util/interpolate\");e.exports=n,n.prototype.instant=function(){return!this.oldTransition||!this.interp||0===this.duration&&0===this.delay},n.prototype.calculate=function(t,e){var r=this.declaration.calculate(a.extend({},t,{duration:this.duration}),e);if(this.instant())return r;var n=t.time||Date.now();if(n<this.endTime){var i=this.oldTransition.calculate(a.extend({},t,{time:this.startTime}),e),o=this.ease((n-this.startTime-this.delay)/this.duration);r=this.interp(i,r,o)}return r}},{\"../util/interpolate\":397,\"../util/util\":403}],351:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/lib/validate_style.min\"),e.exports.emitErrors=function(t,e){if(e&&e.length){for(var r=0;r<e.length;r++)t.fire(\"error\",{error:new Error(e[r].message)});return!0}return!1},e.exports.throwErrors=function(t,e){if(e)for(var r=0;r<e.length;r++)throw new Error(e[r].message)}},{\"mapbox-gl-style-spec/lib/validate_style.min\":285}],352:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.x=t,this.y=e,this.angle=r,void 0!==n&&(this.segment=n)}var i=t(\"point-geometry\");e.exports=n,n.prototype=Object.create(i.prototype),n.prototype.clone=function(){return new n(this.x,this.y,this.angle,this.segment)}},{\"point-geometry\":442}],353:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){if(void 0===e.segment)return!0;for(var a=e,o=e.segment+1,s=0;s>-r/2;){if(o--,o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],u=0;s<r/2;){var c=t[o-1],h=t[o],f=t[o+1];if(!f)return!1;var d=c.angleTo(h)-h.angleTo(f);for(d=Math.abs((d+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:d}),u+=d;s-l[0].distance>n;)u-=l.shift().angleDelta;if(u>i)return!1;o++,s+=h.dist(f)}return!0}e.exports=n},{}],354:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){for(var o=[],s=0;s<t.length;s++)for(var l,u=t[s],c=0;c<u.length-1;c++){var h=u[c],f=u[c+1];h.x<e&&f.x<e||(h.x<e?h=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round():f.x<e&&(f=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round()),h.y<r&&f.y<r||(h.y<r?h=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round():f.y<r&&(f=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round()),h.x>=n&&f.x>=n||(h.x>=n?h=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round():f.x>=n&&(f=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round()),h.y>=a&&f.y>=a||(h.y>=a?h=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round():f.y>=a&&(f=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round()),l&&h.equals(l[l.length-1])||(l=[h],o.push(l)),l.push(f)))))}return o}var i=t(\"point-geometry\");e.exports=n},{\"point-geometry\":442}],355:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int16\",name:\"x1\"},{type:\"Int16\",name:\"y1\"},{type:\"Int16\",name:\"x2\"},{type:\"Int16\",name:\"y2\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"},{type:\"Int16\",name:\"bbox0\"},{type:\"Int16\",name:\"bbox1\"},{type:\"Int16\",name:\"bbox2\"},{type:\"Int16\",name:\"bbox3\"},{type:\"Float32\",name:\"placementScale\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"point-geometry\":442}],356:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c){var h=o.top*s-l,f=o.bottom*s+l,d=o.left*s-l,p=o.right*s+l;if(this.boxStartIndex=t.length,u){var g=f-h,m=p-d;if(g>0)if(g=Math.max(10*s,g),c){var v=e[r.segment+1].sub(e[r.segment])._unit()._mult(m),y=[r.sub(v),r.add(v)];this._addLineCollisionBoxes(t,y,r,0,m,g,n,i,a)}else this._addLineCollisionBoxes(t,e,r,r.segment,m,g,n,i,a)}else t.emplaceBack(r.x,r.y,d,h,p,f,1/0,n,i,a,0,0,0,0,0);this.boxEndIndex=t.length}e.exports=n,n.prototype._addLineCollisionBoxes=function(t,e,r,n,i,a,o,s,l){var u=a/2,c=Math.floor(i/u),h=-a/2,f=this.boxes,d=r,p=n+1,g=h;do{if(p--,p<0)return f;g-=e[p].dist(d),d=e[p]}while(g>-i/2);for(var m=e[p].dist(e[p+1]),v=0;v<c;v++){for(var y=-i/2+v*u;g+m<y;){if(g+=m,p++,p+1>=e.length)return f;m=e[p].dist(e[p+1])}var x=y-g,b=e[p],_=e[p+1],w=_.sub(b)._unit()._mult(x)._add(b)._round(),M=Math.max(Math.abs(y-h)-u/2,0),A=i/2/M;t.emplaceBack(w.x,w.y,-a/2,-a/2,a/2,a/2,A,o,s,l,0,0,0,0,0)}return f}},{}],357:[function(t,e,r){\"use strict\";function n(t,e,r){if(\"object\"==typeof t){var n=t;r=e,t=n.angle,e=n.pitch,this.grid=new o(n.grid),this.ignoredGrid=new o(n.ignoredGrid)}else this.grid=new o(a,12,6),this.ignoredGrid=new o(a,12,0);this.angle=t,this.pitch=e;var i=Math.sin(t),s=Math.cos(t);if(this.rotationMatrix=[s,-i,i,s],this.reverseRotationMatrix=[s,i,-i,s],this.yStretch=1/Math.cos(e/180*Math.PI),this.yStretch=Math.pow(this.yStretch,1.3),this.collisionBoxArray=r,0===r.length){r.emplaceBack();var l=32767;r.emplaceBack(0,0,0,-l,0,l,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(a,0,0,-l,0,l,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,0,-l,0,l,0,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,a,-l,0,l,0,l,0,0,0,0,0,0,0,0,0)}this.tempCollisionBox=r.get(0),this.edges=[r.get(1),r.get(2),r.get(3),r.get(4)]}var i=t(\"point-geometry\"),a=t(\"../data/bucket\").EXTENT,o=t(\"grid-index\");e.exports=n,n.prototype.serialize=function(){var t={angle:this.angle,pitch:this.pitch,grid:this.grid.toArrayBuffer(),ignoredGrid:this.ignoredGrid.toArrayBuffer()};return{data:t,transferables:[t.grid,t.ignoredGrid]}},n.prototype.minScale=.25,n.prototype.maxScale=2,n.prototype.placeCollisionFeature=function(t,e,r){for(var n=this.collisionBoxArray,a=this.minScale,o=this.rotationMatrix,s=this.yStretch,l=t.boxStartIndex;l<t.boxEndIndex;l++){var u=n.get(l),c=u.anchorPoint._matMult(o),h=c.x,f=c.y,d=h+u.x1,p=f+u.y1*s,g=h+u.x2,m=f+u.y2*s;if(u.bbox0=d,u.bbox1=p,u.bbox2=g,u.bbox3=m,!e)for(var v=this.grid.query(d,p,g,m),y=0;y<v.length;y++){var x=n.get(v[y]),b=x.anchorPoint._matMult(o);if(a=this.getPlacementScale(a,c,u,b,x),a>=this.maxScale)return a}if(r){var _;if(this.angle){var w=this.reverseRotationMatrix,M=new i(u.x1,u.y1).matMult(w),A=new i(u.x2,u.y1).matMult(w),k=new i(u.x1,u.y2).matMult(w),T=new i(u.x2,u.y2).matMult(w);_=this.tempCollisionBox,_.anchorPointX=u.anchorPoint.x,_.anchorPointY=u.anchorPoint.y,_.x1=Math.min(M.x,A.x,k.x,T.x),_.y1=Math.min(M.y,A.x,k.x,T.x),_.x2=Math.max(M.x,A.x,k.x,T.x),_.y2=Math.max(M.y,A.x,k.x,T.x),_.maxScale=u.maxScale}else _=u;for(var E=0;E<this.edges.length;E++){var S=this.edges[E];if(a=this.getPlacementScale(a,u.anchorPoint,_,S.anchorPoint,S),a>=this.maxScale)return a}}}return a},n.prototype.queryRenderedSymbols=function(t,e,r,n,a){var o={},s=[],l=this.collisionBoxArray,u=this.rotationMatrix,c=new i(t,e)._matMult(u),h=this.tempCollisionBox;h.anchorX=c.x,h.anchorY=c.y,h.x1=0,h.y1=0,h.x2=r-t,h.y2=n-e,h.maxScale=a,a=h.maxScale;for(var f=[c.x+h.x1/a,c.y+h.y1/a*this.yStretch,c.x+h.x2/a,c.y+h.y2/a*this.yStretch],d=this.grid.query(f[0],f[1],f[2],f[3]),p=this.ignoredGrid.query(f[0],f[1],f[2],f[3]),g=0;g<p.length;g++)d.push(p[g]);for(var m=0;m<d.length;m++){var v=l.get(d[m]),y=v.sourceLayerIndex,x=v.featureIndex;if(void 0===o[y]&&(o[y]={}),!o[y][x]){var b=v.anchorPoint.matMult(u),_=this.getPlacementScale(this.minScale,c,h,b,v);_>=a&&(o[y][x]=!0,s.push(d[m]))}}return s},n.prototype.getPlacementScale=function(t,e,r,n,i){var a=e.x-n.x,o=e.y-n.y,s=(i.x1-r.x2)/a,l=(i.x2-r.x1)/a,u=(i.y1-r.y2)*this.yStretch/o,c=(i.y2-r.y1)*this.yStretch/o;(isNaN(s)||isNaN(l))&&(s=l=1),(isNaN(u)||isNaN(c))&&(u=c=1);var h=Math.min(Math.max(s,l),Math.max(u,c)),f=i.maxScale,d=r.maxScale;return h>f&&(h=f),h>d&&(h=d),h>t&&h>=i.placementScale&&(t=h),t},n.prototype.insertCollisionFeature=function(t,e,r){for(var n=r?this.ignoredGrid:this.grid,i=this.collisionBoxArray,a=t.boxStartIndex;a<t.boxEndIndex;a++){var o=i.get(a);o.placementScale=e,e<this.maxScale&&n.insert(a,o.bbox0,o.bbox1,o.bbox2,o.bbox3)}}},{\"../data/bucket\":290,\"grid-index\":252,\"point-geometry\":442}],358:[function(t,e,r){\"use strict\";function n(t,e,r,n,a,o,s,l,u){var c=n?.6*o*s:0,h=Math.max(n?n.right-n.left:0,a?a.right-a.left:0),f=0===t[0].x||t[0].x===u||0===t[0].y||t[0].y===u;e-h*s<e/4&&(e=h*s+e/4);var d=2*o,p=f?e/2*l%e:(h/2+d)*s*l%e;return i(t,p,e,c,r,h*s,f,!1,u)}function i(t,e,r,n,l,u,c,h,f){for(var d=u/2,p=0,g=0;g<t.length-1;g++)p+=t[g].dist(t[g+1]);for(var m=0,v=e-r,y=[],x=0;x<t.length-1;x++){for(var b=t[x],_=t[x+1],w=b.dist(_),M=_.angleTo(b);v+r<m+w;){v+=r;var A=(v-m)/w,k=a(b.x,_.x,A),T=a(b.y,_.y,A);if(k>=0&&k<f&&T>=0&&T<f&&v-d>=0&&v+d<=p){var E=new o(k,T,M,x)._round();n&&!s(t,E,u,n,l)||y.push(E)}}m+=w}return h||y.length||c||(y=i(t,m/2,r,n,l,u,c,!0,f)),y}var a=t(\"../util/interpolate\"),o=t(\"../symbol/anchor\"),s=t(\"./check_max_angle\");e.exports=n},{\"../symbol/anchor\":352,\"../util/interpolate\":397,\"./check_max_angle\":353}],359:[function(t,e,r){\"use strict\";function n(){this.width=s,this.height=s,this.bin=new i(this.width,this.height),this.index={},this.ids={},this.data=new Uint8Array(this.width*this.height)}var i=t(\"shelf-pack\"),a=t(\"../util/util\"),o=4,s=128,l=2048;e.exports=n,n.prototype.getGlyphs=function(){var t,e,r,n={};for(var i in this.ids)t=i.split(\"#\"),e=t[0],r=t[1],n[e]||(n[e]=[]),n[e].push(r);return n},n.prototype.getRects=function(){var t,e,r,n={};for(var i in this.ids)t=i.split(\"#\"),e=t[0],r=t[1],n[e]||(n[e]={}),n[e][r]=this.index[i];return n},n.prototype.addGlyph=function(t,e,r,n){if(!r)return null;var i=e+\"#\"+r.id;if(this.index[i])return this.ids[i].indexOf(t)<0&&this.ids[i].push(t),this.index[i];if(!r.bitmap)return null;var o=r.width+2*n,s=r.height+2*n,l=1,u=o+2*l,c=s+2*l;u+=4-u%4,c+=4-c%4;var h=this.bin.packOne(u,c);if(h||(this.resize(),h=this.bin.packOne(u,c)),!h)return a.warnOnce(\"glyph bitmap overflow\"),null;this.index[i]=h,this.ids[i]=[t];for(var f=this.data,d=r.bitmap,p=0;p<s;p++)for(var g=this.width*(h.y+p+l)+h.x+l,m=o*p,v=0;v<o;v++)f[g+v]=d[m+v];return this.dirty=!0,\n",
+       "h},n.prototype.resize=function(){var t=this.width,e=this.height;if(!(t>=l||e>=l)){this.texture&&(this.gl&&this.gl.deleteTexture(this.texture),this.texture=null),this.width*=o,this.height*=o,this.bin.resize(this.width,this.height);for(var r=new ArrayBuffer(this.width*this.height),n=0;n<e;n++){var i=new Uint8Array(this.data.buffer,e*n,t),a=new Uint8Array(r,e*n*o,t);a.set(i)}this.data=new Uint8Array(r)}},n.prototype.bind=function(t){this.gl=t,this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,this.width,this.height,0,t.ALPHA,t.UNSIGNED_BYTE,null))},n.prototype.updateTexture=function(t){this.bind(t),this.dirty&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.ALPHA,t.UNSIGNED_BYTE,this.data),this.dirty=!1)}},{\"../util/util\":403,\"shelf-pack\":471}],360:[function(t,e,r){\"use strict\";function n(t){this.url=t&&o(t),this.atlases={},this.stacks={},this.loading={}}function i(t,e,r){var n=1;this.advance=t.advance,this.left=t.left-r-n,this.top=t.top+r+n,this.rect=e}function a(t,e,r,n){return n=n||\"abc\",r.replace(\"{s}\",n[t.length%n.length]).replace(\"{fontstack}\",t).replace(\"{range}\",e)}var o=t(\"../util/mapbox\").normalizeGlyphsURL,s=t(\"../util/ajax\").getArrayBuffer,l=t(\"../util/glyphs\"),u=t(\"../symbol/glyph_atlas\"),c=t(\"pbf\");e.exports=n,n.prototype.getSimpleGlyphs=function(t,e,r,n){void 0===this.stacks[t]&&(this.stacks[t]={}),void 0===this.atlases[t]&&(this.atlases[t]=new u);for(var a,o={},s=this.stacks[t],l=this.atlases[t],c=3,h={},f=0,d=0;d<e.length;d++){var p=e[d];if(a=Math.floor(p/256),s[a]){var g=s[a].glyphs[p],m=l.addGlyph(r,t,g,c);g&&(o[p]=new i(g,m,c))}else void 0===h[a]&&(h[a]=[],f++),h[a].push(p)}f||n(void 0,o,t);var v=function(e,a,s){if(!e)for(var u=this.stacks[t][a]=s.stacks[0],d=0;d<h[a].length;d++){var p=h[a][d],g=u.glyphs[p],m=l.addGlyph(r,t,g,c);g&&(o[p]=new i(g,m,c))}f--,f||n(void 0,o,t)}.bind(this);for(var y in h)this.loadRange(t,y,v)},n.prototype.loadRange=function(t,e,r){if(256*e>65535)return r(\"glyphs > 65535 not supported\");void 0===this.loading[t]&&(this.loading[t]={});var n=this.loading[t];if(n[e])n[e].push(r);else{n[e]=[r];var i=256*e+\"-\"+(256*e+255),o=a(t,i,this.url);s(o,function(t,r){for(var i=!t&&new l(new c(new Uint8Array(r))),a=0;a<n[e].length;a++)n[e][a](t,e,i);delete n[e]})}},n.prototype.getGlyphAtlas=function(t){return this.atlases[t]}},{\"../symbol/glyph_atlas\":359,\"../util/ajax\":386,\"../util/glyphs\":396,\"../util/mapbox\":400,pbf:436}],361:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){function n(n){c.push(t[n]),h.push(r[n]),f.push(e[n]),d++}function i(t,e,r){var n=u[t];return delete u[t],u[e]=n,h[n][0].pop(),h[n][0]=h[n][0].concat(r[0]),n}function a(t,e,r){var n=l[e];return delete l[e],l[t]=n,h[n][0].shift(),h[n][0]=r[0].concat(h[n][0]),n}function o(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}var s,l={},u={},c=[],h=[],f=[],d=0;for(s=0;s<t.length;s++){var p=r[s],g=e[s];if(g){var m=o(g,p),v=o(g,p,!0);if(m in u&&v in l&&u[m]!==l[v]){var y=a(m,v,p),x=i(m,v,h[y]);delete l[m],delete u[v],u[o(g,h[x],!0)]=x,h[y]=null}else m in u?i(m,v,p):v in l?a(m,v,p):(n(s),l[m]=d-1,u[v]=d-1)}else n(s)}return{features:c,textFeatures:f,geometries:h}}},{}],362:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u){this.anchorPoint=t,this.tl=e,this.tr=r,this.bl=n,this.br=i,this.tex=a,this.anchorAngle=o,this.glyphAngle=s,this.minScale=l,this.maxScale=u}function i(t,e,r,i,a,o,u,c,h){var f,d,p,g,m=e.image.rect,v=a.layout,y=1,x=e.left-y,b=x+m.w/e.image.pixelRatio,_=e.top-y,w=_+m.h/e.image.pixelRatio;if(\"none\"!==v[\"icon-text-fit\"]&&u){var M=b-x,A=w-_,k=v[\"text-size\"]/24,T=u.left*k,E=u.right*k,S=u.top*k,L=u.bottom*k,z=E-T,C=L-S,I=v[\"icon-text-fit-padding\"][0],P=v[\"icon-text-fit-padding\"][1],D=v[\"icon-text-fit-padding\"][2],R=v[\"icon-text-fit-padding\"][3],O=\"width\"===v[\"icon-text-fit\"]?.5*(C-A):0,F=\"height\"===v[\"icon-text-fit\"]?.5*(z-M):0,j=\"width\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?z:M,N=\"height\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?C:A;f=new s(T+F-R,S+O-I),d=new s(T+F+P+j,S+O-I),p=new s(T+F+P+j,S+O+D+N),g=new s(T+F-R,S+O+D+N)}else f=new s(x,_),d=new s(b,_),p=new s(b,w),g=new s(x,w);var B=a.getLayoutValue(\"icon-rotate\",c,h)*Math.PI/180;if(o){var U=i[t.segment];if(t.y===U.y&&t.x===U.x&&t.segment+1<i.length){var V=i[t.segment+1];B+=Math.atan2(t.y-V.y,t.x-V.x)+Math.PI}else B+=Math.atan2(t.y-U.y,t.x-U.x)}if(B){var q=Math.sin(B),H=Math.cos(B),G=[H,-q,q,H];f=f.matMult(G),d=d.matMult(G),g=g.matMult(G),p=p.matMult(G)}return[new n(new s(t.x,t.y),f,d,g,p,e.image.rect,0,0,l,1/0)]}function a(t,e,r,i,a,u){for(var c=a.layout[\"text-rotate\"]*Math.PI/180,h=a.layout[\"text-keep-upright\"],f=e.positionedGlyphs,d=[],p=0;p<f.length;p++){var g=f[p],m=g.glyph,v=m.rect;if(v){var y,x=(g.x+m.advance/2)*r,b=l;u?(y=[],b=o(y,t,x,i,t.segment,!0),h&&(b=Math.min(b,o(y,t,x,i,t.segment,!1)))):y=[{anchorPoint:new s(t.x,t.y),offset:0,angle:0,maxScale:1/0,minScale:l}];for(var _=g.x+m.left,w=g.y-m.top,M=_+v.w,A=w+v.h,k=new s(_,w),T=new s(M,w),E=new s(_,A),S=new s(M,A),L=0;L<y.length;L++){var z=y[L],C=k,I=T,P=E,D=S;if(c){var R=Math.sin(c),O=Math.cos(c),F=[O,-R,R,O];C=C.matMult(F),I=I.matMult(F),P=P.matMult(F),D=D.matMult(F)}var j=Math.max(z.minScale,b),N=(t.angle+z.offset+2*Math.PI)%(2*Math.PI),B=(z.angle+z.offset+2*Math.PI)%(2*Math.PI);d.push(new n(z.anchorPoint,C,I,P,D,v,N,B,j,z.maxScale))}}}return d}function o(t,e,r,n,i,a){var o=!a;r<0&&(a=!a),a&&i++;var u=new s(e.x,e.y),c=n[i],h=1/0;r=Math.abs(r);for(var f=l;;){var d=u.dist(c),p=r/d,g=Math.atan2(c.y-u.y,c.x-u.x);if(a||(g+=Math.PI),t.push({anchorPoint:u,offset:o?Math.PI:0,minScale:p,maxScale:h,angle:(g+2*Math.PI)%(2*Math.PI)}),p<=f)break;for(u=c;u.equals(c);)if(i+=a?1:-1,c=n[i],!c)return p;var m=c.sub(u)._unit();u=u.sub(m._mult(d)),h=p}return f}var s=t(\"point-geometry\");e.exports={getIconQuads:i,getGlyphQuads:a,SymbolQuad:n};var l=.5},{\"point-geometry\":442}],363:[function(t,e,r){\"use strict\";function n(t,e,r){for(var n=[],a=0,o=t.length;a<o;a++){var s=i(t[a].properties,e[\"text-field\"]);if(s){s=s.toString();var l=e[\"text-transform\"];\"uppercase\"===l?s=s.toLocaleUpperCase():\"lowercase\"===l&&(s=s.toLocaleLowerCase());for(var u=0;u<s.length;u++)r[s.charCodeAt(u)]=!0;n[a]=s}else n[a]=null}return n}var i=t(\"../util/token\");e.exports=n},{\"../util/token\":402}],364:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.codePoint=t,this.x=e,this.y=r,this.glyph=n}function i(t,e,r,n,i,a){this.positionedGlyphs=t,this.text=e,this.top=r,this.bottom=n,this.left=i,this.right=a}function a(t,e,r,a,s,l,u,c,h){for(var f=[],d=new i(f,t,h[1],h[1],h[0],h[0]),p=-17,g=0,m=p,v=0;v<t.length;v++){var y=t.charCodeAt(v),x=e[y];x&&(f.push(new n(y,g,m,x)),g+=x.advance+c)}return!!f.length&&(o(d,e,a,r,s,l,u,h),d)}function o(t,e,r,n,i,a,o,u){var c=null,d=0,p=0,g=0,m=0,v=t.positionedGlyphs;if(n)for(var y=0;y<v.length;y++){var x=v[y];if(x.x-=d,x.y+=r*g,x.x>n&&null!==c){var b=v[c+1].x;m=Math.max(b,m);for(var _=c+1;_<=y;_++)v[_].y+=r,v[_].x-=b;if(o){var w=c;h[v[c].codePoint]&&w--,s(v,e,p,w,o)}p=c+1,c=null,d+=b,g++}f[x.codePoint]&&(c=y)}var M=v[v.length-1],A=M.x+e[M.codePoint].advance;m=Math.max(m,A);var k=(g+1)*r;s(v,e,p,v.length-1,o),l(v,o,i,a,m,r,g,u),t.top+=-a*k,t.bottom=t.top+k,t.left+=-i*m,t.right=t.left+m}function s(t,e,r,n,i){for(var a=e[t[n].codePoint].advance,o=(t[n].x+a)*i,s=r;s<=n;s++)t[s].x-=o}function l(t,e,r,n,i,a,o,s){for(var l=(e-r)*i+s[0],u=(-n*(o+1)+.5)*a+s[1],c=0;c<t.length;c++)t[c].x+=l,t[c].y+=u}function u(t,e){if(!t||!t.rect)return null;var r=e[\"icon-offset\"][0],n=e[\"icon-offset\"][1],i=r-t.width/2,a=i+t.width,o=n-t.height/2,s=o+t.height;return new c(t,o,s,i,a)}function c(t,e,r,n,i){this.image=t,this.top=e,this.bottom=r,this.left=n,this.right=i}e.exports={shapeText:a,shapeIcon:u};var h={32:!0,8203:!0},f={32:!0,38:!0,43:!0,45:!0,47:!0,173:!0,183:!0,8203:!0,8208:!0,8211:!0}},{}],365:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.bin=new o(t,e),this.images={},this.data=!1,this.texture=0,this.filter=0,this.pixelRatio=1,this.dirty=!0}function i(t,e,r,n,i,a,o,s,l,u,c){var h,f,d=n*e+r,p=s*a+o;if(c)for(p-=a,f=-1;f<=u;f++,d=((f+u)%u+n)*e+r,p+=a)for(h=-1;h<=l;h++)i[p+h]=t[d+(h+l)%l];else for(f=0;f<u;f++,d+=e,p+=a)for(h=0;h<l;h++)i[p+h]=t[d+h]}function a(t,e,r,n,i){this.rect=t,this.width=e,this.height=r,this.sdf=n,this.pixelRatio=i}var o=t(\"shelf-pack\"),s=t(\"../util/browser\"),l=t(\"../util/util\");e.exports=n,n.prototype.allocateImage=function(t,e){t/=this.pixelRatio,e/=this.pixelRatio;var r=2,n=t+r+(4-(t+r)%4),i=e+r+(4-(e+r)%4),a=this.bin.packOne(n,i);return a?a:(l.warnOnce(\"SpriteAtlas out of space.\"),null)},n.prototype.getImage=function(t,e){if(this.images[t])return this.images[t];if(!this.sprite)return null;var r=this.sprite.getSpritePosition(t);if(!r.width||!r.height)return null;var n=this.allocateImage(r.width,r.height);if(!n)return null;var i=new a(n,r.width/r.pixelRatio,r.height/r.pixelRatio,r.sdf,r.pixelRatio/this.pixelRatio);return this.images[t]=i,this.copy(n,r,e),i},n.prototype.getPosition=function(t,e){var r=this.getImage(t,e),n=r&&r.rect;if(!n)return null;var i=r.width*r.pixelRatio,a=r.height*r.pixelRatio,o=1;return{size:[r.width,r.height],tl:[(n.x+o)/this.width,(n.y+o)/this.height],br:[(n.x+o+i)/this.width,(n.y+o+a)/this.height]}},n.prototype.allocate=function(){if(!this.data){var t=Math.floor(this.width*this.pixelRatio),e=Math.floor(this.height*this.pixelRatio);this.data=new Uint32Array(t*e);for(var r=0;r<this.data.length;r++)this.data[r]=0}},n.prototype.copy=function(t,e,r){if(this.sprite.img.data){var n=new Uint32Array(this.sprite.img.data.buffer);this.allocate();var a=this.data,o=1;i(n,this.sprite.img.width,e.x,e.y,a,this.width*this.pixelRatio,(t.x+o)*this.pixelRatio,(t.y+o)*this.pixelRatio,e.width,e.height,r),this.dirty=!0}},n.prototype.setSprite=function(t){t&&(this.pixelRatio=s.devicePixelRatio>1?2:1,this.canvas&&(this.canvas.width=this.width*this.pixelRatio,this.canvas.height=this.height*this.pixelRatio)),this.sprite=t},n.prototype.addIcons=function(t,e){for(var r=0;r<t.length;r++)this.getImage(t[r]);e(null,this.images)},n.prototype.bind=function(t,e){var r=!1;this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),r=!0);var n=e?t.LINEAR:t.NEAREST;n!==this.filter&&(t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,n),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,n),this.filter=n),this.dirty&&(this.allocate(),r?t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width*this.pixelRatio,this.height*this.pixelRatio,0,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)):t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width*this.pixelRatio,this.height*this.pixelRatio,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)),this.dirty=!1)}},{\"../util/browser\":387,\"../util/util\":403,\"shelf-pack\":471}],366:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Uint16\",name:\"textBoxStartIndex\"},{type:\"Uint16\",name:\"textBoxEndIndex\"},{type:\"Uint16\",name:\"iconBoxStartIndex\"},{type:\"Uint16\",name:\"iconBoxEndIndex\"},{type:\"Uint16\",name:\"glyphQuadStartIndex\"},{type:\"Uint16\",name:\"glyphQuadEndIndex\"},{type:\"Uint16\",name:\"iconQuadStartIndex\"},{type:\"Uint16\",name:\"iconQuadEndIndex\"},{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int8\",name:\"index\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"point-geometry\":442}],367:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=t(\"./quads\").SymbolQuad,s=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Float32\",name:\"tlX\"},{type:\"Float32\",name:\"tlY\"},{type:\"Float32\",name:\"trX\"},{type:\"Float32\",name:\"trY\"},{type:\"Float32\",name:\"blX\"},{type:\"Float32\",name:\"blY\"},{type:\"Float32\",name:\"brX\"},{type:\"Float32\",name:\"brY\"},{type:\"Int16\",name:\"texH\"},{type:\"Int16\",name:\"texW\"},{type:\"Int16\",name:\"texX\"},{type:\"Int16\",name:\"texY\"},{type:\"Float32\",name:\"anchorAngle\"},{type:\"Float32\",name:\"glyphAngle\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Float32\",name:\"minScale\"}]});i.extendAll(s.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)},get SymbolQuad(){return new o(this.anchorPoint,new a(this.tlX,this.tlY),new a(this.trX,this.trY),new a(this.blX,this.blY),new a(this.brX,this.brY),{x:this.texX,y:this.texY,h:this.texH,w:this.texW,height:this.texH,width:this.texW},this.anchorAngle,this.glyphAngle,this.minScale,this.maxScale)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"./quads\":362,\"point-geometry\":442}],368:[function(t,e,r){\"use strict\";var n=t(\"../util/dom\"),i=t(\"point-geometry\"),a={scrollZoom:t(\"./handler/scroll_zoom\"),boxZoom:t(\"./handler/box_zoom\"),dragRotate:t(\"./handler/drag_rotate\"),dragPan:t(\"./handler/drag_pan\"),keyboard:t(\"./handler/keyboard\"),doubleClickZoom:t(\"./handler/dblclick_zoom\"),touchZoomRotate:t(\"./handler/touch_zoom_rotate\")};e.exports=function(t,e){function r(t){v(\"mouseout\",t)}function o(e){t.stop(),_=n.mousePos(x,e),v(\"mousedown\",e)}function s(e){var r=t.dragRotate&&t.dragRotate.isActive();b&&!r&&v(\"contextmenu\",b),b=null,v(\"mouseup\",e)}function l(e){if(!(t.dragPan&&t.dragPan.isActive()||t.dragRotate&&t.dragRotate.isActive())){for(var r=e.toElement||e.target;r&&r!==x;)r=r.parentNode;r===x&&v(\"mousemove\",e)}}function u(e){t.stop(),y(\"touchstart\",e),!e.touches||e.touches.length>1||(w?(clearTimeout(w),w=null,v(\"dblclick\",e)):w=setTimeout(d,300))}function c(t){y(\"touchmove\",t)}function h(t){y(\"touchend\",t)}function f(t){y(\"touchcancel\",t)}function d(){w=null}function p(t){var e=n.mousePos(x,t);e.equals(_)&&v(\"click\",t)}function g(t){v(\"dblclick\",t),t.preventDefault()}function m(t){b=t,t.preventDefault()}function v(e,r){var i=n.mousePos(x,r);return t.fire(e,{lngLat:t.unproject(i),point:i,originalEvent:r})}function y(e,r){var a=n.touchPos(x,r),o=a.reduce(function(t,e,r,n){return t.add(e.div(n.length))},new i(0,0));return t.fire(e,{lngLat:t.unproject(o),point:o,lngLats:a.map(function(e){return t.unproject(e)},this),points:a,originalEvent:r})}var x=t.getCanvasContainer(),b=null,_=null,w=null;for(var M in a)t[M]=new a[M](t,e),e.interactive&&e[M]&&t[M].enable();x.addEventListener(\"mouseout\",r,!1),x.addEventListener(\"mousedown\",o,!1),x.addEventListener(\"mouseup\",s,!1),x.addEventListener(\"mousemove\",l,!1),x.addEventListener(\"touchstart\",u,!1),x.addEventListener(\"touchend\",h,!1),x.addEventListener(\"touchmove\",c,!1),x.addEventListener(\"touchcancel\",f,!1),x.addEventListener(\"click\",p,!1),x.addEventListener(\"dblclick\",g,!1),x.addEventListener(\"contextmenu\",m,!1)}},{\"../util/dom\":389,\"./handler/box_zoom\":374,\"./handler/dblclick_zoom\":375,\"./handler/drag_pan\":376,\"./handler/drag_rotate\":377,\"./handler/keyboard\":378,\"./handler/scroll_zoom\":379,\"./handler/touch_zoom_rotate\":380,\"point-geometry\":442}],369:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/interpolate\"),a=t(\"../util/browser\"),o=t(\"../geo/lng_lat\"),s=t(\"../geo/lng_lat_bounds\"),l=t(\"point-geometry\"),u=e.exports=function(){};n.extend(u.prototype,{getCenter:function(){return this.transform.center},setCenter:function(t,e){return this.jumpTo({center:t},e),this},panBy:function(t,e,r){return this.panTo(this.transform.center,n.extend({offset:l.convert(t).mult(-1)},e),r),this},panTo:function(t,e,r){return this.easeTo(n.extend({center:t},e),r)},getZoom:function(){return this.transform.zoom},setZoom:function(t,e){return this.jumpTo({zoom:t},e),this},zoomTo:function(t,e,r){return this.easeTo(n.extend({zoom:t},e),r)},zoomIn:function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},zoomOut:function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},getBearing:function(){return this.transform.bearing},setBearing:function(t,e){return this.jumpTo({bearing:t},e),this},rotateTo:function(t,e,r){return this.easeTo(n.extend({bearing:t},e),r)},resetNorth:function(t,e){return this.rotateTo(0,n.extend({duration:1e3},t),e),this},snapToNorth:function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},getPitch:function(){return this.transform.pitch},setPitch:function(t,e){return this.jumpTo({pitch:t},e),this},fitBounds:function(t,e,r){e=n.extend({padding:0,offset:[0,0],maxZoom:1/0},e),t=s.convert(t);var i=l.convert(e.offset),a=this.transform,o=a.project(t.getNorthWest()),u=a.project(t.getSouthEast()),c=u.sub(o),h=(a.width-2*e.padding-2*Math.abs(i.x))/c.x,f=(a.height-2*e.padding-2*Math.abs(i.y))/c.y;return e.center=a.unproject(o.add(u).div(2)),e.zoom=Math.min(a.scaleZoom(a.scale*Math.min(h,f)),e.maxZoom),e.bearing=0,e.linear?this.easeTo(e,r):this.flyTo(e,r)},jumpTo:function(t,e){this.stop();var r=this.transform,n=!1,i=!1,a=!1;return\"zoom\"in t&&r.zoom!==+t.zoom&&(n=!0,r.zoom=+t.zoom),\"center\"in t&&(r.center=o.convert(t.center)),\"bearing\"in t&&r.bearing!==+t.bearing&&(i=!0,r.bearing=+t.bearing),\"pitch\"in t&&r.pitch!==+t.pitch&&(a=!0,r.pitch=+t.pitch),this.fire(\"movestart\",e).fire(\"move\",e),n&&this.fire(\"zoomstart\",e).fire(\"zoom\",e).fire(\"zoomend\",e),i&&this.fire(\"rotate\",e),a&&this.fire(\"pitch\",e),this.fire(\"moveend\",e)},easeTo:function(t,e){this.stop(),t=n.extend({offset:[0,0],duration:500,easing:n.ease},t);var r,a,s=this.transform,u=l.convert(t.offset),c=this.getZoom(),h=this.getBearing(),f=this.getPitch(),d=\"zoom\"in t?+t.zoom:c,p=\"bearing\"in t?this._normalizeBearing(t.bearing,h):h,g=\"pitch\"in t?+t.pitch:f;\"center\"in t?(r=o.convert(t.center),a=s.centerPoint.add(u)):\"around\"in t?(r=o.convert(t.around),a=s.locationPoint(r)):(a=s.centerPoint.add(u),r=s.pointLocation(a));var m=s.locationPoint(r);return t.animate===!1&&(t.duration=0),this.zooming=d!==c,this.rotating=h!==p,this.pitching=g!==f,t.noMoveStart||this.fire(\"movestart\",e),this.zooming&&this.fire(\"zoomstart\",e),clearTimeout(this._onEaseEnd),this._ease(function(t){this.zooming&&(s.zoom=i(c,d,t)),this.rotating&&(s.bearing=i(h,p,t)),this.pitching&&(s.pitch=i(f,g,t)),s.setLocationAtPoint(r,m.add(a.sub(m)._mult(t))),this.fire(\"move\",e),this.zooming&&this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){t.delayEndEvents?this._onEaseEnd=setTimeout(this._easeToEnd.bind(this,e),t.delayEndEvents):this._easeToEnd(e)}.bind(this),t),this},_easeToEnd:function(t){var e=this.zooming;this.zooming=!1,this.rotating=!1,this.pitching=!1,e&&this.fire(\"zoomend\",t),this.fire(\"moveend\",t)},flyTo:function(t,e){function r(t){var e=(k*k-A*A+(t?-1:1)*L*L*T*T)/(2*(t?k:A)*L*T);return Math.log(Math.sqrt(e*e+1)-e)}function a(t){return(Math.exp(t)-Math.exp(-t))/2}function s(t){return(Math.exp(t)+Math.exp(-t))/2}function u(t){return a(t)/s(t)}this.stop(),t=n.extend({offset:[0,0],speed:1.2,curve:1.42,easing:n.ease},t);var c=this.transform,h=l.convert(t.offset),f=this.getZoom(),d=this.getBearing(),p=this.getPitch(),g=\"center\"in t?o.convert(t.center):this.getCenter(),m=\"zoom\"in t?+t.zoom:f,v=\"bearing\"in t?this._normalizeBearing(t.bearing,d):d,y=\"pitch\"in t?+t.pitch:p;Math.abs(c.center.lng)+Math.abs(g.lng)>180&&(c.center.lng>0&&g.lng<0?g.lng+=360:c.center.lng<0&&g.lng>0&&(g.lng-=360));var x=c.zoomScale(m-f),b=c.point,_=\"center\"in t?c.project(g).sub(h.div(x)):b,w=c.worldSize,M=t.curve,A=Math.max(c.width,c.height),k=A/x,T=_.sub(b).mag();if(\"minZoom\"in t){var E=n.clamp(Math.min(t.minZoom,f,m),c.minZoom,c.maxZoom),S=A/c.zoomScale(E-f);M=Math.sqrt(S/T*2)}var L=M*M,z=r(0),C=function(t){return s(z)/s(z+M*t)},I=function(t){return A*((s(z)*u(z+M*t)-a(z))/L)/T},P=(r(1)-z)/M;if(Math.abs(T)<1e-6){if(Math.abs(A-k)<1e-6)return this.easeTo(t);var D=k<A?-1:1;P=Math.abs(Math.log(k/A))/M,I=function(){return 0},C=function(t){return Math.exp(D*M*t)}}if(\"duration\"in t)t.duration=+t.duration;else{var R=\"screenSpeed\"in t?+t.screenSpeed/M:+t.speed;t.duration=1e3*P/R}return this.zooming=!0,d!==v&&(this.rotating=!0),p!==y&&(this.pitching=!0),this.fire(\"movestart\",e),this.fire(\"zoomstart\",e),this._ease(function(t){var r=t*P,n=I(r);c.zoom=f+c.scaleZoom(1/C(r)),c.center=c.unproject(b.add(_.sub(b).mult(n)),w),this.rotating&&(c.bearing=i(d,v,t)),this.pitching&&(c.pitch=i(p,y,t)),this.fire(\"move\",e),this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){this.zooming=!1,this.rotating=!1,this.pitching=!1,this.fire(\"zoomend\",e),this.fire(\"moveend\",e)},t),this},isEasing:function(){return!!this._abortFn},stop:function(){return this._abortFn&&(this._abortFn(),this._finishEase()),this},_ease:function(t,e,r){this._finishFn=e,this._abortFn=a.timed(function(e){t.call(this,r.easing(e)),1===e&&this._finishEase()},r.animate===!1?0:r.duration,this)},_finishEase:function(){delete this._abortFn;var t=this._finishFn;delete this._finishFn,t.call(this)},_normalizeBearing:function(t,e){t=n.wrap(t,-180,180);var r=Math.abs(t-e);return Math.abs(t-360-e)<r&&(t-=360),Math.abs(t+360-e)<r&&(t+=360),t},_updateEasing:function(t,e,r){var i;if(this.ease){var a=this.ease,o=(Date.now()-a.start)/a.duration,s=a.easing(o+.01)-a.easing(o),l=.27/Math.sqrt(s*s+1e-4)*.01,u=Math.sqrt(.0729-l*l);i=n.bezier(l,u,.25,1)}else i=r?n.bezier.apply(n,r):n.ease;return this.ease={start:(new Date).getTime(),to:Math.pow(2,e),duration:t,easing:i},i}})},{\"../geo/lng_lat\":300,\"../geo/lng_lat_bounds\":301,\"../util/browser\":387,\"../util/interpolate\":397,\"../util/util\":403,\"point-geometry\":442}],370:[function(t,e,r){\"use strict\";function n(t){o.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/dom\"),o=t(\"../../util/util\");e.exports=n,n.createAttributionString=function(t){var e=[];for(var r in t){var n=t[r];n.attribution&&e.indexOf(n.attribution)<0&&e.push(n.attribution)}return e.sort(function(t,e){return t.length-e.length}),e=e.filter(function(t,r){for(var n=r+1;n<e.length;n++)if(e[n].indexOf(t)>=0)return!1;return!0}),e.join(\" | \")},n.prototype=o.inherit(i,{options:{position:\"bottom-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl-attrib\",r=this._container=a.create(\"div\",e,t.getContainer());return this._update(),t.on(\"source.load\",this._update.bind(this)),t.on(\"source.change\",this._update.bind(this)),t.on(\"source.remove\",this._update.bind(this)),t.on(\"moveend\",this._updateEditLink.bind(this)),r},_update:function(){this._map.style&&(this._container.innerHTML=n.createAttributionString(this._map.style.sources)),this._editLink=this._container.getElementsByClassName(\"mapbox-improve-map\")[0],this._updateEditLink()},_updateEditLink:function(){if(this._editLink){var t=this._map.getCenter();this._editLink.href=\"https://www.mapbox.com/map-feedback/#/\"+t.lng+\"/\"+t.lat+\"/\"+Math.round(this._map.getZoom()+1)}}})},{\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],371:[function(t,e,r){\"use strict\";function n(){}var i=t(\"../../util/util\"),a=t(\"../../util/evented\");e.exports=n,n.prototype={addTo:function(t){this._map=t;var e=this._container=this.onAdd(t);if(this.options&&this.options.position){var r=this.options.position,n=t._controlCorners[r];e.className+=\" mapboxgl-ctrl\",r.indexOf(\"bottom\")!==-1?n.insertBefore(e,n.firstChild):n.appendChild(e)}return this},remove:function(){return this._container.parentNode.removeChild(this._container),this.onRemove&&this.onRemove(this._map),this._map=null,this}},i.extend(n.prototype,a)},{\"../../util/evented\":395,\"../../util/util\":403}],372:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/browser\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n;var l={enableHighAccuracy:!1,timeout:6e3};n.prototype=s.inherit(i,{options:{position:\"top-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl\",r=this._container=o.create(\"div\",e+\"-group\",t.getContainer());return a.supportsGeolocation?(this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._geolocateButton=o.create(\"button\",e+\"-icon \"+e+\"-geolocate\",this._container),this._geolocateButton.type=\"button\",this._geolocateButton.addEventListener(\"click\",this._onClickGeolocate.bind(this)),r):r},_onContextMenu:function(t){t.preventDefault()},_onClickGeolocate:function(){navigator.geolocation.getCurrentPosition(this._success.bind(this),this._error.bind(this),l),this._timeoutId=setTimeout(this._finish.bind(this),1e4)},_success:function(t){this._map.jumpTo({center:[t.coords.longitude,t.coords.latitude],zoom:17,bearing:0,pitch:0}),this.fire(\"geolocate\",t),this._finish()},_error:function(t){this.fire(\"error\",t),this._finish()},_finish:function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0}})},{\"../../util/browser\":387,\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],373:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}function i(t){return new MouseEvent(t.type,{button:2,buttons:2,bubbles:!0,cancelable:!0,detail:t.detail,view:t.view,screenX:t.screenX,screenY:t.screenY,clientX:t.clientX,clientY:t.clientY,movementX:t.movementX,movementY:t.movementY,ctrlKey:t.ctrlKey,shiftKey:t.shiftKey,altKey:t.altKey,metaKey:t.metaKey})}var a=t(\"./control\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n,n.prototype=s.inherit(a,{options:{position:\"top-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl\",r=this._container=o.create(\"div\",e+\"-group\",t.getContainer());return this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._zoomInButton=this._createButton(e+\"-icon \"+e+\"-zoom-in\",t.zoomIn.bind(t)),this._zoomOutButton=this._createButton(e+\"-icon \"+e+\"-zoom-out\",t.zoomOut.bind(t)),this._compass=this._createButton(e+\"-icon \"+e+\"-compass\",t.resetNorth.bind(t)),this._compassArrow=o.create(\"div\",\"arrow\",this._compass),this._compass.addEventListener(\"mousedown\",this._onCompassDown.bind(this)),this._onCompassMove=this._onCompassMove.bind(this),this._onCompassUp=this._onCompassUp.bind(this),t.on(\"rotate\",this._rotateCompassArrow.bind(this)),this._rotateCompassArrow(),this._el=t.getCanvasContainer(),r},_onContextMenu:function(t){t.preventDefault()},_onCompassDown:function(t){0===t.button&&(o.disableDrag(),document.addEventListener(\"mousemove\",this._onCompassMove),document.addEventListener(\"mouseup\",this._onCompassUp),this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassMove:function(t){0===t.button&&(this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassUp:function(t){0===t.button&&(document.removeEventListener(\"mousemove\",this._onCompassMove),document.removeEventListener(\"mouseup\",this._onCompassUp),o.enableDrag(),this._el.dispatchEvent(i(t)),t.stopPropagation())},_createButton:function(t,e){var r=o.create(\"button\",t,this._container);return r.type=\"button\",r.addEventListener(\"click\",function(){e()}),r},_rotateCompassArrow:function(){var t=\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassArrow.style.transform=t}})},{\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],374:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../geo/lng_lat_bounds\"),o=t(\"../../util/util\");e.exports=n,n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onMouseDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onMouseDown),this._enabled=!1)},_onMouseDown:function(t){t.shiftKey&&0===t.button&&(document.addEventListener(\"mousemove\",this._onMouseMove,!1),document.addEventListener(\"keydown\",this._onKeyDown,!1),document.addEventListener(\"mouseup\",this._onMouseUp,!1),i.disableDrag(),this._startPos=i.mousePos(this._el,t),this._active=!0)},_onMouseMove:function(t){var e=this._startPos,r=i.mousePos(this._el,t);this._box||(this._box=i.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var n=Math.min(e.x,r.x),a=Math.max(e.x,r.x),o=Math.min(e.y,r.y),s=Math.max(e.y,r.y);i.setTransform(this._box,\"translate(\"+n+\"px,\"+o+\"px)\"),this._box.style.width=a-n+\"px\",this._box.style.height=s-o+\"px\"},_onMouseUp:function(t){if(0===t.button){var e=this._startPos,r=i.mousePos(this._el,t),n=new a(this._map.unproject(e),this._map.unproject(r));this._finish(),e.x===r.x&&e.y===r.y?this._fireEvent(\"boxzoomcancel\",t):this._map.fitBounds(n,{linear:!0}).fire(\"boxzoomend\",{originalEvent:t,boxZoomBounds:n})}},_onKeyDown:function(t){27===t.keyCode&&(this._finish(),this._fireEvent(\"boxzoomcancel\",t))},_finish:function(){this._active=!1,document.removeEventListener(\"mousemove\",this._onMouseMove,!1),document.removeEventListener(\"keydown\",this._onKeyDown,!1),document.removeEventListener(\"mouseup\",this._onMouseUp,!1),this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(this._box.parentNode.removeChild(this._box),this._box=null),i.enableDrag()},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})}}},{\"../../geo/lng_lat_bounds\":301,\"../../util/dom\":389,\"../../util/util\":403}],375:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._onDblClick=this._onDblClick.bind(this)}e.exports=n,n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._map.on(\"dblclick\",this._onDblClick),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._map.off(\"dblclick\",this._onDblClick),this._enabled=!1)},_onDblClick:function(t){this._map.zoomTo(this._map.getZoom()+(t.originalEvent.shiftKey?-1:1),{around:t.lngLat},t)}}},{}],376:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=.3,s=a.bezier(0,0,o,1),l=1400,u=2500;n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._el.addEventListener(\"touchstart\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._el.removeEventListener(\"touchstart\",this._onDown),this._enabled=!1)},_onDown:function(t){this._ignoreEvent(t)||this.isActive()||(t.touches?(document.addEventListener(\"touchmove\",this._onMove),document.addEventListener(\"touchend\",this._onTouchEnd)):(document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onMouseUp)),this._active=!1,this._startPos=this._pos=i.mousePos(this._el,t),this._inertia=[[Date.now(),this._pos]])},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"dragstart\",t),this._fireEvent(\"movestart\",t));var e=i.mousePos(this._el,t),r=this._map;r.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),e]),r.transform.setLocationAtPoint(r.transform.pointLocation(this._pos),e),this._fireEvent(\"drag\",t),this._fireEvent(\"move\",t),this._pos=e,t.preventDefault()}},_onUp:function(t){if(this.isActive()){this._active=!1,this._fireEvent(\"dragend\",t),this._drainInertiaBuffer();var e=function(){this._fireEvent(\"moveend\",t)}.bind(this),r=this._inertia;if(r.length<2)return void e();var n=r[r.length-1],i=r[0],a=n[1].sub(i[1]),c=(n[0]-i[0])/1e3;if(0===c||n[1].equals(i[1]))return void e();var h=a.mult(o/c),f=h.mag();f>l&&(f=l,h._unit()._mult(f));var d=f/(u*o),p=h.mult(-d/2);this._map.panBy(p,{duration:1e3*d,easing:s,noMoveStart:!0},{originalEvent:t})}},_onMouseUp:function(t){this._ignoreEvent(t)||(this._onUp(t),\n",
+       "document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onMouseUp))},_onTouchEnd:function(t){this._ignoreEvent(t)||(this._onUp(t),document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onTouchEnd))},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragRotate&&e.dragRotate.isActive())return!0;if(t.touches)return t.touches.length>1;if(t.ctrlKey)return!0;var r=1,n=0;return\"mousemove\"===t.type?t.buttons&0===r:t.button!==n},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>0&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403}],377:[function(t,e,r){\"use strict\";function n(t,e){this._map=t,this._el=t.getCanvasContainer(),this._bearingSnap=e.bearingSnap,o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"point-geometry\"),o=t(\"../../util/util\");e.exports=n;var s=.25,l=o.bezier(0,0,s,1),u=180,c=720;n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._enabled=!1)},_onDown:function(t){if(!this._ignoreEvent(t)&&!this.isActive()){document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onUp),this._active=!1,this._inertia=[[Date.now(),this._map.getBearing()]],this._startPos=this._pos=i.mousePos(this._el,t),this._center=this._map.transform.centerPoint;var e=this._startPos.sub(this._center),r=e.mag();r<200&&(this._center=this._startPos.add(new a(-200,0)._rotate(e.angle()))),t.preventDefault()}},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"rotatestart\",t),this._fireEvent(\"movestart\",t));var e=this._map;e.stop();var r=this._pos,n=i.mousePos(this._el,t),a=this._center,o=r.sub(a).angleWith(n.sub(a))/Math.PI*180,s=e.getBearing()-o,l=this._inertia,u=l[l.length-1];this._drainInertiaBuffer(),l.push([Date.now(),e._normalizeBearing(s,u[1])]),e.transform.bearing=s,this._fireEvent(\"rotate\",t),this._fireEvent(\"move\",t),this._pos=n}},_onUp:function(t){if(!this._ignoreEvent(t)&&(document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onUp),this.isActive())){this._active=!1,this._fireEvent(\"rotateend\",t),this._drainInertiaBuffer();var e=this._map,r=e.getBearing(),n=this._inertia,i=function(){Math.abs(r)<this._bearingSnap?e.resetNorth({noMoveStart:!0},{originalEvent:t}):this._fireEvent(\"moveend\",t)}.bind(this);if(n.length<2)return void i();var a=n[0],o=n[n.length-1],h=n[n.length-2],f=e._normalizeBearing(r,h[1]),d=o[1]-a[1],p=d<0?-1:1,g=(o[0]-a[0])/1e3;if(0===d||0===g)return void i();var m=Math.abs(d*(s/g));m>u&&(m=u);var v=m/(c*s),y=p*m*(v/2);f+=y,Math.abs(e._normalizeBearing(f,0))<this._bearingSnap&&(f=e._normalizeBearing(0,f)),e.rotateTo(f,{duration:1e3*v,easing:l,noMoveStart:!0},{originalEvent:t})}},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragPan&&e.dragPan.isActive())return!0;if(t.touches)return t.touches.length>1;var r=t.ctrlKey?1:2,n=t.ctrlKey?0:2;return\"mousemove\"===t.type?t.buttons&0===r:t.button!==n},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>0&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403,\"point-geometry\":442}],378:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._onKeyDown=this._onKeyDown.bind(this)}e.exports=n;var i=80,a=2,o=5;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"keydown\",this._onKeyDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"keydown\",this._onKeyDown),this._enabled=!1)},_onKeyDown:function(t){if(!(t.altKey||t.ctrlKey||t.metaKey)){var e=this._map,r={originalEvent:t};if(!e.isEasing())switch(t.keyCode){case 61:case 107:case 171:case 187:e.zoomTo(Math.round(e.getZoom())+(t.shiftKey?2:1),r);break;case 189:case 109:case 173:e.zoomTo(Math.round(e.getZoom())-(t.shiftKey?2:1),r);break;case 37:t.shiftKey?e.easeTo({bearing:e.getBearing()-a},r):(t.preventDefault(),e.panBy([-i,0],r));break;case 39:t.shiftKey?e.easeTo({bearing:e.getBearing()+a},r):(t.preventDefault(),e.panBy([i,0],r));break;case 38:t.shiftKey?e.easeTo({pitch:e.getPitch()+o},r):(t.preventDefault(),e.panBy([0,-i],r));break;case 40:t.shiftKey?e.easeTo({pitch:Math.max(e.getPitch()-o,0)},r):(t.preventDefault(),e.panBy([0,i],r))}}}}},{}],379:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/browser\"),o=t(\"../../util/util\");e.exports=n;var s=\"undefined\"!=typeof navigator?navigator.userAgent.toLowerCase():\"\",l=s.indexOf(\"firefox\")!==-1,u=s.indexOf(\"safari\")!==-1&&s.indexOf(\"chrom\")===-1;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"wheel\",this._onWheel,!1),this._el.addEventListener(\"mousewheel\",this._onWheel,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"wheel\",this._onWheel),this._el.removeEventListener(\"mousewheel\",this._onWheel),this._enabled=!1)},_onWheel:function(t){var e;\"wheel\"===t.type?(e=t.deltaY,l&&t.deltaMode===window.WheelEvent.DOM_DELTA_PIXEL&&(e/=a.devicePixelRatio),t.deltaMode===window.WheelEvent.DOM_DELTA_LINE&&(e*=40)):\"mousewheel\"===t.type&&(e=-t.wheelDeltaY,u&&(e/=3));var r=a.now(),n=r-(this._time||0);this._pos=i.mousePos(this._el,t),this._time=r,0!==e&&e%4.000244140625===0?(this._type=\"wheel\",e=Math.floor(e/4)):0!==e&&Math.abs(e)<4?this._type=\"trackpad\":n>400?(this._type=null,this._lastValue=e,this._timeout=setTimeout(this._onTimeout,40)):this._type||(this._type=Math.abs(n*e)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,e+=this._lastValue)),t.shiftKey&&e&&(e/=4),this._type&&this._zoom(-e,t),t.preventDefault()},_onTimeout:function(){this._type=\"wheel\",this._zoom(-this._lastValue)},_zoom:function(t,e){if(0!==t){var r=this._map,n=2/(1+Math.exp(-Math.abs(t/100)));t<0&&0!==n&&(n=1/n);var i=r.ease?r.ease.to:r.transform.scale,a=r.transform.scaleZoom(i*n);r.zoomTo(a,{duration:0,around:r.unproject(this._pos),delayEndEvents:200},{originalEvent:e})}}}},{\"../../util/browser\":387,\"../../util/dom\":389,\"../../util/util\":403}],380:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=.15,s=a.bezier(0,0,o,1),l=12,u=2.5,c=.15,h=4;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"touchstart\",this._onStart,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"touchstart\",this._onStart),this._enabled=!1)},disableRotation:function(){this._rotationDisabled=!0},enableRotation:function(){this._rotationDisabled=!1},_onStart:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]);this._startVec=e.sub(r),this._startScale=this._map.transform.scale,this._startBearing=this._map.transform.bearing,this._gestureIntent=void 0,this._inertia=[],document.addEventListener(\"touchmove\",this._onMove,!1),document.addEventListener(\"touchend\",this._onEnd,!1)}},_onMove:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]),n=e.add(r).div(2),a=e.sub(r),o=a.mag()/this._startVec.mag(),s=this._rotationDisabled?0:180*a.angleWith(this._startVec)/Math.PI,l=this._map;if(this._gestureIntent){var u={duration:0,around:l.unproject(n)};\"rotate\"===this._gestureIntent&&(u.bearing=this._startBearing+s),\"zoom\"!==this._gestureIntent&&\"rotate\"!==this._gestureIntent||(u.zoom=l.transform.scaleZoom(this._startScale*o)),l.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),o,n]),l.easeTo(u,{originalEvent:t})}else{var f=Math.abs(1-o)>c,d=Math.abs(s)>h;d?this._gestureIntent=\"rotate\":f&&(this._gestureIntent=\"zoom\"),this._gestureIntent&&(this._startVec=a,this._startScale=l.transform.scale,this._startBearing=l.transform.bearing)}t.preventDefault()}},_onEnd:function(t){document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onEnd),this._drainInertiaBuffer();var e=this._inertia,r=this._map;if(e.length<2)return void r.snapToNorth({},{originalEvent:t});var n=e[e.length-1],i=e[0],a=r.transform.scaleZoom(this._startScale*n[1]),c=r.transform.scaleZoom(this._startScale*i[1]),h=a-c,f=(n[0]-i[0])/1e3,d=n[2];if(0===f||a===c)return void r.snapToNorth({},{originalEvent:t});var p=h*o/f;Math.abs(p)>u&&(p=p>0?u:-u);var g=1e3*Math.abs(p/(l*o)),m=a+p*g/2e3;m<0&&(m=0),r.easeTo({zoom:m,duration:g,easing:s,around:r.unproject(d)},{originalEvent:t})},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>2&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403}],381:[function(t,e,r){\"use strict\";function n(){i.bindAll([\"_onHashChange\",\"_updateHash\"],this)}e.exports=n;var i=t(\"../util/util\");n.prototype={addTo:function(t){return this._map=t,window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},remove:function(){return window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),delete this._map,this},_onHashChange:function(){var t=location.hash.replace(\"#\",\"\").split(\"/\");return t.length>=3&&(this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:+(t[3]||0)}),!0)},_updateHash:function(){var t=this._map.getCenter(),e=this._map.getZoom(),r=this._map.getBearing(),n=Math.max(0,Math.ceil(Math.log(e)/Math.LN2)),i=\"#\"+Math.round(100*e)/100+\"/\"+t.lat.toFixed(n)+\"/\"+t.lng.toFixed(n)+(r?\"/\"+Math.round(10*r)/10:\"\");window.history.replaceState(\"\",\"\",i)}}},{\"../util/util\":403}],382:[function(t,e,r){\"use strict\";function n(t){t.parentNode&&t.parentNode.removeChild(t)}var i=t(\"../util/canvas\"),a=t(\"../util/util\"),o=t(\"../util/browser\"),s=t(\"../util/browser\").window,l=t(\"../util/evented\"),u=t(\"../util/dom\"),c=t(\"../style/style\"),h=t(\"../style/animation_loop\"),f=t(\"../render/painter\"),d=t(\"../geo/transform\"),p=t(\"./hash\"),g=t(\"./bind_handlers\"),m=t(\"./camera\"),v=t(\"../geo/lng_lat\"),y=t(\"../geo/lng_lat_bounds\"),x=t(\"point-geometry\"),b=t(\"./control/attribution\"),_=0,w=20,M={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:_,maxZoom:w,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,bearingSnap:7,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,workerCount:Math.max(o.hardwareConcurrency-1,1)},A=e.exports=function(t){if(t=a.extend({},M,t),t.workerCount<1)throw new Error(\"workerCount must an integer greater than or equal to 1.\");this._interactive=t.interactive,this._failIfMajorPerformanceCaveat=t.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=t.preserveDrawingBuffer,this._trackResize=t.trackResize,this._workerCount=t.workerCount,this._bearingSnap=t.bearingSnap,\"string\"==typeof t.container?this._container=document.getElementById(t.container):this._container=t.container,this.animationLoop=new h,this.transform=new d(t.minZoom,t.maxZoom),t.maxBounds&&this.setMaxBounds(t.maxBounds),a.bindAll([\"_forwardStyleEvent\",\"_forwardSourceEvent\",\"_forwardLayerEvent\",\"_forwardTileEvent\",\"_onStyleLoad\",\"_onStyleChange\",\"_onSourceAdd\",\"_onSourceRemove\",\"_onSourceUpdate\",\"_onWindowOnline\",\"_onWindowResize\",\"_update\",\"_render\"],this),this._setupContainer(),this._setupPainter(),this.on(\"move\",this._update.bind(this,!1)),this.on(\"zoom\",this._update.bind(this,!0)),this.on(\"moveend\",function(){this.animationLoop.set(300),this._rerender()}.bind(this)),\"undefined\"!=typeof s&&(s.addEventListener(\"online\",this._onWindowOnline,!1),s.addEventListener(\"resize\",this._onWindowResize,!1)),g(this,t),this._hash=t.hash&&(new p).addTo(this),this._hash&&this._hash._onHashChange()||this.jumpTo({center:t.center,zoom:t.zoom,bearing:t.bearing,pitch:t.pitch}),this.stacks={},this._classes=[],this.resize(),t.classes&&this.setClasses(t.classes),t.style&&this.setStyle(t.style),t.attributionControl&&this.addControl(new b(t.attributionControl));var e=this.fire.bind(this,\"error\");this.on(\"style.error\",e),this.on(\"source.error\",e),this.on(\"tile.error\",e),this.on(\"layer.error\",e)};a.extend(A.prototype,l),a.extend(A.prototype,m.prototype),a.extend(A.prototype,{addControl:function(t){return t.addTo(this),this},addClass:function(t,e){return this._classes.indexOf(t)>=0||\"\"===t?this:(this._classes.push(t),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},removeClass:function(t,e){var r=this._classes.indexOf(t);return r<0||\"\"===t?this:(this._classes.splice(r,1),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},setClasses:function(t,e){for(var r={},n=0;n<t.length;n++)\"\"!==t[n]&&(r[t[n]]=!0);return this._classes=Object.keys(r),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0)},hasClass:function(t){return this._classes.indexOf(t)>=0},getClasses:function(){return this._classes},resize:function(){var t=0,e=0;return this._container&&(t=this._container.offsetWidth||400,e=this._container.offsetHeight||300),this._canvas.resize(t,e),this.transform.resize(t,e),this.painter.resize(t,e),this.fire(\"movestart\").fire(\"move\").fire(\"resize\").fire(\"moveend\")},getBounds:function(){var t=new y(this.transform.pointLocation(new x(0,0)),this.transform.pointLocation(this.transform.size));return(this.transform.angle||this.transform.pitch)&&(t.extend(this.transform.pointLocation(new x(this.transform.size.x,0))),t.extend(this.transform.pointLocation(new x(0,this.transform.size.y)))),t},setMaxBounds:function(t){if(t){var e=y.convert(t);this.transform.lngRange=[e.getWest(),e.getEast()],this.transform.latRange=[e.getSouth(),e.getNorth()],this.transform._constrain(),this._update()}else null!==t&&void 0!==t||(this.transform.lngRange=[],this.transform.latRange=[],this._update());return this},setMinZoom:function(t){if(t=null===t||void 0===t?_:t,t>=_&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between \"+_+\" and the current maxZoom, inclusive\")},setMaxZoom:function(t){if(t=null===t||void 0===t?w:t,t>=this.transform.minZoom&&t<=w)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be between the current minZoom and \"+w+\", inclusive\")},project:function(t){return this.transform.locationPoint(v.convert(t))},unproject:function(t){return this.transform.pointLocation(x.convert(t))},queryRenderedFeatures:function(){function t(t){return t instanceof x||Array.isArray(t)}var e,r={};return 2===arguments.length?(e=arguments[0],r=arguments[1]):1===arguments.length&&t(arguments[0])?e=arguments[0]:1===arguments.length&&(r=arguments[0]),this.style.queryRenderedFeatures(this._makeQueryGeometry(e),r,this.transform.zoom,this.transform.angle)},_makeQueryGeometry:function(t){void 0===t&&(t=[x.convert([0,0]),x.convert([this.transform.width,this.transform.height])]);var e,r=t instanceof x||\"number\"==typeof t[0];if(r){var n=x.convert(t);e=[n]}else{var i=[x.convert(t[0]),x.convert(t[1])];e=[i[0],new x(i[1].x,i[0].y),i[1],new x(i[0].x,i[1].y),i[0]]}return e=e.map(function(t){return this.transform.pointCoordinate(t)}.bind(this))},querySourceFeatures:function(t,e){return this.style.querySourceFeatures(t,e)},setStyle:function(t){return this.style&&(this.style.off(\"load\",this._onStyleLoad).off(\"error\",this._forwardStyleEvent).off(\"change\",this._onStyleChange).off(\"source.add\",this._onSourceAdd).off(\"source.remove\",this._onSourceRemove).off(\"source.load\",this._onSourceUpdate).off(\"source.error\",this._forwardSourceEvent).off(\"source.change\",this._onSourceUpdate).off(\"layer.add\",this._forwardLayerEvent).off(\"layer.remove\",this._forwardLayerEvent).off(\"layer.error\",this._forwardLayerEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.load\",this._update).off(\"tile.error\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent)._remove(),this.off(\"rotate\",this.style._redoPlacement),this.off(\"pitch\",this.style._redoPlacement)),t?(t instanceof c?this.style=t:this.style=new c(t,this.animationLoop,this._workerCount),this.style.on(\"load\",this._onStyleLoad).on(\"error\",this._forwardStyleEvent).on(\"change\",this._onStyleChange).on(\"source.add\",this._onSourceAdd).on(\"source.remove\",this._onSourceRemove).on(\"source.load\",this._onSourceUpdate).on(\"source.error\",this._forwardSourceEvent).on(\"source.change\",this._onSourceUpdate).on(\"layer.add\",this._forwardLayerEvent).on(\"layer.remove\",this._forwardLayerEvent).on(\"layer.error\",this._forwardLayerEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.load\",this._update).on(\"tile.error\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this.on(\"rotate\",this.style._redoPlacement),this.on(\"pitch\",this.style._redoPlacement),this):(this.style=null,this)},getStyle:function(){if(this.style)return this.style.serialize()},addSource:function(t,e){return this.style.addSource(t,e),this._update(!0),this},addSourceType:function(t,e,r){return this.style.addSourceType(t,e,r)},removeSource:function(t){return this.style.removeSource(t),this._update(!0),this},getSource:function(t){return this.style.getSource(t)},addLayer:function(t,e){return this.style.addLayer(t,e),this._update(!0),this},removeLayer:function(t){return this.style.removeLayer(t),this._update(!0),this},getLayer:function(t){return this.style.getLayer(t)},setFilter:function(t,e){return this.style.setFilter(t,e),this._update(!0),this},setLayerZoomRange:function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0),this},getFilter:function(t){return this.style.getFilter(t)},setPaintProperty:function(t,e,r,n){return this.style.setPaintProperty(t,e,r,n),this._update(!0),this},getPaintProperty:function(t,e,r){return this.style.getPaintProperty(t,e,r)},setLayoutProperty:function(t,e,r){return this.style.setLayoutProperty(t,e,r),this._update(!0),this},getLayoutProperty:function(t,e){return this.style.getLayoutProperty(t,e)},getContainer:function(){return this._container},getCanvasContainer:function(){return this._canvasContainer},getCanvas:function(){return this._canvas.getElement()},_setupContainer:function(){var t=this._container;t.classList.add(\"mapboxgl-map\");var e=this._canvasContainer=u.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=new i(this,e);var r=this._controlContainer=u.create(\"div\",\"mapboxgl-control-container\",t),n=this._controlCorners={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(function(t){n[t]=u.create(\"div\",\"mapboxgl-ctrl-\"+t,r)})},_setupPainter:function(){var t=this._canvas.getWebGLContext({failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer});return t?void(this.painter=new f(t,this.transform)):void this.fire(\"error\",{error:new Error(\"Failed to initialize WebGL\")})},_contextLost:function(t){t.preventDefault(),this._frameId&&o.cancelFrame(this._frameId),this.fire(\"webglcontextlost\",{originalEvent:t})},_contextRestored:function(t){this._setupPainter(),this.resize(),this._update(),this.fire(\"webglcontextrestored\",{originalEvent:t})},loaded:function(){return!this._styleDirty&&!this._sourcesDirty&&!(!this.style||!this.style.loaded())},_update:function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this._rerender(),this):this},_render:function(){try{this.style&&this._styleDirty&&(this._styleDirty=!1,this.style.update(this._classes,this._classOptions),this._classOptions=null,this.style._recalculate(this.transform.zoom)),this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.painter.render(this.style,{debug:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,vertices:this.vertices,rotating:this.rotating,zooming:this.zooming}),this.fire(\"render\"),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(\"load\")),this._frameId=null,this.animationLoop.stopped()||(this._styleDirty=!0),(this._sourcesDirty||this._repaint||this._styleDirty)&&this._rerender()}catch(t){this.fire(\"error\",{error:t})}return this},remove:function(){this._hash&&this._hash.remove(),o.cancelFrame(this._frameId),this.setStyle(null),\"undefined\"!=typeof s&&s.removeEventListener(\"resize\",this._onWindowResize,!1);var t=this.painter.gl.getExtension(\"WEBGL_lose_context\");t&&t.loseContext(),n(this._canvasContainer),n(this._controlContainer),this._container.classList.remove(\"mapboxgl-map\")},_rerender:function(){this.style&&!this._frameId&&(this._frameId=o.frame(this._render))},_forwardStyleEvent:function(t){this.fire(\"style.\"+t.type,a.extend({style:t.target},t))},_forwardSourceEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_forwardLayerEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_forwardTileEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_onStyleLoad:function(t){this.transform.unmodified&&this.jumpTo(this.style.stylesheet),this.style.update(this._classes,{transition:!1}),this._forwardStyleEvent(t)},_onStyleChange:function(t){this._update(!0),this._forwardStyleEvent(t)},_onSourceAdd:function(t){var e=t.source;e.onAdd&&e.onAdd(this),this._forwardSourceEvent(t)},_onSourceRemove:function(t){var e=t.source;e.onRemove&&e.onRemove(this),this._forwardSourceEvent(t)},_onSourceUpdate:function(t){this._update(),this._forwardSourceEvent(t)},_onWindowOnline:function(){this._update()},_onWindowResize:function(){this._trackResize&&this.stop().resize()._update()}}),a.extendAll(A.prototype,{_showTileBoundaries:!1,get showTileBoundaries(){return this._showTileBoundaries},set showTileBoundaries(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},_showCollisionBoxes:!1,get showCollisionBoxes(){return this._showCollisionBoxes},set showCollisionBoxes(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,this.style._redoPlacement())},_showOverdrawInspector:!1,get showOverdrawInspector(){return this._showOverdrawInspector},set showOverdrawInspector(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},_repaint:!1,get repaint(){return this._repaint},set repaint(t){this._repaint=t,this._update()},_vertices:!1,get vertices(){return this._vertices},set vertices(t){this._vertices=t,this._update()}})},{\"../geo/lng_lat\":300,\"../geo/lng_lat_bounds\":301,\"../geo/transform\":302,\"../render/painter\":316,\"../style/animation_loop\":336,\"../style/style\":339,\"../util/browser\":387,\"../util/canvas\":388,\"../util/dom\":389,\"../util/evented\":395,\"../util/util\":403,\"./bind_handlers\":368,\"./camera\":369,\"./control/attribution\":370,\"./hash\":381,\"point-geometry\":442}],383:[function(t,e,r){\"use strict\";function n(t,e){t||(t=i.create(\"div\")),t.classList.add(\"mapboxgl-marker\"),this._el=t,this._offset=o.convert(e&&e.offset||[0,0]),this._update=this._update.bind(this)}e.exports=n;var i=t(\"../util/dom\"),a=t(\"../geo/lng_lat\"),o=t(\"point-geometry\");n.prototype={addTo:function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._el),t.on(\"move\",this._update),this._update(),this},remove:function(){this._map&&(this._map.off(\"move\",this._update),this._map=null);var t=this._el.parentNode;return t&&t.removeChild(this._el),this},getLngLat:function(){return this._lngLat},setLngLat:function(t){return this._lngLat=a.convert(t),this._update(),this},getElement:function(){return this._el},_update:function(){if(this._map){var t=this._map.project(this._lngLat)._add(this._offset);i.setTransform(this._el,\"translate(\"+t.x+\"px,\"+t.y+\"px)\")}}}},{\"../geo/lng_lat\":300,\"../util/dom\":389,\"point-geometry\":442}],384:[function(t,e,r){\"use strict\";function n(t){i.setOptions(this,t),i.bindAll([\"_update\",\"_onClickClose\"],this)}e.exports=n;var i=t(\"../util/util\"),a=t(\"../util/evented\"),o=t(\"../util/dom\"),s=t(\"../geo/lng_lat\");n.prototype=i.inherit(a,{options:{closeButton:!0,closeOnClick:!0},addTo:function(t){return this._map=t,this._map.on(\"move\",this._update),this.options.closeOnClick&&this._map.on(\"click\",this._onClickClose),this._update(),this},remove:function(){return this._content&&this._content.parentNode&&this._content.parentNode.removeChild(this._content),this._container&&(this._container.parentNode.removeChild(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"click\",this._onClickClose),delete this._map),this.fire(\"close\"),this},getLngLat:function(){return this._lngLat},setLngLat:function(t){return this._lngLat=s.convert(t),this._update(),this},setText:function(t){return this.setDOMContent(document.createTextNode(t))},setHTML:function(t){var e,r=document.createDocumentFragment(),n=document.createElement(\"body\");for(n.innerHTML=t;;){if(e=n.firstChild,!e)break;r.appendChild(e)}return this.setDOMContent(r)},setDOMContent:function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},_createContent:function(){this._content&&this._content.parentNode&&this._content.parentNode.removeChild(this._content),this._content=o.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=o.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClickClose))},_update:function(){if(this._map&&this._lngLat&&this._content){this._container||(this._container=o.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=o.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content));var t=this._map.project(this._lngLat).round(),e=this.options.anchor;if(!e){var r=this._container.offsetWidth,n=this._container.offsetHeight;e=t.y<n?[\"top\"]:t.y>this._map.transform.height-n?[\"bottom\"]:[],t.x<r/2?e.push(\"left\"):t.x>this._map.transform.width-r/2&&e.push(\"right\"),e=0===e.length?\"bottom\":e.join(\"-\")}var i={top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"},a=this._container.classList;for(var s in i)a.remove(\"mapboxgl-popup-anchor-\"+s);a.add(\"mapboxgl-popup-anchor-\"+e),o.setTransform(this._container,i[e]+\" translate(\"+t.x+\"px,\"+t.y+\"px)\")}},_onClickClose:function(){this.remove()}})},{\"../geo/lng_lat\":300,\"../util/dom\":389,\"../util/evented\":395,\"../util/util\":403}],385:[function(t,e,r){\"use strict\";function n(t,e){this.target=t,this.parent=e,this.callbacks={},this.callbackID=0,this.receive=this.receive.bind(this),this.target.addEventListener(\"message\",this.receive,!1)}e.exports=n,n.prototype.receive=function(t){function e(t,e,r){this.postMessage({type:\"<response>\",id:String(i),error:t?String(t):null,data:e},r)}var r,n=t.data,i=n.id;if(\"<response>\"===n.type)r=this.callbacks[n.id],delete this.callbacks[n.id],r&&r(n.error||null,n.data);else if(\"undefined\"!=typeof n.id&&this.parent[n.type])this.parent[n.type](n.data,e.bind(this));else if(\"undefined\"!=typeof n.id&&this.parent.workerSources){var a=n.type.split(\".\");this.parent.workerSources[a[0]][a[1]](n.data,e.bind(this))}else this.parent[n.type](n.data)},n.prototype.send=function(t,e,r,n){var i=null;r&&(this.callbacks[i=this.callbackID++]=r),this.postMessage({type:t,id:String(i),data:e},n)},n.prototype.postMessage=function(t,e){this.target.postMessage(t,e)}},{}],386:[function(t,e,r){\"use strict\";function n(t){var e=document.createElement(\"a\");return e.href=t,e.protocol===document.location.protocol&&e.host===document.location.host}r.getJSON=function(t,e){var r=new XMLHttpRequest;return r.open(\"GET\",t,!0),r.setRequestHeader(\"Accept\",\"application/json\"),r.onerror=function(t){e(t)},r.onload=function(){if(r.status>=200&&r.status<300&&r.response){var t;try{t=JSON.parse(r.response)}catch(t){return e(t)}e(null,t)}else e(new Error(r.statusText))},r.send(),r},r.getArrayBuffer=function(t,e){var r=new XMLHttpRequest;return r.open(\"GET\",t,!0),r.responseType=\"arraybuffer\",r.onerror=function(t){e(t)},r.onload=function(){r.status>=200&&r.status<300&&r.response?e(null,r.response):e(new Error(r.statusText))},r.send(),r},r.getImage=function(t,e){return r.getArrayBuffer(t,function(t,r){if(t)return e(t);var n=new Image;n.onload=function(){e(null,n),(window.URL||window.webkitURL).revokeObjectURL(n.src)};var i=new Blob([new Uint8Array(r)],{type:\"image/png\"});return n.src=(window.URL||window.webkitURL).createObjectURL(i),n.getData=function(){var t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");return t.width=n.width,t.height=n.height,e.drawImage(n,0,0),e.getImageData(0,0,n.width,n.height).data},n})},r.getVideo=function(t,e){var r=document.createElement(\"video\");r.onloadstart=function(){e(null,r)};for(var i=0;i<t.length;i++){var a=document.createElement(\"source\");n(t[i])||(r.crossOrigin=\"Anonymous\"),a.src=t[i],r.appendChild(a)}return r.getData=function(){return r},r}},{}],387:[function(t,e,r){\"use strict\";r.window=window,e.exports.now=function(){return window.performance&&window.performance.now?window.performance.now.bind(window.performance):Date.now.bind(Date)}();var n=window.requestAnimationFrame||window.mozRequestAnimationFrame||window.webkitRequestAnimationFrame||window.msRequestAnimationFrame;r.frame=function(t){return n(t)};var i=window.cancelAnimationFrame||window.mozCancelAnimationFrame||window.webkitCancelAnimationFrame||window.msCancelAnimationFrame;r.cancelFrame=function(t){i(t)},r.timed=function(t,n,i){function a(l){o||(l=e.exports.now(),l>=s+n?t.call(i,1):(t.call(i,(l-s)/n),r.frame(a)))}if(!n)return t.call(i,1),null;var o=!1,s=e.exports.now();return r.frame(a),function(){o=!0}},r.supported=t(\"mapbox-gl-supported\"),r.hardwareConcurrency=navigator.hardwareConcurrency||4,Object.defineProperty(r,\"devicePixelRatio\",{get:function(){return window.devicePixelRatio}}),r.supportsWebp=!1;var a=document.createElement(\"img\");a.onload=function(){r.supportsWebp=!0},a.src=\"data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA=\",r.supportsGeolocation=!!navigator.geolocation},{\"mapbox-gl-supported\":288}],388:[function(t,e,r){\"use strict\";function n(t,e){this.canvas=document.createElement(\"canvas\"),t&&e&&(this.canvas.style.position=\"absolute\",this.canvas.classList.add(\"mapboxgl-canvas\"),this.canvas.addEventListener(\"webglcontextlost\",t._contextLost.bind(t),!1),this.canvas.addEventListener(\"webglcontextrestored\",t._contextRestored.bind(t),!1),this.canvas.setAttribute(\"tabindex\",0),e.appendChild(this.canvas))}var i=t(\"../util\"),a=t(\"mapbox-gl-supported\");e.exports=n,n.prototype.resize=function(t,e){var r=window.devicePixelRatio||1;this.canvas.width=r*t,this.canvas.height=r*e,this.canvas.style.width=t+\"px\",this.canvas.style.height=e+\"px\"},n.prototype.getWebGLContext=function(t){return t=i.extend({},t,a.webGLContextAttributes),this.canvas.getContext(\"webgl\",t)||this.canvas.getContext(\"experimental-webgl\",t)},n.prototype.getElement=function(){return this.canvas}},{\"../util\":403,\"mapbox-gl-supported\":288}],389:[function(t,e,r){\"use strict\";function n(t){for(var e=0;e<t.length;e++)if(t[e]in s)return t[e]}function i(t){t.preventDefault(),t.stopPropagation(),\n",
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n(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.fullData=null,this.updateAxes(e),this.makeFramework(),this.glplotOptions=d(this),this.glplotOptions.merge(e),this.glplot=u(this.glplotOptions),this.camera=p(this),this.traces={},this._inputs={},this.spikes=c(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/cartesian/axes\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),f=t(\"webgl-context\"),d=t(\"./convert\"),p=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),m=t(\"../../lib/show_no_webgl_msg\"),v=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o&&(a=document.createElement(\"canvas\"),o=f({canvas:a,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}),!o))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=a,this.gl=o}else{var t=document.createElement(\"canvas\"),e=f({canvas:t,premultipliedAlpha:!0});e||m(this),this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r),r.className+=\"user-select-none\";var n=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");n.style.position=\"absolute\",n.style.top=n.style.left=\"0px\",n.style.width=n.style.height=\"100%\",n.style[\"z-index\"]=20,n.style[\"pointer-events\"]=\"none\";var i=this.mouseContainer=document.createElement(\"div\");i.style.position=\"absolute\";var s=this.container;s.appendChild(r),s.appendChild(n),s.appendChild(i)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.updateSize(this.canvas),this.glplot.setDirty(),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=n-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=i[4*(r*o+l)+u];i[4*(r*o+l)+u]=i[4*(r*s+l)+u],i[4*(r*s+l)+u]=c}var h=document.createElement(\"canvas\");h.width=r,h.height=n;var f=h.getContext(\"2d\"),d=f.createImageData(r,n);d.data.set(i),f.putImageData(d,0,0);var p;switch(t){case\"jpeg\":p=h.toDataURL(\"image/jpeg\");break;case\"webp\":p=h.toDataURL(\"image/webp\");break;default:p=h.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(a),p},y.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},y.computeTickMarks=function(){this.xaxis._length=this.glplot.viewBox[2]-this.glplot.viewBox[0],this.yaxis._length=this.glplot.viewBox[3]-this.glplot.viewBox[1];for(var t=[s.calcTicks(this.xaxis),s.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=g(t[e][r].text+\"\");return t},y.updateAxes=function(t){var e=s.subplotMatch,r=\"xaxis\"+this.id.match(e)[1],n=\"yaxis\"+this.id.match(e)[2];this.xaxis=t[r],this.yaxis=t[n]},y.updateFx=function(t){var e=this.fullLayout;e.dragmode=t.dragmode,e.hovermode=t.hovermode};var x=function(t){var e=t.xaxis.range,r=t.yaxis.range;t.graphDiv.layout.xaxis.autorange=t.xaxis.autorange,t.graphDiv.layout.xaxis.range=e.slice(0),t.graphDiv.layout.yaxis.autorange=t.yaxis.autorange,t.graphDiv.layout.yaxis.range=r.slice(0);var n={lastInputTime:t.camera.lastInputTime};n[t.xaxis._name]=e.slice(),n[t.yaxis._name]=r.slice(),t.graphDiv.emit(\"plotly_relayout\",n)};y.cameraChanged=function(){var t=this.camera,e=this.xaxis.range,r=this.yaxis.range;this.glplot.setDataBox([e[0],r[0],e[1],r[1]]);var n=this.computeTickMarks(),a=this.glplotOptions.ticks;i(n,a)&&(this.glplotOptions.ticks=n,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),x(this))},y.destroy=function(){var t=this.traces;t&&Object.keys(t).map(function(e){t[e].dispose(),delete t[e]}),this.glplot.dispose(),this.staticPlot||this.container.removeChild(this.canvas),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this._inputs=null,this.glplot=null,this.stopped=!0},y.plot=function(t,e,r){var n=this.glplot;this.fullLayout=r,this.updateAxes(r),this.updateTraces(t,e);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var l=r._size,u=this.xaxis.domain,c=this.yaxis.domain;o.viewBox=[l.l+u[0]*l.w,l.b+c[0]*l.h,i-l.r-(1-u[1])*l.w,a-l.t-(1-c[1])*l.h],this.mouseContainer.style.width=l.w*(u[1]-u[0])+\"px\",this.mouseContainer.style.height=l.h*(c[1]-c[0])+\"px\",this.mouseContainer.height=l.h*(c[1]-c[0]),this.mouseContainer.style.left=l.l+u[0]*l.w+\"px\",this.mouseContainer.style.top=l.t+(1-c[1])*l.h+\"px\";var h=this.bounds;h[0]=h[1]=1/0,h[2]=h[3]=-(1/0);var f,d,p=Object.keys(this.traces);for(d=0;d<p.length;++d)for(var g=this.traces[p[d]],m=0;m<2;++m)h[m]=Math.min(h[m],g.bounds[m]),h[m+2]=Math.max(h[m+2],g.bounds[m+2]);for(d=0;d<2;++d)h[d]>h[d+2]&&(h[d]=-1,h[d+2]=1),f=this[v[d]],f._length=o.viewBox[d+2]-o.viewBox[d],s.doAutoRange(f);o.ticks=this.computeTickMarks();var y=this.xaxis.range,x=this.yaxis.range;o.dataBox=[y[0],x[0],y[1],x[1]],o.merge(r),n.update(o),this.glplot.draw()},y.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if(i=t[n],i.uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r],this._inputs[i.uid]=r;var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}},y.emitPointAction=function(t,e){var r=this._inputs[t.trace.uid];this.graphDiv.emit(e,{points:[{x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r,pointNumber:t.pointIndex,data:this.fullData[r]._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis}]})},y.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a=r.x*t.pixelRatio,o=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode)this.selectBox.enabled=!0,this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],t.setDirty();else{this.selectBox.enabled=!1;var s=i._size,u=this.xaxis.domain,c=this.yaxis.domain,h=t.pick(a/t.pixelRatio+s.l+u[0]*s.w,o/t.pixelRatio-(s.t+(1-c[1])*s.h)),f=h&&h.object._trace.handlePick(h);if(f&&n&&this.emitPointAction(f,\"plotly_click\"),h&&\"skip\"!==h.object._trace.hoverinfo&&i.hovermode){if(f&&(!this.lastPickResult||this.lastPickResult.traceUid!==f.trace.uid||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var d=f;this.lastPickResult={traceUid:f.trace?f.trace.uid:null,dataCoord:f.dataCoord.slice()},this.spikes.update({center:h.dataCoord}),d.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(h.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(h.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(f,\"plotly_hover\");var p=d.hoverinfo;if(\"all\"!==p){var g=p.split(\"+\");g.indexOf(\"x\")===-1&&(d.traceCoord[0]=void 0),g.indexOf(\"y\")===-1&&(d.traceCoord[1]=void 0),g.indexOf(\"z\")===-1&&(d.traceCoord[2]=void 0),g.indexOf(\"text\")===-1&&(d.textLabel=void 0),g.indexOf(\"name\")===-1&&(d.name=void 0)}l.loneHover({x:d.screenCoord[0],y:d.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",d.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",d.traceCoord[1]),zLabel:d.traceCoord[2],text:d.textLabel,name:d.name,color:d.color},{container:this.svgContainer})}}else!h&&this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),l.loneUnhover(this.svgContainer))}t.draw()}},y.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return s.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../lib/html2unicode\":631,\"../../lib/show_no_webgl_msg\":643,\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/graph_interact\":670,\"./camera\":697,\"./convert\":698,\"gl-plot2d\":187,\"gl-select-box\":218,\"gl-spikes2d\":227,\"webgl-context\":518}],701:[function(t,e,r){\"use strict\";function n(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var n=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),l=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],u=0,c=t.clientWidth,h=t.clientHeight,f={keyBindingMode:\"rotate\",view:n,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:n.modes,tick:function(){var e=i(),r=this.delay,a=e-2*r;n.idle(e-r),n.recalcMatrix(a),n.flush(e-(100+2*r));for(var o=!0,s=n.computedMatrix,f=0;f<16;++f)o=o&&l[f]===s[f],l[f]=s[f];var d=t.clientWidth===c&&t.clientHeight===h;return c=t.clientWidth,h=t.clientHeight,o?!d:(u=Math.exp(n.computedRadius[0]),!0)},lookAt:function(t,e,r){n.lookAt(n.lastT(),t,e,r)},rotate:function(t,e,r){n.rotate(n.lastT(),t,e,r)},pan:function(t,e,r){n.pan(n.lastT(),t,e,r)},translate:function(t,e,r){n.translate(n.lastT(),t,e,r)}};Object.defineProperties(f,{matrix:{get:function(){return n.computedMatrix},set:function(t){return n.setMatrix(n.lastT(),t),n.computedMatrix},enumerable:!0},mode:{get:function(){return n.getMode()},set:function(t){var e=n.computedUp.slice(),r=n.computedEye.slice(),a=n.computedCenter.slice();if(n.setMode(t),\"turntable\"===t){var o=i();n._active.lookAt(o,r,a,e),n._active.lookAt(o+500,r,a,[0,0,1]),n._active.flush(o)}return n.getMode()},enumerable:!0},center:{get:function(){return n.computedCenter},set:function(t){return n.lookAt(n.lastT(),null,t),n.computedCenter},enumerable:!0},eye:{get:function(){return n.computedEye},set:function(t){return n.lookAt(n.lastT(),t),n.computedEye},enumerable:!0},up:{get:function(){return n.computedUp},set:function(t){return n.lookAt(n.lastT(),null,null,t),n.computedUp},enumerable:!0},distance:{get:function(){return u},set:function(t){return n.setDistance(n.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return n.getDistanceLimits(r)},set:function(t){return n.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1});var d=0,p=0;return o(t,function(e,r,a,o){var s=\"rotate\"===f.keyBindingMode,l=\"pan\"===f.keyBindingMode,c=\"zoom\"===f.keyBindingMode,h=!!o.control,g=!!o.alt,m=!!o.shift,v=!!(1&e),y=!!(2&e),x=!!(4&e),b=1/t.clientHeight,_=b*(r-d),w=b*(a-p),M=f.flipX?1:-1,A=f.flipY?1:-1,k=i(),T=Math.PI*f.rotateSpeed;if((s&&v&&!h&&!g&&!m||v&&!h&&!g&&m)&&n.rotate(k,M*T*_,-A*T*w,0),(l&&v&&!h&&!g&&!m||y||v&&h&&!g&&!m)&&n.pan(k,-f.translateSpeed*_*u,f.translateSpeed*w*u,0),c&&v&&!h&&!g&&!m||x||v&&!h&&g&&!m){var E=-f.zoomSpeed*w/window.innerHeight*(k-n.lastT())*100;n.pan(k,0,0,u*(Math.exp(E)-1))}return d=r,p=a,!0}),s(t,function(t,e){var r=f.flipX?1:-1,a=f.flipY?1:-1,o=i();if(Math.abs(t)>Math.abs(e))n.rotate(o,0,0,-t*r*Math.PI*f.rotateSpeed/window.innerWidth);else{var s=-f.zoomSpeed*a*e/window.innerHeight*(o-n.lastT())/100;n.pan(o,0,0,u*(Math.exp(s)-1))}},!0),f}e.exports=n;var i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":27,\"mouse-change\":413,\"mouse-wheel\":415,\"right-now\":459}],702:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0;r<3;++r){var n=s[r];e[n]._gd=t}}var i=t(\"./scene\"),a=t(\"../plots\"),o=t(\"../../constants/xmlns_namespaces\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,o=a.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var s=0;s<o.length;s++){var l=o[s],u=a.getSubplotData(r,\"gl3d\",l),c=e[l],h=c._scene;void 0===h&&(n(t,c),h=new i({id:l,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),c._scene=h),h.plot(u,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=a.getSubplotIds(n,\"gl3d\"),o=0;o<i.length;o++){var s=i[o];!e[s]&&n[s]._scene&&n[s]._scene.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=a.getSubplotIds(e,\"gl3d\"),n=e._size,i=0;i<r.length;i++){var s=e[r[i]],l=s.domain,u=s._scene,c=u.toImage(\"png\"),h=e._glimages.append(\"svg:image\");h.attr({xmlns:o.svg,\"xlink:href\":c,x:n.l+n.w*l.x[0],y:n.t+n.h*(1-l.y[1]),width:n.w*(l.x[1]-l.x[0]),height:n.h*(l.y[1]-l.y[0]),preserveAspectRatio:\"none\"}),u.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\")},{\"../../constants/xmlns_namespaces\":618,\"../plots\":723,\"./layout/attributes\":703,\"./layout/defaults\":707,\"./layout/layout_attributes\":708,\"./scene\":712,\"./set_convert\":713}],703:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\"}}},{}],704:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:i.title,titlefont:i.titlefont,type:i.type,autorange:i.autorange,rangemode:i.rangemode,range:i.range,fixedrange:i.fixedrange,tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,separatethousands:i.separatethousands,tickformat:i.tickformat,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth}},{\"../../../components/color\":533,\"../../../lib/extend\":625,\"../../cartesian/layout_attributes\":672}],705:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/axis_defaults\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"],l=13600/187;e.exports=function(t,e,r){function u(t,e){return i.coerce(c,h,a,t,e)}for(var c,h,f=0;f<s.length;f++){var d=s[f];c=t[d]||{},h={_id:d[0]+r.scene,_name:d},e[d]=h=o(c,h,u,{font:r.font,letter:d[0],data:r.data,showGrid:!0,bgColor:r.bgColor}),u(\"gridcolor\",n(h.color,r.bgColor,l).toRgbString()),u(\"title\",d[0]),h.setScale=i.noop,u(\"showspikes\")&&(u(\"spikesides\"),u(\"spikethickness\"),u(\"spikecolor\",h.color)),u(\"showaxeslabels\"),u(\"showbackground\")&&u(\"backgroundcolor\")}}},{\"../../../lib\":632,\"../../cartesian/axis_defaults\":664,\"./axis_attributes\":704,tinycolor2:489}],706:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open 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a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;r<3;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)!==-1?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":631,\"../../../lib/str2rgbarray\":645,arraytools:33}],707:[function(t,e,r){\"use strict\";function n(t,e,r,n){for(var a=r(\"bgcolor\"),l=i.combine(a,n.paper_bgcolor),u=Object.keys(o.camera),c=0;c<u.length;c++)r(\"camera.\"+u[c]+\".x\"),r(\"camera.\"+u[c]+\".y\"),r(\"camera.\"+u[c]+\".z\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),f=h?\"manual\":\"auto\",d=r(\"aspectmode\",f);h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\")),s(t,e,{font:n.font,scene:n.id,data:n.fullData,bgColor:l}),r(\"dragmode\",n.getDfltFromLayout(\"dragmode\")),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}var i=t(\"../../../components/color\"),a=t(\"../../subplot_defaults\"),o=t(\"./layout_attributes\"),s=t(\"./axis_defaults\");e.exports=function(t,e,r){function i(e){if(!s){var r=o[e].values.indexOf(t[e])!==-1;return r?t[e]:void 0}}var s=e._has(\"cartesian\")||e._has(\"geo\")||e._has(\"gl2d\")||e._has(\"pie\")||e._has(\"ternary\");a(t,e,r,{type:\"gl3d\",attributes:o,handleDefaults:n,font:e.font,fullData:r,getDfltFromLayout:i,paper_bgcolor:e.paper_bgcolor})}},{\"../../../components/color\":533,\"../../subplot_defaults\":730,\"./axis_defaults\":705,\"./layout_attributes\":708}],708:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\"],dflt:\"turntable\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\"},_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":625,\"./axis_attributes\":704}],709:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;e<3;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":645}],710:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,c=[[],[],[]],h=0;h<3;++h){var f=i[l[h]];if(f._length=(r[h].hi-r[h].lo)*r[h].pixelsPerDataUnit/t.dataScale[h],Math.abs(f._length)===1/0)c[h]=[];else{f.range[0]=r[h].lo/t.dataScale[h],f.range[1]=r[h].hi/t.dataScale[h],f._m=1/(t.dataScale[h]*r[h].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var d=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var p=f.nticks||o.constrain(f._length/40,4,9);a.autoTicks(f,Math.abs(f.range[1]-f.range[0])/p)}for(var g=a.calcTicks(f),m=0;m<g.length;++m)g[m].x=g[m].x*t.dataScale[h],g[m].text=s(g[m].text);c[h]=g,f.tickmode=d}}e.ticks=c;for(var h=0;h<3;++h){u[h]=.5*(t.glplot.bounds[0][h]+t.glplot.bounds[1][h]);for(var m=0;m<2;++m)e.bounds[m][h]=t.glplot.bounds[m][h]}t.contourLevels=n(c)}e.exports=i;var a=t(\"../../cartesian/axes\"),o=t(\"../../../lib\"),s=t(\"../../../lib/html2unicode\"),l=[\"xaxis\",\"yaxis\",\"zaxis\"],u=[0,0,0]},{\"../../../lib\":632,\"../../../lib/html2unicode\":631,\"../../cartesian/axes\":662}],711:[function(t,e,r){\"use 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d=r.hoverinfo,p=e(\"xaxis\",u.traceCoordinate[0]),v=e(\"yaxis\",u.traceCoordinate[1]),y=e(\"zaxis\",u.traceCoordinate[2]);if(\"all\"!==d){var x=d.split(\"+\");x.indexOf(\"x\")===-1&&(p=void 0),x.indexOf(\"y\")===-1&&(v=void 0),x.indexOf(\"z\")===-1&&(y=void 0),x.indexOf(\"text\")===-1&&(u.textLabel=void 0),x.indexOf(\"name\")===-1&&(l.name=void 0)}t.fullSceneLayout.hovermode&&m.loneHover({x:(.5+.5*f[0]/f[3])*a,y:(.5-.5*f[1]/f[3])*o,xLabel:p,yLabel:v,zLabel:y,text:u.textLabel,name:l.name,color:l.color},{container:n});var _={points:[{x:p,y:v,z:y,data:r._input,fullData:r,curveNumber:r.index,pointNumber:u.data.index}]};u.buttons&&u.distance<5?t.graphDiv.emit(\"plotly_click\",_):t.graphDiv.emit(\"plotly_hover\",_),h=_}else m.loneUnhover(n),t.graphDiv.emit(\"plotly_unhover\",h)}function i(t,e,r,i){var a={canvas:r,gl:i,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1};if(t.staticMode){if(!h&&(c=document.createElement(\"canvas\"),h=d({canvas:c,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}),!h))throw new Error(\"error creating static canvas/context for image server\");a.pixelRatio=t.pixelRatio,a.gl=h,a.canvas=c}try{t.glplot=f(a)}catch(e){y(t)}var o=function(t){var e={};e[t.id]=u(t.camera),t.saveCamera(t.graphDiv.layout),t.graphDiv.emit(\"plotly_relayout\",e)};if(t.glplot.canvas.addEventListener(\"mouseup\",o.bind(null,t)),t.glplot.canvas.addEventListener(\"wheel\",o.bind(null,t)),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(t){p.warn(\"Lost WebGL context.\"),t.preventDefault()}),!t.camera){var s=t.fullSceneLayout.camera;t.camera=x(t.container,{center:[s.center.x,s.center.y,s.center.z],eye:[s.eye.x,s.eye.y,s.eye.z],up:[s.up.x,s.up.y,s.up.z],zoomMin:.1,zoomMax:100,mode:\"orbit\"})}return t.glplot.mouseListener.enabled=!1,t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=n.bind(null,t),t.traces={},!0}function a(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=w(e[this.id]),this.spikeOptions=M(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],!i(this,e)}function o(t,e,r,n){for(var i,a=0;a<e.length;++a)if(Array.isArray(e[a]))for(var o=0;o<e[a].length;++o)i=t.d2l(e[a][o]),!isNaN(i)&&isFinite(i)&&(n[0][r]=Math.min(n[0][r],i),n[1][r]=Math.max(n[1][r],i));else i=t.d2l(e[a]),!isNaN(i)&&isFinite(i)&&(n[0][r]=Math.min(n[0][r],i),n[1][r]=Math.max(n[1][r],i))}function s(t,e,r){var n=t.fullSceneLayout;o(n.xaxis,e.x,0,r),o(n.yaxis,e.y,1,r),o(n.zaxis,e.z,2,r)}function l(t){return[[t.eye.x,t.eye.y,t.eye.z],[t.center.x,t.center.y,t.center.z],[t.up.x,t.up.y,t.up.z]]}function u(t){return{up:{x:t.up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]}}}var c,h,f=t(\"gl-plot3d\"),d=t(\"webgl-context\"),p=t(\"../../lib\"),g=t(\"../../plots/cartesian/axes\"),m=t(\"../../plots/cartesian/graph_interact\"),v=t(\"../../lib/str2rgbarray\"),y=t(\"../../lib/show_no_webgl_msg\"),x=t(\"./camera\"),b=t(\"./project\"),_=t(\"./set_convert\"),w=t(\"./layout/convert\"),M=t(\"./layout/spikes\"),A=t(\"./layout/tick_marks\"),k=a.prototype;k.recoverContext=function(){function t(){return r.isContextLost()?void requestAnimationFrame(t):i(e,e.fullLayout,n,r)?void e.plot.apply(e,e.plotArgs):void p.error(\"Catastrophic 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n=t.symbol,i=l(n.textposition,n.iconsize);s.extendFlat(e,{\"icon-image\":n.icon+\"-15\",\"icon-size\":n.iconsize/10,\"text-field\":n.text,\"text-size\":n.textfont.size,\"text-anchor\":i.anchor,\"text-offset\":i.offset}),s.extendFlat(r,{\"icon-color\":t.color,\"text-color\":n.textfont.color,\"text-opacity\":t.opacity})}return{layout:e,paint:r}}function o(t){var e,r=t.sourcetype,n=t.source,i={type:r},a=\"string\"==typeof n;return\"geojson\"===r?e=\"data\":\"vector\"===r&&(e=a?\"url\":\"tiles\"),i[e]=n,i}var s=t(\"../../lib\"),l=t(\"./convert_text_opts\"),u=n.prototype;u.update=function(t){this.visible?this.needsNewSource(t)?(this.updateLayer(t),this.updateSource(t)):this.needsNewLayer(t)&&this.updateLayer(t):(this.updateSource(t),this.updateLayer(t)),this.updateStyle(t),this.visible=i(t)},u.needsNewSource=function(t){return this.sourceType!==t.sourcetype||this.source!==t.source||this.layerType!==t.type},u.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==t.below},u.updateSource=function(t){var e=this.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,i(t)){var r=o(t);e.addSource(this.idSource,r)}},u.updateLayer=function(t){var e=this.map;if(e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer),this.layerType=t.type,i(t)){e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type},t.below);var r={visibility:\"visible\"};this.mapbox.setOptions(this.idLayer,\"setLayoutProperty\",r)}},u.updateStyle=function(t){var e=a(t);i(t)&&(this.mapbox.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.mapbox.setOptions(this.idLayer,\"setPaintProperty\",e.paint))},u.dispose=function(){var t=this.map;t.removeLayer(this.idLayer),t.removeSource(this.idSource)},e.exports=function(t,e,r){var i=new n(t,e);return i.update(r),i}},{\"../../lib\":632,\"./convert_text_opts\":716}],719:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../font_attributes\"),o=t(\"../../traces/scatter/attributes\").textposition;e.exports={domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},accesstoken:{valType:\"string\",noBlank:!0,strict:!0},style:{valType:\"any\",values:[\"basic\",\"streets\",\"outdoors\",\"light\",\"dark\",\"satellite\",\"satellite-streets\"],dflt:\"basic\"},center:{lon:{valType:\"number\",dflt:0},lat:{valType:\"number\",dflt:0}},zoom:{valType:\"number\",dflt:1},bearing:{valType:\"number\",dflt:0},pitch:{valType:\"number\",dflt:0},layers:{_isLinkedToArray:!0,sourcetype:{valType:\"enumerated\",values:[\"geojson\",\"vector\"],dflt:\"geojson\"},source:{valType:\"any\"},sourcelayer:{valType:\"string\",dflt:\"\"},type:{valType:\"enumerated\",values:[\"circle\",\"line\",\"fill\",\"symbol\"],dflt:\"circle\"},below:{valType:\"string\",dflt:\"\"},color:{valType:\"color\",dflt:i},opacity:{valType:\"number\",min:0,max:1,dflt:1},circle:{radius:{valType:\"number\",dflt:15}},line:{width:{valType:\"number\",dflt:2}},fill:{outlinecolor:{valType:\"color\",dflt:i}},symbol:{icon:{valType:\"string\",dflt:\"marker\"},iconsize:{valType:\"number\",dflt:10},text:{valType:\"string\",dflt:\"\"},textfont:n.extendDeep({},a,{family:{dflt:\"Open 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a=t(\"../../lib\"),o=t(\"../subplot_defaults\"),s=t(\"./layout_attributes\");e.exports=function(t,e,r){o(t,e,r,{type:\"mapbox\",attributes:s,handleDefaults:n,partition:\"y\"})}},{\"../../lib\":632,\"../subplot_defaults\":730,\"./layout_attributes\":719}],721:[function(t,e,r){\"use strict\";function n(t){this.id=t.id,this.gd=t.gd,this.container=t.container,this.isStatic=t.staticPlot;var e=t.fullLayout;this.uid=e._uid+\"-\"+this.id,this.opts=e[this.id],this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(e),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[]}function i(t){var e=h.style.values,r=h.style.dflt,n={};return u.isPlainObject(t)?(n.id=t.id,n.style=t):\"string\"==typeof t?(n.id=t,n.style=e.indexOf(t)!==-1?a(t):t):(n.id=r,n.style=a(r)),n}function a(t){return c.styleUrlPrefix+t+\"-\"+c.styleUrlSuffix}function o(t){return[t.lon,t.lat]}var s=t(\"mapbox-gl\"),l=t(\"../cartesian/graph_interact\"),u=t(\"../../lib\"),c=t(\"./constants\"),h=t(\"./layout_attributes\"),f=t(\"./layers\"),d=n.prototype;e.exports=function(t){var e=new n(t);return e},d.plot=function(t,e,r){var n=this,i=n.opts=e[this.id];n.map&&i.accesstoken!==n.accessToken&&(n.map.remove(),n.map=null,n.styleObj=null,n.traceHash=[],n.layerList={});var a;a=n.map?new Promise(function(r,i){n.updateMap(t,e,r,i)}):new Promise(function(r,i){n.createMap(t,e,r,i)}),r.push(a)},d.createMap=function(t,e,r,n){function a(){l.loneUnhover(e._toppaper)}var h=this,f=h.gd,d=h.opts,p=h.styleObj=i(d.style);h.accessToken=d.accesstoken;var g=h.map=new 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n=e*Math.PI/180,i=t(n);return[e,i]});return i},o.util.dataFromEquation=function(t,e,r){var i=e||6,a=[],o=[];n.range(0,360+i,i).forEach(function(e,r){var n=e*Math.PI/180,i=t(n);a.push(e),o.push(i)});var s={t:a,r:o};return r&&(s.name=r),s},o.util.ensureArray=function(t,e){if(\"undefined\"==typeof t)return null;var r=[].concat(t);return n.range(e).map(function(t,e){return r[e]||r[0]})},o.util.fillArrays=function(t,e,r){return e.forEach(function(e,n){t[e]=o.util.ensureArray(t[e],r)}),t},o.util.cloneJson=function(t){return JSON.parse(JSON.stringify(t))},o.util.validateKeys=function(t,e){\"string\"==typeof e&&(e=e.split(\".\"));var r=e.shift();return t[r]&&(!e.length||objHasKeys(t[r],e))},o.util.sumArrays=function(t,e){return n.zip(t,e).map(function(t,e){return n.sum(t)})},o.util.arrayLast=function(t){return t[t.length-1]},o.util.arrayEqual=function(t,e){for(var r=Math.max(t.length,e.length,1);r-- >=0&&t[r]===e[r];);return r===-2},o.util.flattenArray=function(t){for(var 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t={data:{name:\"geom1\",t:[[1,2,3,4]],r:[[1,2,3,4]],dotType:\"circle\",dotSize:64,dotVisible:!1,barWidth:20,color:\"#ffa500\",strokeSize:1,strokeColor:\"silver\",strokeDash:\"solid\",opacity:1,index:0,visible:!0,visibleInLegend:!0},geometryConfig:{geometry:\"LinePlot\",geometryType:\"arc\",direction:\"clockwise\",orientation:0,container:\"body\",radialScale:null,angularScale:null,colorScale:n.scale.category20()}};return t},o.BarChart=function(){return o.PolyChart()},o.BarChart.defaultConfig=function(){var t={geometryConfig:{geometryType:\"bar\"}};return t},o.AreaChart=function(){return o.PolyChart()},o.AreaChart.defaultConfig=function(){var t={geometryConfig:{geometryType:\"arc\"}};return t},o.DotPlot=function(){return o.PolyChart()},o.DotPlot.defaultConfig=function(){var t={geometryConfig:{geometryType:\"dot\",dotType:\"circle\"}};return t},o.LinePlot=function(){return o.PolyChart()},o.LinePlot.defaultConfig=function(){var t={geometryConfig:{geometryType:\"line\"}};return 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r={data:[\"a\",\"b\",\"c\"],legendConfig:{elements:[{symbol:\"line\",color:\"red\"},{symbol:\"square\",color:\"yellow\"},{symbol:\"diamond\",color:\"limegreen\"}],height:150,colorBandWidth:30,fontSize:12,container:\"body\",isContinuous:null,textColor:\"grey\",reverseOrder:!1}};return r},o.tooltipPanel=function(){var t,e,r,i={container:null,hasTick:!1,fontSize:12,color:\"white\",padding:5},s=\"tooltip-\"+o.tooltipPanel.uid++,l=10,u=function(){t=i.container.selectAll(\"g.\"+s).data([0]);var n=t.enter().append(\"g\").classed(s,!0).style({\"pointer-events\":\"none\",display:\"none\"});return r=n.append(\"path\").style({fill:\"white\",\"fill-opacity\":.9}).attr({d:\"M0 0\"}),e=n.append(\"text\").attr({dx:i.padding+l,dy:.3*+i.fontSize}),u};return u.text=function(a){var o=n.hsl(i.color).l,s=o>=.5?\"#aaa\":\"white\",c=o>=.5?\"black\":\"white\",h=a||\"\";e.style({fill:c,\"font-size\":i.fontSize+\"px\"}).text(h);var 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n=a({},t),i=[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]];return i.forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",n.dotVisible===!0?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var i=o.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var n=i.indexOf(t.geometry);n!=-1&&(r.data[e].groupId=n)})}if(t.layout){var s=a({},t.layout),l=[[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]];\n",
+       "if(l.forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof s.tickLength&&(s.angularaxis.ticklen=s.tickLength,delete s.tickLength),s.tickColor&&(s.angularaxis.tickcolor=s.tickColor,delete s.tickColor)):(s.angularAxis&&\"undefined\"!=typeof s.angularAxis.ticklen&&(s.tickLength=s.angularAxis.ticklen),s.angularAxis&&\"undefined\"!=typeof s.angularAxis.tickcolor&&(s.tickColor=s.angularAxis.tickcolor)),s.legend&&\"boolean\"!=typeof s.legend.reverseOrder&&(s.legend.reverseOrder=\"normal\"!=s.legend.reverseOrder),s.legend&&\"boolean\"==typeof s.legend.traceorder&&(s.legend.traceorder=s.legend.traceorder?\"reversed\":\"normal\",delete s.legend.reverseOrder),s.margin&&\"undefined\"!=typeof s.margin.t){var u=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],h={};n.entries(s.margin).forEach(function(t,e){h[c[u.indexOf(t.key)]]=t.value}),s.margin=h}e&&(delete s.needsEndSpacing,delete s.minorTickColor,delete s.minorTicks,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksStep,delete s.angularaxis.rewriteTicks,delete s.angularaxis.nticks,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksStep,delete s.radialaxis.rewriteTicks,delete s.radialaxis.nticks),r.layout=s}return r},t}},{\"../../lib\":632,d3:95}],728:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../components/color\"),o=t(\"./micropolar\"),s=t(\"./undo_manager\"),l=i.extendDeepAll,u=e.exports={};u.framework=function(t){function e(e,i){return i&&(h=i),n.select(n.select(h).node().parentNode).selectAll(\".svg-container>*:not(.chart-root)\").remove(),r=r?l(r,e):e,a||(a=o.Axis()),c=o.adapter.plotly().convert(r),a.config(c).render(h),t.data=r.data,t.layout=r.layout,u.fillLayout(t),r}var r,i,a,c,h,f=new s;return e.isPolar=!0,e.svg=function(){return a.svg()},e.getConfig=function(){return r},e.getLiveConfig=function(){return o.adapter.plotly().convert(a.getLiveConfig(),!0)},e.getLiveScales=function(){return{t:a.angularScale(),r:a.radialScale()}},e.setUndoPoint=function(){var t=this,e=o.util.cloneJson(r);!function(e,r){f.add({undo:function(){r&&t(r)},redo:function(){t(e)}})}(e,i),i=o.util.cloneJson(e)},e.undo=function(){f.undo()},e.redo=function(){f.redo()},e},u.fillLayout=function(t){var e=n.select(t).selectAll(\".plot-container\"),r=e.selectAll(\".svg-container\"),i=t.framework&&t.framework.svg&&t.framework.svg(),o={width:800,height:600,paper_bgcolor:a.background,_container:e,_paperdiv:r,_paper:i};t._fullLayout=l(o,t.layout)}},{\"../../components/color\":533,\"../../lib\":632,\"./micropolar\":727,\"./undo_manager\":729,d3:95}],729:[function(t,e,r){\"use strict\";e.exports=function(){function t(t,e){return t?(i=!0,t[e](),i=!1,this):this}var e,r=[],n=-1,i=!1;return{add:function(t){return i?this:(r.splice(n+1,r.length-n),r.push(t),n=r.length-1,this)},setCallback:function(t){e=t},undo:function(){var i=r[n];return i?(t(i,\"undo\"),n-=1,e&&e(i.undo),this):this},redo:function(){var i=r[n+1];return i?(t(i,\"redo\"),n+=1,e&&e(i.redo),this):this},clear:function(){r=[],n=-1},hasUndo:function(){return n!==-1},hasRedo:function(){return n<r.length-1},getCommands:function(){return r},getPreviousCommand:function(){return r[n-1]},getIndex:function(){return n}}}},{}],730:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),i=t(\"./plots\");e.exports=function(t,e,r,a){function o(t,e){return n.coerce(s,l,c,t,e)}for(var s,l,u=a.type,c=a.attributes,h=a.handleDefaults,f=a.partition||\"x\",d=i.findSubplotIds(r,u),p=d.length,g=0;g<p;g++){var m=d[g];s=t[m]?t[m]:t[m]={},e[m]=l={},o(\"domain.\"+f,[g/p,(g+1)/p]),o(\"domain.\"+{x:\"y\",y:\"x\"}[f]),a.id=m,h(s,l,o,a)}}},{\"../lib\":632,\"./plots\":723}],731:[function(t,e,r){\"use strict\";var n=t(\"./ternary\"),i=t(\"../../plots/plots\");r.name=\"ternary\",r.attr=\"subplot\",r.idRoot=\"ternary\",r.idRegex=/^ternary([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^ternary([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"ternary\"),o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"ternary\",s),u=e[s]._subplot;void 0===u&&(u=new n({id:s,graphDiv:t,container:e._ternarylayer.node()},e),e[s]._subplot=u),u.plot(l,e,t._promises)}},r.clean=function(t,e,r,n){for(var a=i.getSubplotIds(n,\"ternary\"),o=0;o<a.length;o++){var s=a[o],l=n[s]._subplot;!e[s]&&l&&(l.plotContainer.remove(),l.clipDef.remove())}}},{\"../../plots/plots\":723,\"./layout/attributes\":732,\"./layout/defaults\":735,\"./layout/layout_attributes\":736,\"./ternary\":737}],732:[function(t,e,r){\"use strict\";e.exports={subplot:{valType:\"subplotid\",dflt:\"ternary\"}}},{}],733:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={title:n.title,titlefont:n.titlefont,color:n.color,tickmode:n.tickmode,nticks:i({},n.nticks,{dflt:6,min:1}),tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,showtickprefix:n.showtickprefix,tickprefix:n.tickprefix,showticksuffix:n.showticksuffix,ticksuffix:n.ticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,separatethousands:n.separatethousands,tickfont:n.tickfont,tickangle:n.tickangle,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:i({},n.showline,{dflt:!0}),linecolor:n.linecolor,linewidth:n.linewidth,showgrid:i({},n.showgrid,{dflt:!0}),gridcolor:n.gridcolor,gridwidth:n.gridwidth,min:{valType:\"number\",dflt:0,min:0}}},{\"../../../lib/extend\":625,\"../../cartesian/layout_attributes\":672}],734:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/tick_label_defaults\"),s=t(\"../../cartesian/tick_mark_defaults\"),l=t(\"../../cartesian/tick_value_defaults\");e.exports=function(t,e,r){function u(r,n){return i.coerce(t,e,a,r,n)}e.type=\"linear\";var c=u(\"color\"),h=c===t.color?c:r.font.color,f=e._name,d=f.charAt(0).toUpperCase(),p=\"Component \"+d,g=u(\"title\",p);e._hovertitle=g===p?g:d,i.coerceFont(u,\"titlefont\",{family:r.font.family,size:Math.round(1.2*r.font.size),color:h}),u(\"min\"),l(t,e,u,\"linear\"),o(t,e,u,\"linear\",{noHover:!1}),s(t,e,u,{outerTicks:!0});var m=u(\"showticklabels\");m&&(i.coerceFont(u,\"tickfont\",{family:r.font.family,size:r.font.size,color:h}),u(\"tickangle\"),u(\"tickformat\")),u(\"hoverformat\");var v=u(\"showline\");v&&(u(\"linecolor\",c),u(\"linewidth\"));var y=u(\"showgrid\");y&&(u(\"gridcolor\",n(c,r.bgColor,60).toRgbString()),u(\"gridwidth\"))}},{\"../../../lib\":632,\"../../cartesian/tick_label_defaults\":678,\"../../cartesian/tick_mark_defaults\":679,\"../../cartesian/tick_value_defaults\":680,\"./axis_attributes\":733,tinycolor2:489}],735:[function(t,e,r){\"use strict\";function n(t,e,r,n){var a=r(\"bgcolor\"),o=r(\"sum\");n.bgColor=i.combine(a,n.paper_bgcolor);for(var u,c,h,f=0;f<l.length;f++)u=l[f],c=t[u]||{},h=e[u]={_name:u},s(c,h,n);var d=e.aaxis,p=e.baxis,g=e.caxis;d.min+p.min+g.min>=o&&(d.min=0,p.min=0,g.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}var i=t(\"../../../components/color\"),a=t(\"../../subplot_defaults\"),o=t(\"./layout_attributes\"),s=t(\"./axis_defaults\"),l=[\"aaxis\",\"baxis\",\"caxis\"];e.exports=function(t,e,r){a(t,e,r,{type:\"ternary\",attributes:o,handleDefaults:n,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../../components/color\":533,\"../../subplot_defaults\":730,\"./axis_defaults\":734,\"./layout_attributes\":736}],736:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color/attributes\"),i=t(\"./axis_attributes\");e.exports={domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:i,baxis:i,caxis:i}},{\"../../../components/color/attributes\":532,\"./axis_attributes\":733}],737:[function(t,e,r){\"use strict\";function n(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework()}function i(t){a.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}var a=t(\"d3\"),o=t(\"tinycolor2\"),s=t(\"../../plotly\"),l=t(\"../../lib\"),u=t(\"../../components/color\"),c=t(\"../../components/drawing\"),h=t(\"../cartesian/set_convert\"),f=t(\"../../lib/extend\").extendFlat,d=t(\"../cartesian/axes\"),p=t(\"../../lib/filter_visible\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/titles\"),v=t(\"../cartesian/select\"),y=t(\"../cartesian/constants\"),x=t(\"../cartesian/graph_interact\");e.exports=n;var b=n.prototype;b.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={}},b.plot=function(t,e){var r,n=this,i=e[n.id],a=e._size;l.getPlotDiv(n.plotContainer.node())!==n.graphDiv&&(n.init(n.graphDiv._fullLayout),n.makeFramework()),n.adjustLayout(i,a);var o=n.traceHash,s={};for(r=0;r<t.length;r++){var c=t[r];s[c.type]=s[c.type]||[],s[c.type].push(c)}var h=Object.keys(o),f=Object.keys(s);for(r=0;r<h.length;r++){var d=h[r];if(f.indexOf(d)===-1){var g=o[d][0];g.visible=!1,s[d]=[g]}}for(f=Object.keys(s),r=0;r<f.length;r++){var m=s[f[r]],v=m[0]._module;v.plot(n,p(m),i)}n.traceHash=s,n.layers.plotbg.select(\"path\").call(u.fill,i.bgcolor)},b.makeFramework=function(){var t=this,e=t.defs.selectAll(\"g.clips\").data([0]);e.enter().append(\"g\").classed(\"clips\",!0);var r=\"clip\"+t.layoutId+t.id;t.clipDef=e.selectAll(\"#\"+r).data([0]),t.clipDef.enter().append(\"clipPath\").attr(\"id\",r).append(\"path\").attr(\"d\",\"M0,0Z\"),t.plotContainer=t.container.selectAll(\"g.\"+t.id).data([0]),t.plotContainer.enter().append(\"g\").classed(t.id,!0),t.layers={};var n=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\",\"frontplot\",\"zoom\",\"aaxis\",\"baxis\",\"caxis\",\"axlines\"],i=t.plotContainer.selectAll(\"g.toplevel\").data(n);i.enter().append(\"g\").attr(\"class\",function(t){return\"toplevel \"+t}).each(function(e){var r=a.select(this);t.layers[e]=r,\"frontplot\"===e?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===e?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===e?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"axlines\"===e&&r.selectAll(\"path\").data([\"aline\",\"bline\",\"cline\"]).enter().append(\"path\").each(function(t){a.select(this).classed(t,!0)})});var o=t.plotContainer.select(\".grids\").selectAll(\"g.grid\").data([\"agrid\",\"bgrid\",\"cgrid\"]);o.enter().append(\"g\").attr(\"class\",function(t){return\"grid \"+t}).each(function(e){t.layers[e]=a.select(this)}),t.plotContainer.selectAll(\".backplot,.frontplot,.grids\").call(c.setClipUrl,r),t.graphDiv._context.staticPlot||t.initInteractions()};var _=Math.sqrt(4/3);b.adjustLayout=function(t,e){var r,n,i,a,o,s,l=this,c=t.domain,d=(c.x[0]+c.x[1])/2,p=(c.y[0]+c.y[1])/2,g=c.x[1]-c.x[0],m=c.y[1]-c.y[0],v=g*e.w,y=m*e.h,x=t.sum,b=t.aaxis.min,w=t.baxis.min,M=t.caxis.min;v>_*y?(a=y,i=a*_):(i=v,a=i/_),o=g*i/v,s=m*a/y,r=e.l+e.w*d-i/2,n=e.t+e.h*(1-p)-a/2,l.x0=r,l.y0=n,l.w=i,l.h=a,l.sum=x,l.xaxis={type:\"linear\",range:[b+2*M-x,x-b-2*w],domain:[d-o/2,d+o/2],_id:\"x\",_gd:l.graphDiv},h(l.xaxis),l.xaxis.setScale(),l.yaxis={type:\"linear\",range:[b,x-w-M],domain:[p-s/2,p+s/2],_id:\"y\",_gd:l.graphDiv},h(l.yaxis),l.yaxis.setScale();var A=l.yaxis.domain[0],k=l.aaxis=f({},t.aaxis,{range:[b,x-w-M],side:\"left\",_counterangle:30,tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+s*_],_axislayer:l.layers.aaxis,_gridlayer:l.layers.agrid,_pos:0,_gd:l.graphDiv,_id:\"y\",_length:i,_gridpath:\"M0,0l\"+a+\",-\"+i/2});h(k);var T=l.baxis=f({},t.baxis,{range:[x-b-M,w],side:\"bottom\",_counterangle:30,domain:l.xaxis.domain,_axislayer:l.layers.baxis,_gridlayer:l.layers.bgrid,_counteraxis:l.aaxis,_pos:0,_gd:l.graphDiv,_id:\"x\",_length:i,_gridpath:\"M0,0l-\"+i/2+\",-\"+a});h(T),k._counteraxis=T;var E=l.caxis=f({},t.caxis,{range:[x-b-w,M],side:\"right\",_counterangle:30,tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+s*_],_axislayer:l.layers.caxis,_gridlayer:l.layers.cgrid,_counteraxis:l.baxis,_pos:0,_gd:l.graphDiv,_id:\"y\",_length:i,_gridpath:\"M0,0l-\"+a+\",\"+i/2});h(E);var S=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";l.clipDef.select(\"path\").attr(\"d\",S),l.layers.plotbg.select(\"path\").attr(\"d\",S);var L=\"translate(\"+r+\",\"+n+\")\";l.plotContainer.selectAll(\".scatterlayer,.maplayer,.zoom\").attr(\"transform\",L);var z=\"translate(\"+r+\",\"+(n+a)+\")\";l.layers.baxis.attr(\"transform\",z),l.layers.bgrid.attr(\"transform\",z);var C=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(30)\";l.layers.aaxis.attr(\"transform\",C),l.layers.agrid.attr(\"transform\",C);var I=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(-30)\";l.layers.caxis.attr(\"transform\",I),l.layers.cgrid.attr(\"transform\",I),l.drawAxes(!0),l.plotContainer.selectAll(\".crisp\").classed(\"crisp\",!1);var P=l.layers.axlines;P.select(\".aline\").attr(\"d\",k.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(u.stroke,k.linecolor||\"#000\").style(\"stroke-width\",(k.linewidth||0)+\"px\"),P.select(\".bline\").attr(\"d\",T.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(u.stroke,T.linecolor||\"#000\").style(\"stroke-width\",(T.linewidth||0)+\"px\"),P.select(\".cline\").attr(\"d\",E.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(u.stroke,E.linecolor||\"#000\").style(\"stroke-width\",(E.linewidth||0)+\"px\")},b.drawAxes=function(t){var 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r(t,e){return t.pxmid[1]-e.pxmid[1]}function n(t,e){return e.pxmid[1]-t.pxmid[1]}function i(t,r){r||(r={});var n,i,a,s,f,d,g=r.labelExtraY+(o?r.yLabelMax:r.yLabelMin),m=o?t.yLabelMin:t.yLabelMax,v=o?t.yLabelMax:t.yLabelMin,y=t.cyFinal+u(t.px0[1],t.px1[1]),x=g-m;if(x*h>0&&(t.labelExtraY=x),Array.isArray(e.pull))for(i=0;i<p.length;i++)a=p[i],a===t||(e.pull[t.i]||0)>=e.pull[a.i]||((t.pxmid[1]-a.pxmid[1])*h>0?(s=a.cyFinal+u(a.px0[1],a.px1[1]),x=s-m-t.labelExtraY,x*h>0&&(t.labelExtraY+=x)):(v+t.labelExtraY-y)*h>0&&(n=3*c*Math.abs(i-p.indexOf(t)),f=a.cxFinal+l(a.px0[0],a.px1[0]),d=f+n-(t.cxFinal+t.pxmid[0])-t.labelExtraX,d*c>0&&(t.labelExtraX+=d)))}var a,o,s,l,u,c,h,f,d,p,g,m,v;for(o=0;o<2;o++)for(s=o?r:n,u=o?Math.max:Math.min,h=o?1:-1,a=0;a<2;a++){for(l=a?Math.max:Math.min,c=a?1:-1,f=t[o][a],f.sort(s),d=t[1-o][a],p=d.concat(f),m=[],g=0;g<f.length;g++)void 0!==f[g].yLabelMid&&m.push(f[g]);for(v=!1,g=0;o&&g<d.length;g++)if(void 0!==d[g].yLabelMid){v=d[g];break}for(g=0;g<m.length;g++){var y=g&&m[g-1];v&&!g&&(y=v),i(m[g],y)}}}function s(t,e){var r,n,i,a,o,s,l,c,h,f,d=[];for(i=0;i<t.length;i++){if(o=t[i][0],s=o.trace,r=e.w*(s.domain.x[1]-s.domain.x[0]),n=e.h*(s.domain.y[1]-s.domain.y[0]),l=s.tiltaxis*Math.PI/180,c=s.pull,Array.isArray(c))for(c=0,a=0;a<s.pull.length;a++)s.pull[a]>c&&(c=s.pull[a]);o.r=Math.min(r/u(s.tilt,Math.sin(l),s.depth),n/u(s.tilt,Math.cos(l),s.depth))/(2+2*c),o.cx=e.l+e.w*(s.domain.x[1]+s.domain.x[0])/2,o.cy=e.t+e.h*(2-s.domain.y[1]-s.domain.y[0])/2,s.scalegroup&&d.indexOf(s.scalegroup)===-1&&d.push(s.scalegroup)}for(a=0;a<d.length;a++){for(f=1/0,h=d[a],i=0;i<t.length;i++)o=t[i][0],o.trace.scalegroup===h&&(f=Math.min(f,o.r*o.r/o.vTotal));for(i=0;i<t.length;i++)o=t[i][0],o.trace.scalegroup===h&&(o.r=Math.sqrt(f*o.vTotal))}}function l(t){function e(t){var e=h.r*Math.sin(t),r=-h.r*Math.cos(t);return d?[e*(1-s*n*n)+r*o*s,e*o*s+r*(1-s*i*i),Math.sin(a)*(r*i-e*n)]:[e,r]}var r,n,i,a,o,s,l,u,c,h=t[0],f=h.trace,d=f.tilt,p=f.rotation*Math.PI/180,g=2*Math.PI/h.vTotal,m=\"px0\",v=\"px1\";if(\"counterclockwise\"===f.direction){for(l=0;l<t.length&&t[l].hidden;l++);if(l===t.length)return;p+=g*t[l].v,g*=-1,m=\"px1\",v=\"px0\"}for(d&&(a=d*Math.PI/180,r=f.tiltaxis*Math.PI/180,o=Math.sin(r)*Math.cos(r),s=1-Math.cos(a),n=Math.sin(r),i=Math.cos(r)),c=e(p),l=0;l<t.length;l++)u=t[l],u.hidden||(u[m]=c,p+=g*u.v/2,u.pxmid=e(p),u.midangle=p,p+=g*u.v/2,c=e(p),u[v]=c,u.largeArc=u.v>h.vTotal/2?1:0)}function u(t,e,r){if(!t)return 1;var n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var c=t(\"d3\"),h=t(\"../../plots/cartesian/graph_interact\"),f=t(\"../../components/color\"),d=t(\"../../components/drawing\"),p=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;s(e,r._size);var u=r._pielayer.selectAll(\"g.trace\").data(e);u.enter().append(\"g\").attr({\"stroke-linejoin\":\"round\",class:\"trace\"}),u.exit().remove(),u.order(),u.each(function(e){var s=c.select(this),u=e[0],m=u.trace,v=0,y=(m.depth||0)*u.r*Math.sin(v)/2,x=m.tiltaxis||0,b=x*Math.PI/180,_=[y*Math.sin(b),y*Math.cos(b)],w=u.r*Math.cos(v),M=s.selectAll(\"g.part\").data(m.tilt?[\"top\",\"sides\"]:[\"top\"]);M.enter().append(\"g\").attr(\"class\",function(t){return t+\" part\"}),M.exit().remove(),M.order(),l(e),s.selectAll(\".top\").each(function(){var s=c.select(this).selectAll(\"g.slice\").data(e);s.enter().append(\"g\").classed(\"slice\",!0),s.exit().remove();var l=[[[],[]],[[],[]]],v=!1;s.each(function(o){function s(e){var n=t._fullLayout,a=t._fullData[m.index],s=a.hoverinfo;if(\"all\"===s&&(s=\"label+text+value+percent+name\"),!t._dragging&&n.hovermode!==!1&&\"none\"!==s&&\"skip\"!==s&&s){var l=i(o,u),c=M+o.pxmid[0]*(1-l),f=A+o.pxmid[1]*(1-l),d=r.separators,p=[];s.indexOf(\"label\")!==-1&&p.push(o.label),a.text&&a.text[o.i]&&s.indexOf(\"text\")!==-1&&p.push(a.text[o.i]),s.indexOf(\"value\")!==-1&&p.push(g.formatPieValue(o.v,d)),s.indexOf(\"percent\")!==-1&&p.push(g.formatPiePercent(o.v/u.vTotal,d)),h.loneHover({x0:c-l*u.r,x1:c+l*u.r,y:f,text:p.join(\"<br>\"),name:s.indexOf(\"name\")!==-1?a.name:void 0,color:o.color,idealAlign:o.pxmid[0]<0?\"left\":\"right\"},{container:n._hoverlayer.node(),outerContainer:n._paper.node()}),h.hover(t,e,\"pie\"),E=!0}}function f(e){t.emit(\"plotly_unhover\",{points:[e]}),E&&(h.loneUnhover(r._hoverlayer.node()),E=!1)}function y(){t._hoverdata=[o],t._hoverdata.trace=e.trace,h.click(t,{target:!0})}function b(t,e,r,n){return\"a\"+n*u.r+\",\"+n*w+\" \"+x+\" \"+o.largeArc+(r?\" 1 \":\" 0 \")+n*(e[0]-t[0])+\",\"+n*(e[1]-t[1])}if(o.hidden)return void c.select(this).selectAll(\"path,g\").remove();l[o.pxmid[1]<0?0:1][o.pxmid[0]<0?0:1].push(o);var M=u.cx+_[0],A=u.cy+_[1],k=c.select(this),T=k.selectAll(\"path.surface\").data([o]),E=!1;if(T.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),k.select(\"path.textline\").remove(),k.on(\"mouseover\",s).on(\"mouseout\",f).on(\"click\",y),m.pull){var S=+(Array.isArray(m.pull)?m.pull[o.i]:m.pull)||0;S>0&&(M+=S*o.pxmid[0],A+=S*o.pxmid[1])}o.cxFinal=M,o.cyFinal=A;var L=m.hole;if(o.v===u.vTotal){var z=\"M\"+(M+o.px0[0])+\",\"+(A+o.px0[1])+b(o.px0,o.pxmid,!0,1)+b(o.pxmid,o.px0,!0,1)+\"Z\";L?T.attr(\"d\",\"M\"+(M+L*o.px0[0])+\",\"+(A+L*o.px0[1])+b(o.px0,o.pxmid,!1,L)+b(o.pxmid,o.px0,!1,L)+\"Z\"+z):T.attr(\"d\",z)}else{var C=b(o.px0,o.px1,!0,1);if(L){var I=1-L;T.attr(\"d\",\"M\"+(M+L*o.px1[0])+\",\"+(A+L*o.px1[1])+b(o.px1,o.px0,!1,L)+\"l\"+I*o.px0[0]+\",\"+I*o.px0[1]+C+\"Z\")}else T.attr(\"d\",\"M\"+M+\",\"+A+\"l\"+o.px0[0]+\",\"+o.px0[1]+C+\"Z\")}var P=Array.isArray(m.textposition)?m.textposition[o.i]:m.textposition,D=k.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==P?[0]:[]);D.enter().append(\"g\").classed(\"slicetext\",!0),D.exit().remove(),D.each(function(){var t=c.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(o.text).attr({class:\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(d.font,\"outside\"===P?m.outsidetextfont:m.insidetextfont).call(p.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var e,r=d.bBox(t.node());\"outside\"===P?e=a(r,o):(e=n(r,o,u),\"auto\"===P&&e.scale<1&&(t.call(d.font,m.outsidetextfont),m.outsidetextfont.family===m.insidetextfont.family&&m.outsidetextfont.size===m.insidetextfont.size||(t.attr({\"data-bb\":\"\"}),r=d.bBox(t.node())),e=a(r,o)));var i=M+o.pxmid[0]*e.rCenter+(e.x||0),s=A+o.pxmid[1]*e.rCenter+(e.y||0);e.outside&&(o.yLabelMin=s-r.height/2,o.yLabelMid=s,o.yLabelMax=s+r.height/2,o.labelExtraX=0,o.labelExtraY=0,v=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+s+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+(e.rotate?\"rotate(\"+e.rotate+\")\":\"\")+\"translate(\"+-(r.left+r.right)/2+\",\"+-(r.top+r.bottom)/2+\")\")})}),v&&o(l,m),s.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=c.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],i=t.cyFinal+t.pxmid[1],a=\"M\"+n+\",\"+i,o=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var s=t.labelExtraX*t.pxmid[1]/t.pxmid[0],l=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);a+=Math.abs(s)>Math.abs(l)?\"l\"+l*t.pxmid[0]/t.pxmid[1]+\",\"+l+\"H\"+(n+t.labelExtraX+o):\"l\"+t.labelExtraX+\",\"+s+\"v\"+(l-s)+\"h\"+o}else a+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+o;e.append(\"path\").classed(\"textline\",!0).call(f.stroke,m.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,m.outsidetextfont.size/8),d:a,fill:\"none\"})}})})}),setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=c.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)}},{\"../../components/color\":533,\"../../components/drawing\":557,\"../../lib/svg_text_utils\":646,\"../../plots/cartesian/graph_interact\":670,\"./helpers\":832,d3:95}],837:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0],r=e.trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\".top path.surface\").each(function(t){n.select(this).call(i,t,r)})})}},{\"./style_one\":838,d3:95}],838:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r){var i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a,fill:e.color}).call(n.stroke,i)}},{\"../../components/color\":533}],839:[function(t,e,r){\"use strict\";var n=t(\"../scattergl/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\"},indices:{valType:\"data_array\"},xbounds:{valType:\"data_array\"},ybounds:{valType:\"data_array\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1},blend:{valType:\"boolean\",dflt:null},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5},sizemax:{valType:\"number\",min:.1,dflt:20},border:{color:{valType:\"color\",arrayOk:!1},arearatio:{valType:\"number\",min:0,max:1,dflt:0}}}}},{\"../scattergl/attributes\":880}],840:[function(t,e,r){\"use strict\";function n(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=a(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}function i(t,e){var r=new n(t,e.uid);return r.update(e),r}var a=t(\"gl-pointcloud2d\"),o=t(\"../../lib/str2rgbarray\"),s=t(\"../scatter/get_trace_color\"),l=[\"xaxis\",\"yaxis\"],u=n.prototype;u.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},u.update=function(t){this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.updateFast(t),this.color=s(t,{})},u.updateFast=function(t){var e,r,n,i,a,s,l=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,c=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,f=t.indices,d=this.bounds;if(c){if(n=c,e=c.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(s=0;s<e;s++)i=n[2*s],a=n[2*s+1],i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),a<d[1]&&(d[1]=a),a>d[3]&&(d[3]=a);if(f)r=f;else for(r=new Int32Array(e),s=0;s<e;s++)r[s]=s}else for(e=l.length,n=new Float32Array(2*e),r=new 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r,n,i,a=e||.5,o=0;o<2;o++)r=this.scene[l[o]],n=r._min,n||(n=[]),n.push({val:t[o],pad:a}),i=r._max,i||(i=[]),i.push({val:t[o+2],pad:a})},u.dispose=function(){this.pointcloud.dispose()},e.exports=i},{\"../../lib/str2rgbarray\":645,\"../scatter/get_trace_color\":852,\"gl-pointcloud2d\":198}],841:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\");e.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),a(\"text\"),a(\"marker.color\",r),a(\"marker.opacity\"),a(\"marker.blend\"),a(\"marker.sizemin\"),a(\"marker.sizemax\"),a(\"marker.border.color\",r),a(\"marker.border.arearatio\")}},{\"../../lib\":632,\"./attributes\":839}],842:[function(t,e,r){\"use strict\";var 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u=t.opacity;if(t.marker&&t.marker.opacity&&(u*=t.marker.opacity),r={gl:o,position:l.position,color:l.scatterColor,size:l.scatterSize,glyph:l.scatterMarker,opacity:u,orthographic:!0,lineWidth:l.scatterLineWidth,lineColor:l.scatterLineColor,project:l.project,projectScale:l.projectScale,projectOpacity:l.projectOpacity},this.mode.indexOf(\"markers\")!==-1?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=p(r),this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:o,position:l.position,glyph:l.text,color:l.textColor,size:l.textSize,angle:l.textAngle,alignment:l.textOffset,font:l.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=l.text,this.mode.indexOf(\"text\")!==-1?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=p(a),this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),n={gl:o,position:l.position,color:l.errorColor,error:l.errorBounds,lineWidth:l.errorLineWidth,capSize:l.errorCapSize,opacity:t.opacity},this.errorBars?l.errorBounds?this.errorBars.update(n):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):l.errorBounds&&(this.errorBars=g(n),this.scene.glplot.add(this.errorBars)),l.delaunayAxis>=0){var f=i(l.position,l.delaunayColor,l.delaunayAxis);f.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(f):(f.gl=o,this.delaunayMesh=m(f),this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},k.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=f},{\"../../constants/gl3d_dashes\":615,\"../../constants/gl_markers\":616,\"../../lib\":632,\"../../lib/gl_format_color\":630,\"../../lib/str2rgbarray\":645,\"../scatter/make_bubble_size_func\":859,\"./calc_errors\":869,\"delaunay-triangulate\":96,\"gl-error3d\":133,\"gl-line3d\":140,\"gl-mesh3d\":173,\"gl-scatter3d\":216}],871:[function(t,e,r){\"use strict\";function n(t,e,r){var n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,h){function f(r,n){return i.coerce(t,e,c,r,n)}var d=n(t,e,f);if(!d)return void(e.visible=!1);f(\"text\"),f(\"mode\"),a.hasLines(e)&&(f(\"connectgaps\"),s(t,e,r,h,f)),a.hasMarkers(e)&&o(t,e,r,h,f),a.hasText(e)&&l(t,e,h,f);var p=(e.line||{}).color,g=(e.marker||{}).color;f(\"surfaceaxis\")>=0&&f(\"surfacecolor\",p||g);for(var m=[\"x\",\"y\",\"z\"],v=0;v<3;++v){var y=\"projection.\"+m[v];f(y+\".show\")&&(f(y+\".opacity\"),f(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":562,\"../../lib\":632,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":867}],872:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":616,\"../../plots/gl3d\":702,\n",
+       "\"../scatter/colorbar\":847,\"./attributes\":867,\"./calc\":868,\"./convert\":870,\"./defaults\":871}],873:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/colorscale/color_attributes\"),o=t(\"../../lib/extend\").extendFlat,s=n.marker,l=n.line,u=s.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\"],dflt:\"ISO-3\"},mode:o({},n.mode,{dflt:\"markers\"}),text:o({},n.text,{}),textfont:n.textfont,textposition:n.textposition,line:{color:l.color,width:l.width,dash:l.dash},connectgaps:n.connectgaps,marker:o({},{symbol:s.symbol,opacity:s.opacity,size:s.size,sizeref:s.sizeref,sizemin:s.sizemin,sizemode:s.sizemode,showscale:s.showscale,line:o({},{width:u.width},a(\"marker.line\"))},a(\"marker\")),fill:{valType:\"enumerated\",values:[\"none\",\"toself\"],dflt:\"none\"},fillcolor:n.fillcolor,hoverinfo:o({},i.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../components/colorscale/color_attributes\":541,\"../../lib/extend\":625,\"../../plots/attributes\":660,\"../scatter/attributes\":844}],874:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../scatter/colorscale_calc\");e.exports=function(t,e){for(var r=Array.isArray(e.locations),a=r?e.locations.length:e.lon.length,o=[],s=0,l=0;l<a;l++){var u,c={};if(r){var h=e.locations[l];c.loc=h,u=\"string\"!=typeof h}else{var f=e.lon[l],d=e.lat[l];c.lonlat=[+f,+d],u=!n(f)||!n(d)}u?s>0&&(o[s-1].gapAfter=!0):(s++,o.push(c))}return i(e),o}},{\"../scatter/colorscale_calc\":848,\"fast-isnumeric\":104}],875:[function(t,e,r){\"use strict\";function n(t,e,r){var n,i,a=0,o=r(\"locations\");return o?(r(\"locationmode\"),a=o.length):(n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length),a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a)}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,h){function f(r,n){return i.coerce(t,e,c,r,n)}var d=n(t,e,f);return d?(f(\"text\"),f(\"mode\"),a.hasLines(e)&&(s(t,e,r,h,f),f(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,f),a.hasText(e)&&l(t,e,h,f),f(\"fill\"),\"none\"!==e.fill&&u(t,e,r,f),void f(\"hoverinfo\",1===h._dataLength?\"lon+lat+location+text\":void 0)):void(e.visible=!1)}},{\"../../lib\":632,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":873}],876:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.location=e.lon?e.lon:null,t}},{}],877:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t){return a.tickText(r,r.c2l(t),\"hover\").text+\"\\xb0\"}var i=t.hoverinfo,o=\"all\"===i?s.hoverinfo.flags:i.split(\"+\"),l=o.indexOf(\"location\")!==-1&&Array.isArray(t.locations),u=o.indexOf(\"lon\")!==-1,c=o.indexOf(\"lat\")!==-1,h=o.indexOf(\"text\")!==-1,f=[];return l?f.push(e.loc):u&&c?f.push(\"(\"+n(e.lonlat[0])+\", \"+n(e.lonlat[1])+\")\"):u?f.push(\"lon: \"+n(e.lonlat[0])):c&&f.push(\"lat: \"+n(e.lonlat[1])),h&&f.push(e.tx||t.text),f.join(\"<br>\")}var i=t(\"../../plots/cartesian/graph_interact\"),a=t(\"../../plots/cartesian/axes\"),o=t(\"../scatter/get_trace_color\"),s=t(\"./attributes\");e.exports=function(t){function e(t){return c.projection(t)}function r(t){var r=t.lonlat;if(null===r[0]||null===r[1])return 1/0;if(c.isLonLatOverEdges(r))return 1/0;var n=e(r),i=l.c2p(),a=u.c2p(),o=Math.abs(i-n[0]),s=Math.abs(a-n[1]),h=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(o*o+s*s)-h,1-3/h)}var a=t.cd,s=a[0].trace,l=t.xa,u=t.ya,c=t.subplot;if(!a[0].placeholder&&(i.getClosest(a,r,t),t.index!==!1)){var h=a[t.index],f=h.lonlat,d=e(f),p=h.mrc||1;return t.x0=d[0]-p,t.x1=d[0]+p,t.y0=d[1]-p,t.y1=d[1]+p,t.loc=h.loc,t.lat=f[0],t.lon=f[1],t.color=o(s,h),t.extraText=n(s,h,c.mockAxis),[t]}}},{\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/graph_interact\":670,\"../scatter/get_trace_color\":852,\"./attributes\":873}],878:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.hoverPoints=t(\"./hover\"),n.eventData=t(\"./event_data\"),n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":687,\"../scatter/colorbar\":847,\"./attributes\":873,\"./calc\":874,\"./defaults\":875,\"./event_data\":876,\"./hover\":877,\"./plot\":879}],879:[function(t,e,r){\"use strict\";function n(t,e){if(!Array.isArray(t.locations))return u.identity;var r=c(t,e),n=t.locationmode;return function(t){var e=h(n,t.loc,r);return e?(t.lonlat=e.properties.ct,t):(t.lonlat=[null,null],!1)}}function i(t,e,r){function n(t,n){d(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function a(t){var e=t.framework.selectAll(\"g.trace.scattergeo\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.each(function(t){var e=t[0].trace,r=o.select(this);r.selectAll(\"path.point\").call(s.pointStyle,e),r.selectAll(\"text\").call(s.textPointStyle,e)}),e.selectAll(\"path.js-line\").style(\"fill\",\"none\").each(function(t){var e=o.select(this),r=t.trace,n=r.line||{};e.call(l.stroke,n.color).call(s.dashLine,n.dash||\"\",n.width||0),\"none\"!==r.fill&&e.call(l.fill,r.fillcolor)})}var o=t(\"d3\"),s=t(\"../../components/drawing\"),l=t(\"../../components/color\"),u=t(\"../../lib\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,h=t(\"../../lib/geo_location_utils\").locationToFeature,f=t(\"../../lib/geojson_utils\"),d=t(\"../../lib/array_to_calc_item\"),p=t(\"../scatter/subtypes\");e.exports=function(t,e){function r(t){return t[0].trace.uid}var s=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,r);s.enter().append(\"g\").attr(\"class\",\"trace scattergeo\"),s.exit().remove(),s.selectAll(\"*\").remove(),s.each(function(e){var r=o.select(this),a=e[0].trace,s=n(a,t.topojson);e[0].placeholder&&r.remove();for(var l=[],u=0;u<e.length;u++){var c=s(e[u]);c&&(i(a,e[u],u),l.push(c))}if(p.hasLines(a)||\"none\"!==a.fill){var h=f.calcTraceToLineCoords(l),d=\"none\"!==a.fill?f.makePolygon(h,a):f.makeLine(h,a);r.selectAll(\"path.js-line\").data([d]).enter().append(\"path\").classed(\"js-line\",!0)}p.hasMarkers(a)&&r.selectAll(\"path.point\").data(l).enter().append(\"path\").classed(\"point\",!0),p.hasText(a)&&r.selectAll(\"g\").data(l).enter().append(\"g\").append(\"text\")}),a(t)}},{\"../../components/color\":533,\"../../components/drawing\":557,\"../../lib\":632,\"../../lib/array_to_calc_item\":621,\"../../lib/geo_location_utils\":628,\"../../lib/geojson_utils\":629,\"../../lib/topojson_utils\":647,\"../scatter/subtypes\":864,d3:95}],880:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/color_attributes\"),a=t(\"../../constants/gl2d_dashes\"),o=t(\"../../constants/gl_markers\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../lib/extend\").extendDeep,u=n.line,c=n.marker,h=c.line;e.exports={x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,text:s({},n.text,{}),mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\"],extras:[\"none\"]},line:{color:u.color,width:u.width,dash:{valType:\"enumerated\",values:Object.keys(a),dflt:\"solid\"}},marker:l({},i(\"marker\"),{symbol:{valType:\"enumerated\",values:Object.keys(o),dflt:\"circle\",arrayOk:!0},size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,opacity:c.opacity,showscale:c.showscale,line:l({},i(\"marker.line\"),{width:h.width})}),connectgaps:n.connectgaps,fill:s({},n.fill,{values:[\"none\",\"tozeroy\",\"tozerox\"]}),fillcolor:n.fillcolor,_nestedModules:{error_x:\"ErrorBars\",error_y:\"ErrorBars\",\"marker.colorbar\":\"Colorbar\"}}},{\"../../components/colorscale/color_attributes\":541,\"../../constants/gl2d_dashes\":614,\"../../constants/gl_markers\":616,\"../../lib/extend\":625,\"../scatter/attributes\":844}],881:[function(t,e,r){\"use 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R,O=A(t),F=t.marker,j=F.opacity,N=t.opacity,B=s(F,j,N,y),U=I(F.symbol,y),V=z(F.line.width,y),q=s(F.line,j,N,y);for(D=i(O,F.size,y),u=0;u<T;++u)for(R=b[u],this.scatterOptions.sizes[u]=4*D[R],this.scatterOptions.glyphs[u]=U[R],this.scatterOptions.borderWidths[u]=.5*V[R],c=0;c<4;++c)this.scatterOptions.colors[4*u+c]=B[4*R+c],this.scatterOptions.borderColors[4*u+c]=q[4*R+c];this.fancyScatter.update(this.scatterOptions)}else this.scatterOptions.positions=new Float64Array(0),this.scatterOptions.glyphs=[],this.fancyScatter.update(this.scatterOptions);this.scatterOptions.positions=new Float64Array(0),this.scatterOptions.glyphs=[],this.scatter.update(this.scatterOptions),this.expandAxesFancy(o,l,D)},L.updateLines=function(t,e){var r;if(this.hasLines){var n=e;if(!t.connectgaps){var i=0,a=this.xData,s=this.yData;for(n=new Float64Array(2*a.length),r=0;r<a.length;++r)n[i++]=a[r],n[i++]=s[r]}this.lineOptions.positions=n;var l=o(t.line.color,t.opacity,1),u=Math.round(.5*this.lineOptions.width),c=(E[t.line.dash]||[1]).slice();for(r=0;r<c.length;++r)c[r]*=u;switch(t.fill){case\"tozeroy\":this.lineOptions.fill=[!1,!0,!1,!1];break;case\"tozerox\":this.lineOptions.fill=[!0,!1,!1,!1];break;default:this.lineOptions.fill=[!1,!1,!1,!1]}var h=b(t.fillcolor);this.lineOptions.color=l,this.lineOptions.width=2*t.line.width,this.lineOptions.dashes=c,this.lineOptions.fillColor=[h,h,h,h]}else this.lineOptions.positions=new Float64Array(0);this.line.update(this.lineOptions)},L.updateError=function(t,e,r,n){var i=this[\"error\"+t],a=e[\"error_\"+t.toLowerCase()],s=this[\"error\"+t+\"Options\"];\"x\"===t.toLowerCase()&&a.copy_ystyle&&(a=e.error_y),this[\"hasError\"+t]?(s.positions=r,s.errors=n,s.capSize=a.width,s.lineWidth=a.thickness/2,s.color=o(a.color,1,1)):s.positions=new Float64Array(0),i.update(s)},L.expandAxesFast=function(t,e){for(var r,n,i,a=e||10,o=0;o<2;o++)r=this.scene[S[o]],n=r._min,n||(n=[]),n.push({val:t[o],pad:a}),i=r._max,i||(i=[]),i.push({val:t[o+2],pad:a})},L.expandAxesFancy=function(t,e,r){var n=this.scene,i={padded:!0,ppad:r};v.expand(n.xaxis,t,i),v.expand(n.yaxis,e,i)},L.dispose=function(){this.line.dispose(),this.errorX.dispose(),this.errorY.dispose(),this.scatter.dispose(),this.fancyScatter.dispose()},e.exports=c},{\"../../components/errorbars\":563,\"../../constants/gl2d_dashes\":614,\"../../constants/gl_markers\":616,\"../../lib\":632,\"../../lib/gl_format_color\":630,\"../../lib/str2rgbarray\":645,\"../../lib/typed_array_truncate\":648,\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/axis_autotype\":663,\"../scatter/get_trace_color\":852,\"../scatter/make_bubble_size_func\":859,\"../scatter/subtypes\":864,\"fast-isnumeric\":104,\"gl-error2d\":131,\"gl-line2d\":138,\"gl-scatter2d\":213,\"gl-scatter2d-fancy\":208}],882:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),h=t(\"./attributes\");e.exports=function(t,e,r,f){function d(r,i){return n.coerce(t,e,h,r,i)}var p=o(t,e,d);return p?(d(\"text\"),d(\"mode\",p<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(d(\"connectgaps\"),l(t,e,r,f,d)),a.hasMarkers(e)&&s(t,e,r,f,d),d(\"fill\"),\"none\"!==e.fill&&u(t,e,r,d),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":562,\"../../lib\":632,\"../scatter/constants\":849,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/xy_defaults\":866,\"./attributes\":880}],883:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":699,\"../scatter/colorbar\":847,\"../scatter3d/calc\":868,\"./attributes\":880,\"./convert\":881,\"./defaults\":882}],884:[function(t,e,r){\"use strict\";var n=t(\"../scattergeo/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/mapbox/layout_attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=n.line,u=n.marker;e.exports={lon:n.lon,lat:n.lat,mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],dflt:\"markers\",extras:[\"none\"]},text:s({},i.text,{}),line:{color:l.color,width:l.width,dash:l.dash},connectgaps:i.connectgaps,marker:{symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},opacity:s({},u.opacity,{arrayOk:!1}),size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,color:u.color,colorscale:u.colorscale,cauto:u.cauto,cmax:u.cmax,cmin:u.cmin,autocolorscale:u.autocolorscale,reversescale:u.reversescale,showscale:u.showscale},fill:n.fill,fillcolor:i.fillcolor,textfont:a.layers.symbol.textfont,textposition:a.layers.symbol.textposition,hoverinfo:s({},o.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../lib/extend\":625,\"../../plots/attributes\":660,\"../../plots/mapbox/layout_attributes\":719,\"../scatter/attributes\":844,\"../scattergeo/attributes\":873}],885:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale\"),o=t(\"../scatter/subtypes\"),s=t(\"../scatter/colorscale_calc\"),l=t(\"../scatter/make_bubble_size_func\");e.exports=function(t,e){var r=e.lon.length,u=e.marker,c=o.hasMarkers(e),h=c&&Array.isArray(u.color),f=c&&Array.isArray(u.size),d=c&&Array.isArray(u.symbol),p=Array.isArray(e.text);s(e);for(var g=a.hasColorscale(e,\"marker\")?a.makeColorScaleFunc(a.extractScale(u.colorscale,u.cmin,u.cmax)):i.identity,m=o.isBubble(e)?l(e):i.identity,v=[],y=0,x=0;x<r;x++){var b=e.lon[x],_=e.lat[x];if(n(b)&&n(_)){var w={};if(y++,w.lonlat=[+b,+_],c){if(h){var M=u.color[x];w.mc=M,w.mcc=g(M)}if(f){var A=u.size[x];w.ms=A,w.mrc=m(A)}if(d){var k=u.symbol[x];w.mx=\"string\"==typeof k?k:\"circle\"}}if(p){var T=e.text[x];w.tx=\"string\"==typeof T?T:\"\"}v.push(w)}else y>0&&(v[y-1].gapAfter=!0)}return v}},{\"../../components/colorscale\":548,\"../../lib\":632,\"../scatter/colorscale_calc\":848,\"../scatter/make_bubble_size_func\":859,\"../scatter/subtypes\":864,\"fast-isnumeric\":104}],886:[function(t,e,r){\"use strict\";function n(){return{geojson:h.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function i(t,e){function r(t,r,n,i){void 0===e[r][n]&&(e[r][n]=i),t[r]=e[r][n]}for(var n=t[0].trace,i=n.marker,a=Array.isArray(i.color),o=Array.isArray(i.size),s=[],l=0;l<t.length;l++){var u=t[l],c={};a&&r(c,p,u.mcc,l),o&&r(c,g,u.mrc,l),s.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:u.lonlat},properties:c})}return{type:\"FeatureCollection\",features:s}}function a(t){for(var e=t[0].trace,r=e.marker||{},n=r.symbol,i=e.text,a=\"circle\"!==n?l(n):u,o=f.hasText(e)?l(i):u,s=[],c=0;c<t.length;c++){var h=t[c];s.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:h.lonlat},properties:{symbol:a(h.mx),text:o(h.tx)}})}return{type:\"FeatureCollection\",features:s}}function o(t,e){var r,n=t.marker;if(Array.isArray(n.color)){for(var i=Object.keys(e[p]),a=[],o=0;o<i.length;o++){var s=i[o];a.push([e[p][s],s])}r={property:p,stops:a}}else r=n.color;return r}function s(t,e){var r,n=t.marker;if(Array.isArray(n.size)){for(var i=Object.keys(e[g]),a=[],o=0;o<i.length;o++){var s=i[o];a.push([e[g][s],+s])}a.sort(function(t,e){return t[0]-e[0]}),r={property:g,stops:a}}else r=n.size/2;return r}function l(t){return Array.isArray(t)?function(t){return t}:t?function(){return t}:u}function u(){return\"\"}var c=t(\"../../lib\"),h=t(\"../../lib/geojson_utils\"),f=t(\"../scatter/subtypes\"),d=t(\"../../plots/mapbox/convert_text_opts\"),p=\"circle-color\",g=\"circle-radius\";e.exports=function(t){var e=t[0].trace,r=e.visible===!0,l=\"none\"!==e.fill,u=f.hasLines(e),m=f.hasMarkers(e),v=f.hasText(e),y=m&&\"circle\"===e.marker.symbol,x=m&&\"circle\"!==e.marker.symbol,b=n(),_=n(),w=n(),M=n(),A={fill:b,line:_,circle:w,symbol:M};if(!r||t[0].placeholder)return A;var k;if((l||u)&&(k=h.calcTraceToLineCoords(t)),l&&(b.geojson=h.makePolygon(k),b.layout.visibility=\"visible\",c.extendFlat(b.paint,{\"fill-color\":e.fillcolor})),u&&(_.geojson=h.makeLine(k),_.layout.visibility=\"visible\",c.extendFlat(_.paint,{\"line-width\":e.line.width,\"line-color\":e.line.color,\"line-opacity\":e.opacity})),y){var T={};T[p]={},T[g]={},w.geojson=i(t,T),w.layout.visibility=\"visible\",c.extendFlat(w.paint,{\"circle-opacity\":e.opacity*e.marker.opacity,\"circle-color\":o(e,T),\"circle-radius\":s(e,T)})}if((x||v)&&(M.geojson=a(t),c.extendFlat(M.layout,{visibility:\"visible\",\"icon-image\":\"{symbol}-15\",\"text-field\":\"{text}\"}),x&&(c.extendFlat(M.layout,{\"icon-size\":e.marker.size/10}),c.extendFlat(M.paint,{\"icon-opacity\":e.opacity*e.marker.opacity,\"icon-color\":e.marker.color})),v)){var E=(e.marker||{}).size,S=d(e.textposition,E);c.extendFlat(M.layout,{\"text-size\":e.textfont.size,\"text-anchor\":S.anchor,\"text-offset\":S.offset}),c.extendFlat(M.paint,{\"text-color\":e.textfont.color,\"text-opacity\":e.opacity})}return A}},{\"../../lib\":632,\"../../lib/geojson_utils\":629,\"../../plots/mapbox/convert_text_opts\":716,\"../scatter/subtypes\":864}],887:[function(t,e,r){\"use strict\";function n(t,e,r){var n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length);return a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\"),h=t(\"../scatter/attributes\");e.exports=function(t,e,r,f){function d(r,n){return i.coerce(t,e,c,r,n)}function p(r,n){var a=r.indexOf(\".line\")===-1?c:h;return i.coerce(t,e,a,r,n)}var g=n(t,e,d);if(!g)return void(e.visible=!1);if(d(\"text\"),d(\"mode\"),a.hasLines(e)&&(s(t,e,r,f,d),d(\"connectgaps\")),a.hasMarkers(e)){o(t,e,r,f,p);var m=e.marker;\"circle\"!==m.symbol&&(Array.isArray(m.size)&&(m.size=m.size[0]),Array.isArray(m.color)&&(m.color=m.color[0]))}a.hasText(e)&&l(t,e,f,d),d(\"fill\"),\"none\"!==e.fill&&u(t,e,r,d),d(\"hoverinfo\",1===f._dataLength?\"lon+lat+text\":void 0)}},{\"../../lib\":632,\"../scatter/attributes\":844,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":884}],888:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t}},{}],889:[function(t,e,r){\"use strict\";function n(t,e){function r(t){return t+\"\\xb0\"}var n=t.hoverinfo.split(\"+\"),i=n.indexOf(\"all\")!==-1,a=n.indexOf(\"lon\")!==-1,o=n.indexOf(\"lat\")!==-1,s=e.lonlat,l=[];return i||a&&o?l.push(\"(\"+r(s[0])+\", \"+r(s[1])+\")\"):a?l.push(\"lon: \"+r(s[0])):o&&l.push(\"lat: \"+r(s[1])),(i||n.indexOf(\"text\")!==-1)&&l.push(e.tx||t.text),l.join(\"<br>\")}var i=t(\"../../plots/cartesian/graph_interact\"),a=t(\"../scatter/get_trace_color\");e.exports=function(t,e,r){function o(t){var e=t.lonlat,n=Math.abs(u.c2p(e)-u.c2p([d,e[1]])),i=Math.abs(c.c2p(e)-c.c2p([e[0],r])),a=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(n*n+i*i)-a,1-3/a)}var s=t.cd,l=s[0].trace,u=t.xa,c=t.ya;if(!s[0].placeholder){var h=e>=0?Math.floor((e+180)/360):Math.ceil((e-180)/360),f=360*h,d=e-f;if(i.getClosest(s,o,t),t.index!==!1){var p=s[t.index],g=p.lonlat,m=[g[0]+f,g[1]],v=u.c2p(m),y=c.c2p(m),x=p.mrc||1;return t.x0=v-x,t.x1=v+x,t.y0=y-x,t.y1=y+x,t.color=a(l,p),t.extraText=n(l,p),[t]}}}},{\"../../plots/cartesian/graph_interact\":670,\"../scatter/get_trace_color\":852}],890:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.hoverPoints=t(\"./hover\"),n.eventData=t(\"./event_data\"),n.plot=t(\"./plot\"),n.moduleType=\"trace\",n.name=\"scattermapbox\",n.basePlotModule=t(\"../../plots/mapbox\"),n.categories=[\"mapbox\",\"gl\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/mapbox\":717,\"../scatter/colorbar\":847,\"./attributes\":884,\"./calc\":885,\"./defaults\":887,\"./event_data\":888,\"./hover\":889,\"./plot\":891}],891:[function(t,e,r){\"use strict\";function n(t,e){this.mapbox=t,this.map=t.map,this.uid=e,this.idSourceFill=e+\"-source-fill\",this.idSourceLine=e+\"-source-line\",this.idSourceCircle=e+\"-source-circle\",this.idSourceSymbol=e+\"-source-symbol\",this.idLayerFill=e+\"-layer-fill\",this.idLayerLine=e+\"-layer-line\",this.idLayerCircle=e+\"-layer-circle\",this.idLayerSymbol=e+\"-layer-symbol\",this.mapbox.initSource(this.idSourceFill),this.mapbox.initSource(this.idSourceLine),this.mapbox.initSource(this.idSourceCircle),this.mapbox.initSource(this.idSourceSymbol),this.map.addLayer({id:this.idLayerFill,source:this.idSourceFill,type:\"fill\"}),this.map.addLayer({id:this.idLayerLine,source:this.idSourceLine,type:\"line\"}),this.map.addLayer({id:this.idLayerCircle,source:this.idSourceCircle,type:\"circle\"}),this.map.addLayer({id:this.idLayerSymbol,source:this.idSourceSymbol,type:\"symbol\"})}function i(t){return\"visible\"===t.layout.visibility}var a=t(\"./convert\"),o=n.prototype;o.update=function(t){var e=this.mapbox,r=a(t);e.setOptions(this.idLayerFill,\"setLayoutProperty\",r.fill.layout),e.setOptions(this.idLayerLine,\"setLayoutProperty\",r.line.layout),e.setOptions(this.idLayerCircle,\"setLayoutProperty\",r.circle.layout),e.setOptions(this.idLayerSymbol,\"setLayoutProperty\",r.symbol.layout),i(r.fill)&&(e.setSourceData(this.idSourceFill,r.fill.geojson),e.setOptions(this.idLayerFill,\"setPaintProperty\",r.fill.paint)),i(r.line)&&(e.setSourceData(this.idSourceLine,r.line.geojson),e.setOptions(this.idLayerLine,\"setPaintProperty\",r.line.paint)),i(r.circle)&&(e.setSourceData(this.idSourceCircle,r.circle.geojson),e.setOptions(this.idLayerCircle,\"setPaintProperty\",r.circle.paint)),i(r.symbol)&&(e.setSourceData(this.idSourceSymbol,r.symbol.geojson),e.setOptions(this.idLayerSymbol,\"setPaintProperty\",r.symbol.paint))},o.dispose=function(){var t=this.map;t.removeLayer(this.idLayerFill),t.removeLayer(this.idLayerLine),t.removeLayer(this.idLayerCircle),t.removeLayer(this.idLayerSymbol),t.removeSource(this.idSourceFill),t.removeSource(this.idSourceLine),t.removeSource(this.idSourceCircle),t.removeSource(this.idSourceSymbol)},e.exports=function(t,e){var r=e[0].trace,i=new n(t,r.uid);return i.update(e),i}},{\"./convert\":886}],892:[function(t,e,r){\"use strict\";var 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o=t(\"../lib\");r.moduleType=\"transform\",r.name=\"groupby\",r.attributes={enabled:{valType:\"boolean\",dflt:!0},groups:{valType:\"data_array\",dflt:[]},style:{valType:\"any\",dflt:{}}},r.supplyDefaults=function(t){function e(e,i){return o.coerce(t,n,r.attributes,e,i)}var n={},i=e(\"enabled\");return i?(e(\"groups\"),e(\"style\"),n):n},r.transform=function(t,e){for(var r=[],n=0;n<t.length;n++)r=r.concat(a(t[n],e));return r}},{\"../lib\":632}]},{},[15])(15)});\n",
+       "     });\n",
+       "     require(['plotly'], function(Plotly) {\n",
+       "         window.Plotly = Plotly;\n",
+       "     });\n",
+       " </script>\n",
+       " <p>Plotly javascript loaded.</p>\n",
+       " <p>To load again call <pre>init_notebook(true)</pre></p>\n",
+       " "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PlotlyJSBackend()"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "using Plots\n",
+    "plotlyjs()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:40:57.380825",
+     "start_time": "2016-12-05T05:40:53.891Z"
+    },
+    "collapsed": true,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "mm = readcsv(\"DatosPlano/mms2.csv\")[:,1]\n",
+    "rr = readcsv(\"DatosPlano/rrs2.csv\")[:,1]\n",
+    "cs = readcsv(\"DatosPlano/ccs2.csv\")[:,1];\n",
+    "append!(mm, readcsv(\"DatosPlano/mms3.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs3.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs3.csv\")[:,1]);\n",
+    "append!(mm, readcsv(\"DatosPlano/mms1.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs1.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs1.csv\")[:,1]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-04T23:41:11.272203",
+     "start_time": "2016-12-05T05:40:55.352Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<html>\n",
+       "<head>\n",
+       "     <script src=\"/home/daniel/.julia/v0.5/PlotlyJS/deps/plotly-latest.min.js\"></script>\n",
+       "</head>\n",
+       "<body>\n",
+       "     <div id=\"f1a64f6c-8d20-49f1-bd8a-3b68d5ba6de3\" class=\"plotly-graph-div\"></div>\n",
+       "\n",
+       "<script>\n",
+       "    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "    window.PLOTLYENV.BASE_URL=\"https://plot.ly\";\n",
+       "    Plotly.newPlot('f1a64f6c-8d20-49f1-bd8a-3b68d5ba6de3', 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+       "\n",
+       " </script>\n",
+       "\n",
+       "</body>\n",
+       "</html>\n"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(mm, rr, cs)\n",
+    "xlabel!(\"M\")\n",
+    "ylabel!(\"R\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "celltoolbar": "Slideshow",
+  "kernelspec": {
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+      {
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+}
diff --git a/proys/InsectPopulation/ProySofi/Proyecciones.ipynb b/proys/InsectPopulation/ProySofi/Proyecciones.ipynb
new file mode 100644
index 0000000..02efbae
--- /dev/null
+++ b/proys/InsectPopulation/ProySofi/Proyecciones.ipynb
@@ -0,0 +1,1356 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "using Plots, LaTeXStrings, TaylorSeries\n",
+    "include(\"AutomDiff_V2.jl\")\n",
+    "import AD: Dual, xdual\n",
+    "#pyplot(grid=:false, size=(400,267))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ciclosestables!"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "    ciclosestables!(xx, f, nit, nout, cc)\n",
+    "\n",
+    "Esta función itera el mapeo `f`, de una variable, `nit+nout` veces, \n",
+    "usando como condición inicial `x0=0`; los últimos `nout` iterados \n",
+    "actualizan al vector `xx` que tiene longitud `nout`. `cc` es el valor\n",
+    "del parámetro del mapeo `f`. El mapeo `f` debe ser definido de \n",
+    "tal manera que `f(x0,cc)` tenga sentido. La idea es los últimos \n",
+    "`nout` iterados reflejen los ciclos estables del mapeo `f`. \n",
+    "\"\"\"\n",
+    "function ciclosestables!(xx, f, nit, nout, cc,x0)\n",
+    "    @assert nit > 0 && nout > 0\n",
+    "    \n",
+    "    # Primeros nit iterados\n",
+    "   \n",
+    "    for it = 1:nit\n",
+    "        x0 = f(x0, cc)\n",
+    "    end\n",
+    "    \n",
+    "    # Se guardan los siguientes nout iterados\n",
+    "    for it = 1:nout\n",
+    "        x0 = f(x0, cc)\n",
+    "        @inbounds xx[it] = x0\n",
+    "    end\n",
+    "    \n",
+    "    nothing\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "diagbifurc"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "    diagbifurc(f, nit, nout, crange)\n",
+    "\n",
+    "Itera el mapeo `f` `nit+nout` veces y regresa una matriz\n",
+    "cuya columna `i` tiene los últimos `nout` iterados del mapeo\n",
+    "para el valor del parámetro del mapeo `crange[i]`.\n",
+    "\n",
+    "La función `f` debe ser definida de tal manera que `f(x0, c)` \n",
+    "tenga sentido.\n",
+    "\"\"\"\n",
+    "function diagbifurc(f, nit, nout, crange,x0)\n",
+    "    xx = Vector{Float64}(nout)\n",
+    "    ff = Array{Float64,2}(nout, length(crange))\n",
+    "    \n",
+    "    for ic in eachindex(crange)\n",
+    "        c = crange[ic]\n",
+    "        ciclosestables!(xx, f, nit, nout, c,x0)\n",
+    "        ff[:,ic] = xx\n",
+    "    end\n",
+    "    \n",
+    "    return ff\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "Ict(x,m, r,s) = (r*x^2)/((r-1)*x^2/m + x + s)\n",
+    "\n",
+    "M=63\n",
+    "R=20\n",
+    "Ict1(x,s) = Ict(x,M,R,s)\n",
+    "\n",
+    "crange = 0:1000\n",
+    "\n",
+    "ff = diagbifurc(Ict1, 1000, 256, crange,50); \n",
+    "cc = ones(size(ff)[1])*crange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "cc = reshape(cc, size(ff));"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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\" />"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scatter(cc, ff, markersize= 0.05)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/sof9409/anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:1288: UserWarning: findfont: Font family [u'Helvetica'] not found. Falling back to Bitstream Vera Sans\n",
+      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1-element Array{Float64,1}:\n",
+       " 300.0"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n = length(cc)\n",
+    "sc=Float64[]\n",
+    "for i in 1:n\n",
+    "    if ff[i]==0.0\n",
+    "        push!(sc,cc[i])\n",
+    "        \n",
+    "        break\n",
+    "    end\n",
+    "end\n",
+    "sc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapeo_liap_all"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "doc\"\"\"\n",
+    "    iterado(F,x0,n)\n",
+    "\n",
+    "Dado un punto $x_0$, esta funció guarda a todas la iteraciones bajo $F$ en un arreglo.\n",
+    "\"\"\"\n",
+    "\n",
+    "function iterado(F::Function,x0::Float64,n::Int)\n",
+    "    y = Float64[x0] ##El primer elemento es x_0\n",
+    "    x = x0\n",
+    "    for i in 1:n\n",
+    "        x=F(x) #El valor de x cambia con cada iteración\n",
+    "        push!(y,x) #Este nuevo valor se guarda en el arreglo\n",
+    "    end\n",
+    "    y\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    Lyapunov(y, F)\n",
+    "\n",
+    "Dado un punto un arreglo que contenga todas las iteraciones bajo $F$ de $x_0$, calcula \n",
+    "$\\frac{1}{n} \\sum_{i=1}^n \\log\\Big| \\, f'(x_i)\\, \\Big|.$\n",
+    "\"\"\"\n",
+    "\n",
+    "function Lyapunov(y, F::Function)\n",
+    "    n = length(y)\n",
+    "    l = 0\n",
+    "   \n",
+    "    for i in 1:n\n",
+    "        x = abs((F(xdual(y[i]))).der)\n",
+    "        l = l + log(x)\n",
+    "       \n",
+    "    end\n",
+    "    l/n\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "\n",
+    "Calcula el exponente de Lyapunov para un mapeo paramétrico $Q_c = Q_c(x, c)$ en un rango de parámetros `crange`, un\n",
+    "valor inicial `x0` y `n` iteraciones.\n",
+    "\"\"\"\n",
+    "\n",
+    "function mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "    mapeo = Float64[]\n",
+    "  \n",
+    "    for i in crange\n",
+    "        Qci(x) = Qc(x,i) \n",
+    "        y = iterado(Qci,x0,n)\n",
+    "        l = Lyapunov(y, Qci)\n",
+    "        if abs(l)<Inf #En algunos puntos labda diverge, por lo que si tiende a infinito, se la asigna el valor-2.5\n",
+    "            push!(mapeo,l)      \n",
+    "        else\n",
+    "            push!(mapeo,0.0)       \n",
+    "        end\n",
+    "      \n",
+    "    end\n",
+    "    mapeo\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "crange = 0.0:1:500\n",
+    "mapeo= mapeo_liap_all(crange,Ict1,1000.0);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p = plot(crange,mapeo)\n",
+    "\n",
+    "xlabel!(L\"c\")\n",
+    "ylabel!(L\"\\lambda\")\n",
+    "title!(L\"Exponente de Lyapunov $Q_c = x^2 +c$\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1-element Array{Float64,1}:\n",
+       " 299.5"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "n = length(crange)\n",
+    "sc=Float64[]\n",
+    "for i in 1:n\n",
+    "    if mapeo[i]==0.0\n",
+    "        push!(sc,(crange[i-1]+crange[i])/2)\n",
+    "        \n",
+    "        break\n",
+    "    end\n",
+    "end\n",
+    "sc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Method definition Ict(Any, Any, Any, Any) in module Main at In[4]:1 overwritten at In[11]:1.\n",
+      "WARNING: Method definition Ict1(Any, Any) in module Main at In[4]:5 overwritten at In[11]:5.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1-element Array{Float64,1}:\n",
+       " 300.0"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Ict(x,m, r,s) = (r*x^2)/((r-1)*x^2/m + x + s)\n",
+    "\n",
+    "M=63\n",
+    "R=20\n",
+    "Ict1(x,s) = Ict(x,M,R,s)\n",
+    "\n",
+    "crange = 0:1000\n",
+    "\n",
+    "ff = diagbifurc(Ict1, 1000, 256, crange,50); \n",
+    "cc = ones(size(ff)[1])*crange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "cc = reshape(cc, size(ff));\n",
+    "\n",
+    "n = length(cc)\n",
+    "sc=Float64[]\n",
+    "for i in 1:n\n",
+    "    if ff[i]==0.0\n",
+    "        push!(sc,cc[i])\n",
+    "        break\n",
+    "    end\n",
+    "end\n",
+    "sc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SC (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function SC(Mrange,Rrange)\n",
+    "    R = length(Rrange)\n",
+    "    Mmax = length(Mrange)\n",
+    "    M = zeros(Mmax,R)\n",
+    "    crange = 0:1000\n",
+    "    for i in 1:Mmax\n",
+    "        for j in 1:R\n",
+    "            I(x,s) = Ict(x,Mrange[i],Rrange[j],s)\n",
+    "            \n",
+    "            ff = diagbifurc(I, 1000, 256, crange,100); \n",
+    "            cc = ones(size(ff)[1])*crange';\n",
+    "            \n",
+    "            if mod(j,10) == 0\n",
+    "                @show(j,i)\n",
+    "            end\n",
+    "            \n",
+    "            n = length(cc)\n",
+    "            for k in 1:n\n",
+    "                if ff[k]==0.0\n",
+    "                    M[i,j]= cc[k]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "        end\n",
+    "    end\n",
+    "    M\n",
+    "end\n",
+    "            "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "j = 10\n",
+      "i = 1\n",
+      "j = 10\n",
+      "i = 2\n",
+      "j = 10\n",
+      "i = 3\n",
+      "j = 10\n",
+      "i = 4\n",
+      "j = 10\n",
+      "i = 5\n",
+      "j = 10\n",
+      "i = 6\n",
+      "j = 10\n",
+      "i = 7\n",
+      "j = 10\n",
+      "i = 8\n",
+      "j = 10\n",
+      "i = 9\n",
+      "j = 10\n",
+      "i = 10\n",
+      "j = 10\n",
+      "i = 11\n",
+      "j = 10\n",
+      "i = 12\n",
+      "j = 10\n",
+      "i = 13\n",
+      "j = 10\n",
+      "i = 14\n",
+      "j = 10\n",
+      "i = 15\n",
+      "j = 10\n",
+      "i = 16\n",
+      "j = 10\n",
+      "i = 17\n",
+      "j = 10\n",
+      "i = 18\n",
+      "j = 10\n",
+      "i = 19\n",
+      "j = 10\n",
+      "i = 20\n",
+      "j = 10\n",
+      "i = 21\n",
+      "j = 10\n",
+      "i = 22\n",
+      "j = 10\n",
+      "i = 23\n",
+      "j = 10\n",
+      "i = 24\n",
+      "j = 10\n",
+      "i = 25\n",
+      "j = 10\n",
+      "i = 26\n",
+      "j = 10\n",
+      "i = 27\n",
+      "j = 10\n",
+      "i = 28\n",
+      "j = 10\n",
+      "i = 29\n",
+      "j = 10\n",
+      "i = 30\n",
+      "j = 10\n",
+      "i = 31\n",
+      "j = 10\n",
+      "i = 32\n",
+      "j = 10\n",
+      "i = 33\n",
+      "j = 10\n",
+      "i = 34\n",
+      "j = 10\n",
+      "i = 35\n",
+      "j = 10\n",
+      "i = 36\n",
+      "j = 10\n",
+      "i = 37\n",
+      "j = 10\n",
+      "i = 38\n",
+      "j = 10\n",
+      "i = 39\n",
+      "j = 10\n",
+      "i = 40\n",
+      "j = 10\n",
+      "i = 41\n",
+      "j = 10\n",
+      "i = 42\n",
+      "j = 10\n",
+      "i = 43\n",
+      "j = 10\n",
+      "i = 44\n",
+      "j = 10\n",
+      "i = 45\n",
+      "j = 10\n",
+      "i = 46\n",
+      "j = 10\n",
+      "i = 47\n",
+      "j = 10\n",
+      "i = 48\n",
+      "j = 10\n",
+      "i = 49\n",
+      "j = 10\n",
+      "i = 50\n",
+      "j = 10\n",
+      "i = 51\n",
+      "j = 10\n",
+      "i = 52\n",
+      "j = 10\n",
+      "i = 53\n",
+      "j = 10\n",
+      "i = 54\n",
+      "j = 10\n",
+      "i = 55\n",
+      "j = 10\n",
+      "i = 56\n",
+      "j = 10\n",
+      "i = 57\n",
+      "j = 10\n",
+      "i = 58\n",
+      "j = 10\n",
+      "i = 59\n",
+      "j = 10\n",
+      "i = 60\n",
+      "j = 10\n",
+      "i = 61\n",
+      "j = 10\n",
+      "i = 62\n",
+      "j = 10\n",
+      "i = 63\n",
+      "j = 10\n",
+      "i = 64\n",
+      "j = 10\n",
+      "i = 65\n",
+      "j = 10\n",
+      "i = 66\n",
+      "j = 10\n",
+      "i = 67\n",
+      "j = 10\n",
+      "i = 68\n",
+      "j = 10\n",
+      "i = 69\n",
+      "j = 10\n",
+      "i = 70\n",
+      "j = 10\n",
+      "i = 71\n",
+      "j = 10\n",
+      "i = 72\n",
+      "j = 10\n",
+      "i = 73\n",
+      "j = 10\n",
+      "i = 74\n",
+      "j = 10\n",
+      "i = 75\n",
+      "j = 10\n",
+      "i = 76\n",
+      "j = 10\n",
+      "i = 77\n",
+      "j = 10\n",
+      "i = 78\n",
+      "j = 10\n",
+      "i = 79\n",
+      "j = 10\n",
+      "i = 80\n",
+      "j = 10\n",
+      "i = 81\n",
+      "j = 10\n",
+      "i = 82\n",
+      "j = 10\n",
+      "i = 83\n",
+      "j = 10\n",
+      "i = 84\n",
+      "j = 10\n",
+      "i = 85\n",
+      "j = 10\n",
+      "i = 86\n",
+      "j = 10\n",
+      "i = 87\n",
+      "j = 10\n",
+      "i = 88\n",
+      "j = 10\n",
+      "i = 89\n",
+      "j = 10\n",
+      "i = 90\n",
+      "j = 10\n",
+      "i = 91\n",
+      "j = 10\n",
+      "i = 92\n",
+      "j = 10\n",
+      "i = 93\n",
+      "j = 10\n",
+      "i = 94\n",
+      "j = 10\n",
+      "i = 95\n",
+      "j = 10\n",
+      "i = 96\n",
+      "j = 10\n",
+      "i = 97\n",
+      "j = 10\n",
+      "i = 98\n",
+      "j = 10\n",
+      "i = 99\n",
+      "j = 10\n",
+      "i = 100\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "100×17 Array{Float64,2}:\n",
+       "  1.0   1.0   1.0   1.0   1.0   1.0   1.0  …   1.0   1.0   1.0    1.0    2.0\n",
+       "  2.0   2.0   2.0   2.0   2.0   2.0   2.0      2.0   2.0   2.0    2.0    3.0\n",
+       "  3.0   3.0   3.0   3.0   3.0   3.0   3.0      3.0   3.0   3.0    3.0    4.0\n",
+       "  4.0   4.0   4.0   4.0   4.0   4.0   4.0      4.0   4.0   4.0    4.0    5.0\n",
+       "  5.0   5.0   5.0   5.0   5.0   5.0   5.0      5.0   5.0   5.0    5.0    6.0\n",
+       "  6.0   6.0   6.0   6.0   6.0   6.0   6.0  …   6.0   6.0   6.0    6.0    7.0\n",
+       "  7.0   7.0   7.0   7.0   7.0   7.0   7.0      7.0   7.0   7.0    7.0    8.0\n",
+       "  8.0   8.0   8.0   8.0   8.0   8.0   8.0      8.0   8.0   8.0    8.0    9.0\n",
+       "  8.0   8.0   9.0   9.0   9.0   9.0   9.0      9.0   9.0   9.0    9.0   10.0\n",
+       "  9.0   9.0   9.0   9.0  10.0  10.0  10.0     10.0  10.0  10.0   10.0   11.0\n",
+       " 10.0  10.0  10.0  10.0  10.0  11.0  11.0  …  11.0  11.0  11.0   11.0   12.0\n",
+       " 11.0  11.0  11.0  11.0  11.0  11.0  12.0     12.0  12.0  12.0   12.0   13.0\n",
+       " 12.0  12.0  12.0  12.0  12.0  12.0  12.0     13.0  13.0  13.0   13.0   14.0\n",
+       "  ⋮                             ⋮          ⋱                      ⋮         \n",
+       " 78.0  79.0  80.0  80.0  81.0  82.0  83.0     87.0  87.0  88.0   89.0   90.0\n",
+       " 79.0  80.0  81.0  81.0  82.0  83.0  83.0     88.0  88.0  89.0   90.0   91.0\n",
+       " 80.0  81.0  82.0  82.0  83.0  84.0  84.0  …  89.0  89.0  90.0   91.0   92.0\n",
+       " 81.0  82.0  82.0  83.0  84.0  85.0  85.0     90.0  90.0  91.0   92.0   93.0\n",
+       " 82.0  83.0  83.0  84.0  85.0  86.0  86.0     91.0  91.0  92.0   93.0   94.0\n",
+       " 83.0  83.0  84.0  85.0  86.0  86.0  87.0     92.0  92.0  93.0   94.0   95.0\n",
+       " 84.0  84.0  85.0  86.0  87.0  87.0  88.0     93.0  93.0  94.0   95.0   96.0\n",
+       " 85.0  85.0  86.0  87.0  88.0  88.0  89.0  …  94.0  94.0  95.0   96.0   97.0\n",
+       " 85.0  86.0  87.0  88.0  88.0  89.0  90.0     94.0  95.0  96.0   97.0   98.0\n",
+       " 86.0  87.0  88.0  89.0  89.0  90.0  91.0     95.0  96.0  97.0   98.0   99.0\n",
+       " 87.0  88.0  89.0  89.0  90.0  91.0  92.0     96.0  97.0  98.0   99.0  100.0\n",
+       " 88.0  89.0  90.0  90.0  91.0  92.0  93.0     97.0  98.0  99.0  100.0  101.0"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Rrange = 4.5:1/2^5:5\n",
+    "M=SC(1:100,Rrange)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(M[:,end-1:end])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "j = 10\n",
+      "i = 1\n",
+      "j = 20\n",
+      "i = 1\n",
+      "j = 30\n",
+      "i = 1\n",
+      "j = 10\n",
+      "i = 2\n",
+      "j = 20\n",
+      "i = 2\n",
+      "j = 30\n",
+      "i = 2\n",
+      "j = 10\n",
+      "i = 3\n",
+      "j = 20\n",
+      "i = 3\n",
+      "j = 30\n",
+      "i = 3\n",
+      "j = 10\n",
+      "i = 4\n",
+      "j = 20\n",
+      "i = 4\n",
+      "j = 30\n",
+      "i = 4\n",
+      "j = 10\n",
+      "i = 5\n",
+      "j = 20\n",
+      "i = 5\n",
+      "j = 30\n",
+      "i = 5\n",
+      "j = 10\n",
+      "i = 6\n",
+      "j = 20\n",
+      "i = 6\n",
+      "j = 30\n",
+      "i = 6\n",
+      "j = 10\n",
+      "i = 7\n",
+      "j = 20\n",
+      "i = 7\n",
+      "j = 30\n",
+      "i = 7\n",
+      "j = 10\n",
+      "i = 8\n",
+      "j = 20\n",
+      "i = 8\n",
+      "j = 30\n",
+      "i = 8\n",
+      "j = 10\n",
+      "i = 9\n",
+      "j = 20\n",
+      "i = 9\n",
+      "j = 30\n",
+      "i = 9\n",
+      "j = 10\n",
+      "i = 10\n",
+      "j = 20\n",
+      "i = 10\n",
+      "j = 30\n",
+      "i = 10\n",
+      "j = 10\n",
+      "i = 11\n",
+      "j = 20\n",
+      "i = 11\n",
+      "j = 30\n",
+      "i = 11\n",
+      "j = 10\n",
+      "i = 12\n",
+      "j = 20\n",
+      "i = 12\n",
+      "j = 30\n",
+      "i = 12\n",
+      "j = 10\n",
+      "i = 13\n",
+      "j = 20\n",
+      "i = 13\n",
+      "j = 30\n",
+      "i = 13\n",
+      "j = 10\n",
+      "i = 14\n",
+      "j = 20\n",
+      "i = 14\n",
+      "j = 30\n",
+      "i = 14\n",
+      "j = 10\n",
+      "i = 15\n",
+      "j = 20\n",
+      "i = 15\n",
+      "j = 30\n",
+      "i = 15\n",
+      "j = 10\n",
+      "i = 16\n",
+      "j = 20\n",
+      "i = 16\n",
+      "j = 30\n",
+      "i = 16\n",
+      "j = 10\n",
+      "i = 17\n",
+      "j = 20\n",
+      "i = 17\n",
+      "j = 30\n",
+      "i = 17\n",
+      "j = 10\n",
+      "i = 18\n",
+      "j = 20\n",
+      "i = 18\n",
+      "j = 30\n",
+      "i = 18\n",
+      "j = 10\n",
+      "i = 19\n",
+      "j = 20\n",
+      "i = 19\n",
+      "j = 30\n",
+      "i = 19\n",
+      "j = 10\n",
+      "i = 20\n",
+      "j = 20\n",
+      "i = 20\n",
+      "j = 30\n",
+      "i = 20\n",
+      "j = 10\n",
+      "i = 21\n",
+      "j = 20\n",
+      "i = 21\n",
+      "j = 30\n",
+      "i = 21\n",
+      "j = 10\n",
+      "i = 22\n",
+      "j = 20\n",
+      "i = 22\n",
+      "j = 30\n",
+      "i = 22\n",
+      "j = 10\n",
+      "i = 23\n",
+      "j = 20\n",
+      "i = 23\n",
+      "j = 30\n",
+      "i = 23\n",
+      "j = 10\n",
+      "i = 24\n",
+      "j = 20\n",
+      "i = 24\n",
+      "j = 30\n",
+      "i = 24\n",
+      "j = 10\n",
+      "i = 25\n",
+      "j = 20\n",
+      "i = 25\n",
+      "j = 30\n",
+      "i = 25\n",
+      "j = 10\n",
+      "i = 26\n",
+      "j = 20\n",
+      "i = 26\n",
+      "j = 30\n",
+      "i = 26\n",
+      "j = 10\n",
+      "i = 27\n",
+      "j = 20\n",
+      "i = 27\n",
+      "j = 30\n",
+      "i = 27\n",
+      "j = 10\n",
+      "i = 28\n",
+      "j = 20\n",
+      "i = 28\n",
+      "j = 30\n",
+      "i = 28\n",
+      "j = 10\n",
+      "i = 29\n",
+      "j = 20\n",
+      "i = 29\n",
+      "j = 30\n",
+      "i = 29\n",
+      "j = 10\n",
+      "i = 30\n",
+      "j = 20\n",
+      "i = 30\n",
+      "j = 30\n",
+      "i = 30\n",
+      "j = 10\n",
+      "i = 31\n",
+      "j = 20\n",
+      "i = 31\n",
+      "j = 30\n",
+      "i = 31\n",
+      "j = 10\n",
+      "i = 32\n",
+      "j = 20\n",
+      "i = 32\n",
+      "j = 30\n",
+      "i = 32\n",
+      "j = 10\n",
+      "i = 33\n",
+      "j = 20\n",
+      "i = 33\n",
+      "j = 30\n",
+      "i = 33\n",
+      "j = 10\n",
+      "i = 34\n",
+      "j = 20\n",
+      "i = 34\n",
+      "j = 30\n",
+      "i = 34\n",
+      "j = 10\n",
+      "i = 35\n",
+      "j = 20\n",
+      "i = 35\n",
+      "j = 30\n",
+      "i = 35\n",
+      "j = 10\n",
+      "i = 36\n",
+      "j = 20\n",
+      "i = 36\n",
+      "j = 30\n",
+      "i = 36\n",
+      "j = 10\n",
+      "i = 37\n",
+      "j = 20\n",
+      "i = 37\n",
+      "j = 30\n",
+      "i = 37\n",
+      "j = 10\n",
+      "i = 38\n",
+      "j = 20\n",
+      "i = 38\n",
+      "j = 30\n",
+      "i = 38\n",
+      "j = 10\n",
+      "i = 39\n",
+      "j = 20\n",
+      "i = 39\n",
+      "j = 30\n",
+      "i = 39\n",
+      "j = 10\n",
+      "i = 40\n",
+      "j = 20\n",
+      "i = 40\n",
+      "j = 30\n",
+      "i = 40\n",
+      "j = 10\n",
+      "i = 41\n",
+      "j = 20\n",
+      "i = 41\n",
+      "j = 30\n",
+      "i = 41\n",
+      "j = 10\n",
+      "i = 42\n",
+      "j = 20\n",
+      "i = 42\n",
+      "j = 30\n",
+      "i = 42\n",
+      "j = 10\n",
+      "i = 43\n",
+      "j = 20\n",
+      "i = 43\n",
+      "j = 30\n",
+      "i = 43\n",
+      "j = 10\n",
+      "i = 44\n",
+      "j = 20\n",
+      "i = 44\n",
+      "j = 30\n",
+      "i = 44\n",
+      "j = 10\n",
+      "i = 45\n",
+      "j = 20\n",
+      "i = 45\n",
+      "j = 30\n",
+      "i = 45\n",
+      "j = 10\n",
+      "i = 46\n",
+      "j = 20\n",
+      "i = 46\n",
+      "j = 30\n",
+      "i = 46\n",
+      "j = 10\n",
+      "i = 47\n",
+      "j = 20\n",
+      "i = 47\n",
+      "j = 30\n",
+      "i = 47\n",
+      "j = 10\n",
+      "i = 48\n",
+      "j = 20\n",
+      "i = 48\n",
+      "j = 30\n",
+      "i = 48\n",
+      "j = 10\n",
+      "i = 49\n",
+      "j = 20\n",
+      "i = 49\n",
+      "j = 30\n",
+      "i = 49\n",
+      "j = 10\n",
+      "i = 50\n",
+      "j = 20\n",
+      "i = 50\n",
+      "j = 30\n",
+      "i = 50\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "50×36 Array{Float64,2}:\n",
+       "  2.0   2.0   2.0   2.0    3.0    3.0  …    9.0   10.0   10.0   10.0   10.0\n",
+       "  3.0   3.0   4.0   4.0    5.0    5.0      18.0   19.0   19.0   20.0   20.0\n",
+       "  4.0   4.0   5.0   6.0    7.0    7.0      27.0   28.0   28.0   29.0   30.0\n",
+       "  5.0   6.0   7.0   8.0    9.0   10.0      36.0   37.0   38.0   39.0   40.0\n",
+       "  6.0   7.0   8.0   9.0   11.0   12.0      44.0   46.0   47.0   48.0   49.0\n",
+       "  7.0   8.0  10.0  11.0   13.0   14.0  …   53.0   55.0   56.0   58.0   59.0\n",
+       "  8.0   9.0  11.0  13.0   15.0   16.0      62.0   64.0   65.0   67.0   69.0\n",
+       "  9.0  11.0  13.0  15.0   17.0   19.0      71.0   73.0   75.0   77.0   79.0\n",
+       " 10.0  12.0  14.0  16.0   19.0   21.0      79.0   82.0   84.0   86.0   88.0\n",
+       " 11.0  13.0  16.0  18.0   21.0   23.0      88.0   91.0   93.0   96.0   98.0\n",
+       " 12.0  14.0  17.0  20.0   23.0   25.0  …   97.0  100.0  102.0  105.0  108.0\n",
+       " 13.0  16.0  19.0  22.0   25.0   28.0     106.0  109.0  112.0  115.0  118.0\n",
+       " 14.0  17.0  20.0  23.0   27.0   30.0     114.0  118.0  121.0  124.0  127.0\n",
+       "  ⋮                               ⋮    ⋱                                ⋮  \n",
+       " 40.0  49.0  59.0  69.0   79.0   88.0     342.0  352.0  361.0  371.0  381.0\n",
+       " 41.0  51.0  61.0  71.0   81.0   91.0     351.0  361.0  371.0  381.0  391.0\n",
+       " 42.0  52.0  62.0  72.0   83.0   93.0  …  359.0  370.0  380.0  390.0  400.0\n",
+       " 43.0  53.0  64.0  74.0   85.0   95.0     368.0  379.0  389.0  400.0  410.0\n",
+       " 44.0  54.0  65.0  76.0   87.0   97.0     377.0  388.0  398.0  409.0  420.0\n",
+       " 45.0  56.0  67.0  78.0   89.0  100.0     386.0  397.0  408.0  419.0  430.0\n",
+       " 46.0  57.0  68.0  79.0   91.0  102.0     394.0  406.0  417.0  428.0  439.0\n",
+       " 47.0  58.0  70.0  81.0   93.0  104.0  …  403.0  415.0  426.0  438.0  449.0\n",
+       " 48.0  59.0  71.0  83.0   95.0  106.0     412.0  424.0  435.0  447.0  459.0\n",
+       " 49.0  61.0  73.0  85.0   97.0  109.0     421.0  433.0  445.0  457.0  469.0\n",
+       " 50.0  62.0  74.0  86.0   99.0  111.0     429.0  442.0  454.0  466.0  478.0\n",
+       " 51.0  63.0  76.0  88.0  101.0  113.0     438.0  451.0  463.0  476.0  488.0"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Rrange = 5:40\n",
+    "M1=SC(1:50,Rrange)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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\" />"
+      ]
+     },
+     "execution_count": 116,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(M1[1:10,1:5])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "writecsv(\"M1.csv\", M1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "50×36 Array{Float64,2}:\n",
+       "  2.0   2.0   2.0   2.0    3.0    3.0  …    9.0   10.0   10.0   10.0   10.0\n",
+       "  3.0   3.0   4.0   4.0    5.0    5.0      18.0   19.0   19.0   20.0   20.0\n",
+       "  4.0   4.0   5.0   6.0    7.0    7.0      27.0   28.0   28.0   29.0   30.0\n",
+       "  5.0   6.0   7.0   8.0    9.0   10.0      36.0   37.0   38.0   39.0   40.0\n",
+       "  6.0   7.0   8.0   9.0   11.0   12.0      44.0   46.0   47.0   48.0   49.0\n",
+       "  7.0   8.0  10.0  11.0   13.0   14.0  …   53.0   55.0   56.0   58.0   59.0\n",
+       "  8.0   9.0  11.0  13.0   15.0   16.0      62.0   64.0   65.0   67.0   69.0\n",
+       "  9.0  11.0  13.0  15.0   17.0   19.0      71.0   73.0   75.0   77.0   79.0\n",
+       " 10.0  12.0  14.0  16.0   19.0   21.0      79.0   82.0   84.0   86.0   88.0\n",
+       " 11.0  13.0  16.0  18.0   21.0   23.0      88.0   91.0   93.0   96.0   98.0\n",
+       " 12.0  14.0  17.0  20.0   23.0   25.0  …   97.0  100.0  102.0  105.0  108.0\n",
+       " 13.0  16.0  19.0  22.0   25.0   28.0     106.0  109.0  112.0  115.0  118.0\n",
+       " 14.0  17.0  20.0  23.0   27.0   30.0     114.0  118.0  121.0  124.0  127.0\n",
+       "  ⋮                               ⋮    ⋱                                ⋮  \n",
+       " 40.0  49.0  59.0  69.0   79.0   88.0     342.0  352.0  361.0  371.0  381.0\n",
+       " 41.0  51.0  61.0  71.0   81.0   91.0     351.0  361.0  371.0  381.0  391.0\n",
+       " 42.0  52.0  62.0  72.0   83.0   93.0  …  359.0  370.0  380.0  390.0  400.0\n",
+       " 43.0  53.0  64.0  74.0   85.0   95.0     368.0  379.0  389.0  400.0  410.0\n",
+       " 44.0  54.0  65.0  76.0   87.0   97.0     377.0  388.0  398.0  409.0  420.0\n",
+       " 45.0  56.0  67.0  78.0   89.0  100.0     386.0  397.0  408.0  419.0  430.0\n",
+       " 46.0  57.0  68.0  79.0   91.0  102.0     394.0  406.0  417.0  428.0  439.0\n",
+       " 47.0  58.0  70.0  81.0   93.0  104.0  …  403.0  415.0  426.0  438.0  449.0\n",
+       " 48.0  59.0  71.0  83.0   95.0  106.0     412.0  424.0  435.0  447.0  459.0\n",
+       " 49.0  61.0  73.0  85.0   97.0  109.0     421.0  433.0  445.0  457.0  469.0\n",
+       " 50.0  62.0  74.0  86.0   99.0  111.0     429.0  442.0  454.0  466.0  478.0\n",
+       " 51.0  63.0  76.0  88.0  101.0  113.0     438.0  451.0  463.0  476.0  488.0"
+      ]
+     },
+     "execution_count": 118,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "MS = readcsv(\"M1.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([5.0,9.0,13.0,17.0,21.0,25.0,29.0,33.0,37.0],[1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0])"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dif=MS\n",
+    "    for j in 1:length(M1[:,1])-1 #fixed m\n",
+    "        dif[j,:]= M1[j+1,:]-M1[j,:]\n",
+    "end\n",
+    "\n",
+    "dif\n",
+    "dif[end,:]= dif[end-1,:]\n",
+    "steadyR = Float64[]\n",
+    "steapR = Float64[]\n",
+    "for i in 1:36\n",
+    "    u = unique(dif[:,i])\n",
+    "    if length(u)==1\n",
+    "        push!(steadyR,Rrange[i])\n",
+    "        push!(steapR,u[1])\n",
+    "    end\n",
+    "end\n",
+    "steadyR,steapR"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([4.0,8.0,12.0,16.0,20.0,24.0,28.0,32.0,36.0,40.0,44.0,48.0],[1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0,11.0,12.0])"
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dif2=MS\n",
+    "    for j in 1:length(M1[1,:])-1 #fixed m\n",
+    "        dif2[:,j]=  M1[:,j+1]-M1[:,j]\n",
+    "end\n",
+    "\n",
+    "dif2\n",
+    "dif[:,end]= dif[:,end-1]\n",
+    "steadyM = Float64[]\n",
+    "steapM = Float64[]\n",
+    "for i in 1:50\n",
+    "    u = unique(dif[i,:])\n",
+    "    if length(unique(dif[i,:]))==1\n",
+    "        push!(steadyM,i)\n",
+    "        push!(steapM,u[1])\n",
+    "    end\n",
+    "end\n",
+    "steadyM,steapM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: MethodError: Cannot `convert` an object of type Int64 to an object of type Range{T}\nThis may have arisen from a call to the constructor Range{T}(...),\nsince type constructors fall back to convert methods.\nwhile loading In[126], in expression starting on line 1",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: MethodError: Cannot `convert` an object of type Int64 to an object of type Range{T}\nThis may have arisen from a call to the constructor Range{T}(...),\nsince type constructors fall back to convert methods.\nwhile loading In[126], in expression starting on line 1",
+      "",
+      " in getindex(::Type{Range}, ::Int64) at ./array.jl:138"
+     ]
+    }
+   ],
+   "source": [
+    "unique(dif[:,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scatter(M1[1,:])\n",
+    "scatter!(M1[2,:])\n",
+    "scatter!(M1[3,:])\n",
+    "scatter!(M1[4,:])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1×8 Array{Float64,2}:\n",
+       " 1.0  9.0  16.0  24.0  31.0  39.0  46.0  54.0"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Rrange = 1+1/2^2:2:16\n",
+    "M2=SC(15,Rrange)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3-element Array{Int64,1}:\n",
+       " 1\n",
+       " 2\n",
+       " 3"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "unique([1,1,2,3])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Julia 0.5.0",
+   "language": "julia",
+   "name": "julia-0.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "0.5.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/proys/InsectPopulation/README.md b/proys/InsectPopulation/README.md
new file mode 100644
index 0000000..3465107
--- /dev/null
+++ b/proys/InsectPopulation/README.md
@@ -0,0 +1,22 @@
+# Proyecto: *Modelos discretos de control de poblaciones de insectos al introducir insectos estériles*
+
+=====================
+
+## Autores:
+
+- Sofía Cruz T. (**@cutsof**)
+
+- Daniel Martínez U.(**@danmarurr**)
+
+- Pablo Reséndiz V. (**@Pablorv**)
+
+
+=====================
+
+
+En este proyecto se estudia el mapeo que modela el control de poblaciones de insectos mediante la inserción de `S` insectos estériles. Dicho mapeo está dado por:
+
+![Mapeo de control](Figures/equation.png)
+
+donde `R` y `M` son parámetros que controlan la rapidez de crecimiento de población y el valor de población final respectivamente.
+
diff --git a/proys/InsectPopulation/TrabajoFinal.ipynb b/proys/InsectPopulation/TrabajoFinal.ipynb
new file mode 100644
index 0000000..66b20ca
--- /dev/null
+++ b/proys/InsectPopulation/TrabajoFinal.ipynb
@@ -0,0 +1,2046 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Control de Poblaciones de Insectos al Introducir Insectos Estériles\n",
+    "\n",
+    "\\ \n",
+    "\\\n",
+    "\n",
+    "\n",
+    "<center>Sofía Cruz T.</center>\n",
+    "<center>Daniel Martínez U.</center>\n",
+    "<center>Pablo Reśendiz V.</center>\n",
+    "\n",
+    "$$\n",
+    "N_{t+1}=\\frac{R N_t^2}{(R-1)\\frac{N_t^2}{M}+N_t+S}\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "En 1937, E. F. Knipling, propuso la Técnica de Insectos Estériles (SIT, en inglés). La técnica no fue implementada haste 1958 sobre una plaga de  `screwworm` en EEUU usando métodos físicos y químicos para causar esterilidad. El método ha sido implementado en México y otros países de Sudamérica con éxito.\n",
+    "\n",
+    "<img src=\"Figures/knipling.png\" width=\"150\">\n",
+    "<img src=\"Figures/worm.png\" width=\"150\">\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Hasta años recientes SIT sigue siendo una técnica usada y estudiada en genética de poblaciones\n",
+    "\n",
+    "* `Oliva, C., Damiens, D., Vreysen, M., Lempeiere, G., & Gilles, J. (2013). Reproductive strategies of aedes albopictus (diptera: Culicidae) and implications for the sterile insect technique. Plos One, 8(11), e78884. doi:10.1371/journal.pone.0078884`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "* `Barnes, B. N., Hofmeyr, J. H., Groenewald, S., Conlong, D. E., & Wohlfarter, M. (2015). The sterile insect technique in agricultural crops in south africa: A metamorphosis …. but will it fly? African Entomology, 23(1), 1-18. doi:10.4001/003.023.0103`\n",
+    "\n",
+    "* `Horner, R. M., Walker, J. T. S., Rogers, D. J., Lo, P. L., & Suckling, D. M. (2016). Use of the sterile insect technique in new zealand: Benefits and constraints. New Zealand Plant Protection, 69, 296-304.`\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "\n",
+    "Basándonos en la ecuación propuesta por `Murray, J. D. (2001). Mathematical biology, part I: An introduction Springer.` Nuestra ecuación tenemos varios parámetros:\n",
+    "\n",
+    "+ $N_t$ población al tiempo $t$\n",
+    "+ R Rapidez de crecimiento\n",
+    "+ S Número constante de individuos estériles\n",
+    "+ M Población convergente si $S=0$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:07:43.102140",
+     "start_time": "2016-12-05T07:07:34.862Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div id=\"interact-js-shim\">\n",
+       "    <script charset=\"utf-8\">\n",
+       "(function (IPython, $, _, MathJax) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    var OutputArea = IPython.version >= \"4.0.0\" ? require(\"notebook/js/outputarea\").OutputArea : IPython.OutputArea;\n",
+       "\n",
+       "    var redrawValue = function (container, type, val) {\n",
+       "\tvar selector = $(\"<div/>\");\n",
+       "\tvar oa = new OutputArea(_.extend(selector, {\n",
+       "\t    selector: selector,\n",
+       "\t    prompt_area: true,\n",
+       "\t    events: IPython.events,\n",
+       "\t    keyboard_manager: IPython.keyboard_manager\n",
+       "\t})); // Hack to work with IPython 2.1.0\n",
+       "\n",
+       "\tswitch (type) {\n",
+       "\tcase \"image/png\":\n",
+       "            var _src = 'data:' + type + ';base64,' + val;\n",
+       "\t    $(container).find(\"img\").attr('src', _src);\n",
+       "\t    break;\n",
+       "\tdefault:\n",
+       "\t    var toinsert = OutputArea.append_map[type].apply(\n",
+       "\t\toa, [val, {}, selector]\n",
+       "\t    );\n",
+       "\t    $(container).empty().append(toinsert.contents());\n",
+       "\t    selector.remove();\n",
+       "\t}\n",
+       "\tif (type === \"text/latex\" && MathJax) {\n",
+       "\t    MathJax.Hub.Queue([\"Typeset\", MathJax.Hub, toinsert.get(0)]);\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        //_.extend(comm_manager.targets, require(\"widgets/js/widget\"))\n",
+       "\t    comm_manager.register_target(\"Signal\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                //Widgets.log(\"message received\", msg);\n",
+       "                var val = msg.content.data.value;\n",
+       "                $(\".signal-\" + comm.comm_id).each(function() {\n",
+       "                var type = $(this).data(\"type\");\n",
+       "                if (val[type]) {\n",
+       "                    redrawValue(this, type, val[type], type);\n",
+       "                }\n",
+       "                });\n",
+       "                delete val;\n",
+       "                delete msg.content.data.value;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "\t    // coordingate with Comm and redraw Signals\n",
+       "\t    // XXX: Test using Reactive here to improve performance\n",
+       "\t    $([IPython.events]).on(\n",
+       "\t\t'output_appended.OutputArea', function (event, type, value, md, toinsert) {\n",
+       "\t\t    if (md && md.reactive) {\n",
+       "                // console.log(md.comm_id);\n",
+       "                toinsert.addClass(\"signal-\" + md.comm_id);\n",
+       "                toinsert.data(\"type\", type);\n",
+       "                // Signal back indicating the mimetype required\n",
+       "                var comm_manager = IPython.notebook.kernel.comm_manager;\n",
+       "                var comm = comm_manager.comms[md.comm_id];\n",
+       "                comm.then(function (c) {\n",
+       "                    c.send({action: \"subscribe_mime\",\n",
+       "                       mime: type});\n",
+       "                    toinsert.bind(\"destroyed\", function() {\n",
+       "                        c.send({action: \"unsubscribe_mime\",\n",
+       "                               mime: type});\n",
+       "                    });\n",
+       "                })\n",
+       "\t\t    }\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery, _, MathJax);\n",
+       "</script>\n",
+       "    <script>\n",
+       "        window.interactLoadedFlag = true\n",
+       "       $(\"#interact-js-shim\").bind(\"destroyed\", function () {\n",
+       "           if (window.interactLoadedFlag) {\n",
+       "               console.warn(\"JavaScript required by Interact will be removed if you remove this cell or run using Interact more than once.\")\n",
+       "           }\n",
+       "       })\n",
+       "       $([IPython.events]).on(\"kernel_starting.Kernel kernel_restarting.Kernel\", function () { window.interactLoadedFlag = false })\n",
+       "   </script>\n",
+       "</div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PyPlotBackend()"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "using Plots, LaTeXStrings, TaylorSeries, Interact\n",
+    "include(\"AutomDiff_V2.jl\")\n",
+    "import AD: Dual, xdual\n",
+    "pyplot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:07:43.203619",
+     "start_time": "2016-12-05T07:07:36.016Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "f (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f(x,α,β,γ) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:07:43.311141",
+     "start_time": "2016-12-05T07:07:36.545Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "iteramapeo"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "Este código nos permite iterar una función f n veces dada una condición inicial x0. \n",
+    "\"\"\"\n",
+    "function iteramapeo(f, x0, n)\n",
+    "    xx = [x0]\n",
+    "    fx = [0.0]\n",
+    "    for it = 1:n\n",
+    "        x1 = f(x0)\n",
+    "        push!(xx, x0)\n",
+    "        push!(fx, x1)\n",
+    "        x0 = x1\n",
+    "        push!(xx,x1)\n",
+    "        push!(fx,x1)\n",
+    "    end\n",
+    "    xx, fx\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:07:43.313639",
+     "start_time": "2016-12-05T07:07:39.416Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#14) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Aquí definimos el valor de los parámetros que utilizamos con la convención \\alpha \\equiv R, \\beta \\equiv M,\n",
+    "#\\gamma \\equiv S ```\n",
+    "α=500.0\n",
+    "β=10.0\n",
+    "γ=2.0\n",
+    "func = x -> f(x,α,β,γ)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:07:43.356637",
+     "start_time": "2016-12-05T07:07:40.663Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "xfin,ffin = iteramapeo(func,200.0,10);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Primero se realizó un análisis gráfico del mapeo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:13.567663",
+     "start_time": "2016-12-05T07:08:13.073Z"
+    },
+    "collapsed": false,
+    "scrolled": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(100.0, nactions=0),\"γ\",100.0,0.0:1.0:200.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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PdYDAgIM3kJLTEwEx3G4ePEiPvnkE73/0tLSIAiC7rbasGHDwHEcBg0ahFdffRUbNmyo0ufipUuXkJ+fjw4dOpT5HAdK8mnoMyoxMREA8NdffxmM0crKChcvXjRq++Hh4bh27Rr27duH2bNno3///igsLMTvv/+OHj164KOPPjJ6X+o7GoNlQVatWgWO4zB69Ogyy8PDw+Hh4YFt27YhKysLTk5OZV4vb7oEuVwOQRDKLJs8eTKWL18OT09P3VgnGxsbACWDzwsKCqoVu4ODAxITEzF79mzs2LEDu3fvBmMMzZo1w4wZM/DWW29V+P6hQ4ciOjoaS5cuxX//+1989913AEq+NJYsWWLwS/RJpeOmSsf5/FtFT3eV99qhQ4fQo0cPcByH3r1746mnnoJKpQLHcdi6dSvOnDlT7XwBQHZ2NjiOM+qx/tL9Ky/WRo0aVelLoLzpIkrbz87O1i1bsmQJpk2bBjc3N/Tp0wdNmzaFUqkEAHz55Zfl5qC8WKvb3r9lZ2eXO9VHVZ7m27x5M+bPn4/169fjo48+AmMMDg4OiIqKwvz583Wx1YSDg4PestJioCoPKDx+/LjcfXZ3d9etU+rrr79G8+bNsWbNGnz22Wf49NNPoVAoMGzYMCxZsgQuLi6VbnP06NH4/PPPsW7dOkRERAAAfvnlF3Ach5dffrnMuqbo2+oe6+Wtn5mZCcYY1q9fX+42OY7TPeTTsWNHxMXFYf78+fjtt9+wdu1aMMbw7LPPYtGiRejevXuF8ZeeO1X5LMrMzASACgfRV2XurNIHbEofshEEAWvXrsWbb76JBQsWYOjQoRX+0UlKUIFlIW7fvo19+/YBQLkDTzmOw7p16zBp0qRqbSM9PR3fffcd2rVrh8OHD+sKKwC4f/8+5s6dW612SzVt2hSrV68GUHJ1Ye/evfj6668xadIkODs7Y/jw4RW+PyIiAhEREdBoNDh48CC2bNmClStXom/fvrh48aLBL6lSpa89ePDA4Ov37983uLyigcmfffYZCgsLceDAAQQHB5d57fDhwzhz5kyF+1MZJycnMMZw586dStct3b/79++jWbNmeq/fv3+/wvz8W3lX3krzVFq0a7VafPrpp2jSpAlOnz6t94W8aNGicrdhKK81ae/fHB0dy30yrbz+NkShUGDevHmYN28eUlNTERsbi++//x7Lli1Dfn4+VqxYYXRbtc3BwaHcYzwtLU23Time5/Hee+/hvffeQ1paGuLi4rBmzRr8/PPPuH//Pnbv3l3pNtu0aYN27dph586dyMnJgVwuR3R0NPz8/MpcSTNV31b3WC/vPHZwcADHcdi5cyf69u1rVAxdunTBrl27UFBQgMTEROzYsQPLly/HgAEDcO7cuQofXik9d6ryWVS6Pzk5ObC1tTUqxqoofcoyPj4ev/zyC2JjY6nAMgLdIrQQa9asgSAICAkJwfjx4/X+Gzt2bIW3CY1x/fp1MMbQo0ePMsUVAJPP7uvv74+pU6di/fr1YIxh+/btRr/Xzs4OvXv3xvfff4+xY8fi/v37ukvo5Sm9wnXo0CG910on2auq69evw9nZWa+4ysvLQ1JSUpXb+7eOHTsCAPbu3VvpuoGBgWCMYf/+/XqvHTlyBPn5+QgMDDR628XFxTh8+LDe8tLjoLStjIwMZGdnIzg4WO8L89ixY0Y/Pl7KlO0FBARAo9EYvF0UHx9frdmyvby8MHbsWOzfvx8qlarMcSuTycAYq9IVp+rgeb7cbQQGBiI3NxfHjx/Xey02Nla3jiGNGzfWPVncsmVL/P3330ZfLRw9ejTy8/OxefNmbN26FWq1Wu9Ku6n61tTHeqdOncAYM/jZUBkbGxuEhoZi8eLFmDVrFvLy8nR/CJfH19cXCoUCx48fR2FhYZnXyoujU6dOAGDwnDSl0qc9iXGowLIQa9eu1c1388MPP+j9t3r1agQHB+PMmTPV/nL38vICUFKEPDk+5fbt25g1a1aNfr7hwoULBv9iK/2rWqFQVPj+hIQEvduZwP//tVfZ+z09PdGlSxecOnUKv//+e5nXPv/8c90l+Krw8vLCo0ePyowlEwQB77//fpXn9DGkQ4cOePbZZxEfH29w7qYnb4OMGjUKcrkcS5cuxb1793TLi4qKMH36dHAcV+axfmPMmjWrzM8w3b59G8uWLYNCodCNiXNzc4NSqURSUlKZL8hHjx5h8uTJVdqeqdsbPXo0GGP48MMPyxw7Z8+exbp164xqIyMjA+fPn9dbnpmZiYKCgjLHXenkuOXNSWcqzs7OuH37tsHXXnnlFTDGMHPmzDLjxG7duoWlS5fCysoKo0aNAgAUFhYa/MLOycmBWq3WjY8yxqhRo8DzPH755Rf88ssv4HkeL730Upl1TNW3pj7WBw4cCE9PTyxdutTgPFTFxcU4ePCg7t9HjhwxWHga+1lmbW2NYcOG4cGDB3pz2f34448Gp1CYMGECZDIZJk+ebPD4ys7ONmqM5Z49e7B9+3aDBfrVq1d1n40hISGVtkXoFqFFiImJwY0bNxAWFqYrggyJiorC4cOHsWrVKoODZivTuHFjDBkyBFu2bEGHDh3Qo0cPpKWlYdeuXejZsyeuXbtW7X3Yt28fpk2bhi5dusDX1xcuLi66OaOUSmWZeZUMefvtt3H37l2EhITA29sbHMfhwIEDOHbsGIKDg436QPjmm28QGhqKUaNGYfPmzWjZsiWSkpKQmJiIbt26IT4+Xu8LpaKB0JMnT8bevXvRpUsXDBs2DAqFAvv378fdu3fRvXt3xMXFGZecCvz6668ICwvDG2+8gV9++QXBwcHIz8/H+fPncerUKV0h17x5cyxatAhTp06Fv78/hg0bBjs7O+zYsQOXL1/GoEGDdF+sxnB3d4dGo4G/vz8iIiJ0P8+UmZmJb775Rjeeh+M4TJgwAUuXLkVAQAAiIiLw+PFj7N69G97e3mjSpEmV9teU7b3yyitYv349/vrrLwQGBqJv3754+PAhNmzYgD59+mDHjh2VtnHnzh0EBgYiICAA/v7+8PDwwMOHD7Ft2zYUFxdj2rRpunWDg4OhVCrx1VdfITMzEw0bNgQAfPjhh1XKQWXCw8Px+++/Y/DgwQgMDIRMJkNkZCTatm2L0aNHY8uWLdi+fTv8/f0xYMAAqNVqbNq0CY8ePcLSpUt1t6/y8vJ052P79u3h6ekJtVqNnTt34v79+5g2bRqsrKyMiqlRo0bo2bMn9u7dC57nERISojcWzFR9a+pj3draGps3b0a/fv3QrVs3hIeHo23btuA4DqmpqUhISICrq6tuhvNFixYhNjYWoaGh8PHxgUKhQFJSEmJiYtCyZUsMHjy40m0uXLgQMTEx+Oijj5CQkKCbB2v37t3o06eP3lXrNm3a4LvvvsOECRPg5+eHfv36oUWLFsjJycH169cRFxeHqKgo3djU8ly8eBHvvvsuXF1dERoaihYtWoAxhqtXr+LPP/9EUVERJkyYUOEDKOQJdfnIIqkdo0aNYjzPs59//rnC9R4/fsxsbW2Zs7Ozbl4bb29v1rx5c4Prd+/enclksjLLNBoNmzZtGmvevDlTKpXMz8+PzZ8/nxUVFTGe5w0+ci+TyfSmaeB5vsyUDsnJyezdd99l7du3182l1LJlSzZu3DiWnJxcpk1Dj2Zv2rSJjRgxgj311FNMpVKxBg0asMDAQPbFF18YnFenPKdPn2Z9+/ZlDg4OzNHRkQ0YMICdP3+eRUREMJ7nqzSvEWMlj3h36NCBqVQq5ubmxkaOHMlu3LhhMC+MMYM5ZKzkkXye59m8efP0Xnvw4AF79913WcuWLZlCoWCurq4sODiYLVu2TG/dHTt2sLCwMObo6MiUSiULCAhgX331lVGPypcqnaogKyuLvfnmm8zd3Z0plUoWFBSkNycTY4wVFxezBQsWMD8/P6ZUKpm3tzf74IMPmEajMXj8lZeb6rZXkby8PDZjxgzWrFkzplQq2TPPPMNWrVpVbr7/3X5WVhabN28e6969O/Pw8GAKhYI1bdqU9e/fn+3du1dve7t372adOnVidnZ2jOf5MueXof2uqN8NnUeMMZaWlsZGjBjB3NzcmFwu1ztGtVotW7p0KQsICGBKpVI3/cHOnTvLtFNUVMQWL17Mnn/+eebp6ckUCgVzd3dn3bt3N9jPlfn11191+7xy5UqD61S1bw19FpQy9lgvL4//dvfuXfbuu+/qYnNycmJt2rRhr7/+OouNjdWtt3fvXjZ27FjWunVr5ujoyBwcHNgzzzzDPv74Y/bw4UMjs1UyN9nIkSOZs7MzU6lUrHv37iwhIaHCfT5+/DgbNWoUa9q0KbOxsWFubm6sQ4cO7MMPP2SXLl2qdJsZGRls1apVbNiwYbr4bWxsmIeHBxs4cCDbunWr0fETxjjGjHgWmZB6TBAEtGjRAvn5+WVuOdRXPj4+4DgO169fFzsUQgiRLBqDRcj/aLVag3NnLViwAKmpqUZd2ieEEEIACY7BKigowIgRI5CcnAylUgk3Nzd89913aNGiBdLT0zFmzBhcu3YNCoUCy5cvR9euXcUOmVgItVoNDw8P9OrVC76+vigqKkJiYiKOHTsGDw8PzJkzR+wQCSGEmAlJXsF64403cPHiRZw8eRKRkZEYP348AGD69OkIDg7G5cuXsXr1aowaNarWH3km9YetrS3Gjx+Pa9euYdWqVfjhhx/w4MEDvPXWWzh69GiVJp+0dDV5YpQQQuoDyY/BOnHiBF588UVcv34d9vb2uHbtmm6G286dO2P+/Pm62WYJIYQQQqRAklewnrRs2TIMGjQImZmZKC4uLvPzAV5eXrh586aI0RFCCCGE6JPcGKwnzZ8/H9euXcMPP/yA3NzcKr03IyMDe/bsgbe3t0l+C4wQQggh9UdeXh5SUlLQp0+fcn9/tSKSLbC++OILREdHIyYmBgqFAgqFAnK5HA8ePNBdxUpJSSn3h0v37Nmj90OihBBCCCFVsW7dOr1fHjCGJAuspUuXYsOGDYiJiYG9vb1u+YsvvogVK1Zgzpw5OHbsGO7evYtu3boZbKN0NuJ169ahdevWdRG2yb3zzjv46quvxA6j3tHm5iDjh48R91DAsP98LXY49Vp9OAfyihluqoEbOQwpaoaUHIYbOUCqGij63zM81jKgqR3QzA5opuKe+F8OjZSAjK+dhw7qQ/6ljvpAPMnJyXj55Zcr/HHuikiuwLpz5w6mTp2KFi1aICwsDIwxKBQKHD58GAsXLsTo0aPh6+sLGxsb/Prrr5DJZAbbKb0t2Lp162r9LIwUODk5mW3s5uzxvg1wb+SEnx8zyr/ILOkcUBcxnMtkOPsISH7EkJzFcDGLIVUNlD5p1EgJtG7KoacTh9ZOQCsnDq2cODS1A3gRnty0pPybK+oD8VV3mJHkCiwPDw+DP9oLlPwY6J49e+o4IlKfMG0x1Ad2wK5DD2guxYgdDjFDxQLD1cfAmYcMZx8xnM1kOJNZclUKAHgOaGFfUjwNa87/r4gq+XcDG5r+ghBLIbkCi/y/q1evih1CvZN3KgFC9kOoQgfi6if/FTucek/q50BWAcPJhwwnM0qKqDOZDBeygIL/3dprrAT8nTm84M2jrTOHts4lV6aUcvMopKSe//pAin1w8+ZNZGRkiB2Gybm6upY7rrs6qMCSMJpEte6p47fBxjcQVu7elH8JkFIfPMwvKaZOpDMkPWQ4kcFw7XHJa7Zy4JkGHIJcOYz15XTFlKvCPAqp8kgp//WV1Prg5s2baN26dZWf7DcHtra2SE5ONlmRRQWWhM2dO1fsEOqVgpRkFKZehMtrnwCg/EuBWH2QXchw9AHDsfSSQiopgyFFXfKavRUQ6MIh0pNHkCuH9q4cfB1rb6C5mOgcEJ/U+iAjIwO5ublm/QCZIaUD2jMyMqjAqg9Gjhwpdgj1ijouGnLXJlC0fhYA5V8K6qIPtAJDchZw5AHDkQcCjjxguPCoZOC5ozUQ5MJhaHMeQS4lxVRLR3EGnIuBzgHxSbUPzPkBsrpCBRYhAIqz0pF3+gCcBr0Ojpf8DxyQGnhUwHAwjf1Gvm5jAAAgAElEQVSvoGI4ms6QU1Qy+LxtAyCkEY9p/hw6u3F4qh4VU4QQ06ICS8IyMjKqNXssqTrNgZ3grG1g27GXbhnlX3ym6IMHeQzx9xji0xji7gk4m1lydcpNCXR24zCzHY9gNw4dGnJQWVEx9SQ6B8RHfWC+6E91CRs3bpzYIdQLQmE+NId3w65TH/AKW91yyr/4qtMHt9UM668KeCNBi9a/F6HRumK8GKPFn7cEtHflsLqbDFeHy5H2khzbessxs50M3ZvwVFwZQOeA+KgPqi81NRVhYWGizSVGV7AkTGqDGy1V7olYCLk5UHWNLLOc8i8+Y/ogq4Ah9i7DvjsMf98RcOV/T/a1dgK6u/OYHciha2MOTVVUQFUVnQPioz6oPgcHB3z22WfIzs7Ghx9+WOfbpwJLwmgAYe1jjEEdFw1Fm86Qu7qXeY3yLz5DfVCoLRk7VVJQlYyhEhjQ0gHo5cFjQceSgspNSQVVTdE5ID7qg8otWbIEly9fxn//WzJ3YXZ2Nlq2bIkrV67gueeeQ1xcnChxUYFF6rWCK6dQnJYKpyETxA6FVOCmmmHXTQF/3iq5WqUpBpxtgB5NOIzzk6GXBwdveyqoCJGC648Zsgqr914na6C5Q9XO5fHjx8PPzw+LFy+Gg4MD1qxZg0GDBsHJyal6QZgIFVikXlPHRcOqiQ9sWvqLHQp5glYouTK18ybDzpsCzmQCMg4Iaczhw0AevTw4BLpwFjn3FCHmLCOf4alNxRBY5esaIuOAtJflVZqk19HREUOHDsXq1avxzjvvYMWKFdi0aVP1AjAhKrAkbNWqVXj11VfFDsNiFaffRf6Fo2gw/B1wBh7Fp/zXrZxCht23Sgqq3bcZMvIBFfIxqKUSs9rx6NOUgxP9Vl+donNAfObWB64KDleGyWt0Bas6v4AwefJkREZGolWrVnBzc0NAQED1AjAhKrAkLCkpyaxOLHOjTtgG3tYBtu3DDL5O+a99WQUM21MZ/kgRsOc2Q4EWaOsMvNaKxwBPDr/Mm4kVr30rdpj1Fp0D4jPHPqjqLT5T8PPzQ/PmzfH666/jiy++KPMaYwyMVfOSWg1QgSVhy5cvFzsEiyXkaaBJ3AtVt0HgrKwNrkP5rx0Z+QzbUhg23xAQc5ehSACC3Th81oHHC948fJ74cH5uORVXYqJzQHzUB8Z77bXXMHnyZAwZMgQAkJeXB19fXxQWFiI7Oxuenp4YPXo0PvvsszqJhwosUi9pEveCFRdB1WWA2KHUC9mFDFtuMKy/JiD2bslTf6HuHJZ04vGCDw8PO7r1RwipmdjYWEyYMAEymQwAoFQqcevWLdHioQKL1DtM0EKdsA227bpC5ugidjgWq1BbMqbq16sCtt9kKNQC3dw5LO/CY5AXj0a2VFQRQmru3r17CA8Ph4uLC/bs2SN2ODpUYJF6J//8UWgfpkH1ykyxQ7E4jDEcvM+w7grDphsCHhUAAc7Af9rzGNmCp8k+CSEm5+7ujuTkZLHD0EM/lSNhkZGRla9EqkwdHw1rn6dh7elX4XqUf+Ol5TJ8floLv03F6LpDi923BbzRisfZIXKcGmKFaQGyahVX1AfiovyLj/rAfNEVLAmbNGmS2CFYnMK711Fw5TScX5lV6bqU/4oVCwx7bjOsvChg500GOQ8M9eHwQ1ceoe4ceANTX1QV9YG4KP/ioz4wX1RgSVjv3r3FDsHiqOOiIXNyhdL/uUrXpfwbdlvN8N+LAtZcFnBHU3IL8KtgHqNa8mhg4nmqqA/ERfkXH/WB+aICi9QbWnUWck/EwuH50eBkdOhXBWMMCWkM35wXsDWFwVYOvNSSx3g/HkGuMDhRKyGE1Gf0LUPqDc2hP8FxPFTBfcUOxWzkFjOsv8rw7XktTmcCrZyAZcE8xjzFw96aiipCiHTFxsZixowZ0Gg04DgO/fv3x8KFC+ts+zTIXcKio6PFDsFisOIiqA/shO2zPcDb2Rv1nvqc/3u5DDOOatF0fTFeT9DCU8Vhb18ZLgyVY2IbWZ0VV/W5D6SA8i8+6oPqc3Z2xsaNG3Hu3DmcOHECBw8exM8//1xn26cCS8J+++03sUOwGHmnEiA8zoQqdKDR76mP+b+UxfBafDG8fyvGdxcERPnyuDpcju195OjVlK/zW4H1sQ+khPIvPuqDyi1ZsgRvvPGG7t/Z2dlo2LAhvLy84O3tDQCwtrZGu3btkJKSUmdx0S1CCdu4caPYIVgExhhy4qNh4xcEq8ZeRr+vPuU/8YGARacFRKcwNFIC89rzePNpHo4i3wasT30gRZR/8VEfVG78+PHw8/PD4sWL4eDggDVr1mDQoEFwcnLSrZOWlobNmzdj165ddRYXFVjE4hWmJKPo5mW4vD5P7FAkJ/augHlJAvbfY/B1BH7oKsPLLTko5DS+ihBSPcUZ9yDkqav1Xl6pgtzVvUrvcXR0xNChQ7F69Wq88847WLFiBTZt2qR7/fHjx4iMjMSMGTMQFBRUrbiqgwosYvHUcdGQN/SAolUHsUORjLh7AuacEBB3jyHIFfijpwwDvTjIeCqsCCHVp1VnI+2zVwEmVK8Bnof7vN8gUzlW6W2TJ09GZGQkWrVqBTc3NwQEBAAA1Go1+vbti8GDB2PKlCnVi6maqMAiFq34UTryzhyA0+A3wfE05DDhf4VV7D2GQBdgW28ZIjw5mmaBEGISMpUjGn+4qkZXsKpaXAGAn58fmjdvjtdffx1ffPEFAECj0aBPnz7o27cvZs6s+59Go28cCYuKihI7BLOnObADnLUSth17Vfm9lpT/4+kCev1ZjNCdWmQWMGztJcOJwXJEetX9wPWqsKQ+MEeUf/GZYx/IXd1h3eypav1X1duDT3rttdeg1WoxZMgQAMCyZctw/PhxbNmyBYGBgQgKCsKCBQtMtZuVoitYEkYz+NaMUJgP9eE/Yde5D3gbZZXfbwn5v/6Y4cPjWmy4xvC0U8mtwEHepvkZm7pgCX1gzij/4qM+MF5sbCwmTJgAmUwGAJg1axZmzar8Z9FqCxVYEjZy5EixQzBrucf/AcvLhapr9X4s1Zzz/zCf4dOTApZfENBQAazsKsMrvhzkZjbGypz7wBJQ/sVHfVC5e/fuITw8HC4uLtizZ4/Y4ehQgUUsEmMM6vhoKNp2htylsdjh1JkCLcOycwLmnxIgMGBOEI93nuFhZ2VehRUhhBjL3d0dycnJYoehhwosYpEKLp9EcdpNNBhaf36JfvctAVMOaXE9B3izNY/ZQTzclFRYEUKIGGiQu4QdOHBA7BDMljouGlYeLWDdom212zCX/F97zBC5pxj9/tKiqR2H0y/I8W0XmUUUV+bSB5aK8i8+6gPzRQWWhH3++edih2CWih7cRv6Fo1CFDqzRE3JSz39uMcPHx7Vos7kYpx4ybOohQ0x/Gdo4m39hVUrqfWDpKP/ioz4wX3SLUMI2bNggdghmSZ2wHbzKEbZB3WvUjpTzH3NHwOsJWtzWANP8ecxsZ5njrKTcB/UB5V981AfmiwosCbO1tRU7BLMj5KqRm7gXqrAh4Kysa9SWFPP/MJ9haqIWay8zdHfnsPt5GXydLK+wKiXFPqhPKP/ioz4wX1RgEYuiSdwDpi2Gqkt/sUMxKcYYNl5nePuQFkVCybQL4/xoBnZCCCnPkSNH8NZbb4HjOBQVFSEkJARff/01rKys6mT7NAaLWAwmaKFO2A7bwFDIHJzFDsdk7uUyRO7VYuQ/WnR355D8ohyvtpL2DOyEECK2du3a4fjx40hKSsLZs2dx//59fPfdd3W2fSqwJGzatGlih2BW8s8dgTbzPlTdBpukPSnkf/N1AW03F+NYOkN0Lxk29ZSjsW39Kayk0Af1GeVffNQHlVuyZAneeOMN3b+zs7PRsGFD5Ofn62Z1z8/PR15eXp3+YUq3CCXM09NT7BDMSk5cNKx9noZ1s6dM0p6Y+c8qYJh0SItfrzIM8eHwfYgMror6U1iVonNAXJR/8ZljH9zNSYO6SFOt96qs7NDEvmqTQ48fPx5+fn5YvHgxHBwcsGbNGgwaNAhOTk5ITU3FwIEDcf36dfTv3x8TJkyoVlzVQQWWhE2ePFnsEMxG4e1rKLx2Fs5jPzRZm2LlP+aOgLFxWuQUAb90l+GllvV3rBWdA+Ki/IvP3PogK/8xXtrxFgQmVOv9Mo7Hlhd+gpPCwej3ODo6YujQoVi9ejXeeecdrFixAps2bQIAeHl54dSpU8jNzcXLL7+MLVu2YNiwYdWKraqowCIWQR0fDVkDNyjbPid2KNVWLDDMPiFgwSkB4U04rO0mQzNV/SysCCHmyUnhgF8jVtToClZViqtSkydPRmRkJFq1agU3NzcEBASUed3W1hbDhw/Hr7/+SgUWIcbS5mQh98R+OPYbA+5/99vNzS01w8h/tDjygGHhszymBfDg6+lVK0KIeavqLT5T8PPzQ/PmzfH666/jiy++AABcu3YNXl5ekMvlKCwsxNatW+Hv719nMdEgdwm7ePGi2CGYBc2hXeBkPOw6P2/Sdusq/ztSBbTbUoxbGob4CBmmt5NRcfU/dA6Ii/IvPuoD47322mvQarUYMmQIAOCff/5BYGAgAgMD0b59ezRu3Bgff/xxncVDBZaEffDBB2KHIHmsuAjqgzth26EneDt7k7Zd2/kvEhjeO6xF5F4tujbmcHKwHM81olPySXQOiIvyLz7qA+PFxsZiwoQJuicHX3vtNZw9exYnT57E2bNn8dVXX8HaumYTUFeF5D7Np0yZAh8fH/A8jzNnzuiWd+/eHc2bN0dQUBCCgoKwbNkyEaOsG99++63YIUhe7ql4CI8fQRU60ORt12b+H+Qx9PpTi2/OC/gqmMfWXjI418OnBCtD54C4KP/ioz6o3L1799C6dWucPHkS77zzjtjh6EhuDNaLL76I6dOnIyQkpMxyjuOwbNkyREREiBRZ3TPHx3PrEmMM6rho2LRqD6vGps9VbeX/eLqAwftKZmSPHSBDSGPJ/Z0jGXQOiIvyLz7qg8q5u7sjOTlZ7DD0SO6TPSQkBE2aNAFjTO81QajeY5/EMhXeuICiW1egCh0kdihG++mygJAdWnjYcTgxWE7FFSGEWCiz+nSfPn06AgICMHLkSNy4cUPscIjI1PHRkLs1haJVe7FDqVSxwDDlkBZj47R4uSWHuAEyeNjRLUFCCLFUkrtFWJ5169bBw8MDALB8+XIMGDAA58+fFzmq2rVo0SJMnz5d7DAkqfjRA+SdOQinF94Cx9fO3wmmyn9OIcPwf7TYe5vhuy483mxNvyNoLDoHxEX5F59U+0CKt+Rqolb2h0mUt7c3O336dLmvKxQKlpmZWe7rJ06cYABYo0aNWERERJn/OnfuzLZu3Vpm/T179rCIiAi9diZMmMBWrlyp13ZERARLT08vs3z27Nls4cKFZZalpqayiIgIlpycXGb5119/zaZOnVpmmUajYRERESwhIUHXHmOMrV+/no0dO1YvtmHDhpnFfpQy5X482raS3Z7+AtPm59bafsycObPG+7Fu137msPgyc1hTyPbe0urtx5PMuT9qaz9KzwFz348nmdN+lObf3PejlDnuh6+vr6T2IzU1ldna2jIAFveflZUV69GjB4uIiGC+vr7M29ubAWAnTpzQy4kxOMYMDHaSAB8fH2zbtg3+/v7QarV4+PAh3NzcAAB//PEHpk6dWuFtwqSkJLRv3x4nTpxAUFBQXYVN6oBQkI97n7wMu0594DTwNbHDKVdSBkPEnmJY8cCuPnK0caarVoQQ83fz5k1kZGSIHYbJubq6lnmooKZ1hORuEb755pvYtWsX7t+/jz59+sDe3h6nT59G//79UVhYCI7j0LBhQ2zfvl3sUIlIco/HgOXlQtU1UuxQyrUzVcCIf7R4ugGH7b1laGxLxRUhxDJ4enrS041GkFyB9f333xtcfuzYsTqOhEgREwSo46KhbBsMuXMjscMx6KfLAl6N1yLSi8O6MBls5VRcEUJIfWNWTxHWN5Z4CbamCi4lofjBLai6Da71bVUn/0vPlDwp+Kofj997UHFVU3QOiIvyLz7qA/NFBZaEjRs3TuwQJEcdvw1WTVvAunmbWt9WVfLPGMOsY1q8nyhgVjse34fwkPFUXNUUnQPiovyLj/rAfFGBJWFz584VOwRJKbp/C/nJx6AKHVwn0xwYm3+twPDGAS0WnBKwpBOPz56V0TQMJkLngLgo/+KjPjBfkhuDRf4fPf1YljphG3j7BrANCq2T7RmT/2KBYcx+LTZdZ1jbTYZXfOlvFlOic0BclH/xUR+YLyqwiFkQctXIPfo3VGFDwMnr7tfQK1IsMLwcq8UfNxg29pBhiA8VV4QQQkpQgUXMgiZxD5hWC1WX/mKHAgAoEhhG/aNFdArDph4yDKbiihBCyBPoW0HCVq1aJXYIksC0Wqjjt8E2qBtkDs51tt3y8l+oZRgRo8W2VIY/elFxVZvoHBAX5V981Afmi74ZJCwpKUnsECQh/9xhaB89gCp0YJ1u11D+iwSG4TFa7LzJsKWnDJFedArVJjoHxEX5Fx/1gfmS7E/l1BT9VI7lePD1VACA29tfiBqHVmB4eX/JmKvoXjL086TiihBCLFVN6wj6hiCSVnj7Kgqvn4Oq2yBR42CM4c0DJU8Lbgin4ooQQkjFaJA7kTR1XDRkDdygfCZYtBgYY5iaKGDlJYafusnwAo25IoQQUgn6piCSpc15hNykOKi6RoKTyUSL4z8nBSw9K+Db53iMoXmuCCGEGIG+LSQsMjJS7BBEpTm4C5yMh13nPqJsPzIyEl+f02LOCQHzn+UxsY14RV59Vd/PAbFR/sVHfWC+qMCSsEmTJokdgmhYcSHUB3fBtmMv8Lb2osQQEPUJ3jksYKo/j5ntqLgSQ30+B6SA8i8+6gPzRQWWhPXu3VvsEESTmxQPIecRVF3rdmqGUgfSBCx+9AxGtOCwqCOdJmKpz+eAFFD+xUd9YL7om4NIDmMM6vitsGnVAVaNmtX59i9mMUTu1SLYjcOabjLw9MPNhBBCqogKLCI5hdfPo+j2NdiLMDVDWi5D393FaGILbO0lg42MiitCCCFVRwWWhEVHR4sdgijU8dGQuzWDTav2dbpdTRFD/z3FKBSAP5+XY//ubXW6faKvvp4DUkH5Fx/1gfmiAkvCfvvtN7FDqHPFmfeRd+YQVN0GgavDW3MCYxizX4tLWcCu5+XwVHH1Mv9SQ30gLsq/+KgPzBdNNCphGzduFDuEOqdO2A5OYQvbDj3qdLufJAnYmsKwtZcM7VxKCrv6mH+poT4QF+VffNQH5osKLCIZQkE+NEf2wC74efA2ijrb7u/XBcxLEvBZBx4DvemiLiGEkJqjbxMiGbnH/gYryIWqa91NrJeUwfDKfi1GtuAwsx2dDoQQQkyDvlGIJDBBgDo+Gsq2z0HewK1OtpmWyzBwbzHaNOCwKlRWp2O+CCGEWDYqsCQsKipK7BDqTMGlJBQ/uA1VHU3NUCQwvPi3FloGRPeWQSnXL67qU/6livpAXJR/8VEfmC8agyVh9WkG35y4rbBq9hSsfdrUyfZmHBVw5AHD/gEyeNgZvnJVn/IvVdQH4qL8i4/6wHzRFSwJGzlypNgh1Imi+7dQcPEEVKED6+Q23ebrApaeFfBFZx5dGpd/CtSX/EsZ9YG4KP/ioz4wX1RgEdGp47eBt28A28DQWt/WxSyGqHgthjfn8HYbOvwJIYTUDvqGIaIScnOQe2wfVF0GgJNb1+q21EUMQ/YVo5kdsJIGtRNCCKlFVGBJ2IEDB8QOodZpjvwFphVg16VfrW6HMYY3ErRIVQN/9JRDZVV5cVUf8i911AfiovyLj/rAfFGBJWGff/652CHUKqbVQp2wA7btu0Nm36BWt7X2MsP6awwrQ2Vo3cC4K1eWnn9zQH0gLsq/+KgPzBcVWBK2YcMGsUOoVXlnD0H76AFUobU7NcOlLIZJh7R41Y/DiBbGH/KWnn9zQH0gLsq/+KgPzBcVWBJma2srdgi1Sh0fDesWbWHdtEWtbaNAyzDin5JxV8uCZVV6r6Xn3xxQH4iL8i8+6gPzRQUWEUXhrSsovH4e9rU8seiMowIuPAI29JDDzohxV4QQQogp0ESjRBTquGjInBtB8UznWtvGrpsCvjonYFkwj3YuVFwRQgipO3QFS8KmTZsmdgi1Qvs4E7kn46DqGgmOr9ptO2Ol5TKMjdOifzMOk6s535Wl5t+cUB+Ii/IvPuoD80UFloR5enqKHUKtUB/cBU4mh12nPrXSPmMM4+O1kHHAmm7Vn+/KUvNvTqgPxEX5Fx/1gfniGGNM7CBqQ1JSEtq3b48TJ04gKChI7HDI/7DiQtybOwbKdl3RYOjEWtnGqosCxidosb23DBFe9DcEIYSQqqtpHUHfPqRO5SbFQVBnQRU6sFbaT8lheOeIFlG+HBVXhBBCREPfQKTOMMagjouG4ulnYeXW1OTtC6xk3JWzDfBVFadkIIQQQkyJCiwJu3jxotghmFTh9XMounOt1iYW/ea8gLh7DGu7yeBgXfOnBi0t/+aI+kBclH/xUR+YLyqwJOyDDz4QOwSTyonbCnkjT9j4mX5M3MUshhlHBbzdhkdYE9Mc1paWf3NEfSAuyr/4qA/MFxVYEvbtt9+KHYLJFD9MQ/7ZI1CFDqz2U33l0QoltwY9VcCCjqY7pC0p/+aK+kBclH/xUR+YL5poVMIs6fFc9YEd4JS2sH22h8nb/vaCgKMPGBIiZLCVm654s6T8myvqA3FR/sVHfWC+6AoWqXVCQR40h/+CKrgfeGuFSdtOyWH48JiACU/z6NKYDmdCCCHSQN9IpNblHt0HVpgHu5AIk7bLGMObB7RoYAMseJYOZUIIIdJB30oStmjRIrFDqDEmCFDHb4PSPwTyBg1N2vavVxn23GZY0UUGexM8NfhvlpB/c0d9IC7Kv/ioD8wXFVgSlpubK3YINZZ/8TiK0+9A1c20UzOk5zG8c1iLES04DKilCUUtIf/mjvpAXJR/8VEfmC/JFVhTpkyBj48PeJ7HmTNndMvT09PRt29f+Pr6wt/fHwkJCSJGWTc++eQTsUOoMXVcNKyaPQVr79Ymbfedw1owAMtqcUJRS8i/uaM+EBflX3zUB+ZLcgXWiy++iIMHD8Lb27vM8hkzZiA4OBiXL1/G6tWrMWrUKGi1WnGCJEYpSktFwaUk2HcbbNKpGf66JWD9NYYvO8vgpjT9rUFCCCGkpiQ3TUNISAiAkgHMT9q0aROuXbsGAOjQoQM8PDwQFxeH8PDwOo+RGEcdvw28gzOU7bqarM38YoZJh7QIc+cw+ikqrgghhEiT5K5gGZKZmYni4mK4ubnplnl5eeHmzZsiRlX7MjIyxA6h2gRNDnKPxUDVpT84uZXJ2v38jICbamB5F5nJJyz9N3POv6WgPhAX5V981AfmyywKrPpq3LhxYodQberDu8GYALvn+puszeuPGRacEvB+Wx6tG9T+1Stzzr+loD4QF+VffNQH5sssCixnZ2fI5XI8ePBAtywlJcWoGW779euHyMjIMv8FBwcjOjq6zHp79+5FZGSk3vsnTpyIVatWlVmWlJSEyMhIvb8s5syZo/dI7c2bNxEZGan3g53ffPMNpk2bVmZZbm4uIiMjceDAAQDA3LlzAQC//fYboqKi9GIbPny4JPdDk5ODlOjVyGn6NGT2TrrlNdkPxhjePqSFPC8Tzc6sq5P9mD59epn+MMV+lBLzuDKn/Sg9B8x9P55kTvtRmn9z349S5rgf2dnZFrEfUu+PH374oUyd4OfnhyFDhui1URUc+/dgJ4nw8fHBtm3b4O/vD6Ckivfy8sKcOXNw7NgxvPDCC0hJSYFMZvgpsqSkJLRv3x4nTpxAUJDpf1yYlC/3VDwy186H27TvYO3R3CRtbksRMGifFlt6yjDYxyz+LiCEEGLGalpHSG6Q+5tvvoldu3bh/v376NOnD+zt7XH58mUsXLgQo0ePhq+vL2xsbPDrr7+WW1wRcanjomHT0t9kxVVuMcOUw1r0bcZhkDcNbCeEECJ9kiuwvv/+e4PL3dzcsGfPnjqOhlRV4c1LKLxxAS7jZpuszc9OCkjLA2L61/7AdkIIIcQU6F6LhP37XrE5UMdFQ+bSGIpnOpmkvavZDIvPCJgewKOFQ90WV+aYf0tDfSAuyr/4qA/MFxVYEpaUlCR2CFWizX6I3FMJUHWNBMeb5vbttEQtGiuB6QF1f6iaW/4tEfWBuCj/4qM+MF+Su0VI/t/y5cvFDqFK1Ad3gZNbwa5TH5O0988dAdGpDOvDZLCV1/2tQXPLvyWiPhAX5V981Afmi65gEZNgRYXQHNoFu469wCvtatyeVmB494gWwW4cRrSgcVeEEELMC13BIiaRm7QfguYx7EIHmqS9VZcYzmQCiQN5GthOCCHE7NAVLFJjjDGo46KhaP0srBp61Li97EKGj45rMbolh45udIgSQggxP/TtJWGGZqKVooKrZ1B09zpU3QaZpL1PTwrQFAMLOoo7z5m55N+SUR+Ii/IvPuoD80UFloRNmjRJ7BCMoo7fBnljL9j4Bta4ravZDMvOCZgRwMPDTtxbg+aSf0tGfSAuyr/4qA/MFxVYEta7d2+xQ6hUccY95J87DFW3QSYZK1U6LcNUf/EPTXPIv6WjPhAX5V981Afmiwa5kxpRJ2wHr1TBtn1Yjds6mFYyLcO6MBmUIkzLQAghhJiK+JcJiNkS8nOhSdwDu+C+4K0VNWqLMYZpiQICXYCRNC0DIYQQM0cFloRFR0eLHUKFco/uAyvMh13XiBq3FZ3CcPgBw6KOMvASmZZB6vmvD6gPxEX5Fx/1gfmiAkvCfvvtN7FDKBcTBKgTtkMZ0BVyp4Y1aqtYYJh5TIteHhx6NZXOISnl/NcX1AfiovyLj/rAfEnn24zo2bhxo9ghlCs/+RiK0+9AZYKJRYVOdnAAACAASURBVFddEnApG1gk8rQM/ybl/NcX1AfiovyLj/rAfFGBRapFHRcNK08/WHu3rlE7miKGuScEvNSSQ6CrNG4NEkIIITVFBRapsqJ7KSi4fBL2JpiaYelZAZkFwKcdpHX1ihBCCKkJKrBIlanjt4F3dIEyIKRG7TzIY/j8jICJT/PwtqerV4QQQiwHFVgSFhUVJXYIerSax9Acj4GqywBwcqsatfXpSQEyDvgwUJqHoRTzX99QH4iL8i8+6gPzJc1vNgJAmjP4ag7vBhiD3XN9a9ROSg7D98klP4njopDm1Ssp5r++oT4QF+VffNQH5osKLAkbOXKk2CGUwbTF0CTsgG2HcMhUTjVqa16SFs42wOQ20j0EpZb/+oj6QFyUf/FRH5gv+qkcYrS80wehzc6AfeigGrVzOYvhpysMX3bmYWclzatXhBBCSE1I9/IBkRx1fDRsngqAVROfGrUzJ0mLJrbA663o8COEEGKZ6BtOwg4cOCB2CDqFqZdQmJIMVbeaXb0685BhwzWG2UEyKCT+g85Syn99RX0gLsq/+KgPzBcVWBL2+eefix2CTk58NGQu7lA83bFG7cw5oUVze2Csr7SLK0Ba+a+vqA/ERfkXH/WB+aICS8I2bNggdggAAG1WBvJOxkMVOhAcX/0JQY+lC4hOZZjbXgYrXvoFllTyX59RH4iL8i8+6gPzZfEFlsCY2CFUm62trdghAADUB3eCs7KBXadeNWrn4+MCWjsBo1pIv7gCpJP/+oz6QFyUf/FRH5gviy+wjj4w3wJLClhhATSHdsOuUy/wCrtqt5NwT8Ce2wzz2ssgM4OrV4QQQkhNWHyBtem6IHYIZi03KRZC7mOoug6sdhuMMXx0XEA7F+AFHyquCCGEWD6LL7Di04DUHPO8ijVt2jRRt88YgzouGoqnO0LesEm12/n7DkN8GsN/2svA1/DHoeuS2Pkn1Adio/yLj/rAfFl8gWUnB75PNs+rWJ6enqJuv+DqGRTdS6nR1AyMMXx8QkBnNw79Pc2nuALEzz+hPhAb5V981Afmi2PMjEeBVyApKQnt27fHyDVHsZdvh9uj5JKfd0lqMlbORfHDNDT6YAW4al552nNLwPN/abGnrwy9m1p8PU8IIcRClNYRJ06cQFBQUJXfb/HfeC/68HhYAGy6bpF1ZK0pzriL/POJsA8dWO3iijGGT5JKrl718qDilhBCSP1h8QWWlz2H3h4cll8wz9uEYtBoNLgS/TPy5UrYtg+vdhsbk+7g8C01Zgfx1S7SCCGEEHNk8QUWAExqw+NoOsOxdPMqsi5evCjKNr/74Wus3LYRG/KUuHT9RrXaWLH6e3y8ciW8z/8Ib/WlWoi09omRf1IW9YG4KP/ioz4wX3JjVlKr1Th27BguXbqErKws2Nraws3NDQEBAWjdunVtx1hj/Zpx8FIBy88LWNvdfGrKDz74ANu3b6+z7Wk0Guzctwu5hSlw6+CG9Ebu+GnHLxhuNwK2dsZNdperycWG7RtwVwnkPeOD52WP8GfMbnh6esLOrvrzaImhrvNP9FEfiIvyLz7qA/NVYYF17NgxzJ8/H2fPnkVAQADc3Nzg7OyMjIwMnDp1Cj/88APu3buH4cOHY+rUqVCpVHUVd5XIeA4TnuYx+4SALzozuCrM43bVt99+W6fby87ORk5BDuyQjl0tFSjWXED6xTuI3XYcNg0URrVR8CgfmZfS0LCTB1rYnUOQ10A8OHob2dnZZldg1XX+iT7qA3FR/sVHfWC+DBZYxcXFmDVrFvLy8rBo0SL4+vqW20BRURH27NmD0aNH46233kLv3r1rLdiaGOdXUmCtuihgervq/55eXarrx3MdHR2hyMpC6sN7KG7QAM8Ut4Rzq0AMH1i1K1hL0tdj/w0NPH2uIuXSdTSydoajo2MtR2969Hi0+KgPxEX5Fx/1gfkyWGDNmTMHUVFRRt3+s7KywoABAzBgwACsWbMG+/btQ69eNfvNutrgquAwojmHFckCpvrz9HMtBtjZ2aEbr8HGx3KkJ96Bc6tAvBIxGq2atTK+EWfgivtLkJ1aj/QHdyBrFYj+Ef3M7uoVIYQQUhMGByTNnj27WmOroqKi0K1btxoHVVsmteGRqgZ23aIpGwwpunsDno9vYWTUeDgHNsbwESPQqlUViisAB9IEJMr88F7U8Gq3QQghhJg7gwWWjY2NwZWNmZPU2tq6ZhHVog4NeXRsyOHb8+bxNOGiRYvqdHvq+G2QObqiQUAwbBoojL4t+KRPkgS0dQZ6t7SrdhtSUdf5J/qoD8RF+Rcf9YH5MvqRutGjR8Pb21v378OHDyM2NrY2YqpVk9rw2HeH4VKW9K9i5ebm1tm2tOpsaE78A7uQAeBk1Rujdui+gL/vMMwONK/fHCxPXeafGEZ9IC7Kv/ioD8yX0QVWYGAgVqxYoft3cHAwlEolfvvtt1oJrLa8+H/t3Xt80/W9P/DXN+k9gUILyK2lLdCWcm3LHVoUFRRnQBkHZccxOCqcARu6wdSzHXA4XTnOM36IFxwTYUcqwig4QMVbL3IrTSkyKZdCKXcohUKSXkjy+f3RUSltIUmTfPJtXs/Ho4+NJN9v3t/3C+3bb775fGMVdAgB3lLBwqMvv/yy197LvGs7AEA3coLL+/i90Y6+7YHHY9U/XAHe7T81jRnIxf7LxwzUy+EBKyYmBmfOnMGVK1fqHxs+fDiuXbvmkcI8JSRAwTOJGqw+Yofphu+fxfIGYbPClPcJdKljodW1dWkfey7a8dlpgd+1krNXRERELeHwgJWbm4ulS5eia9euGDRoEObNm4dly5Zh586dnqzPI2b30cBkBf7vmO+fxfKGqv25sFdehn7MJJf38XujHX3aAT9uJWeviIiIWsLhASsqKgpHjx5FRUUF/vSnP6Fdu3ZYuXIlnn32WU/W5xHRegWG6LqL3R25cF+W8vJyr7yPKWczguMHIbBLjEvb51+yY9spgd8ma1vV8hfe6j81jxnIxf7LxwzUy+EBy2q1wmazITQ0FPfffz+WLFmCgwcPIi8vz5P1ecycvhocvALknvfdAWvmzJkef4+a0kOoPVkMfbrrZ6+WGO1ICAemxrWe4QrwTv/pzpiBXOy/fMxAvRwesGbNmoXXX38dBQUFAOqWbOjTpw8OHjzoseKaEhMTgz59+iA5ORkpKSn4+OOPXdrP/V0VJITDp5dsWLx4scffw5SdBW2HLghJGurS9sZygU/KWt/ZK8A7/ac7YwZysf/yMQP1cuhmz0DdbVR+85vfwG6vG0gURcGSJUsQFRXlseKaotFosH79evTv379F+1EUBXOSNHh+tx1nzALddL43HKSkpHh0/9arl1BVlIfwic9A0bh2E+wlRht6tQWe6Ol7/WspT/ef7o4ZyMX+y8cM1KvJ36q1tbXNb3DLL+IpU6Zg+PDhDm/rDkIIt103NT1eg5AAYGWx757F8iRz3j+gBAZDN8y1WxsVXRbIOinwX8laBLSys1dEREQt0eSAtWvXLmzatMnpnR06dAivv/56i4u6m6eeegoDBw7EM88806ILANsGKXiqlwYrD9lRa/Pda7E8QdTWwLxrO3TDx0MT4tp9Al8ptCGuDfCTXhyuiIiIbtXkgDVmzBhERkZi+vTp2L59+113cvToUfziF7/Ahx9+iJdeesntRd4qNzcXRUVFMBqN9TW2xJwkDc5XAX8v9b0Ba9WqVR7bt6XgK9gt16FPM7i0/cEKgQ0nBF4apEVgKz175cn+k2OYgVzsv3zMQL2avfAmPT0db7/9NgoKCjBw4EA8+OCD+PnPf44XX3wRv/vd7zB37lxMmTIF8fHx+M1vfoOnn34aS5Ys8XjB3bt3BwBotVrMnz//rt9inDBhAgwGQ4OfESNGICsrCwDQN0LBvV0UvPLtZRgMjYeNOXPmNPoLbjQaYTAYGp09W7RoUaP7RpWVlcFgMKC4uLjB48uXL8eCBQsaPGaxWGAwGOqPyWg0AgDWrVuHGTNmNKpt6tSp9cdx0+eff37X4xBC4Hp2Fmq6J+LxmbMaHcc777zTaPvbj+MP+23ooQeu7Xi7yeN47rnnGu3D3cdxk6fy2LNnT4M81Hoct/+9UtNx3PxnQO3HcSs1HcfN/qv9OG5S43G88sorreI4fD2PlStXNpgTEhISMHny5Eb7cIYiHLygqbi4GPv378eFCxdQXV2NDh06ICYmBqNGjUJISEiLinCUxWLBjRs3EB4eDgB44403sGXLFnzzzTeNXms0GpGamoqCgoK7XiS44bgdU760Yf/jARgY2TrPxtyq+kghyt96ER3mZCCk98BGzx+pKMEz25/Hew+/gfiIno2eL74qkPSxFW+P1mBWn6bvW3i3fRAREfkyZ+aIpjj8LcLExEQkJiY6/QbudOHCBUyePBl2e90CoXFxcVizZk2L9zsxRkE3HbDiextWpjncEtUyZWchsGssgnsNcGn7PxTa0E0H/CzetW8eEhERtXaqmiZiY2MbfGTgLoEaBbMSNfhjkR0ZQwXaB7fes1jWS2dR/f1etJ86H4oL9ww8WinwYYnAshEaBGtbb5+IiIhawuVTEKWlpTh9+nT9n8+ePeuWgmR5JlGDG3Zg9ZHWvWSDKXczNGFtEZZ6n0vbv7bfhntCgacTePaKiIioOS7/loyJicG5c+fw1ltvoaysDOvWrXNnXV7XOUzBj2MVvPW9HXYfuT9hUxfptYS9ygzzns+hG/kwlMAgp7c/cU1gzVGBhQM0CAlo/Wev3N1/ch4zkIv9l48ZqJfLA9aHH36I559/Hh9//DGmTp1av8K7ms3tq8Gxa8Dnp31jwJo7d65b92fe8znEjVroRz/q0vavFdkQGQI828c/zl65u//kPGYgF/svHzNQL5evwaqtrUVubm79nzdu3OiWgmQa0UnBoEhgxfd2PBQlf4gYN26c2/Yl7DaYcrcgNDkd2vBIp7c/eV1g9RGBV4doEOYHZ68A9/afXMMM5GL/5WMG6tXsFLFp0ybs3LkTZWVlsFqtjZ6vqalp8OfQ0FD3V+dliqJgbpIWW8sETlzzjbNY7lL9z72wXT6HNumTXNo+o8iOtoHAbD85e0VERNQSzf62fOKJJ5CTk4P8/Hzs2rWr0fNJSUkYN24cVq9ejezsbBQWFnq0UG95speCdsHA24fU/5HnrUw5WQiK6YOgHglOb3vGLLDqsB2/GqCBPtA/zl4RERG1RLMD1qRJk/DCCy9g8uTJSEtLa/R8Wloa3n33XZSUlGDbtm148sknPVqot4QFKJgZr8Gqw3ZUWeWexbp9dVpX1Z49jpqjRdC7ePZqaZEdusC62wr5E3f1n1zHDORi/+VjBurV7G/MLl261P//r776Cl988QXMZnOD18TGxmLJkiXIyMhAXFyc56r0sv9M0uBKDZBZInfActc3M03ZWdC264DQgaOc3vacRWBlsR3P9dOgbZB/nb1S+zdjWwNmIBf7Lx8zUK9mB6xbF6EcM2YMKioqEBkZifnz5+PLL7/0SnGy9Gyr4KEoBW9+b4ODdxLyiI8++qjF+7CZrsJS8DV0ox+FonX+Ow2vH7AjWAvM6+tfZ68A9/SfWoYZyMX+y8cM1KvZ37i3DhZarRb/9m//hk2bNuHPf/6zVwqTbW6SBo98ZsOeiwLD71HvmRvzzm1QFA10Ix52etvyaoG3v7djwUAN2rXi1e2JiIjcrdnTEh988AFmzJiB999/HyUlJQDqPhK8XVFRkeeqk+ihKAVxbeqWbFArYb0BU94/EDZ4LLS6tk5vv/qIHUFa4Ll+/nf2ioiIqCWa/c3ZsWNHXLhwAc899xzi4+PRtWtXbNq0CcuWLUNBQUH9wqLvvfee14r1Jo2i4OdJGqw/LnCxSp1LNlQV5cF+rQL69Ikubb/hhMCv+vPsFRERkbOaHbAee+wxbNu2DVeuXMG+ffvw0ksvYcCAAVi6dCmGDBmCdu3aYfz48di+fbs36/WqGfEaaBTgL8VyzmLNmDHD5W1NJhOOblkLa0w/BHaJcWpbi9mCmivVCLZa8Es/PnvVkv6TezADudh/+ZiBejX72zMjIwNA3cXuycnJmDt3Lj766COcOXMGx44dw/Lly9G9e3dcvnzZa8V6W0SIgp/0UvD2ITusdu+fxXJ1Bd/i4mKseGMJ1uTvxbrLVhQXFzu17V/WrENF4Xn0PbIeZ48fdqmG1oArKMvHDORi/+VjBurl0q1y4uLiEBcXh+nTp0Or1bq7Jp8yJ0mLVYet2HxSYHKsdz8qc2VtMbPZjH/s2Apz9XF0vjcBFyN0+OCTtZiqewJhurA7bmsxW5C5JROFMKHjsG7or9Fg6xfbEBUVBZ1O5+phqFZrWdtNzZiBXOy/fMxAvVy+F+FNP/3pT91Rh89K7qBgTBcFS4vseDxGabB8hS+qrKzEtWuXoAuuxD+6hcJqLsSl4jP4evM+BLcPueO2NVeqUXH4PDoO64YAXSDiY3riwp7TqKys9MsBi4iIyFUtHrBGjx7tjjp82gsDNXj4Uxuyzwnc29W3B6zw8HAEnT2JMlhg7RKAftZeiEhMxtSJjp3BevrohzhbpuC58b1w9WQF2gTpER4e7qXqiYiIWgf/vYLZCeO7KxgYAfyxyLsXu+fl5Tm9TWigFmnWywi2R+LSnjOIMLfB9EefwqCo/oiP6HnHH13bfjB2mIYUJQIV+acRVKHBIw9M8NuzV670n9yLGcjF/svHDNSLA5YDFEXBbwZq8dlpgcJy713svnTpUqe3sez7Cj3DAjBtzvOISO6MqU88gcTERIe2/e8CG7r2TMTKX8/Gs088jdkzZjm8bWvkSv/JvZiBXOy/fMxAvThgOWhKnILYNsDSAzavvWdmZqZTrxdCwJSThZB+w9G2a3cEtw+568eCNxnLBTJLBF5O0SIyXI+uXbv67Zmrm5ztP7kfM5CL/ZePGagXBywHBWgU/HpA3cKjJde8cxYrLMyx4eimmiOFsJ4vQ5sxk5x+rxf22tCnHTA93revMfMmZ/tP7scM5GL/5WMG6sUBywkz4jWIDAb+dMA3b59jys5CYNc4BPXs79R2O07bseOMwGtDtAjQcMAiIiJqKQ5YTggNUPDLfhr89YgdZ82+dfucG5fOoPr7vdCPmeTUUhJ2IfBCvg0j71Fg6MHhioiIyB04YDlpbl8NQrXe+UbhggULHH6tKWczNPpwhKXc69R7rD8uYCwHMoZqfH6NL29zpv/kGcxALvZfPmagXhywnBQeVHct1spiO06bPHsWKzo62qHX2S0mWPZ8Dt3IR6AEBjm8/1qbwH/l22DooWB0Z/5VuJ2j/SfPYQZysf/yMQP14m9VF8zrq4EuAHjNw2ex5s2b59DrzHs+g7BZoR/1iFP7f+t7O0pNwKuDW/ftjlzlaP/Jc5iBXOy/fMxAvThguaDtv85i/aXYjjIPn8W6G2G3wZS7BWHJ6dCGRzq83aUqgcVGO2YlatA3gh8NEhERuRMHLBfNTdKgbRDwaqHcbxRWH9wDW8UF6NOdW5rhd/vsUAD8fjD/ChAREbkbf7u6qE2QggUD6r5ReMJD62IVFxff9TXXszchKDYJQdHxDu+36LLAe4ftWJyqQYcQnr1qjiP9J89iBnKx//IxA/XigNUCc5I06BgCvLTPM6u7L1y48I7P154uQW3Jd9A7sbCoEALzd9kQHw78PInx38nd+k+exwzkYv/lYwbqxd+wLaALVLBksBaZJQL5l9z/UeGbb755x+dNOZuhbdcRof1HObzPjScEvjkn8L/DtQjkoqJ3dLf+k+cxA7nYf/mYgXpxwGqh6b0V9I8Afr3bDiHc+1Hhnb6ea7t+FZaCr6FPM0DROvYtwMpagV/uqluW4aEoRn83/Hq0fMxALvZfPmagXvwt20JajYKlQ7XIOS+w5aT3vlFo3rkVikYD3fCHHN7mt/l2VNYCy0dyWQYiIiJP4oDlBuO7K3iwm4IFe2yosXl+yBLWGzB9+w+EDbkfGl0bh7bZe9GOFd/b8cpgDaL1/GiQiIjIkzhguYGiKPjf4VqcuA687sYbQWdkZDT5uGV/DuzXrkCfPtGh/VjtAs/m2pDcoe5WP+SY5vpP3sMM5GL/5WMG6sXftm7SN0LB8/01eKXQjuNuWrbBYrE0ekwIAVN2FoITUhDYuYdD+1laZMd3V4CVowMQwAvbHdZU/8m7mIFc7L98zEC9OGC50e9S6pZtmLfT5pYL3l9++eVGj9We+B43Th11eGmG4qsCiwrseGGgBqkdOVw5o6n+k3cxA7nYf/mYgXpxwHIjfaCC/zdSi22nBDaccP+1WGazGUc3r0FteCeEJA6+42stZgtqrlTjv/Kuo297YFEKoyYiIvIW/tZ1s4k9FEzqoeDn39pwweK+Iau4uBgr3voT3v9iGzJNQTh85MgdX5u5LhMVhedR+uV6/L7bMQRpefaKiIjIWzhguZmiKHg3TQsFwDO5LfuosLy8HEDdmat/7NgKS9UxdBoRjYrEjvjgk7XYf+o7HKkoafCz/9R3WL1lLY4EXEfHYd2QPkDB0X3bYTab3XSE/uNm/0keZiAX+y8fM1CvANkFtEadQhW8l6bFpB02vH9EYGaCa2ePZs6ciS1btqCyshLXqyoRpr2MbTEBsJqLcKn4DL7evA/B7UMabFNzpRoVh8+j47BuCNAF4pGkXri49zQqKyuh0+nccXh+42b/SR5mIBf7Lx8zUC8OWB4yMUaDmfF2zP3WhsEdFAyIdH7IWrx4MQAgPDwcwZfOocxUAWvH9uhn7YWIxGRMnfgEwnRhDba5UmnGEwfX4fwpBXMf7IXKsgq0CdIjPDzcHYflV272n+RhBnKx//IxA/XigOVBy0dpUVBuxeQvrMifFIB2wc4NWSkpKQCAsLAwpFkrsbG6DS7tOYOIxGRMf/QpJEYlNni9XQhMK7ThbNQ0zAnYgcp9p9EmSI9HHpjAs1cuuNl/kocZyMX+y8cM1IsDlgeFBSjY+GAABm+y4t+/tiFrnNaldahqDhsRK65h2qw52L3vLUyd+ESj4QoAfrvPjvXHBT6e1hcPdYpDZWUlwsPDOVwRERF5GS9y97CebRVkjtXis9MCs/Ncu+jdlJ2FwG49Ed67L4LbhzT6WBAAlh204bX9diwdpsHkWA10Oh26du3K4YqIiEgCDlheMD5Kg1XpWqw6LPBSvt3hIWvVqlW4ceEUqg/lQz9mEhSl6bNfyw/aMH+XHQsHaPCr/ozUXVatWiW7BL/HDORi/+VjBurF38Ze8tN4DV4fpsEfi+x4frdjQ5bRaIQpdws0+nYISxnT6HkhBJYYbfjFLjsWDNDgj0M1zQ5h5Dyj0Si7BL/HDORi/+VjBuqlugHr2LFjGDVqFBISEjBs2DAcOnRIdkkO+9UALVaM0uDPB+2Y9rUN5ht3HrKW/08GLHt3QDfqESgBQQ2es1gFfpZtw38X2LEkVYMMDldut2LFCtkl+D1mIBf7Lx8zUC/VDVizZs3C7NmzcfjwYSxcuBDTp0+XXZJTfp6kxfr7tfjkpMCwzVYcuNz0kGU2m3Fs6zqYq6uhH/UIgB9uf1N41ozUTVZ8fFzg/+7T4rcpWg5XREREPkRVA9alS5dQUFCAn/zkJwCAyZMn49SpUzh+/LjkypwzJU6DvZPqvsCZssmK53bZcP6W2+oUFxdjyLAh6Df1WTy6sQBHz15EcXEx/rJmHSoKz2Pm/6wDzhWj4LEATOvlmxHeHAYtZt4JnoiI/I+qlmk4deoUunTpAo3mh6EiOjoaZWVliIuLk1iZ85LaKzA+FoA/fWfHq/vteOt7Ox6PVfBghyr8x8A+CO2sR1hCBE5drUafPn3Q59nncT3yBqKHdUPCdQVpyg5EB8UB8L1vCRYXFyNzSyYqDp9HpiUTIYZAJCY2XlaCiIiotfLN0x9+Ikir4MVBWpx6MgBLBmtw+KrAfzzxYwR31qPL2Gj0mjkQXcZGI7SzHkez3kJ0zDEE6AIxYXgvWG6YUFlZKfsQGrl530R7pIKOw7rBHqlg6xfbVHkvRIPBILsEv8cM5GL/5WMG6qWqASsqKgrnzp2D3W6vf6ysrAzR0dHNbjNhwgQYDIYGPyNGjEBWVlaD133++edN/kWeM2dOo6/JGo1GGAyGRjfhXLRoETIyMho8VlZWBoPBgOLi4gaPL1++HAsWLAAAtAtWsHCgFnkP3QCKv0BIuyC0H9gRoZ11aD/oHgS1C4L1YjVGaVPwRMxEXD1Zd/ubefPm+dRxAEBlZSWuWK4i/0ABAnSBiEvsieu1dcPgunXrMGPGjEa1TZ061eeOAwCefvppGAwG5OXlNXhcbcdhsVhUexxz585tFcdxKzUdx83+q/04blLjcVy6dKlVHIev57Fy5coGc0JCQgImT57caB/OUIQrK19KNHbsWEyfPh3Tp0/Hhg0bsHTpUuzdu7fR64xGI1JTU1FQUKCqWw1MnjwZ23d+ji73RaP9oHtwpegCzn1VhhFJQzHhsUdwvdZUf/sbX/zYzWw24+2/voMbkQL3xHXBhePnEFShwewZs7joKRERqUZL5whVXYMFAO+88w5+9rOf4dVXX0V4eDjef/992SW51frVf0FA2wic+7oMlwvPo/ZqLaovmPHluS9hNpt9/vY3Op0OP3rwEWz9YhvKzpfwXohEROSXVDdgxcfHY+fOnbLL8Bjzt1txeoEB8w4LfJWdg4fvH4eNGzcCqBte1DCoJCYmIioqyueHQSIiIk9R1TVYrZ2w1sL07VaEDXkQf9+8BatXr64frtSmNdwL8fbP9cn7mIFc7L98zEC9OGD5EIsxB/brV6BPnwig7qI+kof9l48ZyMX+y8cM1IsDlo8QQsCUk4XgxMEIvCcKAPDRRx9Jrsq/sf/yMQO52H/5mIF6ccDyEbUn/okbp4+hzZhJskshIiKiFuKA5SNM2VkI6NQdwQnqWVKCiIiImsYBywdYKy6gD2iM1gAAFLxJREFU6sBO6NMnQdEwEiIiIrXjb3MfYMr7BEpIGMKGPNDg8aZWrSXvYf/lYwZysf/yMQP14oAlmb2mGuZdn0I34iFogkMaPDdu3DhJVRHA/vsCZiAX+y8fM1AvDliSWfK/gKi2QD/60UbPPfnkkxIqopvYf/mYgVzsv3zMQL04YEkk7HaYcrIQOmAkAiLukV0OERERuQkHLIlqDhthvXgaei7NQERE1KpwwJLoenYWArv3QlBs3yafz8vL83JFdCv2Xz5mIBf7Lx8zUC8OWJLcuHAKNcX76pZmUJQmX7N06VIvV0W3Yv/lYwZysf/yMQP14oAliSlnMzRt2iMsJb3Z12RmZnqxIrod+y8fM5CL/ZePGagXBywJ7JbrsOTvgH7UI1ACgpp9XVhYmBerotux//IxA7nYf/mYgXpxwJLAvPtTCJsdulGPyC6FiIiIPIADlpcJmw2m3E8QljIG2jbtZZdDREREHsABy8uqvtsJ25WLDi3NsGDBAi9URM1h/+VjBnKx//IxA/XigOVlppwsBPXsj6Duve762ujoaC9URM1h/+VjBnKx//IxA/VShBBCdhGeYDQakZqaioKCAqSkpMguBwBQe+ooLv5pHiJn/BahA0fLLoeIiIia0dI5gmewvMiUnQVt+04I6T9CdilERETkQRywvMR2rQKWwmzo0ydC0Whll0NEREQexAHLS0zfboWiDYBu2HiHtykuLvZgRXQ37L98zEAu9l8+ZqBeHLC8QFhrYf52K8KGPgBNmN7h7RYuXOjBquhu2H/5mIFc7L98zEC9OGB5gcWYDbvpKvRpE53a7s033/RQReQI9l8+ZiAX+y8fM1AvDlgeJoSAKTsLIX2GIPCeKKe25ddz5WL/5WMGcrH/8jED9eKA5WG1xw/ixpkShxYWJSIiotaBA5aHmbKzEHBPNIITfGMtLiIiIvI8DlgeZL18HlXf7apbmkFRnN4+IyPDA1WRo9h/+ZiBXOy/fMxAvThgeZAp7xMooWEIG3y/S9tbLBY3V0TOYP/lYwZysf/yMQP14q1yPMReU4Vzi/4dupET0M7wH15/fyIiInIdb5Xjoyx7d0DUVkGf9qjsUoiIiMjLOGB5gLDbYcrZjNABoxDQvpPscoiIiMjLOGB5QHXxPlgvnYE+vWVLM5SXl7upInIF+y8fM5CL/ZePGagXBywPMGVnITCqN4Jik1q0n5kzZ7qpInIF+y8fM5CL/ZePGagXByw3u3H+JGoOG6EfM8mlpRlutXjxYvcURS5h/+VjBnKx//IxA/XigOVmppzN0LRtj7BB6S3el4xvP9IP2H/5mIFc7L98zEC9OGC5kd18HZb8L6Ef9SMoAYGyyyEiIiJJOGC5kXn3pxB2O3QjH5FdChEREUnEActNhM0GU+4WhKXeC22bdm7Z56pVq9yyH3IN+y8fM5CL/ZePGagXByw3qfruW9iuXmrx0gy3MhqNbtsXOY/9l48ZyMX+y8cM1Iu3ynGTi8ueBzRadJr3Px5/LyIiIvIs3irHB9SWHUHtie/RZsxjskshIiIiH8AByw1MOVnQRnZGSL9hskshIiIiH8ABq4VslZdhKcyBfvSjUDRa2eUQERGRD+CA1UKmb7dCCQiEbvhDbt+3wWBw+z7Jcey/fMxALvZfPmagXgGyC3BGTEwMQkNDERISAkVR8OKLL2LKlCnS6hE3amHeuRVhQx+EJlTn9v3PnTvX7fskx7H/8jEDudh/+ZiBeqlqwNJoNFi/fj369+8vuxQAgMX4DeymSujTPPNfGOPGjfPIfskx7L98zEAu9l8+ZqBeqvqIUAgBX1lVQggBU3YWQpKGIrBTd9nlEBERkQ9R1YAFAE899RQGDhyIZ555BuXl5dLqqDl2ADfOHod+jPsWFiUiIqLWQVUDVm5uLoqKimA0GhEZGYnp06dLq8WUsxkBnaMRHJ/ssffIysry2L7p7th/+ZiBXOy/fMxAvXx6wFq7di2Sk5ORkpKCDz74AN27130Up9VqMX/+fOTl5d11HxMmTIDBYGjwM2LEiEZ/aT///PMmv60xZ86cRveC2p/9BSwHdgIpD0BRlPrHFy1ahIyMjAavLSsrg8FgQHFxcYPHly9fjgULFjR4zGKxwGAw1B/XunXr6v93xowZjWqbOnVqi47DaDTCYDA0OhPo7uO4SW3HsXbt2lZxHGrO4+Y/A2o/jlup6Thu9l/tx3GTGo9jzpw5reI4fD2PlStXNpgTEhISMHny5Eb7cIZqbpVTVVWF2tpahIeHAwDeeOMNbNmyBd98802Tr/fkrXKubnoXlvwv0HnxWmiCQty6byIiIpKvpXOEar5FeP78eUyePBl2ux1CCMTFxWHNmjVer8NebYF5z2fQj/oRhysiIiJqkmoGrNjYWJ+4q7gl/wuI2mroRj8quxQiIiLyUT59DZavEXY7TDmbETpgNALad5RdDhEREfkoDlhOqD6UD+ulM15bmqGpC/rIe9h/+ZiBXOy/fMxAvThgOcGUnYXA6HgExfTxyvtxBV+52H/5mIFc7L98zEC9OGA56Ma5UtQcKUSb9EkNlmbwpCeffNIr70NNY//lYwZysf/yMQP14oDlIFPOZmjaRiB0UJrsUoiIiMjHccBygM18DeZ9X0I/+kdQAgJll0NEREQ+jgOWA8y7tgNCQDdyglff15GV6slz2H/5mIFc7L98zEC9OGDdhbBZYc77BGGp90Grb+fV9166dKlX348aYv/lYwZysf/yMQP14oB1F1VF38J2tdxrSzPcKjMz0+vvST9g/+VjBnKx//IxA/XigHUXppwsBPceiKCucV5/77CwMK+/J/2A/ZePGcjF/svHDNSLA9Yd1J48jNrSQ9Cne//sFREREakXB6w7uJ6TBW1kZ4T0HSq7FCIiIlIRDljNsFVeRlVhDvRpE6FotFJqWLBggZT3pTrsv3zMQC72Xz5moF4csJphyvsESmAQdMPk3aYgOjpa2nsT++8LmIFc7L98zEC9FCGEkF2EJxiNRqSmpqKgoAApKSlObStu1OLc4qcQlnov2j3+nx6qkIiIiHxVS+YIgGewmmQp+Bp2yzXo0ybKLoWIiIhUiAPWbYQQMGVvQkjSUAR07Cq7HCIiIlIhDli3qTl2ADfOlUpZWPR2xcXFskvwa+y/fMxALvZfPmagXhywbmPK3oSALjEI7j1IdilYuHCh7BL8GvsvHzOQi/2XjxmoFwesW1jLz6L6n3ugT58IRVFkl4M333xTdgl+jf2XjxnIxf7LxwzUiwPWLUy5n0AT1ga61LGySwHAr+fKxv7LxwzkYv/lYwbqxQHrX+zVZph3fwbdiIehBAXLLoeIiIhUjAPWv5j37IC4UQPd6B/JLoWIiIhUjgMWAGG3w5S7GaEDRyOgXUfZ5dTLyMiQXYJfY//lYwZysf/yMQP14oAFoPr7vbCVn/OJpRluZbFYZJfg19h/+ZiBXOy/fMxAvXirHACX3noBoqYanZ77s5eqIyIiIl/GW+W00I2zJ1BzZD/06bwtDhEREbmH3w9YppzN0IRHInRQmuxSiIiIqJXw6wHLZqqEueAr6Ec/CkUbILucRsrLy2WX4NfYf/mYgVzsv3zMQL38esAy79oOANCNeFhyJU2bOXOm7BL8GvsvHzOQi/2Xjxmol98OWMJmhTnvH9CljoVWHy67nCYtXrxYdgl+jf2XjxnIxf7LxwzUy28HrKqiPNgqy3364nZXvrVA7sP+y8cM5GL/5WMG6uW3A5YpOwvBvQchsGus7FKIiIiolfHLAaum9BBqTxb73MKiRERE1Dr45YBlys6CtkMXhCQNlV3KHa1atUp2CX6N/ZePGcjF/svHDNTL7wYs29VyVBXlQZ82EYrGtw/faDTKLsGvsf/yMQO52H/5mIF6+d2tciq3roYpZwu6vLwWmhCdxAqJiIjIV/FWOU4QtTUw79wG3bBxHK6IiIjIY/xqwLIUfAW75Tr06QbZpRAREVEr5jcDlhAC13M2I6TvMAR06Cq7HCIiImrF/GbAqjm6H9ZzpdCnq2dpBoOBZ9pkYv/lYwZysf/yMQP18psBy5SdhcAuMQjuPVB2KQ6bO3eu7BL8GvsvHzOQi/2Xjxmol18MWNZLZ1H9/V7ox0yCoiiyy3HYuHHjZJfg19h/+ZiBXOy/fMxAvfxiwDLlboYmrA3CUu6TXQoRERH5gVY/YNlrqmDeswO6kROgBAXLLoeIiIj8QKsfsKq+2wVxowb60Y/KLsVpWVlZskvwa+y/fMxALvZfPmagXq1+wLIU5iB0UBq04ZGyS3FaRkaG7BL8GvsvHzOQi/2Xjxmol08NWL/85S8RGxsLjUaDAwcONHju0qVLePjhhxEfH48BAwYgNzfXoX3aK8vRZsxjnijX4zp27Ci7BL/G/svHDORi/+VjBurlUwPWlClT8O233yImJqbRcy+88AJGjBiBI0eO4K9//SumTZsGm812130GdolBUI8ED1RLRERE1LQA2QXcavTo0QDqVl2/3fr161FSUgIAGDx4MLp164bs7GyMHTv2jvsM5TcHiYiIyMt86gxWcyoqKmC1WtGpU6f6x3r06IGysrK7bhsSr56FRYmIiKh18KkzWO5UVVUFACg+chSKVp2HuXfvXhiNRtll+C32Xz5mIBf7Lx8zkOfQoUMAfpgnnCYkWrNmjRg0aJBITk4Wq1evrn88JiZGFBUVNXitXq8XFy5cqP/z0KFDxZdfftnsvv/2t78JAPzhD3/4wx/+8Ic/Lv/87W9/c2nGUYRo4oInyWJjY7F582YMGDCg/rGZM2eiR48eWLRoEfLz8/H444+jtLQUWq22yX2Ul5fjs88+Q0xMDEJDQ71VOhEREbUCVVVVKC0txfjx49GhQwent/epAWv27NnYunUrLly4gMjISLRp0wZHjhwBAFy8eBFPPfUUTpw4geDgYKxYsQLp6emSKyYiIiJqzKcGLCIiIqLWQBXfIiQiIiJSEw5YPujYsWMYNWoUEhISMGzYsPpvMpBn1NTU4LHHHkNiYiKSk5Mxfvz4+jXXXL2DALnm/fffh0ajwZYtWwCw/95UW1uLefPmIT4+HgMHDsRPf/pTAMzAm7Zt24bU1FQkJydjwIABWLNmDQBm4CnN3T3mTv2uqqrCtGnT0Lt3byQmJmLjxo3Nv4FLl8aTR40dO1asWbNGCCHEhg0bxJAhQyRX1LpVV1eL7du31//5zTffFPfee68QQogZM2aIl19+WQghRH5+vujevbuwWq1S6mztSktLxciRI8XIkSPF5s2bhRBCzJw5k/33kvnz54tf/OIX9X+++a1tZuA9ERER4uDBg0KIun8eQkJChMlk4r+HPCQ3N1ecOXNGxMbGNli54E5/53//+9+LGTNmCCGEOHHihOjUqZOoqKhocv8csHzMxYsXRXh4uLDZbPWPde7cWZSUlEisyr/s27dPxMbGCiEaLw8ybNiwOy4PQq6x2+3igQceEEajUdx77731Axb77x1ms1m0bdtWXL9+vdFzzMB7OnToIHJzc4UQQhQVFYnu3buL2tpaZuBhty8Ndad+9+3bV+zZs6f+ualTp4pVq1Y1uV9+ROhjTp06hS5dukCj+SGa6Ohoh1atJ/dYtmwZJk2a1KI7CJBz3njjDaSlpSE5Obn+Mfbfe0pKShAREYE//OEPGDJkCMaMGYOvvvqKGXhZZmYmHnvsMcTExCA9PR0ffPABrl+/zgy86G5/58vKytCjR48mn7udOpc4J/KQV199FSUlJVi5ciUsFovscvzCP//5T2zcuJHXlUhktVpx8uRJ9OvXD6+99hr279+PcePG4eDBg03eG5bcz2az4ZVXXkFWVhZGjRqFffv2wWAwYP/+/cxApXgGy8dERUXh3LlzsNvt9Y+VlZUhOjpaYlX+4fXXX0dWVhY+/fRThISEICIiAgEBAbh48WL9a0pLS5mFm+Xm5uLkyZPo3bs3YmNjsXv3bjz77LNYv349++8l0dHR0Gq1mDZtGgBg0KBBiImJwXfffYfAwEBm4AX79+/HuXPnMGrUKADA4MGD0b17dxw4cIAZeNHd/r3fo0cPnDx5ssnnbscBy8d07NgRKSkpWLt2LQBgw4YNiIqKQlxcnOTKWrc33ngDmZmZ2LFjB9q0aVP/+JQpU/D2228DAPLz83H27FmMGTNGVpmt0uzZs3HmzBkcP34cJ06cwPDhw/Hee+9h9uzZ7L+XREZG4v7778enn34KADhx4gRKS0uRlJTEDLzk5n9cFxcXA6j7Nvnx48eRmJjIDLzsTv3+8Y9/jHfeeQdA3T8n2dnZmDRpUtM78sgVY9Qihw8fFiNGjBDx8fFiyJAh9d8qIc84ffq0UBRF9OrVSyQnJ4tBgwaJ4cOHCyHqvkk1btw40bt3b9GvXz+RnZ0tudrW77777qu/yJ39957jx4+L++67T/Tv318MGjRIbNq0SQjBDLwpMzOzvv8DBgwQmZmZQghm4CmzZs0S3bt3F4GBgaJz586id+/eQog799tsNoupU6eKnj17ioSEBLFhw4Zm98+V3ImIiIjcjB8REhEREbkZBywiIiIiN+OARURERORmHLCIiIiI3IwDFhEREZGbccAiIiIicjMOWERERERuxgGLiIiIyM04YBERERG5GQcsIiIiIjfjgEVERETkZhywiIiIiNyMAxYRERGRmwXILoCIyJsqKyvx7rvvIiAgAKdOnUJaWhpKS0tRWFiItWvXyi6PiFoJDlhE5Ffeeecd/PrXv4ZWq0Xv3r2RlJSExMRELFu2DEIIKIoiu0QiagUUIYSQXQQRkTfY7XYUFhYiNTUVVVVViIiIwNmzZ9G+fXvZpRFRK8NrsIjIb2g0GqSmpgIAdu7ciYSEBA5XROQRHLCIyK/cPGn/zTffIC0trf7xXbt2ySqJiFohDlhE5Dc+/vhj9OnTB0II/P3vf0evXr0AALt370Z1dbXk6oioNeE1WETkN3bv3o0VK1agX79+GD16NFauXImRI0eibdu2ePLJJ2WXR0StCAcsIiIiIjfjR4REREREbsYBi4iIiMjNOGARERERuRkHLCIiIiI344BFRERE5GYcsIiIiIjc7P8DiMPQvxIkfToAAAAASUVORK5CYII=\" />"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {
+      "comm_id": "b7486aaa-42c2-4cd0-9ac6-afd6bc76c0d3",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 20.0\n",
+    "#``` Este código genera una gráfica interactiva del mapeo variando el parámetro \\gamma.\n",
+    "#```\n",
+    "@manipulate for γ in 0:1.0:200\n",
+    "    pobla(x)=f(x,α,β,γ)\n",
+    "    xfin,ffin = iteramapeo(pobla,10.0,16); #Añade la condición inicial con la que se analiza el mapeo y \n",
+    "    #su trayectoria, la función  definida un renglón arriba y el número de iteraciones.\n",
+    "    plot(-10:1/32:100, pobla, xaxis=(L\"x\", (-10.0, 100.0)), yaxis=(L\"F_\\alpha(x)\",(-10.0,20.0))) # Hace la gráfica\n",
+    "    #con especificaciones para ejees.\n",
+    "    title!(\"Analisis grafico para distintos valores de S\")\n",
+    "    plot!(-10:1/32:50, identity) #Grafica la identidad del análisis gráfico\n",
+    "    plot!(xfin, ffin, marker=(:dot, 3, 0.4)) #Señala dónde terminó la condición inicial dada\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T00:06:39.575149",
+     "start_time": "2016-12-05T06:06:39.567Z"
+    },
+    "collapsed": true,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "source": [
+    "![Variando S](Figures/g1.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Aquí mostramos una gráfica del comportamiento temporal del mapeo cuando $S=0$ y se varía la condición inicial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:17.284291",
+     "start_time": "2016-12-05T07:08:17.279Z"
+    },
+    "collapsed": false,
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α = 10.0\n",
+    "β= 25.0\n",
+    "g(x,α,β)=(α*(x)^2)/((((α-1.0)*(x^2))/β + x)) #Define el mapeo con \\gamma = 0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:18.195736",
+     "start_time": "2016-12-05T07:08:17.710Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(50.0, nactions=0),\"i\",50.0,0.0:1.0:100.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {
+      "comm_id": "4a0bb2d9-308d-485b-8e83-890a59227dde",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@manipulate for i in 0:1.0:100 #Este código realiza una gráfica interactiva que cambia la condición inicial\n",
+    "    # en cada paso entre 0 y 100 con los valores de \\alpha y \\beta dados anteriormente.\n",
+    "    poblaciones(i) = g(i,α,β)\n",
+    "    xfin,ffin = iteramapeo(poblaciones,i,20);\n",
+    "    plot(0:1/32:100, poblaciones, xaxis=(L\"x\", (-10.0,100.0)), yaxis=(L\"F_\\alpha(x)\",(-100.0,100.0)))\n",
+    "    title!(\"Evolucion de la poblacion sin insectos infertiles\")\n",
+    "    plot!(0:1/32:100, identity)\n",
+    "    plot!(xfin, ffin, marker=(:dot, 3, 0.4))\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Vemos que en este caso, la población total nunca muere, tal como se esperaba, pues no hay insectos infértiles."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Se resolvió la ecuación $N(x)-x=0$ para encontrar los puntos fijos del mapeo en términos de los parámetros R,S y M, obteniendo:\n",
+    "\n",
+    "$X_{0}= 0$\n",
+    "\n",
+    "\n",
+    "y    \n",
+    "\n",
+    "\n",
+    "\n",
+    "$X_{12}= \\frac{\\pm M(1-R)+\\sqrt{R-1}\\sqrt{M^{2}(1-R)-4MS}}{2(1-R)}$\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Por lo que, para encontrar poblaciones estacionarias distintas de cero, tenemos que se deben cumplir las siguientes condiciones:\n",
+    "\n",
+    "$R> 1 $ ^ $M > \\frac{4S}{R-1}$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:21.762009",
+     "start_time": "2016-12-05T07:08:21.650Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Recompiling stale cache file /home/pablorv/.julia/lib/v0.5/NaNMath.ji for module NaNMath.\n",
+      "INFO: Recompiling stale cache file /home/pablorv/.julia/lib/v0.5/Roots.ji for module Roots.\n"
+     ]
+    }
+   ],
+   "source": [
+    "using Roots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:24.597799",
+     "start_time": "2016-12-05T07:08:24.587Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "puntofijo (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function puntofijo(F::Function, range) #Este código calcula los puntos fijos de una función F en un rango range.\n",
+    "    pf= fzeros(x -> (F(x) - x) , range)\n",
+    "    return pf\n",
+    "end "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:27.548054",
+     "start_time": "2016-12-05T07:08:27.536Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "F (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "\n",
+    "F(x) = (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x)) #Se define la función con nuevos parámetros arbitrarios, pero que\n",
+    "#cumplen las condiciones mencionadas."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:37.583836",
+     "start_time": "2016-12-05T07:08:28.182Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "-"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3-element Array{Float64,1}:\n",
+       "  0.0    \n",
+       "  8.33333\n",
+       " 16.6667 "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pf=puntofijo(F,[0,20.0]) #Se calculan los puntos fijos de éste mapeo."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:37.589452",
+     "start_time": "2016-12-05T07:08:31.416Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "g (generic function with 2 methods)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g(x)= (α*(x)^2)/((((α-1.0)*(x^2))/β + γ + x)) -x  #Se define el mapeo que nos permite estudiar la localización \n",
+    "#de los puntos fijos al variar los parámetros."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:37.594141",
+     "start_time": "2016-12-05T07:08:32.254Z"
+    },
+    "collapsed": false,
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(::#27) (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "α= 10.0\n",
+    "β= 25.0\n",
+    "γ= 50.0\n",
+    "func=x -> g(x) #Se dan valores a los parámetros para realizar un ejemplo de sus puntos fijos."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "A continuación se muestra una gráfica de los puntos fijos del mapeo en términos de los parámetros\n",
+    "$R=10$,$M=25$ y $S=50$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:39.441692",
+     "start_time": "2016-12-05T07:08:34.711Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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\" />"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(-10:1/32:30, func,xticks=-10:0.5:100,yticks=-10:0.5:50) #Se grafica el mapeo N(X)-x\n",
+    "xlabel!(L\"x\")\n",
+    "ylabel!(L\"N(x)-x\")\n",
+    "title!(\"Puntos fijos de N(x)\")\n",
+    "plot!([8.3,8.3], [1, -1, 0]) #Se marcan los puntos fijos sobre la gráfica.\n",
+    "plot!([0,0], [1, -1,0])\n",
+    "plot!([16.66,  16.66], [1, -1, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "A continuación se muestran graficas que relacionan los parámetros y el comportamiento de los puntos fijos dependiendo de éstos."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "La función a estudiar es:\n",
+    "\n",
+    "$N(X)-X= \\frac{MRX^{2}}{(R-1)X^{2}+M(X+S)} -X $\n",
+    "\n",
+    " Nos interesa analizar este mapeo pues nos permite observar el comportamiento de los puntos fijos en función de los parámetros.\n",
+    " \n",
+    " En primer lugar, estudiemos a los puntos fijos para distintas $M$ en cada gráfica en función de $R$ y $S$ para una condición inicial fija $X_{0}=10.0$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb416613e50>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.5184747648677959>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código realiza una gráfica para cada valor de M entre 1 y 80\n",
+    "x = y = linspace(2.0, 40, 40) #Establece el paso entre cada x,y y sus valores máximo y mínimo.\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0 #Condición inicial arbitraria\n",
+    "@gif for i in linspace(1, 80, 100) #Creando el .gif, con 100 imágenes.\n",
+    "    G(x,y) = (x*(x0)^2)/((((x-1.0)*(x0^2))/i + y + x0))-x0\n",
+    "\n",
+    "\n",
+    "plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"R\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas M\")\n",
+    "        \n",
+    "   end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Distintas M](Figures/M.gif)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Ahora estudiamos el comportamiento de los puntos fijos con un valor distinto de $R$ en cada gráfica que varía en función de $M$ y $S$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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BFBZEif/JWqagX3rppdixYwd+9atf4eKLL4amabjssstaOq5SBD1GaZGqhRkzZni/9+STT3p/Xn75Zbz++utYunRpzd/VKjKZDI4//ni8733vw7Zt23DLLbdg48aNNX9eZrgBBcvfQQcdBKBgddmwYYN3jJs2bcIbb7yBL3/5yxPKElS7JvVSPJ5Gjk9V1X1ee+CBB3DIIYfgsssuwzHHHIPf/va3uPjii2seVz3zpBSpVAq33norXnvtNfz0pz/F2rVr8dJLL+GGG24o+f77778fX//615v6zUpceumlePrppwEAX/va13DEEUfg1ltvxQUXXICnnnoKK1eunPB+IQSuvfZabN++Hffeey8++MEPYteuXfjKV77S1DhkED8R1dURg2EAFmRMA9STOVRqM3nxxReb+s5EIgEAXouiBx54ALZt49BDD/XcUlu3bvXeL/8+ODiI1atX46tf/SouvPBCpFIprFmzBtdffz1OPfVU5HK5qr9dbpy1jj/oMa5evRr9/f0gIrz++usV3yuLfL755psThAgAfOc732mo9lQ5aj0///7v/45HHnkEg4OD+MUvfoGlS5dWFfB+S5bMkovFYjjttNOwevVqTJs2DUQ04XwDwFNPPYWf/OQnOO6447xzVuqaHHLIIZ6LsxZKjWfy5MlYvXp1Q8dXissuuwzZbBbnnXceLr/8ckyePLkui+Zpp50GAFXnSKXP33nnnZg2bRre+9734p577sHAwIA3P+U9ChRiubZs2VLV+tTMGvDII48gm80il8t5Dy3f+MY38MEPfhCpVAqO40z4/IUXXoivfvWrGBoawrp163DnnXfisMMOq2kNqITfui/Xue3btzdteWP2D1iQMXVDRHXFmvifFu+//34vYN0fF1bt+/z/vmrVKgDAn//8Z7z55psQQnjWnuuvvx6qquKOO+7A2NgYTNPEd7/7XQgh8LWvfQ2pVAqGYeD222/33H+5XA6vvvpqTa6xcuOsJwA+yDGmUin80z/9EwDg3/7t37yg79tvv90bpzzvZ5xxBt73vvfBNE388z//s/cdP/zhD/Gtb31rnwSCeoP8/e/3u2RLfY98TbqqTNPEzp07QUT41re+BUVRQEQT+oTKz918882wbRuGYeDmm2+GEAKXX345ZsyYgWQyiZtuugmqquKGG27A6OgogILYOvvsszF58mT09vZ61pubb74ZlmV5HRlisRi+9a1v1XXMGzZsAADs3bsX3//+9yGEwHXXXYdEItHQ8ZU6X/J7pGjetm0bfvKTnwDAPt9Rik984hOYP38+Nm3a5N2PL774ojffysVsyrEYhoErr7zSc8G//PLL0DTNi/1asmSJ55p+/vnn8fTTT+Ooo44q+33+v1ebI8Bba8Dzzz8P0zSxdetWDA8PQ1EUDAwMgIjw6quvAgB+97vf4cknn5xwbgzDwHXXXYfNmzcDAHbu3Ik9e/bU5R4vHhMAvOc97/GE5f/8z/+AiPDlL38ZP/vZz+r6XmY/pVXpmkz38rOf/YyWLl1KkydPJkVRSFEUWrBgAS1dutRLGy/Hs88+S2vXrqVp06bR4sWLac2aNXT++ed7KfHz5s2jyy+/nObPn+9999KlS2nDhg20dOlSSiaTpCgKzZo1i8477zwiKpSS+MhHPkLTpk2jQw45ZJ80/4ceeojWrl1Lc+bMofnz59Pxxx8/oefdNddcQ+9973vp9NNPp5GREVq8eDF94hOfIF3XKx7Lhg0b6PDDD58wzvXr1+/z+sjICD322GPe50r1kAxqjJI77riDli9fTgsXLqTVq1d7pQAURaHBwUG64YYbiKhQPuIb3/gGLV26lObOnUsjIyN00UUX0a5du4ioUF5g1qxZpCgK9fX10cjICL3xxhtlf/fUU0+ladOmkaIo1N/f711L//lZtGiRd337+vpIURSaNm0arVu3zjvPRx55JB100EG0ZMkS+tKXvkRXX3019fX10dSpU73rLcsOnHvuubRq1SqaM2cOrVy50isn4ed3v/sdnX766TRjxgxasmQJnXTSSRNKbRAR/fSnP6XjjjuO5s2bR3PmzKFTTz215t6sr7zyijeeiy66iFauXEkzZ86k448/fp+ehtWOT95v8nwdfvjh3rmR7Nixgz72sY/R7NmzacGCBXTsscfSL3/5Szr22GNJVVVavnw5OY5Tcczbtm2js88+m2bNmkVHHXUUvf/976fTTjvNmyfz58+nxx57jJYsWeLdhwsWLKANGzbQu9/9bvrYxz5GRx99NI2MjNDIyAjdeOONE77/vvvuoxUrVtD06dPpzDPPJNd1iWjinGp0jriuS5/+9Kfp4IMPpjlz5kwoB/P444/TGWecQQceeCAdfvjh9J73vIfuuecemjdvHvX09NAFF1xAf//3f09nn302nXjiiTQyMkLDw8P0pS99yRtjOYrHJNcB//XZuHEjve9976PZs2fTvHnz6NRTT6VcLlfxexmGiEgQRazUMcN0OPl8Hs8//zyWL18OoFASQQiBLVu2NJXFxUxEntcHHngAJ5xwQqhj2bJlCxYsWAAhBF555RXMmTMn1PEwDNN5sMuSYVrM3/zN3+DII4/Ehg0bvKBuRVG4jUoXwxXZGYZpFhZkDNNiMpkMgEJpAVnr69xzz61a7oGpH6ojnjHoccj/RmE8DMN0HizIGKbF3HjjjTj++ONx55134sorr8Tll19eV40opjI///nPMTIyAiEEhBBYv349rrjiitDGc+ONN2LdunXeeE477TR85zvfCW08DMN0JhxDxjAMwzAMEzJsIWMYhmEYhgkZFmQMwzAMwzAhw4KMYRiGYRgmZFiQMQzDMAzDhAwLMoZhGIZhmJBhQcYwDMMwDBMyLMgYhmEYhmFChgUZwzAMwzBMyLAgYxiGYRiGCRkWZAzDMAzDMCHDgoxhGIZhGCZkWJAxDMMwDMOEDAsyhmEYhmGYkGFBxjAMwzAMEzIsyBiGYRiGYUKGBRnDMAzDMEzIsCBjGIZhGIYJGRZkDMMwDMMwIcOCjGEYhmEYJmRYkDEMwzAMw4QMCzKGYRiGYZiQYUHGMAzDMAwTMizIGIZhGIZhQoYFGcMwDMMwTMiwIGMYhmEYhgmZWNgDYBimvRARXNeFZVlQFMX7I4SAECLs4TEMw+yXsCBjmP0EIoLjON4fTdOgKAUjuRACiqJAVVWoqspCjWEYps0IIqKwB8EwTHBIIZbP5yGEQCxWeA4zTdMTWkQ04Q8AT4gREVRVRSwWKynWGIZhmOZhCxnDdCmu63rWMNd1oWka4vE4EokEXNcFAE9QFQsrKcqICLquQ1EUT8jJ9wshSlrU2KrGMAxTPyzIGKaLkBYu27bhOA6IyHNH1iOQ/EJN/onH4xN+Q/6OZVkTvpvdnwzDMPXDgoxhugAZqC8tYo0KsVooJ6r8VjU5lmL3p7SqScHG7k+GYZgCLMgYpoOR4se2bbiuCyIKzRJVi/uTiGBZFvyhq+z+ZBiGYUHGMB2JDNS3bXuCFUpmTUaJckINYPcnwzCMhAUZw3QQxYH6fldgNWTGZL0EKXrY/ckwDFOABRnDRJxWBeo3O4Z2Uo/70/86uz8ZhulUWJAxTEQpDtSXtEqIdaIwYfcnwzDdCgsyhokY5QL1geZEVLHL0m9V6gZqdX9algXTNBGPx6GqKrs/GYaJBCzIGCYidFKgfidRzqomLWXs/mQYJgqwIGOYkCknxHizD5ZKCRHs/mQYpt2wIGOYkPC7JevNmGwEIYTXMqnez+1vLW9bkf1ZzqrGMAxTChZkDNNGgg7Ur5V6f2t/E2TlqCf7018Al92fDMNUgwUZw7SBoAL1m4EFQOvg7E+GYZqFBRnDBIg/PkzTNFiWhcHBwVAC9fdH12MUYPcnwzC1wIKMYQKgVKC+fJ03UgZorftTlu9gqxrDdC4syBimhVRqbcQWKqYWGnV/Oo4DIYRXX43dnwzTWbAgY5gmiUJro0aotTBslI9hf6OS+9M0Tc9yxu5Phuk8WJAxTIMUZ0zKQP1ym2bYFjJZ9sKyLGiaBtu2AWCfzZmtKZ1HseiSlHN/ytfkg0NxUoH/dYZh2gMLMoapExkfJt2S1YRYFJBjJiJkMhmoqopEIgEAXh00KdAk8pj8wpOtKdGlVHwiZ38yTOfAgoxhaqTZ1kZyA2tnYD8RwTAM6LruFYUdGBiAqqrecfjHJcWXFJry7wCgaZp3HOWsakznUK1LAQDO/mSYNsKCjGGqUClQP6q4rusJMSJCPB5HPB73mmqXcp3KYyoWmIZhwLIspFIpT6BJi5r/e4qFGmf9dSa1lOmo1/0ps0AZhikPCzKGKUEQgfrtsJC5rgtd12EYBogIyWQSPT09UFXVs3A1gt8i4sdvRSsn1ACOU2sXQZ5Pdn8yTLCwIGMYH1FpbVQvjuN4QgwAenp60NPT05Kg7ErHXUmolRNrfliodQfs/mSY5mFBxjCIZmujWrBtG7queyUPUqkUkslkSSHWzizPcu7PeoRaqVi1KF+LsIlijbtG3Z/+61/OqsYw3QYLMma/ptlA/XrwuyybQbqFZOkKRVHQ29uLZDIZ2EbVqs2+VqHmF8iV4tR4g+5M6nF/6roO27a9+c3uT6ZbYUHG7JcU1w8Dyj/NRwVpSdA0DY7jQFVV9PX1IZFIRHrctVBOqAG1xalxQkH3UHzNpDDzu8XZ/cl0IyzImP0Kv1uy3RmTjVrIiktXxGIxDAwMIBaL1TXuUr/fCb01W51QEEXXHlOdRtyf/s+x+5OJOizImK7HX8hV9vsDoh+oX6p0RX9/P2Ixvm2B5hMKdF3vOpdXJ4+9HNVafNWb/Vn8GXZ/MlGBV3ama/HHIVmWhUwmg/7+fsTj8VAW2lotZJVKVzDVqRanZts2TNOEoihdlVDAlr99qZb96c+qZvcnEzYsyJiuozhQ358xCUTXiuAvXSGE8IRY2P0Eo3q+6sW/yQLwslH9G7PfssYJBdGh1eeY3Z9MFGFBxnQNlTImZfufMClnIZMZk7KYZqXSFa36/UY2jk6IN2sETiiINu20/LH7kwkTFmRMx1NLa6NWlZxoFWGUrmDqp56EAsdxJlhTAC58202w+5MJGhZkTEfSaGujMAWZHFdx6Yow4tpYFDRHswkFQQm1brymUbfMNuP+BOBZ1WKxGAu1/RwWZExHUdzayF/Vu9ICFvbiJktXAIVm3Y2WrmiGqFkJu5FaC9+WE2qNxqnxNY0etbg/XddFLpdDLBab0ICd3Z/7JyzImI7AX7rC39qonsVJiPa1DpIUl64ACn0me3t72zoOJlxqEWqcUFCebjvO4nUrFoshFoux+3M/hwUZE2na2dqolcjSFbquA4CXMZlOpyMz9nqELBMMrUookNeouOBxN7A/Wf+azf6UIo2zPzsTFmRMJKklUL9e2mEhKy5d0dPTM6F0RRhWOkmxy3J/2ug6kXoTCgBM2Kg5oSD6VCt6K6k1+9OyrH2+k92fnQMLMiYyNBqoXytBiqF2la4Ik6gHV+8vlBJqRIRcLodEIuGVeWl3QkGQRHlsraDZB81qQq1c3152f0YLFmRM6BQH6kuivig0WrqCLVNMUCiKsk9rraATCoKmmx8EglwL2P3ZebAgY0LD39rIH6gPBPNE3CoLGRHBNE3oul536YowFzPOsuxeKl1TTiiIPu0ueVPuN9n9GS4syJi2E2agfjNiRJau0HUdruuGUrqiVcgFVwpKXlD3P1qVUODvThDEPGILWftg92e4sCBj2kZx/TCgvQVKG/2d4tIViUQCPT09+7iGah1D2IuwYRjIZrPeOPzuilKWEGb/o96EguLWZJ0YpxYGtQb1h00z7k8i8grfsvuzMizImEApF6gfxuIshKirp2W50hXFm1Qn4LouNE0DAJimiWQyiXg8DsdxvPNSKb4IKAg5/4LKG2z0CPp6VBJqQXYo4HkWTWpxf+q6PiG2Ub53w4YNmDRpEi6++OL2DTjisCBjAsEfqJ/L5QDAK/8Q5uJai3WqWumKZmi3hcx/LJLe3l709PR4lo1SljD/BmtOY6tFAAAgAElEQVTbthfn50+6ANgSwhSoJU6t0YSCsC3KQdLN7lj/OqAoCuLxOIC35sTzzz+P4eHhMIcYOViQMS2lVKC+v8VRmFRb+EqVrujp6enIBdNxHGiaBtM0vWOJx+MYGxur6Tr4N1ghBGzb9kRpmL0amdJEVbRUE2rFc6lUnBpQuDeL49S6hW46llIUi045J9LpNCZPnhziyKIHCzKmJVQK1I/KU26pcci4B13X6ypd0coxtJJiUek/lmJ3rdwQ66FZS4h/Q5W9+9q9wUZhLu7v+MV5tTg1y7K8OE7/59uRUBA03T4XK8XIjY6OYtKkSe0eUqRhQcY0RTkhVvxEFLWFp5nSFVGjVD20vr4+JBKJfa6DfH+rqVWo+V3ZxcG/XFqBASbGqckHpmQyiVgsNkGoybWn0xMKojquoEmn0yzIimBBxjSE3y1ZrbVRVASZtBLJQP0wSlfUm1hQiWLrnqqqJYVYszTzXa0srcBCrTrdfF7CSigIkiisi0FSzkJGRBgbG2OXZREsyJiaCbq1UZD4F+h8Pt9U6Yqw6RbrXj2lFVio7Z/UUhYiyISCdtDNc7aay5IF2UQ6bzdi2k65ivq1Pl2GaSErLl0BAIODg6EJsWbOhRRimqY1ZN1r1mXZrmvIQq1+ut3S0gitSCgIei51c5aln1IWsnQ6jSlTpoQ0omjCgowpi78qsyx30IiZPwxBVpxlKDME8/l8x9URK+4QEI/H0d/f37So7LSNoFVCzV/MkukMWu2CrzWhoNJcKhZsjbg/u12QlbvHMpkMXNfFwMBAm0cUbViQMftQKlC/mSdDv2Um6MWnUukKmaUV5iJYjzhtZYeAbqZRoaZp2n5rUesU2i2aa51Lfq+BnyjGqYVJOZdlOp3G4OBgxz0cBw2v7IyHv7VRtUD9eghakJUqXVEpyzDqSDerYRggopZ2CPALwk45H41SbnO1LAuGYSCRSEzYWLvB9Rn18XUqrU4okPNrf7GQFR+jLHnRzcfeCCzI9nM6OVC/3uD2IMs+1EO535ftjaQlr5UdAsoR9WscBPKYY7HYhHNbr+uzk+tfdRpRPbfNJhQA8OZYJwn/eigX0D80NBTCaKINC7L9FH89qKCFWKuFUKmYqt7e3raVrmiGUuMLslVTK4j6OW0V1dxV/g02avWvwn7ICIpOPa5ayr04jgPTNL0H4m6w0BZT7vrJGmSddjxBw4JsP6PZjMlGaJUgazamKioWMolt29B1fUJ7o3a0aorK8XcKUqgV08n1r5jwkPNJURSYpukVva3VQltKrEV1PpVzyXKV/tKwINtPqNTaKGiaFULFpSsajamKgiCTMVyZTAaWZQXeqqnU7zcKC7mJNOuuYqFWnW6Odyy+n7oxoaCcIOMq/aVhQdblFLslgX1bGwVNo0KoVOmKKLny6kG6JaSodBwnkKr6TPiwUGPqodp1DSqhoF3ziQVZ7bAg60LKBep3yqJeqXRFM4RhIZMZoJqmwXEcb5MeHBzsSGHJNE47hFon3N9MgWbXoWbnUzvi1Cq5LKdPn96y3+kWWJB1Ef5gUV3Xkc/nMTAwAFVVQ12oaxFCtZauCHocraI4A1RW1XccB/l8viPqoDHtoRVCTSLvnU55+KrG/uCyDCKJqlpCQbs6FFRyWS5atKju7+t2WJB1AaUC9eXGG4WFuZIQqrd0RdQplwEaj8e9f5f/7ZTj65Rxdhv1CDXZScPfIoxdn0wxtcaptSqhgIP664MFWQdTKVA/au1hii0zYZSuCNJCRkRe4gFX1WeCpJRQM00Tpmmit7e3Ztdn8eYaVaEW1XE1S5Ssf7UINf/fa3Gn+7+7mLGxMW4sXgLeLTqQckKsVCxJ1ARZFNoBtfKclDqeVCpVNgM07OvSjMsyKnOJKU/xZigptan6E32AaNa+4jkXLs0mFACFzhhEhG3btiGTyWDhwoVsISsDC7IOwu+WrNbaKOyNvxh/jBjQeOmKZmnV5tKqUhxhIoU9u7G6g0rXsJxQa3dMEfMWUbKQ1Ust7nTHcTwxZpombr/9dlx77bVQVRUHHHAArrrqKhx77LFYvHgxFi9ejEWLFqG/vz+kI4oGLMgiTnHGpKTaghgVQSZLV8jNP+zSFc0GtTdbVT8K14WIkM/nPTEpj4U33c6l0fnUbExRWFl63UK3HZtfqAkhYFmW96B68cUX4x3veAeee+45fPvb34brurjjjjvw2muveZ9/4YUXsHDhwhCPIFxYkEWUchX1gfpu4rA2/uLSFYqiQFVV9Pb2hjKeZimuiZZKpZBMJjuqdIV/c7UsC8lkcp9/K7fpAvDq2bFQ636iLtS6gbAfltuFvO5TpkzB29/+dhxzzDH45Cc/iaeffhr9/f3IZDLYvHkznnvuOcydOzfk0YYLC7KIIS1JsleeFGL1bvzySSWMmlulSldks9m2jaMS9Z6TYmHZbFX9MCxkxU3LFUXB4OAggEIweCm3Q/GmC7wlSgHedPdXwhBq3TynuvnYyq1xY2NjSCaT3sP5wMAAVq1ahVWrVrVzeJGEBVlECKK1UbsEWS2lK4QQ+zRjDoNazol0EWuaFlhNtHZQyr1q27Y3r8pdj1Kbbi6XQywWQywWY+sIsw9BCbVutiJ187EB5WPkRkdHMTQ0FMaQIg8LspDxtzaqFqhfL0EvaPWWroj6AlRs4VNVtSOL0xYLMb97NZPJ7LMZ1hOnw26s6BLFc9msUJNzU/Z97aY50+3xcdUEWTcfe6OwIAuBcq2NWr3YBCXIGildEZWbr9Q56ZbitKXi3IpbTpWqB9fsMXK8EVMvtc4ZmaUn3e3ys6VqqXG2cPQodT1kH0u+VvvCgqyN+NOBgxRiklYLMr/lBaiv1EOU3A/+ormmaULTNLiu67U3CrI4bRDIpuVSiDUb59YqWiXUVFXlDbcKUbm3mqV4zsgkkmQyWbKOWrHbvZO6E/gTtbqRcnNy79697LIsAwuyNlAuYzLohaJVcVvFlpdGSldERZDJcyJriElXa39/f1uK07bSZelPOFAUJTJCrBr1CjXLsrz3dNKGy7QOOWeKqbVAaVTnTdi/HyTlrO/pdJqr9JeBBVmABBGoXw/NiiAZTyUzDEu5wNo1llbgt07m8/mObW9ULMTqiXPzX4d6rmM7No5KQk1aQzptw2Wap9I19Ne98tMJQi3s9TBoKgkytpCVprN2og6h2C0J7NvaqB00IoIqla5oxfjDCGSVFjHDMLzfHxwcDKWqfjMWMsuyWp752QmCRQixj2huZsPt1o2wE65lvTRT8LYThFo3XjM/pY5vdHSULWRlYEHWIsoF6of5lF6PIAs6sD2Mc1Ac89bT0+MJzk5pcVRcgiPMhIMoCZlmN1yg0KFAxqexRS26tDrRKSpCLUr3UxCUe/geGxvDIYccEsKIog8LsibxB+pns1nEYjHE4/FIZIrVIsjqLV3RzFjk7wV9Xiq1N5JtnMKk1utSXIKjFUIsCq7jIKllw7Vt2wsjME1zwvs61fXZrde0XcfVbqHWSNhAp1FurefG4uVhQdYgpQL1ZdC7vyVNmFQSQY2UrmjVWIKiONuwmZi3sJBCTNM0OI6DWCzWkSU4okbxhmvbtjc3ouTCYqJFUEJtf4CD+uuHBVmdVArUj9qNVkqQNVO6olVjaTX+5INq2YZRsBCVGkOxy7hTS3B0Gq3ecFVV5evVIqJsRWp23shjkq93m1irdO3YQlYeFmR1IDdNWUqi+Ak5Cpt9KWQckt961EjpilaNpVXf00h7o3a6TmuhXC20eDweyO9FdY5GjWY2XPm5dltGojCfOwLXBOxdgDoJUFJAG2LUgLce5v0P9TL5y//5braqERHS6TSmTJkS9lAiCQuyOvAH6ZezvkShX6NEjjGXy3miJaxaVa36vWKXXidW1ZfzxDAMT4i1sxZaI3TKuQ2aWoSaLNHBXQkiBLmA9gyEmwfUA0A9C1sqxGrBny2sKAps20YqlYKiKF3X0aKShUxW6mf2JZqrf4SpFDcib6yw8YsWoBAvFnZz7GZdlq1y6YVtIfNv2qZpRl6IMbXhF2r+a9mu9lFRsfgGQcPHRQQYL0PknoQQMbh9K0G9R7R2cE0i5023tR4rJ8ikhYwFWWl4F6iTau6wMN1BpUpXAPCaS4dJo4KsXBZosy69dl8neRwyy1NRlNCEWPGCXk9pFKY+unGzbRcNzzftecR23QlSJoGS8+AOrQXFo1WItJZj64a5U/x7suMLC7LSsCBrIWEJsnKiRVEUpNPpSC3g9Wz+sr1RK7NA230uSh2HFMthiLEozYX9mVZvtt0slmuas9YuKLt+iNjO7wNEEK4NYTsQ2Pe8aEc/FcAoG6OR+7EThFq5+Tg6OhpojGynw4KshbRbkFUrXSHHEoXFulYLWaljSqVSLcsCbUf5DWDf4/Bns46NjUXimjDRo5nNVia5hG0VaRVV7xEnBzG2Eeqee6FknwZsGwq5AAhwXZQ76tSjy72/hyXOgrj/oyTUyrksR0dHMTQ01LFzMmhYkNVJLS7LoOM5ai1d0S7xUSuVzom/4TfQvnIcraa4TVOp44jCYhSVOcHURrXNVtf1CaUUoui+agmuCeQehbL3PqjpByFMA8J1IAiAQME6VuNXhWkpa2dJjzCEWjVBxpSGBVkLkZlXQQmyRkpXhB3X5qfUWCpV1Q9qDEDrBUkpQSkzqEoR1jVpdF5GaR4xbyE3WwBQVdWLFa1ls+2UYrcCLpB/BkrmASiZJyCyz0MxDQjHBVRl/D1ACe9kWaLktgyLZoVaKbHmnz+VMiyjNseiAguyOqm1xlUrqafwaakxRWUj9Y/FcRwvwFMI4SUeBF0XrdXXqFiIdZJIlvWQAHSuxYQpST2bbSTbR5EL6JuRzPwWsV1PQc38CcLQoVhGQXgpKoRa/1oRFSEW5azYSnOn1mLJ8v2y3JKcP5xhWRkWZC2klZu9LF3h72XYSOmKqGz+QGEsjuMgk8nAsiwIIUKri9Ys7bbstRp/MVpJtY04KvOIaZxym23xJhtK+ygiwNoCkXsMSv5JxHIvQWS3QDE1CNsBIIB4Y50roiLE/HTamldLDb7iuSMz/o888kjMnTsX06dPx65du/Df//3fGB4exqxZszruPAQJC7I6CdpCVqreVjOFT6MgyOSTkqxSXWtV/SBo9hoVC7FGLHthZuPKhTKXyyEWiyGZTHqiTNZHK7URy/EWP/Ey3YEUWH7qsYg0JdSs1yH0x4H8c1DzL0KknylYwgwDwnWBWAwikWjouKIoxIDuergpJdRkeZ+enh5ks1lceOGF2Lx5MzZt2oQXXngB69atAwAMDAxgeHgYF154IdavXx/WIUQGFmQtpJnNPqh6W2EKsmIrH1CIcxkcHAx9M6/3nJRysXZK4/Li9kwAPJEvLZX+xbTaE69Ebr6qqnZ2oHiX0OpzX49FpGahBgtCSQL2Tgj9MQjjJQh9K5Tdj0BYBoRhQJhGwVoWi0P09DQ09qgKMT/dfq/Iaz44OIhPf/rTAIDPfvazOOOMM/CRj3wEzz77LJ599lls2rQp9DqZUYEFWQtpRJAVZ+W1qt6Wf0zt7h5QqkBtf3+/d4xhLkT1/nZxIkUrXKztEsnFQiwejyOZTELTtIrzq9RGLK9lKpWKZB9Hpn3ULdSsMcTxFOLWfwK2BVushGq/CSX3KpTMc1AsEzB0iPGscdHbB8Qay67uBCEGdJeFrBTl1vl0Oo0FCxZ4f971rneFMLrowoKsTmpxWdYigGotXdEs7bSQFQuA4vZGlmXt8xQdBrWcE1nTqZFEirApJcRkVwDLsrz31BuL6Bdbxb8XlYKU+ytR2OAnCDVyAPsFiOy/FP7RtSEcC2QNIDn6QyiWCWHoELoGZHKA6UBM6geGBhv+/U4RYwC80I1upZIg46D+8rAga4BKG3q1qtmNlK4IaqytopS7tVRboCjEs0nKjaNYiAUR6xbUeagkxIKkmfT5SGT0Ma3D2Q4YD0Lk7y+IMteGYuiAmYCafQUw9ML/53JA1iiUqxjoAw7sAxqcp50kxPYXWJA1BguyFlNus22mdEUQ42kF1ToFlCIKgqzUOZfN2GXQetjN2OuhUSFWr/Cp99rVKtTKJRKwUOsQSAOM30LkflAoSeHahXgwPQs1OwrYBhTTBHJ5UFYDDBuICYgDhoC+XqDRa7r1DQBAauu0CS9r79/Z5AEFT9ihG0FSrigsUaGx+OTJk8MYVkfAgqwBKokc/7+1qnRFK8baygWglmr05cYSBfznRFrE2nl9WiWSm7GIhSmMSwm1RgPFVVVt+FpFZT62irbXCbOehsh8C4AAXKcgwswcFC0DYeQgDBPC1IGsBspogAOgJw4x80Ag0USy0rgQK0fqRwWBNnbG6+wajxijo6NsIasAC7IWI4PopeWoFaUrmh1PqyiOe6vX3RqEOGwEufFnMhlPiIV1fRqhGSEW1eNrJqNvf49Pa6u4tl8DtLshrMcBciFsE8LMA0YOip6FomuF4HzDAI3lQFqh8DAG+6AcMAA0E5pRRYhJ9rxrK1zXBY2vU0D05kjYa2CQVGoLlU6nMWXKlHYPqWNgQdYA5W4kuXFIF0yrSlc0gz/zs9EFoFVFUMNegKTFUm7qYQmxRq9JWDFiYVKLUHMcp65EAqZOnDRg3Auh/xoAQTg2YOYhLA2KloXQclBMAzB1IKeBsjqgA4gpwLTJUPp7GndLAjULMemqTI3/f1STTdrZxzIMyh2f4zgYGxtjl2UFunclbyPFLjwAGBwcjMRG2UxttOIEhGZrb7VCHDaCFGKapsFxHG8RjkI9tFrYH4VYNfxCzX8eat2EgUK3AllDjePTinDygPUQYP0Bwn4dcG3A1CFsHYqehdBzUIw8YJoQug5k8gVrmIWCO3L2IJTeFtSWqiLGKsWLNZNsEjWLWidSfK7GxsagKAr6+/tDGlH02X9X9BZQqnQFUFjoo7JZNiLIgk5ACLsMhyxuGtbiWqswDUKINSrQO2UjqmUTll0jLMvyyoAAnEgANw/YTxREmPUSQBZgGoClQbH0cZdkQYTBtiCyWSCjg3QCOaIQoD+zH2qyBWtfBSHWbNB+VIRat86rcmsLNxavTjRUQ4fhOA6y2WzJxtgy4zAq1LoBFwe4B5Fp2K4bsZSQ6evr81zHhmG0vVhuPUTVIhaleV0v/k1YiEJP1b6+vrYnEgRJQ2Ny84D9DGA/BmFtKpSqsHTA0sdrhWUg9DwUUwdsCzAtiNE0kHfgGgBsAZo8ADG9F2q8BTUUAxRi1WiXUOvk+6gWyrksR0dHMTQ0FMl7JyqwIGsA27Zh23ZJy1FYbrlyVBNkxe68IOOqmnGf1kKt9dCCHEMzRFWIdTON9nDsaJeWmwWc5wB7E+C8DOHsHBdbGoRjQtFzgJGDauoFC5ltA3kdYiwH0l04OuDmVEBLQMxLIT6rsfZGEygjxPa8aytSqVTJf2sXra6zJx8GO2KuNEA5QcYWsurwSt8AssRDqYnVKYKsuL1RcVX9do6lWYqFWLV6aGFfl+Lz0E4hFrQo7gaCSCRoR5B4RdwxwHkWcF8BnC0Q1quAYwKWCbgmFEOD0LOF/5o6hG2BTBvI5QtlKwzAyQtQJgGiOMTMJOKzEhA9TSZJlBFi2vt3QtO00O/VSjRTZw+YGMPYbe7xUschLWRMeViQNUClGydqG16pzT+IJuaNjKVZiAi6rk8oTJtKpWqqhxaF6yOvRZgWsW7ZANpBs4kExc3YA9+A3TTgbALodcB5FTBfhnAtwDYA1yq4IY0cVFMDDK3Q1Nt2AUMHxjKA5haEWE6Fm0tAxGJQFyahTo9DqE2Ou4QQK3ZJRuWhtl6q1dmTHhb5IOanG+IYy62tXIOsOizIGqDSzSGfqmVZhSgga6NpmlZXVf0gxgE0L8iKhVhQfUCDJpPJhHYtmNZRr0sr0EQCdw/gPgvQDsDdATijgPkq4BgQjg3F0gGzEBMmjHxBiDkOyLKBnAaM5UAm4JgCTjoB0mMQA3HElyWgTGqB9byEELNe623uOzuAYqurbdueK7aROMYoCzVum9Q4vAO0mKhZyGS8gswsrNWKFEWKWzU1KsTCspD5LWIAoKoqent7QxXFtS7oUVz4o045oVa8+Ta1ARMBtAtx9U9QaBSw9xZixIyXAMeEcG0IS4cwtELJCkMDtFzBUmY5BZflWBYiZ4NswM2rcMbiICsGHJBA8sgElFQLarcVCTG/CLP/35ayH+vGeVdsOa3mHu80oVZOkLGFrDosyFpMVASZrI0mhZgM1g9TiDV6boqPJZlMIpVKNVzks92CrJSb2LIspFKpjrOKdaobKUo0mkgAYNzdKaAou6Aqz0NgDwSloUKDYuwBrFchXAfCNgFLLxRvNfRC3TDLBBwLZLlAXoPI5EAmwbEFKK3CySYBkYCYEUPy0DiUWLDWsEpCTJ6T/ZVOF2qlfmdsbAyzZ89uy+93Kp21G0SEWiZ1WItJqar6lmWVfFIPg3rEULEQa7RDQDmCFhflkg2EEEin04H9bj3IBZ4Jl+obsA3XfQOKeBHAHoCycC0bwt4L1XoZcXIgHBOwDMDSoVo6oOchDA2KZQGOA7IsiGweyBvjbkkV7mgMjhYH1ASUeSoS82NQlNYKsXpEWDHdKP6bqdQfhFBrdfeKcuvq3r17MTIy0tLf6jZYkDVIOWEhb5h2b3KO40DTtJK10WSsUhSo5dzIeLdmWzVVGkOQlBJifjexdCOHeU2iMh+YSjgQ4lUI8TIUsRdQdMC1ADsP6P8HQQ7gWBC2MW4NG8+WNMetYZYNcl24mg6RyQGGA9cScLUEnFEFjpkAxRKIL4ojOTtca1gpunmOBlFSqFmh5s/4bCYzuJwg47ZJ1WFBFgAyiL4dyGKularqt3M81agkyIqte35R2eoxAK23kFUTYlGgGy0O3YUJ4FVAbAFoLwB7XIRZgPUahPU64DqAbULYGhTbLGRH6tnxfpIG4BJcx4GSyQE5HcIguE4cTjYON6PA0ROgeAKJkRiSM5oYagAibH+gnUKzHqEmu1f4P9tICRcO6m8cFmQNUklYBG0hq7eqflTKPJSjlHWvmZ6Z7aZeIRaVOEM5btu2EYvFOqu4aRcgRA7A+L0p/gIh3gBhbyFQ3zUBmwDrDQjrlXERZgFWHoprQ1gGoOfHi7cWqugTEYRmQWQzEHkbrgu4RgJuWsDJx+HoCVi5HhAl0X+sjeQMp7GBt0GINePWizpRiMOsJNSa6UpQ7roREUZHR9lCVgUWZAGgKEogm62sqq/rOmzbhqqqNbU3ipIg84+lWIi1umdmpTEArSm/EXWLWDlkdwa5Och+rEDpmllMq7Chxt6AGvsdCC5cR4frDIAoBnLNQh0weydg74Zw3gRsEzA1KGQXrGJGvhCkb2iFDElyAccFsnkouRzIAFxHhaP3wNkLuGYSdr4HVi4FxBX0r7SRnG9A1Lvy11Cugi1inU+9JVxKCTWgsLZLkSZfGxsbYwtZFViQNUg1AdRKF2FxVf162xtFTZC5rotMJhNY8/JaafSctEqItfuayPptQEGQJZNJJBIJz8parWYWUOgDGqUU+86AoKhvIhbfCAIBRHAcA647ALgDIJsA+w3AyQL2q+PB+XkIx4awLQhLB0wNqqEVrGGOA7gEGBaQy0HkDLg24FoqnHwclFFhmwlYmYJFTJ2kYvBEC/GZJuq+VFWEWO71aVC++tvCfIiA5acTiIKFrF7q6UoAvNVe8Otf/zp+9KMf4fDDD8fAwAA2btwIXdexePFi9PZ2f/25emFBFgCtEkDFLXUabW8UFUHmr1AdphBrJlhV1hGrpzNAq36/UYrHDRRKh/T19XkLaKUFV7Z+sW078IDgbkKIMcTimyGUlwBBcB0LLlmAa8K1pgH2mwXXpLsXMLZDOIWWRcKxCkH6pg7F0iF0DXAswHUB2wE0AyKTBUx3XIil4IwCjqbCsXpgjiVg5xOIz1Aw5SQTsQOs6oP1U4M1LPf6NACA/cUHQGWsq62YD906j7rluIrXDen1kCEnJ554IkzTxLPPPovXX38dl1xyife5BQsWYOnSpfjJT37SEV6FdsCCrEGCdBGWqlvVTEudoILYa0W6WS3L8iwqQ0NDoS1K9bosWyXEiscQtEguN+6xsTHPjVDtGgghvHln27a30BY/GUehp2M0yCMWfw5q7AUAAJEDxzVBjgly8iAzBUAB3JcBfQvg6FBcG/AsYXkojg2h5yEMvSDCiADLArJ5iKxWKODqxuDqPXBGCa4Rg2WkYKZ74FoJJOY4OOBoE7H+OuZXmZ6SxdYwSfLrjxb+i8abbFeyrkbhATIoOtFCVi/yGp900kk46aSTsGPHDixbtgyjo6PYvHkzNm3ahGeeeQZvvvkmizEfLMgCoNHNtrgSfata6oQhyIoTD2S8m2VZcBynIxakIIRYO6jmUm1WDDYTEBx2wcpAEBnEYi9DjW0ef4HgkgXH1kF2HmSNATQNoDhgPAPYBhTXBjkWFMsATA3CtSBkAVfHBjlUCOTXTYhsBtAcuA7gOElQVoGbEXCsBGyzB8buJFwkkJhvY8oxeajJOsZehzUMeEuITTj8GtxZ/mbsfqqJ9o6eFxXo1uOq1MdyaGgIg4ODOOaYY3DMMce0eWSdAQuyAJBB/bUKIFkA1TCMploClaOdWX2lhJg/3k26v8Kk2vlolxBr9fUodnHX02y9FVTbmOWmXGlj9rs+g9q0mj/vBCH2Qo1thaLuhFDGIAC45MK1NThODmRlAHIAdwZga4DxRwiyAceGsA0IIwfFdSBME8LIAaYBxXVBtgNyCSKXBbIaYBFcV4Vr9cAdFXDzKly3B1YuCT0dhyvi6FloY9LbclBqnZ41WMOAt4RYKRFWC/75EI/HC2eujrpYALzXu8m62u3WP2DfNYXbJtUGC7IGqeayBKpbpPx1t4DWV6IvNZ6gkBmgmqZVTDyIQjxbufPRTotYq+uf+YVYszxWk/cAACAASURBVC7uVlNKqNWyMUfL7WkX2hXFXoNQ0hDKbggUHrwcOw/HzoCc7LiL0QWsfkB/DoK2AuQWWhmZOQjHgrAdKHrec0+S4wAOgQyrIMTyJlwbICRAegLOqAPSVdhOL8xMAuZYDyihonfYxOBROdS8XLTAGtYstdbFkrGNlmV5iSXRmg/N0YljroVKgizMMJVOIRordpdRTQCVam8UhBCrdTzNUCzEqiUeREGQFdPJrslGhFgj16DVC2mnuD1VdTvU+F8ghAYh0igUbi1kSdp2BmRrAFkACLB1QHcg7O2FY3RswMgDrgHhOIXG3kYOql2IGSPbBpECaHmIXB6kF9ySLnpBYwJuhkCWCsvshzGagK0nYZlJ9B+dx6Tl+dosYnVaw4BghFg1iueDDA5PpVIAUHE+dJpQi9r612pKnXe2kNUGC7IGqdVC5se2bei63vYCqEEIsuJSHLVmgIadYOAfg3QVhyHEmhGmxSK4nRaxoDeTetLrK8UjSddn49l9GuI9f4KipAHKAiA4rgHHGoPrGiiYsFzAMQAzDWGOjRd0tSEsvdDOiJxC9Xw9C8UyIWwLsCwQBMhxoWSyQE4DmYAr4nCdFNxRgpsluG4SttkDc08ClpOAnknCNJIYXGRicLFZXYzVYA0DmndLBoXf0iKvZ/G/R0m410o3F7wFyq8PXKW/NliQBUCxAPJnGYZR7qGVgqyUVaa3t9eLEekE5HnQNA0AOsoiVsoa2UnnvlFa6fasfB84iCefQSz+CogcuI4Jy0oDsEGuVQi0d0zAGoOw8wVB5jqFMhW2AeE6ELKAq6kDpgFhWwWtJhQIzYDI5SHyViHETPSAjBicvQ7IIDhIwcr0wEzHYYs4tL09sOwkJo1omP22nYgPVYi/7BBrWCtolXCPilDrFso9aKfTaQwNDYUwos6CBVmD1GIFkptnLe2N2kEUSnGEaSHzuyYBeHFuYQixeixkQQixbnCbVItHKk4iKD5mXdc9S5oayyGWeBGxWEGIGcYYQDZc1wbIBmxjvFhrtlATzDEAW4ewNAjXLbgnrUIFfcUyIIyCUCOhgCwHyGtQchrIcEAUg+v2ws2poLQD11Zhu32w0glY2QQspQe53Um4IoYpR2ZxwNF7EOstU2i6RhEGTBRiozsOwPQ77qvzjLefeteIRoU7sK9QU1W15WvU/mAhK+ey5LZJ1WFB1mLk5gm8teDXU1U/COTG1cgmHGRNtHYhK9TLciLJZBKmaSIej0faKiYzVvP5fEstYt26GUiqxadZluUJNNM0AViYPPWecWuYDXIdEFmApQGODjg5CNcuxIhZOoSVhyC3UDts3BombAvC1AvtjFDwZsIwAU0DcjpgAS5iIGcAzhiBsm6hxZHdD2NvApYeh5PoQXZXDyimYMoxWRx4dBpKosx90oA1DCgIMQCRF2OtXB9qTSRoZ2JJN9+D5SxkM2fODGE0nQULsibwi5zimCqg4Arr6+uLxM1XryArFjGtcuu1uwRHsRCT5UQsywrVSlTtevitq6qqNtShgZmItJ7ITTeVSgFiO1T1YdhmLyDSIOmGtPOFeDDHAKwcYBmFWmGysbeRh+I443/XIVwb5ArABaDrQC4PaCbgAK6SAplxuKM2SCPYlIRj9sLaE4NlxuCkemFNTUJ7ETjw7WlMXZWBKHWbNWENk0RdiLWTZiysjQq1brBMV6KSy5ItZNVhQdYkpSxIvb29yOVykcr0qVWQBSXE/OOQvxMUlYRY8TiiRrEQC9u6Kgn791uOMKGoT0JgB1ybACcDuBbgFALzYe4uBOeTDbgF4SXMcUuYbRWae9smBAFE0i2pQ2RzIItAiIHQD1cDaNSFawKO6IeV64E9qsJ2ErBSSdhDvdBfJhx46CjmvSuDkqe5SSHWiSIsTNdeMxnAUvRXi0/ruvtpnEouSw7qrw4LsibQdR35fN4TLv6q+lEr71BtPMVdAlpdnLaYoEpwVBNikrCvjxATG9BL12Q7hFizGZ4dDREEXkRP4v/gmhqEmwXIKNQPM14CbB0KOZ4Ig5EvFHB1zIIIM3QIIrgkIOxCIVdkcxA5HeQAjpIEKAl31AVlCK6dgK2kYI2psMYScEQCbn8vRp+PQ+kXmHroHswvJcTKiDCge9ySnUatiQSu6467wt9CijOJ67pdmUjAFrLmYEHWBLLkQCkLUtgbfjHlxlOqS0AqlQq8JlorqUeIRQ3Z1cCyrEhZxLoSGgPc+6BgDORkAPQA9g7AfB2K6xYq61sGhKkBjg3Ftb12RsJ1QBCA44JsF0LTgFwewnAK1S+UHpCdKAixvAvHTcBxkzD3JuHkFDiJHuTSSehaD0QvYeqavZi+qnYhtj+6JTvlHqgnkUA+hOm6DqA9iQTtopxVk4gwNjbGFrIaYEHWBP39/ROsHH6iKMj8Y5VCTC4MQRen9Y8DaF0JjkaFWNjXRwbsy0bfYWfgdjVEAD0OuI8Abh9g7YZqvABBBIDGA/NzhbZG5EBYJoSWgbCs8dpiABwHsJ2CCMvnARNwSYUbH4STA5AulK2w0QvHTsLaHYNjKnASKWRH49CNHqAfmPqONGYcPQrhv83qsIYB3S/EgM63xJZze5qmCdM0kUwmJwi26HaoaA2cZVkbLMiaoNINoihK6D0b/UgB4rouNE0LvF1TNZotwdGsRaxYoLYLv0UMQChCLKxjDwV3J+A8CDjbAe0VCDcNFSi4JI1sQYy5LuA6ULQsYOpQXKfQ3NuxAQjAtIB0BsKwABtwlQRcpReUdkFjNhwrDkcdgKMnYO1R4dgxGHYC+dEkTCsJMQhMPjqDmW/bCyXmm/cNWsOAiUJs0r/dFam1hqlOcaa036Lmb8TeSR0JKlnI0uk0pkyZEsawOgoWZE1QrRZZ1J7yHMfB6Oio1yUgmUy2XYg1W4KjU12TshWMaZpQFAWxWAyO4yCZTIY9tO6ELEC/B7Ae91oZySr6MLXxODEXwjQKLknHAhwHwnFBrgtAHY8NywMmgRyAYn1w3RhorwM3Z8OhGFyaBDubgJUWsN0emJYCPd0Lw42B+gUmj2Rw8Kq9iKfGBXAT1jDgLSE25Xs/9zbk4nilbiEqQqMd+C1q/pJCtSYSlOpQEUadRzkeP5lMBq7rYmBgoK3j6URYkAVEVASZXwgAaFu7pmo0U4KjFUKsXdenWIjJLg2y00GnEPZ8qRkiwHwYIn/HuKvShbALIky4TqFshV3oManY4+2MbAdwHJASA2kmhJYH8rJ2mApS++CaAthlw9VcOOiB4yZhjcYL8WFODLreg3wmBUeocPsJfYdomPW2PUjJyvp1WMOA8m7JXXsnY/5//ptn4fZjGEYkLSeNEIW1MwjqLYhdTyKBbdue5R0IryNB8ffLKv2d8OAcNizIAkJu+GH1bPQLASEE4vE4LMvymvWGSa3nI2iLWJCLfvH5L9UuK6xNp1iMyv/v5A0clAfM30Lkf1T4f8uAsPNQnPGyFY4NGNp4n8lCeyM4DogE4BKg6wVrmGaDbACxJBy1F5RxgVEbjingKH1wnR5YexQ4mgrbjUHLp6Bnk7BUFRgEemYZOHjVHgweZBRE2Gjp4dbrlty1txB/s+Tufy8crm9DtiyrY3o5Mq15uCkn1EolEbSrdVS59Wx0dBRDQ0M872qABVkT1NI+qd0UNzCXQsA0Ta8Yatg3RjXrVDtck0GdA8dxvKzVckIsyN+vF5lcUGt2V1QtF2LPxwECYGlQxgu4wnEL9cOM3Hj9MBuw7UKJCwi4LkHJjAGaAeguCArcxADIiRVqh6UtEMXgKIOw7QTsPQocQ4XtJpDPJaDne0BxBe4BgDrFwowVaUxyXkbMsIGt+46xFmsYUFmIecfr25ClpbW3t3eCUPPHIvlpZRP2oIjCOhUEQd8/xeU15G/W0jqquH5avfOinMtSCjKmOizIAsKfTdiOhcUfLF6qgXm7x1OJcoKslBALqgRHq12W/mQJGaMXBddwOeS51jRtwkJaKgU/qscAAHBGoaRvATlToJivQLhOoaWRnoPiWIBlFrIlbRtQ1ELpCs2E0DUoOR1kAaQmQLEekAbQbhdu1oIjEiClH3YuBmuPgGMnYCMGbawHhpaA26PAnUqgPmDq4lHM6PszYqoDlHhmqMUaBtQmxEpRqjCpqqpe4HiYLYKYfWn3Oa3WkaC4EXujiQTl1tN0Oo1JkybxXKoBFmRNUC3LEihs1EEGzluWBV3XPSFWLWsvChaOYjHUTiHWahoVYmHFGPpbwuTzecTj8QlztZLry/+e0K8NEYT2IJTsz0EYgmInIKypEOZuKPlthRIWpg7hunDjPQAJIJsdrx9mg1yAYim4sR4gT3D32oX6sErBVWmNxuCkFdiuCpviyI+mYJkq3KQKmkYwE4CiGThi5dOIJ0tnODbqlgRqE2K10o7K80HQjRt4FNZfSbPzotjKKh/2S1nIuAZZbbAgC4hW1tsqhb/FTi1CLOjx1It8OgtLiDUriPx13JqxiLXLYklE3pyRvVYHBwehqqonJovj2/xuL+kWsywLlmWFa1Gxd0AZ+wGEuRvCcKBYLwO2BkXbCphmIWPSdSFMC7AsKFYa0B2QSShc8jjIVuDkE3BHLZClwFX74Cg9sN8kOFocNsVgWnHk0ynYVgzUJ+BOJpiKAOVNHHHsn5Dqs/YZWivdkkFTa8C4tJz4CbqgaRQs+UFAROE/zFShmUQCoFD0VlEUPPDAAzjssMOwd+9eFmQ1woKsCWqJIWulAJLxPo30OoyaIHNdF6Ojo6FZxBp14baqoG67NptiIRaLxZBIJGDbNmKxWNnjL16UiQi5XA7xeByqqlaslRSYRYUcKKN3Qck9Chg7IQhQcs8BlgFYdqHQq21DGEbBRWk5hSB9Z7zfpBsDWSrcjICrKXBdASg9sKwE7F0JOLoKB3EYVhz5vb1wSAH1Ae5UYPvzQ+jHHixd/TQmHZjbZ2hBuyXbSakNmd2eTCWh5jgOTNP05sWuXbvw/ve/H0Ch1uLg4CA+8pGPYOnSpd6f6dOn89woggVZk5SztLRSABVvqo202ImCIJP9MuUTVae5JsPobNAMfitqLBbDwMAA4vE48vl83d8l54+sk1SpVlI5i0opoVbz7+svIrbjm/j/7L15sCRneaf7fJlZ2zndfbpbaEcCyS0kIQkJbCzbYQnG9jB3fMczF/teh2+MHUPcCM8Ns8gG23i8wXjDhsGAAbMYDNceZGRjDNgIzABisQViEaIltUBISK2lRUtqdZ+lqnL5tvtHnqzOk117ZVVlVecTodDW59RXuXz5y3f5vdZYnPAoor0dDbNmOxoWxQau2kAgsaHBAhg3FmKBwGw5mNDBWg/rVpFBFblewUgX7Xr4fo1gs47Gwe4S6F2WJ+5do37GJs/937/C2U8/vvP4DhkNg+kLsVlYGfSrQ0pHUnult9LnfxiRvowP62WM/Akh8DyvM/4tyRYcOnSIQ4cO8aEPfYjvfOc7fPOb3+TGG2/s7KFve9vbePnLXz7n1ReLUpBNiTwEULfoxrizDucpyLKDy5POsNXV1ZmvJWHYCFl27XkJsWk2WQwaVD5JurbXy8cwERWt9Y70Rrc6lFMe1CbCfeqvcTb/BRGu47Qejgv3tY6jYlG07T0mwZdYFTdbolysrWDaAtMS2Mjd7pisxkaumxW08tDCIfDrBFtVjOPCGhx9cB9601Db1+TA9Xdx0aVHSJ/ucdKSML2I2DxfskapQ+o1cDv7V/LzJYtH+sXtggsu4IILLuAf/uEfeMlLXsKv/MqvoLXmwQcf5O677+aqq66a82qLRynIpogQ442osdYSRRFBEHSE2O7du/E8b+yH9zwEWVbMJBGx5L8VgV7HYxEbDbKdtvMcVD5qwXA3Q0vPP0j92Htwt74JSiNsSoQl9hWhwgZxkT5aAB5We5gtML6DjRyMW0VTRW16qGYFrV2UqOA360TtCsYTsA+e+O4+1LrG3b/F05/1GJdedZhKJa63mzQaBnB0K279v2Lcg7pATJr2TNcwLlPacxkjZAm9vlu6qN91XQ4cOMCBAwdmvbyFoBRkE9Iv2pBsLMOSCLHExT2dZspjnbMiSe+FYdhTzMz7DbhfF+oshFieAjk7DaDIg8p71aGkH9C2fT+rj/4+bvCd7TmTSUoyjE1clQE/xKp4pBHWxeJhIwe9ZbGBg1UeVCpIU0GtV5GtCla4SOMSbqwQhh62Cpv+Ci2/jjmucc7YYv+5x3n2877L6q74hSFPIfbjX3jnpIdvoRnGfiFJfcLJ6zr52SKMB5qEXj5dy0IvQba5uVkOFh+SUpBNkWFTQ9baTtTIGEOlUmHXrl076nRmuZ5xGUaIJeuA+b4tZgVRcg4SX65FmJM5rAltlnlZbvTDEeC1v071vpfFKUhjtgv0gzg9aYAgwoYy/mcN1rhYUcG2BKYFJvTiejHPQ6kq8qkKOvDQTmxd4Z/Ytq6oCDZbK7SOV7EVjdjfZPf+LQ4850HOOie21p80LQmlEBuWtFBL9rxms0mlUsHzvEKOByo5lW77ubW2tL0YgVKQTcigTstBjvSzEGLDrmdcskJsUJ1VkTbLZO2zFmKTRMgWzYR2GET7bqrfeWksvsIgdtW3gJTgR1hlQBELMSpxfdiWxfgCE7rguBinhvIrqCcqqNDDuIJI12k/VUPLCgpothq0oxqipnCe1kQ0JM+87FEuPvAo6sjKWN2SMH8htsjnvhdJNKxXV9+g8UCTNJFMk6KsI0/6Rf82NjbKCNmQlIJsivSqIctGY6rVKvV6fWpCLL2evN3pRxFi6XVAMeopWq1W5xw0Go1CR8Ty8j4bl6l8jrU4T34C98mPY9WZOO374+hYILFhFIswGQfNcKoY6WKbYHwwsgqeh3EryM0KastFqyraFUSqhn+sjtYuEodmq4EvK1BRiDM2MRXDOc94kiuufgB7tIY6MpkQS0QYzD4iVoT7KE8G7VFJV1/2Z7L1aZO4zk+DokWlZ0UpyIanFGQTMkqELFufNGsRkJcgG1eIpdcB89mgkjq9xPrBdV1WV1dnLsRGOQbZ62bSTs/sZ49yXeR5zoR/hMp3XotQLVABlv2YcC+i+UhHiKFjfWZNHdN2ML6LNS5UKijHQ63HYszgYFyXMKoTrFfR1iG0Hq1WgyCqQiPEWdtCuZY9Z2xx2TkPs3s1wh6tnbKuRRFiJScZtYmk2ySKaac9l7mGrNd3k1LSbDZLQTYkpSCbIsmDrlu34TzqkyYVZHl7cc1SkGUbJiqVClLKQteJLWKn51BYg3fkA7jf+weM2AvNEzjNR3H8J7ARoMAaMNKByMVELiasgHExVqClhzzeQAdVtBUY1yNo1gk3qygriKzH1uYqkfYQqyHu3nWkEHiNkGef8xjnnnXilCUtQlrydCMP4TLIdT7rn5Ym20RQpLRn0eglyDY3N6nVaqysdK/JLNlJKcimSJKy3NjYKESh+Lg2HHkLsVluat2E2K5du3BdlxMnTswtjdAvQraIDQbDIpr34x1+F6L5EKL5FN76l+JOSbkdCVOAdDGhhwnd2FnfuljrYMIKsllDRdtCzDr4rQay3cBYi28qbG2toIwHjQB3V4sI0C48Y//jXHrxEbKX3rhC7LpP/9mO+X0l+TGLe3Ie0wiWOUKWkP1u6+vrrK2t9fjTJVlKQTYh3W6urIBJUpPzjmyMGiGbljv9LFKWWVPdbMNEuruyKGTF47RS2nOp4TMS7/534jxxC07zMGw9BgqMBGHBaoENXXTkYoIKaAeLQBsX49eImjV0VME6oI2Dv7mLKKyiLYTaY3NrFWkd3NUAZ6VJhCBse5x11nGuuuQw9cwA8HGF2NH2Ki/+wu/vMDmdd21SsoaSyZhV2nMZz1WvfTTpsFzG7zwNSkGWI+nuN6CTFiuCGIPhBdm0xwRNU5B1E2Krq6unFAEXaYPoFcWbdpPHrBDrd1I9+BsI/3HYfBQiwMSF+jZyMHI7LRlUsMbB4mCUQPl1VKuGVh7GAWU8gs0GkV/DOBAqj83NVZRwcHcFVFYDpHVob1ZprPr80PPu5Yy9J+dOdhNhMLwQA/jPX3sj0N07a161SctG0SJJg9Ke2WsgTfrcF+nlL296nbONjQ3W1tYKcy6LznLs+HNECHGKH1QiYJJRMUW5EQcJslnNa5yGIMsKsWFMdefpx5Ucg35RvKIx8qaq2lTveBXuwx/BRjauDQOsFPE/ywomcDHSwxgnTksqF9mqYfwaWjlYFyJVIdhaRUYexrH42qO5sQttBWK3j9OI8NsVwo06wlU8+9IH+L4LnuwsI08hlj4WWe8sGO4hnbVjmDSaVpT95XQjLdSSfWaYtGe73Z57RDVvel2DJ06cKFOWI1DMnX+BUEqxsbHRsSGo1WodAZPUaxVlw0wESDZVNa/B2Xkcl3GEWN5rGIfE3DIMw1wnMoxLrulL1cY99EYq9749Tksa4oiYFHF9mHQwgYdVHsY6WCuw2iPaaKCDCto4WM8SqRrB8VWUjIVYO6rRatfRwsHZ08atR/itCtFWlQi44JzHueayh6h48X03aloSBguxQQz7kM5rAPcys4jfvV/aMwxDlFIds9tu10A377RFOQ7d1lpaXoxGKcgmJEmJdRtVk/z7OIX00yC7vnkJsTw2GGttZ3ZjssmNOu9zHhtdIh6TN+akA2ke9UbjiLC+AtY/infvO/C+9a5YgCWO+tIB42D8uDDfGheDwBoHHVZRW3F9mLYCPAj8GuFTDaTyMK6lLWu023W0I3D3tPEaEUGrQrBZI7CCvXuaXHfF/axtjzuahxDrxyi1Sf0GcKdHBi0zRXmBzZPkGhBCUKudtFoZ9RpIroOiXQO9zlmSsiwZjlKQ5UC9Xu96QSYbcFE2mOQm1lp3hpfD7IRYdi3jHpe0qHFdd+wh2rNMWaYHfydrbjabhdxcx6Xxj8/BauK/IgFKYIyL9T2sdGMBZhzAQfk1VKuODrfFmYDArxM2V1DGxTqWlmzQ3qijBThrbdCWthSEUYNQgVsPee6Bh/m+px+jdeQsWht7TlnTPIXYIPLq9CvK/lIyOvPo9pwGvV7u1tfXywjZCJSCbAYUZcNM1rG5uQnMR4gljCOG8hJis6Tf4O951rDlSngC7643o9aux/ohaAubd2D9Cla5GO1gBVjrIpvbhfrSwzoW60DQbBC0VmIrCwHNoI4f1DGOwVlrIQyE2iEwgkA7KAsXX3iU77/0MOHRM8fumIT5CLF+jNvpJ6VEa931Ib2oFPm+HodhI9L9roFBjSRpoTbLIey9vtvGxgYHDhyY6mcvE6UgmyJFeeh2s+FYWVmZ62Y9ynHpFl3KQ4hN89z0E2LzJttUkWz04+A8cDPOvX8DreOYyl44/gTm2MNg6/GYI+1gtIdqVVGyilEuuKCEINhaJWzXsQiUgKbfIPDrmIrB29fCKEOgPCIj8LUg1IJ9+zb50Svvw9tYIzx65o61ZEUYLI4QG0S/Tr9Wq9WJtBY9kjIM894vi8owjSTzHMLeS5CVg8WHpxRkOdDvwT5PQZYVYrVajTAMdzQezJNBxyUtxKYhaqZxbrKDv1dWVqjVaj39iOb58Emuj6RmZVBR8Y7v0H4C79bXgH8cwgDz1HHYvBerBUbWsVagwgomqKCj7Y5JYYmiCqHfIAqrWAHKOrT8OkFYx3oKVnzwDO3AIcLBVy6BAa8ScfWZ61x81iZs7KxJGUeI/afP/XdWV1dzO5bzIjknrutSrVaB0pKjqEzL96+XWM+KtGl2/PaLkJUpy+EpBdmUmcdDt1exPtCZPzlv+t300xZi02Deg79HIWkyaTabnSLj5CGute7qpeS6LsYYHCEQ3/473G99EBNqxKN3YY3ASgej4oJ9FXqxCAsrGB3Xh4WRR9huoGQVLUAjaDZXCGQV6xjEShscTWgcQukSGEGoQWG5cHeb77/wKJ6787odtj4MTgqxx/wqv3LH73W8ApeRYSMp/c71PKNpRfMhy5NZfqduKetsfVpyDfRKe6abCPqtvV8NWRkhG55SkOVAvwt1loIsKwqyNWJFcqfvdlxmneZLUjyTMEmn6qzFurUW3/d3pK5XV1dRSnXqj5I/123TZusI1YN/Ad+7A/vkA2BE7J5vXKwRyKAad01GFTAOVhjCqErYXkFKDyNAGYdme4VQVsHTOKstjGuJlEuoKwRaEBoIjGC30Lzw+x5l3+rOrrNxhRjAr9/9uh2pnGVh2NqkYQrIi1KXtGwUYczWuDWK0D+q2u27WWvZ2Nhg//79M/luy0ApyKaM4zhTt70YJMQSsrVD8yQthuZVbzWJILJ25+DveTZIDCI7G7NarRJFUd9U6o5N2xrEN94Pt78PZ+MxjHbQURW7Pehbh148XzKqAAJtQYZVglYdpStYxyJx2NrchdQeeAqx2opNXo1DJOP6MF85tFo1HEfx/c88yqXnrHfWNCgtCYOFWMmpjPqA7lWXlLclx7yFy7Qo6vfqV6OYHsDeaxoB0Hl5S19PZQ3ZaJSCLAfmFSHL1isNIwrmXbeUXocxhmazSRRFA+utikJW3NRqtbFHY037XGRHMiVrTf57eh09eeQrOJ/6NTjxKFY6aF2N7Sukiw5ryG2DV4tAW4EMtj3DlAeeQRrB1tYuIlUBT+HtbqKEJdIuoXIIjSDQglazjrSWi846zo9c9D0qXnxcSiHWn2ldP+PWJeXRRFCE/WkaLOL3EkKcMjmkWwQd4lITpRRvectbuPHGG7n88svZu3cvt9xyC1EUcemll3bqHEu6UwqyKTOLwvHshIBZr2dUkhSYMQYp5dyE2CjHIhFiQRBMdfB3HiTTC9rtdte1ZidIdD0GR76B88GfBiswkQemhjECFXoYWUUFVYxyQIC2gjBoELbqKO1iXUNkHLZO7EEZF1GReGtNNBbfOgTSJdIOvga/VScwsLsR8BOXPMrZu+N0ainEikm/uqR0JKVsIjiVIqQs8yAbVTXGYJpqTQAAIABJREFU0G63O8+g66+/Ht/3OXToEEeOHOGlL30pEJuoX3rppVx77bW8973vnedXKCylIMuBWUXIJhFi01jPqKRnfiZr2bt371w3qUHHIhtlylOITeNcJEJs7NmYT30X573/FmMcjK6CFWjlxgausoYMKmBdDBZtHML2CqFfRRsXPEOgPVpbDaTxcDxJZdUntBAoh8iKjp9Yu1Uj0CCE5poLH+eapx9HiNkKsWV4OBaBQWnPrFBL063LL/mdJYtBsoclqevrr7+e66+/niNHjvCDP/iDHDt2jHvuuYe77rqLu+6665RJBCUnKQXZlEkeupO8HeUhxLLrmSXd1p9EnOa58Q7qGlqkwd9KKdrtdsc0d6zZmFoi3vPv4m5JKzBRXCumo0qnZkxZ0NohbDeQQS0ed+QafOnR2lpBGQdRiXBXfRSCwDhEWhAaQatdJ1RxvVhgLE/ft8mPXXqE6MReNp4oI2LLxjBNBN26/BKSmtJliKYtc+doQva7ra+vs7a2xv79+7nuuuu47rrr5rSyxaGYT5clYpIbME8hll7PLLs+s+tPrCCSYvh50u1YZIWY53ns2bNnakJs0mOgtabdbo9kmtu1uePxb2NveTP6/H+LaUlMs4k+9gBGuRjjYgClXcJWnSioYyxYT+OHDdobDZR1caohXj1CWYFvXSItiIyg2WoQKkGgLKGBejXkJy57jKfpGtGJnQW//UQYnCrEXvH11+A4TkeILvMDrx+L8r2HaSKIouiUOkc4mfbMDmBfJBZtvcPQaw9LBFnJ8JSCLAf63WTpPPuwaa5pCLH0Wmfd9dlt/WlRMO9NKllDejRTMqx85CjTCEwijvPqTDUyxHzpA9j7bkNvSczmU6jHvoc1LlrXUNJF6wpRUEHKCsYKDIJAebQ2V9AInIrErbdR1sFX3nZqUmzXhwlCbQk1SGF59rnHuGaPwtG1HesYVYhBLMYGFZUP46G0yMz7pSYv0tG05HwmM4KHbSIosiXHspynbvSK/iWmsEU7F0WmFGRTZhSriWkKsfR6ptn1OawnVxEEWfK5SimCIMh9NNM0GGUSwCDso4eIPvtu9NYGerOJOnoUqwVaeWjjoGSNKKyipIe2YC20wxp+VEcZF41lM2zgb1awQrP3aU/RatWJAGnA1xAqQ2hg364mP3yGzxmNnTVE4wixx9oOb37gD09+jxGLypf54bhM5GXJkRbm86YIa8ibXvfTxsZGGSEbkVKQ5cDI6aEM/VJ701jrNLo+k2L9ontypUkihVtbWziOM3MhNmqXZ2LqOuk1YmWI97l3ox85hD52DPXEMaxxUNLFGA8ZVYjCKlq7GBt3UfphHT+soRFoYdmMarSjKlYYqvUW1tGc2GzEBfwaIgOBAlzFlXsDnndOc8caxhViwA4xBv0f3P08lFqt1kJEV05HBu2p43hm5WHJMS7L/hLQ7b4pU5ajUwqynOj1cO0nyGYpxAatcxwmMUcdJXKYN+l0H1Bo/7Os79mkYlcf/ibhx9+Ouft2tHHR2kGpCtY6REEVGdVQ23MntXE6Qkwh0MCmX8fXVSyaSq2FqChC7cQ1YhoiYwmVZSuocP7eFi+6cIOGdzJFnqcQG0QvD6UoipBS4nnezA1PSwYzbtS8n2dWUSw5lvE66hchK+dYjkYpyKZMN+GRtn+YlRBLr2dSEZQVYuOYo85DkGWPezJsfV7pyX7nopep69hCLGgT3PQ65G2fwOi4LkwrB2M8orCCjKpo7WARcS1YUMcPq2jrYIRl3a8TqCo4hmq9jXUU0kAgXcJtIRYZw6bvUfEkL7r4SQ7sPTkvcpiOSchHiPUjHUmr1U7WsY1ieFrEaFpR1lE0hkl7pgewp8lr8HbyectKvzmWpSAbjVKQ5cSgCFly489LiGXXM85baB5CrNs6pk2vSKRSqjDD1hMGmbqO/Pu0Irj5vQQ3vxdrBErG0TCjHYKghpJVpHJAWJR18cMV/KCCdeLB3pthDV9WQRi8egvh6NjKQjqEBkJjiTRstV0iAQf2bfKiC7fwnFNFGMxPiA2il+HpsLVKi9z5V0SmfQzTac+kcWeUuZ7Z8z1ovctse9HrWbKxscHFF188hxUtLqUgmwFCiE60Y15CLL0WGE2QdRsXVK/XJzJHnYUg69btmT7u894csyJ+YlPXFDb0CT//Ifx/eCvGxOauRrto4xD5VZSqoLQLApR1afsNAlnBAFpspyZlFYTGq7UQnkEaS6hcIm3xLUTa0PQrBFaxu9bmPz5zk/NW1UIJsX70qlUaNpo26kN7HIr0MpEX8/pOozQRLKMlxyT0EmTlHMvRKAXZFEkiYkkNwzyFWMIoQqjbUOqijgtKM2xt2zzr2NLkYuqawlrL+g3XYbSDkvHvkaqCDCpIWUUbAY4lMi5tv04kK2ixXSMWbAsxx1BtxMX6ygpCFXuKhdoSaMtW2yPEokSb553d4vpzA45v7ONYxoR7EYXYIIaNpnV7aGfTYKfTQ3tR6SbMu0XT+qW5p201NE/6RchKQTYapSDLifQFmU1NJhtxo9GY4wpjhhEhs5jbOA0xNG5KdV6CLNnUNzc3c7PbMH6b5offgwy9uFA/clFRHSndWIghiLRHu1UjUlWMACVgqyPENF69jXDjYv1oewB4qAzNdo1Aa0I0IT77VwL+0zNbiGAvxzd2XtvLKMT6MexDO68U2DJTBG/CQYxqyZGc83Rnb7eRUYtIt/NlrS2L+segFGQ50qtGrNlsDv7hGdFPCE1zbuMo6xiVcVOq89r0s12e45q6Zgnv/hrtmz+IcWvI/VfhP/AQSntYK9DaJVIOgaoQySrGIfYR8xsEsop1NF6tjfA00kKonE5ErNmuIK0m0BGBkFgv4EfP8XlWZTcEO9+ARxFiRwPNBx/744m+c5EZ9qGttZ44mlZ0AXO60CvNHQQBSimq1WrhLDkmpV9RfxkhG41SkOWE7/s0m82etUpFCVl3E0JZITaruY2TdnxOKiBnnbLMNhdUq1WiKJpYjJl2k+ZH/4rgge8in9okOPwwSnkYW0VpB6k8fFlFKg8NKCPYCuuE0sMKQ207NSmtINKCQAoiGwuxyGoCExGiCJ2I83b7vGCtwW5vd+fze1lXQG8hdjozSTQtK9LmnW6fFosgREYhEVzV6sn7IX3O052e87LkGId+zQobGxvs379/1ktaaEpBlhOVSqVnjVie3l+TkhYh8xJi6bWMc1zmve5R6WXqGkXRKZGRUfHv/Bqtz95M8MDDBI88itIVjKmizbYQiypIXdkWYg6bUZVIeVgBwpE4rqEZVIhMJe6a3DZ1jawhMJIQiU+I4wVcu1bj6j0rnc8eVYjBSTG2zJGxcRglmpa1Z4B4EPcyFJQXZZ/Mm14d+Mk5T+9dw5zzotcjaq3Z3NwsU5YjUswn2ALSL8pRxKJOKSVBEOTS0TcJo2zAiSVEMvh70nVPO0I2yNR1EgsS02py4n++G/9bhwgeehSlXaytIrVAqgpBVENqF21BWYetqIovKwjHIlyFcAzKxMX6oYLI0vETC62K/yJiUysuWNH8h7MbNNx4jZMIsb86/HsIIVBK9RQhJScZFE1TSqGUOuWhXfTIyunIsMd+0nrEWXrl9YqQbW5udqaflAxPKchmQFEiZImggfiNehYDtPsxykYxzcHfeZ+bvE1ds7S+/EVO3Pg+/EeOoo2DMdupSV3Zjoi5GCtQVrAlk9SkxfMirGOQ2876fuQgrYlrxrQlMIbISgInYjPSuF7Avz+7wuW7YwPVSSNixpjOgyV5uKTJCrRSqHUne5yUUjQajU5pRC+z00WqUyrimiZh0j1m1CaCWU2e6CXIkg7LZTuP06YUZDNgkkhIHmQjSxBH9Ob99jKMUO1mCeF5Xm7HMc/zkbepa5boe0d48m1vxL/nW2gtUNpDG0GkawRRFakdDHFqciuqEapYiAknwnEMgXFQ0iHQgtBYpDFExhAaQygUoYjYUIbI+HzfbsN/OKtBw3MnEmLv+c5vA3F3WfLWn35AdBNpaaGWPIjKaFp/kuPTz+x0lDqleR3nIry4TgNr7VSO6aReeXmJ8+zPJXMsS0E2GqUgy4lhOqBmLcistR1Bo7XuRJZarVYhbpR+gkwphe/7SClzs4QYdQ2jMI6p67ApU3XsGI+/+x20vvJlrHXQxkNqh0hVCaIKUjsgQG4X6/vKw3EMjhtihUXa2L4iMhBaiJQlspbQaiKrYyEmLb7xqbkhP3V2lSt27+Lo1hobqXWMIsT+7vE3nDKeJukmTH/fRKC5rrtDaCc/1yualk3HlEKtO8PUKS16NK3kVEaZPDFJE0GvvauMkI1HKchmwDwMSNMpvmxkqSjdWd26T9OWEI7j5GYJ0Y9JjkXepq47fvexYzz0i/8ZvZ2CNMZFKkGoqoSyhtLxEPDIOjSDOoGuIISJU5PYWHzpeNakwhJpGxu8Wk2AIkSxEWkCfCQBz9olePG5uznR2sfRrZPrGFWIJXSL2ACniDStdc9xRK7rntKIMijleTpF08a9dvOKpqXPTx4s64ihInir9YqmZc/5KOK81/lKImQlo1EKspwYJkJmjJm6y31WiHWLLBWlpg1ObsDzEGIw/savtabdbk8UwRsk1B/5f/9vpKqilEAbl1BWCFQFZRwsEBmHVlQj0B4Ii+OE4FhCE1tbhEYQGpBmOyKm44L9wEZsKYN0AgJ8am7Ei8/ZxV57DidaJz8/LcTgpBjrJsRgpxjrR7Khd4vYpEVaOpqWPBSyac/k55I/V4q08RkUTRv2gZ2ItHkLkKJR1OMxTBNB0jSSbSJIvlPyvEn+WzlYfDxKQZYjvYRO8hCYpgjKRmr6CYRukal5kByvVqvV8eZaWVmhVqvNbPMaVZzOQjjqZpMn//4jmEt+BKEF4eEn8B9fJ+ykJh2aUR1fuTjC4G6nJhUOkXaQxhJokAYiLFIb2loTImlKS+j4RKJNqAIOrApesOdiqvbkZtxLiEF3L7FHzXG+9OR7J/rO/R4KaZGmlNphFZIWaUnaE+iItPTfO8d3u45Sa12mPIdg0LkZNv01SjStqOJlXIryAjwswzYRJMI8DEOstVx77bWcf/75nH322ayvr/PlL3+ZK6+8kt27d3f7mJIMpSCbAdNMWY5Ta1WECFlyMycz/4ow57MfWVPXPIRjt+ti86u388RHbkb5Ea0jJ2g/fmK7WN8jUB5tWSE0btxAYB3q1ZDQCKRxiDRIazteYoE2SKvZkCCJCJwA6bSITEDNifiJfRdyycqezmePI8SAicVYL9IPhXTKMyvSjDE7Up5pAZEWAUlqNBFiiTDLfl4ZTRtMvwd2WqSNGk2b9740DZYpDdtNnEspWVlZwfd9XvKSl3Do0CEOHjzIgw8+yI/8yI8AcPHFF/Oc5zyHV77ylVx//fXzWn7hKQVZjgwSOnluNmkhNmqkZp6CzBjTmTeZsLa2NreH3zDnrJupa96bq262eOx9N9J+6DFO3P4tpHG37Ss8Au3RVh6hcrFCIDVsyCqhcSGoUHUkBoM04GuL44aEGDYVBCZCOgEhPpHxUcbnvMou/v3Tvo/69qZaNCE2CCEEnuf1Tat1ayBIqFQqVCqVzjW3DA0ERXnYJ+cmzSjRtPTPlBSfpHs0eQa9+tWvBuBXf/VXOeecc/jpn/5p7rzzzs5f6RenklMpBdkMSDbzPDaZSYRYej2z3vCs3Tn4OxE1vu/P9QHXK307yNQ1r88G2PrGnRz76Kc49uWDKO2iTAVjHQLt4qsKgfawWKQVbEYVAu0i0FScEG0Nvo7rxEINodGECkIkISGhaBOZgGYU4VnJi848j2fvOgNYPCHWj15ptTAMCcMQOCmkpJSdB0Pam2kRGwgWQbiMEk1LjrPv+zuiabMyOp0mi7rufvRqVjhx4gRXXXUV11xzDddcc80cVraYlIJsRkwqgvKsXZqlIMsKm7RJahIlK0IHUsK0TV3TqGabx97612x+/rbY2NVUsQgC6dLWFSLtbTvtW7ZUFV+5WAwVEYIwJ8ccGYuvNVLE8yYDQqTwkbbNViiRJuTCeo3/4+zLabjeUEIMToqxRIhBMcVYlsTuJQiCzmittJju1kDQLeWZHU+TrkkrskhbFLpF05JxYrVabaDR6aKMiloE0TwJ3Y59OTZpPEpBliPTqNvKCrG8a5emtZElQix5KHYzSS3CJpqcl2mbumb53kc/zYNveV886shUAEGgXNoqFmKxwStsqUpHiFWdECMMSrM97sgSGkOEJHAjIiJCGxDZNq1IomyAIOJ/e9qFXL3nTI62V3f4ii2bEIOT90viu7eysnLKORy2gUBK2bOBIOuZ1quBIPm8tGgohVpvkmOUNX8e1ug0K9KKsMcsUw1Zll7PkPX1dfbu3TuHFS02pSCbEYkr+bCkhVje3YfTFGTZCFM/YTMLYTgMxhg2NzdnMtdz/Y57OPQrf4AyDtK4gIOvXHxZITJxalIZy6aq4msXaw0eEQhDoOPuSW0hQhNoRSQkgQgJbZvQBLSkRFsfpX3ObzR48VlX0pL7Odo+uYZlFGJJbWKSyl9ZWRlposOwDQS9ommDPNPKBoLh6CVehjU6TQvo5OeKPIR70em2d1tr2djYKCNkY1AKshwZFCEbRpBprQmCYCY2EHmG0pMI0yiDv+fdWZWkQpLPn+Zcz8277+Oul70WaVy08bBW4G/XiEXbxq/abgsx5WIweCJCOBppRGzqqi3amm1TV0nohEQiIDQ+TalQpo2yAR6aF+4/n4vql9JK1dAuoxBL14kJIajX67nakAxqIEhqoLpNIOgm1KbRQHC6Cox+kc60SOsmomcZTTsdI2Sbm5tlhGwMSkE2IwalLLO2CtO0gchTCGWFmOd57NmzZ6gI07wEWdrUNVnDnj17prZhfvXHfpZ2VMPgonTsFdZWJyNi2lo2ZIW2iv+96oSARWKJJEjieZORVUQo2iYkcgIkPpuBQto22gYY7XNBYzfX7nk+a95K5/MHCTE4KcYeEw9w+IlbpnIc8iSJxCb+R7VabWb+dcOkPJOUWj/PtEQEDDt0vVs0bRnrkyYtx+jVQDDvaNqyCbJ+QrM0hh2PUpDlyDg1ZLMUYtl1TrqZp6cCJHMyx4kwzeqh0q0xIolITut4n/jGt6hccy3ytoOdrkmpXbQVWLaFmPYw1lJBIhxNZCyRiscdBcai0bRMREhsYRE5bbakRmsfaQKM9XlapcoP7P1Bzquf3ARHFWKLwKCC/XkxKOWZjqj1SnmmhcCwDQTLJsim9X2GjaZ1c6PvJtJG2S+W7RwNIggCfN8vBdkYlIJsRmQ3z7Qf16yEWHotMP5Gkdfg71m9MfYzdU37oeWJ9kMOf/Cfeeqb97P5ZJPjQQNpHJRxUAha0qWtXcDiioiqa2JjV73dPWktkdEESKQTEjgREW2aSiNNG60DtA1YdRyu2XUlz1o9t/PZ4wqxokfG0gX7yXU37VFkk9KtkzAtAsYZup5OmSqlEEJ0oj1lA8HwDBtNS45zmqxIOx1r03pFyDY2Njp7bMlolIJsRiSCTGvd6T4EpuJvNcxaYHRBlvVAG1eITbqOYRnG1HUajQVPHbyfwzd9mvUHHufJ+76Htg7KuCjr0FQugXZR1qK0ZVM5+KoB1lARilo1IDCGyErUtoVFZNpsKoXUsbGrsT51B56zeoCrdz+js+5RhBicFGNFF2KTFuwXjXS0Zpyh647jdKZcCCE6LxfL0kAw7/M6TDSt22zHUQdwLzr9BNna2trSfd9ZUAqyHBmUsoT4YoX5CLHsWoYVQtOa3zgtQTYLU9du6CDi3r/8Jx6/7ds8ec/Dsdu+cdHWoaVcfO2iDBhj2ZQOLe2ANVTdELbrxLZCTSS2C/aVT2TjtKSyPsYEVBzNxbULuXbtAK6Iv8+4QgyKLcamXbBfNIYZui6l3BGtSWo4s7M8oX8DQVakJZ8/b4qa3pskmpYc3+SFYtmiadnvUlpejE8pyKaMMaYjDgCq1SorKytzd6eHwZvfrDo+89qExzF1zStCdvyu+7nzzX/P0TseRFkXbV00gqZ0CZSHBrSxbEpBS1WwVlN1I4QwBImpq5BETkBEQKh9ND7S+mgTABFPr5zDj+67jIYbC7BJhNjB+z4CwNbWVs9i83mRiIxkqkO1Wi30nNNpkoiARIwlx6Nare4Qav0aCLqlPEtz23wYJpqWRDmTiRHQPZq2aMe61769vr5eRsjGpBRkOZK+AK3dOSqoWq0SRVEhCpChf9fnrBoN8oqQ5WHqOu4aZBDxjdf9DYc/fhvKOmjjohBxalJ5cUTMWrakQ1N5GKupihAcTagNkVBIIWM/Mdsm1D6KAG1aKBOAkJzh7OcF+y/vdE5OGhHr5lSfrmFKFzKnC85nscEmQqxIBfvzJCkT6HY8sinPbJfnMJ5pyT5QlAkE8/YkzIPscUqEWaPR2BFJGzR4vejRtF4pyzJCNj6lIJsCSd1S0o7faDQ60ZuihOS7CbJ5NBpM+rsTITauqeu4n2+t5d4bb+Gbb/oQyjho66ARcWpSxSOPjDU0pcOWqsQROzcEa5BCExpN5EhCGxGJgIg20gYofJQOsCZgl7vG9Xsv5ezaGtBbiEF3L7FeqclhbBu6OdWnxVnWX2tSkmisUgrXdVldXZ2aOe8ikK6bG/Z4JA0Eow5dT5/XcgLB9OhWO5gWwWmR1q82Lc/7bhJ6Pcs2NjZKQTYmp++ONwWstayvr3fSZfV6vfPQSzazIgmyhGw0b5b1beO27iulaLfbnQf4uJYbo0bprLU8cssdfOnX34O2IhZjqYiYtmCtoakcNqMK2lqqQlJxFJExhGiklQQ2RIqQSLSIVIiijTYBRgdU3RV+dO/VPHPlLGA4IQaTdU72sm3IFponxeQJ2Sha8vdhWbaC/UnJ1s01Go2JG2ey4hs4RaT1Oq+Dhq5Po4Fg2c59v6hf+jj1E9JFjaZ1K28oBdn4lIIsR4QQrK6udjax7P8DTnnLnBdCiE5qMhvNm3XH5yiCLG3qOonlRpZh1rDxwFE++X/+HsoKlBEYBG3l0t5OTQphaUrBRlRBWUtNSCquJrIGaU08a1LEnZPKaROZAL1dtK+tj2Or/NDeZ3P5ynkIIXYIMRjNwuJEcP9ExyNhmELzQamxbg+L061gfxDZurlpG932G0U0ztD1dKRnUANBv/1lGVKW3Rj1Ow2qTStCNK1fDVkpyMajFGQ5U6vVuoqudL3GvMkWnGajebNk2GMy7U7PgZ+vNJ/6v15LoN0dQkwbsMLSVoIN6SGNpSoUq64itHFELLKaUMTu+oGNOyal9NEE8V9KcPWei3jermfiOu7IQgxOirG0ENvYfHisYzKIXg+LYVNjifgATuuC/YTE6DaZdDHrl6KEcVPZZQNBf/ISmXlF0/Jq3On1vTY2Njj//PMn+t2nK6UgmyHzFmTZLkQhBHv27Jm7uWa/Y9LP1DUPBqUsrbWsH36cb/z5J1j5/qtpPnicYw8fR1nAWtoaNiOXyAgqaBqOQglDy2h8K5FCEgofSYTULaJtQ9e2UjhCclnjXH74aQeoupWJhBjMRoz1YlBqrFsnIJwsWu8293HZyaZri1g31yuVnRVp6W7C5OdGbSDIpkKXSaRNuw63n5DuNYUgK9LGSXn2EmSlS/94FOvuXwL6XdDzEmRZIVapVHBdF2PM3MVYr+M1jKnrNLHWYrTmWx+6lQc+exfHHj7OUw+tExnQVhAZ2IpcQgMinlJJhKGlLY4T4hMRuRFKBIQ6njUpjU9LSgSKi+r7uW7fZay6tYUWYoNIUlpRFHUc9hNBPezDvAhWHHmSd53YPBjUQDDq0HUpZcfWI7k2sp+3qA0E89jze0UdsyKtXzQtLdK6XZu9ImRlynJ8SkE2Q2YtyJLUUDJuJt2FmHQmzpukli1h1qau2QhZ8ma58egx7njvZ3joKw9w7PBxpAVtIDSCrcghsiCswcWgrCUUmlArQhER6ohIhEjdjt31ib3EjI04r7qbF+y/nP2VXTzmV9lIrWWZhBic9OCLoqir8BhUl1YUK468sNZ2IoLL6K82TMqz29D19M8npRPJvjDtBoJZUKS6uERIp0mXsKRFWrcpEdnawTJCli+lIMuZokTIBg3+nnf6NLuObBRv1g0GyRqUUtx905c4eNOtPHn/k0gj0FYQGmhKh1ADWBw0Vhh8bQit3u6YjIickNC0kSZEb9eLGRuw16vzgr3XcH59P4/5VR5LmXkvmxBLR4CAoQr2x61fmqYVR56k53B6nje3ms1Z0697NxHrED/wkxRu8nO9hq7n1UBQEtOv3KCbUEuT3OsnTpyg1WrxjGc8o+yynIBSkM2QbqH4vOlmB9HNRiAthOb9ADPGsLGxMbap6yQk311rzVMPHuXT/+2DHDn4CJEVGON0hFhgIBFiRlgCbZBCEQiJdCIC46NEQGTiaJiyAUaHrLguP7L32Vyyek4sxPyTn72MQizrsF+r1cZ+KA5bv5S3FUeedLP1GMeeZZlIm/+mo4TpSM24Q9cHNRAk18EsX/SSz180+nXiJoIa4mfOTTfdxGte8xpWV1fZt28fb37zm7n++uu5+uqrufLKK9m9e/c8vsLCIWwRwiRLRLYeJk273SaKoqm8PaQHf7uuO7AuJQxDWq0W+/btm9tmIaWk2WxiraVSqdBoNGZa1JxsLsePHee2N32Sez92B9KA1nFKsqUEvokfFC4GbQ1RIsRQRCIitLEQk9ZH6vjvxgQ0HJfn7r6Qa3Y/g+8FtR2f20uIwWALiyIKMTi1U3DWEaBuKc/0y88wVhx5ryeKok7E53S39YCTDTrJy+KwL17dhq5nBXg2QtqtgSD7qJtFNM1aS6vVol6vF65hYxKS75WM8Tp27Bi33347d911F+95z3tYW1vjvvvu69yDz3ve87j99tvnvOriUwqynOknyJIi9Tzz61k7iEajMdTGH0URzWaTvXv3zjx6kI7iJRsYbYo1AAAgAElEQVTn/v37Z/b5nYe3VNzxN1/iC6//x22TV4GyNk5NGoG2FheNBSKjt1OTitBGSCcgYNtHTPsoG6BMQEVYrlw9jx9cO8DjQX3H5w4jxGCxxFjWYb9ID55uERetdd8i80lFWpL2TkeAJokSLgPdPOcmbWLoJsAT8QUni9PT5zYhm+rsJtTyaiAwxtButwt1X+RBIshqtdqOiO/GxgYXXnghYRhijOGee+7h4MGDbG5ucsMNN8xxxYvB8lwhC0CeacJJfbkG2T1Mg26mrsn3mEXqNF2TdM8/fYP/9Zt/2xFi0kJTCULtoq3BQeMQ14hF1sT2FUgifEIClPFROkTbNsoECDSXrJzJdXsv5Xi0i8eDk587jLs+LJYQG1SwXwTSUbFs/VK/IvPsg3zYurSsON21a9dpUSfWj17pyUkZtuZw0ND15HdNu4GgSPdFHvRKxW5sbLC2tta555773Ofy3Oc+dx5LXEhKQZYzgwqXJyUvX65ZCrJ+4jGpQ5gm6boSYwxRK+RTv/m3RJo4IqYcAu2gbWxf4WIItEEJTSQUgVBE+Cgn7pwMbYjWbbSIwERcUF/j+n2X05J7OZ5qHltGIZZNxU3bUX4aJCmuSXy10qmxtDgtxz/FpMWp53msrKxMXZwOU3M46tD1SRsIlj0Blb3GT5w4wdra2ml97U9CKchmSFoEjXrB5j34exaCbBjxOMkxGUR2MwV45OsP8o2bvsLuKy/iu19/mECLjhBzMEhriawhEpLISnwRdor1lYqL9bUJMTrgrNoq151xFdqcSSuVpV5WIZZnwX7RGMZXq5sVR9q2ZdmOyThk05NFEKeDzu24Q9eHaSBI/t+yCZRez40kQlYyHqUgy5lhImTGmKE37bQQA3Lz5ZqmILM2Hlbu+/7Q4jHPdSS/K4mIWWvRoeILf/5ZHj74CN/50oMEGpSN3+RbGpraYNAIoTFOhOeFhCKIi/Z1gBVB7LJvAta8Ktfvv4oK56NTe/EyCjGYf8H+vOiXFgvDECnljodxFEVEUbQwVhx5kvVYK3rktJ/Vw6hD17ulPNO/B+J7KG2yuuiivV/Kcu/evYU970WnFGRToJfHV3ITDiM+ElGTRCTyNkidhiAbx9R1GlGxpHDbWovjODx21xFueeunefTbT/DEo+tIC9YYWga2pEZjcIQGJyJyJJIAaQJC00bbEGNCjA3Z41p+eN+z2ONchODkuicVYg8/chcAzWYz1wLzSdFad4RHUUf7zJrkBSnbKbhIVhx5k01PLrJgH3foerY2Lbl30tNQukXTsk74i3JN9BJkpUv/ZJzeu+uMGUYEZUXNtAxS8xRkk5i65rWOtBBLfq+Rms+953N89e9u5+hDJ2IhZi1tbWlKjcTgOAaICJ1td33jE9k2atvY1ZgIF8Plq8/gipUDO77TOEIMdoqxE+uHT3kjz6PAfBKSl4EiF+zPmkHHZNiUZ7/apWlbceRN9pgsq8fasA0EWdNioHNNpO/bZR66XprCTkYpyKZArwhZP/GRCLF0R9K0DVJ7rXNYkrqidrs99ponFWTZgttkE3vo9of58O98hEe+dXRbiBnamo4QQxiEExGhCJ3YP0ybEGV9pIn/2ROWixrn8Nzdl+GJk7fKsEIMhktP9po31+tBPi2RlgjrMAwXIu00C7K1c6Mck14P8mHMT4sUKc0yyTFZFro1ECR7IdCpOUtPH0h+rlcDQT+hVjSRVkbIpkMpyGZIN/GRjS7N0ql+EkGWbD7ZGZnjrAFGF2TZzslkkwpbIR/45Zs49NlvExnAWnxtaarYvgKhEY5EO4rI+gQijL3ETIAxIdL6CKt4euVpfP/aFTSc0U1dYbI6sTyiLaMM5M56Z1UqlanOD10UkpqoPI/JICuOIkVKu5EdATXL8WZFJW142y1lm713Rxm6XuQJBN2uv42NDc4555yZrGEZKQXZjEm3U/ca/D3rtYxCt9FMk6QpRhVkvYSYjjSfecfn+NRbPou0YKwl1JatbSFmhUa4GkmEJEARxgX7JkBrHyMk2gTsd3fxQ2vPZ83bOepj3qau/aItgwZy90uJZQv2Z2FPUHTS445c151J7Vyv2qVxrTjyJp2eLEdAxaQtYPql9odJeQ7yw0vuW8dxdtTIpvfC9OdNO5rWT5BddtlluX/e6UIpyKbAoA1RKcXm5mbnIbhnz565FEuPIsi6mbrOsq6om4WF4zgYbfjKh2/npld/GG3BYImUZUsbQmOxQuF6GmUlgROiCJHbNWKRDrDERfu7vTo/sPf5nFXdOTFg3kKsH8PWtvSaB5iIuWWu/xmFrGXDvGvnxrXiyEbTJkl5ZtOT5QiomHT0dBzD224pTzgpwtPnuJsIT8/zTEiXbsyigaDb9y1TlpNRCrIZIqXsbHCe500cXZqUYQTZpBMBhlkD9I6QZS0skp9Jfu73n/1bHAsEFkukLS1t8bXGoHEcgxGSgIBIhNseYj6R9tGEGBuxIlyu3vNsntk4f8fnLqqFRa+NPrvBpzf5RIgkrfmni1VDwiLVRI1bYJ614Rjm/KbTk2UaOyYbPc17GkMiwtN0qzvsd37H8UwbNZrWa7/e3NzMdTTg6UYpyKZAdqNLD/4GOqm+eW/4SdFpN/KaCDDsOno1OmQtLNKff/vNd3L2dVdgHnyK7x56jLYxWBSOo8FRhCIisv62jYWPsRJt4rmTFQFXrB7g0pVn7vidkwoxKKafWHKuk2hKrVajWq3u2OT7WTUsq0jLpmwXsSZqULRlmOaQtBVHdvJAaXcy30hhv7rDfnWlwwxdT35P9vMGibRkP87+t/X19VKQTcDpfZdNmbQQcxyHXbt2dTrYivBg6yaEklqRUUxd815HNyGWvvnbGz6fetcXuftf7udbX38IX2sUGisMiojQSpQJcR2f0PoYE6GNj7YSB8llKxdy1eoluOLkm20eFhZFFGKDCvYTF/L0n++XMslu8ovqp5WOdCyr6BinOSRNpVI57ScPQHEjhcm9OEpKG05tIEgYpYGgXw1ZmbIcn+XagQqCMYZms9k1zSelRCk17yUCO4VQ1v8sbyPaYdbRzcIiGxU79K/38cl3/AvfuOXbHSEWe+xHSKEIrI8Sca2YkttF+zZCWMXZlbP4N/sup+ZWO78vbwuLIpF+kAybXumXMklv8ukZpLMsLp+UotWJzZpeKU8pZcfINDkW6dR20a04pkH6WlkU0T5sSntQF2/y37o1ECilOv8spdxxr29sbJQRsgko9tW1oCRvnb1mN07i/ZUnSRorEWKjmrrmSToy002IRb7kg39wM//rL2/FtxZlYyGmkEhHEtkgTk2KAK1DtA1RxkdgeJqzxmWNK1hxV3mqxyzzZRJi2ejPpPMEx2keyLu4fFKSSGHywjFOIfYy0i9SuChWHNMg6YAvek3hMAyT0h40dD051+la0+Q6ScTZPffcQ7PZpFarnbKGkuEoBdkUqNVqPed59avbmiXJzQjQarVm6n+WXkPyAI+iqFMom32I3/3F+3j/b36Ew995HInZjogpIiQhAZqQiDZKRxhCIt0GK9kjdvHslStZ83qH0IvWOTkJ2ejPNOtchmke6FV8PGuRlvXOWuTRPnmRtmwAul4rg6w4Bj3Eix4t7cYgT7FlYlBKu9fQdSEEDz74IF/60pe4+uqrueSSS3jXu97F29/+dl784heXw8UnoBRkU6LXBpSeZzmvTSpt6grMvNszm56s1+tdncub6z5/+esf4+Dn7kN2UpMKJSSRiP3EJAHKBCgbYHSEtgF1PK5YeR5Pq5zVcw3jCDEophgrUpdg8hDvV1w+q0hLt0jh6W7tAZMZ3g5Tl5Y1Pi1atLQbw3qKLTvZaHhaoCb3tTGGr3/967z61a/u2ObU63Ve8IIX8AM/8AN85jOf4ZprruG888477Y7fpAhblPzZEpHc3N2Ioohms8nevXtnnhbMmrpWKhWCIJjZWgZZWCREgeTv/vTTfOTPbkFZg45lGMZRBDYgEnEkTJo20gZYE5u6VoXDgfolnF+5sOdGsGxCbFEd9ruZniYvCDDZMO7swzXpKD3dHw5Zy4Z6vT61mqhuKe30rFkYz4pjGkzqKbaMpI3LE8GVFqibm5u89rWv5bbbbuPaa6+lXq9z8OBBDh48yMbGBmeccQZPPvnkaX8cR6WMkE2BfhfhIN+tadDL1DV5mM9iLYMsLOJ1Gj7/d1/nHTf8LQpQKASGiIhQRGgiQuGjrI8xEq19JD6eFVxceyYX1w7giO4P7WGFGCxGelJrTRAEHXG9CAXHacbpAByUDssK1Gq1WnYJMp/oz6RWHFlBPg3S9h6LeA9Ni35dpdZaPvnJT/LKV76S5z//+dx88808/elP7/ystZaHHnqIRx99tBRjY1BGyKZENu+ekLj0z8KdP2vq2mg0dkQKZrGWYYRYwkvO/XVOKI3GYNEoJAEhxpFExAPAjZUo7aNsiLCS8yvn86zG5TuGf6dZNiGWTcMlUY5l3fy61bSkIy2JSBNCdP6M67ozr4csKtnoTxEFajchno6WZoV4txFgo35eOX3gVLJdpY1GY8dz4fHHH+fVr341t956K29961v5mZ/5mdP+mOVN+TowY2YRIRvW1HWaaxnGwiLNrR8/yEU/cQlP/vNdccG+kITCRxJhCJAmQBl/Oz0ZcaZ3BlesXEXNqXf9ff2EGJQF+4vCoA5PpVRnAkZC8iJS5JqlaTNtR/k86XWOs8ang/y0hjnHRfUUmzdp4Z6tQTXGcOONN/Lbv/3bvPjFL+bQoUOltcWUKAXZlOhlb5G+yPNmVFPXaQiydMH+MEKstenz13/yCe69+2G++uVDBIRoIcHK7WhYgCdClAnAKtbcXTx79fnscnd3/X0wnoXFkcfuwXXdTvqiKA/w7Nt8WeOy8x5KxFgSKUynxE4nm4aEZfFZS4u0bl28o1pxZKM/ZYNHTPLMSPa9rHB/4IEHuOGGG3j00Uf50Ic+xAtf+MKFu5YWiVKQzZhpiaBxTF3zXMuoQgzgzlvv48a3fIp//fxBQkIkEZY4AmasRJk2yvhgFTVqPKNyNWve02hKaErNOfWdb/zjCDGAJ568r5AP8ESILVrB/rQZdFy6TR4YZnxQOh22iKSPy7IK93GtOJI9LrGyWNRznCdpr7VsxF1KyTve8Q5e//rX80u/9Et8/OMfZ2VlZc4rXn5KQTZjkmLXvERQFEU7Qs3j+OZMspashQUwUIiFQcRf/Y+b+cBb/5k2AYoQi4pFGCFK+xgboU1ABZcLK1dyhnfuKb8nm5ZMmKRzctQH+DRE2qIX7E+L7HEZZfJAns0DRSNtTVD09OQ06HWO0w0eyZ6rlKLZbC6EFce0SKezs/NbrbXceeedvOxlL8PzPD73uc9xzTXXnBbHpQiUu/yUGNRpOakISrzEkrfhcYqYJxGH3YTYMA+tg7fdx+t+5f/jge8+SkQEQoHVKHyk9jFItA4RaC70DnC298yhN4M8CvbHeYDnJdKyQ50nddhfFtJplTzScP1qlvp5aXWz4ZjnuVmW9GTe9OoqTf5fP0+8olhxTIN0+QNwyvXSbrf54z/+Y973vvfxu7/7u9xwww3li+CMKY/2HJhEkKVNXT3PY9euXRPdNOOsZZTOyYRW0+d3/uu7ufXTB4kIAIVFIXWItSHK+kgd4AFnu+dxvvcsXGe47zXtzslhHuCTtO+frgX7g5il4e2g5oE8C8snJTsGatFH++TJIE+xoltxTItBVhZf/OIXecUrXsHFF1/M7bffzsUXXzznFZ+elIJsSuQdIcuauublrj/KWroJsUEbk5SKD7z9E7zzdR9GorBILApFuD1z0keZCKzkTOccLqxejieG+17ztLAYR6R1a99P0nBJwX4RbQnmwSRu8nnRy0trUGH5NKMs6bTtso/2GYV0FHXUQeB5pLUnteKYFtloYbaZ4cSJE/zO7/wOH//4x/nTP/1Tfv7nf77cf+ZIKcjmgBDDz7PsZeqa140/jCBLF+unI2L91mCt5dMf+wq//Yt/jkJjtq1eDRFSx6OOtAkwVrIm9nFR7UpqznBFo0W1sBhWpHWbDVepVHYM6y3axj4rsvVQRayfG1RYPo20djaKWqazY6blKbZIEdNe9IsWWmv56Ec/yq/92q/xYz/2Y9x9992cffbZc1lnyUmKtdMtEf1uQsdxUEr1/fmsqevq6upU0lj9BNmoXmLpn/vJs1/BUU5gt4WYJsKYEGl8tI0wJmKFFS6qfj+r7nDDaEfpnCyKn1h2Y0+nDpKHdJKCSh7gi1ZUngeLXg+VV/NAN6FXpie7M2tPsXEjprPu1s5GC7NNHkeOHOFVr3oVd955J+9973v5yZ/8yfJ6KgilIJsD/UTQsKauea4lG60bx8IiQSnFrbfcwcUvOpfvfeookgCMJDJtlAkRVuHh8czK1ez1eg//TrOIQixLumC/m+AY9Pa9rF1hs6wTmzXDRkzDMOz6M0IIoijCGFOmJ1MUzVNsXCuOabx09bOy0Frz/ve/n9e+9rX8wi/8AjfeeCN79uyZ6PNK8qUUZFNi1BqyUU1d81xnspZJhJjWmvUTm/zP936cL37+69z+tYOEtomxEteI+O9WcEblIi7zLhvqdy6DEEvXcAA9UyqD3r7TEZZsvdKiirTEluB0ck0fNhWWFmnJn0nMOxftPOdJ2mutyOJ9mIhpt07ecV+6spMZ0l331lruvfdebrjhBtbX17n55pv54R/+4UIet9OdUpDNgUQEJTfiOKauea8lXSMGg73EEpKN4NCd9/P2N93EF265jdBuoU2EYxwca8FKzvCezpp7AUIIjtgTkAkQPt3Zv+PfF33mZDeH/XEK9pO3714izRjTtai8yCItO4+ziHVisyQR48m9mJzLarWK67p9mweyVhxFOs95skijoHoxrBgfpUlkkJVFFEW86U1v4q1vfSuvetWr+I3f+A1qtdoMv3XJKJy+u+AcSW6WMAx3vO3NOiWRiK9ks0u3dw/zs0EQEAQB73/3x/jw3/4z333oAYyVCGMQViNQ7BJPY3/lYlyn//fKRsNgMYUY7Iz8TCPV1E2kDbOpz1ukLXqd2DRJ10NlzTrTDDrP854ukTe9PMUW+Tul6RUZH6ZJxHGczot0N4PXr33ta7z85S9n37593HrrrVxxxRUz/34loyFsHpbxJV3Jph0gvlF83++80Yxr6jopyQ2fjuIk9Ht4JxtkGIY88N1H+J1X/xnf+MZdKBPE0TBjEGjqrHFW9QCuqI68tkUVYmlLAsdxaDQac438dNvU0/WCs3p4d4sWLuNYn3HIFmDX6/WR66G61StpfXKKxaL6aA3yFDvdSDIZSQNQ+hwD/OzP/izVapUrrriCw4cP8/nPf54/+qM/4qUvfenCRRNPV0pBNkWyLdFpU1eA1dXVmYeP015isHOeZTo1kv4zwI4uQSkVf/Df/5wPffCTaBsiOn9WUWOVsyqXUB3SwiLLItaJZQv2k4dqER8esxZp2chPWZgeMy27hvTvz9Yfph/gRe7kzYrUeb/YFIn0/ZSUQST//XWvex1f+cpX+Na3vsUTTzwBxM+Yq6++mmuuuYaf+7mf47rrrpvn8ksGUF7lMyBr6rq6ukqr1ZrpW2o3C4v0BpyEzT3P69zk6e4gKSXWWj72kU/z27/2ZqQJwBqEsYCmQoUzvUtpDGlhkWURhVi2YL/IRcYJ49gzjCPSsnVi8+6EKxKzsGvo1+GZPtdF6uSdtkhdZLKdpdm6y6eeeoqHH36Ye++9l7e97W288IUv5ODBg3zzm9/kjjvu4HOf+xxXX311KcgKThkhmyK+79NqtXZ0vlQqFay1rK+vs2vXLqrV0VN6o9Ctc3LYN+F0LdTXv3oXL/nZ/0YkfKxVCG1xsLhWsN+7iF3emWOtb1GFWHpw8TI67A+KsPRKg2Vrfmq1WvlQ3SY7q7QIkZ9uReXdouPTFmmz9hRbJNKp2+xLnzGGm266id/8zd/kp37qp3jjG9/I/v37B/zGkqJSCrIp8uSTT2KModFo7HgoWWs5ceLEVFOWkwixbC2U74c859IXYdC4xsFYiWMt+9wLWfPOG2tzXtQ6sWkX7BeZYdJgyXaSRFrnLTiKQLruclEiP9lI2rRS29nIzzg1dMtKPysLgMOHD/PLv/zLHD58mHe+8538+I//eKGvqZLBlLvlFNmzZ0/XMThpYZY3aSE2joVF1rz0ocOP8j/e8A6efc0zuOf2+7FWss89j33ehQgx+hvsogqx0qqhdxosHS1MRJlSCqVUoWuVZkERZnKOQ9LFl01tjzIeatCs20XxFJs12dRttrNUKcU73/lO/uRP/oRf/MVf5KMf/Sirq6tzXnVJHpxeT5QZ47ruKZ0wCd0c8ichbWGhtR4pIpa1I0jeUm/8wIf5+w99jC9+4TZA4YkGjepZBI7hexwG4Dx78VDr6yfEHn7kLgCazebcrRmypAuMl7HtfhKyKbhkviKc+vDO1iotu0hbRgGf13ioZL9ZZE+xaZGe5drNyuLuu+/mZS97GdZaPvOZz/C85z1vqe6b050yZTlFkm7FbmxsbOB5Xi5vNunOSWvt0EImm0pJ3lKPHXuKP/njP+OfP/UpjjzyJC5VVqpn4jrD1bulRVo/IQZwYv3w3OtXutHr2JSb33gpuEG1SvMuKM+LsoauuyN99r6GOK1dqVQW9lznSS+/tQTf93n961/PX/zFX/Bbv/VbvPKVryxTu0vIYr+yFZxRxyeNSjchNqypq5SSMAxPSaX84z9+gj/8wzdw77cP4+Cyq3IunlsfaV1ZEQb9C/aLNC4om4JbpDTTLEinmUY5NqfDaKisb9ayNXoMS7fUdvq6SSKiicVOwiKd6zzJWlmk/dastfzrv/4rr3jFK7jgggv42te+xiWXXDLnFZdMizJCNkWyG06ara0tAHbv3j3y7x1kYdGP9EMjXZTebLb4L//lv3LLp28DDCuVs6i4k0fv8uqc7FZMnnck7XQu2B9EutGjW4FxnnSLrqTT+0V7cGeLr+v1+sKnJ/NikKdY+vx2ax7oNzZo0ck2NGSPzfr6Oq95zWv46Ec/yhve8AZe8pKXnJYC/3Si3DWmyKAI2ag1ZN06J0cZ/p1+oCY1LdZa3vWu9/Bbv/EGjJE0KmdQdffksunlWbA/aKbjJNGV0jOrN9kauqRObJoPxUUZDbXsY30mYVhPsW5R/VGbBxZRpPWzsrDW8k//9E+86lWv4rrrruOuu+7i3HPPnfOKS2ZBGSGbIsaYHRtJmlarhVKKtbXBRqrp+puka3PYiFhWbCRv70IIvvKVr/If/93/Q2SaVJ016pX9hRNiozJqJC2K/v/27jw4yvpwA/gThISEEAlHUghIgAghAZI9EMuAoK3UOh1KGVup7ajFdhATwl0oQuRIBYqAaaAxodNBanUYaREVKSoUKHIlmwQIoRQMR9Bwo4bcm31/f/h7t+++2St7vcc+nxln2oDm3fvZ7/F8WzTRsB9q8g9UNa6hU/JoKB7r45r0y5+7czk7QssnD0hJv+A4G2mura3F/PnzYbFYsGnTJkyePFl1t4GChyNkQeTvCFmgKyzEsHHhwud49OHn0NBai/siYhAXlexThYWcGiosfBlJi4iIsP99m82m+BSY0rRS1eBq118wR1eku+C4Q9CRfLd2IEea3Z084O1uXvG9QanXdmtrKxobG52OGNpsNrz55ptYtmwZpk2bhjfffNOrL+ukLxwhCyJxSsOZpqYmNDQ0OG1VFoOY+IYDwOtve9I3RcD5cT79eppgtTWha+de6NTJ/0yu1YZ98Y3a2S4wta1TCgV52NDLWihvTx1wF9JcVcPo/TnhLbV0iqnl5AEpd1UWAHD+/HnMmjULN2/eRHFxMcaNG8fnVZhiIAsid4GsubkZ9fX1iI+Pd3jxBarCwtkur6amJlRWnkFCQh8kJCQg9YEn/bp9WgligONOJleL0t1Nd8prGcRpXz28cYZj2OjI0VAA7CMvnJ505KlNXi283SgifY37+xg7W2MoXX/Z0tKC/Px8bNy4ETk5OViyZAm6du3YjnbSFwayIBNHquRaWlpw79499OjRw34GoK9BzNuahtbWVo9TCMkJj3n8nVoKYu7W0Hn773sKaZ07d1b1uhVXtLBOLJR8WaekxqncUJCHDS2G+GCuQZR+AezSpQuio6MdFu2XlZUhKysLsbGxKCoqwogRIzR131FwMJAFmXRNg1Rrayvq6uoQFxdn7yTz5/DvYNY0SEOaGtaJeUM+6hPIgk5PIU0Li4ulzx01rxNTgnzaXxwRk35oa+3xDiTpc0dvfWtiSJO/xkXiOjRXodxTlUV9fT1WrVqFv/71r1i5ciVeeuklVY4okjK0v0BE45qbmzu84NRVhUWg3R/3gNOfqz2IBXvUx5uNA2o9KkiPR/oEijjaLC68dvXccbZOSa2PdyDJO8X0+NwRN4pIORs5lc58iI93REQErFar06ltQRCwb98+zJ49G2lpaSgvL0dycnIobxppAEfIgqy1tdVhGFz6Zn7v3r0OvYnLP0yjoqKCMk2gxSAG+N4iHyxqGkkLx3ViHSGvaujoaLOej4bytlMsnEgfb6vVitbWVoeZkC+//BKzZ89GRkYGhg0bhk8++QTHjx9Hfn4+nn76ad2MKFJgMZAFmRjInFVYiFOV3nxoiy/8QE+/yWkxjMlHDNW8OzDUIU3+YcpF6Y7kQVW+8NpfoThhIpiC0SmmJ/Iqi86dO8Nms+HcuXNYuXIlTp06hZqaGgBATEwMRo0aBYPBAKPRiMmTJyMhIUHhW0Bqos5PLZ0Rm/WlH7zim674zVmc/pJ/8xL/kRKHxcXF5IF4A9diEHPWsB/sFnl/hXK6U7qwmEdBOQrVhgZPj7fNZlPFqQNywewU0wN3VRb33Xcf4uLi7K+7HTt2ID4+HhUVFSgrK8PBgwdRVFQEg8HAQEYOOEIWRDabDQsXLkR6eucBdrAAABgSSURBVDoMBgNSUlK8enOVf1h06dIFkZGR9jUuvvQouaLFIBbMBftq4c9ImrOdpfww/R95UFXDqI+nHX+hDGnujvUJd+J7c2Njo9Op/7a2NhQXFyMvLw/Tp0/HihUrEBsb2+6/09DQgKioKH5BIgccIQui5uZmREZG4p133sGCBQsgCAIyMzNhNBphNBphMpnQv39/+4eBzWbDRx99hMzMTHTv3h1dunRp96KVjqQ5a6AXeQppWg1i4TL95stImvg8EsM6P0wdyRelq2nUx5tTB+QjaYE+GkreKcZTCBzJqyyka1QFQUBVVRWys7PR3NyMvXv3YvTo0S4fj5iYmFBeOmkER8hCxGazobq6GidOnEBpaSlKS0tRUVGBrl27wmg0IjExEVVVVSgtLcUf/vAHzJgxo8ProLwpu+yflO7031VzEAO0c5xPqIlTXuLCYim97vbrKD31rQWjO0sPnWLB5KnKoqmpCevWrUNhYSEWLVqEBQsWqCbok7YwkClEfGPds2cPVqxYAYvFgr59+6Jv3764fv06DAYDTCaTfQFoz56+HfwtDWl9eqe0+/MvvqxSfL2KO1pasK8EZ+vEpJ1ZSu/uVJq7UQ298OdoqHC4f/zh7hB5QRBw9OhRzJo1C4mJiSgqKsKwYcMUvmLSMgYyBW3btg3Tp09HUlIS8vLy8Mwzz6CtrQ2VlZUoKSmBxWJBaWkpzpw5g6SkJPtUp9FotE9r+hrS1LJexRVnh6OrfcF+KEnvH29OIFBTBUcoyKcn5aMaeufNqQMRERH2Muro6GiO6kg4m96WTt9+/fXXeOWVV/D3v/8dq1evxq9//WsGWfIbA5mCrly5gh07duCll15yeYaZ+MZQUVGB0tJSlJSUoKysDP/9738xZMgQ+wia0WhERkaGz2uq1BLSnLWk623Bvj+k00uAf/ePHkMaO7NcE1/jLS0t7aa3AR4NJZJXWUifP4IgYPfu3Zg3bx4efvhh5OfnIykpSeErJr1gINMgQRBQV1eH8vJy+0iaxWLB5cuXMXz4cIeQlp6e7vN6EGlIE3d3Sp8u0jMc/f3AdrZgX09HsgSCtPg2WPePlkMaj4Nyz1mnmDhKJv8ippXHPJCkmxqc7b69du0aFi5ciGPHjqGgoAA/+clPdHk/kHIYyHRCEATcuXMHFovFIaTduHEDI0aMgNFohMFggNlsxtChQ33ekdXRD2xvPhBDdSanVsnX0UVHR4fs/vGmgV7pD2x5zUe4TU964qz81t30pBYe80CSfhkE0G5Tg81mw1tvvYWXX34ZTz31FNauXYsePXooecmkUwxkOiYIAq5fv46SkhL7zk6LxYL6+npkZGQ4jKQNGTLE5zdVX0MaF+y7J13HoqZ1dGr5wBanb5ubmzk96UKgOsX0ejSU9D3I2ajq559/jlmzZqG2thZFRUWYMGGC6m8TaRcDWZgRBAE1NTUoKSlxGEkTBAEGg8Ee0uQdaR39Hc46lETSBcUA14nJyYOGFmoaQh3SWIPinrxTLFijqlo9Gkpe9SEfNWxtbcWmTZuwbt06ZGVlYenSpYiOjlbwiikcMJAR2tracPHiRZcdadKQlpiY6Ff9RnNzs9MFxYEuudQqPQWNYIQ0edDgqKojNXSKyY+GUtsu7ra2NjQ0NLissqioqEBWVhYiIyNRXFyMjIyMsHwvotBjIKN2xA/R//znPw47O0+ePIlevXohMzOzQx1prhbsO1tQ7G1/kt5Iz8bTc9DwNaQBUDxoqJ2aO8XUsIvbUxVKQ0MDfv/732Pr1q3Izc3FrFmzdPkaJPViICOviKHq9OnTDuvRPHWkHT58GPv378fs2bO9WrDvbcmluMNTLVMgvpIvuA7HoOFNSBP/d+fOne3HiYXTfeSOVjvXgnHqgCvu1tIJgoADBw4gJycHDz74IAoLCzFo0KCA3EaijmAgI59JO9LEjQMWiwXnz5/HgAEDEBMTg8rKSowYMQK7d+9Gr169NN2RFkh6Os4nGMTHXNx9CzgGM73t9POFIAj2oKGXTQ2BDmme1tLduXMHS5YswZ49e7Bhwwb84he/UM2oIoUfBjIKqNu3byM3NxfFxcWIjY3FpEmTUF5eHtSONK2FNPZluedqHZT4Z4GuXdEiZ51ier2tvhwNBcDhC4+4aF9aZbFz504sXLgQ3//+97F+/XokJiYqcvuIRAxkFDCCICAzMxPV1dVYvHgx5s6di5iYmJB1pHkb0sTpTvZlqY+8/NbTyRO+rEnTcnDpaKeYXnkKaaJOnTrBarXCarWiT58+AICrV69i3rx5qKysxJ/+9Cf88Ic/VM2XNQpvDGQUUEePHsXgwYM9fttUa0dasPqywn2dmCfyTQ3+1DToNaQFqlNMr6TnuwLfhjGbzYYPPvgAM2bMQFJSEgYPHoySkhJMmjQJ69evR0pKisJXTfQ/DGSkGqHoSAOCc9qAq9sj313q61mjehWqsKrlkBaqTjEtk+4wlb7OBEFAbW0tdu7ciY8//hjV1dW4efMm6urqAAD9+vWD0WhEQUEBkpOTlb0RFPYYyEjVpB1pYkirqKhAdHS0Q0gzm81ISEgIWgu5s+lOT9ctfkDwOCjnOjo9GWhqD2lq6BRTO2mgd7YMoLm5GRs2bEBBQQHmz5+PRYsWoUuXLrh06RLKyspQVlYGi8WCd955B/Hx8QreEiIGMtIYaUeadGfnyZMn0bt3b4epToPB4LEjzd3vEXexdaQjjevEPJMvSFdTWFVLSFNzp5haeKqyOHHiBLKzs9GrVy+88cYbSEtLU/iKidxjICPNc9eR1r9/fxgMBnuRrcFgQGxsrF+nDbhaSCytZRDLb/kh+j/OFqSr4WxOT0IZ0rTaKRZKgiCgsbHR5RRuXV0dli9fju3btyMvLw8zZsxQTeAncoeBjHRJfNM+efJku460IUOG2EfQTCYTRo0a5fN0mc1mQ2trq/3cSWkoA8LrtAFX5H1ZeliQHuiQpsdOsUDzdB8JgoB//vOfmDt3LkwmEwoKCtC/f3+Fr5rIewxkFDYEQUBdXR3KysocjoS6cuWKTx1prtaJSUfSxClPrXSkBZqapycDzdeQJt1hqvdOMV95uo9u3LiBRYsW4dChQ/jjH/+Ip556SrevKdIvBjIKa950pIk7O8WOtJs3byIvLw/Tp0/HkCFD7OdOeurL0mqRrS+kU29amp4MNE8hTSoqKgqRkZEMYxLyjQ3y3jWbzYa3334bS5YswY9//GOsW7cOPXv2VPCKiXzHQEYkI+1Ik4a0e/fuITExEbdu3QIArF271n7USridNuAKj4TyTH4fyae5ld7dqRauqixEFy9eRE5ODmpqavDGG2/g0Ucf5fOMNI2BjMgLu3fvxuzZs1FdXY2xY8fi/vvvx9GjRx060kwmE4xGo18dadKQJk53Sl+iYu2GGs9vlE/hcuqtPVedYmrZ3akGnqosrFYrNm/ejLVr1+LFF19Ebm4uYmJiFLxiosBgICPyYNeuXZgyZQomTpyI119/HRkZGfZ1YtXV1Q4jadKONOmRUL52pAGhK7L1lXxnoPTsSfqWdFQMgFedYuEY0jxVWZw+fRpZWVmIiIhAcXExDAaDar6QEPmLgYzIA6vVir179+LJJ5/0ap1YsDvSAHWENPnUG3cGOhfITjF5SBNHUUVaDWnSUO+syqKxsRGrV6/Gn//8ZyxduhRz5sxhHQjpDgMZURB56kgTA5rRaERmZqZfHWmePqidTXf6isWlnoWqU0z62EuLjEVqD2mtra1uqywOHTqEnJwcDBw4EEVFRRgyZIjCV0wUHAxkRCEmdqRVVFQ41G+cP38eKSkpDiNp/nSkeSqy9aUjTXqAM4tLnVNDp5g3JcZKhzRPVRZ3797FsmXL8P777+O1117Ds88+q6ogSRRoDGREKiAIAr755huUl5c7THdeuXIFaWlpDkW2aWlpPp9p6GtI4/Skd9TcKaaWkCY+lxobG51WogiCgF27dmH+/PmYOHEiNm7ciO985zsBvw4itWEgI1IpsSNNnOosLS1FWVkZbty4gZEjR9pH0qQdacEKaeK0mN7LXX2l5WOhQhnS5FPd0dHRDvfRF198gfnz56OiogKbN2/Gj370I9Xfh0SBwkBGpCGCIODatWv2qU6xI62+vh4ZGRkOIW3w4ME+12KI025NTU0O3WgiLXakBYt0Z6CzviytCUZI81Rl0dbWhq1bt+KVV17BM888g1dffRVxcXFBu41at3PnTuzfvx/x8fGor6/HlClTsGPHDuTn5yt9aeQHBjIijbPZbLh69SpOnDjhMJLma0eatB0dgH16EoDuimz94apTTI/8CWnuqiwA4Ny5c8jJycGdO3dQXFyMsWPH6vp546/i4mKUl5ejsLDQ/rMpU6YgNTUVa9asUfDKyF8MZEQ6I+1Ik4a0iooKxMTEuO1IO3z4MGprazFp0iSvdk96e9qAuMNTTUW2vvKlU0yPvAlp4t9z1k/X0tKCjRs3Ij8/H3PmzMHixYvRtWvXkN8OLamrq8PgwYNx9epVREVF2X9eVFSEgQMH4oknnlDw6shfDGREYUAMTmfPnnXY2Sl2pA0fPhzNzc04dOgQHnvsMezcudPn3ZMd7UjTUkhj3Yd7YkhraWlBS0uLw5/t3bsXy5YtQ2ZmJpKTk/HBBx8gISEBf/nLX5Cenq6Z54CSTpw4gXHjxuHq1atISEiw/3z37t145JFH0L17dwWvjvzFQEYUpgRBQH19PXJzc1FYWIiIiAhMmDAB+/fvD2hHGqCOIlt/hKpTTOuk07jiLtOIiAjYbDacPHkSf/vb33DixAlUVVXZRxiTk5NhMplgNpvx7LPPol+/fgrfCvW6e/cuHnjgAcTFxeH555/Ho48+iu9973sMszrBQEYUptra2jBmzBiUl5dj5syZWLlyJeLj40PWkebtsUDS6c5Qk3eK8bB05zxN4wqCgE8++QRz5szBiBEjsGnTJrS0tNg3pYj/HD16FOnp6UreFNU7cOAAcnNzcezYMVitVowePRoHDx7kdK8OMJARhbGtW7ciMzMTmZmZLv+Oq460mpoaDB8+PKAdaWIAClSRrT/U3CmmJp6mcW/duoXFixdj//79eP311/Gzn/3M6f1os9k0NX2ttPr6euzYsQO/+c1vsGXLFjz33HNKXxL5iYGMiDpMTR1pgQ5p0l2mWuoUCzVn3WvSRfs2mw3bt2/H7373Ozz55JNYv349evXqpeAVa9vHH38Ms9mMnj17Ovz8Bz/4AZ544gnMnTtXoSujQGEgI6KAkHekiSNpDQ0NAe9IC1ZI01unWLB4up8uX76MOXPm4MKFCygsLMTjjz/O+9FPM2fOxOrVq9GjRw/7zwRBQGpqKt577z0MHz5cwaujQGAgI6KgsdlsqKmpQUlJib3IVtqRJq5HM5lMSEpK8nlKUBrSxCnPjnSkhVOnmD/kmxtiYmIc7ier1YqioiK8+uqreOGFF7BixQp069ZNwSvWj9TUVMycOROzZ8+2/2z16tX46quvsHbtWgWvjAKFgYyIQsZTR5q4Hk0MadKONF9+lzcdaeKCdAD2aTeO5rQnnj/p7CxTQRBw5swZZGVlwWq1ori4GGazmfdjgFy/fh0bN25Eeno6Dh48iO7du+Orr76C2WxGVlaW0pdHAcJARkSKcteR1qdPH2RmZsJkMtmDWnx8fEBCmtVqhdVqdfjzcDttwBvyKgv5WaZNTU1Yu3YtioqKsHjxYsyfP99hLRkReYeBjIhUR1xYX1lZaZ/qLC0tRVVVld8dafJpN3H9k3S6U/q2KNZuaLHI1h/eVFkcOXIE2dnZ6NevH4qKijB06FAlL5lI0xjIiEgTBEHwqiPNZDJh5MiRThfknzt3Dn379vXYKab1Ilt/SSs/nFVZfP3111i2bBl27tyJNWvW4IUXXtDdfUAUagxkRKRZ8o40MaTV1NQgLS3NHtL69++PwsJCHDp0CMePH8fgwYM7HCDCIaQ5q/yQTj8KgoAPP/wQ8+bNw9ixY5Gfn89mfaIAYSAjIl0RBAG3b9+GxWLBsWPH8O6776Kqqgo9e/bEmDFj7FOegehIk69Jkx+u7Wy6U62kBa/Oqixqa2uxYMEClJSUoKCgAFOmTFH17SHSGh7GRkS6EhERgd69eyMuLg7vvvsuzp49i5ycHGRlZdk3DuzatQu5ubloaGiwn1RgMplgNBq97kgT/06nTp3so0jOOtLEHZxA6E8b8IZ8TV23bt0czum02WzYtm0bli5diqeffhqVlZUOXVhEFBgMZESkS9XV1YiNjUVpaSkMBgMA4MEHH8TkyZMBtO9Ie+uttzBv3jy/OtKkU5ciNYc0acGrszV158+fR05ODq5fv4733nsP48ePVzxAEukVpyyJSJfEKUVv13K560jr1q2bPaSJ53b625HmzWkD4pRnoOs3PBXhtra2Ij8/Hxs2bEB2djZefvllREdHB+z3E1F7DGRERC5IO9Kkx0GdOnUKffr0cRhJMxgMAetIc1dk609HmrTKQhCEdkW4giCgvLwcWVlZiI6ORlFREUaNGsVRMaIQYCAjIuoAcSfi6dOn7aNoFosFVVVVGDBgQLuQ1q1bN1WENGmVRefOnREdHe0welhfX4+8vDxs27YNy5cvR3Z2No+PIgohBjIiIj9JO9KkI2kXLlxASkqKw1Snq460jvwub0KaON0JwD4q5qrKYv/+/cjJyUFqaioKCwuRnJzs1/1BRB3HQEZEFATedqQZjUakpaX5dYamu440UadOnWCz2fDNN9/YNyncvn0bS5Yswd69e7Fx40b8/Oc/12R/GpEeMJAREYWItCNNPBLKYrHg5s2bGDlypMNImr8daWKVhVjNYbPZsG/fPvzyl79EQkIChg0bhrKyMjz00EPYtGkT0tLSgnCLichbDGRERAoSBAHXrl2zj6KJIc3XjjRXVRZiGPzoo4/w/vvv48KFC7h27Rrq6uoAAAMGDIDZbMaCBQswduzYUN18Ivp/DGRERCojdqRJ6zfKy8sdOtLEkCZOP969excrVqzAjBkzMGDAgHZVFm1tbdiyZQtWrVqF559/HitXrkRsbCwuXrxo/x2lpaXIzc3FxIkTlbvxRGGKgYyISOXE3rLPP//cYSStoqICMTExSEpKwtWrV9HY2IjNmzdj6tSp9rVggiDg7NmzyM7ORkNDA7Zs2YKHHnqIVRZEKsNARuSlNWvWYPv27Thz5gyOHDkCs9nc7u8cOXIEjz32GMaMGYPx48cjLy9PgSulcCAIAi5fvozp06fjX//6F9LT09GnTx8cO3bM3pE2atQoXLx4ER9++CEWLFiA3/72t4iMjFT60onICR6dROSlxYsXo76+HpGRkTh//ny7QGa1WrFv3z60tLTg7bffRlJSkkJXSuHgwoULMJvNiImJwY4dOzB16lQAcOhI27dvHw4fPoxjx44hNTVV4SsmIncYyIg6QBAEDBo0CBcvXmz3Z//4xz+QkJCA5ORkhjEKupSUFCxfvhy/+tWvHA77joqKgtlshtlsxosvvqjgFRJRRzCQEXnp1q1bSExMRFtbW7tA9uWXXyI+Ph6ffvopHnnkEYWukMJJREQE5s6dq/RlEFGAsAGQyEuHDx/GuHHjnI6Q7dmzB48//jgOHz6M8ePHK3SFRESkVQxkRF46deoUMjIyMHDgQIdA9u9//xsTJkzArVu3cO7cOQYyIiLqMAYyIi+1tbWhU6dOGDRoEGpqauyHTF+6dAkpKSn47LPP0Lt3bwwdOlTpSyUiIo3hGjIiL9TX1yM2NhYAMHDgQLS1teHKlSv47LPP8NOf/hTAtyNlHB0jIiJfcISMyAvHjx/Hd7/7XQDf7mLr168fDhw4gN69e6Nr164AwPVjRETkMwYyIi98+umnGD16tP3/JycnY+/evZg0aRIAoKGhAeXl5Rg3bpxSl0hERBrGQEbkxpkzZzBt2jS89tprmDZtGi5dugQAMBgMWLVqFYBvG/ynTp0Kq9WKgoICHDp0SMErJiIiLeLRSUREREQK4wgZERERkcIYyIiIiIgUxkBGREREpDAGMiIiIiKFMZARERERKYyBjIiIiEhhDGRERERECmMgIyIiIlIYAxkRERGRwhjIiIiIiBTGQEZERESkMAYyIiIiIoUxkBEREREpjIGMiIiISGEMZEREREQKYyAjIiIiUhgDGREREZHCGMiIiIiIFMZARkRERKQwBjIiIiIihTGQERERESmMgYyIiIhIYf8H01aOn0/BCW0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb41d8ea250>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.30877001457821573>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código realiza una gráfica para cada valor de R entre 1 y 100.\n",
+    "x = y = linspace(2.0, 40, 40)\n",
+    "zs = zeros(0,40)\n",
+    "x0= 10.0\n",
+    "@gif for i in linspace(1,100,100) #Se genera el .gif con 100 imágenes. \n",
+    "    G(x,y) = (i*(x0)^2)/((((i-1.0)*(x0^2))/x + y + x0))-x0\n",
+    "    title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0, 50)),yaxis=(L\"S\",(-1.0, 50)),title=\"Puntos fijos del mapeo para distintas R\")\n",
+    "        \n",
+    " end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Distintas R](Figures/R.gif)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Finalmente, observemos la evolución de los puntos fijos para un valor distinto de $S$ en cada gráfica que se encuentra en\n",
+    "función de $M$ y $R$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Jk517Y8WKFfjMZz6DTZs2ORa9v/71rzW3nZl4sCBjQsUbcF0vxx9/PN566y3HogHYrjuJ+5v1tGnTAADnn38+3nzzTTzwwAM4++yzkc1mceGFFwbarmI0uo3SIuWHWbNmOZ/31FNPOT8vvvgiXnvtNSxfvtz3ewXF7t27sXr1anzkIx/B9u3bcdNNN+HBBx/0/XpZlgSwLX8zZ84EYFtdNmzY4PRx8+bNeP3113HZZZc54w1UvibV4m1PLf1TVXXcYw899BD23ntvXHjhhXj3u9+Nxx57DGeffbbvdlUzT4qRSqVw880349VXX8WPf/xjrF27Fi+88AKuvfbaos+///778V//9V91fWY5zj//fPzxj38EAFx55ZXYf//9cfPNN+OMM87A008/jQMOOGDM84UQuOqqq/DGG2/gnnvuwXHHHYcdO3bgK1/5SsXPGhwcxNatW8e93z//8z8DqE9MMhMPFmRMXVSTyl5sMyn2DbKa94zH4wDgHFH00EMPwTAM7LPPPo5batu2bc7z5d/d3d045JBD8NWvfhVnnnkmUqkU1qxZg2uuuQZHHnkkRkZGKn52qXb6bX+j23jIIYegs7MTRITXXnut7HNlkc+33357jBABgG9+85t49dVXffXJD37H53vf+x4ef/xxdHd342c/+xmWL19eUcC7LVkyS07TNBx11FE45JBDMGPGDBDRmPEGgKeffho/+tGPcOihhzpjVuya7L333o6L0w/F2jN58mQccsghNfWvGBdeeCGGh4dx6qmn4qKLLhpjtfHDUUcdBQAV50i5199xxx2YMWMGPvzhD2Pjxo3o6upy5qe8RwE7luvll1+uaH2qZw14/PHHMTw8jJGREedLy9e+9jUcd9xxSKVSME1zzOvPPPNMfPWrX0VPTw/WrVuHO+64A/vuu6+vNQBAUWukDKs47LDDfPeDYViQMXVBRFXFmhCRU/Lh/vvvdwLW3XFhld7P/f8HHXQQAOC5557D22+/DSGEY+255pproKoqbrvtNgwNDaFQKODGG2+EEAJXXnklUqkU8vk8br31Vsf9NzIygldeecWXa6xUO6sJgG9kG1OpFP7jP/4DAPDtb3/bCfq+9dZbnXbKcT/mmGPwkY98BIVCAf/5n//pvMf3v/99fOMb3xiXQFBtkL/7+W6XbLH3kY9J60KhUMBbb70FIsI3vvENKIoCIhpzTqh83Q033ADDMJDP53HDDTdACIGLLroIs2bNQiKRwPXXXw9VVXHttddiYGAAgC22TjzxREyePBnpdNqx3txwww3Qdd05kUHTNHzjG9+oqs8bNmwAALzzzjv47ne/CyEErr76asTj8Zr6V2y85PtI0bx9+3b86Ec/AoBx71GMc889FwsXLsTmzZud+/Gvf/2rM99KxWzKtuTzeVx88cWOC/7FF19ENpt1Yr+WLVvmuKa3bt2KP/7xjzjwwANLvp/770pzBNizBmzduhWFQgHbtm1DX18fFEVBV1cXiAivvPIKAOA3v/kNnnrqqTFjk8/ncfXVV2PLli0AgLfeegu7du3y7R7fsGGDU/QZsK/1TTfdhNWrV+Poo4/29R4MA4DLXjDVcdddd9Hy5ctp8uTJpCgKKYpCixYtouXLlztp46X4y1/+QmvXrqUZM2bQfvvtR2vWrKHTTjvNSYlfsGABXXTRRbRw4ULnvZcvX04bNmyg5cuXO+fDzZ07l0499VQisktJfOITn6AZM2bQ3nvvPS7N/5FHHqG1a9fS/PnzaeHChbR69eoxZ95dccUV9OEPf5jWr19P/f39tN9++9G5555LuVyubF82bNhAS5YsGdPOU045Zdzj/f399Pvf/955XbEzJBvVRsltt91GK1eupMWLF9MhhxzilAJQFIW6u7vp2muvJSK7fMTXvvY1Wr58Oe21117U399PZ511Fu3YsYOI7PICc+fOJUVRqKOjg/r7++n1118v+blHHnkkzZgxgxRFoc7OTudausdn6dKlzvXt6OggRVFoxowZtG7dOmec3/Wud9HMmTNp2bJldOmll9Lll19OHR0dNG3aNOd6y3IDJ598Mh100EE0f/58OuCAA5xyEm5+85vf0Pr162nWrFm0bNky+sAHPjCm1AYR0Y9//GM69NBDacGCBTR//nw68sgjfZ/N+tJLLzntOeuss+iAAw6gOXPm0OrVq+nuu+8e89xK/ZP3mxyvJUuWOGMjefPNN+mTn/wkzZs3jxYtWkTvfe976b777qP3vve9pKoqrVy5kkzTLNvm7du304knnkhz586lAw88kD760Y/SUUcd5cyThQsX0u9//3tatmyZcx8uWrSINmzYQB/60Ifok5/8JB188MHU399P/f39dN111415/3vvvZdWrVpFvb29dOyxx5JlWUQ0dk7VOkcsy6LPfe5zNHv2bJo/f/6YcjBPPvkkHXPMMTR9+nRasmQJ/cM//ANt3LiRFixYQMlkks444wz6t3/7NzrxxBPp/e9/P/X391NfXx9deumlThvLMXfuXPre975Hn/70p6m/v5/2339/WrhwIZ155pm0e/fuiq9nGDeCiEucM0yjyGQy2Lp1K1auXAnALokghMDLL7/sO4uLqYwc14ceeih0N9HLL7+MRYsWQQiBl156CfPnzw+1PQzDtAbssmSYBvJP//RPeNe73oUNGzY4Qd2KomDq1Kkht4xpFHyGIcMwtcCCjGEayO7duwHYpQVkra+TTz65YrkHpnqoinjGRrdD/o5CexiGaQ1YkDFMA7nuuuuwevVq3HHHHbj44otx0UUXVVUjiinPT3/6U/T390MIASEETjnlFHzpS18KrT3XXXcd1q1b57TnqKOOwje/+c3Q2sMwTOvAMWQMwzAMwzAhwxYyhmEYhmGYkGFBxjAMwzAMEzIsyBiGYRiGYUKGBRnDMAzDMEzIsCBjGIZhGIYJGRZkDMMwDMMwIcOCjGEYhmEYJmRYkDEMwzAMw4QMCzKGYRiGYZiQYUHGMAzDMAwTMizIGIZhGIZhQoYFGcMwDMMwTMiwIGMYhmEYhgkZFmQMwzAMwzAhw4KMYRiGYRgmZFiQMQzDMAzDhAwLMoZhGIZhmJBhQcYwDMMwDBMyLMgYhmEYhmFChgUZwzAMwzBMyLAgYxiGYRiGCRkWZAzDMAzDMCHDgoxhGIZhGCZkWJAxDMMwDMOEDAsyhmEYhmGYkNHCbgDDMM2FiGBZFnRdh6Iozo8QAkKIsJvHMAwzIWFBxjATBCKCaZrOTzabhaLYRnIhBBRFgaqqUFWVhRrDMEyTEUREYTeCYZjGIYVYJpOBEAKaZn8PKxQKjtAiojE/lmXBNE3E43FHqLl/u8UawzAMUz9sIWOYNkWKKtM0YVkWstksYrEY4vE4LMsCAEdQeYVVoVCAZVkQQoCIoOs63N/dpNWsmEWNrWoMwzDVw4KMYdoIaeEyDAOmaYKIHHdkNQJJPrfY69yWNMMwoOv6mOew+5NhGKZ6WJAxTBvgdjPWI8T8UEpUSQuauy3yMfkaaVVj9yfDMMxYWJAxTAsjxY9hGLAsC0QUmiWqlPvTLdTY/ckwDFMcFmQM04LIQH3DMMZYoWTWZL0EKYBKCTWA3Z8MwzASFmQM00J4A/XdrsBKyAD9apCuz0bB7k+GYRgbFmQME3GCCtRvJapxf7ofZ/cnwzCtCgsyhoko3kB9SVBCrBWFST3uT0ksFoOmaSzUGIaJFCzIGCZilArUB+oTUV6Xpduq1A5Ucn/quo5CoQAiQqFQGPMadn8yDBM2LMgYJiI0OlB/ouKuqQbAEVzs/mQYJkqwIGOYkCklxMLc7CeC0ODsT4ZhogQLMoYJCbdbstqMyVoQQjhHJvlloh51G0T2ZymrGsMwTDFYkDFME2l0oL5fWBjURjXZn+4CuOz+ZBimEizIGKYJNCpQvx5YAAQHuz8ZhqkXFmQM00Dc8WHDw8NQVRWpVCqUQP1aCsO2I2EcKcXuT4ZhKsGCjGEaQLFAfdM0I7WRNroKP1OeIN2fqqqOKRbM15VhWg8WZAwTIOWONorKJmkYBrLZrOM681peoiQaJyLVuj/l37FYzLl+7P5kmNaDBRnD1EkrHG3kdosNDQ1BURTEYjEAe7I9i7kzC4XCmI2dN/VwKTb+Mi5RVVUAYPcnw7QoLMgYpka8GZMyUL+UaAkjhktWpc/lck5WZ0dHB2KxmFMIVbZV9kf2SW707mxQACUtaryph0O52nWl3J/yMbeF1C3W3I8zDNMcWJAxTJXI+DDplqwkxMKAiJDP55HL5WBZFjRNQywWg2EYSCQSRYWh24KiqqrzXFVVx4g1+WMYxpjXFxNpbH0JF87+ZJjWgQUZw/ik3qONmmEhsyzLEWJEhHg8jmQyCU3TkMlkxli7/LZHbr7efsrN3CvU3O4y+XqOU4se5bI/5fVj9yfDNA8WZAxTgXKB+lHBsizkcjnkcjkAQCKRQDKZdOKKgOoEoZ++lRJqAEpa1FioNY6gxs1PmY5q3Z8yC5RhmNKwIGOYIjQiUL+Wo4sqYZomstksCoUChBBIJpNIJpOhx/64LShu/Ag1gOPUogi7PxmmsbAgYxgXUTnaqBLe0hWpVArJZDLwNgbtYq0k1LyCrVKcGm/o0ThvlN2fDFM/LMgYBs052qjeGDLpJsrlcjAMA4qioKOjA/F43LeLMQqbdzHkpuylVJxaKaHmdYPyhh4utbo/3UJbVVVomsbXlWl7WJAxE5p6A/Wbgbd0haqq6OzsRCwWa/uNyW9CQbHjh+Tr5SbuFgHtPm5Rx6/7s1AoONm+7tew+5NpR1iQMRMSb/0woPS3+aCo1kLlLV0Ri8WQTqehadqE33TqSSjIZDJFLWmtvKG3YptL4b4GMmwgFoux+5Npe1iQMRMKt1syyhmTpUpX1IO7AKykHa1FpeLUdF1HPp9HIpHghIIWwm0Zq9b96X5dOasaw0QBFmRM2xOVQP1KFjLTNJHL5ZDP5wEUL13RLNpxk5J98loYq41Ti5pQi2pcYBD4rZPn/u19vTf70/sadn8yUYEFGdO2uAP1h4eHoSgKUqkUgGgJDsMwkMvlIle6AmjvzV5SbeFbr1DjemrRpVL2Z7HYQ3Z/MmHBgoxpO7yB+vLfQLhCzGshkxmTuq5DURSk0+kxwctMuPgRam7BxoVvG0Mjxovdn0wUYUHGtA3lMiajtFDKjEnDMKCqalWlK+rBHUMWpfFoNepJKJCvL1amg11k42m2hZbdn0yYsCBjWh4/RxuFXYNLLuIAMDw8DE3TJkzpiolEpcK37jIdcr66qTVOrZ3nUFT6xu5PptGwIGNaklqONgpDkHlLVwBAV1cXYrFY09viZqJv8s2mnFCrJaEgipbfRtAKMYz1uD9lEdxYLMbuT4YFGdNaeDMmvVW9S9FsC5k87DufzzulK1RVRTabrbt8Ra0UK3vBhEu1CQXFCt/K58tYRN7Mo4Ef92ehUHCuq/c17P6ceLAgY1oC6eKRbh6/QkzSLEFWrnRFoVAA0FoxXCzewqGaODVpTZNzTr6+XRIKWrHNlXC7MqWFDGD350SHBRkTaVrhaCNgfOmKVCqFRCIRuXa64cW7NfG6P+XmnUqlKiYUANGtp1aMVvryUgvea1Nv9qcUaez+bE1YkDGRxE+gfjU0wkImY9j8lq4I22Xo/Xy2frUPXsuJm2IlOlqp8G2749fCX+q5bquarutjvrjK3+z+bA1YkDGRoZZAfb8EKcjkwpfNZp3DvptVuoJhqkUKNS/VJhR43aDNmuvtfE8FYQH0k/1Z6txedn9GCxZkTOhE5WijSsgg3Gw2C8uyqi5dEbaFTOLuBxGVdG9EaeyZ0tQ6n/wmFBSLZ5Kvb3ScWtj3SjNo1H3G7s/WgwUZExruo43cgfpA8ItUPRYyIkIul3MO+47FYujs7AwtW7JeRkZGYFmWs7gWK1wqhHDKdBiGwe6NCUQ1CQV+TihwW7l5/owlDMHJ7s/o0po7CtPShBGo77ZO+V00ipWuSKVSNR/2HZaFzG0Rk+3o6uoCYGeFKopS0n0lx0DCcUYTm0pfQQhfAAAgAElEQVRxakEnFEyEoP4o9Y/dn+HCgoxpGt76YYC/AqXNxlu6IkqHfVeDtyitpmmwLAvpdBqxWGxMrFAxq0gmk4EQAolEourCpSzUmkvY41xOqNVS+JY38WhRj/tThkVomsbuzwqwIGMaSqlA/WZv1n4sZI0uXdEsC5llWY4Qk5a9ZDIJIQQGBwer+ny3+8lNvRstL8QTA79xaqXmDwDH0tZuG7nXHdiK+HF/5nI5KIrihHjI527YsAGTJk3C2Wef3bwGRxwWZExDkIttoVBwMhGB8AP1vWJEisVsNuvESpUrXRFlvC5Wd1Fa+f9u6ulfvRstC7XgiJrbyw9+50+hUHDu0WYnFDSLVmyzH9z3c7Hit1u3bkVfX1+YTYwcLMiYQPEG6g8PD0MIgc7OzlAXHu9ny7iqXC7XtNIVjbKQNcrFWss4sFBj6sE9f+Q9Go/HEYvFqkooKJZYELU5NBEySIHxXxjktRgcHMTkyZNDbFn0YEHGBEKpQP2olFCQn29ZFnRdHxNX1dXVBU3TQm9jtZimiWw2W7OLVYqkZhC0UHNvvEx7415D/CQUuL8Uuomq2A/78xtJObfswMAAJk2a1OwmRRoWZExd+BFiXldZGMi2DQ8Pj4mrCqN0Rb0iyBvr5tfFWouFrtGCza9QK5bdJV/fLq4rZix+517QCQXNEvsTxUJWisHBQRZkHliQMTXhdkuWO9pIZtmEhYyrkqUbNE1DOp2uuXRFPdS7wEvLnp9jmlqdUkINqK0WlnSBtSvtOAfqpV6rbKPFfjsE9VeiVB+JCENDQ+yy9MCCjPFNqYzJcotUWILMHVclSzfk83kkEolQxFityFTyXC4HwzD4mCbUXwtLZn2xRS3aNEqwNELs8xwqTiWXJQuysbAgYypSqqK+n/iLZgsymTGp67oTV5VMJp2aXGHjdzykEHOfl1nNMU2lPlu+dztSSajpuu5YQdppk23X6xkG9Yr9auLUJoKFTFLMQjY4OIgpU6aE1KJowoKMKYk7bkeeMRmVQFg3XitSOXde1Dcvd1X9RicdRE1MNwq5yUrrrqzJxtaQ1iAKY11JqHnnkp+Egna4typRqo+7d++GZVnOiSGMDQsyZhzFAvVr3YTkxteIWknFSldUsiKFvQiWEjneqvqtfl5mK1CPNYSFWuMJ+171g5xDXqopfCvDKtpxHpWyAg4ODqK7u7ulwkeaAa/2jIP7aKNygfrV0IiFpZh4SafTZa1IUV3gSlXVb5QQcwtCP2PSCpti0NQr1IqJtUZblaM6vycqfhIKdF13YnHbNXu41FojS160Wn8aDQuyCU4tgfrV4I5bqvf96hUvUXDBuV1l5arqN7M9jD8a4baKmvs/irTT+LiFmvzim0qlANRmmXWv1VEdp1IB/T09PSG0JtqwIJugyJvfXdupEfV3gggk91air0e8hC3IpPgdGBgA0LoHlzN7qNdtVa9QC3tON4rG9ku+d3SKwjYzoaBZlLqGsgZZVEVkWLAgm2DUkzFZ7+dWi7cAar3iJcybX1bVl0Vygz64vBradQOPGvXWwYriBtvakOt3+F+Awip828x5VMozwlX6i8OCbIJQqqJ+owVBLTd9owqghuGy9IpKRVGgqqrjpmg21Yxhu238URGiQQs1+dp2I7iyEDpiiedgmr8e86hlfLLO962PesM46p1HzYhTK9VHrtJfHBZkbY7XLQmgqd+y/bos260AailROTw8HHbTmIhSzwYrA8TZouaGoGqvgnA3Rqv2jEHRrgtdlDUCP/PIPZ8anUHMgsw/LMjakFKB+mEszpUEmbd0haZpdRdALdeWRloS2k1UAu1peWk1Km2wmUwGqqpCCBGpsxqDoGYRoAxBKLej3OwNW4zJcJFmUWoeybb4TSgollhQrsxQKZdlb29vcJ1rE1iQtRHypioUCk5dLqD2GmJBUEqQlSpdEYvFGtqWRgiMaqrqy00zLKKQacoEg3tuaZrm3DulLGqtVlqhtnmqQ4tvGXVPFu9H2ELMTVTG2m9CgTsG2U2peVTOZbl06dKG9qkVYUHWBngD9aVbrKurKzI3vFxcveUeGl13q5E0s6o+w/glKEtIVIVacQiq9jos+glMExBifN+jJMSA1rA+15tQANgJTYVCAYODg3jjjTewzz77cFB/CVpvF2QcygXqy8KuYSPbYFkWRkZGAildUU9bgrBO1VNVPyoWKnnmpzxqqrU2X6ZW6i162+y54ue9hRgG4WaYFkEIddxroibE3LTqfeY33rFQKDhfXO+55x586lOfgqqq6O3txa5du/Dcc89hv/32w3777YelS5dO+KOUWJC1IKWEmLy5o7LpA3C+MeVyOQghQi33UO+4NLuqfqMoFArI5/NOxqeMN/RuvsAedywLtfYmikKt8r1qQlG3wLJ+CUBAUcbeh1EWYkBrWMiqxS3UpBCLx+OIxWI45phjsGjRImzZsgW33XYbiAi33347XnnlFef1Dz74INasWRNiD8KltXaSCY7bLVnuaKOwBZnc4GWWIQDHndeKG3pUqurXirweMsZNCIGOjg5omuaILfm8Yu4HadUEWtWd1f40avyjKNQAQFHfgqXfDgsalCJfiFpFjLXzfePtY09PD973vvdh9erVuPrqq7Fx40asWLECw8PD2LJlC5599lmsWLEizCaHDguyiOPNmJSUW9jCEmTFgts7OjqQzWadLLAwqXZcvCcEBFFVv5nXpljWp7SKJRKJce5b7+YrhEChUEBHR0ck3VlMeDRLqI17TOQA8zpYlgCU8WIs6kJsIlFOdA4ODmLKlCkAgM7OThx44IE48MADm9q+KMKCLKKUqqgPVP5WJTf9egsPVtNWb3C7O8tQuviigJ92yKr6sphrmG7WWiiX9VlLHbSoWkmY6Lm96p0r8vXueE8igqBhwPwDoPwBEAJKPDHm/VtNiE0EC5nE20dd1zE8PIzJkyeH1KLowoIsYsj4MHnwrBRi1YiBZt3kRIRcLucIrlLB7VFZdCq1w1tVP5VKIZlMBtr+RlrIvEKs0VmfLNQYv1SaK+45I9c++wkmjMwvENPvB5Q0xOS9xswR8dqjMHtvb2ZXGJ+UWueGhoaQSCSQTqeb3KLow4IsIgR5tJE7ILsRG1yx0hWpVKpkTFXYMW2V2tGoo5qaRanyG42s6VYOFmqMX+Rc8UJEyI08g1T+GiA+CdA6ILrn7Elceu1R57nqmx8v+t5RFmoTwUJWqo8DAwPo6ekJo0mRhwVZyLiPNioXqF8NpYqx1kutMVVhF0P1IscljKr6QYpTrxDzW37DK4BKCfegx4GFWuNoq3Gw3oGy8zyktMlAfCpEdy+EZltT3EKsEsWEWtREWltdNw+VBFk7971WWJCFQKmjjYLaYIIWZMVcedXEVEXJQgZgzFFN5arqR5Ug66A1K86wHPUItVIiLew+MTVAOlB4ABi6CxTvheicDMTtjbsaIVaKwY7roWQykZgvUVgPm0GpgP5JkybxPVoEFmRNRG4w7sO+gxRikiAEmbtUgiweWo8rL+wFSPYHAEZGRkKrql+PO1kKsWw229Q6aGGJNr9CTbr63RQTamHPwUbQNn0y/gLs/E8gMQ1IzoDo6YVQ1ECEmD79NliWhXiZivJhCft2FiWl5uY777zDLssSsCBrAqUyJht1w9cjyKQbzG1BqteVF+ai47UmAXaadTweD61N1eJNnqgUs9fulBJqXmtaqaNccrmcUwKELWohY+0E3jwPUDuB1DyI7mkQWhJAde7JUpi9t0MBKlaU9yvUgvoC3TZCugylvsgNDg5yhmUJWJA1kCAD9auhFkHmFS5BWpDCcFkWq6qvaRoymUyoQqYaC5m3D0EUpHVfi3YTIcWykd0br67rjmW6UCgUfW3YrqwJg3RP7vw+kJ4JdE2HiHcG5p6sFCsmr61fodaog9nbeX6VE2RsISsOC7IG4HVLAmjq4l6NIGvGcUDNFGTlqurLb79R/3ZarA+pVKohQr6dNwRg/FEupmkilUoBKB2j5qZVhFrU2lMWYzPw1leA+DRg0kKIrmkQIhj3JFBf4H4poQYEm3wS9TUoKIrNy4GBAbaQlYAFWUCUCtQPa/GuJILkpp/L5QA09rDvRpfhABpTVb8RlBPL3msSdh9aapOvkmotJK0q1CKFuRPYfg6gpoDuRbYQUxOREGJ+CDJL2H3qSrtSar0fGhrC3nvvHUKLog8LsjrxBupLwk7JLyXI3MJFCNGUTb+RgqyaqvqNKgdSL5ZlIZvNNuWaRCXjNaq0mlBriWtp6VDevhrW2/cBvf3AlPkQ8TSU1x8L5O3DLmVRj1AbGRlp23Iupdb7gYEBTJo0KYQWRR8WZDXiDtQfGRkBAKfycBRuJu/GKzMmdV13hEvQVeibST1V9cPcxNyi0CuOo3pEUxRKY4RNqwm1qCCG7gW9eBmsrpnAjP2gWEMQO54K7P3DFmPlKCfU3LG67Vp3j4P6q4cFWZUUC9SX2XtRulmEsIuxyozJIEpX1NMWIBghVE9V/Shdn3YSxxOZRgi1qAnymsi/BPHcSSAlDvQuA+JxqMZAYG8fZSFWCfecSST2nMnZTgWSyyUOsYWsNCzIqkBmZ7kFmPyJWiV6Gc+m63roxU/rFWREFEhV/bBdloZhIJPJOH+HJY5bws3V4gQh1NylOaK46RbFzEJ95XKYOx8ETV0E9MyCYgxCBCTGWlmIuSl2DwYVo+b9O0rzhogwODiIKVOmhN2USMKCrArcAsw9yaOyyXlLVwghnAruYcezyfZVgxRi8rDssIVlrXjdxQAcQclMLKoRaqZpQtf1Ma8tVew29PuBCMrAXaDnL4XZPQuYeyAQ06AW3gzsI9pFjEn8XrNKQs09b8YczD5KGO7ycvNSVupnxsOCrEqKTeSwLWTFSlfImzSsA6bdVCvIpCXSe1h2vcKy2RYytxBTFAUdHR1QVRVDQ0NN+fx6CX2Tn0CUE2qVrCOA7QIPy6Imslsh/vTPsOIdwKzlwORZELldUHS2ipUiiLhMKdSKvXfYcY2lBJm0kLEgKw4LsiopNlnDOpbFW+rBXboik8lELrW60hh5LXzVnNHol2ZYM6VVT8btud2rUXBte10dUbDuMsWpZB3RdR2GYUAI0fx4I3MY2ouXwXjnAdDkBcCMBQAI6shrAIKZU4Vpt6Jdz6NolGCOUgKK9zUyI54FWXFYkAVAM+psufFmGBYrkxCljbbSmDSjOG2jkTF7UohF1b1aS1uiMo+YPUihJjdUmRTSlMBwsqDu+jHo2Yth9MwE5r4L6JkGkdsJxcgE0r/CtFuRzWaRCuTdokcY91QzhVqp/g0MDKCrqysSnpso0jo7XoRpliCrJsMwioLM255yVfUb2ZYgx6XaOLewEwvcSBEJAKqqRko4MrURVGB4KaEmRv4C9enjYCTSwJz9gGkLAVi2VYyCsf6avbeDRudlu87JKJWSaYRQK1V5YGBgAD09PZHpe9RgQVYlzd5ka80wbLbVrhJuIRRmVf2gBJlXiGmaFkmLWCnkiQBuF6pclGUsUhREI+OPSnOuXqGmWkOY9MzhKECBMXU+MHMREO+CyA9A0XcH0od2jBVrZeoVagCQz+ehKAoef/xxTJs2DTt27OBzLMvAgiwAGiHIZGB7LperacOPoiAzTRPDw8O+qupHlWLXpZqEgzAtZG6LWCaTQSwWQyKRGLfA6ro+pn25XK5owHgU5hVTHxWFmqkj9vp3oP7pP5Cf3AuaNheYsy8gBJSR1yEomDjVUmKsHedYZDJja8SPUNN13cn4NE0Tp59+OrZv3w5N09DR0YGPfvSj6Ovrc36WLFkypibbRIUFWZWUCuoHMMbaUCvFAtvT6XTVPvcoucYMw3CK1EohFlYh1FotZN7Mz1qvSxh45xQAdHd3Q1VVR3x5r4VcSOU3XK4+H00adX8LIaANb4L26D/BSHbBnLcE6F0IdE2HMHZDyb8TyOeUEmJRWLcaTbvdJ26hJsWYPL3m0UcfxbPPPov77rsP9913H9555x1861vfwhtvvAEAOProo7Fx48Ywmx8JWJAFQBDixxtPVW9gexQEmTvmDYBjTQp7IapmTBqR+dms+D5v2+PxOFRVdUoklMP97Ve+ru2LmjI2+k4kHz4Yes6EMXUOaOZ8YMpcQItDZN6AYhWC+Zjpt0FExILfTCaC2PR+yZs+fTqmT5+OzZs34+CDD8btt9tCfNeuXXj22WdbKoGrkfAoVEm5xaOWG61c6Yp6CEuQlYp5y+VykdiY/X5+MTHTKpmfsu3ZbNYR96lUCqqqolAoOM/x69Z2u1iCLGoahfnAuCAT2otXA09djfy0XtD86bZ7MtkJYekQw69CBFDOYqjzBntOjZ5aUWxeTATR0s5zv9Sa4j3HcsqUKTj00EOb2bRIE/3dpQWQG1U1i0ixw7GDjKdqtiCrlG1YKBQischWqgVGRE7Au1fMBNmGRiWAlBJijaSeoqYs1KKB2PkwYg9/DEbHJND8RaB5i4HOyYCSBHK7oBgjdX+GdE92YM+ZwH6DwtvJJR6FdbAZFLtOAwMDfLB4GViQBYSfTVYGVdd6OHa17ZGf2Uj8VtWPSlHUUnhroTWjBEdQhCXEKlFPZh/Hp/mnrjHJvYXkLw6AkSfo0+eB5uwFTJkFqAlAUSAy26FY44VStXhjxYQQ46zNpYLC2zV2sdXaWw3lLGSLFi0KoUWtAQuyKil1E5UTHMWsR7Ucjl0LjRJk1cZWRaUumrcdrVwLrRYhFoXsW79CzTTNtt2Mg6LmeWRZ0J67FOKpb0KfPhXWrOmgvRYDsQ5ATQJGFkpmJ+od1WpKWbgtrXIOpNPpUCrMN5IorIONppwg4yr9pWFBVgPFNtRicQ/FrEfNqlVVixvVD61eVV+OiRRiuVwOQHNrodVLsyxizd7Iigm1WjdjLnRbGuXNnyP2qxNgJjthLpgLWrAPKDUZUGKAkgBy70Ct00VZb00xr1s76MKlYQq1Vi974QcWZLXRGrtoC+C2kHnjkBpxJqPfNgUlyOq1JEXFQiYX8IEB++DjsIRYraU3goxvi6L1wEs9m7E3Pi3KLvOmkHkdyXtWwjRjMKbPgjV3PjBtFkiJ2S5KKFAyb0JQ7S7KIIu7+il2205CrV0oJTiJaFxQPzMWFmQ1UExcSEGWyWTGlK4IM5YnCBEUVFX9sAVZmKcDeKl2wfcKsSDcqtWW/ogafjdj6fZ09yGTyUysRAKrAO3Pl0A8820YUyfB6ukBLd4PFE8BatwO3DfzUHK1uyiDrrJfz5yLulCbCBayUgwMDLCFrAwsyAJALvrSihQV91c9Isg0TWSz2cCyQMMSZN5+xGIx6LruFCwMCz9j0Qgh1u6bQLnNuFAoQNd1aJrmK+NTuj2jPmbl2qe8+jNoD58GK5GCNXcOaHIvaNYsUDw56qKMA4UhqPpwTZ/dSscdRUmoRX1O1UM5wTk4OIgpU6Y0u0ktAwuyGpATzV26QjJp0qTQhZikFhFUrBxHEFX1mx1MXkxQJpNJ5PP5ktXpm0Wlz22EEJvouDdidzJNu2Z8it0vIX73u2FCgzVtKqyeyaA580EdXYA6KsSECpHdAcXSK7+hh/i2zcge/HQDWr6HZo1vI4RauT0gihbnICklyEzTxNDQELssy8CCrAZ0Xcfw8DAMw3BKVxARstlspBbpakpNuKvqN7IcR6MxDAPZbLZkP6LcHxZizcdPxmeUyy+M29yNEWhPfRG0+bvQJ3cBPd3AtOmg3tkgLQFAtcUYWVAyO2oq9Gr23o5sbzDtL0UUREsQQq3UiRVRXoeCwtvHoaEhKIqCzs7OkFoUfViQ1YC0sLhLVxSrgB42lSxkshyHt6p+I8pxNNpCVkmIeQnbQuYWys0UYtXUp4vKPA4Dt1CT55XWYjGRG3LDx5IIyrYfQf3lv8FMJ4DZ00BTp0JMmwbqnGJbxaACWgIwclDzg1V/RDOsYq1ANUKt2IkV8rlyrWq3+MVSa4vMsGynvgYNC7IaSKfT40RLNRtdsyglyIrVRWt0OY5GjY/XsldJUEZpMSgmxFKpVGRc3sxYgsz4DHIjVnc/j/gP1sJQVBjTukDTpkDt7gJNnwuKxUGKBgjbMibyQ1CMbFXvL4VYo61iXqJ0r/qh3PwoNi9kgpF8bbskmpRyWQ4MDKCnp6cl+9QsWJDVQDG3RCsIMr9V9RvVFtmGeiEixyJWrWUvKtfJNE0MDAy0hBALe6yiTiWh5j4iKNCjo/RhpB/7FPDSRhS6UxA93VB7J4HSaViTZgJqDAQVELYgE7l3qooXi2/bDAChWMWi5GmoF69bXFrHk8lkWx4tVkqQsYWsMizIaqDYhIrKRu9GCjJZSNRvVf1GtQWob3yKuVibVWg3CGRRXeneDkOIRXGetit+LSblNmJ3DJLzRZAI6tabgF//O8y4CsycBDFjCtTOFKx4CtTTa4sxoQCKBkBA5HZBIX/xpGEKsYkAETnXs9ajxaIu1Iq1Q1rImNKwIAuIKG900hIThar6tRZEdbtY6znxIIzr5C2qq6oqLMtCR0dH09pQiqgs4BOJajZiGa8qiQ1uRue9H4KuAOhJA9MmQZvWCYolbTHWPRVQNRCELcYsC0ph0Fd9MSnEgPDFWDtZyIpRrm+tLtRKra1cg6wyLMhqoJyFLArVwL3HAsVisdAPm65lQZAu1lwu5wixel2szRRkxU43SKVS40qlMAxQeiO2LAtWfgiJh06H+erDKHTEISZ3Q53ZDZGMg9QEKJ4GdY2KMaHYbkqzAFWvfARSlITYRKDWtadVhBofm1Q7LMgCQroTolSNXhZBDVuMAdUJIW+sWywWQzqddrLdoo5XiHkLBYc5T7zXwW/MHRMSRNA2Xwc89mUYmgIxpQuidxLURBIiGQNpMVA8BeqaBgjFtowJDULPQjFzFd8+ymKsnedekH2LmlArJcjYQlYZFmQBEtZGW6qqfjGXR1j4EWTNiHVrpIWsVQ8sj8L8YMYj3noSyv8dDUMAoisOTJsMdVIHlPSoENNiIC1pW8aEYlcUEypEYbhi8L5biA0fsMnehBvbnapo5znZrL6FKdSKPW9oaAjz5s2rr1NtDguyGihXUqGZC0mlqvqyLVFZ3MqV4WhW0kEjBFm1QixsSyqwZ8wzmYwTZFyqiGXYbZ1w5HdD+/mJ0F97DEZChdLZDTGnE7F0DIjFQFocpMTskhajljFbTakQhd1lg/fdQgwA3u57FMjaZTCiEH/U7kThHMughJq7xp67P6UsZO+88w76+/sb17E2gAVZjRTbVJu10fqtqh/FDdVbhsNdhyvsw9irpRUtYnL8s9ksiGiM6C22+MqyDe1axDJSEEF56lpYv7kMBQ1AVwpKbw/iUxJALGZnTqranp/OqXZ9MRAAAUUfgSghxrxCDLBdlB0+NuFmn0gQBdEyEalWqLkL3rrnhmVZUBRlnDDjY5Mqw4IsQITwf1RRtdRSVT9qgszdnrCEWBBjUq8Qc7ehWZuOOy4PgFNEF7AFvhx77+Kr67pTrkMShSOD2o7Xn4T4v6OhAxApFaJnEmLzU1BjMViqBtI0kDoqyhTFdlMqKgB7vRGFbNFjkEoJMYnfTdg0zUgeHdWqtNIYlZsj7hp77qK3hmHAMAw8+eSTuPnmm7F06VJYloVMJuMUI2fGw4KsRopZwxRFGbdo1UsQVfWjIsgAe/N3Zx2GdVZjLWPSqhYx9/yJxWKwLAuJRAKapo2br97F1zAMaJqGeDxe1dmOTTsyqNXJ7IJ6/QoURB5IA0h0QZmdRmJKAqRqsFTVrrSvxABFAykqkOgA1DhsMSYg9Oy4+K9iQgzwH7hfbBOu5egoORd4HthEaS2uFyHEuLASKbrk/pTNZvHqq6/iF7/4BQYHB/Hggw/i3HPPxdKlS7Fs2TIsW7YMn/jEJzB9+vSQehEtWJAFSJAuyyCq6kch8xPYI2Sk9TDsyvTVbg5BC7FmWMiKCbGOjg5omoZdu3ZV3Vb3Bl3N2Y4cl1QCywB+vwHmY5fDigOUTEHpSiKxVwpKLAbSVFt8KTG7lIWi2RYxVQMlRw9nJgKM3BgxVkqIAfVnUVY6kSDoedCOc6Td3bGyX4qiIBaLYf369Vi/fj1M08T++++PL37xixgZGcHmzZuxefNm/OxnP8NJJ50UcqujAwuyGilVi6xe8RN0gHuYgswrZOQiHHZBVL9j4m6/EKIlLWJSyLtLhrj7X8/G0LBK9G0ObfstcOeHYcYBkQasRA8Ss1XEpqTszEkxahUbtY6Rqtp/Cw2Id9hB/GRCGHlHjJUTYkBjS1r4FWrS7Vkpm28i0K7zvNS6oigKduzYgQ9+8IOYPXv2uOczNizIAkRudLVYPmScjjuuKoiq+mEIMnc9NLeQyWQykSicWwnLspDNZse1P8qbhR8hVs97V0M1wcHeArltHZe0+w3g2vfAiGUgOgDSOqB0K0gvTEJoowH7QtkjwFSXVUxRgdGaY9WIsTBri9Uj2AGgUCjANM0xbs9WnwftLkBKCbJcLodsNjsuqL/Vr2fQsCCrkVIWsmopVs09yLiqZgoyrxCT9dCiJmRKjUmzhFiQyRZE9kHrMli2WiHWzAWxnrgkb0mOlnJ7Gnng0WuhP3oFRCeAeAyW0gXRGUNqkbCFlmq7KEnV9ljDVHX0cHAFQih2UL8AhF6AQLhWsXqoJNjdGXxhZ3w2ilZrb7V4+zc0NORUA2BKw4IsQOQktCyroqDyVtVv5ObfaEFWrDCtux5aM9viB287vEIsqkLSjRRi2WzWybr1G2MYlesABOvuiqQV5flfQP/u8UCnCaUHMNVOkJZEepaB2AzVtoYpiu2mVFVAUUFCBRQBkAAUARKjoiOfBbQ4Etv+XPFjoyrGyiGFGmAn/yQSCaiqOm4e+EkkiKpQi8p91yjKnWPZ09MTuesRNViQBYjcVMrddKWq6jdq829kKQ5vYdpS9dDcbYnSghSWEDw1NlEAACAASURBVKvXQiZdk1KI1XrQurc9UaIed1cUkgho4FVYX38fjNgIlB4A8TgMtQPJKSYSU/NAdxeg2tYv2zqm2GJMGbWGCcV+TItBjPYt9vbfIN6qfC+3ohgrRr0JJQBn/jabUi5LPjbJHyzIaqScy7LYRlupqn4j2xm0CJKWmUqFaZvRlloxDAMDAwNNvRb1ErQQ80PUxqSWmkju1wJ76q41ZHM28qAH/gOF31wH0QGoKQ0US0Dp0NA5Iw+R0ICubkd8QVFsYabYP0JRQUKAVBVCqCDLhCCC+vYrJYu+umkHMeZnjWh2xmdQtHuWZTlBxhayyrAgC5BigsxvVf1GtikoEeTtS6XCtI1sSy1IN7FcnMMSYtVayGSMWJAWsagI46AQYnxNJO/mLC1p7kSCIDdn+vPdKNxxFihRgNYDmLEErFQMnb0G1BTs+LDOztFyFnssYgQVUDRA2KVdSVEgnDKvAto72yeMGKuXSkLNLdqbcdC2l2YWgw6LYv1jC5k/WJDVSDkLmcweq6aqfiPbWc/mWyxWqd6+NHtR8iYbSOtKKpVqWhtqwW2JbJZFrBitKt68m7MQAvl8Hul0epwVpdjmXOxsz2JjT7v+BuPqw2FgCKIDUNIxmHENySmEZLc+mjGp7nFTQozGjQlA2H/L448gBIQaA5kWoGqI7XwNwqxcbLodxViQ85xLtDSHUmvF4OAgCzIfsCBrAPKcwDA3UUmtgqzYUU2tFqtULOtTlt8I+kSFaqhkIfO6hMMS8+2Ke4N1U+1xQYIsKD/7IvJP3g4lZUBJKhDpGLRugY4pthCDLPDa1WnHi0EKMGH/Wyi2KCPYok0ogGFAKArUXdshjLFlQYoxuPIJxIMcoJBp5heAakq06Lped8Znu1vISvVvcHAQPT09IbSotWBBViPuSec9J1AI4RRzDfvmc2/+ftoSxFFNQbWlVkoJMe81ixrNFGJR7H/YVFOWg566C/jx52DFs1C6FSCRhOiw0DFdh5YYjQnTRuuIpZN7YsbEqBAbjR8TigIigBQBAQGQBUqkoQzugKLnKrb57b5H20qMRYVSQs07D2rJ+Ax7T2gkpdb2gYEBPljcByzI6qBYVX0AiMVigRTkDAK/IqhUYdEgRWW92YWV8CPE3O0IC+84uBM+mmERC7v/rYTX1WW9/TIKV66DqQ5CpAlqMgmkCKlpOpKdGLWKKaNHHimgWAyIx0eFmNtVqdheSqI9wmz085Tdu6Bmhyu2LXvw08Bw5ee1GlEOfC92mkA1GZ+yb7LgbRT7WC+lLGRz5swJoTWtBQuyGiEiDA4OwrKsMVX1h4aGIml9KNWmUmdmNkJQNkqQ+a2D5m5HFK6RZVkYHh5umhCrhaiMVdiQnof+g4uQ33Qn1JQBEU9ApACt24QSV5HoNAFVAKoyWl1f2FawZAK2e9L+BXh+qxpgWQARhKpA5LNQR4aqaluU5stEpJqMTynS3N6UKJRpCYpyLku2kFWGBVmNCGHX3fKataO2gZUSQV4hVu+ZmdUQ1Ph4hVizM1hrxTRNAPaiHEbmbbVEaT43GyKC+fufInvH+RCxLNQOFVYsDbVbR2qSAS0BxNLGnvIVUpAJFYjFR+PFYFvFIOz/AyAVGlnm6PMFYBlQhgd8tSt78NNtfV2iei9UQzGhlslkIIRAPB73lUjQakKtnMuSg/orw4KsDpLJ5Liiq0I0rhBrLXgFWTE3a7OEWFCLSb1CLCzR7G43AGfsWy3zdqJgvf4CRq74MBAbgpommFoKVlwgNX0EyS4TWhIui9ioIHPckgASMQCjljJIN6Vl/60pgGkBimYbzEwLYngAfmZC5qCnfD2vVWn3uSkTSvwkErTa0VFsIasPFmQBE1VBJs/MlBmgQR1eXktbal1wg7KINSu5QOKNbUun08hkMpFI+mDGQ5ndyN5xGQp/+iHUVAGIxVEQMcS7THTOGkQ8CQh1NFtSHQ3UV0ZjxOS/Y5pjHbODxUZLWygaBAFkWYCqQBg6EE9CGRnwVWsMAEZGRsZYS2TyTZQ2ZqY45dY+vxmflbJ/wxJqpWL/iAhDQ0NsIfMBC7I6KDbZ3YGbUWJkZAQAEI/HkUqlAju8vBpqFWSt7JoslWQgY0iY6ECWBeOxuzBy5wVQk1moaQWW0gFLUdA1cwgdU3Xb4ygr7CujVi9pHZPuSUW6Jkfnp5B1xmQgv2n/bVl23bGRIV/lLSSJRMIpcArYSSFyg/ZuylKotRqt2GY/1PIlsJrs30pCLaz5wFmW/mBBFjBRcQdZluW4JgFA0zR0dHSEIsS8+B2fRgmxRlvIip2RWSzJIKx5EjUrbhQwX96M3Vd8HEjshtZhgbQ4CkJDLGlixoKd0OIAVNgizDnySAqy0XuKyBZYELYoA9kCzLKLvNruSsV+jWkC8QRgGhCFyuUtJNmDn0YMtrubiDAyMuLcE1E8KqgWorB+Rp1qEgmaNR/KWcgGBwcxZcqUut5/IsCCrA6KTeBmu8O8SNdkPp8HESGRSCCfzyMWi4UuxvxayNxCrJFB70Ev/H6FGBANC4BpmshkMk7ds4lYjZx2v4Phzx2NAt5BLJ2DiGvIixQUjdAzdQidM3QIFbYYU0etYspo1iTBFmWjQgyKMlr8FQBGHwf2xI4JAVgWSNMAiyD0HJDN+IoHK1eJX4jSx0b5OSpool3zsGhGOQ+/Qk26PYNMJCjVv927d8OyLHR1ddXZu/aHBVnAhCXIpBCTFrFkMolkMglFUVAoFCLzrbPcmDRLiAX9fu6xl0IskUiMWxS9hHVN5EY9ODg4ZjMv9k1aPl8e39QuGzZZJvT7v4ehH1wBrSOHRIpgKgnoQkOyK4ueaSOIdZEtvBS4hJirZoUs9AphW8mIALIgEgkQWQDsyvuCyK7Cj9H/NwwgFoPI5iqKsXJCrFI8UqmN2Ws9cZ/tCYQfj9Tu1ezD6Fs186GSUKu0Dngfl1X6wzYItAIsyAKmUbW2SuG1yriFmLtNURJk3rZ4C6M2OkYsqGtUTgT7bUMzkXNF13UAQDqdRiwWc0SYvDbFXB35fN55n2Ibtp8+RwVj6x8weMUZEIkRxCaZEKqGvFBBCmHyjAEkO3SonRitE4axQkxgNGhfCjCy/1/+FgrIMAAtZgs26cY0dECLgewgMohctuwZlY06m7KeeCTv2Z5RdntGkaiswW78JhL4yfgsFQYxMDCAnp4enis+YEFWB+VcUZZlNfQbQbGA8VJWmSjdCG5B1mwh5qXWBbIeIRYGXtGuqiqIyCnb4rZIFFugDcNAOp0e4/5qxTgla3gAhc8dg4wxhFhXHiKhwBIaCiIOEgKd3RmkOgwonaNx+M6PcP2MWsXMURdkXAOM0b9loH4yCegGYMXsx6VLc1SUCZD9dxHCOCQ8TDdXuTa1K63QNz9CTa4HXuGey+WgKAo2btyIzs5OFAoFdHd3N7P5LQsLsoCRi1ojjweqpio9ED0LmWma2L17txO71GwhVuvneOPz6hFizbgmxVyptR6uXi5Oybs4ezdsr2Wl6en4loXcT2/E4I82INZRQLzLhKWpMKBBh4pkOo+p0wYRSxgQcZcYk9YwAdjuRiEftOuIEQDD3GMJ0wRgKhDZPKgjBeg6IE+8ELaVTZgGYJrjXJX1CLFGWpJrdXPV4/ZsV5dlVNbgenALNXmai1wHCoUCDMNwrGWXXXYZXnzxRQB2dv9hhx2G5cuXOz/9/f0c6O+BBVkdVArqDxK3NanajMOoCDLDMGCaJogIYR4VVO01IiJH2NQrxJqBn/YGMR/cG7ZbrFVTN8kbUB40hT8/gXeuOhsUy0LrsaAmBCxFRYHiUDQTvb27kEznIRSCUAFl9KQju4MY+4cUYU5HZfbk6IOmNRpLZkJksqBU0raYKaNZlaPCTXjGPgyrWD1Usp54EwncNOu6R5l26697HZBhMwCwadMmbNu2DXfeeSfuvvtuzJs3D4899hhuvPFG6LqOk08+GTfddFPIrY8WLMgaRFACyDAMJ+6nVmtS2GUO3H0A7FiU7u7uyC9MXmGTSCSQSqUCEWKNEMl+2+se90rXoJZrVGucktv9JTfsWq1p5tAA3vmv86C//DS0pAUtpYAShLylwYKCSVMH0N0z4lShECqgpOGyjMGxatl6TAAm2aLMIvsHCqBbQCoOFAy7vhgREI8BhgmRzYEScUDTbKE2emalpF4hFoUvWW6CuO5RreMYBO3aL4m3f6qqYtGiReju7sa73vUu3HLLLQAAXdfx/PPPN7UoeavAI1IHpSxkQWy2XiFWjzUpLAtZsT7IjM8wxVglC1kjhVgjkMdhyVMYEokEksmk7xjGStciaGua972LbdZSvAPVFbckImR+cAMGfvptxFI5aF0aRJxgagSd4ujozGHytAEoqh2ELxQAguyzJoWrn9JNCeGKA1P2xI4J1+O5ApCMA7q559+pBKCbEIYJc9K7oQxvGq1R1noWsXqo1e1pGAZGRkZCd3cHSTPKXoSJ33MsY7EY+vr6mtm0loEFWZ0UEzv1WKR0XUc2m3V88UG49ZotyMqJSXdV8bDxjkm9wqYagrBayrgNeUB8mKcw1Eo591e1SQSFP23CrivPA7QMtLQFxBIQiQIsTUAoArN6d0CLGxCKXc7C/m3/n4h7xBjBDuIH7RFjlmUH8Ztkx45p6miGJYB8wQ7mN027XlkmZ59laVlQhzfB7FiJwrKbmzCirUG56+4WYn6PCYrql6WJRLlzLHt7e0NoUevBgqwBVCuAiMgRMYZhQFVVdHZ2IhaLBfJtqlmCzI9VLwrxbN4xbaYQCwKvEIvFYujq6qrKIhb2NahENUkE5q4d2P25kwFlN7SUBdJioDigJHIgBejqGUF3dw5QLMdFCYWcv0kI22ImXZXy6Em7JaPWsFFrmW5CxDWQYdrWMih2CQwLQC6/p3hsPAYQYEz/Oyj6LugLLmja2LUy0gKmqiri8TiAcKvPB0m7W8iA4n0bHBzE0qVLQ2hN68GCrAH4jYOQBTez2axzQHCQQkwiN+BGuQqrca9GRQxIC5X3wPVmWZhqGQfvfInFYujs7JwwsRjeJALSdQz94FYM/uTbiKfzoJgGQ4lDjeWhJA3EkyYmTR6CqtEYAQZhjeosxakLBuz5BdX5QNixY5ZtDbMfBBUM2/pljsaE5XTbciZgB+7ndVuYQUAbeBRG70dBHUsaOi7tRDGPQ6WyHOWyfKspatpo2u1aufHrsmRKMzFW8gZSi8vSu7FqmtYQIeZuTyMIMs6tmciFXNYRi7qrT1pQM5mMM1+6urqctPOJBhEh++QTeOvKz0KLZ6F1EkwtAQMK4okctKSOnsm7kUrrEEKKMbKNXzS6wY/WdVVUAkEe/o09FjIBwCQITYDIJcoUYZe/yOujVjCyHy8YthgzdCARt4P+VQVm57ugz/90w8ahXfGbPe4nyzfoshy10s7XCygtyIaGhvhgcZ+wIGsApawf0tWUy+XGbKyapjV0IXAHsQfxObquI5fLOcfpVCPEGm2tK4fb1QfYi3I1rr4g8Wshc8cUBiXEqrHORU1c66+/htc+fQpUbTfiaR2IadBJsz2HyTw6ujIgFUgkjVExZjnuRxKAUCxAESBTAAqBBEBmETE2+ptMCyKmgiwatYgJCE21RZwxGsSvEaAo9vNMy44nIwKSHbC63w3EuNaSX4JKIKklLhHAuJIcQbs9o3Y/BUmxNZ2I2EJWBSzI6sSPW65YzI88tqaZbax3sXOLg2qFmLctzaTY+AOIxIHrpZAWsUbEFNZC2JmxVjaLnbfdjMH77kAylYOIKTCUFCwFIIUQT+UwdeogYnED8bjhiC3pdQTIFmiwa4kJVR72PfociYAdD6bZr4EQIN20y12MqjRyXJIYjSezAMUC5QwgNlqXLK4BRg7GvFObOUxMGSrFJbrr5rmzfIOKT2tnC1m5+LjBwUG2kPmEBVkDkC5LGSyey+UcIRBGzE+9gswrxOoRB0Fb68pRTIjJ8R8cHAx9gSz2+V43cNhCLGyICCMP/wrbv34ZYskckl0WoMVQEBpIsWAKge6u3Zg5fQCKRhCjwfkCBKGMlrMgC0KxLWLO3yRsl6UGkEWwDAEl5grsNzFqWRvNsJTHI4nR7EpyibOYar9mND6JZOmLggGo6RBHr3Vp1nyvtSwHUJvbcyLexyzI/MOCrE5KWcgAO5hRBosnk8nQgq9rFWRBCrF621IN5YSYtx1h4f1895FYjY7H816DqCRaeMlvexmvnPtvgDKMREcOIhaHIVSYELZeUgkzJ7+DSZNHbIvXqIASsGwLmf1PiBiBLDGaKKmALEAkLMBQYOmAkqQ9bsvRxEmMvnbPg6N+TAt2vTEhIGKj76UodqC/ECDdsK1mFoCC6QjrRmb8hT2XgyQq87Cc27PSWY6l6uZFpW+NoJSFTNd1DA8PsyDzCQuyAHEXFAUATdOQTqdDd4tVK4IaIcS8NGJxqiYLMQoLpIxpcQuxZp/rGUWsTAavX3sNhh75OVIdeagJARJJ6EKBpQhANdGVzmLG5CHEknk7TsztllTsMhUCBFIEYArbuKUIENmKiwoKRMwCmf+fvTePkSxLr/t+9973Xiy5L5VL7V291PRS3bOIQ5GCBNIAaYqA/cfANkTJFmQDEizAkkXJlGXB1kiySEjEUKRFSiIljCTK8hCEbIr7NhZJiYtJztrV3dVd3bVXdS1ZVVm5xvbevZ//uPdFRkVnZuUSW9XEAWayOjIy4r4l3jtxvvOdTyN1UAVBMlARW/wLtkqYOTvLxycZ5aMvAKk1IIrC64fn1f1Nevxnj3H/T/p5fq2lr8NOIhiiP2glau2zHJ8Uy5FXBXpB0nuNnQjZ2toahUKBcnmoFO8FQ0LWATjnmqVJESGOY9I0HQgyBnsnZL0gYt24AG3XtTroXYj5sVhdXUWp/c0mfVYhIqz96q/w4Y/9CHGhxtiEQ4zG6ogGnmQV4gZz02sUk5So2GiGvOZxYahQDkdtlRwjQZyGLFfLAinLNKbosA0NdfzVUIuPxsg/KqF0qZTPKyNX0tIMlEZFOuTGKiTLfI5smkHDNrerVCp1bBJB+/56VvE0fQ6eFMuRK2lpmjZtLK1/+yyR9PZ1r6ysMDEx0afVPH0YErJDIk3Tph8pDxTNCcKgXDB3I2TdDqXdz1r2i8MQsSdFk3QLefZZrqKWSiWKxWJPL8D78fH1al21y5e59lf+MqKqJCOWpKBxKGrECBDHKRNjm0yNVlHaoSPryViIs0AE0fmaCQZ+vFcs0yhjQTSShVR+5xA0tqoxJYfLNAqHqyr0+AQqW9lSybz1zP9DEaIw8P0B1stpUm/4MqZW3uTfgtGfWaT6Xy499li7mvI0Bp12A4NyzewE2ola3imdJMm+x4UNOlHb6bjlHZaDuu5Bw5CQHRJRFDWJWP7BszaUMgbo4rJd52cviVjrOvL3Pyg6oYj1umTZTsRyFbXXZOyg6FYThq1WufkPPsfml36bJG5gSgodKTKlqEpEZDJGy3VmxjdIYgmxFQ6T+M+YCjVFpfOMMZqGfRUJuLBup1HG4ZyGBqgYlPJGfVsNhn4BPToCorBTH8csf70lsZ+mEifWPxfn/15FynvJTDinso+eV6V/O/cYKdtu3E+7ovIkI3n+haLfHbDdwLO2PTlyUrWdP+1JJB34SCTHoJD0nUqWq6urTExMDMQanwYMCdkhYYz5SH08P/n6ocDshNb8r34QsdZ1wMEIWfvae5Xjdhi0+gpFhGKxSLFYJE3Tx74RfyNi+ed+kQ9//J8QxzXikkYnGpSjoQwWwFhGynUWptZQGpT2hEzlnjElCJ6MeHN9IEran1tiVShRCkoUYg0mtjirkMzXOHXiwrgjh2tomH8FTIS5/3vY+T+Kefj7tIb5Nwla/tNsnXeSuTBOaXu0k7J27KXjbzsjeaVS6Xp+Vq8wSF9iO40nbdtuJH23bs9BUFN32rZHjx4NS5b7wJCQdQG96CQ8CKy1rK+vD0S2Vb87PrutkOVekdb5mKVSqXnB7WX8x5OQR7T0yu9YuXSFK3/5r4BUiYs+eNXEvjOyToRDcFoxWkyZHqt4MqYEVHDb58GtOs8Q82OR8hR+oPlcyZRXysKhtg2Djm1TQXN1guql0AWHq95H127gyicAgx39OLp6E1V/2DJSiS2ClgVPWn4f3YGP7UbEnoSdjORpmtJoNJolsN1u1M+CP+lpxm45Xbuh17Ech8F2rz2MvNgfhoTskNgp9mIQuvhg68Kdf2j7TcT2+57dbDToVqfnoA8qz/ddlmXU6/WmUtf+TdsY09F9lG1Wufr9P0jtq79PVEghilGRI44bpGgyicgUFKOUhel1Roop+WEWwBjnzflKml2VYeG+NGnCQ075MUZagoeMMFDcoZVA5udMirjm4yiFGzmFjL2AI4LSDObO72Ln/yhq5SF2+hyqtoSu3nu8AzOsRakQTdaGwxCx3dB6/udDuGHnG3Unmgh6iUFbz6DhSbEc7WXvVrQf+06oaTtdJ/KS5RB7w5CQdQDbka9+E7J2n1V+sx0fH+/7xW4v+6bbHZ+d3gft2WdPmo/ZTxU1L6VvbGygtaZQKDxWGmn/pg1Qr9ebN4D9XsBFhPv/7pe5/eM/jonqmKLCqgImspg4o6EMNasxkWNxcp3JchXdVMVAa4sojdigLuZqGL7EiQsKmVVN3xiiEAs6EkS8pCWpBhPEtdj58UkOXKrQkYAqY259ESnPox5eR1QBcZBNfwtKGuiNe9iFb8U8+D2/YS3ETATfkRke6xYRexIO6k8ahLIXDF5VodPo9v7c7vjvNZbjMMd/J6V/ZWVlqJDtA0NC1iX0i5DtZHjPPUz9JmOw+75pTarvpprXqeOzlxDaQYFzjmq12my7L5VKFAoFsizDOfdYWSQ3l2dZ1vx93qwCey+HrV+4xMW/8teJdJW4ZBGVkBqIohQTZ9ScIsUwNVplcXIdpcWTMZOXeMLwb/EkylqDSyOiYsMTL7z/ywe6iidlBvJMMpcqlPEhsVuPg6vr8Lj4hH8tiDFIMo2d/ji6eh+Jypg7v4ObeAGzeQkxJfTqBQDs3LdAVkM11tBrl/3GRv0jYk9CJ5oInoZuv0FFP4nmYcqe+d+1+hO3O/473VtWV1d54YUXurNhzyAG767xjKDXhGwnIpYb3huNxkek635hu33TPjKom0n1rTgoSd1PCO126KVC1trhqZSiUChQr9d3JbpKqea5k2VZs4t4r+Uwu7LOhT/7P6JYpxDXIYrJVIzVQmIaxHFGwymi2PLczCPi2IFyIVcsD9EMpcBgGHPWoE0GzuAy7cceiUM5FeIvQoqrVcFfppoGf5zPC0NJUMOC0uZ8udOm2o86kgLm1m+CZKjRo/5vi1NIfRR75JtRtoKkDfSt3wcEJk4AkL76vWSv/y9dO4bdwEGbCGA4hHu/OKiHrJt4Utmz9X+NRuOx57STdBH5yHkEnpANB4vvHUNC1gFsRzBa29K7iScRsd3W2E/ka+kXETvo6+ednpVKZeBDaHfq8MyDjPeLvZTDsnqDe//Pr3H7X/4kxUJKZBROF7EolLFE2hLHGaJgbnKTyZGG92GRp0oor4ZpnxPmrMLEDmdDq6P4TDHJjFfGjEZwvovSJ7Q2X08sgdGpULr0sy4llDRdQ4csM4Myglp5H3f0m9H37mCP/BFUto5b+DZUdQmp1FArl9Hr17AL34JCcNPnMGtvIbpAdvYvHPJoHQzdygrcSxp9N5oIBuka9Y2Kg5Y9cwX+3r17/MZv/AavvvrqcGzSPjEkZF1CL7r49kLEerWe/UApH8q6vr7ecyLWugbYn0LW7ms7TORGNxWyJ3V4tn5R6ET5Kb8Jr3zpLS789b9LHNcoFwUVRTQU3khvLFYJ5aRBqZgyM1Ylilpv5nmImAsKWSBeorFWY6IMF8z4iEJFGTaNMGRNUpZ3PyrUVsI+gHY+2DWExCKyVb7M/WiRn2epbv4hduHTUNtErXyALM6gH17AzbyKXn0H0QX0yrt+0YVx7PQncTOfhsLMofbhQdDLz/N+y15PWxNBtzGICtl+sNvxF5Fm9ArAV7/6Vf7qX/2rzevM+fPn+emf/mnOnTvHa6+9xrlz5zh79uxANToNCoaErAPoJQE6aChqaw5ZPy8K1lqstU2Ju9dE7CDola/tsNhrY0GnyWDtzhJf+zPfi0iFUiFFRX7ckeAQLWSA0Y6xpM70WI2xcgOlwtzJ4OlCPDHSceu6dHiOwtkInWS4zBMySWOiQuof15nvrFR6a66lAkQ8EVO5B82f/z4iI/jGrMIJKOv3kY4Eqa2j1y8iKkavXPT7Ki4hxTns9OuodANqa+ibX0K5BtnL39uR/fg0otNNBP2+PnUbz9q2tX6hy6cQfOYzn+G7vuu7uHDhAn/tr/01Xn75ZR48eMDnP/957ty5A8D169c5efJkP5c+kBgSsi6h04TssOn0/b4QtA7RBv+tuZ8JznshJd0sp3aSFG3nZxsbG+v6N1Bbq3PrJ3+Oa//Xv6VcaBAlgqiILDAspzRaZSQmY6TYYG6iQhxvNQb4CqPy4a7BA+ac9l2VooI3zKGUT9h3aYSOLD4FFtJajIkzpDCLqj0gj8EQ681nCtkarWRCqr1TWzFi4o+BChEaKvjN1KP3IQKZ/xTiMmTiVdTadVh/iEqW0A/fxi18GuUaSHEGd/w/6ep+fhpx0CaCHI1G45lqIhiU6kQ3sJ36Vy6X+dSnPsWtW7f4qZ/6Kc6ePQvAw4cPeeuttzhx4kRf1jroGBKyDmA3heyw3/gOS8Ta19jrb6CtREwpP0Q7y7JmFEe/sBshal3zoKt4aZo+5mcbHx/fd4fnbtu13e9EhOX/+BXe/lv/kEhVGSk7IuO7JR3glPJELEpJEstUsc7EWA2tXNOo3xwGLrlSlstkgZQZh3MKJRpRCpNYbKZwaeRHJ8UWLYI2Qjb3Miqro2//Icr5yeDeURFd7gAAIABJREFUOuYDYcUJyhlv6te5od+vJW8eEFGgBJcBSnv/2fUveXHt6KfR67dCHMY7fr80VgGwz/3nXtYb4onYS9kzz0xsN5EP6sigIXaGiHwkGHZmZoZv+7Zv69+iBhxDQtYldCJorxNErH09vfqmZq2lVqtRr9ebRKxQKKCUolKpDEzHZyt2W3O3cNDjkTcWtPrZ9quW5u+9lzXkz6l+eI8v/Zn/CXFVSoUMYwSMpi4aqxRKWWLToBBbRpIGk6WMSFtU8Gvlr+W7J/NMMeV9+BqU+NwwsRodBe8XPmHfJBZnwcQWm2qUKNL5b8Jc+31kdA5MjOgYskpQyXTwkHmiRyCEgo/WcC6oclkggy7yvzN5A0DYXzUfZeEmn8PcvYuMHoPGGvbIN2Ff+K/2tM+7hWeBlLSWPfNolVKptOcmgidFMgwCnnYP2W7YadvyL7XDYNi9Y0jIOoDtPmStBur9lI5yH1CtVutoF1+vCFk/SM1B0Lo/WvO5erXmg762tZZKpdJzP5trpLz3Qz/Jhz//6xQKKXEBjFGIMtTFp+LHpkEhykhiy0SxTikOZUAtW2oUyhMzwZv3wwxKX0pUiHIo5UmZy3xWmFJ+rJJLFYjG1SOfVxYJuCoKQY68iG2cRKIi5sbvIpPHMWtXyVW3rdf1BNA1dN606Z8TyKJS+ecjhMk6Qa1cQZxCVAk79SkkGsPc/m1oaOTIJ7u6379RsZ8mgt0iGTqVRH9YPMveuJ0I2crKysB2oA8qhoSsS9gvAWonYnEcUy6XO3Yyd5uQtZOaUqlEsVgc+I7PWq1GmqZPXHO/0c8y6vJvfYUP/sE/J6JGsaiII19STDGkTpNEDZIow2hLOcmYLGdEoTRojENQXgVTqhlRgRIf5tpKyiworRElXh0LSRfOmqa/Kx8OrpTDnfwmFA6ZfR0u/SHKxOhihBKHiiMEhVt4HXP3zWbKPwBRKJGqIL+pLcKoDbjQF+BSDQ4kiLnm6m8DINOnAXBnvjs3oPUFg/IZ6jSeVELvRxL9EE/GdoSsnz7hpxFDQtYl7JUAbZf0PjIy0vGk924Rsv0Qsda19PNmkgelgvdg5flc2wUbdgt7PR7dUO/2+t7VD5f4vT/111FSI4kyVBQTRXWUVtTEeAIWNzyxUcJkOWOskOGzJ3yMRW7S92+IJ2CIJ2Vath4LY47yv7WpJ30+YT/vxgwBrijIFKq6Bkvvw8lPosQixz8Oj64gp/4YNCpI8SRq6SpiI5g5DctXfNmSEDyrg7/M+EYAr8qFfdNUzqRp+s/3mVq94o/Nme8+8DEYYnsc5Lqw30iOfkwi+EZQyNqRE7Ih9o4hIesAdlKBYOeTtdcjdzpNyNrT3/ejLvWrwaA9KBV8N1CxWOzZGvaKw+zf/aL9NV2W8db3f577v/YfieIUZSLQEbFpIErTECHWDZQRrAgjScbcaINIB34VypKeZDlA+Y7KYBwT8KqU8zEVCny8mNVhAHjortTgnG4qVCoQOBM7nAO99D4yegSV1XEnPg2bj2BlBUaqqNvn4dQnUR/eQiZPopevIEohE0fRSiMrt7zPTDy5A/dR5YwWAaxtt4uA+ek/BSiy773W8WMyxOGxUyRHTtR2G8A9bCLYO3YqWeaG/uF+2zuGhKxL2IkA9Wv2YacIWTtROIi61GtCtl1QarFYZHV1tevvvRu2Uwp3StfvlXr34a/9IW//nX9MbBokBYUjRhlHZGww7TsSY1HaYYxlqpgyVrRedULQyg86wim0Eaw1RHHmjfoSeI3gh3yLV8rE4VUqBKPBWb9vrNUo46DZEBBKitbvNzv3Oiopw7UvwYlzqKVLMHoE7oZOyM27SDIK08/jRhewJOhbf+CnBhSmUPV1mDwGqzc9DyNP+w/rVC2qmPIE04lGZcrnnoVDEv3waQBqf+lSz43lz9rNbqcRPJ3EXsqe+RzXTjURfCMqZKurq0OFbJ8YErIOYDeFLE8r7hcRa1/TQQlZKxED+lLm2y9yIlar1XYNSh0EPCldv9vYuHmf3/6ev0mkahRii2iD1Z4kFXUWyFKGCUQsioQj5RSjQwkQh1Z4v5gTT7icQmtHlhnixALioyy0QD4EXHxZ0LlAwlKN0l5VI4+mcL6kKaKRoJLpSJAbF9Ajo34DbNXvx9kzqMY8rjiNWr0F1Udw/U2oraFOvI5yGXL0ddTdNxFTQFWX/d8tnkMtvUUewOEyhVIGJ97crwidCPqjKlqO/LMB3Z/1OERn0Ysmgmf5+G9HTIcly/1jSMg6hO3ITj7PMr/R9ouI7bbGJ6EbRKzbDQb7Sazvp5dNKfWR86MXpLF1/6eVGl/6gX/Ng1/+TYpxA60jrNI4AY2laFLEWIzyREyUMF6wjBUcKpQXBQnb4k38aHBOYSKHKEVkLFnDoLQfgaTQntDk5UtrgucM8gwxZwWUxmaewCkFStlmXIbfAIXU1uHUJ0Er3ORZ1O2ryOYy6tTrcP8qHD8Ht89DXEItvRu2P/z9wsuwdhs38xJERezkOSQZRd38MozOQuW+f562zZJlrgS23nqy772GiFBuu3lbax8bIdTpmIZvRFN/r9GpJgLn3EB/eT0MdlPIhnMs94chIesS8g9tvV6nXq/3lYjl2A8ByYlCN0pn3SJkeXZbpVLpO/l9EvLzo9Fo9OX8EOe4/kt/yPm/988oRilJ4nA6IhVfloxNRjHOQpnR4ZSjEAlzpQydh6sq1VSUwBMd5zQm8mVG53KVWKONoHBYawCLyoeAawkUh9B1CS41LS/6eHaYuNAskPnz0DY0XDqPNg6OvQqblyEuwb338i31PxbPwsNLZFPPY3QZN/NxSBPUg0dQOIq68WX/zLFwA5l+Dir3kZFpdC0Qs3xNoSGh1Tt2WIVlqKZ5PA0k86BNBHlkTS+aCHqJncqxKysrQ0K2TwzeneopRU52WtWZ/ETNh1D3G3shZO0epm6UzjpNyLYbHbQXctMvhSxfa+v50cusngdvXeWL/83fpmQalOMMrQ0NIhAhNpZEpygtpA6UtkRGWBjJKBiHbnYdEqIsPPGKIi93KS3YTGEivAE/ctjMu/2VUkSxw7zwceTK18MMSR9zocDHXegQ0urfgdbsMOuiZsBsHlHhuyV9+VDpsLCjZ+H2m7gjL6FMCVn4FFLXsFzHlUvoS18Fk0AUnh8n/ufs86jlD/y/c3Vs+jTcvo/oGBVHkFZwn/pzyLf/rT3t670qLE9z6OkQHrs1EWxubj6mlj1LTQQ7EbLV1VXOnDnThxU9veg/S3hG0OoBytWZ/EM1CGQMdicgvSBirevI3/OwyMlNlmUHmu/ZS0LWPqRca00URT0jY9X7q/zCf/p9OFthJE4xBpyKyERhTEpiBKUynBKMdohyzJRSxosOo3Iippomdy+feeXKWuWVMwETCc76Y5ymhiiyiPPkTKYXEDRy+pPw4SWktu4N+wryUNbmEbEgYei3T83PPVw81vWYlzjV9XfguW/yhvu0DGYS3v8aFEZRrhr+LERwLLyEunPe//HDq/6xkSlYBhmdQy9fbb64zH4MV15EpVWoV5HXvudQx6FTatrToCYdBE8LEdkr8u3Jh29D95sIeo2dCNnk5GQfVvP0YjCYwjOAtbU10jR9TJ3Z2NhomvoHAblnqRXbEbFisdgT4/thbiitRCwfHRRF0UBerHYKdV1fX+/N+6cZ73/hN/nSD/2fjMYZhUKGKEMDjVaOxKQ+K0wLkXE4QOuMmZJlouAT7pXayuPKRyChFOJUyOoK6fp516QKI4hC6VJEI6khmZjDvn8e8+LHkdom5vnXkQ/fw9Vrfm6l87ljPjpjy9zP1lviXBh9ZBXOKZyNggInyMWvo6Ow1tT7HtXC83Dz64hJ0Pcv+xfKvyQdeR718H0kGfENCcf+CFKYQlbvImsPUVcuQ1qF07Nw4+swMgNHXuzKcTqomparL0/DjftJeFZJZjt60UTQK+ymkA0J2f4wJGQdwsjICM65x9Sw7QhQP9GqCO0UBdELInaYi0e7ynSY0UHdVshaQ1211n0ZI3Xn/3uXL/73nyOhznhsMQYaxKCEWPt0fa0cceSITMZmpijHGYtlRxx5kpWjqWA5Xx702WIujBXSKMSrYN6vT5YFUqAgihx6Zh537R0ojSKVdTjzcZxNcanCnHoDd+0d9OQ0rN8nH7PkjWVejEPAhiHhgva/a97P8rKlJ20igrr7vv9VHmS2+CLcvYBMHgcVI8e/GYnLyGoVUlAX3/SvcfI15MP3Yf5F2Hjg/7byyP88/U1dOU47Ybcbd6VSaZI4a+3Qmzag2Cmnazt0qonAGNMzUr4dIRP56GDxIZ6MISHrEOI4bg7GzTFoZYWcINZqtSYR60cUxEFKlq0zHDs5Oqgbx2evoa7dJISbtx/ys9/9N8lsjdHYEoXux4ZTRCajYASURSkhMpaGEzKE2aIwWQCtvarlSZi37jfDXXEtpEw3lTOUkGXhbwS0Bq1zlQzM0TPIxDwqScje+zLm1Eu4W++ixqdxN97zZcvIIEkRNX0Ue+cKiGl61vxaVNMz5suc4b1pfU7evelLperaBTj9KUQXsPUS2o7Be4F8zZ+C1Qeo06/DzXv+BR/4cqUqjfsXLYxulTVPf3NXjtd+0UrUCoUCsHdv2nYkbRCI2n6Iy9OIg27XQZsIoDeTCHYz9Q8Vsv1hSMg6hJ1yZ/KLZL8vMiKCtbb5zbrfmVx7JSPdnOHY6WOSl3+rVe9XKhaLlEqlnh5720g5/xO/wps/8bPEJmU0cRgtOOX1plKUoUyGIzfPOxLjiMWxWBY02geyBrIG+X7y5npCxEXu+XIuz6FQLSOOCEb8LZVMIaTnvwxKYcZG/OtiEUAvnkaqmzA6jV2+g8tqqKUlsBHm6Ank3nXyFkwRAVGeiLXtVucEjcKmJkhq/gnKAJfeBnzHJqOTcB8oj8OD6+Gvw7k4exoe+tFIVENw8JHTPvkf4LnBIGTbYa837tyv1IqhmtY9dOtL125NBLtNImhX0w5zvHcj0aurq0xPT+/7Nb+RMSRkXcQgXNDaM7kAJiYm+h6O+iRCZq2lVqt1dIbjdmvoREn5MKGunbxY3/qdd/j1v/gjGBoUY0uklU++BxKdoZTDKRCnEe08OdNCwQgTsfYp++LCjZ2gfmVhHmXbmkVhXSgP4v1izoX2/kw3fWZK+c5M5xQ4i3nxVeTW++gzryGRxs29iLt+A1lfIXohxt2+jn7+NeTqW6jRSeT+LQD00TPInSvoiVlk/QHWgnLad3qG6H+lXLDsSxhG3uo/a+kOvfIVlAJ15BTcPO9520NPzNTotCdkcamplBH5pguZOoGaOdWx49UrHKbTsx9q2iBcN7uBXm3XXo73Tk0EnTre1lrW1taGJct9YkjIOoSdFDLYWdLtJrYLRzXGUK1WByKgcCdCdpBh5YfBYQhR+z7erw+vUyXLytIK//Y7/gZZ1qBoLNooIqPQypcRIy0IDgndkxmO0djREMd8oilGIVrCgYm80pRlxgfBSoTWlnyZzhl0SNDPIyl8l6MO2wRbcRWCaRI15eMvUrA1iCXCvXsec/osbn0FSiO4Wz5yQqW1oJydRO5cgrnTSBQjx87hrMM9WEMfew535wq5jyxX5baUs+3Pl2aHKOCun/dEc+YkPLrqmxREYP4sjM4jjRrSyJAqiMyjZz41cBfMbpfBeqmmDZK9o5MYhO3qRBNBe9NI/vf567dibW0NrTWjo6Nd3KpnD4N2fXmmkJ+kvUxpbicJrV2f+QdtEEqo7ejlMO0cB33t9gDaw5R/D0UIneMPfujfcf5f/gpFYylEgNLExqKU745EWVBCIXJUnWCUQ2EpRTAXacjDXLXDiZ8fabQPdhVROCeIGPJOS1/ay0cd5ed0/jsPpXOCp0hT4/1kITOMy++CiXC3r4a/9H+nj52CG+/BsRdxSRlOvk62abHLKdGRIu7dN1Fjk36AOKCiyJO2M6/B9bdzqS5fDgRjv24e4sf3sy+1KqxVyK1bCAVwCnXxMmQN9PMzyJW3oDCCshsgDnXq3IGP1dOCp01Ne5owiPvisE0ErcSs9b6Sd1gO4jYPMoaErIvISVgvviHtRsRydDL/67Bo9df1a5j2fhUqESHLMiqVCtZaoig6VLr+YS5WN3/3Ar/8F/4PYpVRiiyiffJ9YlKvXuHIB4E7LWxYiyjLYklj0CRmiziBH5odGYd1vpNRKUekwYnCBLUrV52sjTHGAormOKNcKXOA21LLFGyZ8AOi0y8g1y6gZhbBxPD8G1gr2EaMicaQd99CjU/BhidfUlnzrzd/HLm8DIVSk9ApFaYFHH0ebvuuSjU2CdUNJMv8IHLny69ImEcpflTTVrOA3xaUQOa/tLgrX/XRG0eOwZ0wcunU6wc+Xt1Arz7Hh1HTDhJ4+qzdxAfhersf7LeJAGhOpPmBH/gBlpaWOH78OHNzcywtLbGwsNCPzXgqMSRkHcKTSpbdwn5S6geJkIGPsFhZWdm376ofyIlYa+5ZL9P1c2w+WOfn/rvPsXnpNgXjZyyK0kTKkmiHVi74pxxoR00cOMtkotBaUVC5V8yTJ5OrWQJp5kmZE0ErIQ2GfGeFOM7zv0KXpdD0m4koP9ZI1Ba5CQb6XKVyLp9RqalffB81MYcqH0Heexc1PoHafAQiqOqGV77mj+PWl2FkDLkTjPeNkCu2eBpuXACtkPWHqKMvwuQCEo8honH3biCbNcypl7E3LqImZ2DNx1coteUp+0hZU+WPbX0+5Pa7nrjFRdTRl7pzUJ9SdNqrNCjXpU7jWeke3e54Z1lGrVajUCg0r+MffPABv/ALv0C1WmVxcZG5uTnOnTvH66+/znd+53fyXd/1XX3cisHGkJB1Ed0kQO1ELIoixsfHd1VrBoGQ5Qb4/JtVP4nYXm4Cncw9O8j753CZ5Xf+4c/z9r/8NUo6I9YOp7TvkFQOYxxaWTIEJQ5lMiZi4VEjYywmmPYNkM+f9CVJ60Dnwa+AdcoHpDpCOr/jQaqZjyE5eZLGjZuApplBJrqF5Gz93Oq0VGSpf74/xGF7V1eQtUcoBXr+qFe+Ridwt68BINUNAMziCeTq274zUmk48wauMIqbfQkxCdx4H1hGLzjk3i3MC68gayugFG7pJgB67jhu7YHPP6tthD2Qo4WYiWr+U7WRNWnUaPzP39r878Ln/nBPx+0bDYf1pgHNx4ednoOP/PqVh3J/9rOf5bOf/Sw/8zM/w4//+I/zfd/3fZw/f57z58/z8z//82RZNiRku2BIyDqEXilk2xGxvao1/SRk7SXV/OI7MjLS87Xk2I0QdTNuY7+4/Jvv8Et/8ccoYSnFFkFjNCTaopX3i2WSR05kTBfhYcOykjmOlQ1FrdCBazSDgVFERnBCSNf3HZkCRMaHvaKE88sJn/7jZ8EY6m+9iZmeRVYfguRkjKZ/zBOwPHvPu+t16Hb0yplHrpzlu1I3qlggOnoSd/09mD2KFMq40+ewxLhoFjUyD+9707+enEBWHxF/7HUsoMqjyNJt/2ISAmLnjsOSV9aaJc8jx+CmHzquZxaR5buoxTNw9/Jj+zsvv/pw2iE6gb2oaTkRS9OUNE2B3uRodRvPikK2HXa6fq6trXH06FE+85nP8JnPfOaJzx/CY0jIOojtbvCdkuIPQ8Ra15K/Vq+wXbdnqVSiVqt95Btyv9BqRm3v8uxmuv6Tzo2HV5b419/9d0iwlCPrlR0FcSBhIoJTfri20V4hszhWU0tBC/PFmESrJrlACVr5kpxSkNn8xiYYnRM68Y/j4zE+fnaGytsXKL3ohwQniwvUVx5QePlV3Po6jZvXcS7MmwzdjVrn/rIw+ohtokXyTkcrNK5dRZxBZRGNTU2yMEnjwgUwGlNMoFbBHD3pydfMHLJ8FwC7GYjW3DHkuidaPLoHgB6fwi1dhyhGglImUezfdnSi+RqqOOI1splFeORJnZ6aR1buBW6ncWFagY5k4JSxp/km366maa2p1WqUSiWAjnvT+olBXtthsR1BXl1dZWJiYtvnDrEzhoSsyzhs1tV2RvLDzm3sVZPBbt62QfCMtO6/fnR57oTaWpXf+KGf572f+g+UTUasPRHTyhFp5TsTlSNSjmIsrGWWWFlGI1hNGxwvFShHCo0gvt3Qb4eEeNVmZW4rxNU6b3jXIbZCG6F49iXq779PvLhIducOyYtn/ciiueOka1XSG7cpvfYG9QtvY6amcCvLQfVQPL7b/HH28Rfadzi2ZIcp50lb4723CRsKQHTsJO7DENK6uuwfm50jW77rs8GWPvS/y8v0k7PI6pJ/r0YYJj5/Eu5c8r/fXIXiCGrxeahtIFEBa4rIiU8gxVFIy7iNddR6hGyWMc+/ir38DgCj/9s/w5zozgzLg6Lfn59uISdp+/WmDaqa9qweJ9h524Yp/QfDkJB1ENuRjMOMT+r0AO384tTLJoOdvG2DQMhy5IpYv7s8nXWc/7//gF/9X/8No9oxFvmB3yBESoL3yaK0UDKOqrM0rCXWjkQ7Gs5yqlygYPJU1lwZU8FcH0JUBVx43NqcmAomeLx0MPrrcpnCK69BFFG9s4RWEdW3LhDNz5PeuQFakd32wa3x/Dz1lWWS557D3btNVqmilAldnApPviyEGZS+lEkbcfP/0bj4DkqBGR3zBHJsEpuXJINSEh09tZVbtv7I07u5RYgVUhpHojJy6g1ccQQ5EiO1OnLnEdSEaCbCfnADVRpB1YNX7cXXcHdvw8gYrHny1yxYjk7C0TPNL1aD2njytGO30t5evGl5Mv0gqmn9JoXdwk4RSmtra5w4caIPK3q6MSRkXcZBiEc7EeuXkXy/aF33k0qq/SZkufIINLuE+tnlefPLV/jCn/5hErFMRg6UQ7QQKedN9zpkfSmHw2FxpNJgLolYtxkamC+UMdp3QGolONHoUDZUeeKXeNO+DiZ+aYl/EHw+lxM/t3LjK2+hSiWUWHCCbHrykszOUFu6S+G557BLd4nPvIBECea5szhjaGxYCh87R+Pie2AMynk/0NbcS2jvZtx6fGs9jffe9J2Za498Q4A2SHUTc/JF1PQ8ujSGoMlWV8iSeaJqTHpzDX2kjDy4CIB57gXc9evoYyeh5rs0XWXdv8HMHNz22yThMTO7gLux9thj+sTzH5lTmxOEnYjCEL1Bqzctv9YMmpo2KF88u4GdCNmjR484d+7Zz+3rNIaErMvYT8mym0SsdT2dvkC0R0LsZd39mmKw3SipfkVYKKXYvL/Gv/jWv0uWpZSMI4kFhZ8/aZQ0yVgmFnCUtMPivWKJFpbTOqfKZbRSOBGUaE++vIMfh0LhEDRKJIw08l2Q1vkSpRXvGfNBryGoNYTAFs+conbhXeLFBRq3bxMdO4aYhPilV7BRTG3lOsX5hMrXL6AKBQye5Kqwbwtnnqdx6aInZlpBlja3f0s9e/w88M0BghKFE72VIwZw+b5/3ecTsmuXiZ9/keyG94i5ovceMTYBD+74fz/yz4/GJkjzt3vofWamPOLdbUoh970C5+IkPzhIeI3o5IskSdK8ybfe8NuP55Ck9R8HVdPyv+mGmvasKmSw/bYNxyYdDENC1kHsJLX3M1rhIOvZK3q57sNiO09bsVikUqn0Zb1ZI+NLn/8tfuuHfpGSspRjIVGejOlQnhRxZMqhxYKyTMSK1bSBFcdiuUA1E2aSMs6FbsYQzKq1BCO6N4iZQLTyUUc+7sKrZzlhUzqUNXXIDgtlS5UUKLzyKqpYpLa0itZl1r76NsoYopInsSrc+IqnTtC49D4qimjcvOF/F/nfJSdPkV7z3YzRzAzYDKKE7MF9RHxJ07m8EaC1vJlnh7V2ajqya5cAhS4U/HOKJex9b9Q3kaeFamoat/rQ/0lQuPTsAvLAky/lwmNHjm7NzLTWk7SZhSapS+dPYjc2mr4mY8xj1oGcpLX+bEV7qnknidogftYOim53Iz5JTWslaU9S0/ZzDL8RFbKhh+xgGBKyLmM3AtQPQtMJQtaJSIheKmQ7lVL71eV55Xfe4wv/7T8lloxyJETaEWkJQREgOJxyFCNLzVmKBmrO8qCRcbo8wp3aGqkVjhTKiIDRLgz69plgGh1CXPO8Mf/CVkI3JJCrZFs/PZzzMRjOae9Y+/LbvrNzZgppNNClIgCF506SXrmMMobGjUC+ggk7PnWK9MolKBaR1JKcfQU9NoFRCYKmcuUyZJbC6TnSbJXC6dOk16/i1bl8ukXeGLDTuRr8Zu++CSikVtkqvYZSYzQzRxYImQtNAWZymiwQMlnxYbF6YgobCJmsPgjPm8EGQlZ+4TUoFrHWYq1tRjLA4zd5Y8xj53Xr/zpd8nyWb/K9ROv+b/W5dlJN819wnk21dLvrt4iwuro6VMgOgCEh6yB2UsjavzG3ErFeZ1wdpuuzk9lcvYjgaCe87U0RvY4BWb+7wo/9ib+NWB9LobUvSUZK0CK4kLIfhxiLTZuhcCQ6ouH88x42apwojaOUwoacLCsKo4O6pn1shVaQWdDK3yRMSNBX5GqTpzoioVXA6lCmVGjlkGZsBYgTsofLoBSNW76z0RQTUqDw3Ckat24RnTgBcUL8sXNIoUQ2uoYuj7D+7jUACseP0vjwQ0qvvAyZRUUR6e0QMzHiS43R/AJ2yatc0fQM9tFy2HP5cfLr3jrdtjuPhezWDf+8oIKoYgn7wL8uOpDS8ihu2Xdk5gqfKo8iocSp8ueVRkiOnnrsHG9VVPKbdaPReOw8aiVprUQtv8nvVPZs9zI9qzfynTAoil8n1bRnGbuZ+ocK2f4xJGRdRus8y5zQ9IOI5TiIQtaNbK5ukqF24tjvUqrLLL/zT77Ib/3wL1MwPjfMe7a8TwwEtM8WKxqoSoq1GadKJW5U11huNDhRHkWhiJTCChgA5UcfOfGkzDmFCWOQYiMs1YXFUr6PFeJCWRPwcx01WlloMf+3Jtc/5r8HCqdPItXiKkUJAAAgAElEQVQK0cICYgpEz3+MrFiiunGTwlRM5Ss+CyxZnCN9uMrI0aNkH95Clcs07gRPVygTJseP0bh+DQD7yM+sjGamPSFTCletAFB85VXq776DShJI6y0L2i5eI/y22RRw3jcFVCs074v1CmpiGrNwAqrrYBJcPIJ+/hNIsQy1KuKElBJu4Rxm/thHzpvdQk5bSVqWZTQajeZzWkueOUnLvyC1qmnfqN60QVf9Dqqm5c+p1+tPTW7aXrBbiXllZWWokB0AQ0LWQeykkAFsbGz0lYi1rmfP43raiFgns7m6QcistdRqteaF70n7uRcK2bU/uMS/+p5/TKwsxciFDDHv50qMI9ZCRgahTClKiJWAFW5VVzkzMkHDZhgiwJOvSEtzzY1MN0Ndo/CzKmDEseYaPNqAT75xls0PrpIrY+CaERdbtCsk6uf/Jc6XOZ2fVZmhaHxwC1AUdYnGBZ8PlizMgkA8OUZ6E8zEOOldb5qXhidQhWOL1C/5LLD0XghuHR31P0dGyO4G9cr5bfK5Z16Jy4lZdOIk2RUfc2GmJpHVMHg8eOIkjD0SadkiAUIam7PGE7i37/htmChRv3A5rOEhUqlQeOVVGu/6AeVmbBS3sc7IybN7Os6tN+vWBpGcpLUqajuVPFtv1k9qIMiRE4FnlaQ9DXiSmlYL3b2d9qYNKmq1GtVqdUjIDoAhIesicoIA/sPYzdT3vWIvhKyXIamdIEPt693rfu4mIautVfn8n/1RHr75IUmIrMgQEu1Lj4kOw7/JUFhmCzF36zUUitkkZlMyxuJREEUxipsdiQohcxqlBI1X2ZTKyQdkTnOjVsUKvDpaJpoco3LlFihNMj1BuryypXwJvptQXNOp5ZrkRpM637GZ70YdTPX1Gx+iFETTk6T3fInPbXriVDg6T3VtFbQiDeVNXfCdi9GRI9gHvkwoVR/cmiwu0rjsiZZ9+AAVJ5gjc77cmBQhSdAvvkZWLGGPnwUH2doaWSaUXnyeyjsXUCNlqGwCtDQD5CG3vinAd2nmKiA03j3ffJ5U/NpV/o1/1JMxgPj4yYOfBPhzrD2Dr11RsdZuW/LMFbX2BoIsy5qkrjW+JX+/bjUQ9AJPu2qUo13NjOP4sU7dnKT3stOz09hJIVtdXW1eg4fYH4aErAtoLZnlJ2teNus3diNkItIkNt0OSe3EBSZfbzXc3PuZrt+6pt/4sS/yHz/3K0SRj6aw2mGCgmWUQ2tHQ1k0lnIw7C81GhwtlrlXX8NJwpHCKPmMSLfFI4KG5b1jTrwHLbO+HcAiLNuUl8plRj92isrFa4ycWmDj/EXKL5ygevkGulykfOwILrVsXv0Qsb7DMR/83SQxwZ/lfWSPkxkVvGbZ8qPg1YqoB/KV1wYLx4+S3fJxFHZlFYB4YR6dxKhyGUpFkpdfR8plOOEVofU797GbBrcO1Yv3iBfmyO5d86/3wnM0Lt+gcOoE6QOvjuUkMFmYp3HFK3bxiVOkN28SLyxg790NxyQ/H1p9YI9vC0A9nxSwudZ87LCEbDtsp6gAHyFp26lpfu3eJF4oFDDGdL2BoFcY9JLlQdBOWnYrd3ez07Mb2I2QTUxMDCSJHHQMCVkH4ZxjY2OjScTK5TJRFLG2tjYwF5vtuhvbiVgvQlIPo07lfoxqtXoo4thphezqV67x+f/iHxGLI44diGCVUNCCwoJyOO0YiRWraUpRK4wCXEakFTWbcqo8jcJ5+hMULB0ImA4dkwIhrmJr/UZ7lWwuiYkmR6lcugFKkW1WKZ59DsZHMcct0fgoK29fwoyVcSoGcZQWp2nce9CsYG5daGGLhOVb+dF9JWm6Za/XmuLLL2PGx2BkHJc6Ko9WacgYqmbYvPKQZNGQ3fWdmaUXTlO7fJ3i889hNz2xzlZW/HuOj0IocbrgMzOjo+QUJV3yapsOsw9RkIXHotlZT8iUQsUJ0mgQzc9jl+7R6j/b3oe2RdKW//7fQCk4+oVf39M5cBjkN9l2f1KutLcSrVwVzglWaxxH63N2Knu2k7T8/fuNb8Sb+JO8aYOuprW/3zDy4uAYErIOQin1kdJkfnMbREIGPEZsCoUCxWLxsW9vvVrHXtAe6tqp9R722KzeW+MHPv13iJWjYFwYcSTExitjDm/YH0sUG1nGWuqYiCIepRVKusCRwgiJNhgdRhoFquWzwYKXSwSbl+JC6VKFteeq1vuVR5SM4ZPf+gnqD1cRpVm5cAVlNHE5xm5WGTnrywiFY3NU37uKGSnReOC7GUdeOkX10nWS2Smy5Uf+Rp77zoQ86x+HCt2Z+U+HiAEUta96X9boK89TefcypTMnqd/10RNZrpRNTZIFn1m65EuepuxJlYpMswwaJb6TU4+NkC17QqbCGvLZmUAzYyyamcU+9H/bHLE0O0t2P7ze1DR26R5mZha3HOItpqabMzi3zsl8osBWufb2n/7OnpCyVuTZea1flPIyUGsDQZ5Ev1MDwXaZaYPYQDAo18hu4KCd6J1Q01q7fDuJnY7XysrKUCE7IIaErIMwxux4Ig7KxSZfW71ep16v45wjSRJKpVJPiFj7WvayX/IbU6VS6fh6D3PRaFRTfuVHv8jv/tj/SznyWWLW+Vwxo50PXDWCEYvWjop1IBkFY1jPQnwFQqI9AbDiuy6dgFGCdQqttE/SD12QOpCEfNVOfAFTHDxXnEYpzfrVu1RvLTH1cT8Me/SF41Q+uIaOI+o3fBlPh1conpyndvEKupBQu/4hulQkOXWUaG4GFcXU7y1Tu3MfwQBmKzYD1+xcNMG3pdRWWbPy7geAonblmn9+HNG4G2ImwqzNaHqy2WGZ1X0DQDQ3i70TSo3Bf5nMHaG+4Ucc2fAznpmmHgiZXV8LrzfVJGQuPGYmJ5uELH8smpqikROy0VHcyjKF586QXr/y2PHNy5q9JmKwFdninGuGGLeSo90aCFqbCJ6UmZZ/BocTCLqDTl/3B0lN26lkOVTIDo4hIesw2oeJt170+o1WA3C1WiWOY8bGxnpOxNrXtNvv2tP1R0dHP2KSPgwOcmxEhK/83Nf5yf/h3zBhHCOR75wUccTae8SKEVSdRYsQGaFiG8wlJTINqXMcScZRooiMV8UUORlTIVvso1EUIg5Ruacsj6ZQKAm+MqUoHZ2lemsJFFRveRUqKnpT/cjzJ9i8eAUVGezaBiMvnSaenIJXPoYqFli/eJN0dYPahdvY9Qqjr51h8/Yjkvk5siWvckWT42Qr64/tC0d72a+1ezM8kqbNh9ymN+DHR2a2CNkjX6ZMpiapBkKWq2dbJUlFei+UKYvBMKw1WXieSpLmY3k5s/mYUk1ipnKzsYIsNBmocrm5VjMxgVtbZeRPfDuzf+n7tj8JuoS8szkfQzYyMrLn8z1vINjtRr1TA0HeRNDvCQTPmqqyWzREJ9EPNW2n6+bq6uqQkB0QQ0LWA/SbkLUTG4ByuUyxWOzbmmD3i9R+BpUfFvs5Nte+doMf/s/+EQmO6Ri0doAjUqCVIzGOFEfVZvhoC03dpYwYw0pWZaEwhgm+MEHRsEKkAVEodCAt+TxJ/28ngjiFUjoQNmn+TrV5umq376MVjD53lMrVD4mnxhBg9PWz6HIZc/wEplzk0YWrwCOSqTXSR+tMffwl0pUNikdnadzxxEWCp6swO+kJmVbYiletyi+foXbxCma0DKFL0YkPpJWP8rEW87xQu3odUFQvXvJqX7GADWVTFeqvZmoCG7xkBCIQH5nF3g9dmmEmZjx3hCw376e+ZBfPz2Hv3gmPhdJly99is/AeM7hHXil7rMNyzZdWk1PPPeFs6BxyX2RrxEwnsvO2u1EDHyFpWZY9Rrjym3P7TbqbDQQ7hYwOcTD0Qk1r9SDmGBKyg2NIyDqM7chXvwhZOxGLoojR0VE2wly+fmO7/dLrcVJ7fd3Vu6v83U//PVLrKBuhGAleG/LlSXCgPBlLJWMuKbKSbrKWZswWRoiUpmQixEeMYVFEJvjFAokR8COPlCdddeuPkVG5r8zfMHXzv2FLQctfQ+EE9JFZsrvrmJEJ7n71GgDluQnq9x8x/QlfyiwuzlK/4wlJuupVr+LsJI0791FxRPXDoEaFEmPpxAK162HsUOhsLZ5cpPbeZVBgCglSb7TkgG3dYHOyRnPNW5Bavflvu+HVs2R2hlogZHbVE6RoehK3topKEsQ6ovl5ooUFVKHgxzYlJZIXz6LHxtET06A0UigQf+x1dLmEml5AlCJLCuiX3oBSGaaPgQgNU0JOn0OVy9jNCjhBHXt+T+fGYbCTT6zbxGS7Lr3WG/VumWmtZC2vCLSqMU9qIBiEa0+v0CuFbD/YTU1rJ2m7qWk7ZeMNS5YHx5CQ9QBKHXxc0UHRqjDlY4PiOB6oJoNWQtbJsUwHXcN2SGspv/HPf5uf+/u/TFkL5ciRaB/wGhtv2LfKYXAY7UmaUY579TVOlCbJXEZi4mZMRdAZvIHfeWLVsJ6ANYCCVsE07xWyrZFHWwoT5BfQLY3MK2dbpcP7v/cOoBh74Rib16F4ZJL6fa9CpWue9BSPTFG/8wBdTJrlTcK+KJ+c9/llQOOBJ0bxxBg1QMcRjduhmzH2l5BkbrZZYiy9eIr65evEi3PYu0uPEUUrKhDMsDkhzVXwszPr799GiKm8fQOhQHRkluqDFOsmkWyMteUYpRXqwX3EWsbHIjbefYjSGqUfINYy9voY6+dveJIYGyTNGD33MTbf8h4xXSriqjX/2Nsh4HZqnGxllfIrZ6lcuAbA4pG5fZxJ+0eWZc3uye18Yr3Gk27UrSStGw0E+WPPIgZ9u3Yiy09S04DmdftXf/VXOXfuHKurqxw7dqyXy39mMCRkPcBu3yY6jSzLqFQqTSK2k8I0KITMOcfm5mZHxzJ1AiLC21+8wD/9c/+KSHtVLNKOWAkq5IlZLCKWmSTmYaNG6hxzyQgb1jKZjIAoYp2Q53vlKpg34autuArAaHjUEOYKiqq1JFqjUbg8Q0u8bUyABr6jMVfOdHM+ZavnzOPR198HFOXFaVYfLKOLCZUbeTK+PydHTsyzecnHUNRCR2Q0NgKAGStTv+tVNKzFjJUpnzyK1KuopIAUSpReewU9WkZNz2IblrqFxuQx1PQRVm5WwQnaKCSzFBenqd59SGsHo8KF3tGtx4zKcGKwS8tNLXDjrQuAIT4yRbrk1yTh5hAfmW4SQrGhxDkzhX0YOjHFP2bGR7FrG/lRBkAnSbMDVEWBjChFsnBk7yfMPpBHVrRO7uikL7KTaL1R79RAkN+sD9NAkP8771R/VtS0QbjOHga7kfRc1QW4ePEif/7P/3kAkiRhYWGBixcv8sYbb/D666/zxhtvMD093ZdteJowmFeBpxg71dm7/cFsH1i+ExEblCaDdg9Lv0Jdt9sXS1fv8/f++A/inFCMvPoVaSFSDrSfRenEUtKKisu4X69ztDjBUn2ZzazOTDLW0gnpWVjWYqwywf+Vl/B0UIzWXQWdxlyvLlPWMQ742Nisr4ZKTrX832m2yFf7kfSv5yMycqyc936t0ZPzbHzgyVf1tic10ViZwvw08dQE2miSo/NQLFJ8+SV0uUz19gMaaxWW71SoPnSo40VWLtz0ClQS4Rop0594kZWvXyMaG8GuewXOTE8hmaMwP00amgKSyXEadx9SOn20Wf40E2Nkq5u0NgM4CQO/Wx7L9UWfNeZ/bzfCaKWJsSYhsyEwNp4cbxIyV/Xet3h6qknIJKg80ewUWd7ZmRO8mSl03hDQIXTLJ9YPPKmBYK9D18Gr+TmZax0b1f5+T/MEgmcJ7eXnYrHIpz/9aa5evcr58+f5kR/5EUSE8+fP84UvfIF66KA+f/48586d6/PqBxtDQtYDdJMAHaTU109C1h5Cq5RiYmKibxfY1nJyo9rgl/7hr/NrP/YfKGpHHDkiJSjlEOWwShgxmoqkGAStYiIgU8JyY52F4kyzHCci2DxPLHjCPEl7fNSRFbhe30SLYjoqMKYLTEUjHC9MMPep53n4tUuMn1lg48pdUBAlEa6R4cSHyorkXwJaj6dq+X/ISZsILL97E9BMfOIstfur1IvC+mrG6s0NJsdmWDl/HYDS7Dj1h6vMfOJF1q/fRxdiGqHUmaM4P039nidatu7JTXFuis1AyNLwszA93iRkeYdmPDZCLV+t9jfm0ddeZPOdS4+9hxPdJK5biftbqN34EFDUPrhETtIaD0OIbGmraSVd9gqYKW89lgViFo2PkoXZ53k4bbI4/5H3OijafWJJkvR9okQ3sJeS53ZD14GmArfb0PWncQLBIHrIOoX2JoyZmRm+/du/nc9+9rP84A/+IN/xHd9BlmV88MEHvPnmm7z00kt9XO3TgSEh6zB6pZC1E7H9lPr6QchydaA1hDa/yA7ChfTtf/8uP/pf/4sQ7ioY7ckYypv1y5Gm4hpUnGMmLnG/vsJGZpmKS8Q6IlJbJAxAB5KkWkqIftQRZG4rzet6fYMzxXGuVB8wFo1SmBrlxCqIE+oPPYkoTo6yAYyfWWT9ym1QUBwvk67n3Y25ab6VgnkSaCXya8jVuFAefPDVS+QPVu96FcnkMyfHys33lrwrd3GGzeuetWRBlSpMjzcJWSM8XxW3VKX0vveemaIvdanIUFsK3ZShUUCXi6SPQmZYnk82PtJUsUY/9hyVi1dRSYw00rC9W8Gt7eoZSFOh23z7Xb+Xk7ilJBkueQrSQNx0slWKa8ZvLHTGP9bqE4uiqGfBy4OC7UqezjkqlQrW2qbS5pxrKin53+00dP1payB4FskYbN8VKyKPdVlGUcTLL7/Myy+/3I8lPnUYErIeICdAnWjrznOKDuO56iUhE3k8Xb811DX3uvUT6/c3+N//2OcQgcTY5sxJrf2cSMGCdlh86RIRHjbWOFaaxbr6lmEfb8IXFEbldMsjC/cLhUL0Vn4YCEcif5PKydT46TkefG2d0vwkGzd8Ca66tELxyASlxWnisTK6VKDxaANbqiBKqHy4zMTpOdavL/G4N0uH99kKbJWmeiZ51j+NFU9+lr/m/WYji9Osf+BJTeNRULQmRpr7rHbPkypdCGsvJNQD+cpjK5KZiSZJk9STuuL8NPXQDOByRe3INJVQurSh2zKZnaKa+7yCH6x4fJ5qaDIonlikfusOenQEQqbZVuTGR0chSWOr83Pj/AVAEU9PkS3n/rKgYpSK2DW/vYVDKmRPk0+sV3hSyTYnVwcdur6XBoKcoPWKqPXbGtJtbHffWV1dZWpqqg+refrxjX2F6AK2O0HzD/9hCFl+gc/n1x3Gc9ULQraXUNd+l05/7nO/yi/+0L+noB2R8R4xrYQ4UjQkQ5SjbCI2sholXaBsEpxYirrgg1x10iwU6vxfEsIwZOtcyP8/94q1YiwqYEoJLxbmECfoyDD92mmS6THqc1M4Bw/fv42tZ8jICquX7zL3yTM8uHCLeKxEtuFLbPGoD0+dfvUUjy5cb3lfP+pI01re3MLjHi2P9Q9u+PVGpqme5USrMDtO+sATLRcUq8LcJPXQpSk1T7SSmckmIcuCYhVPjjYJWboSVLGxrUDWdDkk6Y+0lhpXwmOl5mOu4rd55PQxNt9537/f5DjZ6tpj29aai9b+MckeLjd3kAtEMJ6ZonHLq4AHLVm2k45isdiTbuFBR16yzb+UbXftalXF9jN0vTXU9EkNBL1W057VbLV8n273+Orq6tDAf0AMCVkP0PoNcL9oJWLAgQdpt6+nm12f+ZijvEwzPj6+rTrQL0J25Ws3+P4/+Y+IcRSNYLRPyY+04HCkWDSORGmqtsZMXGY5XWcqHmc0KjSt9E48EcunV275ulpVsq24itbLcr7Zs596AVMu8OjKErXlDW5++Tousxx57QQP37nB3BunsfUMU4hYD4qZZF5xGjs+w6N3bwKweduXDk1QrUpzk9SXPJmZOLPA+tW7JJMjwTy/Vfbbygfb5uKaZU0mk22G829msknI6sGXlUyMNglZfcmXAaNSnpDfoqglW6XLRlDU8owzncQ0HuYqmy/p6ULSLGeigsm/EJM+CuXH8LcqMmTrXlEbf+NjrJ9/DxRoY/ycy5ag2lxBc0LTm1b94ApKKRq3bjefmCzur2SZT8HIS/LPqk9sv8gHo+cBz+Vyed8l252GrreTtFY1LSdYOw1d7/UEgmcV7ef3+vo6zjnGxsb6tKKnG0NC1gMchJC1m987QcRa19MNItQeubHXdP1efYusrFX5wT/9E3z45RsUlaA1GO19Yt64D5k0mNIlaq5G1dYo6ojUORaLs83sL5TQcL6LUdBhvmRrx2PrvpXmjwyfNBHCFtBKuPmlqyx84jnWbj5k9uXjLL93C6Vg7XoY6RP2y//P3nnHx3HW+f89s72pWu52nNhOsZPYspwLR7kccJU7c8DlBRzc8YNAjuLECUkIIYUUnEZIhZDY5MdRLrRcKEe4UBJyvwDBxJJLbKfZjnuTbEmrstKWmef3x8wzml2t+u5qV3re/1gerXafmdmd+ey3fL7VC2cS33PE2o/jtugJWyOAgg3VJG2RJIVTeNaAIOs/aYma6sVzOLVlD77qMEZOgb7buHUg7TegZGTUrOu1A1ajgkcfEFW2VYQ3FiEdtzsYTWsvAzNqSJ+01ovtmh+YWUfymJ26TLm2HbE6HWU6MzCzjqQdsZL1Y4EZdSSPSmd+l+WFPSfTtGvefLUDczJj559F787X0MIhsKNrztlxm9eamjOfc8+VN6JpcN7//GDE96as55yudWL5yI0UhsPhrBTjRBmtZ9pIQ9flcxWrgWAqR8hgsCCLx+NUV1dP+/f/eFGCrMAMVdQPoxNk+YrfQ6FQQb+lFVqQGYZBIpEY0XIj3zpKQTqV4cdf+w3/c9dvCHo0fLpA9wg0TEzNxKODrgtMYeDV4FQ6zix/LQHdQ8QTRKCRMQccvnQs8eKkBIVlZaHLUno7bWkIMNEBHQ8mQmiWdUZW5AxObN0LaPgilsCKLWyg56AlMBJtlpjyV1kpu2B9jL42S3yleyzxFZ1dS/vJOGjQc8Qemm0btgZn1pBss4SJkbBuTJG5M+iyBVlkdi19JzqInTGH3n3H7BuIbBTw4NWFLTvtqjfph5Zxekg5uWU3tSvOxBMOYvYlQQMRChI9/2w84SD+ubOsCGIwQOi8c/BGguj19daxC/gJnXsO3mgI3U5zmH4fwXOX4YmGCNZYtSgi4CN07jl4omH02hrLTSQcIHTOWXiiITxVVdbZ8QcJnnEanqooZjSMME2E5sE3ow5vbQ2pY8cxUxkiSxaSeGU3vvpaTFu4yZo6uY+n/WAjXV1dWTdxd5G5LER3N9YUa7xXpZAbKSzV5AEYnWfaWIeuF6KBYCoKMknuvnV0dFBdXT2l97mYKEFWAkYjyPIJsWJ90y6UIJuou777uBTjA2yaJn96eicPfORbxLwQ8lrpSU0zEZgIzaDGFyBu9JDOQK0vRJ/Zz2x/HSYmAT1ERlimrQir8F52Spr2/zOmwKtB0rCL6DW7VsxJW8pIWu6+y59cwqzF6nwMz4jRc7CVQHWEniO2rUSfVecUnVtHe3sXmgY9hy3xpfs9+KJBInNnYKZT6PMb0AIBas5fjK8qRGheA6YpMHWd8LLFaNURvItMhIDu7n4y0ToC0RriZgeRmTV0H7NSjOFZ1XSeiGeJRznwXMe0xSZ4MIhvPmSZ5dr+YaH6GMn2bmY0nsGpbVZNmy8aIt3TR0PjYk5ttbzQPCE/Rl+KhlWLObnVepwn4MNIppnRuIRTW62UrC/kw+hPUb9yCae2HbGfL0imp4+6lUto32YJ2GBdlFRHN7Xn19LxslWgH5kToO+4QU2kis7jpwAfkVYPib46qiML6O8K4Q14Cc9voP9UJ6GGGlbcf03WDTz3Ju7G5/MRCASmfWorNz1ZLpHCkTzTxjt0fTQNBFM9QpaLjJApxocSZAVmuAhZvrqt4boQi7nGiQiyQnR6ynVA4TuRhBDs2XqIL/ztAwQwqfZbIsl6ORM0A7+mkcKgI9PDTF81nZk4/UaSqCeCiW4nIsWA1xeWCANImZoTNTqZyjDT76Mrk6TWZ7nyy5RfxvbQ0l11ZIOE2cCqnZ9OtOwlWBuhZulc0t196AEfesBHXeNS9EiA8FmL0P0+ek90khR+2jsytLcb6PODtL1u1XIFanpIdvYyZ/UZHG/ejy8SwEhYom5W4yJOvn6C2MIGuo9b0bZwQxKREQRqIiRsQSZd62vPXUjHTksYeQJ+jGQa02UzIX8eOI2CZHsXoNG5bTeg440ESfdkpwt9sQHrDvm3vqqIM9pJbvTGQo4BrHxZTyjgNDQ4tT5ej9MxKuvLAJLtljDTfAOfqXRnDyJjonk9JDsTJAHT46fv6Cn8c+c6N3E30o0+mUxm3Wjdxqa5xqdDDWWeSsjyikqKFOZLecL4hq7nS3lKvzX5t+l0uuzsOCbCcCnLmpqaKf+eLxZKkBWBXMHjDoFLcoVYvi7EYq5PrmEsHxwhBH19fQXp9MxdR6FoPdTOulW3Y4gMEa+OX9cQttV9wKvTZ6bQhYbP4ydjpjGF4GSqgxn+WjsNKdOJlh4wsYWYBqDhtc+js3YtBfjoNpPU4udEqos5gWrQQLMKzuz5jWCb9qNpwv5ZYNqvI9AQwkpzahr0tCXpOLkXE51wQ5WTupy5bC4nXz7CrPMWED8ii+Bt01O/dXPxx4IkO+3ifdtyIjKzmq79doejneoMVIXpto9bf4dtkhocuJH22bVnPtux3hP0OQawM1Ys5uT2N/CGgxgJ6/lkxMwiu3PTcs+3ft9hi7RAfcwRZPJ5A3VRR5AZdt1YsDZGwhZkhl1zFqyLkjhiv67d5OCvi5Gy07NyLJSvamBygNPv6vWQspsbdNcNWVp8BBsGD0Z2R388Hk/Wl6Zcd/rh6pbcabFKJ9fwtpTpyWIx3qHruec4mUw6I6CkOM0XTZOCvdIaCIYSZKMkGrcAACAASURBVGqw+MRQgqxEuGsSRrKDKMVaYPSCrJgNBvL5J0pvVx/f//LT/M/XnyfsA78Gum6ABgGPTlqk6TdNar0R2tMddKXTVPnC+HUvPrkfAgy7ksgEvJolpmR1kdxbgdWh12emmeG1a7t0ax+a3tJI/OBJqhfOwDQEQoP+7n56TnSR6OwGew6lfC7L60zDpxkYQrfFoPytdW762zqdbYlW2y7C7qb0x4L0d+SKrxpS3Vbhe6rbiiIFqgbsJaTQ8gTsomav7myTxcyB2ihJW6RJwRNqqCZxuM1+LeuGFJlbR9cey0esevEc4nuPEWqoJimfz+7mFELP6nQESOw/ah8PiL9yAKuOzuWkbwtHX9S1zXbS97nsMjK2IPRXRxxBZiSt9flrovTZgkyORfLXxZyGB2HfID3hgQhicOaAh1K+OrHc4nR5Ex/LrMdcqwZ3tKUSyG1kKHSdazkx2gaC3KHrMsoq/36sKc9KjKa5TWEVY0cJsiIwVErQMAy6urqci9houxCLxUhCqNgNBoW4+WQyBr/57iY2Xv1f+D0mYR9oumkV2Wug6QIrjWiJivZUnJmBGaREHwHdj4blnK/Z07ulYarbrsJZr/1vq9FDDUEO9bcR0H0kjQxvu/DP6OlIcKotwamjPQTmNnC4eT+RmTH62qzIS8NZ8zj5+nHqFjXQub8NEJiu9Kbmeg1cr+xOayZOWs8lRVJ0dg0dtuhKdtljf2IDnl29rVb0TLfTdd5IwImeySHc4ZnVJI5aQkZ2PYZmxBxBlu4diKjZiUOScXtepN3pab2+tS06v8ERZH57okBoVg19tgiS+2yguxKfFvGX9yHFZ7+dapTiEyBlr11OFQCciJpjtQGku6U/WxCZKJUdqP6qqCPIZBTOXxOjzyXIZARbpifH6ic2Ut3SUFYN7nRYOaY8KzE9WQxyGwhyI6hy+sB4h66X+wQCFSErDkqQlYB0Ou18OKUdRCFbwMfKSKnCUtW1TSRlKYRg+/Ovc9v7NuDRTEJea/C3V7ellG7iRSdppvB7goSkmaumYQoTnxa00oP283lyrm8DFhBWCtEwQdj/ekwPQvOjE2CWr4H5Fyzk0LaDVsrQ3hcjZQmm6tk19LV1o2kQP2QXy9dH6NzfRv2S2bTvtWq+/NEg6Z5+J70p06WaZv0LZCUE27bvBzQ6d9veWRr0nrBTmNb0coK1kYEol20REZlZTfd+S5ike21D1JgrAtVtR6Vckar+U5Yw8gYGLhf9bdlCT/PoJE9ZIkyayOoBn5OSjMyrp6+1E084gJDCZ4YVSXNHag1zYCySrBHr2PY6sjlCphrla6AN1IhJ+w2ApO1f5h6LlLYFo8cl3Bxj3VjYEW6+uhg9PT1OKUEh7WbGE2lxi7PJSnnmpieV4a1FPnuPXIGaK8RHM3R9PA0EUNoJBPnOfTweZ/bs2SVZw1RECbIiItu/3QW/VVVVk34RG0oIlTqdOl5/tmP7TrLugjvJYBLwgK4Z6Bp4PVayUQgDPz6SIkmtN0Z7+hQxT5ioN2yV4ttpQo8dDbMGgg9U75umtd0AZxyPrgkMoXEyHafBZ3URnTXvdHpP9jhCoO70Bk6+bvlmddkRJ68d3amaX0fXYatjsr/TEgbBaivtpvs9ZPqsG/CcFQtp3XGQYE2YlC0gDLs5wLDtNfI1ByCE8xwpuyMzWD+QdnRSl7GQUzeWsL3L/PYQbk2DRJs0XbX2yRPyOxE1SbA26tScyShbqKHa8UeT4i80o4rEUasT1LQFaqi+ikTCSnuGZ9WSPNlFdGGDkwr110RIx3txj0AyXAPGpeBt3/oaoBOorbIbCAa8zzyRIIYdDXM+a7pGqnOwcJPb3FE4EbPqIqPRaNG7BIeyash1px+quDzXiqMYuNOThRSolY68vpumOWz93GiE+Ei1hzJSqus6hmEMEmnlMoEgHo9z9tlnF/z1pgtKkBUBwzDo6enJmmOXSqUwTXPSxRjkF0JSiMmW9VKmU0frz9bX088T9z/Dfz3wDEEd/LaXmFfX0TQTQ2So8limrr1GAq+m059J0uBrsJ4D7JQkA62TCNLCjnyhYaJZQ8WH6Ips8FUBUDWnhp7jVkQqccoSJ6FqK1UYmRGl104tJu0ITKQhRtfhU+gezYmUyURdzfx6Ot+wImWy4L5u8UyOb90PuobXo2OmDSea5zZxNUS2JxpA+8uHAY34nuPOtt4TltCyS7bQA16StjCU74fgjCrHYFaKqvCMKnoOWaLKsMciBepjjiDL2NEuf3XYEWQDqcEwCau8jLRd++WPhpy0p/O42EAqNFgXIx3vpeaseXS9btlb5N9vS6RZ0wKsjR3bdwMagdoYCfu5hVMTVzUwMN0WbnrA50TI3HGH6vmzCEYik/pZHa07/XDpsInWpeXWz6l5nBbuOaUej2dcwn0kz7Sh7FZy09pjmUBQ6AaCfO8rlbKcGOrTVQT6+/sxDCPLl0t+uMoBtyBzR/HkxWU0pq6FXsdQyG+BL/z3du6+5Ft4dQh6TDTdspPw6BDSre5JgI50nHpfLbqAmC/qFCcJBBlzwEfMo0FaaJYlhVyH/WBZOaZp7v9lUz23mp7jnfhCPjoOWpGvjF1IXj23lr6TPeBKU+q2kqieX0/8gCVw+uMyUmYJOU3X6DoqZ0daF8vY7Bq67WjbzGXzOPnKEWYsnU3n3gGxBZARGj5NBpBynfaFI5zatu5H06zoVe8R67XSdlF8sC7iCDJ3J6Y95tupEfOFB9KZSdtmwhty1ZLZYs0ddZJpRY+rizNfjZh8nPs1gjOqSJ7qou7cRXTu2m8dH/t3bnd9KdgSh1udR3TusE13qyOOIJNiM1Abo/+Ede5kTZ43GiJUXZ5jX4aKtIzWT2u0dWkTrZ+bqsjj4u4yL/S1Mp/dijsKNlxaeyJD18caTRvqmt3V1aUGi08AJciKQCQSGWQHMVHvr0Ii1yWF43hMXQu9lnxY6ck2PrP6doQm8HssR30Nga4JYp4A3UYv3ZkUtb4YCaOXWl8dhmkQ8UYdd/2MwHaVB68tsjJO+s9eh52+BHcxvbXNnpiIW5gd2bIf0Kg/vYHWl60wUNfRTgKxIIFYkJqF9YTqIpgpA92r4wkFmN14OoGqEMEZVXadm0bDqih6LEjdijPwBb2kEmkrdez1Ez17IcGaMEYkCgiSXh/BJQvwzKrCj9cynjRNhCkIBz10HYuTaIs7+4o9UUBHoGtW2lXHEpr9B9qtizACEYtQde5peGIhqpZ5QQg0r4eqpXPxVkeILmzATBsIw8QXCTp+XppHd+rLpIDU/V5HkDm1ZEGfk351vp0HfU5Nl1yu7vc6NWJSJGu6RtK2o/D4By5XnoAPM5Wm7vzT6dy5z/00ZEwdr931KkVa994jzmtbjQMaHlednCZTr7MqayjySH5aY7XiyGQyznVBpScHmMy0rfscF3rounye3NcbSaQJIfLag3R2dipBNgGUICsCcqyKG7ftxWR+05SmrmBdZMZr6loo8glVWcv2o/t/zQ/u/hU+TUPTTXRdI6BppIWBrmn0GAlqPVX0mt0kjD68+MkIDV3zYgj5/CCDYMIOewkxULRvYGXxDNMq7Hd3V8q5lKa1KCf6ZKU8NUxg30tHCM2oQvd6OXLUSmH6T/VzZG8H86MRDm+3asrCNWH6OhOcfuHp7PvTASIzovTZqc4F58/nyEuHmbN8Lsd2WeKuZn4N8SMdLFy9iIM7jqJp4PHqmBmTheEgh3YdJzYrRs8JS6zMPX8Bp473Muus+bS9bkXPog0xetq6rbFNWaYdGh7NcHzD2n+3H4FGQDdJmzq6T8dMW+/fOSvDHHu1i0BVyOlcnLvAw4l0mOqGWoz+JL6Alx49hH7GIgLVIUil8Xg0zFCIqhVn4vV7MfqTkMmA309k4Uy84QC9h9rIJJLOsPRgfZVjSiu3BeqrSJ2UFhXWGfFXD8zM9HjlIHIf2IJjxnmL6NyVLdIModupaJz6tO49R5zoWtdrlu1GPg+ySmQ8VhwSTdMIBAIqKsbgrtJyStuOZ+g6DI6YSgoxgUDZXkyM8nhnTTGGKuycTGTdgwy3A854psnELcjkReDEgZP8++ov4dV0vDrouolf1zFEBhMPUU+QXqMXIUzajDbqfPXomo4uoyq2+HI14mX9222kCHg89BgJBAIvXqr1EGnDsqGQYkzXrLu11y7o92kCwxZr9ivh1SDe2jPQGAAkOqzIjyzo94f99Nn1WobtFRatiziCrF92NgYHuv9kDZqMMoXrBwScNEcNVYcdQZaSHZOh7G/QAPNWn8Hh5v328+kIcyAaiCsyaAeJEGnD2ZeT2w8AOsHqAUGW6kthpE2ErtHVahfKR0K0vXqchrNm0/aaJQhnnjWHk68do+GcubS9YgnNGWfO5uTr3cxcVkVbm4amB8n0eOmrmo1nRj0iWI3P7yEVDhFZcRa+kJ/AnBlgGBDwE57fgC8awujrx0xlMOz0Y7C+iv5jVipYuvT7a6JkbOFWt/w0ul7Z71LmdvSMbJHW+sed/Pqt/87f/H4jU418VhzuOjEY+DLp7hwsdyuOYuAu56iktO1oO3lHipjKbfkaCDKZjPOzewIBWIJMRcjGjxJkJWKsZqyFYihT166urpKtYTjcIfRMJsNdn/y/bP7ZK3h1HTQTD4KA7iMtknjwkDT7EMLAp/kJ6EErBalpOVaqFgLrPq5pltu+EJA2DLpFP/VaFSkDaj1VmMIkYWbwaT7mLZ/DkV3HHLd+wEp9alY0beA17BoN1zYZUes43I7TtQnEZsZo32/VKiVt4RSIDtRc9dg+ZbqdQw3XhOiLS2d62+y1dkDApewh4X6XB5h8vPtA9HVmjxYKVoedurW5jadzZOt+Ig1V9Nqv74xAch1DwzZx7T180nnyjlePADq+8ICAlM0L7vFEKbsOzev2EetJ2tusS48wobc9QdexLkKzajm202puqJlfS9fhdmafv5DjL9lRw9Nm0Hmgl1nn1tHWEcAfjmEkA6RnL8Q/qxpPdT0+r4YRDhI9byneoA+jowsj0YfwAJqGf0Y1qTYr4la3/DS6Xt0PHt1JWUpBPh1wdwn6/X5nHmelWHEUi9yZnJVuejtSA8Fohq7L8ywnELgjc/L6/fLLL9PT00MgEBi0BsXoUIKsCAwXITNNsyQf7pFMXcvh4ikjY+l0mh9842m++YX/JqwH8OhW4b1P92CINL1GL1FPhH67Rqzf6CWoh+Q0I8uzS3Om5WRZuuYO8/FqHgJYF6V+sxc8MWYsrKfzsN0hmLQiLosvPIM3XtxHIOon1ZOy12sLMzkKiYH5lvJo6q7/Hdxs1SrJ7kuA3lO2iaktXALRAElbpJgZ26i1PuoILEd8uQRcwnbm9zi1XBqJdunPZa0gXBtxtjlO+zUhR5BJQ9RIfcwRZPVLZnNqzwlqFzXQsd+2q7Bf03DZUJi2SOt4+ZCzx922CPX4XF5l9muZ2oDAkfule/VBj3NvS8Ytgae7BJ40vpUjolKJFPHj3fSciKNHoxzfbnVlVi+oJ37oFA3L53HyZUt81Zo1xPuizK6aQ5oqQhEfqViMwLkhfAEvJPshneK0917EwjVvZiqT2yWYm4arBCuOYjAaT7GpxEjmxUM1iWiaxr59+3jhhRdYsWIFS5cu5dFHH+VrX/sa733ve9Vw8QmgBFmJkBemYhf2j9bUdTKbDNzh783/7xVu+z+PEcJLSAvg13QypOw6LQhoAQKaHx3NGvxtmoT0MKYUc8KKjglhS4NcnWn/v93sol6vIi3ShDVL3Hg16+1f3RCj83AHmq5x6pAlzGS9Ut28Oo7bKbi6+XV0HOlgztKZtO5pzYp2pu0UqUn2iCWAYy8dQkrEnpPdgIZpR2SiM6J02IIsKQ1T84gvbx7xJc9fqCZMwhZ6snguVBN2Hpfus8RXwDWCSIpAd4pTCp5IfdQRZP5okFRPkvqls2nfcwK3FUhaDJi4ym1t26TTvnCiYR479av7PI4Zrew41v0eJ90q0T06ye7s6B4a9Nvrc9/kHTHnc4k5+2/dXRuZRBIzI8iY0LbPqlOrPUPQ8UYr9WfOocP2j1v4sambbplol2A5WHEUi9F6ik11clOesuZYRsV8Ph+madLc3My1116LYRhomkYwGOSiiy5i9erVPPPMM6xcuZK5c+dOy2M4EZQgKxETcaUfDflMXWOx2JD+OJMhyNxdPTu37OHyv72HAD6imh+PpiEwSJGmWo/SY8YRaMQz7YT0ECFPCIEPE0dzDJiFOjuV9U/Oi1v/9Jjd1HutTrrFc06nq60brx1xqZtfy6mD1s06Ydd8haosEePxeYgft2wTwnbEa/ZZszjxujWwO1oXIdGRsBsHLIEorTPMrMNsre5Qy35As4WPtU2mGOWMSXSN3vZsU9ZIfZQeu24rbfuChV2CLC0jahGXDYVdo5Y1OFwKGdeIgtwom8fvcURVqMYysQ3Ewo7gqT9jJu37WrP2KyMGR0RObH0D0BHpjPM4YQdWAlUhyyIESMth4jVhp3tTCuNAVdgZ1yTxBn1k+uXNf+DkS2HpdUfrZHQtK6WaHHRcQnXRQeufCuSmJ3O7wMdLqaw4ikUhPMWmIu77ST7xfvHFF7Njxw42bdrEhRdeSDAYZPv27Xz5y18mHo9TX19PW1vbJO9F5aEEWREYLmVZDBGUTqdJJBLOjMyqqqoRO4E0TRvURVNMZL3CG68d4eNv+xI+PIQ1Pzrg1XQ8mkZGpMmYGU4a7UQ8ERA6NZ4G254hOxXp0bBnTrptKrIf48Zrb/mztzSx90/7iNZH6LJTdbKuKzYjyqmD7WgadByxxxDZ5612Xg3tB6w6sD5b4ISqbP8wDdK2MFh84ens37yfcG3IEVjSYV92clrHw1qou/as63gnbjkZnTEgvmQhfzAWdLZl+u1h2a7IlxQeXpdFhIyyOTYUXp1+OyUoXy5YHSZlCx45cDtcG6H7hFVrKNOewZqQI8j89silmkUz7dmcUD2/jvjh9ixRLOd0us/Jye37Ad2eeWlHjzPWI3yRgCPIUv12zV0s6Agywx4SHqwJ02OLZLk+t3BzLDZckTlNc0XS5Cgll0ibaoLMHeEoleAotBVHMSiFp1ilMpzFhxCCp59+ms9+9rNccMEF/OIXv2D+/PnO3wohOHDgAIcPH1bHchwoQVYkciNQxRBkmUyGRCLhXGzH4q5fqgiZFGKH9h3n3y68GQ8egvgJ6B5MYQCCpNlPSA9hmiZVnmq6jTg+zW/5YWnZoitXQrp/l7s38tabFmlq/bWYhukIm7p5NU49V8dR66Yub8w1c6qJH7O29duF6ZG6sCPIZKRMXqSiM6L02lEeWYNWO6/WEWT18+voPNJB/Wn1dB5qt1K29n6lTPDpsj7Njp5tfgPQ6GntQiomuQ6vq5Beiip3JEhG1OQ8S1/I50TN5PkO10edoeOybi1UE3IEmdyHQCzkCDIZiQq4Im9pe0ST37Um6RU269wFtO48bB2fhoE6NUnGTneaLul2yp4w0HuwzdlvOXLJ60qtpuzUrvtYpG1T3kDVgHAT9r4FayIk2rqyjoHHFV1z3zemiiDLrYcqB8ExHiuOXC+tQqQ81Sio/LjfM/ksPk6cOMG1117LH/7wBx566CH++Z//edB50DSNRYsWsWjRohKvfmqgBFkJKVRUyjAMEonEhNz1iy3IZNri6ME2/qXpBjR0gvjxalb/YspMEdMjJMxeqjxVJIweop4YhjCIeazxRLq9xowQBDy6Y2qquf/N2idboA2Y76MBuubjmqc+hcfnwef1ons86LqGabdemoZAmCamKTDShiXckhkyaQMjY5LuS6Fp0BfvJ51Mk+5Lk0qk8Pq9zFo6E4/fQ/xonGRvEn/IR8PimcRmVhHYf4pUIul0UdbMqabzUDuxhpgzbql2djU9rV0YQprWQsbU8OhWqlOmZU/ttdznT+ywRIuma07kSx6EUHXYifrIaFO4LkK3He1zR9mkIEvb8y+zhZa1zecawi3rvNzpvVT34C5KGT1zm7hKpTx31ekc3bLfer1Y0OnClMjGAcNlbdux5zigEd9zDCmxDbsmzu3wL+d4et2Dw22R5o8GHUHmNDhUh+npzx6l5I8Gs/alUpFDwAudniwGIxWW5/PSGq8VRzl7ik02w9XQmabJ448/zg033MB73/tedu3apawtioR6NxaJfIJHtpSPF/nNzn1BGa83TrEEmSzYP7TvBB++4CYEJgF8eNDx4UUDPOhoupcMaTKin/ZMAl14yGgR0HQyYiCSIYRVMF4XGMM+aoP/e++7vg7Al166ztqWp9i4GN+STdMk2Z2kr6uPZE+SRGeCZG+SxKkeEp0JzIxJ/EgHHr+Xw9sP0d3aRSaZpj/e58yptOrRbLFiizRLQGZH1MK1A4JMplCDsRDdWIIs1Svry1x2FU592eDIm+xmhIGB6O7B3NJbTXcVzzuPcx3LgcfZ27SBiNu81WdwpNkycfV4dUzDdNLOYHV0ys5WiTWkXcvqwMzYUUC3EEza8yw9gYHHOWIzGoQT2aOUKj065rZrqOR6qNF6aY3WiqNSPcVKgVuk5nvPvPHGG6xbt47Dhw/zxBNP8Jd/+ZfquBURJchKyHhFkKwDcbdjT7QLqNCTA+RzvfHaYT76llsxMAngJ0SINGkEJh3iFBmznx6zg6SRwBBJGvQ5zPeficfjHZRylOvUgOP9A3NAD5vtHNXe4N2hC8e8zpvOv8v5+Y5dN5BMDnT4FUOk6bpOqDqUZX0xHPKmmk6l6Yv30fZKK4e2HeHYy0fZ+8IeTGFFz4I6aJolVuVxa9/f5pxLKUbydVG6rSnyiaq+TjvyJmvOfB5HuEm8IR+Z/gE7ELDrvJzH2cX4sYGaM6dAPxYiJTshbaHliwScOq/5q8/gaPMb6D4Ppm2k69QGusRp20sHkdLNivhp+FwRvLRdtK+7RZodlXMLN9mFWqmCLJ9dg3ue4VRgIlYc8tqk67pzbBQ4Rfv5RGo6nebrX/86d999N5/+9Kd56qmnCIfDk7ziqY96Z5aQsQqyXHf9UChU0O6oQuDYV/z+Za56z/12wb2GhkaCXk5ygozoJ230YYgUpplCExlqaWBB4AL8ntGbCEohJsMn3+54POv38a6DAKw77Qujer7rl9/u/PyV3bfm7QgrVdu+2zFd0zTCkTDVNdXMWTSH8/9+hfO4VH+aI7uOMm/ZHPwhP3ed83lgIJKo2RYUnQdOogFHth4YmPFopyxlcb835BuwnLDfliF7xJO1KDvtWTtQgyXtOkI1EXqO24LM3hasDjuCTAqpYM1AV6bTGFA1IMicbdVhR5DJsUmh2gi9rdbrzlpxGq3bDxKIBcnYYlOmpt31d0ebrWghCPo7egANn0uAyqHpuiv6J9fnqwqSSCRKUlReCHIjP9PRrmEoKw7DMBwTU4lpmvT29laMFUexcHeW5hrfCiF46aWXWLt2LV6vl+eee46VK1dOm2Mz2ShBViSG6rQcTQ3ZUO76hUypTXRygBCCA3uP8dPv/i/ff+hXtou9gdBMTC1DSiRJiySYadJmHxkziSYyVGm1LAqeQ0Af27ctR4zZdPTvcX6WQkzy0IE7B/39SCLtmqU3Oz8/uP+OQemRYok0d3QDGDGd4g/6OL3pNOf/171y96DHSJGWi0xnHnzxDTQN/v7WfyZ+tIPu43GrwaA3ie71OIJMFvcHqwZqsGRdViAWpMeyZ3PsN9xWGzJlOtK2gTov17bUQPeoFGSmvS1cF6HLFmRzVi7i+PYDhGfE6JM2GY5IGzCyPdL8hn08hS0EtawbuBRpobpo3gHNper8Gwu5bvLBYLAi05PFQJZ2uGvogIqx4igW0sqiv99+v+c0eiQSCe68806++c1vctNNN7Fu3ToVTSwx6miXkJEiZCO56xd6LfI1R8vBN47zxH88w5MP/xZTWDMQTQxMTNAEppYiLVJkzCQZM4lhJhFmGkP0EyXKAv9KYt6xDZ7NjYoNJ8SGYywi7YpF1w/623w1LBO5oLsvjkKIrNE1E2U4keZezs+v/UHev80k03Sf6KK7tYvuIx30dyU4tecEXcc6MQ0TX9iflQrN5+eVOyIJXI0B7r+VMzhdxfQyUqa7ar9kt6Uvj5gL1oQdQTbrvIW07jxEdE41CbtGbCDd6RZpex2RJl8vNrOGWCxW1man7pqfqZqeHC8jeYqVuxVHMRnJyuL555/n8ssv54wzzqClpYUzzjhjklc8PVGCrEiMJUI2Wnf9YqxvNIIsncrwp+d2ceO/fJ0klrmn0ASCDEITmCRJiiSmmcIw05hmPxkzhSGSRAgzz3setf7ZY17ji6J5wkJsOEYr0nK3uf8u3407X6GxW6TJ6Ib0jStFdGO0kbR82/L9bV88QfexTrqOdtB9Ik78cDvCMBGGIH603alXcxfeD4xIco9Dsr3AXDVd/XYKMXsG5uCOzrQzUN3VWWkX7YeqI44gm7VsPm2vHCE2t5aeYx1Z+yFcHQRbN/6aV7/5Kz6y5f5hzU5HEzWVqbRClga4Bfx0TE8OxUQ8xcrFiqNY5B6b3HFQHR0d3HjjjTz11FPce++9/Ou//quyAJlElCArIbldlvnc9aPRaEnCxKMRZK9u38/PH/8dR/a30d7axYp3nonQTPAKjre18vqWg5aZq+gjbSYRZgbD7McUKfz4WaCfyazgwnGt70XRDBRHiA3HaERaPoE2UqGxW6SBdfz9fj9+v3/SLoATFWmh6jAzz56b97nTfSm6jnTQ09pF59+1ET/SQdfRDroOtzu+ZZpHo7/Lrgdz7mXCmWPp/hzknXfZNbgbdMCew120b4u02rAjyBrOmcfJV49SvaCensOWv9yqy97FBf/+V3n3Z7Sdf8VIg7mjG1Nh2HUhKYanWCmtOIrJcNMZhBD89Kc/5ZprruEd73gHO3fuZNasWZO2VoWFEmRFYiS3fvlhkTUgYzF1bnwrRwAAIABJREFULeT6cgVZsj/FL5/8I//zxAuk+jL0dCWI1oQI1flIakla206wddsukqIPIQw0dDBN0mYSRJoYfuZ5z2C27/RxX4xeFM0lF2LDMZJIyxdVe+jAnc4F3Z1KAesmLb+5SqGWe9OerNRIoSJpvpCf+iWzqF8yi9PevHTQY1O9/XQd6aDz0ClO7W+lrzuBJ+AlGe+jc89xMobpNBp4s0xc7WOiawPzLt2zLe0O0awoXHeezkrbXDZQFaYHS5DNXblo0DqHY7jOv+HSYEPZM+SS65s11Yddj4VSe4oV2oqjmOQem9zU7ZEjR7jqqqt46aWXeOyxx3jXu95VltG96YgSZCVEvum7u7uzvIImw0E7V5DFO3r43mO/5E//byfH9p/C5/cSqw/jrQICGQ63nmDnrldIixQIAzmwMWP0Y4okmhBUe2ZR612AoXs4IjqcG+p8vW5MaysnMTYUYxVpX3rpukEF+7kX83KtXyl0uhPAFw4QO60O/+wIDasXZB0bIQSJk910H+ugY/9Jek/Ead/XSvzQKccvLVQdoq/D7gZ13Pe9g4UbDIxS8gwWaV5/4ccmjSYNls+ewX3zll23yjcrm3LyFBtKkI/1XBfSA3E4KwvDMPiP//gPbr75Zv7t3/6Nxx9/nKqqqoK8rqIwaKLUE6anCTICIjEMg97eXjKZjOVNFQpN+kW2vb2ddNLk8cee5uVt+9j0/3ZSUxdj0dLZaJogbRgcP9HKG/v2kRHpAcMpITDMJGmzHw8mUWZQ7z8djz56fT8akfajE18e765NKu56nxvPGyzcJPlEXe7FXEZZJOUi0oZiqA5PN9fsuN1JpYwnzWSlQ9uJHzxJ/NApkt19nHjpIKneJK27DiMMk7lNp3Nsyz78saAzUWBu0xkcbbEaRDRdRxgm85pO51iL1b370f+9paReZO5z7Y6qufF6vUU3L64U3HM5Ky11my/l6T7XE20UyW1ocNcgCyF47bXXWLduHZ2dnWzcuJE///M/L6vrhsJCCbIiIQVZrqmrEKLk6cl8JPtTPPrQD/nlk39k/95jeH0eLnzbeaSSKTrjcXa89Dpp0YcpTDRhj7IRJmkjiSnSaKQJUkWDfzFeffReYsCQ9hV/G/rgkH9TKeIsk8mMWLA/nAXHUCJtuIt5pYu0oaJo48FIG3Qfbaf7aAcd+9vobY1zavdx4gdOEp4R5WjLPgLVAwPIpSDTPDqfbLkrK/1ZSnJ96OT1odA37kpkqLmclY78XOd+tsdSg5hrZREMBrMyLqlUivvuu4+HHnqIq666is9//vMEAmO7XitKhxJkRcIwDLq6upzuFhk+jsfjRKNR/H7/yE9SBIQQPPurTXzpCxs4cqiV2roqFi9eyKHDRzl+tI20SGGKDKYw0YV1czJFGmFmyIgkQqQJiRj1/tMJeCJjfv3ReolJ3j/rWufnchZlbl8oGQEdS03LUCItn0CD0Yu03PTIZJBr1RAMBrlvxU3D/k0hRZrENEy6j3XQdaSdzn1txA+exEimOfLiHjL9KT7ym+HXVAxyuyfzpeBGunHLtNlU9NAarjB9qpJbgzhUlFzXdTKZzJBWFps3b+ayyy6jtraWRx99lOXLl0/WLilGiRJkRUIIQWtrq2NhIaNjHR0dRCKRSfmWcutND/LrpzZx+GArM2bU0nmy1zJvRWAKy3hTR7cyk8LEEBkMM4UpUgiRwS+CzPCdQcg79rqDsQqxSiE3spH7DXUiFFqklWp+p3s9Y7FqKGUkLZdCjRAbC+5o6nhSt/nO9VQxOh0uBTcdyVeX5j7XnZ2dfO5zn+P888/nnHPO4ZlnnuFnP/sZt99+O5/61Kem9bGrJJQgKyLuOYmAI8jC4bDjHl0KhBB8/7tPce0Vd6NrduG0aWBioONFQ0dggjARwsQQaUwzjUkGzDQevNToC6nyN4z5taeqEHP7+wAl84WSIm0oUZZLPpFmmmbRR0O5IxsTsSOYTJFWLNxiYzzR1JGeO9/5lpR7etttBVToLzhTgVybD7/fj2ma7N69m6uuuoodO3YQj1v+e3V1dTQ1NbFy5UoaGxv5u7/7O2prayd5DxTDoQRZEcn1JALLiC8YDBIKjW7Y9ERpb+/kSzc9zBPffxqAVU3LiVVFeeXlPXQc70VgYgoDU2RsMWanLM00HqFT71lI1DdzTBdEtwiDqSfEZGRDplEK5bBfKvK16+emwMYr0tyF1x6Ph2AwWHA7gkoVabkmnYFAoCSNPfmMToeqQSx0199YKIan2FTBXUeXT8S3tbVx3XXX8dxzz3Hrrbcya9Ystm/fztatW9m2bRsHDhxg586dKm1Z5ihBVkTS6fQgZ/7Ozk78fj/h8NhmOY6HLS27+MT/uY5MxsDvDVBXV8XRY8eZM7eBZCpFdU2MaDTAseNH2b7tVUxh4Dd96EKn2jObGt/8ggkxqHwxNpqC/UplNCJtuDql3MLrUkc2yl2k5dZCTbaIL3bX31jX4vbNKmTEcCrgfu/kRuJN0+QHP/gBX/jCF1izZg1f+cpXqKsb3MHe0dFBVVXVlLleTVWUICsi+QRZPB7H6/USiYy9IH4s/Od3fsL/3fAjXnl5L7qu8+dvWUk6nSYYClgWYmaGYyeOsGvHXgyRRogMCBOfFiPkr8+6WcwVQ881yxVhMPWEWDFTTOXOaOqUAOdmXk6F1+Ug0nJroYoRMSwUuSJN/lwsN/py8hQrR0aqo9u/fz9XXHEF+/fv55FHHuGd73ynOnYVjhJkRUR2wLjp7raGIMdisaK8pmEY3H7bQzz0wDepqoqyZPESkqkkHR0dVNfGmDmrjsNHDvH6KwcwRAYh0ghh4NeihAMNaNr4v7XnCrGDh3YAlVtcnK87UNWzDIi0dDo9qLgYyvt8l0qk5aYnK/W9M1LkFMZ3vivZU6zY5DbD5M7mzGQyPPLII9x1111ceuml3HzzzUX/gq8oDeX5VW0KM9SA8Ykiv21edeXN/OmP2wGYPWcmbxzczVlnLUZ4wrS2HWXHjl0IYdqdkwZ+PULIPwN9DKauueSLiI3kQl/ON215M5VO6WqQ82DS6bQTMQyHw3g8noo430MJrtEY2o6WqWTVMNJ4KPnvaKdM5Ka2w+EwXq+3Yo9PoRlOqAoh2LlzJ2vXrkUIwTPPPMOqVavUsZtCqAhZEckXIZNu/dXV1QV7HSEEiUQfl378ap7+n2epqopxwQWr2L17D7V1VWzf+hoCYfmJCQOEwIOfSGAmuj5+g8WxpiZHcqGf7Jv2VCjYLyZjrROr9KkDYyW3oWG6WTWMdL6lIANUVCyH3IhqrvltX18fd999Nxs3buT666/ns5/97JQwx1VkoyJkRWSoAeOF0sDyAphMJrniihto3rwNgHnzZ/Lsc7/FzGjs349lZ4GJKTL49TABXx1ez/h90MZbI6ZpGl6vN6uGplwiabkF+zLqoxicQhlt1Gc051umPiWVKNKGcpIv93UXmqHOdyaTIZlMZn05zWQydHd3T8vJA7m4u0tzP1tCCH7/+99z+eWXs2DBAjZv3szSpUsnecWKYqEiZEVECgw3fX199Pf3T8gPRhbfCiHYtOlPXH75dex+fT86Xjx6AFNk0AAhLK8xhMCjBQj7Z+AZ45gjN6Uq1i9lJC23YF9GfRQW7ptFsTpL5fnObSCQlLNIk0J1KqQnC81QY31gcLPIcN54clj7VDuuI1lZdHZ28sUvfpGf/vSnfPnLX+ajH/2oiihOcVSErIgMFyEbjzO4/Dtp/gjwT+/6d5JGF1gSjIzZC0KgoQMCDR/RwMxxC7FcEQbF75osRSQtt2B/ukY1hiJXqEYikaJ1B8rz7SafLcNwkTR50y4VuenJaDSqIqouRvIUk+dNkq95INfHcbJLGgrJcFYWQgh+/vOfc9VVV/G2t72NHTt2MGfOnElesaIUKEFWYtwFmqO9mLgvVvLvdF3na197lL7McVavXk1tbQ1GJsPzz72IIQwC3jBBbz0efXwzM/MJMZg8C4tCiTRAFewPQ77uwMmwInBHSdxrG06klWI0lCpKH55cT7HRCvmRmgdG+oy7BXo5nwv38ckn5I8dO8bVV19NS0sLjzzyCO9+97vLen8UhUWlLIuIvLm5SafTdHd3U11dPeI3andEzB3O1zSNp5/+NR/4wL8RjUaYO3c2dXU1VFdX8xd/8Vbe+95/oq6ujkAggMfjYdHMd4y41qEEmKRSvMRGSndKPB4PgUBA3Uxt8jU0VEL6rVQGp7meWUrIZ1PK41OpzSJyJFQ+zzXTNPn2t7/NTTfdxAc/+EHuvPPOgjZ+KSoDJciKSD5Blslk6OrqoqqqashvjlKIyZsNMOgmsm/ffh5+eAOmaTB79ize9KYLOe+85c6NNJ/Yq65aOOZ9qBQhNhzuOh93WkAylVIh46EUdWKlpNCjoQzDoL+/37EiqPTjU2jKwVPMfb7dAl0iU9rFjJ4OxUjHZ/fu3Vx++eW0tbWxceNG3vrWt06r649iACXIikg+QWYYBvF4nFgslrd43J2aFEIMKw7cN4qRCtLHKsamghAbrmC/3C04SoFpmiSTSSe9NJUbGsYi0uSNW9M0J70t6wxVRHWAfN2l5XR8Jns8VD4rC/fxSaVSPPjgg9x///2sW7eO66+/nmAwWJDXVlQmqoasiAxV1A/ZERr5/1whNtQ3OLfQGKkgfToKsdHYEOSrSZPNEu76pHI0N50o7hsFMC1G1oy2Rim3kBys8+73+1WHm4tKML8drg7Rfd7d53ykma2jJbepIRQKZV37t2zZwtq1a4lGo/zud7/j3HPPLbvjpyg9KkJWZHIv8EIIOjo6CIfDBIPBrBoxmVIb6ltabmdgIBAY8kY6XYVYoQv25cVbmvwWYmzMZJJr06CMb7MxDINEIoFpms6Xoko/54VkpPmKlUghx0ONZGXR29vLl770Jb773e9y22238ZnPfKbij5+icKgIWYmRYsv9TU0KseE+5KMVGtNViLkL0vO12Y8XeVPOjaTldvqVeyTNnd5WNg2Dye0ODIfDgyJp7vNerqOhikWup9hUsokZLno63DnPjaTJ99BQVhbPPvssV1xxBcuWLWPr1q0sWrSo1LuqKHNUhKzIpNPprNokIQTxeBxN0/D5fMN2AeVzSB8qojEdhRhkpwYm8xt7vlqVcoiq5AqNYDBYVnU+k03uZ2ws6dvR1CHm3rQr8biP5Ck2nRhNF7fX6+W5557D7/ezcuVKdF3n+uuv5ze/+Q0PPPAAH/jAB6bt8VMMjxJkRUYKMnfXpLxBSmStg9frdS7iMqIhIz7SwiKXsQixqSLCIH/BfrkJjckUablR1elQJzZWiiE0KtWSIR+5Yj43/aawru+JRAKwhJi8dv/DP/wDzc3NgBVNrK+v50Mf+hBvectbaGxsZP78+WV73hWThxJkRSadTpPJZAZ5iUH+G7YbGUWTkTT3B3i6CrHcgv3h6ujKkVKINHfB9XSPaOQjt7u02EKj0kSa8lwbmZGsLPbv388NN9xAPB6noaGBjo4Otm7dysmTJwH44Ac/yPe///3JWr6iTFFfd4qIaZpcd911LF++nMbGRpYsWZJ1g3V3AKXTaWcAr4yYySiHjKa5L9zDMZUEmKQYBfuTgaxJG67Tb7w1aapObHgmkp6cCENNmRjLaKhSibRy8BQrZ+R7qK+vL28Ht2EYbNy4kfXr13PJJZdw6623Eo1Gnb89fPgwW7duJRaLTeZuKMoUFSErIn19fdx22200NzfT0tKCEIKVK1eyatUqVq1aRVNTE5qmcccdd9DW1sY3v/lNxwvKXQw6XCRNXrjd6c5KEynDUcyC/XJmrJG0ZDLp2KDkvocUOO+hcq6DGo9vVqH2odw9xcqB4VLcQghefvllLrvsMpLJJBs3buSCCy5Qx08xJpQgKxGmafLGG2/w4osv0tzczKZNm2hpacE0TaLRKGvWrGHNmjU0NTUxa9asEQdjTwdT03Ip2C8XRhJp7kYReTOtxPNeSHJrDSutDqoUIq0SPMUmk5GsLPr7+7nnnnt45JFH+PznP88111wzZQ2WFcVFCbISk0ql+PrXv8769etJJBJ8+MMf5oILLmD79u1s2bKF7du3U19fz8qVK2lqaqKxsZFVq1ZRV1c3bURaJRTsTzbum6g8p/LGnWtyKaOnhXYiL2dyXdIrrdZwOHJFWr7zPhoH+qnoKVZohhOrQgj++Mc/cvnllzNr1iw2bNjAWWedNckrVlQySpCVmP7+fs455xz++q//mptvvpl58+Y5v5P1CTt37mTz5s20tLTQ3NzMrl27mDdvnpPqXLVqFStXriQWixVEpMkb9mTfrCu9YL8U5N5EpVjNfcxoRgRNVZE2HZsaxjoaSjY2qBR3fvL50rnFajwe5+abb+bJJ5/kzjvv5BOf+MSUf48pio8SZJNAIpEgHA6P6rHywrBt2zaam5vZvHkzW7Zs4fXXX2fx4sVOBG3VqlWsWLFixHTDWG/WpbjI5BZbV2rBfjHJFatjvYlOB5E2GrE6nSikA/10Qhbt52v8EELwi1/8gquuuoo3velNPPjgg1lfqhWKiaAEWQUihKC7u5utW7c6kbSWlhYOHDjAOeeckyXSli9fPuKNezJFmnuUz3SJZoyFYorVqSLSctOTKuIzmNyxa36/H0CJNBduQZ+vw/T48eN87nOfY9OmTXz1q1/lve9977Q4LorSoQTZFEEIQXt7Oy0tLVkirbW1lXPPPZdVq1bR2NjI6tWrOfPMM4dtox9L+sOd7hwLuRYN0z2akQ93Z2CpLAgqTaSpgvThGa2nmDzvubVpkqks0nLHQuUKetM0+c///E9uuOEGLr74Yu6++25qamomc8mKKYoSZFMYIQQnTpxg8+bNNDc3O/Ybvb29rFixIiuStnjx4mFvrqO13xjJN0kV7I9MuXUGlqNIUwXpIzNRT7Gp1Cg0FO4vhvki9Hv37uXyyy/n2LFjbNiwgYsuuqji9lFROShBNs0QQnDo0CE2b96cFUkTQtDY2OiItKamJubPnz/sBXwsIk3XdWc4ryrYz89E68RKyWSJtEo6RpNFbgq3kJ5ilTZ1YCjyHSO3VUU6neZrX/sa99xzD2vXruXGG28kFApN4ooV0wElyBQYhsG+ffscj7Tm5ma2bdtGMBh0Up1SpI3GI819s5ZjoyRu1/JK/VZdaPINka/E1FuxRZq73rBSj1GxmYwUbqWJNMMwSCQSQ1pZbNu2jbVr1+L3+9m4cSMrVqxQ7zNFSVCCTDEIeYF99dVXszo7x+qR1t7ejs/nc7yyvF5vVq2KZCqkPsaL2/zW6/USDAanVOqtECLNnXpT6cn8lFsKt1AlDoVe03DD0hOJBLfffjvf+ta3+OIXv8jll1+u6loVJUUJMsWokFGcHTt2ZNWj5fNICwaDrF+/nvb2dp5++um8NVDToT5lOPLV0k0Hd++x+mUZhuGkudU4n8GMVJBeToy1xKGQHd3uyGFuY4MQgv/93/9l3bp1LF26lEceeYTTTz+9IK+rUIwFJcgU48btkbZ582Z+97vf8cwzz9DZ2cn8+fO56KKLWLFiBatXr+b8888fMX1SaUa242EqO8iPl3wiLZPJZD3GPW2gUs99oXFHVyvVMqbYo6FGihy2t7dz/fXX8/TTT3Pffffx4Q9/uOKOoWLqoOKxinEjoxarV6/m2Wef5Ze//CU+n4877riD1atXs337djZv3sw3vvGNUXmkuevLJLkX63Q6TSqVch4/GUa24yF3SLrf7ycQCJTtekuJFFe6rjtRMbAEuM/nc8RaKpWa9O7OciA39RaJRCo2teY+j5J8Ii2ZTOb9m6HOfW5dpizad1tZ/OQnP+Fzn/scf/VXf8XOnTuZNWtW6XZcociDipApJowQgre//e00NTVx4403UltbO+j3hfJIg/KcNjAcU71OrBDkdk/mS0+OJd05VUWa20V+Ok20GMu51zSNdDo9ZOTw8OHDXHXVVezcuZOvf/3r/P3f//20OIaK8kcJMkVBMAxjTCKj0B5pxTayHQ9yXqCMZCjPtcFMdBLBeETaZAv08TBRT7GpyGhS3e3t7WzYsIGVK1fS2NjIc889x5e+9CU+8pGPsH79emKx2CStXqEYjBJkirKh0B5pMk1Y6i4vd50YMGgensIiN3JYKJExlURaMT3FphK59XSyo7ulpYWPfvSjHD16FLA+9ytXruSiiy6iqamJpqYmli5dqiLWirJACTJFWeP2SJMibdu2bYRCoSyRtnr1ambOnDkmj7RiiLRcryxVJzaY3BqoUnSYVqJIU2OhRsad6s5nZZFMJrnvvvv49re/zZo1a5gzZw7bt2+npaWFffv2AfDzn/+cf/zHf5ysXVAoHJQgU1QUbo80me5saWlh+/btzJgxIyvV2djYOKRHmvv5RivSvF7vkPYb7hEs5eADVY4Uc1D6eNdTjiKt3DzFypWRrCxefPFFLrvsMurr63n00UdZtmxZ1t93dHSwdetWVq1apWZTKsoCJcgUFc9wHmnz58+nsbHRMbJtbGwkGo0WxH5D3qBTqZSazTkClWLRMJkiLVewqlR3foQQ9PX1DSlYu7u7ueWWW/jhD3/I+vXr+eQnP6kEraIiUIJMMSWRF21pvSFF2u7du1m8eLETQWtqaiqIR5qmafh8vilrZDtechsbJntQ+ngohUirFME6mciaUNllmitYhRD88pe/5LOf/SxNTU189atfZf78+ZO8aoVi9ChBppg2CCHo7u5my5YtWSOhDh48OKJHmpuenh4n1TmakVCVbGQ7XqZ6tKdQIm2kcT4Ki5G6TFtbW/n85z/P888/z0MPPcTFF188Zd5riumDEmSKac1oPNJkZ6eu69xwww1kMhkef/xxJz3pptgDtisBaYA73aI9YxVpUoyVQz1duZKvy9TdAGKaJt/73ve4/vrr+ad/+ifuuece6urqJnHFCsX4UYJMocjB7ZG2efNmNm3axB/+8Af6+/tpaGjgXe96F29961tZvXo1Z5xxxoiiqtKMbMdL7nxOFe0Z31ioSj3/hcadxs3XZbpv3z7WrVvHoUOHePTRR3n729+uBK2iolGCTKEYAtM0+da3vsX1119PV1cXn/rUp7jgggvYvn07zc3NbNmyJcsjrampiVWrVo3aI63cjGzHi/JdGx25x8nv9wMUfH5jpTOSlUUmk+Hhhx/m7rvv5lOf+hRf/OIXCYfDk7hihaIwKEGmUAxBJpOhqamJc889l7vuuosFCxY4v5M1ZG+88UaWka3bI809Emo0HmmTZWQ7EdzWA9MpPTlWRvIUK/aQ7UphJCuLHTt2sHbtWjRNY+PGjTQ2NpbF50ChKARKkCkUw9Db20skEhnVYyfTI63UIi3XKytfPZ1iYp5i00mkuZsb8h2nvr4+7rzzTh577DFuvPFGrrzySvV+U0w5lCBTKIrISB5pUqCtWrWKlStXjsojrRBGthPZH3eRtXTZV1GKbIrVZToVRZp7YHo+K4vnn3+edevWcdppp7FhwwYWL148yStWKIqDEmQKRYmRHmnbtm3Lst/YvXs3S5YsyYqkjdYjzTTNrHTnUEa2E/FIU6N8RkepPcUqVaSNZGXR0dHBTTfdxH//93/zla98hY985CNlsW6FolgoQaZQlAFCCLq6uti6dWtWuvPgwYMsW7Ysy8h22bJlI0alxjJtYCSRpkb5jI5y8hQrZ5Emo4d9fX15B6YLIfjZz37G1VdfzV/+5V9y//33M3v27JKsTaGYTJQgUyjKFOmRJlOdsrOztbWV8847z4mkNTU1ceaZZ45YQzYWkSaFRCqVIplMqvTkCLjTbuXqKVYOIi03ehgKhbKO05EjR7j66qvZtm0bDz/8MP/4j/9YdsdRoSgWSpApFBWEEILjx487qU5pZNvb28uKFSuyRNpoPdJy0525lwRd1wkEAk4UQ90gB8hNuwWDwYqKHpZKpI1kZWEYBt/61re4+eab+dCHPsQdd9xBVVVVQfZxKnH77bfzox/9iL1793LJJZegaRrxeJy+vj7Wr1/P0qVLJ3uJigmgBJlCUeGYpsnhw4d58cUXsyJp4/FIM02TRCKBYRhomoau65imOSWNbCdCPgf5qTJUfrQizW1oO9x+D2dlAfDaa6+xbt062tvb2bhxI29+85unxHEsFpdeeimdnZ088cQTzravfe1rrF+/nt27dxOLxSZxdYqJoPqGFYoKR9d1Fi5cyMKFC7n44ouzPNKkSHvkkUfYtm0b4XA4r0daX18f99xzD7W1tXz0ox8lHA47AiOfkW0qlapYI9uJMtWbG9znU5JPpEmDW8hvwQJkWVlEo9Gs50ylUtx///08+OCDXHnllVx33XUEg8HS7WiF8vzzz7N27dqsbXPmzKG1tZXXX3+dpqamSVqZYqIoQaZQTDHkDXXp0qUsXbqUD3/4w46geuWVV5x057333su2bduIRqPouk5nZyeXXnqpk36TIkOmKXVdd+YI5jOylSkpKF8j24mQ29yQKzCmMqMVael0etDfer1eOjs7SafT1NbWIoSgubmZyy67jKqqKn7/+9+zfPnyin9/lILW1lZ2797NW9/61qztzzzzDLNmzWLZsmWTtDJFIVApS4VimvLqq6+ybt06fvOb33Deeefxpje9ic2bN/Pyyy8X3SOtkkRasTzFpiIycpbJZBwRbxgGX/ziF3nsscdYtGgRM2fO5KWXXuITn/gEt9xyC/X19ZO97IrhySef5GMf+xidnZ1OqcCTTz7Jtddey49+9CMVHatwlCBTKKYhiUSC+fPnU1NTwwMPPMCaNWuc9GQxPNImy8h2opTaU6xScYtWIKsjVwjB3r17eeKJJ3j++efZv38/J0+eJJFIALBkyRKampr45je/qWZSjsCVV17Jr3/9a6644gr6+/v5wQ9+wKpVq7j33ntVuncKoASZQjFN+cMf/sCqVasIhULDPm4oj7RDhw5xzjnUshJJAAAJv0lEQVTnjMsjrRRGthOhnDzFyp2RROvJkye57rrr+O1vf8sDDzzA+9//foQQvP7667S0tNDc3MyePXv4+c9/XlZivBxpamriPe95DzfddBMAbW1tnHPOObS0tHDaaadN8uoUE0UJMoVCMWYm0yOt2CKtEjzFygG3lYXsNJU1hmDV3P3whz/kC1/4Au9617u49957VXpyAnR3d1NXV8evf/1r3v72twOWGK6rq+Mb3/gG73//+yd5hYqJogSZQqEoCLkeaTKSlkgkxuWRNlYj24l6pFW6p1gpGanT9MCBA1x55ZXs2bOHRx55hL/+679WonaC/OpXv2LNmjXE43Enqv3HP/6Rt7zlLTz33HNcdNFFk7xCxURRMXiFQlEQNE1jzpw5rFmzhjVr1gCWyDl06BCbN29m8+bNPP7441x99dWOR5qsR2tqamLevHlZqS5N0/B6vVmpQinSZLoznU6TSqWcx+drGhhJCOR6irktPxTZ5KZycztNM5kMGzZs4I477uDjH/84P/7xj4lEIpO44qnD7373O1auXJlVYnD06FHAsr3o6emhpaVFCbMKRkXIFApFycjnkdbc3Ox4pMl6NCnSZs6cOaIwytc0MFoj26nuKVZI3Knc3E5TIQS7du1i7dq1ZDIZNm7cyOrVq9WxLABbt25l48aN/OQnPyEQCPC+972Pe+65B6/XS29vLx/60IdYunQpM2bM4DOf+YyacFDBKEGmUCgmlXweaVu2bGH79u00NDSwcuVKmpqaHKFWW1s7YqozX7ozV6TJsVG6rhMOh1V6cgjc/mv5Urn9/f3cfffdbNiwgeuuu46rr746q5ZMoVCMDiXIFApF2SHTiDt37nRmdjY3N0/II00a2abTaTKZTNbvK9UjrZgMZ2Uhf//CCy9w2WWXMXfuXDZs2MCZZ545mUtWKCoaJcgUCkVFMFqPtKamJs4777xB6cedO3cSi8WoqanB5/MRCAQAppyRbSFwNzjks7KIx+PcdNNN/OQnP+Guu+7i4x//uPJnUygmiBJkCoWiYsn1SJMi7dChQyxbtozGxkaWL1/OK6+8wre//W0+/elPs379+iE9xabqtIHRkm9oujv9KITgqaee4qqrruLNb34zDz74IHPnzp3EFSsUUwclyBQKxZRCCMGpU6doaWnhu9/9Lj/+8Y9JpVK86U1vIpPJsHLlSsfIdrQeaVKkye7OcjOyLQRug9d8DQ7Hjh3jmmuuYfPmzXz1q1/lPe95T0Xup0JRrihBplAophwdHR1ccskl/PSnP+Vv//Zv+epXv0o0GnX80dweaStXrnQaB1atWlVwj7RyF2kjTSUwTZPvfOc73HjjjXzgAx/gzjvvpKamZhJXrFBMTZQgUygUU450Os273/1uLrnkEi6++OK8YijXI62lpYUtW7aMyiMtH6U2si0EbtuPfFMJdu/ezbp16zhx4gQbN27kbW9726SvWaGYqihBplAoFAzvkRaJRByRJtOdo/FIc4s0me4cziOtVCLNbWXh8XgIhUJZVhbpdJoHH3yQ++67j8suu4wbbrhhxJmnCoViYihBplAoFEPg9khzj4N66aWXaGhoyIqkNTY2juiRBhMzsi3E/kgrCyGEU7TvtrLYunUra9euJRQKsWHDBs4//3wVFVMoSoASZAqFQjEGZCfijh07surRXn75ZRYsWDBIpEUikbIQabmzOkOhUNbz9Pb2sn79er7zne9wyy23cNlllymzXIWihChBplAoFBPE7ZHmjqTt2bOHJUuWZKU683mk5Xu+3Lmd47XfGI2VxW9/+1vWrVvH2WefzSOPPMKiRYsKdmwUCsXoUIJMoVAoisBoPNJkJG3ZsmVZqcOhnm+sHmkyKjaUlcWpU6e4/vrr+dWvfsX999/Pv/zLvyiDV4ViklCCTKFQKEqE2yNNdna2tLTQ1tbGeeedlxVJG6tHWj6RJvH7/Rw9epT58+cTCAQwTZMnn3ySa6+9lr/5m7/hvvvuo6GhoZi7rlAoRkAJMoVCoZhEhBAcP348y35jIh5p6XSavr4+hBBOtMs0Tf7iL/6CgwcPcvbZZ2OaJseOHeO2227j0ksvVcPAFYoyQAkyhUKhKDOkR5rbfmPr1q1ZHmlSpEmPtI6ODm699VY++clPsmDBgiwrCyEEmzZt4oknnmDbtm3s27ePtrY2p9OysbGRd77zndx2222TvOcKxfRFCTKFQqEoc2Rqcu/evVmRtG3bthEOh5k3bx6HDx+mr6+Phx9+mPe9731OdEwIwSuvvMJll11GIpHgG9/4Bn/2Z39Gb28vW7dudQa1h8NhHnvssUneU4Vi+qIEmUIxSu666y5++MMfsmvXLl544QVWr1496DEvvPAC73jHO7jwwgt529vexvr16ydhpYrpgBCCAwcOcMkll/Dcc8+xfPlyGhoa2LRpk+ORdv7557Nv3z6eeuoprrnmGq699lr8fv9kL12hUOTBO/JDFAoFwHXXXUdvby9+v5/du3cPEmSZTIZnn32WVCrF9773PebNmzdJK1VMB/bs2cPq1asJh8P813/9F+973/sAsjzSnn32WX7/+9+zadMmzj777ElesUKhGA4lyBSKMSCE4PTTT2ffvn2DfvfjH/+YmTNnsmjRIiXGFEVnyZIl3HLLLXzsYx/LGvYdCARYvXo1q1ev5v+3d4cqsUVRHIf/miZYhAHBMgpiFYNBGDXpAwjCPILVZ7DafBgRJojOBJMgGGyDgmmqJg/cIAiXe7kcRVgM9/vaaSv+WOyz9/HxceGEwFcIMmhpOp1maWkpTdP8EWQvLy9ZXFzMcDjM7u5u0YT8T+bm5nJyclI9BvBD3AAILY1Go/T7/b9uyC4uLrK/v5/RaJSdnZ2iCQGYVYIMWrq/v8/GxkZ6vd5vQXZzc5O9vb1Mp9M8Pj4KMgC+TJBBS03TZH5+Pqurq3l+fv58I3AymWRtbS3j8Tjdbjfr6+vVowIwY5whgxZeX1+zsLCQJOn1emmaJk9PTxmPxzk6OkrysSmzHQPgO2zIoIXb29tsb28n+fiLbXl5OVdXV+l2u+l0Okni/BgA3ybIoIXhcJitra3P75WVlVxeXubg4CBJ8vb2lru7u/T7/aoRAZhhggz+4eHhIYPBIGdnZxkMBplMJkmSzc3NnJ6eJvm4wf/w8DDv7+85Pz/P9fV14cQAzCJPJwEAFLMhAwAoJsgAAIoJMgCAYoIMAKCYIAMAKCbIAACKCTIAgGKCDACgmCADACgmyAAAigkyAIBiggwAoJggAwAoJsgAAIoJMgCAYoIMAKCYIAMAKCbIAACKCTIAgGKCDACgmCADACgmyAAAiv0CiH8YjePQ1OMAAAAASUVORK5CYII=",
+      "text/plain": [
+       "PyPlot.Figure(PyObject <matplotlib.figure.Figure object at 0x7fb41d3a6dd0>)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO: Saved animation to /home/juser/tmp.gif\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img src=\"tmp.gif?0.32854563172234674>\" />"
+      ],
+      "text/plain": [
+       "Plots.AnimatedGif(\"/home/juser/tmp.gif\")"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pyplot(leg=false, ticks=nothing) #Este código genera una gŕafica para cada valor de S en función de M y R.\n",
+    "x = y = linspace(2.0, 80, 90)\n",
+    "zs = zeros(0,90)\n",
+    "x0= 50.0 #Se utiliza otra condición inicial.\n",
+    "@gif for i in linspace(1, 100, 100) #Se construye el .gif con 100 imágenes también.\n",
+    "    G(x,y) = (y*(x0)^2)/((((y-1.0)*(x0^2))/x + i + x0))-x0\n",
+    "    title!(L\"Puntos fijos del mapeo\")\n",
+    "    p = plot(x, y, G, st = [:surface, :contourf],xaxis=(L\"M\",(-1.0,100)),yaxis=(L\"R\",(-1.0, 100)),title=\"Puntos fijos del mapeo para distintas S\")\n",
+    "        \n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Distintas S](Figures/S.gif)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Bifurcaciones\n",
+    "\n",
+    "Una vez observado el comportamiento del mapeo en función de sus parámetros se prosiguió a encontrar para varios parámetros $R$ y $M$ el valor de $S$ para el cual la población desaparece"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:51.372051",
+     "start_time": "2016-12-05T07:08:51.360Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "diagbifurc"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "    ciclosestables!(xx, f, nit, nout, cc)\n",
+    "\n",
+    "Esta función itera el mapeo `f`, de una variable, `nit+nout` veces, \n",
+    "usando como condición inicial `x0=0`; los últimos `nout` iterados \n",
+    "actualizan al vector `xx` que tiene longitud `nout`. `cc` es el valor\n",
+    "del parámetro del mapeo `f`. El mapeo `f` debe ser definido de \n",
+    "tal manera que `f(x0,cc)` tenga sentido. La idea es los últimos \n",
+    "`nout` iterados reflejen los ciclos estables del mapeo `f`. \n",
+    "\"\"\"\n",
+    "function ciclosestables!(xx, f, nit, nout, cc,x0)\n",
+    "    @assert nit > 0 && nout > 0\n",
+    "    \n",
+    "    # Primeros nit iterados\n",
+    "   \n",
+    "    for it = 1:nit\n",
+    "        x0 = f(x0, cc)\n",
+    "    end\n",
+    "    \n",
+    "    # Se guardan los siguientes nout iterados\n",
+    "    for it = 1:nout\n",
+    "        x0 = f(x0, cc)\n",
+    "        @inbounds xx[it] = x0\n",
+    "    end\n",
+    "    \n",
+    "    nothing\n",
+    "end\n",
+    "\n",
+    "\"\"\"\n",
+    "    diagbifurc(f, nit, nout, crange)\n",
+    "\n",
+    "Itera el mapeo `f` `nit+nout` veces y regresa una matriz\n",
+    "cuya columna `i` tiene los últimos `nout` iterados del mapeo\n",
+    "para el valor del parámetro del mapeo `crange[i]`.\n",
+    "\n",
+    "La función `f` debe ser definida de tal manera que `f(x0, c)` \n",
+    "tenga sentido.\n",
+    "\"\"\"\n",
+    "function diagbifurc(f, nit, nout, crange,x0)\n",
+    "    xx = Vector{Float64}(nout)\n",
+    "    ff = Array{Float64,2}(nout, length(crange))\n",
+    "    \n",
+    "    for ic in eachindex(crange)\n",
+    "        c = crange[ic]\n",
+    "        ciclosestables!(xx, f, nit, nout, c,x0)\n",
+    "        ff[:,ic] = xx\n",
+    "    end\n",
+    "    \n",
+    "    return ff\n",
+    "end\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:54.970074",
+     "start_time": "2016-12-05T07:08:52.718Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: scatter not defined\nwhile loading In[4], in expression starting on line 16",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: scatter not defined\nwhile loading In[4], in expression starting on line 16",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "Ict(x,m, r,s) = (r*x^2)/((r-1)*x^2/m + x + s)\n",
+    "\n",
+    "M=63\n",
+    "R=20\n",
+    "Ict1(x,s) = Ict(x,M,R,s)\n",
+    "\n",
+    "crange = 0:1000\n",
+    "\n",
+    "ff = diagbifurc(Ict1, 1000, 256, crange,50); \n",
+    "cc = ones(size(ff)[1])*crange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "cc = reshape(cc, size(ff));\n",
+    "\n",
+    "scatter(cc, ff, markersize= 0.05)\n",
+    "xlabel!(L\"S\")\n",
+    "ylabel!(L\"N\")\n",
+    "title!(\"Mapeo de SIT con M= 63 , R=20\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<img src=\"Figures/mapeo.png\" width=\"600\">"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:55.595287",
+     "start_time": "2016-12-05T07:08:55.581Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapins (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function intermap(M, R)\n",
+    "    m1(x, s) = mapins(x, M, s, R)\n",
+    "    srange = 0:2500.0\n",
+    "    #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "    ff = diagbifurc(m1, 300, 10, srange, 1000); \n",
+    "    cc = ones(size(ff)[1])*srange';\n",
+    "\n",
+    "# Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "    ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "    cc = reshape(cc, size(ff));\n",
+    "    return ff, cc\n",
+    "end\n",
+    "#Mapeo\n",
+    "mapins(x, M, S, R) = (R*x^2)/((R - 1)*(x^2)/M + S + x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:08:59.520160",
+     "start_time": "2016-12-05T07:08:57.758Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Int64}(Signal{Int64}(50, nactions=0),\"M\",50,1:100,\"d\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "Interact.Slider{Float64}(Signal{Float64}(50.5, nactions=0),\"R\",50.5,1.1:0.1:100.0,\".3f\",true)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" />"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {
+      "comm_id": "ebf7a472-b6b0-43ff-aa5f-ffa8581f91dc",
+      "reactive": true
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@manipulate for M in 1:100, R in 1.1:0.1:100\n",
+    "    ff, cc = intermap(M, R)\n",
+    "    scatter(cc, ff, markersize= 0.5, legend = :false, title =\"Diagrama de bifurcacion\", xlabel =L\"s\", ylabel =L\"x_{300}\")\n",
+    "    xlims!(0, 2500)\n",
+    "    ylims!(0, 100)\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "También hacemos el análisis del exponenete de Lyapunov"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:09:02.343432",
+     "start_time": "2016-12-05T07:09:02.223Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "mapeo_liap_all"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "doc\"\"\"\n",
+    "    iterado(F,x0,n)\n",
+    "\n",
+    "Dado un punto $x_0$, esta funció guarda a todas la iteraciones bajo $F$ en un arreglo.\n",
+    "\"\"\"\n",
+    "\n",
+    "function iterado(F::Function,x0::Float64,n::Int)\n",
+    "    y = Float64[x0] ##El primer elemento es x_0\n",
+    "    x = x0\n",
+    "    for i in 1:n\n",
+    "        x=F(x) #El valor de x cambia con cada iteración\n",
+    "        push!(y,x) #Este nuevo valor se guarda en el arreglo\n",
+    "    end\n",
+    "    y\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "    Lyapunov(y, F)\n",
+    "\n",
+    "Dado un punto un arreglo que contenga todas las iteraciones bajo $F$ de $x_0$, calcula \n",
+    "$\\frac{1}{n} \\sum_{i=1}^n \\log\\Big| \\, f'(x_i)\\, \\Big|.$\n",
+    "\"\"\"\n",
+    "\n",
+    "function Lyapunov(y, F::Function)\n",
+    "    n = length(y)\n",
+    "    l = 0\n",
+    "   \n",
+    "    for i in 1:n\n",
+    "        x = abs((F(xdual(y[i]))).der)\n",
+    "        l = l + log(x)\n",
+    "       \n",
+    "    end\n",
+    "    l/n\n",
+    "end\n",
+    "\n",
+    "doc\"\"\"\n",
+    "mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "\n",
+    "Calcula el exponente de Lyapunov para un mapeo paramétrico $Q_c = Q_c(x, c)$ en un rango de parámetros `crange`, un\n",
+    "valor inicial `x0` y `n` iteraciones.\n",
+    "\"\"\"\n",
+    "\n",
+    "function mapeo_liap_all(crange::FloatRange, Qc::Function, x0::Float64, n = 100000)\n",
+    "    mapeo = Float64[]\n",
+    "  \n",
+    "    for i in crange\n",
+    "        Qci(x) = Qc(x,i) \n",
+    "        y = iterado(Qci,x0,n)\n",
+    "        l = Lyapunov(y, Qci)\n",
+    "        if abs(l)<Inf #En algunos puntos labda diverge, por lo que si tiende a infinito, se la asigna el valor-2.5\n",
+    "            push!(mapeo,l)      \n",
+    "        else\n",
+    "            push!(mapeo,0.0)       \n",
+    "        end\n",
+    "      \n",
+    "    end\n",
+    "    mapeo\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:00:18.532899",
+     "start_time": "2016-12-05T06:59:58.315Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "ename": "LoadError",
+     "evalue": "LoadError: UndefVarError: mapeo_liap_all not defined\nwhile loading In[2], in expression starting on line 2",
+     "output_type": "error",
+     "traceback": [
+      "LoadError: UndefVarError: mapeo_liap_all not defined\nwhile loading In[2], in expression starting on line 2",
+      ""
+     ]
+    }
+   ],
+   "source": [
+    "crange = 0.0:1:500\n",
+    "mapeo= mapeo_liap_all(crange,Ict1,1000.0);\n",
+    "p = plot(crange,mapeo)\n",
+    "\n",
+    "xlabel!(L\"c\")\n",
+    "ylabel!(L\"\\lambda\")\n",
+    "title!(L\"Exponente de Lyapunov de N(x)\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<img src=\"Figures/liap.png\" width=\"600\">\n",
+    "\n",
+    "Vemos cómo el rompimiento es un punto de bifurcación ya que $\\lambda = 0$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Por último, se encontró a $S_c$ como función de $M$ y $R$, para esto empleamos el dominio $M\\times R = [1,100]\\times[1.1,100]$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:09:08.994760",
+     "start_time": "2016-12-05T07:09:08.975Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "iteram (generic function with 1 method)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "function iteram(M1::Range, R1::Range)\n",
+    "    P, Q = length(R1), length(M1)\n",
+    "    Mat1 = zeros(P, Q) \n",
+    "    K = Int(P*Q)\n",
+    "    n = 1\n",
+    "    #@show (P, Q)\n",
+    "    for j in 1:Q\n",
+    "        for i in 1:P\n",
+    "            if mod(100n/K, 5) == 0\n",
+    "                println(100n/K, \"%\")\n",
+    "            end\n",
+    "            #@show i, j\n",
+    "            M, R = M1[j], R1[i]\n",
+    "            m1(x, s) = mapins(x, M, s, R)\n",
+    "            srange = 0:3_000.0\n",
+    "            #map1 = mapeo_liap_all(srange, m1, 1000.0)\n",
+    "            ff = diagbifurc(m1, 300, 50, srange, 1000); \n",
+    "            cc = ones(size(ff)[1])*srange';\n",
+    "            \n",
+    "            # Esto cambia las matrices en vectores; ayuda un poco para los dibujos\n",
+    "            ff = reshape(ff, size(ff)[1]*size(ff)[2]);\n",
+    "            cc = reshape(cc, size(ff));\n",
+    "            for l in eachindex(ff)\n",
+    "                if ff[l] == 0\n",
+    "                    Mat1[i, j] = cc[l]\n",
+    "                    break\n",
+    "                end\n",
+    "            end\n",
+    "            n += 1\n",
+    "        end\n",
+    "    end\n",
+    "\n",
+    "    mm = ones(size(Mat1)[1])*M1'\n",
+    "    rr = R1*ones(size(Mat1)[2])'\n",
+    "    A1 = reshape(Mat1, size(Mat1)[1]*size(Mat1)[2])\n",
+    "    mm1 = reshape(mm, size(A1)[1])\n",
+    "    rr1 = reshape(rr, size(A1)[1])\n",
+    "    return mm1, rr1, A1\n",
+    "end"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "Con esto hemos hecho un mapeo preliminar con $M=1:50$ , $R=1:40$. Vemos el siguente comportamiento para \"cortes\" a R constante"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "MS = readcsv(\"M1.csv\")\n",
+    "Rrange = 5:40;"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "plot(MS[1:10,1:5])\n",
+    "xlabel!(L\"M\")\n",
+    "ylabel!(L\"N\")\n",
+    "title!(\"Cortes a R=cte\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<img src=\"Figures/rcte.png\" width=\"600\">"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "scatter(MS[1,:])\n",
+    "scatter!(MS[2,:])\n",
+    "scatter!(MS[3,:])\n",
+    "scatter!(MS[4,:])\n",
+    "xlabel!(L\"R\")\n",
+    "ylabel!(L\"N\")\n",
+    "title!(\"Cortes a M=cte\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "<img src=\"Figures/mcte.png\" width=\"600\">\n",
+    "\n",
+    "Vemos un comportamiento de agrupación en 4. Para indagar más en esto buscamos los puntos donde hay una crecimiento constante de $S_c$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([5.0,9.0,13.0,17.0,21.0,25.0,29.0,33.0,37.0],[1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "dif=MS\n",
+    "    for j in 1:length(MS[:,1])-1 #fixed r\n",
+    "        dif[j,:]= MS[j+1,:]-MS[j,:]\n",
+    "end\n",
+    "\n",
+    "dif\n",
+    "dif[end,:]= dif[end-1,:]\n",
+    "steadyR = Float64[]\n",
+    "steapR = Float64[]\n",
+    "for i in 1:36\n",
+    "    u = unique(dif[:,i])\n",
+    "    if length(u)==1\n",
+    "        push!(steadyR,Rrange[i])\n",
+    "        push!(steapR,u[1])\n",
+    "    end\n",
+    "end\n",
+    "steadyR,steapR"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(Float64[],Float64[])"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "MS = readcsv(\"M1.csv\")\n",
+    "Rrange = 5:40;\n",
+    "dif2=MS\n",
+    "    for j in 1:length(MS[1,:])-1 #fixed m\n",
+    "        dif2[:,j]=  MS[:,j+1]-MS[:,j]\n",
+    "end\n",
+    "\n",
+    "dif2\n",
+    "dif[:,end]= dif[:,end-1]\n",
+    "steadyM = Float64[]\n",
+    "steapM = Float64[]\n",
+    "for i in 1:50\n",
+    "    u = unique(dif[i,:])\n",
+    "    if length(unique(dif[i,:]))==1\n",
+    "        push!(steadyM,i)\n",
+    "        push!(steapM,u[1])\n",
+    "    end\n",
+    "end\n",
+    "steadyM,steapM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:09:26.297429",
+     "start_time": "2016-12-05T07:09:24.044Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "mm = readcsv(\"DatosPlano/mms2.csv\")[:,1]\n",
+    "rr = readcsv(\"DatosPlano/rrs2.csv\")[:,1]\n",
+    "cs = readcsv(\"DatosPlano/ccs2.csv\")[:,1];\n",
+    "append!(mm, readcsv(\"DatosPlano/mms3.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs3.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs3.csv\")[:,1]);\n",
+    "append!(mm, readcsv(\"DatosPlano/mms1.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs1.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs1.csv\")[:,1]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:10:02.663726",
+     "start_time": "2016-12-05T07:09:27.863Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" />"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(mm, rr, cs, st = :surface)\n",
+    "xlabel!(\"M\")\n",
+    "ylabel!(\"R\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:10:18.451492",
+     "start_time": "2016-12-05T07:10:14.007Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script charset=\"utf-8\" type='text/javascript'>\n",
+       "    // This script was adapted from\n",
+       "// https://github.com/JuliaLang/Interact.jl/blob/master/src/IJulia/ijulia.js\n",
+       "(function (IPython, $) {\n",
+       "    $.event.special.destroyed = {\n",
+       "\tremove: function(o) {\n",
+       "\t    if (o.handler) {\n",
+       "\t\to.handler.apply(this, arguments)\n",
+       "\t    }\n",
+       "\t}\n",
+       "    }\n",
+       "\n",
+       "    function resolve_promises(comm, val) {\n",
+       "        val === undefined && (val = null);\n",
+       "        if (val && val.constructor == Promise) {\n",
+       "            val.then(function(val) {\n",
+       "                return resolve_promises(comm, val);\n",
+       "            })\n",
+       "        } else {\n",
+       "            return val;\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    $(document).ready(function() {\n",
+       "\tfunction initComm(evt, data) {\n",
+       "\t    var comm_manager = data.kernel.comm_manager;\n",
+       "        console.log(\"plotly comm init\");\n",
+       "\t    comm_manager.register_target(\"plotlyjs_eval\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                // Call the code in the message\n",
+       "                eval(msg.content.data.code);\n",
+       "\n",
+       "                // Clean up\n",
+       "                delete msg.content.data.code;\n",
+       "            });\n",
+       "\t    });\n",
+       "\n",
+       "        comm_manager.register_target(\"plotlyjs_return\", function (comm) {\n",
+       "            comm.on_msg(function (msg) {\n",
+       "                // Call the code in the message\n",
+       "                val = eval(msg.content.data.code);\n",
+       "\n",
+       "                // resolve any promises so we get a raw value\n",
+       "                val = resolve_promises(comm, val);\n",
+       "                console.log(\"About to send\", val);\n",
+       "\n",
+       "                // Send the value back to Julia\n",
+       "                comm.send({action: \"plotlyjs_ret_val\", ret: val});\n",
+       "\n",
+       "                // Clean up\n",
+       "                delete msg.content.data.code;  // clean up\n",
+       "                delete val;\n",
+       "            });\n",
+       "\t    });\n",
+       "\t}\n",
+       "\n",
+       "\ttry {\n",
+       "\t    // try to initialize right away. otherwise, wait on the status_started event.\n",
+       "\t    initComm(undefined, IPython.notebook);\n",
+       "\t} catch (e) {\n",
+       "        console.log(e);\n",
+       "\t    $([IPython.events]).on('kernel_created.Kernel kernel_created.Session', initComm);\n",
+       "\t}\n",
+       "    });\n",
+       "})(IPython, jQuery);\n",
+       "\n",
+       "</script>\n",
+       "\n",
+       " <script charset=\"utf-8\" type='text/javascript'>\n",
+       "     define('plotly', function(require, exports, module) {\n",
+       "         /**\n",
+       "* plotly.js v1.19.1\n",
+       "* Copyright 2012-2016, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
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t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,t|=t>>>16,t-(t>>>1)},r.parity=function(t){return t^=t>>>16,t^=t>>>8,t^=t>>>4,t&=15,27030>>>t&1};var a=new Array(256);!function(t){for(var e=0;e<256;++e){var r=e,n=e,i=7;for(r>>>=1;r;r>>>=1)n<<=1,n|=1&r,--i;t[e]=n<<i&255}}(a),r.reverse=function(t){return a[255&t]<<24|a[t>>>8&255]<<16|a[t>>>16&255]<<8|a[t>>>24&255]},r.interleave2=function(t,e){return t&=65535,t=16711935&(t|t<<8),t=252645135&(t|t<<4),t=858993459&(t|t<<2),t=1431655765&(t|t<<1),e&=65535,e=16711935&(e|e<<8),e=252645135&(e|e<<4),e=858993459&(e|e<<2),e=1431655765&(e|e<<1),t|e<<1},r.deinterleave2=function(t,e){return t=t>>>e&1431655765,t=858993459&(t|t>>>1),t=252645135&(t|t>>>2),t=16711935&(t|t>>>4),t=65535&(t|t>>>16),t<<16>>16},r.interleave3=function(t,e,r){return 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e?this.words[n]=this.words[n]|1<<i:this.words[n]=this.words[n]&~(1<<i),this.strip()},i.prototype.iadd=function(t){if(this.sign&&!t.sign){this.sign=!1;var e=this.isub(t);return this.sign=!this.sign,this._normSign()}if(!this.sign&&t.sign){t.sign=!1;var e=this.isub(t);return t.sign=!0,e._normSign()}var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++){var e=r.words[a]+n.words[a]+i;this.words[a]=67108863&e,i=e>>>26}for(;0!==i&&a<r.length;a++){var e=r.words[a]+i;this.words[a]=67108863&e,i=e>>>26}if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},i.prototype.add=function(t){if(t.sign&&!this.sign){t.sign=!1;var e=this.sub(t);return t.sign=!0,e}if(!t.sign&&this.sign){this.sign=!1;var e=t.sub(this);return this.sign=!0,e}return this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(t.sign){t.sign=!1;var e=this.iadd(t);return t.sign=!0,e._normSign()}if(this.sign)return this.sign=!1,this.iadd(t),this.sign=!0,this._normSign();var r=this.cmp(t);if(0===r)return this.sign=!1,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++){var e=n.words[o]-i.words[o]+a;a=e>>26,this.words[o]=67108863&e}for(;0!==a&&o<n.length;o++){var e=n.words[o]+a;a=e>>26,this.words[o]=67108863&e}if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.sign=!0),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)},i.prototype._smallMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0;n<e.length-1;n++){for(var i=r>>>26,a=67108863&r,o=Math.min(n,t.length-1),s=Math.max(0,n-this.length+1);s<=o;s++){var l=n-s,u=0|this.words[l],c=0|t.words[s],h=u*c,f=67108863&h;i=i+(h/67108864|0)|0,f=f+a|0,a=67108863&f,i=i+(f>>>26)|0}e.words[n]=a,r=i}return 0!==r?e.words[n]=r:e.length--,e.strip()},i.prototype._bigMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0,i=0;i<e.length-1;i++){var a=n;n=0;for(var o=67108863&r,s=Math.min(i,t.length-1),l=Math.max(0,i-this.length+1);l<=s;l++){var u=i-l,c=0|this.words[u],h=0|t.words[l],f=c*h,d=67108863&f;a=a+(f/67108864|0)|0,d=d+o|0,o=67108863&d,a=a+(d>>>26)|0,n+=a>>>26,a&=67108863}e.words[i]=o,r=a,a=n}return 0!==r?e.words[i]=r:e.length--,e.strip()},i.prototype.mulTo=function(t,e){var r;return r=this.length+t.length<63?this._smallMulTo(t,e):this._bigMulTo(t,e)},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.imul=function(t){if(0===this.cmpn(0)||0===t.cmpn(0))return this.words[0]=0,this.length=1,this;var e=this.length,r=t.length;this.sign=t.sign!==this.sign,this.length=this.length+t.length,this.words[this.length-1]=0;for(var n=this.length-2;n>=0;n--){for(var i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);s<=o;s++){var l=n-s,u=this.words[l],c=t.words[s],h=u*c,f=67108863&h;i+=h/67108864|0,f+=a,a=67108863&f,i+=f>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var d=this.words[l]+i;this.words[l]=67108863&d,i=d>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var o=this.length-1;o>=0;o--)this.words[o+n]=this.words[o];for(var o=0;o<n;o++)this.words[o]=0;this.length+=n}return this.strip()},i.prototype.ishrn=function(t,e,n){r(\"number\"==typeof t&&t>=0);var i;i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=n;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o){this.length-=o;for(var u=0;u<this.length;u++)this.words[u]=this.words[u+o]}else this.words[0]=0,this.length=1;for(var c=0,u=this.length-1;u>=0&&(0!==c||u>=i);u--){var h=this.words[u];this.words[u]=c<<26-a|h>>>a,c=h&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip(),this},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.testn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n)return!1;var a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),t<0?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),t<0)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(s===-1),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var h=n.clone()._ishlnsubmul(a,1,u);h.sign||(n=h,l&&(l.words[u]=1));for(var f=u-1;f>=0;f--){var d=67108864*n.words[a.length+f]+n.words[a.length+f-1];for(d=Math.min(d/o|0,67108863),n._ishlnsubmul(a,d,f);n.sign;)d--,n.sign=!1,n._ishlnsubmul(a,1,f),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[f]=d)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(t<=67108863);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(t<=67108863);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),h=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(h).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(h).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;a<n+1;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=t<0;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:n<t?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new f(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(h,s),h.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function t(e){if(v[e])return v[e];var t;if(\"k256\"===e)t=new l;else if(\"p224\"===e)t=new u;else if(\"p192\"===e)t=new c;else{if(\"p25519\"!==e)throw new Error(\"Unknown prime \"+e);t=new h}return v[e]=t,t},f.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},f.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},f.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},f.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},f.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},f.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},f.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},f.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},f.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},f.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},f.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},f.prototype.isqr=function(t){return this.imul(t,t)},f.prototype.sqr=function(t){return this.mul(t,t)},f.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),h=this.m.bitLength();for(h=new i(2*h*h).toRed(this);0!==this.pow(h,c).cmp(u);)h.redIAdd(u);for(var f=this.pow(h,o),a=this.pow(t,o.addn(1).ishrn(1)),d=this.pow(t,o),p=s;0!==d.cmp(l);){for(var g=d,m=0;0!==g.cmp(l);m++)g=g.redSqr();r(m<p);var v=this.pow(f,new i(1).ishln(p-m-1));a=a.redMul(v),f=v.redSqr(),d=d.redMul(f),p=m}return a},f.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},f.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},f.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},f.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new d(t)},n(d,f),d.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},d.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},d.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},d.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var 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S=0;S<3;++S)O[S]+=M*R[S]*this.tickPad[S]/r[5*S];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],O,this.tickColor[A])}if(this.labelEnable[A]){for(var S=0;S<3;++S)O[S]+=M*R[S]*this.labelPad[S]/r[5*S];O[A]+=.5*(s[0][A]+s[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],O,this.labelColor[A])}}},p.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":121,\"./lib/cube.js\":122,\"./lib/lines.js\":123,\"./lib/text.js\":125,\"./lib/ticks.js\":126}],121:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}function i(t){for(var e=[],r=[],i=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,h=[0,0,0],f=[0,0,0],d=-1;d<=1;d+=2){r.push(i,i+2,i+1,i+1,i+2,i+3),h[l]=d,f[l]=d;for(var p=-1;p<=1;p+=2){h[u]=p;for(var g=-1;g<=1;g+=2)h[c]=g,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),i+=1}var m=u;u=c,c=m}var v=a(t,new 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s=n(f);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},g.drawGrid=function(t,e,r,a,o,s){if(this.gridCount[t]){var l=n(h);l[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[e]+=r[0][e],this.shader.uniforms.offset=u;var p=n(c);p[t]=1,this.shader.uniforms.majorAxis=p;var g=n(f);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},g.drawZero=function(t,e,r,a,o,s){var l=n(h);this.shader.uniforms.majorAxis=l,l[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=l;var u=i(d,a);u[t]+=r[0][t],this.shader.uniforms.offset=u;var c=n(f);c[e]=1,this.shader.uniforms.screenAxis=c,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,6)},g.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":124,\"gl-buffer\":128,\"gl-vao\":236}],124:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.line=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"}])};var o=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvoid main() {  \\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n  mat2 planeXform = scale * mat2(cos(angle), sin(angle),\\n                                -sin(angle), cos(angle));\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n  vec4 worldPosition = model * vec4(dataPosition, 1);\\n  \\n  //Compute clip position\\n  vec4 viewPosition = view * worldPosition;\\n  vec4 clipPosition = projection * viewPosition;\\n  clipPosition /= clipPosition.w;\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec4(viewOffset, 0, 0);\\n\\n  //Done\\n  gl_Position = clipPosition;\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\";r.text=function(t){return n(t,o,s,null,[{name:\"position\",type:\"vec3\"}])};var l=\"#define GLSLIFY 1\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  if(dot(normal, enable) > 0.0) {\\n    vec3 nPosition = mix(bounds[0], bounds[1], 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n  colorChannel = abs(normal);\\n}\",u=\"precision mediump float;\\n#define 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g=[0,0,0];d.drawTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=g;a[0]=a[1]=a[2]=0,a[t]=1,this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}};var m=[0,0,0];d.drawLabel=function(t,e,r,n,i){this.labelCount[t]&&(this.shader.uniforms.axis=m,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},d.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this,t(\"_process\"))},{\"./shaders\":124,_process:445,\"gl-buffer\":128,\"gl-vao\":236,\"vectorize-text\":509}],126:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u=0|u);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var h=\"\"+u;h.length<i;)h=\"0\"+h;return c+\".\"+h}return c}function i(t,e){for(var r=[],i=0;i<3;++i){for(var a=[],o=(.5*(t[0][i]+t[1][i]),0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:n(e[i],o)});for(var o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:n(e[i],o)});r.push(a)}return r}function a(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}r.create=i,r.equal=a},{}],127:[function(t,e,r){\"use strict\";function n(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}function i(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=p,s=g,l=0;l<3;++l)s[l]=o[l]=r[l];s[3]=o[3]=1,s[a]+=1,h(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,h(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,c=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+c*c)}return t}function a(t,e,r,n,a){var h=e.model||f,p=e.view||f,g=e.projection||f,y=t.bounds,a=a||l(h,p,g,y),x=a.axis;a.edges;u(d,p,h),u(d,g,d);for(var b=m,_=0;_<3;++_)b[_].lo=1/0,b[_].hi=-(1/0),b[_].pixelsPerDataUnit=1/0;var w=o(c(d,d));c(d,d);for(var M=0;M<3;++M){var A=(M+1)%3,k=(M+2)%3,T=v;t:for(var _=0;_<2;++_){var E=[];if(x[M]<0!=!!_){T[M]=y[_][M];for(var S=0;S<2;++S){T[A]=y[S^_][A];for(var L=0;L<2;++L)T[k]=y[L^S^_][k],E.push(T.slice())}for(var S=0;S<w.length;++S){if(0===E.length)continue t;E=s.positive(E,w[S])}for(var S=0;S<E.length;++S)for(var k=E[S],z=i(v,d,k,r,n),L=0;L<3;++L)b[L].lo=Math.min(b[L].lo,k[L]),b[L].hi=Math.max(b[L].hi,k[L]),L!==M&&(b[L].pixelsPerDataUnit=Math.min(b[L].pixelsPerDataUnit,Math.abs(z[L])))}}}return b}e.exports=a;var o=t(\"extract-frustum-planes\"),s=t(\"split-polygon\"),l=t(\"./lib/cube.js\"),u=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/transpose\"),h=t(\"gl-vec4/transformMat4\"),f=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),d=new Float32Array(16),p=[0,0,0,1],g=[0,0,0,1],m=[new n(1/0,-(1/0),1/0),new n(1/0,-(1/0),1/0),new n(1/0,-(1/0),1/0)],v=[0,0,0]},{\"./lib/cube.js\":122,\"extract-frustum-planes\":103,\"gl-mat4/multiply\":151,\"gl-mat4/transpose\":159,\"gl-vec4/transformMat4\":242,\"split-polygon\":483}],128:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}function i(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function a(t,e){for(var r=l.malloc(t.length,e),n=t.length,i=0;i<n;++i)r[i]=t[i];return r}function o(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}function s(t,e,r,i){if(r=r||t.ARRAY_BUFFER,i=i||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(i!==t.DYNAMIC_DRAW&&i!==t.STATIC_DRAW&&i!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var a=t.createBuffer(),o=new n(t,r,a,0,i);return o.update(e),o}var l=t(\"typedarray-pool\"),u=t(\"ndarray-ops\"),c=t(\"ndarray\"),h=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"],f=n.prototype;f.bind=function(){this.gl.bindBuffer(this.type,this.handle)},f.unbind=function(){this.gl.bindBuffer(this.type,null)},f.dispose=function(){this.gl.deleteBuffer(this.handle)},f.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof 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:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},{}],130:[function(t,e,r){var n=t(\"./1.0/numbers\");e.exports=function(t){return n[t]}},{\"./1.0/numbers\":129}],131:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.plot=t,this.shader=e,this.bufferHi=r,this.bufferLo=n,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.color=[0,0,0,1]}function i(t,e){var r=a(t.gl,l.vertex,l.fragment),i=o(t.gl),s=o(t.gl),u=new n(t,r,i,s);return u.update(e),t.addObject(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"typedarray-pool\"),l=t(\"./lib/shaders\");e.exports=i;var u=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]],c=n.prototype;c.draw=function(){var t=new Float32Array([0,0]),e=new Float32Array([0,0]),r=new Float32Array([0,0]),n=new Float32Array([0,0]),i=[1,1];return function(){var a=this.plot,o=this.shader,s=this.bounds,l=this.numPoints;if(l){var 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h=0;h<3;++h)e.lineWidth(this.lineWidth[h]),r.capSize=this.capSize[h]*u,e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var f=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();h.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;u<3;++u){this.lineOffset[u]=l;t:for(var c=0;c<s;++c){for(var h=r[c],f=0;f<3;++f)if(isNaN(h[f])||!isFinite(h[f]))continue t;var d=n[c],p=e[u];if(Array.isArray(p[0])&&(p=e[c]),3===p.length&&(p=[p[0],p[1],p[2],1]),!isNaN(d[0][u])&&!isNaN(d[1][u])){if(d[0][u]<0){var g=h.slice();g[u]+=d[0][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,g[0],g[1],g[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,p,u)}if(d[1][u]>0){var g=h.slice();g[u]+=d[1][u],o.push(h[0],h[1],h[2],p[0],p[1],p[2],p[3],0,0,0,g[0],g[1],g[2],p[0],p[1],p[2],p[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,p,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":134,\"gl-buffer\":128,\"gl-vao\":236}],134:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":220}],135:[function(t,e,r){\"use strict\";function n(t){var e=t.getParameter(t.FRAMEBUFFER_BINDING),r=t.getParameter(t.RENDERBUFFER_BINDING),n=t.getParameter(t.TEXTURE_BINDING_2D);return[e,r,n]}function i(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function a(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);y=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;a<n;++a)i[a]=t.COLOR_ATTACHMENT0+a;for(var a=n;a<r;++a)i[a]=t.NONE;y[n]=i}}function o(t){switch(t){case p:throw new Error(\"gl-fbo: Framebuffer unsupported\");case g:throw new Error(\"gl-fbo: Framebuffer incomplete attachment\");case m:throw new Error(\"gl-fbo: Framebuffer incomplete dimensions\");case v:throw new Error(\"gl-fbo: Framebuffer incomplete missing attachment\");default:throw new Error(\"gl-fbo: Framebuffer failed for unspecified reason\")}}function s(t,e,r,n,i,a){if(!n)return null;var o=d(t,e,r,i,n);return o.magFilter=t.NEAREST,o.minFilter=t.NEAREST,o.mipSamples=1,o.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,a,t.TEXTURE_2D,o.handle,0),o}function l(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function u(t){var e=n(t.gl),r=t.gl,a=t.handle=r.createFramebuffer(),u=t._shape[0],c=t._shape[1],h=t.color.length,f=t._ext,d=t._useStencil,p=t._useDepth,g=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,a);for(var m=0;m<h;++m)t.color[m]=s(r,u,c,g,r.RGBA,r.COLOR_ATTACHMENT0+m);0===h?(t._color_rb=l(r,u,c,r.RGBA4,r.COLOR_ATTACHMENT0),f&&f.drawBuffersWEBGL(y[0])):h>1&&f.drawBuffersWEBGL(y[h]);var v=r.getExtension(\"WEBGL_depth_texture\");v?d?t.depth=s(r,u,c,v.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p&&(t.depth=s(r,u,c,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):p&&d?t._depth_rb=l(r,u,c,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):p?t._depth_rb=l(r,u,c,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=l(r,u,c,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(var m=0;m<t.color.length;++m)t.color[m].dispose(),t.color[m]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),i(r,e),o(x)}i(r,e)}function c(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var l=0;l<i;++l)this.color[l]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var c=this,h=[0|e,0|r];Object.defineProperties(h,{0:{get:function(){return c._shape[0]},set:function(t){return c.width=t}},1:{get:function(){return c._shape[1]},set:function(t){return c.height=t}}}),this._shapeVector=h,u(this)}function h(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var a=t.gl,s=a.getParameter(a.MAX_RENDERBUFFER_SIZE);if(e<0||e>s||r<0||r>s)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var l=n(a),u=0;u<t.color.length;++u)t.color[u].shape=t._shape;t._color_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._color_rb),a.renderbufferStorage(a.RENDERBUFFER,a.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(a.bindRenderbuffer(a.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?a.renderbufferStorage(a.RENDERBUFFER,a.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&a.renderbufferStorage(a.RENDERBUFFER,a.STENCIL_INDEX,t._shape[0],t._shape[1])),a.bindFramebuffer(a.FRAMEBUFFER,t.handle);var c=a.checkFramebufferStatus(a.FRAMEBUFFER);c!==a.FRAMEBUFFER_COMPLETE&&(t.dispose(),i(a,l),o(c)),i(a,l)}}function f(t,e,r,n){p||(p=t.FRAMEBUFFER_UNSUPPORTED,g=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,m=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,v=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var i=t.getExtension(\"WEBGL_draw_buffers\");if(!y&&i&&a(t,i),Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]),\"number\"!=typeof e)throw new Error(\"gl-fbo: Missing shape parameter\");var o=t.getParameter(t.MAX_RENDERBUFFER_SIZE);\n",
+       "if(e<0||e>o||r<0||r>o)throw new Error(\"gl-fbo: Parameters are too large for FBO\");n=n||{};var s=1;if(\"color\"in n){if(s=Math.max(0|n.color,0),s<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(s>1){if(!i)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(s>t.getParameter(i.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+s+\" draw buffers\")}}var l=t.UNSIGNED_BYTE,u=t.getExtension(\"OES_texture_float\");if(n.float&&s>0){if(!u)throw new Error(\"gl-fbo: Context does not support floating point textures\");l=t.FLOAT}else n.preferFloat&&s>0&&u&&(l=t.FLOAT);var h=!0;\"depth\"in n&&(h=!!n.depth);var f=!1;return\"stencil\"in n&&(f=!!n.stencil),new c(t,e,r,l,s,h,f,i)}var d=t(\"gl-texture2d\");e.exports=f;var p,g,m,v,y=null,x=c.prototype;Object.defineProperties(x,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return h(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return t=0|t,h(this,t,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t=0|t,h(this,this._shape[0],t),t},enumerable:!1}}),x.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},x.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":232}],136:[function(t,e,r){function n(t,e,r){\"use strict\";var n=o(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===a.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var u=i(\"Error compiling %s shader %s:\\n\",l,n),c=i(\"%s%s\",u,t),h=t.split(\"\\n\"),f={},d=0;d<h.length;d++){var p=h[d];if(\"\"!==p){var g=parseInt(p.split(\":\")[2]);if(isNaN(g))throw new Error(i(\"Could not parse error: %s\",p));f[g]=p}}for(var m=s(e).split(\"\\n\"),d=0;d<m.length;d++)if(f[d+3]||f[d+2]||f[d+1]){var v=m[d];if(u+=v+\"\\n\",f[d+1]){var y=f[d+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),u+=i(\"^^^ %s\\n\\n\",y)}}return{long:u.trim(),short:c.trim()}}var i=t(\"sprintf-js\").sprintf,a=t(\"gl-constants/lookup\"),o=t(\"glsl-shader-name\"),s=t(\"add-line-numbers\");e.exports=n},{\"add-line-numbers\":29,\"gl-constants/lookup\":130,\"glsl-shader-name\":244,\"sprintf-js\":484}],137:[function(t,e,r){r.lineVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi, dLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvec2 project_2_1(vec2 scHi, vec2 scLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi\\n       + scLo * posHi\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 dir = project_2_1(scaleHi, scaleLo, dHi, dLo);\\n  vec2 n = 0.5 * width * normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(p + n, 0.0, 1.0);\\n}\",r.lineFragment=\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\",r.mitreVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo;\\nuniform float radius;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  gl_Position = vec4(p, 0.0, 1.0);\\n  gl_PointSize = radius;\\n}\",r.mitreFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\nattribute vec4 pick0, pick1;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  vec2 n = width * normalize(screenShape.yx * vec2(dHi.y, -dHi.x)) / screenShape.xy;\\n  gl_Position = vec4(p + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\",r.fillVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aHi, aLo, dHi;\\n\\nuniform vec2 scaleHi, translateHi, scaleLo, translateLo, projectAxis;\\nuniform float projectValue, depth;\\n\\n\\nvec2 project_1_0(vec2 scHi, vec2 trHi, vec2 scLo, vec2 trLo, vec2 posHi, vec2 posLo) {\\n  return scHi * posHi + trHi\\n       + scLo * posHi + trLo\\n       + scHi * posLo\\n       + scLo * posLo;\\n}\\n\\n\\nvoid main() {\\n  vec2 p = project_1_0(scaleHi, translateHi, scaleLo, translateLo, aHi, aLo);\\n  if(dHi.y < 0.0 || (dHi.y == 0.0 && dHi.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\",r.fillFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\"},{}],138:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l){this.plot=t,this.dashPattern=e,this.lineBufferHi=r,this.lineBufferLo=n,this.pickBuffer=i,this.lineShader=a,this.mitreShader=o,this.fillShader=s,this.pickShader=l,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=s(r),c=l(r,[1,1]),f=o(r,h.lineVertex,h.lineFragment),d=o(r,h.mitreVertex,h.mitreFragment),p=o(r,h.fillVertex,h.fillFragment),g=o(r,h.pickVertex,h.pickFragment),m=new n(t,c,i,a,u,f,d,p,g);return t.addObject(m),m.update(e),m}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),h=t(\"./lib/shaders\"),f=n.prototype;f.setProjectionModel=function(){var t={scaleHi:new Float32Array([0,0]),scaleLo:new Float32Array([0,0]),translateHi:new Float32Array([0,0]),translateLo:new Float32Array([0,0]),screenShape:[0,0]};return function(){var e=this.bounds,r=this.plot.viewBox,n=this.plot.dataBox,i=e[2]-e[0],a=e[3]-e[1],o=n[2]-n[0],s=n[3]-n[1],l=r[2]-r[0],u=r[3]-r[1],c=2*i/o,h=2*a/s,f=2*(e[0]-n[0])/o-1,d=2*(e[1]-n[1])/s-1;return t.scaleHi[0]=c,t.scaleHi[1]=h,t.scaleLo[0]=c-t.scaleHi[0],t.scaleLo[1]=h-t.scaleHi[1],t.translateHi[0]=f,t.translateHi[1]=d,t.translateLo[0]=f-t.translateHi[0],t.translateLo[1]=d-t.translateHi[1],t.screenShape[0]=l,t.screenShape[1]=u,t}}(),f.setProjectionUniforms=function(t,e){t.scaleHi=e.scaleHi,t.scaleLo=e.scaleLo,t.translateHi=e.translateHi,t.translateLo=e.translateLo,t.screenShape=e.screenShape},f.draw=function(){var t=[1,0],e=[-1,0],r=[0,1],n=[0,-1];return function(){var i=this.vertCount;if(i){var a=this.setProjectionModel(),o=this.plot,s=this.width,l=o.gl,u=o.pixelRatio,c=this.color,h=this.fillShader.attributes;this.lineBufferLo.bind(),h.aLo.pointer(l.FLOAT,!1,16,0),this.lineBufferHi.bind();var f=this.fill;if(f[0]||f[1]||f[2]||f[3]){var d=this.fillShader;d.bind();var p=d.uniforms;this.setProjectionUniforms(p,a),p.depth=o.nextDepthValue(),h.aHi.pointer(l.FLOAT,!1,16,0),h.dHi.pointer(l.FLOAT,!1,16,8),l.depthMask(!0),l.enable(l.DEPTH_TEST);var g=this.fillColor;f[0]&&(p.color=g[0],p.projectAxis=e,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[1]&&(p.color=g[1],p.projectAxis=n,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[2]&&(p.color=g[2],p.projectAxis=t,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),f[3]&&(p.color=g[3],p.projectAxis=r,p.projectValue=1,l.drawArrays(l.TRIANGLES,0,i)),l.depthMask(!1),l.disable(l.DEPTH_TEST)}var m=this.lineShader;m.bind(),this.lineBufferLo.bind(),m.attributes.aLo.pointer(l.FLOAT,!1,16,0),m.attributes.dLo.pointer(l.FLOAT,!1,16,8),this.lineBufferHi.bind();var v=m.uniforms;this.setProjectionUniforms(v,a),v.color=c,v.width=s*u,v.dashPattern=this.dashPattern.bind(),v.dashLength=this.dashLength*u;var y=m.attributes;if(y.aHi.pointer(l.FLOAT,!1,16,0),y.dHi.pointer(l.FLOAT,!1,16,8),l.drawArrays(l.TRIANGLES,0,i),s>2&&!this.usingDashes){var x=this.mitreShader;this.lineBufferLo.bind(),x.attributes.aLo.pointer(l.FLOAT,!1,48,0),this.lineBufferHi.bind(),x.bind();var b=x.uniforms;this.setProjectionUniforms(b,a),b.color=c,b.radius=s*u,x.attributes.aHi.pointer(l.FLOAT,!1,48,0),l.drawArrays(l.POINTS,0,i/3|0)}}}}(),f.drawPick=function(){var t=[0,0,0,0];return function(e){var r=this.vertCount,n=this.numPoints;if(this.pickOffset=e,!r)return e+n;var i=this.setProjectionModel(),a=this.plot,o=this.width,s=a.gl,l=a.pickPixelRatio,u=this.pickShader,c=this.pickBuffer;t[0]=255&e,t[1]=e>>>8&255,t[2]=e>>>16&255,t[3]=e>>>24,u.bind();var h=u.uniforms;this.setProjectionUniforms(h,i),h.width=o*l,h.pickOffset=t;var f=u.attributes;return this.lineBufferHi.bind(),f.aHi.pointer(s.FLOAT,!1,16,0),f.dHi.pointer(s.FLOAT,!1,16,8),this.lineBufferLo.bind(),f.aLo.pointer(s.FLOAT,!1,16,0),c.bind(),f.pick0.pointer(s.UNSIGNED_BYTE,!1,8,0),f.pick1.pointer(s.UNSIGNED_BYTE,!1,8,4),s.drawArrays(s.TRIANGLES,0,r),e+n}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(r<n||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},f.update=function(t){t=t||{};var e,r,n,a,o,s=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var h=t.dashes||[1],f=0;for(e=0;e<h.length;++e)f+=h[e];var d=c.mallocUint8(f);n=0;var p=255;for(e=0;e<h.length;++e){for(r=0;r<h[e];++r)d[n++]=p;p^=255}this.dashPattern.dispose(),this.usingDashes=h.length>1,this.dashPattern=l(s,u(d,[f,1,4],[1,0,0])),this.dashPattern.minFilter=s.NEAREST,this.dashPattern.magFilter=s.NEAREST,this.dashLength=f,c.free(d);var g=t.positions;this.data=g;var m=this.bounds;m[0]=m[1]=1/0,m[2]=m[3]=-(1/0);var v=this.numPoints=g.length>>>1;if(0!==v){for(e=0;e<v;++e)a=g[2*e],o=g[2*e+1],isNaN(a)||isNaN(o)||(m[0]=Math.min(m[0],a),m[1]=Math.min(m[1],o),m[2]=Math.max(m[2],a),m[3]=Math.max(m[3],o));m[0]===m[2]&&(m[2]+=1),m[3]===m[1]&&(m[3]+=1);var y=c.mallocFloat64(24*(v-1)),x=c.mallocFloat32(24*(v-1)),b=c.mallocFloat32(24*(v-1)),_=c.mallocUint32(12*(v-1)),w=x.length,M=_.length;n=v;for(var A=0;n>1;){var k=--n;a=g[2*n],o=g[2*n+1];var T=k-1,E=g[2*T],S=g[2*T+1];if(!(isNaN(a)||isNaN(o)||isNaN(E)||isNaN(S))){A+=1,a=(a-m[0])/(m[2]-m[0]),o=(o-m[1])/(m[3]-m[1]),E=(E-m[0])/(m[2]-m[0]),S=(S-m[1])/(m[3]-m[1]);var L=E-a,z=S-o,C=k|1<<24,I=k-1,P=k,D=k-1|1<<24;y[--w]=-z,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I,y[--w]=z,y[--w]=L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=-z,y[--w]=-L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=z,y[--w]=L,y[--w]=S,y[--w]=E,_[--M]=P,_[--M]=D,y[--w]=-z,y[--w]=-L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I,y[--w]=z,y[--w]=L,y[--w]=o,y[--w]=a,_[--M]=C,_[--M]=I}}for(e=0;e<y.length;e++)x[e]=y[e],b[e]=y[e]-x[e];this.vertCount=6*A,this.lineBufferHi.update(x.subarray(w)),this.lineBufferLo.update(b.subarray(w)),this.pickBuffer.update(_.subarray(M)),c.free(y),c.free(x),c.free(b),c.free(_)}},f.dispose=function(){this.plot.removeObject(this),this.lineBufferLo.dispose(),this.lineBufferHi.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":137,\"gl-buffer\":128,\"gl-shader\":220,\"gl-texture2d\":232,ndarray:427,\"typedarray-pool\":496}],139:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":220}],140:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=m(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=d(new Array(1024),[256,1,4]),h=0;h<1024;++h)s.data[h]=255;var f=c(e,s);f.wrap=e.REPEAT;var p=new o(e,r,n,i,a,f);return p.update(t),p}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),h=t(\"glsl-read-float\"),f=t(\"binary-search-bounds\"),d=t(\"ndarray\"),p=t(\"./lib/shaders\"),g=p.createShader,m=p.createPickShader,v=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||v,view:t.view||v,projection:t.projection||v,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){var e,r;this.dirty=!0;var i=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var a=t.position||t.positions;if(a){var o=t.color||t.colors||[0,0,0,1],s=t.lineWidth||1,l=[],u=[],c=[],h=0,p=0,g=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],m=!1;t:for(e=1;e<a.length;++e){var v=a[e-1],y=a[e];for(u.push(h),c.push(v.slice()),r=0;r<3;++r){if(isNaN(v[r])||isNaN(y[r])||!isFinite(v[r])||!isFinite(y[r])){if(!i&&l.length>0){for(var x=0;x<24;++x)l.push(l[l.length-12]);p+=2,m=!0}continue t}g[0][r]=Math.min(g[0][r],v[r],y[r]),g[1][r]=Math.max(g[1][r],v[r],y[r])}var b,_;Array.isArray(o[0])?(b=o[e-1],_=o[e]):b=_=o,3===b.length&&(b=[b[0],b[1],b[2],1]),3===_.length&&(_=[_[0],_[1],_[2],1]);var w;w=Array.isArray(s)?s[e-1]:s;var M=h;if(h+=n(v,y),m){for(r=0;r<2;++r)l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,b[0],b[1],b[2],b[3]);p+=2,m=!1}l.push(v[0],v[1],v[2],y[0],y[1],y[2],M,w,b[0],b[1],b[2],b[3],v[0],v[1],v[2],y[0],y[1],y[2],M,-w,b[0],b[1],b[2],b[3],y[0],y[1],y[2],v[0],v[1],v[2],h,-w,_[0],_[1],_[2],_[3],y[0],y[1],y[2],v[0],v[1],v[2],h,w,_[0],_[1],_[2],_[3]),p+=4}if(this.buffer.update(l),u.push(h),c.push(a[a.length-1].slice()),this.bounds=g,this.vertexCount=p,this.points=c,this.arcLength=u,\"dashes\"in t){var A=t.dashes,k=A.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var T=d(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)T.set(e,0,r,0);1&f.le(k,k[k.length-1]*e/255)?T.set(e,0,0,0):T.set(e,0,0,255)}this.texture.setPixels(T)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=h(t.value[0],t.value[1],t.value[2],0),r=f.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;u<3;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(o<.5?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":139,\"binary-search-bounds\":53,\"gl-buffer\":128,\"gl-texture2d\":232,\"gl-vao\":236,\"glsl-read-float\":243,ndarray:427}],141:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r*a-i*n;return o?(o=1/o,t[0]=a*o,t[1]=-n*o,t[2]=-i*o,t[3]=r*o,t):null}e.exports=n},{}],142:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=c*o-s*u,f=-c*a+s*l,d=u*a-o*l,p=r*h+n*f+i*d;return p?(p=1/p,t[0]=h*p,t[1]=(-c*n+i*u)*p,t[2]=(s*n-i*o)*p,t[3]=f*p,t[4]=(c*r-i*l)*p,t[5]=(-s*r+i*a)*p,t[6]=d*p,t[7]=(-u*r+n*l)*p,t[8]=(o*r-n*a)*p,t):null}e.exports=n},{}],143:[function(t,e,r){function n(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}e.exports=n},{}],144:[function(t,e,r){function n(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],145:[function(t,e,r){function n(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],g=t[14],m=t[15],v=e*o-r*a,y=e*s-n*a,x=e*l-i*a,b=r*s-n*o,_=r*l-i*o,w=n*l-i*s,M=u*p-c*d,A=u*g-h*d,k=u*m-f*d,T=c*g-h*p,E=c*m-f*p,S=h*m-f*g;return v*S-y*E+x*T+b*k-_*A+w*M}e.exports=n},{}],146:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-m,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+g,t[7]=0,t[8]=f+m,t[9]=d-g,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],147:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,g=a*u,m=o*s,v=o*l,y=o*u;return t[0]=1-(d+g),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+g),t[6]=p+m,t[7]=0,t[8]=f+v,t[9]=p-m,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],148:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],149:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,A=c*g-h*p,k=c*m-f*p,T=c*v-d*p,E=h*m-f*g,S=h*v-d*g,L=f*v-d*m,z=y*L-x*S+b*E+_*T-w*k+M*A;return z?(z=1/z,t[0]=(s*L-l*S+u*E)*z,t[1]=(i*S-n*L-a*E)*z,t[2]=(g*M-m*w+v*_)*z,t[3]=(f*w-h*M-d*_)*z,t[4]=(l*T-o*L-u*k)*z,t[5]=(r*L-i*T+a*k)*z,t[6]=(m*b-p*M-v*x)*z,t[7]=(c*M-f*b+d*x)*z,t[8]=(o*S-s*T+u*A)*z,t[9]=(n*T-r*S-a*A)*z,t[10]=(p*w-g*b+v*y)*z,t[11]=(h*b-c*w-d*y)*z,t[12]=(s*k-o*E-l*A)*z,t[13]=(r*E-n*k+i*A)*z,t[14]=(g*x-p*_-m*y)*z,t[15]=(c*_-h*x+f*y)*z,t):null}e.exports=n},{}],150:[function(t,e,r){function n(t,e,r,n){var a,o,s,l,u,c,h,f,d,p,g=e[0],m=e[1],v=e[2],y=n[0],x=n[1],b=n[2],_=r[0],w=r[1],M=r[2];return 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r=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=e[0],c=e[1],h=e[2],f=e[3],d=e[4],p=e[5];return Math.abs(r-u)<=n.EPSILON*Math.max(1,Math.abs(r),Math.abs(u))&&Math.abs(i-c)<=n.EPSILON*Math.max(1,Math.abs(i),Math.abs(c))&&Math.abs(a-h)<=n.EPSILON*Math.max(1,Math.abs(a),Math.abs(h))&&Math.abs(o-f)<=n.EPSILON*Math.max(1,Math.abs(o),Math.abs(f))&&Math.abs(s-d)<=n.EPSILON*Math.max(1,Math.abs(s),Math.abs(d))&&Math.abs(l-p)<=n.EPSILON*Math.max(1,Math.abs(l),Math.abs(p))},e.exports=i},{\"./common.js\":162}],165:[function(t,e,r){var n=t(\"./common.js\"),i={};i.create=function(){var t=new n.ARRAY_TYPE(9);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=1,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},i.fromMat4=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[4],t[4]=e[5],t[5]=e[6],t[6]=e[8],t[7]=e[9],t[8]=e[10],t},i.clone=function(t){var e=new n.ARRAY_TYPE(9);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e},i.copy=function(t,e){return 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t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t[3]=e[3]+r[3],t[4]=e[4]+r[4],t[5]=e[5]+r[5],t[6]=e[6]+r[6],t[7]=e[7]+r[7],t[8]=e[8]+r[8],t},i.subtract=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t[3]=e[3]-r[3],t[4]=e[4]-r[4],t[5]=e[5]-r[5],t[6]=e[6]-r[6],t[7]=e[7]-r[7],t[8]=e[8]-r[8],t},i.sub=i.subtract,i.multiplyScalar=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t[3]=e[3]*r,t[4]=e[4]*r,t[5]=e[5]*r,t[6]=e[6]*r,t[7]=e[7]*r,t[8]=e[8]*r,t},i.multiplyScalarAndAdd=function(t,e,r,n){return t[0]=e[0]+r[0]*n,t[1]=e[1]+r[1]*n,t[2]=e[2]+r[2]*n,t[3]=e[3]+r[3]*n,t[4]=e[4]+r[4]*n,t[5]=e[5]+r[5]*n,t[6]=e[6]+r[6]*n,t[7]=e[7]+r[7]*n,t[8]=e[8]+r[8]*n,t},i.exactEquals=function(t,e){return t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]&&t[3]===e[3]&&t[4]===e[4]&&t[5]===e[5]&&t[6]===e[6]&&t[7]===e[7]&&t[8]===e[8]},i.equals=function(t,e){var r=t[0],i=t[1],a=t[2],o=t[3],s=t[4],l=t[5],u=t[6],c=t[7],h=t[8],f=e[0],d=e[1],p=e[2],g=e[3],m=e[4],v=e[5],y=t[6],x=e[7],b=e[8];return 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e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},i.copy=function(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.fromValues=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,g,m){var v=new n.ARRAY_TYPE(16);return v[0]=t,v[1]=e,v[2]=r,v[3]=i,v[4]=a,v[5]=o,v[6]=s,v[7]=l,v[8]=u,v[9]=c,v[10]=h,v[11]=f,v[12]=d,v[13]=p,v[14]=g,v[15]=m,v},i.set=function(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,g,m){return t[0]=e,t[1]=r,t[2]=n,t[3]=i,t[4]=a,t[5]=o,t[6]=s,t[7]=l,t[8]=u,t[9]=c,t[10]=h,t[11]=f,t[12]=d,t[13]=p,t[14]=g,t[15]=m,t},i.identity=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.scalar.transpose=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t},i.SIMD.transpose=function(t,e){var r,n,i,a,o,s,l,u,c,h;return r=SIMD.Float32x4.load(e,0),n=SIMD.Float32x4.load(e,4),i=SIMD.Float32x4.load(e,8),a=SIMD.Float32x4.load(e,12),o=SIMD.Float32x4.shuffle(r,n,0,1,4,5),s=SIMD.Float32x4.shuffle(i,a,0,1,4,5),l=SIMD.Float32x4.shuffle(o,s,0,2,4,6),u=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,0,l),SIMD.Float32x4.store(t,4,u),o=SIMD.Float32x4.shuffle(r,n,2,3,6,7),s=SIMD.Float32x4.shuffle(i,a,2,3,6,7),c=SIMD.Float32x4.shuffle(o,s,0,2,4,6),h=SIMD.Float32x4.shuffle(o,s,1,3,5,7),SIMD.Float32x4.store(t,8,c),SIMD.Float32x4.store(t,12,h),t},i.transpose=n.USE_SIMD?i.SIMD.transpose:i.scalar.transpose,i.scalar.invert=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*u-a*o,_=n*l-i*s,w=n*u-a*s,M=i*u-a*l,A=c*g-h*p,k=c*m-f*p,T=c*v-d*p,E=h*m-f*g,S=h*v-d*g,L=f*v-d*m,z=y*L-x*S+b*E+_*T-w*k+M*A;return z?(z=1/z,t[0]=(s*L-l*S+u*E)*z,t[1]=(i*S-n*L-a*E)*z,t[2]=(g*M-m*w+v*_)*z,t[3]=(f*w-h*M-d*_)*z,t[4]=(l*T-o*L-u*k)*z,t[5]=(r*L-i*T+a*k)*z,t[6]=(m*b-p*M-v*x)*z,t[7]=(c*M-f*b+d*x)*z,t[8]=(o*S-s*T+u*A)*z,t[9]=(n*T-r*S-a*A)*z,t[10]=(p*w-g*b+v*y)*z,t[11]=(h*b-c*w-d*y)*z,t[12]=(s*k-o*E-l*A)*z,t[13]=(r*E-n*k+i*A)*z,t[14]=(g*x-p*_-m*y)*z,t[15]=(c*_-h*x+f*y)*z,t):null},i.SIMD.invert=function(t,e){var r,n,i,a,o,s,l,u,c,h,f=SIMD.Float32x4.load(e,0),d=SIMD.Float32x4.load(e,4),p=SIMD.Float32x4.load(e,8),g=SIMD.Float32x4.load(e,12);return o=SIMD.Float32x4.shuffle(f,d,0,1,4,5),n=SIMD.Float32x4.shuffle(p,g,0,1,4,5),r=SIMD.Float32x4.shuffle(o,n,0,2,4,6),n=SIMD.Float32x4.shuffle(n,o,1,3,5,7),o=SIMD.Float32x4.shuffle(f,d,2,3,6,7),a=SIMD.Float32x4.shuffle(p,g,2,3,6,7),i=SIMD.Float32x4.shuffle(o,a,0,2,4,6),a=SIMD.Float32x4.shuffle(a,o,1,3,5,7),o=SIMD.Float32x4.mul(i,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.mul(n,o),l=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(SIMD.Float32x4.mul(n,o),s),l=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),l),l=SIMD.Float32x4.swizzle(l,2,3,0,1),o=SIMD.Float32x4.mul(n,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),s),c=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),o=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(n,2,3,0,1),a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),i=SIMD.Float32x4.swizzle(i,2,3,0,1),s=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),s),u=SIMD.Float32x4.mul(r,o),o=SIMD.Float32x4.swizzle(o,2,3,0,1),s=SIMD.Float32x4.sub(s,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(r,o),u),u=SIMD.Float32x4.swizzle(u,2,3,0,1),o=SIMD.Float32x4.mul(r,n),o=SIMD.Float32x4.swizzle(o,1,0,3,2),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(SIMD.Float32x4.mul(i,o),c),o=SIMD.Float32x4.swizzle(o,2,3,0,1),u=SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,o),u),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(i,o)),o=SIMD.Float32x4.mul(r,a),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(i,o)),u=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),u),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(i,o),l),u=SIMD.Float32x4.sub(u,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.mul(r,i),o=SIMD.Float32x4.swizzle(o,1,0,3,2),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(a,o),l),c=SIMD.Float32x4.sub(c,SIMD.Float32x4.mul(n,o)),o=SIMD.Float32x4.swizzle(o,2,3,0,1),l=SIMD.Float32x4.sub(l,SIMD.Float32x4.mul(a,o)),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(n,o),c),h=SIMD.Float32x4.mul(r,s),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,2,3,0,1),h),h=SIMD.Float32x4.add(SIMD.Float32x4.swizzle(h,1,0,3,2),h),o=SIMD.Float32x4.reciprocalApproximation(h),h=SIMD.Float32x4.sub(SIMD.Float32x4.add(o,o),SIMD.Float32x4.mul(h,SIMD.Float32x4.mul(o,o))),(h=SIMD.Float32x4.swizzle(h,0,0,0,0))?(SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(h,s)),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(h,l)),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(h,u)),SIMD.Float32x4.store(t,12,SIMD.Float32x4.mul(h,c)),t):null},i.invert=n.USE_SIMD?i.SIMD.invert:i.scalar.invert,i.scalar.adjoint=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],h=e[9],f=e[10],d=e[11],p=e[12],g=e[13],m=e[14],v=e[15];return t[0]=s*(f*v-d*m)-h*(l*v-u*m)+g*(l*d-u*f),t[1]=-(n*(f*v-d*m)-h*(i*v-a*m)+g*(i*d-a*f)),t[2]=n*(l*v-u*m)-s*(i*v-a*m)+g*(i*u-a*l),t[3]=-(n*(l*d-u*f)-s*(i*d-a*f)+h*(i*u-a*l)),t[4]=-(o*(f*v-d*m)-c*(l*v-u*m)+p*(l*d-u*f)),t[5]=r*(f*v-d*m)-c*(i*v-a*m)+p*(i*d-a*f),t[6]=-(r*(l*v-u*m)-o*(i*v-a*m)+p*(i*u-a*l)),t[7]=r*(l*d-u*f)-o*(i*d-a*f)+c*(i*u-a*l),t[8]=o*(h*v-d*g)-c*(s*v-u*g)+p*(s*d-u*h),t[9]=-(r*(h*v-d*g)-c*(n*v-a*g)+p*(n*d-a*h)),t[10]=r*(s*v-u*g)-o*(n*v-a*g)+p*(n*u-a*s),t[11]=-(r*(s*d-u*h)-o*(n*d-a*h)+c*(n*u-a*s)),t[12]=-(o*(h*m-f*g)-c*(s*m-l*g)+p*(s*f-l*h)),t[13]=r*(h*m-f*g)-c*(n*m-i*g)+p*(n*f-i*h),t[14]=-(r*(s*m-l*g)-o*(n*m-i*g)+p*(n*l-i*s)),t[15]=r*(s*f-l*h)-o*(n*f-i*h)+c*(n*l-i*s),t},i.SIMD.adjoint=function(t,e){var r,n,i,a,o,s,l,u,c,h,f,d,p,r=SIMD.Float32x4.load(e,0),n=SIMD.Float32x4.load(e,4),i=SIMD.Float32x4.load(e,8),a=SIMD.Float32x4.load(e,12);return c=SIMD.Float32x4.shuffle(r,n,0,1,4,5),s=SIMD.Float32x4.shuffle(i,a,0,1,4,5),o=SIMD.Float32x4.shuffle(c,s,0,2,4,6),s=SIMD.Float32x4.shuffle(s,c,1,3,5,7),c=SIMD.Float32x4.shuffle(r,n,2,3,6,7),u=SIMD.Float32x4.shuffle(i,a,2,3,6,7),l=SIMD.Float32x4.shuffle(c,u,0,2,4,6),u=SIMD.Float32x4.shuffle(u,c,1,3,5,7),c=SIMD.Float32x4.mul(l,u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),h=SIMD.Float32x4.mul(s,c),f=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(SIMD.Float32x4.mul(s,c),h),f=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),f),f=SIMD.Float32x4.swizzle(f,2,3,0,1),c=SIMD.Float32x4.mul(s,l),c=SIMD.Float32x4.swizzle(c,1,0,3,2),h=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),h),p=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(h,SIMD.Float32x4.mul(u,c)),p=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),p),p=SIMD.Float32x4.swizzle(p,2,3,0,1),c=SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,2,3,0,1),u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),l=SIMD.Float32x4.swizzle(l,2,3,0,1),h=SIMD.Float32x4.add(SIMD.Float32x4.mul(l,c),h),d=SIMD.Float32x4.mul(o,c),c=SIMD.Float32x4.swizzle(c,2,3,0,1),h=SIMD.Float32x4.sub(h,SIMD.Float32x4.mul(l,c)),d=SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,c),d),d=SIMD.Float32x4.swizzle(d,2,3,0,1),c=SIMD.Float32x4.mul(o,s),c=SIMD.Float32x4.swizzle(c,1,0,3,2),d=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),d),p=SIMD.Float32x4.sub(SIMD.Float32x4.mul(l,c),p),c=SIMD.Float32x4.swizzle(c,2,3,0,1),d=SIMD.Float32x4.sub(SIMD.Float32x4.mul(u,c),d),p=SIMD.Float32x4.sub(p,SIMD.Float32x4.mul(l,c)),c=SIMD.Float32x4.mul(o,u),c=SIMD.Float32x4.swizzle(c,1,0,3,2),f=SIMD.Float32x4.sub(f,SIMD.Float32x4.mul(l,c)),d=SIMD.Float32x4.add(SIMD.Float32x4.mul(s,c),d),c=SIMD.Float32x4.swizzle(c,2,3,0,1),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(l,c),f),d=SIMD.Float32x4.sub(d,SIMD.Float32x4.mul(s,c)),c=SIMD.Float32x4.mul(o,l),c=SIMD.Float32x4.swizzle(c,1,0,3,2),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(u,c),f),p=SIMD.Float32x4.sub(p,SIMD.Float32x4.mul(s,c)),c=SIMD.Float32x4.swizzle(c,2,3,0,1),f=SIMD.Float32x4.sub(f,SIMD.Float32x4.mul(u,c)),p=SIMD.Float32x4.add(SIMD.Float32x4.mul(s,c),p),SIMD.Float32x4.store(t,0,h),SIMD.Float32x4.store(t,4,f),SIMD.Float32x4.store(t,8,d),SIMD.Float32x4.store(t,12,p),t},i.adjoint=n.USE_SIMD?i.SIMD.adjoint:i.scalar.adjoint,i.determinant=function(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],h=t[10],f=t[11],d=t[12],p=t[13],g=t[14],m=t[15],v=e*o-r*a,y=e*s-n*a,x=e*l-i*a,b=r*s-n*o,_=r*l-i*o,w=n*l-i*s,M=u*p-c*d,A=u*g-h*d,k=u*m-f*d,T=c*g-h*p,E=c*m-f*p,S=h*m-f*g;return v*S-y*E+x*T+b*k-_*A+w*M},i.SIMD.multiply=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4.load(r,0),l=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(s,3,3,3,3),o))));SIMD.Float32x4.store(t,0,l);var u=SIMD.Float32x4.load(r,4),c=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(u,3,3,3,3),o))));SIMD.Float32x4.store(t,4,c);var h=SIMD.Float32x4.load(r,8),f=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(h,3,3,3,3),o))));SIMD.Float32x4.store(t,8,f);var d=SIMD.Float32x4.load(r,12),p=SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,0,0,0,0),n),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,1,1,1,1),i),SIMD.Float32x4.add(SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,2,2,2,2),a),SIMD.Float32x4.mul(SIMD.Float32x4.swizzle(d,3,3,3,3),o))));return SIMD.Float32x4.store(t,12,p),t},i.scalar.multiply=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*h+w*g,t[1]=x*i+b*l+_*f+w*m,t[2]=x*a+b*u+_*d+w*v,t[3]=x*o+b*c+_*p+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*h+w*g,t[5]=x*i+b*l+_*f+w*m,t[6]=x*a+b*u+_*d+w*v,t[7]=x*o+b*c+_*p+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*h+w*g,t[9]=x*i+b*l+_*f+w*m,t[10]=x*a+b*u+_*d+w*v,t[11]=x*o+b*c+_*p+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*h+w*g,t[13]=x*i+b*l+_*f+w*m,t[14]=x*a+b*u+_*d+w*v,t[15]=x*o+b*c+_*p+w*y,t},i.multiply=n.USE_SIMD?i.SIMD.multiply:i.scalar.multiply,i.mul=i.multiply,i.scalar.translate=function(t,e,r){var n,i,a,o,s,l,u,c,h,f,d,p,g=r[0],m=r[1],v=r[2];return e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],h=e[8],f=e[9],d=e[10],p=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=u,t[7]=c,t[8]=h,t[9]=f,t[10]=d,t[11]=p,t[12]=n*g+s*m+h*v+e[12],t[13]=i*g+l*m+f*v+e[13],t[14]=a*g+u*m+d*v+e[14],t[15]=o*g+c*m+p*v+e[15]),t},i.SIMD.translate=function(t,e,r){var n=SIMD.Float32x4.load(e,0),i=SIMD.Float32x4.load(e,4),a=SIMD.Float32x4.load(e,8),o=SIMD.Float32x4.load(e,12),s=SIMD.Float32x4(r[0],r[1],r[2],0);e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11]),n=SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(s,0,0,0,0)),i=SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(s,1,1,1,1)),a=SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(s,2,2,2,2));var l=SIMD.Float32x4.add(n,SIMD.Float32x4.add(i,SIMD.Float32x4.add(a,o)));return SIMD.Float32x4.store(t,12,l),t},i.translate=n.USE_SIMD?i.SIMD.translate:i.scalar.translate,i.scalar.scale=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.SIMD.scale=function(t,e,r){var n,i,a,o=SIMD.Float32x4(r[0],r[1],r[2],0);return n=SIMD.Float32x4.load(e,0),SIMD.Float32x4.store(t,0,SIMD.Float32x4.mul(n,SIMD.Float32x4.swizzle(o,0,0,0,0))),i=SIMD.Float32x4.load(e,4),SIMD.Float32x4.store(t,4,SIMD.Float32x4.mul(i,SIMD.Float32x4.swizzle(o,1,1,1,1))),a=SIMD.Float32x4.load(e,8),SIMD.Float32x4.store(t,8,SIMD.Float32x4.mul(a,SIMD.Float32x4.swizzle(o,2,2,2,2))),t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t},i.scale=n.USE_SIMD?i.SIMD.scale:i.scalar.scale,i.rotate=function(t,e,r,i){var a,o,s,l,u,c,h,f,d,p,g,m,v,y,x,b,_,w,M,A,k,T,E,S,L=i[0],z=i[1],C=i[2],I=Math.sqrt(L*L+z*z+C*C);return Math.abs(I)<n.EPSILON?null:(I=1/I,L*=I,z*=I,C*=I,a=Math.sin(r),o=Math.cos(r),s=1-o,l=e[0],u=e[1],c=e[2],h=e[3],f=e[4],d=e[5],p=e[6],g=e[7],m=e[8],v=e[9],y=e[10],x=e[11],b=L*L*s+o,_=z*L*s+C*a,w=C*L*s-z*a,M=L*z*s-C*a,A=z*z*s+o,k=C*z*s+L*a,T=L*C*s+z*a,E=z*C*s-L*a,S=C*C*s+o,t[0]=l*b+f*_+m*w,t[1]=u*b+d*_+v*w,t[2]=c*b+p*_+y*w,t[3]=h*b+g*_+x*w,t[4]=l*M+f*A+m*k,t[5]=u*M+d*A+v*k,t[6]=c*M+p*A+y*k,t[7]=h*M+g*A+x*k,t[8]=l*T+f*E+m*S,t[9]=u*T+d*E+v*S,t[10]=c*T+p*E+y*S,t[11]=h*T+g*E+x*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)},i.scalar.rotateX=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],h=e[10],f=e[11];return e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[4]=a*i+u*n,t[5]=o*i+c*n,t[6]=s*i+h*n,t[7]=l*i+f*n,t[8]=u*i-a*n,t[9]=c*i-o*n,t[10]=h*i-s*n,t[11]=f*i-l*n,t},i.SIMD.rotateX=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,4),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,4,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateX=n.USE_SIMD?i.SIMD.rotateX:i.scalar.rotateX,i.scalar.rotateY=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],h=e[10],f=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-h*n,t[3]=l*i-f*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+h*i,t[11]=l*n+f*i,t},i.SIMD.rotateY=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,8);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.sub(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,8,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,n),SIMD.Float32x4.mul(o,i))),t},i.rotateY=n.USE_SIMD?i.SIMD.rotateY:i.scalar.rotateY,i.scalar.rotateZ=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],h=e[6],f=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+h*n,t[3]=l*i+f*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=h*i-s*n,t[7]=f*i-l*n,t},i.SIMD.rotateZ=function(t,e,r){var n=SIMD.Float32x4.splat(Math.sin(r)),i=SIMD.Float32x4.splat(Math.cos(r));e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);var a=SIMD.Float32x4.load(e,0),o=SIMD.Float32x4.load(e,4);return SIMD.Float32x4.store(t,0,SIMD.Float32x4.add(SIMD.Float32x4.mul(a,i),SIMD.Float32x4.mul(o,n))),SIMD.Float32x4.store(t,4,SIMD.Float32x4.sub(SIMD.Float32x4.mul(o,i),SIMD.Float32x4.mul(a,n))),t},i.rotateZ=n.USE_SIMD?i.SIMD.rotateZ:i.scalar.rotateZ,i.fromTranslation=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t},i.fromScaling=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromRotation=function(t,e,r){var i,a,o,s=r[0],l=r[1],u=r[2],c=Math.sqrt(s*s+l*l+u*u);return Math.abs(c)<n.EPSILON?null:(c=1/c,s*=c,l*=c,u*=c,i=Math.sin(e),a=Math.cos(e),o=1-a,t[0]=s*s*o+a,t[1]=l*s*o+u*i,t[2]=u*s*o-l*i,t[3]=0,t[4]=s*l*o-u*i,t[5]=l*l*o+a,t[6]=u*l*o+s*i,t[7]=0,t[8]=s*u*o+l*i,t[9]=l*u*o-s*i,t[10]=u*u*o+a,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t)},i.fromXRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromYRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromZRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.fromRotationTranslation=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,h=n*l,f=n*u,d=i*l,p=i*u,g=a*u,m=o*s,v=o*l,y=o*u;return t[0]=1-(d+g),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(c+g),t[6]=p+m,t[7]=0,t[8]=f+v,t[9]=p-m,t[10]=1-(c+d),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.getTranslation=function(t,e){return t[0]=e[12],t[1]=e[13],t[2]=e[14],t},i.getRotation=function(t,e){var r=e[0]+e[5]+e[10],n=0;return r>0?(n=2*Math.sqrt(r+1),t[3]=.25*n,t[0]=(e[6]-e[9])/n,t[1]=(e[8]-e[2])/n,t[2]=(e[1]-e[4])/n):e[0]>e[5]&e[0]>e[10]?(n=2*Math.sqrt(1+e[0]-e[5]-e[10]),t[3]=(e[6]-e[9])/n,t[0]=.25*n,t[1]=(e[1]+e[4])/n,t[2]=(e[8]+e[2])/n):e[5]>e[10]?(n=2*Math.sqrt(1+e[5]-e[0]-e[10]),t[3]=(e[8]-e[2])/n,t[0]=(e[1]+e[4])/n,t[1]=.25*n,t[2]=(e[6]+e[9])/n):(n=2*Math.sqrt(1+e[10]-e[0]-e[5]),t[3]=(e[1]-e[4])/n,t[0]=(e[8]+e[2])/n,t[1]=(e[6]+e[9])/n,t[2]=.25*n),t},i.fromRotationTranslationScale=function(t,e,r,n){var i=e[0],a=e[1],o=e[2],s=e[3],l=i+i,u=a+a,c=o+o,h=i*l,f=i*u,d=i*c,p=a*u,g=a*c,m=o*c,v=s*l,y=s*u,x=s*c,b=n[0],_=n[1],w=n[2];return t[0]=(1-(p+m))*b,t[1]=(f+x)*b,t[2]=(d-y)*b,t[3]=0,t[4]=(f-x)*_,t[5]=(1-(h+m))*_,t[6]=(g+v)*_,t[7]=0,t[8]=(d+y)*w,t[9]=(g-v)*w,t[10]=(1-(h+p))*w,t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t},i.fromRotationTranslationScaleOrigin=function(t,e,r,n,i){var a=e[0],o=e[1],s=e[2],l=e[3],u=a+a,c=o+o,h=s+s,f=a*u,d=a*c,p=a*h,g=o*c,m=o*h,v=s*h,y=l*u,x=l*c,b=l*h,_=n[0],w=n[1],M=n[2],A=i[0],k=i[1],T=i[2];return t[0]=(1-(g+v))*_,t[1]=(d+b)*_,t[2]=(p-x)*_,t[3]=0,t[4]=(d-b)*w,t[5]=(1-(f+v))*w,t[6]=(m+y)*w,t[7]=0,t[8]=(p+x)*M,t[9]=(m-y)*M,t[10]=(1-(f+g))*M,t[11]=0,t[12]=r[0]+A-(t[0]*A+t[4]*k+t[8]*T),t[13]=r[1]+k-(t[1]*A+t[5]*k+t[9]*T),t[14]=r[2]+T-(t[2]*A+t[6]*k+t[10]*T),t[15]=1,t},i.fromQuat=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,h=n*s,f=i*o,d=i*s,p=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-h-p,t[1]=c+v,t[2]=f-m,t[3]=0,t[4]=c-v,t[5]=1-u-p,t[6]=d+g,t[7]=0,t[8]=f+m,t[9]=d-g,t[10]=1-u-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t},i.frustum=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),u=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*u,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*u,t[15]=0,t},i.perspective=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t},i.perspectiveFromFieldOfView=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),u=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=u,t[6]=0,t[7]=0,t[8]=-((o-s)*l*.5),t[9]=(i-a)*u*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t},i.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},i.lookAt=function(t,e,r,a){var o,s,l,u,c,h,f,d,p,g,m=e[0],v=e[1],y=e[2],x=a[0],b=a[1],_=a[2],w=r[0],M=r[1],A=r[2];return Math.abs(m-w)<n.EPSILON&&Math.abs(v-M)<n.EPSILON&&Math.abs(y-A)<n.EPSILON?i.identity(t):(f=m-w,d=v-M,p=y-A,g=1/Math.sqrt(f*f+d*d+p*p),f*=g,d*=g,p*=g,o=b*p-_*d,s=_*f-x*p,l=x*d-b*f,g=Math.sqrt(o*o+s*s+l*l),g?(g=1/g,o*=g,s*=g,l*=g):(o=0,s=0,l=0),u=d*l-p*s,c=p*o-f*l,h=f*s-d*o,g=Math.sqrt(u*u+c*c+h*h),g?(g=1/g,u*=g,c*=g,h*=g):(u=0,c=0,h=0),t[0]=o,t[1]=u,t[2]=f,t[3]=0,t[4]=s,t[5]=c,t[6]=d,t[7]=0,t[8]=l,t[9]=h,t[10]=p,t[11]=0,t[12]=-(o*m+s*v+l*y),t[13]=-(u*m+c*v+h*y),t[14]=-(f*m+d*v+p*y),t[15]=1,t)},i.str=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\";\n",
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 , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution_2_0(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n  \\n  if(!gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = cookTorranceSpecular_1_1(L, V, N, roughness, fresnel);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(f_data, clipBounds[0])) || \\n     any(greaterThan(f_data, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\",l=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5,0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\",u=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\",c=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(f_position, clipBounds[0])) || \\n     any(greaterThan(f_position, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\",h=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || \\n     any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\",f=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\",d=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor,1);\\n}\\n\";r.meshShader={vertex:n,fragment:i,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:a,fragment:o,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:s,fragment:l,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:f,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{}],173:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c,h,f,d,p,g,m,v,y,x,b,_,w,M,A,k,T){this.gl=t,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=u,this.triangleVAO=d,this.triangleCount=0,this.lineWidth=1,this.edgePositions=p,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=w,this.pointSizes=M,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=k,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this._model=R,this._view=R,this._projection=R,this._resolution=[1,1]}function i(t){for(var e=A({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return M(r,[256,256,4],[4,0,1])}function a(t,e,r){for(var n=new Array(e),i=0;i<e;++i)n[i]=0;for(var a=t.length,i=0;i<a;++i)for(var o=t[i],s=0;s<o.length;++s)n[o[s]]=r[i];return n}function o(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}function s(t){var e=m(t,L);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function l(t){var e=m(t,z);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function u(t){var e=m(t,C);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function c(t){var e=m(t,I);return e.attributes.position.location=0,e.attributes.id.location=1,e}function h(t){var e=m(t,P);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function f(t){var e=m(t,D);return e.attributes.position.location=0,e}function d(t){var e=t.gl,r=s(e),i=l(e),a=u(e),o=c(e),d=h(e),p=f(e),g=x(e,M(new Uint8Array([255,255,255,255]),[1,1,4]));g.generateMipmap(),g.minFilter=e.LINEAR_MIPMAP_LINEAR,g.magFilter=e.LINEAR;var m=v(e),b=v(e),_=v(e),w=v(e),A=v(e),k=y(e,[{buffer:m,type:e.FLOAT,size:3},{buffer:A,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:b,type:e.FLOAT,size:4},{buffer:_,type:e.FLOAT,size:2},{buffer:w,type:e.FLOAT,size:3}]),T=v(e),E=v(e),S=v(e),L=v(e),z=y(e,[{buffer:T,type:e.FLOAT,size:3},{buffer:L,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:E,type:e.FLOAT,size:4},{buffer:S,type:e.FLOAT,size:2}]),C=v(e),I=v(e),P=v(e),D=v(e),R=v(e),O=y(e,[{buffer:C,type:e.FLOAT,size:3},{buffer:R,type:e.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:I,type:e.FLOAT,size:4},{buffer:P,type:e.FLOAT,size:2},{buffer:D,type:e.FLOAT,size:1}]),F=v(e),j=y(e,[{buffer:F,type:e.FLOAT,size:3}]),N=new n(e,g,r,i,a,o,d,p,m,A,b,_,w,k,T,L,E,S,z,C,R,I,P,D,O,F,j);return N.update(t),N}var p=1e-6,g=1e-6,m=t(\"gl-shader\"),v=t(\"gl-buffer\"),y=t(\"gl-vao\"),x=t(\"gl-texture2d\"),b=t(\"normals\"),_=t(\"gl-mat4/multiply\"),w=t(\"gl-mat4/invert\"),M=t(\"ndarray\"),A=t(\"colormap\"),k=t(\"simplicial-complex-contour\"),T=t(\"typedarray-pool\"),E=t(\"./lib/shaders\"),S=t(\"./lib/closest-point\"),L=E.meshShader,z=E.wireShader,C=E.pointShader,I=E.pickShader,P=E.pointPickShader,D=E.contourShader,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=n.prototype;O.isOpaque=function(){return this.opacity>=1},O.isTransparent=function(){return this.opacity<1},O.pickSlots=1,O.setPickBase=function(t){this.pickId=t},O.highlight=function(t){if(!t||!this.contourEnable)return void(this.contourCount=0);for(var e=k(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=T.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var u=r[l],c=0;c<2;++c){var h=u[0];2===u.length&&(h=u[c]);for(var f=n[h][0],d=n[h][1],p=i[h],g=1-p,m=this.positions[f],v=this.positions[d],y=0;y<3;++y)o[s++]=p*m[y]+g*v[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),T.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=x(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),\n",
+       "this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],h=[],f=[],d=[],m=[],v=[],y=[],_=[],w=[],M=[],A=[];this.cells=r,this.positions=n;var k=t.vertexNormals,T=t.cellNormals,E=void 0===t.vertexNormalsEpsilon?p:t.vertexNormalsEpsilon,S=void 0===t.faceNormalsEpsilon?g:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=b.faceNormals(r,n,S)),T||k||(k=b.vertexNormals(r,n,E));var L=t.vertexColors,z=t.cellColors,C=t.meshColor||[1,1,1,1],I=t.vertexUVs,P=t.vertexIntensity,D=t.cellUVs,R=t.cellIntensity,O=1/0,F=-(1/0);if(!I&&!D)if(P)for(var j=0;j<P.length;++j){var N=P[j];O=Math.min(O,N),F=Math.max(F,N)}else if(R)for(var j=0;j<R.length;++j){var N=R[j];O=Math.min(O,N),F=Math.max(F,N)}else for(var j=0;j<n.length;++j){var N=n[j][2];O=Math.min(O,N),F=Math.max(F,N)}P?this.intensity=P:R?this.intensity=a(r,n.length,R):this.intensity=o(n);var B=t.pointSizes,U=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var j=0;j<n.length;++j)for(var V=n[j],q=0;q<3;++q)!isNaN(V[q])&&isFinite(V[q])&&(this.bounds[0][q]=Math.min(this.bounds[0][q],V[q]),this.bounds[1][q]=Math.max(this.bounds[1][q],V[q]));var H=0,G=0,X=0;t:for(var j=0;j<r.length;++j){var Y=r[j];switch(Y.length){case 1:for(var W=Y[0],V=n[W],q=0;q<3;++q)if(isNaN(V[q])||!isFinite(V[q]))continue t;y.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?_.push(Z[0],Z[1],Z[2],1):_.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],w.push(Q[0],Q[1]),B?M.push(B[W]):M.push(U),A.push(j),X+=1;break;case 2:for(var q=0;q<2;++q)for(var W=Y[q],V=n[W],K=0;K<3;++K)if(isNaN(V[K])||!isFinite(V[K]))continue t;for(var q=0;q<2;++q){var W=Y[q],V=n[W];f.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?d.push(Z[0],Z[1],Z[2],1):d.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],m.push(Q[0],Q[1]),v.push(j)}G+=1;break;case 3:for(var q=0;q<3;++q)for(var W=Y[q],V=n[W],K=0;K<3;++K)if(isNaN(V[K])||!isFinite(V[K]))continue t;for(var q=0;q<3;++q){var W=Y[q],V=n[W];s.push(V[0],V[1],V[2]);var Z;Z=L?L[W]:z?z[j]:C,3===Z.length?l.push(Z[0],Z[1],Z[2],1):l.push(Z[0],Z[1],Z[2],Z[3]);var Q;Q=I?I[W]:P?[(P[W]-O)/(F-O),0]:D?D[j]:R?[(R[j]-O)/(F-O),0]:[(V[2]-O)/(F-O),0],c.push(Q[0],Q[1]);var $;$=k?k[W]:T[j],u.push($[0],$[1],$[2]),h.push(j)}H+=1}}this.pointCount=X,this.edgeCount=G,this.triangleCount=H,this.pointPositions.update(y),this.pointColors.update(_),this.pointUVs.update(w),this.pointSizes.update(M),this.pointIds.update(new Uint32Array(A)),this.edgePositions.update(f),this.edgeColors.update(d),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(v)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(h))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);_(l,s.view,s.model),_(l,s.projection,l),w(l,l);for(var o=0;o<3;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;o<3;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;o<3;++o){for(var c=l[12+o],h=0;h<3;++h)c+=l[4*h+o]*this.lightPosition[h];s.lightPosition[o]=c/u}if(this.triangleCount>0){var f=this.triShader;f.bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var f=this.lineShader;f.bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var f=this.pointShader;f.bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var f=this.contourShader;f.bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=S(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=d},{\"./lib/closest-point\":171,\"./lib/shaders\":172,colormap:80,\"gl-buffer\":128,\"gl-mat4/invert\":149,\"gl-mat4/multiply\":151,\"gl-shader\":220,\"gl-texture2d\":232,\"gl-vao\":236,ndarray:427,normals:429,\"simplicial-complex-contour\":474,\"typedarray-pool\":496}],174:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[0,0,0,1,1,0,1,1]),i=o(e,s.boxVert,s.lineFrag);return new n(t,r,i)}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawBox=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o){var s=this.plot,l=this.shader,u=s.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,l.uniforms.lo=t,l.uniforms.hi=e,l.uniforms.color=o,u.drawArrays(u.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"gl-buffer\":128,\"gl-shader\":180}],175:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function i(t,e){return t-e}function a(t){var e=t.gl,r=o(e),i=s(e,u.gridVert,u.gridFrag),a=s(e,u.tickVert,u.gridFrag),l=new n(t,r,i,a);return l}e.exports=a;var o=t(\"gl-buffer\"),s=t(\"gl-shader\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.draw=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){for(var n=this.plot,i=this.vbo,a=this.shader,o=this.ticks,s=n.gl,l=n._tickBounds,u=n.dataBox,c=n.viewBox,h=n.gridLineWidth,f=n.gridLineColor,d=n.gridLineEnable,p=n.pixelRatio,g=0;g<2;++g){var m=l[g],v=l[g+2],y=v-m,x=.5*(u[g+2]+u[g]),b=u[g+2]-u[g];e[g]=2*y/b,t[g]=2*(m-x)/b}a.bind(),i.bind(),a.attributes.dataCoord.pointer(),a.uniforms.dataShift=t,a.uniforms.dataScale=e;for(var _=0,g=0;g<2;++g){r[0]=r[1]=0,r[g]=1,a.uniforms.dataAxis=r,a.uniforms.lineWidth=h[g]/(c[g+2]-c[g])*p,a.uniforms.color=f[g];var w=6*o[g].length;d[g]&&w&&s.drawArrays(s.TRIANGLES,_,w),_+=w}}}(),c.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,h=this.ticks,f=s.gl,d=s._tickBounds,p=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var M=d[w],A=d[w+2],k=A-M,T=.5*(p[w+2]+p[w]),E=p[w+2]-p[w];e[w]=2*k/E,t[w]=2*(M-T)/E}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var S=c.uniforms;S.dataShift=t,S.dataScale=e;var L=s.tickMarkLength,z=s.tickMarkWidth,C=s.tickMarkColor,I=0,P=6*h[0].length,D=Math.min(l.ge(h[0],(p[0]-d[0])/(d[2]-d[0]),i),h[0].length),R=Math.min(l.gt(h[0],(p[2]-d[0])/(d[2]-d[0]),i),h[0].length),O=I+6*D,F=6*Math.max(0,R-D),j=Math.min(l.ge(h[1],(p[1]-d[1])/(d[3]-d[1]),i),h[1].length),N=Math.min(l.gt(h[1],(p[3]-d[1])/(d[3]-d[1]),i),h[1].length),B=P+6*j,U=6*Math.max(0,N-j);a[0]=2*(g[0]-L[1])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=L[1]*m/y,o[1]=z[1]*m/x,U&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,U)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-L[0])/x-1,o[0]=z[0]*m/y,o[1]=L[0]*m/x,F&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,F)),a[0]=2*(g[2]+L[3])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=L[3]*m/y,o[1]=z[3]*m/x,U&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,U)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+L[2])/x-1,o[0]=z[2]*m/y,o[1]=L[2]*m/x,F&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,F))}}(),c.update=function(){var t=[1,1,-1,-1,1,-1],e=[1,-1,1,1,-1,-1];return function(r){for(var n=r.ticks,i=r.bounds,a=new Float32Array(18*(n[0].length+n[1].length)),o=(this.plot.zeroLineEnable,0),s=[[],[]],l=0;l<2;++l)for(var u=s[l],c=n[l],h=i[l],f=i[l+2],d=0;d<c.length;++d){var p=(c[d].x-h)/(f-h);u.push(p);for(var g=0;g<6;++g)a[o++]=p,a[o++]=t[g],a[o++]=e[g]}this.ticks=s,this.vbo.update(a)}}(),c.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":177,\"binary-search-bounds\":179,\"gl-buffer\":128,\"gl-shader\":180}],176:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[-1,-1,-1,1,1,-1,1,1]),i=o(e,s.lineVert,s.lineFrag),l=new n(t,r,i);return l}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawLine=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o,s){var l=this.plot,u=this.shader,c=l.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,u.uniforms.start=t,u.uniforms.end=e,u.uniforms.width=o*l.pixelRatio,u.uniforms.color=s,c.drawArrays(c.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"gl-buffer\":128,\"gl-shader\":180}],177:[function(t,e,r){\"use strict\";var n=\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\";e.exports={lineVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\",lineFrag:n,textVert:\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\",textFrag:n,gridVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\",gridFrag:n,boxVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\",tickVert:\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"}},{}],178:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}function i(t){var e=t.gl,r=a(e),i=o(e,u.textVert,u.textFrag),s=new n(t,r,i);return s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,h=i.dataBox,f=i.screenBox,d=i.pixelRatio,p=i.tickEnable,g=i.tickPad,m=i.tickColor,v=i.tickAngle,y=i.labelEnable,x=i.labelPad,b=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],M=this.labelCount[n],A=l.lt(o,h[n]),k=l.le(o,h[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(f[2+n]-f[n])-1;var T=2/f[2+(1^n)]-f[1^n];e[1^n]=T*c[1^n]-1,p[n]&&(e[1^n]-=T*d*g[n],A<k&&s[k]>s[A]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=m[n],a.uniforms.angle=v[n],u.drawArrays(u.TRIANGLES,s[A],s[k]-s[A]))),y[n]&&M&&(e[1^n]-=T*d*x[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=b[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,M)),e[1^n]=T*c[2+(1^n)]-1,p[n+2]&&(e[1^n]+=T*d*g[n+2],A<k&&s[k]>s[A]&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=m[n+2],a.uniforms.angle=v[n+2],u.drawArrays(u.TRIANGLES,s[A],s[k]-s[A]))),y[n+2]&&M&&(e[1^n]+=T*d*x[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=b[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,M))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;u<2;++u){var c=a[u],h=a[u+2],f=h-c,d=.5*(o[u+2]+o[u]),p=o[u+2]-o[u],g=l[u],m=l[u+2],v=m-g,y=s[u],x=s[u+2],b=x-y;e[u]=2*f/p*v/b,t[u]=2*(c-d)/p*v/b}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){var e,r,n,i,a,o=[],l=t.ticks,u=t.bounds;for(a=0;a<2;++a){var c=[Math.floor(o.length/3)],h=[-(1/0)],f=l[a];for(e=0;e<f.length;++e){var d=f[e],p=d.x,g=d.text,m=d.font||\"sans-serif\";i=d.fontSize||12;for(var v=1/(u[a+2]-u[a]),y=u[a],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=s(m,x[b]).data,r=0;r<n.length;r+=2)o.push(n[r]*i,-n[r+1]*i-b*i*1.2,(p-y)*v);c.push(Math.floor(o.length/3)),h.push(p)}this.tickOffset[a]=c,this.tickX[a]=h}for(a=0;a<2;++a){for(this.labelOffset[a]=Math.floor(o.length/3),n=s(t.labelFont[a],t.labels[a],{textAlign:\"center\"}).data,i=t.labelSize[a],e=0;e<n.length;e+=2)o.push(n[e]*i,-n[e+1]*i,0);this.labelCount[a]=Math.floor(o.length/3)-this.labelOffset[a]}for(this.titleOffset=Math.floor(o.length/3),n=s(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)o.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(o.length/3)-this.titleOffset,this.vbo.update(o)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":177,\"binary-search-bounds\":179,\"gl-buffer\":128,\"gl-shader\":180,\"text-cache\":488}],179:[function(t,e,r){arguments[4][72][0].apply(r,arguments)},{dup:72}],180:[function(t,e,r){\"use strict\";function n(t){this.gl=t,this.gl.lastAttribCount=0,this._vref=this._fref=this._relink=this.vertShader=this.fragShader=this.program=this.attributes=this.uniforms=this.types=null}function i(t,e){return t.name<e.name?-1:1}function a(t,e,r,i,a){var o=new n(t);return o.update(e,r,i,a),o}var o=t(\"./lib/create-uniforms\"),s=t(\"./lib/create-attributes\"),l=t(\"./lib/reflect\"),u=t(\"./lib/shader-cache\"),c=t(\"./lib/runtime-reflect\"),h=t(\"./lib/GLError\"),f=n.prototype;f.bind=function(){this.program||this._relink();var t,e=this.gl.getProgramParameter(this.program,this.gl.ACTIVE_ATTRIBUTES),r=this.gl.lastAttribCount;if(e>r)for(t=r;t<e;t++)this.gl.enableVertexAttribArray(t);else if(r>e)for(t=e;t<r;t++)this.gl.disableVertexAttribArray(t);this.gl.lastAttribCount=e,this.gl.useProgram(this.program)},f.dispose=function(){for(var t=this.gl.lastAttribCount,e=0;e<t;e++)this.gl.disableVertexAttribArray(e);this.gl.lastAttribCount=0,this._fref&&this._fref.dispose(),this._vref&&this._vref.dispose(),this.attributes=this.types=this.vertShader=this.fragShader=this.program=this._relink=this._fref=this._vref=null},f.update=function(t,e,r,n){function a(){d.program=u.program(p,d._vref,d._fref,_,w);for(var t=0;t<r.length;++t)S[t]=p.getUniformLocation(d.program,r[t].name)}if(!e||1===arguments.length){var f=t;t=f.vertex,e=f.fragment,r=f.uniforms,n=f.attributes}var d=this,p=d.gl,g=d._vref;d._vref=u.shader(p,p.VERTEX_SHADER,t),g&&g.dispose(),d.vertShader=d._vref.shader;var m=this._fref;if(d._fref=u.shader(p,p.FRAGMENT_SHADER,e),m&&m.dispose(),d.fragShader=d._fref.shader,!r||!n){var v=p.createProgram();if(p.attachShader(v,d.fragShader),p.attachShader(v,d.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var y=p.getProgramInfoLog(v);throw new h(y,\"Error linking 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p=0;p<2;++p)if(h[p]&&n[p]<=0&&n[p+2]>=0){\n",
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e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}}(),f.pick=function(){return function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){var h=u[c].pick(a,o,l);if(h)return h}return null}}}(),f.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},f.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},f.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},f.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;u<2;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},f.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},f.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},f.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},f.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},f.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":174,\"./lib/grid\":175,\"./lib/line\":176,\"./lib/text\":178,\"gl-select-static\":219}],188:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":220}],189:[function(t,e,r){\"use strict\";function n(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function i(t,e){var r=null;try{r=t.getContext(\"webgl\",e),r||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}function a(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){var r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function o(t){return\"boolean\"!=typeof t||t}function s(t){function e(){if(!_&&H.autoResize){var t=w.parentNode,e=1,r=1;t&&t!==document.body?(e=t.clientWidth,r=t.clientHeight):(e=window.innerWidth,r=window.innerHeight);var n=0|Math.ceil(e*H.pixelRatio),i=0|Math.ceil(r*H.pixelRatio);if(n!==w.width||i!==w.height){w.width=n,w.height=i;var a=w.style;a.position=a.position||\"absolute\",a.left=\"0px\",a.top=\"0px\",a.width=e+\"px\",a.height=r+\"px\",j=!0}}}function r(){for(var t=D.length,e=F.length,r=0;r<e;++r)O[r]=0;t:for(var r=0;r<t;++r){var n=D[r],i=n.pickSlots;if(i){for(var a=0;a<e;++a)if(O[a]+i<255){R[r]=a,n.setPickBase(O[a]+1),O[a]+=i;continue t}var o=f(A,q);R[r]=e,F.push(o),O.push(i),n.setPickBase(1),e+=1}else R[r]=-1}for(;e>0&&0===O[e-1];)O.pop(),F.pop().dispose()}function s(){return!!H.contextLost||void(A.isContextLost()&&(H.contextLost=!0,H.mouseListener.enabled=!1,H.selection.object=null,H.oncontextloss&&H.oncontextloss()))}function y(){if(!s()){A.colorMask(!0,!0,!0,!0),A.depthMask(!0),A.disable(A.BLEND),A.enable(A.DEPTH_TEST);for(var t=D.length,e=F.length,r=0;r<e;++r){var n=F[r];n.shape=G,n.begin();for(var i=0;i<t;++i)if(R[i]===r){var a=D[i];a.drawPick&&(a.pixelRatio=1,a.drawPick(V))}n.end()}}}function x(){if(!s()){e();var t=H.camera.tick();V.view=H.camera.matrix,j=j||t,N=N||t,C.pixelRatio=H.pixelRatio,P.pixelRatio=H.pixelRatio;var r=D.length,n=W[0],i=W[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-(1/0);for(var o=0;o<r;++o){var l=D[o];l.pixelRatio=H.pixelRatio,l.axes=H.axes,j=j||!!l.dirty,N=N||!!l.dirty;var u=l.bounds;if(u)for(var h=u[0],f=u[1],d=0;d<3;++d)n[d]=Math.min(n[d],h[d]),i[d]=Math.max(i[d],f[d])}var g=H.bounds;if(H.autoBounds)for(var d=0;d<3;++d){if(i[d]<n[d])n[d]=-1,i[d]=1;else{n[d]===i[d]&&(n[d]-=1,i[d]+=1);var v=.05*(i[d]-n[d]);n[d]=n[d]-v,i[d]=i[d]+v}g[0][d]=n[d],g[1][d]=i[d]}for(var x=!1,d=0;d<3;++d)x=x||Z[0][d]!==g[0][d]||Z[1][d]!==g[1][d],Z[0][d]=g[0][d],Z[1][d]=g[1][d];if(x){for(var b=[0,0,0],o=0;o<3;++o)b[o]=a((g[1][o]-g[0][o])/10);C.autoTicks?C.update({bounds:g,tickSpacing:b}):C.update({bounds:g})}N=N||x,j=j||x;var _=A.drawingBufferWidth,w=A.drawingBufferHeight;q[0]=_,q[1]=w,G[0]=0|Math.max(_/H.pixelRatio,1),G[1]=0|Math.max(w/H.pixelRatio,1),m(B,H.fovy,_/w,H.zNear,H.zFar);for(var o=0;o<16;++o)U[o]=0;U[15]=1;for(var M=0,o=0;o<3;++o)M=Math.max(M,g[1][o]-g[0][o]);for(var o=0;o<3;++o)H.autoScale?U[5*o]=H.aspect[o]/(g[1][o]-g[0][o]):U[5*o]=1/M,H.autoCenter&&(U[12+o]=.5*-U[5*o]*(g[0][o]+g[1][o]));for(var o=0;o<r;++o){var l=D[o];l.axesBounds=g,H.clipToBounds&&(l.clipBounds=g)}if(T.object&&(H.snapToData?P.position=T.dataCoordinate:P.position=T.dataPosition,P.bounds=g),N&&(N=!1,y()),j){H.axesPixels=c(H.axes,V,_,w),H.onrender&&H.onrender(),A.bindFramebuffer(A.FRAMEBUFFER,null),A.viewport(0,0,_,w);var k=H.clearColor;A.clearColor(k[0],k[1],k[2],k[3]),A.clear(A.COLOR_BUFFER_BIT|A.DEPTH_BUFFER_BIT),A.depthMask(!0),A.colorMask(!0,!0,!0,!0),A.enable(A.DEPTH_TEST),A.depthFunc(A.LEQUAL),A.disable(A.BLEND),A.disable(A.CULL_FACE);var L=!1;C.enable&&(L=L||C.isTransparent(),C.draw(V)),P.axes=C,T.object&&P.draw(V),A.disable(A.CULL_FACE);for(var o=0;o<r;++o){var l=D[o];l.axes=C,l.pixelRatio=H.pixelRatio,l.isOpaque&&l.isOpaque()&&l.draw(V),l.isTransparent&&l.isTransparent()&&(L=!0)}if(L){E.shape=q,E.bind(),A.clear(A.DEPTH_BUFFER_BIT),A.colorMask(!1,!1,!1,!1),A.depthMask(!0),A.depthFunc(A.LESS),C.enable&&C.isTransparent()&&C.drawTransparent(V);for(var o=0;o<r;++o){var l=D[o];l.isOpaque&&l.isOpaque()&&l.draw(V)}A.enable(A.BLEND),A.blendEquation(A.FUNC_ADD),A.blendFunc(A.ONE,A.ONE_MINUS_SRC_ALPHA),A.colorMask(!0,!0,!0,!0),A.depthMask(!1),A.clearColor(0,0,0,0),A.clear(A.COLOR_BUFFER_BIT),C.isTransparent()&&C.drawTransparent(V);for(var o=0;o<r;++o){var l=D[o];l.isTransparent&&l.isTransparent()&&l.drawTransparent(V)}A.bindFramebuffer(A.FRAMEBUFFER,null),A.blendFunc(A.ONE,A.ONE_MINUS_SRC_ALPHA),A.disable(A.DEPTH_TEST),S.bind(),E.color[0].bind(0),S.uniforms.accumBuffer=0,p(A),A.disable(A.BLEND)}j=!1;for(var o=0;o<r;++o)D[o].dirty=!1}}}function b(){_||H.contextLost||(requestAnimationFrame(b),x())}t=t||{};var _=!1,w=(t.pixelRatio||parseFloat(window.devicePixelRatio),t.canvas);if(!w)if(w=document.createElement(\"canvas\"),t.container){var M=t.container;M.appendChild(w)}else document.body.appendChild(w);var A=t.gl;if(A||(A=i(w,t.glOptions||{premultipliedAlpha:!0,antialias:!0})),!A)throw new Error(\"webgl not supported\");var k=t.bounds||[[-10,-10,-10],[10,10,10]],T=new n,E=d(A,[A.drawingBufferWidth,A.drawingBufferHeight],{preferFloat:!0}),S=v(A),L=t.camera||{eye:[2,0,0],center:[0,0,0],up:[0,1,0],zoomMin:.1,zoomMax:100,mode:\"turntable\"},z=t.axes||{},C=u(A,z);C.enable=!z.disable;var I=t.spikes||{},P=h(A,I),D=[],R=[],O=[],F=[],j=!0,N=!0,B=new Array(16),U=new Array(16),V={view:null,projection:B,model:U},N=!0,q=[A.drawingBufferWidth,A.drawingBufferHeight],H={gl:A,contextLost:!1,pixelRatio:t.pixelRatio||parseFloat(window.devicePixelRatio),canvas:w,selection:T,camera:l(w,L),axes:C,axesPixels:null,spikes:P,bounds:k,objects:D,shape:q,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:o(t.autoResize),autoBounds:o(t.autoBounds),autoScale:!!t.autoScale,autoCenter:o(t.autoCenter),clipToBounds:o(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:V,oncontextloss:null,mouseListener:null},G=[A.drawingBufferWidth/H.pixelRatio|0,A.drawingBufferHeight/H.pixelRatio|0];H.autoResize&&e(),window.addEventListener(\"resize\",e),H.update=function(t){_||(t=t||{},j=!0,N=!0)},H.add=function(t){_||(t.axes=C,D.push(t),R.push(-1),j=!0,N=!0,r())},H.remove=function(t){if(!_){var e=D.indexOf(t);e<0||(D.splice(e,1),R.pop(),j=!0,N=!0,r())}},H.dispose=function(){if(!_&&(_=!0,window.removeEventListener(\"resize\",e),w.removeEventListener(\"webglcontextlost\",s),H.mouseListener.enabled=!1,!H.contextLost)){C.dispose(),P.dispose();for(var t=0;t<D.length;++t)D[t].dispose();E.dispose();for(var t=0;t<F.length;++t)F[t].dispose();S.dispose(),A=null,C=null,P=null,D=[]}};var X=!1,Y=0;H.mouseListener=g(w,function(t,e,r){if(!_){var n=F.length,i=D.length,a=T.object;T.distance=1/0,T.mouse[0]=e,T.mouse[1]=r,T.object=null,T.screen=null,T.dataCoordinate=T.dataPosition=null;var o=!1;if(t&&Y)X=!0;else{X&&(N=!0),X=!1;for(var s=0;s<n;++s){var l=F[s].query(e,G[1]-r-1,H.pickRadius);if(l){if(l.distance>T.distance)continue;for(var u=0;u<i;++u){var c=D[u];if(R[u]===s){var h=c.pick(l);h&&(T.buttons=t,T.screen=l.coord,T.distance=l.distance,T.object=c,T.index=h.distance,T.dataPosition=h.position,T.dataCoordinate=h.dataCoordinate,T.data=h,o=!0)}}}}}a&&a!==T.object&&(a.highlight&&a.highlight(null),j=!0),T.object&&(T.object.highlight&&T.object.highlight(T.data),j=!0),o=o||T.object!==a,o&&H.onselect&&H.onselect(T),1&t&&!(1&Y)&&H.onclick&&H.onclick(T),Y=t}}),w.addEventListener(\"webglcontextlost\",s);var W=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],Z=[W[0].slice(),W[1].slice()];return b(),H.redraw=function(){_||(j=!0,x())},H}e.exports=s;var l=t(\"3d-view-controls\"),u=t(\"gl-axes3d\"),c=t(\"gl-axes3d/properties\"),h=t(\"gl-spikes3d\"),f=t(\"gl-select-static\"),d=t(\"gl-fbo\"),p=t(\"a-big-triangle\"),g=t(\"mouse-change\"),m=t(\"gl-mat4/perspective\"),v=t(\"./lib/shader\")},{\"./lib/shader\":188,\"3d-view-controls\":26,\"a-big-triangle\":28,\"gl-axes3d\":120,\"gl-axes3d/properties\":127,\"gl-fbo\":135,\"gl-mat4/perspective\":152,\"gl-select-static\":219,\"gl-spikes3d\":229,\"mouse-change\":413}],190:[function(t,e,r){r.pointVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\",r.pointFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\",r.pickVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],191:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{\"./lib/GLError\":192,\"./lib/create-attributes\":193,\"./lib/create-uniforms\":194,\"./lib/reflect\":195,\"./lib/runtime-reflect\":196,\"./lib/shader-cache\":197,dup:180}],192:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],193:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":192,dup:182}],194:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":192,\"./reflect\":195,dup:183}],195:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],196:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],197:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":192,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],198:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}function i(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}function a(t,e){var r=t.gl,i=s(r),a=s(r),l=o(r,u.pointVertex,u.pointFragment),c=o(r,u.pickVertex,u.pickFragment),h=new n(t,i,a,l,c);return h.update(e),t.addObject(h),h}var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"typedarray-pool\"),u=t(\"./lib/shader\");e.exports=a;var c=n.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){function e(e,r){return e in t?t[e]:r}var r;t=t||{},this.sizeMin=e(\"sizeMin\",.5),this.sizeMax=e(\"sizeMax\",20),this.color=e(\"color\",[1,0,0,1]).slice(),this.areaRatio=e(\"areaRatio\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.blend=e(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,a=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,o=t.positions,s=i?o:l.mallocFloat32(o.length),u=a?t.idToIndex:l.mallocInt32(n);if(i||s.set(o),!a)for(s.set(o),r=0;r<n;r++)u[r]=r;this.points=o,this.offsetBuffer.update(s),this.pickBuffer.update(u),i||l.free(s),a||l.free(u),this.pointCount=n,this.pickOffset=0},c.unifiedDraw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=void 0!==r,a=n?this.pickShader:this.shader,o=this.plot.gl,s=this.plot.dataBox;if(0===this.pointCount)return r;var l=s[2]-s[0],u=s[3]-s[1],c=i(this.points,s),h=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(c,.33333)));t[0]=2/l,t[4]=2/u,t[6]=-2*s[0]/l-1,t[7]=-2*s[1]/u-1,this.offsetBuffer.bind(),a.bind(),a.attributes.position.pointer(),a.uniforms.matrix=t,a.uniforms.color=this.color,a.uniforms.borderColor=this.borderColor,a.uniforms.pointCloud=h<5,a.uniforms.pointSize=h,a.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),n&&(e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,this.pickBuffer.bind(),a.attributes.pickId.pointer(o.UNSIGNED_BYTE),a.uniforms.pickOffset=e,this.pickOffset=r);var f=o.getParameter(o.BLEND),d=o.getParameter(o.DITHER);return f&&!this.blend&&o.disable(o.BLEND),d&&o.disable(o.DITHER),o.drawArrays(o.POINTS,0,this.pointCount),f&&!this.blend&&o.enable(o.BLEND),d&&o.enable(o.DITHER),r+this.pointCount}}(),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":190,\"gl-buffer\":128,\"gl-shader\":191,\"typedarray-pool\":496}],199:[function(t,e,r){function n(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],h=e[2],f=e[3],d=r[0],p=r[1],g=r[2],m=r[3];return a=u*d+c*p+h*g+f*m,a<0&&(a=-a,d=-d,p=-p,g=-g,m=-m),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*d,t[1]=s*c+l*p,t[2]=s*h+l*g,t[3]=s*f+l*m,t}e.exports=n},{}],200:[function(t,e,r){\"use strict\";e.exports={vertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo, pixelScale;\\n\\nvarying vec4 fragColor;\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo, vec2 screenScale, vec2 screenOffset) {\\n  return vec4(scHi * posHi + trHi\\n            + scLo * posHi + trLo\\n            + scHi * posLo\\n            + scLo * posLo\\n            + screenScale * screenOffset, 0, 1);\\n}\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo,\\n    pixelScale, offset);\\n}\\n\",fragment:\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo, pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\n\\nvec4 computePosition_1_0(vec2 posHi, vec2 posLo, vec2 scHi, vec2 scLo, vec2 trHi, vec2 trLo, vec2 screenScale, vec2 screenOffset) {\\n  return vec4(scHi * posHi + trHi\\n            + scLo * posHi + trLo\\n            + scHi * posLo\\n            + scLo * posLo\\n            + screenScale * screenOffset, 0, 1);\\n}\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    positionHi, positionLo,\\n    scaleHi, scaleLo,\\n    translateHi, translateLo,\\n    pixelScale, offset);\\n}\\n\",pickFragment:\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],201:[function(t,e,r){arguments[4][180][0].apply(r,arguments)},{\"./lib/GLError\":202,\"./lib/create-attributes\":203,\"./lib/create-uniforms\":204,\"./lib/reflect\":205,\"./lib/runtime-reflect\":206,\"./lib/shader-cache\":207,dup:180}],202:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],203:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":202,dup:182}],204:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":202,\"./reflect\":205,dup:183}],205:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],206:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],207:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":202,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],208:[function(t,e,r){\"use strict\";function n(t){if(t in f)return f[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var h=s[0]-o[0],f=s[1]-o[1],d=Math.sqrt(h*h+f*f);h/=d,f/=d,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-f,h),r.push(o[0],o[1]+1.4),n.push(-f,h),r.push(a[0],a[1]+1.4),n.push(f,-h),r.push(o[0],o[1]+1.4),n.push(f,-h)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;o<2;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return f[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o,s){this.plot=t,this.shader=e,this.pickShader=r,this.posHiBuffer=n,this.posLoBuffer=i,this.offsetBuffer=a,this.colorBuffer=o,this.idBuffer=s,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,h.vertex,h.fragment),a=o(r,h.pickVertex,h.pickFragment),l=s(r),u=s(r),c=s(r),f=s(r),d=s(r),p=new i(t,n,a,l,u,c,f,d);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),h=t(\"./lib/shaders\"),f={},d=i.prototype;!function(){function t(){var t=this.plot,o=this.bounds,s=t.viewBox,l=t.dataBox,u=t.pixelRatio,c=o[2]-o[0],h=o[3]-o[1],f=l[2]-l[0],d=l[3]-l[1],p=2*c/f,g=2*h/d,m=2*(o[0]-l[0])/f-1,v=2*(o[1]-l[1])/d-1;e[0]=p,r[0]=p-e[0],e[1]=g,r[1]=g-e[1],n[0]=m,i[0]=m-n[0],n[1]=v,i[1]=v-n[1];var y=s[2]-s[0],x=s[3]-s[1];a[0]=2*u/y,a[1]=2*u/x}var e=new Float32Array([0,0]),r=new Float32Array([0,0]),n=new Float32Array([0,0]),i=new Float32Array([0,0]),a=[0,0],o=[0,0,0,0];d.drawPick=function(s){var l=void 0!==s,u=this.plot,c=this.numVertices;if(!c)return s;t.call(this);var h=u.gl,f=l?this.pickShader:this.shader;if(f.bind(),l){this.pickOffset=s;for(var d=0;d<4;++d)o[d]=s>>8*d&255;f.uniforms.pickOffset=o,this.idBuffer.bind(),f.attributes.id.pointer(h.UNSIGNED_BYTE,!1)}else this.colorBuffer.bind(),f.attributes.color.pointer(h.UNSIGNED_BYTE,!0);return this.posHiBuffer.bind(),f.attributes.positionHi.pointer(),this.posLoBuffer.bind(),f.attributes.positionLo.pointer(),this.offsetBuffer.bind(),f.attributes.offset.pointer(),f.uniforms.pixelScale=a,f.uniforms.scaleHi=e,f.uniforms.scaleLo=r,f.uniforms.translateHi=n,f.uniforms.translateLo=i,h.drawArrays(h.TRIANGLES,0,c),l?s+this.numPoints:void 0}}(),d.draw=d.drawPick,d.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},d.update=function(t){t=t||{};var e,r,i=t.positions||[],a=t.colors||[],o=t.glyphs||[],s=t.sizes||[],c=t.borderWidths||[],h=t.borderColors||[];this.points=i;var f,d,p=this.bounds=[1/0,1/0,-(1/0),-(1/0)],g=0,m=[],v=[];for(e=0;e<o.length;++e)for(f=l(\"sans-serif\",o[e]),d=n(o[e]),m.push(f),v.push(d),g+=f.data.length+d.coords.length>>1,r=0;r<2;++r)p[r]=Math.min(p[r],i[2*e+r]),p[2+r]=Math.max(p[2+r],i[2*e+r]);p[0]===p[2]&&(p[2]+=1),p[3]===p[1]&&(p[3]+=1);var y=1/(p[2]-p[0]),x=1/(p[3]-p[1]),b=p[0],_=p[1],w=u.mallocFloat64(2*g),M=u.mallocFloat32(2*g),A=u.mallocFloat32(2*g),k=u.mallocFloat32(2*g),T=u.mallocUint8(4*g),E=u.mallocUint32(g),S=0;for(e=0;e<o.length;++e){f=m[e],d=v[e];var L=y*(i[2*e]-b),z=x*(i[2*e+1]-_),C=s[e],I=255*a[4*e],P=255*a[4*e+1],D=255*a[4*e+2],R=255*a[4*e+3],O=.5*(d.bounds[0]+d.bounds[2]),F=.5*(d.bounds[1]+d.bounds[3]);for(r=0;r<f.data.length;r+=2)w[2*S]=L,w[2*S+1]=z,k[2*S]=-C*(f.data[r]-O),k[2*S+1]=-C*(f.data[r+1]-F),T[4*S]=I,T[4*S+1]=P,T[4*S+2]=D,T[4*S+3]=R,E[S]=e,S+=1;var j=c[e];for(I=255*h[4*e],P=255*h[4*e+1],D=255*h[4*e+2],R=255*h[4*e+3],r=0;r<d.coords.length;r+=2)w[2*S]=L,w[2*S+1]=z,k[2*S]=-(C*(d.coords[r]-O)+j*d.normals[r]),k[2*S+1]=-(C*(d.coords[r+1]-F)+j*d.normals[r+1]),T[4*S]=I,T[4*S+1]=P,T[4*S+2]=D,T[4*S+3]=R,E[S]=e,S+=1}for(this.numPoints=o.length,this.numVertices=g,M.set(w),e=0;e<w.length;e++)A[e]=w[e]-M[e];this.posHiBuffer.update(M),this.posLoBuffer.update(A),this.offsetBuffer.update(k),this.colorBuffer.update(T),this.idBuffer.update(E),u.free(w),u.free(M),u.free(A),u.free(k),u.free(T),u.free(E)},d.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.posHiBuffer.dispose(),this.posLoBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":200,\"gl-buffer\":128,\"gl-shader\":201,\"text-cache\":488,\"typedarray-pool\":496,\"vectorize-text\":509}],209:[function(t,e,r){r.pointVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 positionHi, positionLo;\\nattribute float weight;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4(scaleHi * positionHi + translateHi\\n            + scaleLo * positionHi + translateLo\\n            + scaleHi * positionLo\\n            + scaleLo * positionLo, 0.0, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\",r.pointFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\",r.pickVertex=\"precision highp float;\\n#define GLSLIFY 1\\n\\nvec4 pfx_1_0(vec2 scaleHi, vec2 scaleLo, vec2 translateHi, vec2 translateLo, vec2 positionHi, vec2 positionLo) {\\n  return vec4(scaleHi * positionHi + translateHi\\n            + scaleLo * positionHi + translateLo\\n            + scaleHi * positionLo\\n            + scaleLo * positionLo, 0.0, 1.0);\\n}\\n\\nattribute vec2 positionHi, positionLo;\\nattribute vec4 pickId;\\n\\nuniform vec2 scaleHi, scaleLo, translateHi, translateLo;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_Position = pfx_1_0(scaleHi, scaleLo, translateHi, translateLo, positionHi, positionLo);\\n  gl_PointSize = pointSize;\\n  fragId = id;\\n}\",r.pickFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\"},{}],210:[function(t,e,r){arguments[4][72][0].apply(r,arguments)},{dup:72}],211:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){a<=4*f?i(0,a-1,t,e,r,n):h(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;o<=e;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],h=a[o],f=o;f>t;){var d=r[f-1],p=n[2*(f-1)];if((d-s||l-p)>=0)break;r[f]=d,n[2*f]=p,n[2*f+1]=n[2*f-1],i[f]=i[f-1],a[f]=a[f-1],f-=1}r[f]=s,n[2*f]=l,n[2*f+1]=u,i[f]=c,a[f]=h}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],h=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=h}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0;\n",
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if(!c(it,D,R,O,F,r,n,d))for(;;){if(c(E,D,R,O,F,r,n,d)){c(E,L,z,C,I,r,n,d)?(s(it,T,E,r,n,d,p),++T,--E):(a(it,E,r,n,d,p),--E);break}if(--E<it)break}l(t,T-1,L,z,C,I,P,r,n,d,p),l(e,E+1,D,R,O,F,j,r,n,d,p),T-2-t<=f?i(t,T-2,r,n,d,p):h(t,T-2,r,n,d,p),e-(E+2)<=f?i(E+2,e,r,n,d,p):h(E+2,e,r,n,d,p),E-T<=f?i(T,E,r,n,d,p):h(T,E,r,n,d,p)}e.exports=n;var f=32},{}],212:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;u<n;++u){var c=t[2*u],h=t[2*u+1],f=e[u];i<=c&&c<=o&&a<=h&&h<=s&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=h,e[l]=f,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var h=.5*o,f=s+1,d=u-s;r[_]=d,b[_++]=c;for(var p=0;p<2;++p)for(var g=0;g<2;++g){var m=i+p*h,v=a+g*h,y=n(t,e,f,u,m,v,m+h,v+h);if(y!==f){if(y-f>=Math.max(.9*d,32)){var x=u+s>>>1;l(m,v,h,f,x,c+1),f=x}l(m,v,h,f,y,c+1),f=y}}}var u=t.length>>>1;if(u<1)return[];for(var c=1/0,h=1/0,f=-(1/0),d=-(1/0),p=0;p<u;++p){var g=t[2*p],m=t[2*p+1];c=Math.min(c,g),f=Math.max(f,g),h=Math.min(h,m),d=Math.max(d,m),e[p]=p}c===f&&(f+=1+Math.abs(f)),h===d&&(d+=1+Math.abs(f));var v=1/(f-c),y=1/(d-h),x=Math.max(f-c,d-h);a=a||[0,0,0,0],a[0]=c,a[1]=h,a[2]=f,a[3]=d;var b=o.mallocInt32(u),_=0;l(c,h,x,0,u,0),s(b,t,e,r,u);for(var w=[],M=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*v,t[2*_+1]=(t[2*_+1]-h)*y;var k=b[_];k!==M&&(w.push(new i(x*Math.pow(.5,k),_+1,A-(_+1))),A=_+1,M=k)}return w.push(new i(x*Math.pow(.5,k+1),0,A)),o.free(b),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":211,\"typedarray-pool\":496}],213:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o){this.plot=t,this.positionBufferHi=e,this.positionBufferLo=r,this.pickBuffer=n,this.weightBuffer=i,this.shader=a,this.pickShader=o,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=o(r),h=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),d=new n(t,i,s,l,u,h,f);return d.update(e),t.addObject(d),d}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var h=n.prototype,f=new Float32Array(2),d=new Float32Array(2),p=new Float32Array(2),g=new 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h=0,f=0;h<r;h++,f+=2)c[f]=a[f]-s[f],c[f+1]=a[f+1]-s[f+1],o[h]=a[f];this.positionBufferHi.update(s),this.positionBufferLo.update(c),this.pickBuffer.update(n),this.weightBuffer.update(i),u.free(n),u.free(a),u.free(s),u.free(c),u.free(i),this.xCoords=o,this.pointCount=r,this.pickOffset=0},h.draw=function(t){var e=void 0!==t,r=this.plot,n=e?this.pickShader:this.shader,i=this.scales,a=this.positionBufferHi,o=this.positionBufferLo,l=this.pickBuffer,u=this.bounds,c=this.size,h=this.borderSize,v=r.gl,y=e?r.pickPixelRatio:r.pixelRatio,x=r.viewBox,b=r.dataBox;if(0===this.pointCount)return t;var _=u[2]-u[0],w=u[3]-u[1],M=b[2]-b[0],A=b[3]-b[1],k=(x[2]-x[0])*y/r.pixelRatio,T=(x[3]-x[1])*y/r.pixelRatio,E=Math.min(M/k,A/T),S=2*_/M,L=2*w/A;f[0]=S,f[1]=L,d[0]=S-f[0],d[1]=L-f[1];var z=2*(u[0]-b[0])/M-1,C=2*(u[1]-b[1])/A-1;p[0]=z,p[1]=C,g[0]=z-p[0],g[1]=C-p[1],n.bind(),n.uniforms.scaleHi=f,n.uniforms.scaleLo=d,n.uniforms.translateHi=p,n.uniforms.translateLo=g,n.uniforms.color=this.color,n.uniforms.borderColor=this.borderColor,n.uniforms.pointSize=y*(c+h),n.uniforms.centerFraction=0===this.borderSize?2:c/(c+h+1.25),a.bind(),n.attributes.positionHi.pointer(),o.bind(),n.attributes.positionLo.pointer(),e?(this.pickOffset=t,m[0]=255&t,m[1]=t>>8&255,m[2]=t>>16&255,m[3]=t>>24&255,n.uniforms.pickOffset=m,l.bind(),n.attributes.pickId.pointer(v.UNSIGNED_BYTE)):(n.uniforms.useWeight=1,this.weightBuffer.bind(),n.attributes.weight.pointer());for(var I=this.xCoords,P=(b[0]-u[0]-E*c*y)/_,D=(b[2]-u[0]+E*c*y)/_,R=!0,O=i.length-1;O>=0;O--){var F=i[O];if(!(F.pixelSize<E&&O>1)){var j=F.offset,N=F.count+j,B=s.ge(I,P,j,N-1),U=s.lt(I,D,B,N-1)+1;U>B&&v.drawArrays(v.POINTS,B,U-B),!e&&R&&(R=!1,n.uniforms.useWeight=0)}}},h.drawPick=h.draw,h.pick=function(t,e,r){var n=r-this.pickOffset;return n<0||n>=this.pointCount?null:{object:this,pointId:n,dataCoord:[this.points[2*n],this.points[2*n+1]]}}},{\"./lib/shader\":209,\"binary-search-bounds\":210,\"gl-buffer\":128,\"gl-shader\":220,\"snap-points-2d\":212,\"typedarray-pool\":496}],214:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;c<2;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":509}],215:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],h={vertex:a,fragment:l,attributes:c},f={vertex:o,fragment:l,attributes:c},d={vertex:s,fragment:l,attributes:c},p={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},m={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,h)},r.createOrtho=function(t){return n(t,f)},r.createProject=function(t){return n(t,d)},r.createPickPerspective=function(t){return n(t,p)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,m)}},{\"gl-shader\":220}],216:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,h,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=h,this.pickProjectShader=f,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=L,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function h(t,e,r,n,a){var o,h=e.axesProject,f=e.gl,d=t.uniforms,p=r.model||b,g=r.view||b,m=r.projection||b,y=e.axesBounds,x=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/f.drawingBufferWidth,w[1]=2/f.drawingBufferHeight,t.bind(),d.view=g,d.projection=m,d.screenSize=w,d.highlightId=e.highlightId,d.highlightScale=e.highlightScale,d.clipBounds=x,d.pickGroup=e.pickId/255,d.pixelRatio=e.pixelRatio;for(var _=0;_<3;++_)if(h[_]&&e.projectOpacity[_]<1===n){d.scale=e.projectScale[_],d.opacity=e.projectOpacity[_];for(var L=E,z=0;z<16;++z)L[z]=0;for(var z=0;z<4;++z)L[5*z]=1;L[5*_]=0,o[_]<0?L[12+_]=y[0][_]:L[12+_]=y[1][_],v(L,p,L),d.model=L;var C=(_+1)%3,I=(_+2)%3,P=s(M),D=s(A);P[C]=1,D[I]=1;var R=i(m,g,p,l(k,P)),O=i(m,g,p,l(T,D));if(Math.abs(R[1])>Math.abs(O[1])){var F=R;R=O,O=F,F=P,P=D,D=F;var j=C;C=I,I=j}R[0]<0&&(P[C]=-1),O[1]>0&&(D[I]=-1);for(var N=0,B=0,z=0;z<4;++z)N+=Math.pow(p[4*C+z],2),B+=Math.pow(p[4*I+z],2);P[C]/=Math.sqrt(N),D[I]/=Math.sqrt(B),d.axes[0]=P,d.axes[1]=D,d.fragClipBounds[0]=u(S,x[0],_,-1e8),d.fragClipBounds[1]=u(S,x[1],_,1e8),e.vao.draw(f.TRIANGLES,e.vertexCount),e.lineWidth>0&&(f.lineWidth(e.lineWidth),e.vao.draw(f.LINES,e.lineVertexCount,e.vertexCount))}}function f(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||b,s.view=n.view||b,s.projection=n.projection||b,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=I,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}h(e,r,n,i,a),r.vao.unbind()}function d(t){var 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w=[0,0],M=[0,0,0],A=[0,0,0],k=[0,0,0,1],T=[0,0,0,1],E=b.slice(),S=[0,0,0],L=[[0,0,0],[0,0,0]],z=[-1e8,-1e8,-1e8],C=[1e8,1e8,1e8],I=[z,C];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;f(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;f(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;f(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in 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U=Math.cos(B),V=Math.sin(B),b=n[y],_=0;_<3;++_)s[_]=Math.max(s[_],b[_]),o[_]=Math.min(o[_],b[_]);a[0]<0?C[0]=a[0]*(1+k[1][0]):a[0]>0&&(C[0]=-a[0]*(1+k[0][0]));for(var q=M.cells,H=M.positions,_=0;_<q.length;++_)for(var G=q[_],X=0;X<3;++X){for(var Y=0;Y<3;++Y)E[3*I+Y]=b[Y];for(var Y=0;Y<4;++Y)S[4*I+Y]=D[Y];z[I]=d;var W=H[G[X]];L[2*I]=N*(U*W[0]-V*W[1]+C[0]),L[2*I+1]=N*(V*W[0]+U*W[1]+C[1]),I+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],X=0;X<2;++X){for(var Y=0;Y<3;++Y)E[3*P+Y]=b[Y];for(var Y=0;Y<4;++Y)S[4*P+Y]=R[Y];z[P]=d;var W=H[G[X]];L[2*P]=N*(U*W[0]-V*W[1]+C[0]),L[2*P+1]=N*(V*W[0]+U*W[1]+C[1]),P+=1}d+=1}this.vertexCount=p,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(S),this.glyphBuffer.update(L),this.idBuffer.update(new Uint32Array(z)),m.free(E),m.free(S),m.free(L),m.free(z),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":214,\"./lib/shaders\":215,\"gl-buffer\":128,\"gl-mat4/multiply\":151,\"gl-vao\":236,\"typedarray-pool\":496}],217:[function(t,e,r){\"use strict\";r.boxVertex=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],218:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,h=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],f=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],d=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],p=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(h=Math.max(h,u[0]),f=Math.max(f,u[1]),d=Math.min(d,u[2]),p=Math.min(p,u[3]),!(d<h||p<f)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,f,i),o.drawBox(0,f,h,p,i),o.drawBox(0,p,g,m,i),o.drawBox(d,f,g,p,i)),this.innerFill&&o.drawBox(h,f,d,p,n),r>0){var v=r*c;o.drawBox(h-v,f-v,d+v,f+v,a),o.drawBox(h-v,p-v,d+v,p+v,a),o.drawBox(h-v,f-v,h+v,p+v,a),o.drawBox(d-v,f-v,d+v,p+v,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":217,\"gl-buffer\":128,\"gl-shader\":220}],219:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(_inline_46_arg0_<255||_inline_46_arg1_<255||_inline_46_arg2_<255||_inline_46_arg3_<255){var 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this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){s.free(this.buffer);for(var n=this.buffer=s.mallocUint8(u(r*e*4)),i=0;i<r*e*4;++i)n[i]=255}return t}}}),h.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},h.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},h.query=function(t,e,r){if(!this.gl)return null;var i=this.fbo.shape.slice();t=0|t,e=0|e,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),i[0]),o=0|Math.min(Math.max(t+r,0),i[0]),s=0|Math.min(Math.max(e-r,0),i[1]),u=0|Math.min(Math.max(e+r,0),i[1]);if(o<=a||u<=s)return null;var 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v=p.createProgram();if(p.attachShader(v,d.fragShader),p.attachShader(v,d.vertShader),p.linkProgram(v),!p.getProgramParameter(v,p.LINK_STATUS)){var y=p.getProgramInfoLog(v);throw new h(y,\"Error linking program:\"+y)}r=r||c.uniforms(p,v),n=n||c.attributes(p,v),p.deleteProgram(v)}n=n.slice(),n.sort(i);for(var x=[],b=[],_=[],w=0;w<n.length;++w){var M=n[w];if(M.type.indexOf(\"mat\")>=0){for(var A=0|M.type.charAt(M.type.length-1),k=new Array(A),T=0;T<A;++T)k[T]=_.length,b.push(M.name+\"[\"+T+\"]\"),\"number\"==typeof M.location?_.push(M.location+T):Array.isArray(M.location)&&M.location.length===A&&\"number\"==typeof M.location[T]?_.push(0|M.location[T]):_.push(-1);x.push({name:M.name,type:M.type,locations:k})}else x.push({name:M.name,type:M.type,locations:[_.length]}),b.push(M.name),\"number\"==typeof M.location?_.push(0|M.location):_.push(-1)}for(var E=0,w=0;w<_.length;++w)if(_[w]<0){for(;_.indexOf(E)>=0;)E+=1;_[w]=E}var S=new Array(r.length);a(),d._relink=a,d.types={uniforms:l(r),attributes:l(n)},d.attributes=s(p,d,x,_),Object.defineProperty(d,\"uniforms\",o(p,d,r,S))},e.exports=a},{\"./lib/GLError\":221,\"./lib/create-attributes\":222,\"./lib/create-uniforms\":223,\"./lib/reflect\":224,\"./lib/runtime-reflect\":225,\"./lib/shader-cache\":226}],221:[function(t,e,r){arguments[4][181][0].apply(r,arguments)},{dup:181}],222:[function(t,e,r){arguments[4][182][0].apply(r,arguments)},{\"./GLError\":221,dup:182}],223:[function(t,e,r){arguments[4][183][0].apply(r,arguments)},{\"./GLError\":221,\"./reflect\":224,dup:183}],224:[function(t,e,r){arguments[4][184][0].apply(r,arguments)},{dup:184}],225:[function(t,e,r){arguments[4][185][0].apply(r,arguments)},{dup:185}],226:[function(t,e,r){arguments[4][186][0].apply(r,arguments)},{\"./GLError\":221,dup:186,\"gl-format-compiler-error\":136,\"weakmap-shim\":517}],227:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}function i(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r}e.exports=i;var a=n.prototype;a.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map(function(t){return t.slice()}),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},a.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],228:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":220}],229:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}function i(t,e){function r(t,e,r,n,a,o){var s=[t,e,r,0,0,0,1];s[n+3]=1,s[n]=a,i.push.apply(i,s),s[6]=-1,i.push.apply(i,s),s[n]=o,i.push.apply(i,s),i.push.apply(i,s),s[6]=1,i.push.apply(i,s),s[n]=a,i.push.apply(i,s)}var i=[];r(0,0,0,0,0,1),r(0,0,0,1,0,1),r(0,0,0,2,0,1),r(1,0,0,1,-1,1),r(1,0,0,2,-1,1),r(0,1,0,0,-1,1),r(0,1,0,2,-1,1),r(0,0,1,0,-1,1),r(0,0,1,1,-1,1);var l=a(t,i),u=o(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),c=s(t);c.attributes.position.location=0,c.attributes.color.location=1,c.attributes.weight.location=2;var h=new n(t,l,u,c);return h.update(e),h}var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders/index\");e.exports=i;var l=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],u=n.prototype,c=[0,0,0],h=[0,0,0],f=[0,0];u.isTransparent=function(){return!1},u.drawTransparent=function(t){},u.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||l,o=t.view||l,s=t.projection||l;this.axes&&(i=this.axes.lastCubeProps.axis);for(var u=c,d=h,p=0;p<3;++p)i&&i[p]<0?(u[p]=this.bounds[0][p],d[p]=this.bounds[1][p]):(u[p]=this.bounds[1][p],d[p]=this.bounds[0][p]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=o,\n",
+       "n.uniforms.projection=s,n.uniforms.coordinates=[this.position,u,d],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(var p=0;p<3;++p)n.uniforms.lineWidth=this.lineWidth[p]*this.pixelRatio,this.enabled[p]&&(r.draw(e.TRIANGLES,6,6*p),this.drawSides[p]&&r.draw(e.TRIANGLES,12,18+12*p));r.unbind()},u.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},u.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":228,\"gl-buffer\":128,\"gl-vao\":236}],230:[function(t,e,r){var n=t(\"gl-shader\"),i=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\",a=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor = step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) + step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\",o=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  vec4 worldPosition = model * vec4(dataCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z = clipPosition.z + zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f;\\n  kill = -1.0;\\n  worldCoordinate = dataCoordinate;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":220}],231:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=b([y({colormap:t,nshades:O,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return x.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,h,f,d,p){this.gl=t,this.shape=e,this.bounds=r,this.intensityBounds=[],this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=f,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=p,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(v.mallocFloat(1024),[0,0]),_(v.mallocFloat(1024),[0,0]),_(v.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}function o(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||j,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=N.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],M(l,t.model,l);var u=N.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return N.showSurface=o,N.showContour=s,N}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||P,n.view=t.view||P,n.projection=t.projection||P,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],s=0;s<3;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V,n.vertexColor=this.vertexColor;var l=U;for(M(l,n.view,n.model),M(l,n.projection,l),A(l,l),i=0;i<3;++i)n.eyePosition[i]=l[12+i]/l[15];var u=l[15];for(i=0;i<3;++i)u+=this.lightPosition[i]*l[4*i+3];for(i=0;i<3;++i){var c=l[12+i];for(s=0;s<3;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var h=o(n,this);if(h.showSurface&&e===this.opacity<1){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=h.projections[i],this._shader.uniforms.clipBounds=h.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(h.showContour&&!e){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var d=this._contourVAO;for(d.bind(),i=0;i<3;++i)for(f.uniforms.permutation=R[i],r.lineWidth(this.contourWidth[i]),s=0;s<this.contourLevels[i].length;++s)this._contourCounts[i][s]&&(s===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==s&&s-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),f.uniforms.height=this.contourLevels[i][s],d.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s]));for(i=0;i<3;++i)for(f.uniforms.model=h.projections[i],f.uniforms.clipBounds=h.clipBounds[i],s=0;s<3;++s)if(this.contourProject[i][s]){f.uniforms.permutation=R[s],r.lineWidth(this.contourWidth[s]);for(var p=0;p<this.contourLevels[s].length;++p)p===this.highlightLevel[s]?(f.uniforms.contourColor=this.highlightColor[s],f.uniforms.contourTint=this.highlightTint[s]):0!==p&&p-1!==this.highlightLevel[s]||(f.uniforms.contourColor=this.contourColor[s],f.uniforms.contourTint=this.contourTint[s]),f.uniforms.height=this.contourLevels[s][p],d.draw(r.LINES,this._contourCounts[s][p],this._contourOffsets[s][p])}for(d=this._dynamicVAO,d.bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=R[i],r.lineWidth(this.dynamicWidth[i]),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),s=0;s<3;++s)this.contourProject[s][i]&&(f.uniforms.model=h.projections[s],f.uniforms.clipBounds=h.clipBounds[s],d.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));d.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();x.assign(t.lo(1,1).hi(r[0],r[1]),e),x.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),x.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),x.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),x.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function h(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function f(t){var e=t.gl,r=S(e),n=z(e),i=L(e),o=C(e),s=p(e),l=g(e,[{buffer:s,size:4,stride:I,offset:0},{buffer:s,size:3,stride:I,offset:16},{buffer:s,size:3,stride:I,offset:28}]),u=p(e),c=g(e,[{buffer:u,size:4,stride:20,offset:0},{buffer:u,size:1,stride:20,offset:16}]),h=p(e),f=g(e,[{buffer:h,size:2,type:e.FLOAT}]),d=m(e,1,O,e.RGBA,e.UNSIGNED_BYTE);d.minFilter=e.LINEAR,d.magFilter=e.LINEAR;var v=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,d,i,o,u,c,h,f),y={levels:[[],[],[]]};for(var x in t)y[x]=t[x];return y.colormap=y.colormap||\"jet\",v.update(y),v}e.exports=f;var d=t(\"bit-twiddle\"),p=t(\"gl-buffer\"),g=t(\"gl-vao\"),m=t(\"gl-texture2d\"),v=t(\"typedarray-pool\"),y=t(\"colormap\"),x=t(\"ndarray-ops\"),b=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),M=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),k=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),E=t(\"./lib/shaders\"),S=E.createShader,L=E.createContourShader,z=E.createPickShader,C=E.createPickContourShader,I=40,P=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],D=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],R=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;t<3;++t){var e=R[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var O=256,F=a.prototype;F.isTransparent=function(){return this.opacity<1},F.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},F.pickSlots=1,F.setPickBase=function(t){this.pickId=t};var j=[0,0,0],N={showSurface:!1,showContour:!1,projections:[P.slice(),P.slice(),P.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:P,view:P,projection:P,inverseModel:P.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},U=P.slice(),V=[1,0,0,0,1,0,0,0,1];F.draw=function(t){return s.call(this,t,!1)},F.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:P,view:P,projection:P,inverseModel:P,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};F.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||P,r.view=t.view||P,r.projection=t.projection||P,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;for(u.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=R[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){l.uniforms.permutation=R[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}u.unbind()}},F.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var h=c?a:1-a,f=0;f<2;++f)for(var d=f?l:1-l,p=i+c,g=s+f,m=h*d,v=0;v<3;++v)u[v]+=this._field[v].get(p,g)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=k.le(this.contourLevels[x],u[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-u[x])>Math.abs(_-u[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},F.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=h(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=h(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0);var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var n=(e.shape[0]+2)*(e.shape[1]+2);n>this._field[2].data.length&&(v.freeFloat(this._field[2].data),this._field[2].data=v.mallocFloat(d.nextPow2(n))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(v.freeFloat(this._field[o].data),this._field[o].data=v.mallocFloat(this._field[2].size)),this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var s=t.coords;if(!Array.isArray(s)||3!==s.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=s[o];for(y=0;y<2;++y)if(c.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[o],c)}}else if(t.ticks){var f=t.ticks;if(!Array.isArray(f)||2!==f.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=f[o];if((Array.isArray(p)||p.length)&&(p=_(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var g=_(p.data,a);g.stride[o]=p.stride[0],g.stride[1^o]=0,l(this._field[o],g)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=_(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var y=0;y<a[0];++y)this._field[0].set(y+1,0,y);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),y=0;y<a[1];++y)this._field[1].set(0,y+1,y);this._field[1].set(0,a[1]+1,a[1]-1)}var x=this._field,b=_(v.mallocFloat(3*x[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)T(b.pick(o),x[o],\"mirror\");var M=_(v.mallocFloat(3*x[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(y=0;y<a[1]+2;++y){var A=b.get(0,o,y,0),k=b.get(0,o,y,1),E=b.get(1,o,y,0),S=b.get(1,o,y,1),L=b.get(2,o,y,0),z=b.get(2,o,y,1),C=E*z-S*L,I=L*k-z*A,P=A*S-k*E,R=Math.sqrt(C*C+I*I+P*P);R<1e-8?(R=Math.max(Math.abs(C),Math.abs(I),Math.abs(P)),R<1e-8?(P=1,I=C=0,R=1):R=1/R):R=1/Math.sqrt(R),M.set(o,y,0,C*R),M.set(o,y,1,I*R),M.set(o,y,2,P*R)}v.free(b.data);var O=[1/0,1/0,1/0],F=[-(1/0),-(1/0),-(1/0)],j=1/0,N=-(1/0),B=(a[0]-1)*(a[1]-1)*6,U=v.mallocFloat(d.nextPow2(10*B)),V=0,q=0;for(o=0;o<a[0]-1;++o)t:for(y=0;y<a[1]-1;++y){for(var H=0;H<2;++H)for(var G=0;G<2;++G)for(var X=0;X<3;++X){var Y=this._field[X].get(1+o+H,1+y+G);if(isNaN(Y)||!isFinite(Y))continue t}for(X=0;X<6;++X){var W=o+D[X][0],Z=y+D[X][1],Q=this._field[0].get(W+1,Z+1),K=this._field[1].get(W+1,Z+1);Y=this._field[2].get(W+1,Z+1);var $=Y;C=M.get(W+1,Z+1,0),I=M.get(W+1,Z+1,1),P=M.get(W+1,Z+1,2),t.intensity&&($=t.intensity.get(W,Z)),U[V++]=W,U[V++]=Z,U[V++]=Q,U[V++]=K,U[V++]=Y,U[V++]=0,U[V++]=$,U[V++]=C,U[V++]=I,U[V++]=P,O[0]=Math.min(O[0],Q),O[1]=Math.min(O[1],K),O[2]=Math.min(O[2],Y),j=Math.min(j,$),F[0]=Math.max(F[0],Q),F[1]=Math.max(F[1],K),F[2]=Math.max(F[2],Y),N=Math.max(N,$),q+=1}}for(t.intensityBounds&&(j=+t.intensityBounds[0],N=+t.intensityBounds[1]),o=6;o<V;o+=10)U[o]=(U[o]-j)/(N-j);this._vertexCount=q,this._coordinateBuffer.update(U.subarray(0,V)),v.freeFloat(U),v.free(M.data),this.bounds=[O,F],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===j&&this.intensityBounds[1]===N||(r=!0),this.intensityBounds=[j,N]}if(\"levels\"in t){var J=t.levels;for(J=Array.isArray(J[0])?J.slice():[[],[],J],o=0;o<3;++o)J[o]=J[o].slice(),J.sort(function(t,e){return t-e});t:for(o=0;o<3;++o){if(J[o].length!==this.contourLevels[o].length){r=!0;break}for(y=0;y<J[o].length;++y)if(J[o][y]!==this.contourLevels[o][y]){r=!0;break t}}this.contourLevels=J}if(r){x=this._field,a=this.shape;for(var tt=[],et=0;et<3;++et){J=this.contourLevels[et];var rt=[],nt=[],it=[0,0,0];for(o=0;o<J.length;++o){var at=w(this._field[et],J[o]);rt.push(tt.length/5|0),q=0;t:for(y=0;y<at.cells.length;++y){var ot=at.cells[y];for(X=0;X<2;++X){var st=at.positions[ot[X]],lt=st[0],ut=0|Math.floor(lt),ct=lt-ut,ht=st[1],ft=0|Math.floor(ht),dt=ht-ft,pt=!1;e:for(var gt=0;gt<3;++gt){it[gt]=0;var mt=(et+gt+1)%3;for(H=0;H<2;++H){var vt=H?ct:1-ct;for(W=0|Math.min(Math.max(ut+H,0),a[0]),G=0;G<2;++G){var yt=G?dt:1-dt;if(Z=0|Math.min(Math.max(ft+G,0),a[1]),Y=gt<2?this._field[mt].get(W,Z):(this.intensity.get(W,Z)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(Y)||isNaN(Y)){pt=!0;break e}var xt=vt*yt;it[gt]+=xt*Y}}}if(pt){if(X>0){for(var bt=0;bt<5;++bt)tt.pop();q-=1}continue t}tt.push(it[0],it[1],st[0],st[1],it[2]),q+=1}}nt.push(q)}this._contourOffsets[et]=rt,this._contourCounts[et]=nt}var _t=v.mallocFloat(tt.length);for(o=0;o<tt.length;++o)_t[o]=tt[o];this._contourBuffer.update(_t),v.freeFloat(_t)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},F.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)v.freeFloat(this._field[t].data)},F.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=v.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],h=this._field[l],f=(this.intensity,w(u,r[o])),d=f.cells,p=f.positions;for(this._dynamicOffsets[o]=n,e=0;e<d.length;++e)for(var g=d[e],m=0;m<2;++m){var y=p[g[m]],x=+y[0],b=0|x,_=0|Math.min(b+1,i[0]),M=x-b,A=1-M,k=+y[1],T=0|k,E=0|Math.min(T+1,i[1]),S=k-T,L=1-S,z=A*L,C=A*S,I=M*L,P=M*S,D=z*c.get(b,T)+C*c.get(b,E)+I*c.get(_,T)+P*c.get(_,E),R=z*h.get(b,T)+C*h.get(b,E)+I*h.get(_,T)+P*h.get(_,E);if(isNaN(D)||isNaN(R)){m&&(n-=1);break}a[2*n+0]=D,a[2*n+1]=R,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),v.freeFloat(a)}}},{\"./lib/shaders\":230,\"binary-search-bounds\":53,\"bit-twiddle\":54,colormap:80,\"gl-buffer\":128,\"gl-mat4/invert\":149,\"gl-mat4/multiply\":151,\"gl-texture2d\":232,\"gl-vao\":236,ndarray:427,\"ndarray-gradient\":418,\"ndarray-ops\":421,\"ndarray-pack\":422,\"surface-nets\":487,\"typedarray-pool\":496}],232:[function(t,e,r){\"use strict\";function n(t){m=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],v=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],y=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function i(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function a(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var 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n=t(\"./literals\");e.exports=n.slice().concat([\"layout\",\"centroid\",\"smooth\",\"case\",\"mat2x2\",\"mat2x3\",\"mat2x4\",\"mat3x2\",\"mat3x3\",\"mat3x4\",\"mat4x2\",\"mat4x3\",\"mat4x4\",\"uint\",\"uvec2\",\"uvec3\",\"uvec4\",\"samplerCubeShadow\",\"sampler2DArray\",\"sampler2DArrayShadow\",\"isampler2D\",\"isampler3D\",\"isamplerCube\",\"isampler2DArray\",\"usampler2D\",\"usampler3D\",\"usamplerCube\",\"usampler2DArray\",\"coherent\",\"restrict\",\"readonly\",\"writeonly\",\"resource\",\"atomic_uint\",\"noperspective\",\"patch\",\"sample\",\"subroutine\",\"common\",\"partition\",\"active\",\"filter\",\"image1D\",\"image2D\",\"image3D\",\"imageCube\",\"iimage1D\",\"iimage2D\",\"iimage3D\",\"iimageCube\",\"uimage1D\",\"uimage2D\",\"uimage3D\",\"uimageCube\",\"image1DArray\",\"image2DArray\",\"iimage1DArray\",\"iimage2DArray\",\"uimage1DArray\",\"uimage2DArray\",\"image1DShadow\",\"image2DShadow\",\"image1DArrayShadow\",\"image2DArrayShadow\",\"imageBuffer\",\"iimageBuffer\",\"uimageBuffer\",\"sampler1DArray\",\"sampler1DArrayShadow\",\"isampler1D\",\"isampler1DArray\",\"usampler1D\",\"usampler1DArray\",\"isampler2DRect\",\"usampler2DRect\",\"samplerBuffer\",\"isamplerBuffer\",\"usamplerBuffer\",\"sampler2DMS\",\"isampler2DMS\",\"usampler2DMS\",\"sampler2DMSArray\",\"isampler2DMSArray\",\"usampler2DMSArray\"])},{\"./literals\":249}],249:[function(t,e,r){e.exports=[\"precision\",\"highp\",\"mediump\",\"lowp\",\"attribute\",\"const\",\"uniform\",\"varying\",\"break\",\"continue\",\"do\",\"for\",\"while\",\"if\",\"else\",\"in\",\"out\",\"inout\",\"float\",\"int\",\"void\",\"bool\",\"true\",\"false\",\"discard\",\"return\",\"mat2\",\"mat3\",\"mat4\",\"vec2\",\"vec3\",\"vec4\",\"ivec2\",\"ivec3\",\"ivec4\",\"bvec2\",\"bvec3\",\"bvec4\",\"sampler1D\",\"sampler2D\",\"sampler3D\",\"samplerCube\",\"sampler1DShadow\",\"sampler2DShadow\",\"struct\",\"asm\",\"class\",\"union\",\"enum\",\"typedef\",\"template\",\"this\",\"packed\",\"goto\",\"switch\",\"default\",\"inline\",\"noinline\",\"volatile\",\"public\",\"static\",\"extern\",\"external\",\"interface\",\"long\",\"short\",\"double\",\"half\",\"fixed\",\"unsigned\",\"input\",\"output\",\"hvec2\",\"hvec3\",\"hvec4\",\"dvec2\",\"dvec3\",\"dvec4\",\"fvec2\",\"fvec3\",\"fvec4\",\"sampler2DRect\",\"sampler3DRect\",\"sampler2DRectShadow\",\"sizeof\",\"cast\",\"namespace\",\"using\"]},{}],250:[function(t,e,r){e.exports=[\"<<=\",\">>=\",\"++\",\"--\",\"<<\",\">>\",\"<=\",\">=\",\"==\",\"!=\",\"&&\",\"||\",\"+=\",\"-=\",\"*=\",\"/=\",\"%=\",\"&=\",\"^^\",\"^=\",\"|=\",\"(\",\")\",\"[\",\"]\",\".\",\"!\",\"~\",\"*\",\"/\",\"%\",\"+\",\"-\",\"<\",\">\",\"&\",\"^\",\"|\",\"?\",\":\",\"=\",\",\",\";\",\"{\",\"}\"]},{}],251:[function(t,e,r){function 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Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},n.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=i+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var a=new Int32Array(e+r+this.keys.length+this.bboxes.length);a[0]=this.extent,a[1]=this.n,a[2]=this.padding;for(var o=e,s=0;s<t.length;s++){var l=t[s];a[i+s]=o,a.set(l,o),o+=l.length}return a[i+t.length]=o,a.set(this.keys,o),o+=this.keys.length,a[i+t.length+1]=o,a.set(this.bboxes,o),o+=this.bboxes.length,a.buffer}},{}],253:[function(t,e,r){r.read=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,u=l>>1,c=-7,h=r?i-1:0,f=r?-1:1,d=t[e+h];for(h+=f,a=d&(1<<-c)-1,d>>=-c,c+=s;c>0;a=256*a+t[e+h],h+=f,c-=8);for(o=a&(1<<-c)-1,a>>=-c,c+=n;c>0;o=256*o+t[e+h],h+=f,c-=8);if(0===a)a=1-u;else{if(a===l)return o?NaN:(d?-1:1)*(1/0);o+=Math.pow(2,n),a-=u}return(d?-1:1)*o*Math.pow(2,a-n)},r.write=function(t,e,r,n,i,a){var o,s,l,u=8*a-i-1,c=(1<<u)-1,h=c>>1,f=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,d=n?0:a-1,p=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=c):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),e+=o+h>=1?f/l:f*Math.pow(2,1-h),e*l>=2&&(o++,l/=2),o+h>=c?(s=0,o=c):o+h>=1?(s=(e*l-1)*Math.pow(2,i),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,i),o=0));i>=8;t[r+d]=255&s,d+=p,s/=256,i-=8);for(o=o<<i|s,u+=i;u>0;t[r+d]=255&o,d+=p,o/=256,u-=8);t[r+d-p]|=128*g}},{}],254:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;r<=t;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function 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This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\nuniform mediump float u_blur;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_blur;\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_fade;\\nuniform float u_opacity;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float x_a = mod(v_linesofar / u_pattern_size_a.x, 1.0);\\n    float x_b = mod(v_linesofar / u_pattern_size_b.x, 1.0);\\n    float y_a = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_a.y);\\n    float y_b = 0.5 + (v_normal.y * v_linewidth.s / u_pattern_size_b.y);\\n    vec2 pos_a = mix(u_pattern_tl_a, u_pattern_br_a, vec2(x_a, y_a));\\n    vec2 pos_b = mix(u_pattern_tl_b, u_pattern_br_b, vec2(x_b, y_b));\\n\\n    vec4 color = mix(texture2D(u_image, pos_a), texture2D(u_image, pos_b), u_fade);\\n\\n    alpha *= u_opacity;\\n\\n    gl_FragColor = color * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform mediump float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying float v_linesofar;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n    v_linesofar = a_linesofar;\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},linesdfpattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\n\\nuniform float u_blur;\\nuniform sampler2D u_image;\\nuniform float u_sdfgamma;\\nuniform float u_mix;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    // Calculate the distance of the pixel from the line in pixels.\\n    float dist = length(v_normal) * v_linewidth.s;\\n\\n    // Calculate the antialiasing fade factor. This is either when fading in\\n    // the line in case of an offset line (v_linewidth.t) or when fading out\\n    // (v_linewidth.s)\\n    float blur = u_blur * v_gamma_scale;\\n    float alpha = clamp(min(dist - (v_linewidth.t - blur), v_linewidth.s - dist) / blur, 0.0, 1.0);\\n\\n    float sdfdist_a = texture2D(u_image, v_tex_a).a;\\n    float sdfdist_b = texture2D(u_image, v_tex_b).a;\\n    float sdfdist = mix(sdfdist_a, sdfdist_b, u_mix);\\n    alpha *= smoothstep(0.5 - u_sdfgamma, 0.5 + u_sdfgamma, sdfdist);\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n// floor(127 / 2) == 63.0\\n// the maximum allowed miter limit is 2.0 at the moment. the extrude normal is\\n// stored in a byte (-128..127). we scale regular normals up to length 63, but\\n// there are also \\\"special\\\" normals that have a bigger length (of up to 126 in\\n// this case).\\n// #define scale 63.0\\n#define scale 0.015873016\\n\\n// We scale the distance before adding it to the buffers so that we can store\\n// long distances for long segments. Use this value to unscale the distance.\\n#define LINE_DISTANCE_SCALE 2.0\\n\\nattribute vec2 a_pos;\\nattribute vec4 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform mediump float u_ratio;\\nuniform mediump float u_linewidth;\\nuniform mediump float u_gapwidth;\\nuniform mediump float u_antialiasing;\\nuniform vec2 u_patternscale_a;\\nuniform float u_tex_y_a;\\nuniform vec2 u_patternscale_b;\\nuniform float u_tex_y_b;\\nuniform float u_extra;\\nuniform mat2 u_antialiasingmatrix;\\nuniform mediump float u_offset;\\n\\nvarying vec2 v_normal;\\nvarying vec2 v_linewidth;\\nvarying vec2 v_tex_a;\\nvarying vec2 v_tex_b;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_extrude = a_data.xy - 128.0;\\n    float a_direction = mod(a_data.z, 4.0) - 1.0;\\n    float a_linesofar = (floor(a_data.z / 4.0) + a_data.w * 64.0) * LINE_DISTANCE_SCALE;\\n\\n    // We store the texture normals in the most insignificant bit\\n    // transform y so that 0 => -1 and 1 => 1\\n    // In the texture normal, x is 0 if the normal points straight up/down and 1 if it's a round cap\\n    // y is 1 if the normal points up, and -1 if it points down\\n    mediump vec2 normal = mod(a_pos, 2.0);\\n    normal.y = sign(normal.y - 0.5);\\n    v_normal = normal;\\n\\n    float inset = u_gapwidth + (u_gapwidth > 0.0 ? u_antialiasing : 0.0);\\n    float outset = u_gapwidth + u_linewidth * (u_gapwidth > 0.0 ? 2.0 : 1.0) + u_antialiasing;\\n\\n    // Scale the extrusion vector down to a normal and then up by the line width\\n    // of this vertex.\\n    mediump vec2 dist = outset * a_extrude * scale;\\n\\n    // Calculate the offset when drawing a line that is to the side of the actual line.\\n    // We do this by creating a vector that points towards the extrude, but rotate\\n    // it when we're drawing round end points (a_direction = -1 or 1) since their\\n    // extrude vector points in another direction.\\n    mediump float u = 0.5 * a_direction;\\n    mediump float t = 1.0 - abs(u);\\n    mediump vec2 offset = u_offset * a_extrude * scale * normal.y * mat2(t, -u, u, t);\\n\\n    // Remove the texture normal bit of the position before scaling it with the\\n    // model/view matrix.\\n    gl_Position = u_matrix * vec4(floor(a_pos * 0.5) + (offset + dist) / u_ratio, 0.0, 1.0);\\n\\n    v_tex_a = vec2(a_linesofar * u_patternscale_a.x, normal.y * u_patternscale_a.y + u_tex_y_a);\\n    v_tex_b = vec2(a_linesofar * u_patternscale_b.x, normal.y * u_patternscale_b.y + u_tex_y_b);\\n\\n    // position of y on the screen\\n    float y = gl_Position.y / gl_Position.w;\\n\\n    // how much features are squished in the y direction by the tilt\\n    float squish_scale = length(a_extrude) / length(u_antialiasingmatrix * a_extrude);\\n\\n    // how much features are squished in all directions by the perspectiveness\\n    float perspective_scale = 1.0 / (1.0 - min(y * u_extra, 0.9));\\n\\n    v_linewidth = vec2(outset, inset);\\n    v_gamma_scale = perspective_scale * squish_scale;\\n}\\n\"},outline:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    gl_FragColor = outline_color * (alpha * opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos;\\n\\n#pragma mapbox: define lowp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\n\\nvoid main() {\\n    #pragma mapbox: initialize lowp vec4 outline_color\\n    #pragma mapbox: initialize lowp float opacity\\n\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},outlinepattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    // find distance to outline for alpha interpolation\\n\\n    float dist = length(v_pos - gl_FragCoord.xy);\\n    float alpha = smoothstep(1.0, 0.0, dist);\\n    \\n\\n    gl_FragColor = mix(color1, color2, u_mix) * alpha * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_world;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\nvarying vec2 v_pos;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n\\n    v_pos = (gl_Position.xy / gl_Position.w + 1.0) / 2.0 * u_world;\\n}\\n\"},pattern:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity;\\nuniform vec2 u_pattern_tl_a;\\nuniform vec2 u_pattern_br_a;\\nuniform vec2 u_pattern_tl_b;\\nuniform vec2 u_pattern_br_b;\\nuniform float u_mix;\\n\\nuniform sampler2D u_image;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n\\n    vec2 imagecoord = mod(v_pos_a, 1.0);\\n    vec2 pos = mix(u_pattern_tl_a, u_pattern_br_a, imagecoord);\\n    vec4 color1 = texture2D(u_image, pos);\\n\\n    vec2 imagecoord_b = mod(v_pos_b, 1.0);\\n    vec2 pos2 = mix(u_pattern_tl_b, u_pattern_br_b, imagecoord_b);\\n    vec4 color2 = texture2D(u_image, pos2);\\n\\n    gl_FragColor = mix(color1, color2, u_mix) * u_opacity;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_pattern_size_a;\\nuniform vec2 u_pattern_size_b;\\nuniform vec2 u_pixel_coord_upper;\\nuniform vec2 u_pixel_coord_lower;\\nuniform float u_scale_a;\\nuniform float u_scale_b;\\nuniform float u_tile_units_to_pixels;\\n\\nattribute vec2 a_pos;\\n\\nvarying vec2 v_pos_a;\\nvarying vec2 v_pos_b;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    vec2 scaled_size_a = u_scale_a * u_pattern_size_a;\\n    vec2 scaled_size_b = u_scale_b * u_pattern_size_b;\\n\\n    // the correct offset needs to be calculated.\\n    //\\n    // The offset depends on how many pixels are between the world origin and\\n    // the edge of the tile:\\n    // vec2 offset = mod(pixel_coord, size)\\n    //\\n    // At high zoom levels there are a ton of pixels between the world origin\\n    // and the edge of the tile. The glsl spec only guarantees 16 bits of\\n    // precision for highp floats. We need more than that.\\n    //\\n    // The pixel_coord is passed in as two 16 bit values:\\n    // pixel_coord_upper = floor(pixel_coord / 2^16)\\n    // pixel_coord_lower = mod(pixel_coord, 2^16)\\n    //\\n    // The offset is calculated in a series of steps that should preserve this precision:\\n    vec2 offset_a = mod(mod(mod(u_pixel_coord_upper, scaled_size_a) * 256.0, scaled_size_a) * 256.0 + u_pixel_coord_lower, scaled_size_a);\\n    vec2 offset_b = mod(mod(mod(u_pixel_coord_upper, scaled_size_b) * 256.0, scaled_size_b) * 256.0 + u_pixel_coord_lower, scaled_size_b);\\n\\n    v_pos_a = (u_tile_units_to_pixels * a_pos + offset_a) / scaled_size_a;\\n    v_pos_b = (u_tile_units_to_pixels * a_pos + offset_b) / scaled_size_b;\\n}\\n\"},raster:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_opacity0;\\nuniform float u_opacity1;\\nuniform sampler2D u_image0;\\nuniform sampler2D u_image1;\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nuniform float u_brightness_low;\\nuniform float u_brightness_high;\\n\\nuniform float u_saturation_factor;\\nuniform float u_contrast_factor;\\nuniform vec3 u_spin_weights;\\n\\nvoid main() {\\n\\n    // read and cross-fade colors from the main and parent tiles\\n    vec4 color0 = texture2D(u_image0, v_pos0);\\n    vec4 color1 = texture2D(u_image1, v_pos1);\\n    vec4 color = color0 * u_opacity0 + color1 * u_opacity1;\\n    vec3 rgb = color.rgb;\\n\\n    // spin\\n    rgb = vec3(\\n        dot(rgb, u_spin_weights.xyz),\\n        dot(rgb, u_spin_weights.zxy),\\n        dot(rgb, u_spin_weights.yzx));\\n\\n    // saturation\\n    float average = (color.r + color.g + color.b) / 3.0;\\n    rgb += (average - rgb) * u_saturation_factor;\\n\\n    // contrast\\n    rgb = (rgb - 0.5) * u_contrast_factor + 0.5;\\n\\n    // brightness\\n    vec3 u_high_vec = vec3(u_brightness_low, u_brightness_low, u_brightness_low);\\n    vec3 u_low_vec = vec3(u_brightness_high, u_brightness_high, u_brightness_high);\\n\\n    gl_FragColor = vec4(mix(u_high_vec, u_low_vec, rgb), color.a);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform mat4 u_matrix;\\nuniform vec2 u_tl_parent;\\nuniform float u_scale_parent;\\nuniform float u_buffer_scale;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_texture_pos;\\n\\nvarying vec2 v_pos0;\\nvarying vec2 v_pos1;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos, 0, 1);\\n    v_pos0 = (((a_texture_pos / 32767.0) - 0.5) / u_buffer_scale ) + 0.5;\\n    v_pos1 = (v_pos0 * u_scale_parent) + u_tl_parent;\\n}\\n\"},icon:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp float u_opacity;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    lowp float alpha = texture2D(u_fadetexture, v_fade_tex).a * u_opacity;\\n    gl_FragColor = texture2D(u_texture, v_tex) * alpha;\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n    if (u_rotate_with_map) {\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    } else {\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},sdf:{fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform sampler2D u_texture;\\nuniform sampler2D u_fadetexture;\\nuniform lowp vec4 u_color;\\nuniform lowp float u_opacity;\\nuniform lowp float u_buffer;\\nuniform lowp float u_gamma;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    lowp float dist = texture2D(u_texture, v_tex).a;\\n    lowp float fade_alpha = texture2D(u_fadetexture, v_fade_tex).a;\\n    lowp float gamma = u_gamma * v_gamma_scale;\\n    lowp float alpha = smoothstep(u_buffer - gamma, u_buffer + gamma, dist) * fade_alpha;\\n\\n    gl_FragColor = u_color * (alpha * u_opacity);\\n\\n#ifdef OVERDRAW_INSPECTOR\\n    gl_FragColor = vec4(1.0);\\n#endif\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nconst float PI = 3.141592653589793;\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_offset;\\nattribute vec2 a_texture_pos;\\nattribute vec4 a_data;\\n\\n\\n// matrix is for the vertex position.\\nuniform mat4 u_matrix;\\n\\nuniform mediump float u_zoom;\\nuniform bool u_rotate_with_map;\\nuniform bool u_pitch_with_map;\\nuniform mediump float u_pitch;\\nuniform mediump float u_bearing;\\nuniform mediump float u_aspect_ratio;\\nuniform vec2 u_extrude_scale;\\n\\nuniform vec2 u_texsize;\\n\\nvarying vec2 v_tex;\\nvarying vec2 v_fade_tex;\\nvarying float v_gamma_scale;\\n\\nvoid main() {\\n    vec2 a_tex = a_texture_pos.xy;\\n    mediump float a_labelminzoom = a_data[0];\\n    mediump vec2 a_zoom = a_data.pq;\\n    mediump float a_minzoom = a_zoom[0];\\n    mediump float a_maxzoom = a_zoom[1];\\n\\n    // u_zoom is the current zoom level adjusted for the change in font size\\n    mediump float z = 2.0 - step(a_minzoom, u_zoom) - (1.0 - step(a_maxzoom, u_zoom));\\n\\n    // pitch-alignment: map\\n    // rotation-alignment: map | viewport\\n    if (u_pitch_with_map) {\\n        lowp float angle = u_rotate_with_map ? (a_data[1] / 256.0 * 2.0 * PI) : u_bearing;\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, asin, -1.0 * asin, acos);\\n        vec2 offset = RotationMatrix * a_offset;\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos + extrude, 0, 1);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: map\\n    } else if (u_rotate_with_map) {\\n        // foreshortening factor to apply on pitched maps\\n        // as a label goes from horizontal <=> vertical in angle\\n        // it goes from 0% foreshortening to up to around 70% foreshortening\\n        lowp float pitchfactor = 1.0 - cos(u_pitch * sin(u_pitch * 0.75));\\n\\n        lowp float lineangle = a_data[1] / 256.0 * 2.0 * PI;\\n\\n        // use the lineangle to position points a,b along the line\\n        // project the points and calculate the label angle in projected space\\n        // this calculation allows labels to be rendered unskewed on pitched maps\\n        vec4 a = u_matrix * vec4(a_pos, 0, 1);\\n        vec4 b = u_matrix * vec4(a_pos + vec2(cos(lineangle),sin(lineangle)), 0, 1);\\n        lowp float angle = atan((b[1]/b[3] - a[1]/a[3])/u_aspect_ratio, b[0]/b[3] - a[0]/a[3]);\\n        lowp float asin = sin(angle);\\n        lowp float acos = cos(angle);\\n        mat2 RotationMatrix = mat2(acos, -1.0 * asin, asin, acos);\\n\\n        vec2 offset = RotationMatrix * (vec2((1.0-pitchfactor)+(pitchfactor*cos(angle*2.0)), 1.0) * a_offset);\\n        vec2 extrude = u_extrude_scale * (offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n        gl_Position.z += z * gl_Position.w;\\n    // pitch-alignment: viewport\\n    // rotation-alignment: viewport\\n    } else {\\n        vec2 extrude = u_extrude_scale * (a_offset / 64.0);\\n        gl_Position = u_matrix * vec4(a_pos, 0, 1) + vec4(extrude, 0, 0);\\n    }\\n\\n    v_gamma_scale = (gl_Position.w - 0.5);\\n\\n    v_tex = a_tex / u_texsize;\\n    v_fade_tex = vec2(a_labelminzoom / 255.0, 0.0);\\n}\\n\"},collisionbox:{\n",
+       "fragmentSource:\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nuniform float u_zoom;\\nuniform float u_maxzoom;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n\\n    float alpha = 0.5;\\n\\n    gl_FragColor = vec4(0.0, 1.0, 0.0, 1.0) * alpha;\\n\\n    if (v_placement_zoom > u_zoom) {\\n        gl_FragColor = vec4(1.0, 0.0, 0.0, 1.0) * alpha;\\n    }\\n\\n    if (u_zoom >= v_max_zoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 0.0, 1.0) * alpha * 0.25;\\n    }\\n\\n    if (v_placement_zoom >= u_maxzoom) {\\n        gl_FragColor = vec4(0.0, 0.0, 1.0, 1.0) * alpha * 0.2;\\n    }\\n}\\n\",vertexSource:\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#define lowp\\n#define mediump\\n#define highp\\n#endif\\n\\nattribute vec2 a_pos;\\nattribute vec2 a_extrude;\\nattribute vec2 a_data;\\n\\nuniform mat4 u_matrix;\\nuniform float u_scale;\\n\\nvarying float v_max_zoom;\\nvarying float v_placement_zoom;\\n\\nvoid main() {\\n    gl_Position = u_matrix * vec4(a_pos + a_extrude / u_scale, 0.0, 1.0);\\n\\n    v_max_zoom = a_data.x;\\n    v_placement_zoom = a_data.y;\\n}\\n\"}},e.exports.util=\"float evaluate_zoom_function_1(const vec4 values, const float t) {\\n    if (t < 1.0) {\\n        return mix(values[0], values[1], t);\\n    } else if (t < 2.0) {\\n        return mix(values[1], values[2], t - 1.0);\\n    } else {\\n        return mix(values[2], values[3], t - 2.0);\\n    }\\n}\\nvec4 evaluate_zoom_function_4(const vec4 value0, const vec4 value1, const vec4 value2, const vec4 value3, const float t) {\\n    if (t < 1.0) {\\n        return mix(value0, value1, t);\\n    } else if (t < 2.0) {\\n        return mix(value1, value2, t - 1.0);\\n    } else {\\n        return mix(value2, value3, t - 2.0);\\n    }\\n}\\n\"},{path:434}],265:[function(t,e,r){\"use strict\";function n(t,e){this.message=(t?t+\": \":\"\")+i.apply(i,Array.prototype.slice.call(arguments,2)),null!==e&&void 0!==e&&e.__line__&&(this.line=e.__line__)}var i=t(\"util\").format;e.exports=n},{util:504}],266:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1;e<arguments.length;e++){var r=arguments[e];for(var n in r)t[n]=r[n]}return t}},{}],267:[function(t,e,r){\"use strict\";e.exports=function(t){return t instanceof Number?\"number\":t instanceof String?\"string\":t instanceof Boolean?\"boolean\":Array.isArray(t)?\"array\":null===t?\"null\":typeof t}},{}],268:[function(t,e,r){\"use strict\";e.exports=function(t){return t instanceof Number||t instanceof String||t instanceof Boolean?t.valueOf():t}},{}],269:[function(t,e,r){\"use strict\";var n=t(\"../error/validation_error\"),i=t(\"../util/get_type\"),a=t(\"../util/extend\");e.exports=function(e){var 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this.paintVertexArrays)t.push(this.paintVertexArrays[e].arrayBuffer)}},{\"../util/util\":403}],290:[function(t,e,r){\"use strict\";function n(t){if(this.zoom=t.zoom,this.overscaling=t.overscaling,this.layer=t.layer,this.childLayers=t.childLayers,this.type=this.layer.type,this.features=[],this.id=this.layer.id,this.index=t.index,this.sourceLayer=this.layer.sourceLayer,this.sourceLayerIndex=t.sourceLayerIndex,this.minZoom=this.layer.minzoom,this.maxZoom=this.layer.maxzoom,this.paintAttributes=i(this),t.arrays){var e=this.programInterfaces;this.bufferGroups=c.mapObject(t.arrays,function(r,n){var i=e[n],a=t.paintVertexArrayTypes[n];return r.map(function(t){return new u(t,{layoutVertexArrayType:i.layoutVertexArrayType.serialize(),elementArrayType:i.elementArrayType&&i.elementArrayType.serialize(),elementArrayType2:i.elementArrayType2&&i.elementArrayType2.serialize(),paintVertexArrayTypes:a})})})}}function i(t){var e={};for(var r in t.programInterfaces){for(var n=e[r]={},i=0;i<t.childLayers.length;i++){var s=t.childLayers[i];n[s.id]={attributes:[],uniforms:[],defines:[],vertexPragmas:{define:{},initialize:{}},fragmentPragmas:{define:{},initialize:{}}}}var l=t.programInterfaces[r];if(l.paintAttributes)for(var u=\"{precision}\",h=\"{type}\",d=0;d<l.paintAttributes.length;d++){var p=l.paintAttributes[d];p.multiplier=p.multiplier||1;for(var g=0;g<t.childLayers.length;g++){var m=t.childLayers[g],v=n[m.id],y=p.name;f(\"a_\"===p.name.slice(0,2));var x,b=p.name.slice(2);if(v.fragmentPragmas.initialize[b]=\"\",m.isPaintValueFeatureConstant(p.paintProperty))v.uniforms.push(p),v.fragmentPragmas.define[b]=v.vertexPragmas.define[b]=[\"uniform\",u,h,y].join(\" \")+\";\",v.fragmentPragmas.initialize[b]=v.vertexPragmas.initialize[b]=[u,h,b,\"=\",y].join(\" \")+\";\\n\";else if(m.isPaintValueZoomConstant(p.paintProperty)){v.attributes.push(c.extend({},p,{name:y})),x=[\"varying\",u,h,b].join(\" \")+\";\\n\";var _=[v.fragmentPragmas.define[b],\"attribute\",u,h,y].join(\" \")+\";\\n\";v.fragmentPragmas.define[b]=x,v.vertexPragmas.define[b]=x+_,v.vertexPragmas.initialize[b]=[b,\"=\",y,\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\"}else{for(var w=\"u_\"+y.slice(2)+\"_t\",M=m.getPaintValueStopZoomLevels(p.paintProperty),A=0;A<M.length&&M[A]<t.zoom;)A++;for(var k=Math.max(0,Math.min(M.length-4,A-2)),T=[],E=0;E<4;E++)T.push(M[Math.min(k+E,M.length-1)]);x=[\"varying\",u,h,b].join(\" \")+\";\\n\",v.vertexPragmas.define[b]=x+[\"uniform\",\"lowp\",\"float\",w].join(\" \")+\";\\n\",v.fragmentPragmas.define[b]=x,v.uniforms.push(c.extend({},p,{name:w,getValue:o(p,k),components:1}));var S=p.components;if(1===S)v.attributes.push(c.extend({},p,{getValue:a(p,T),isFunction:!0,components:4*S})),v.vertexPragmas.define[b]+=[\"attribute\",u,\"vec4\",y].join(\" \")+\";\\n\",v.vertexPragmas.initialize[b]=[b,\"=\",\"evaluate_zoom_function_1(\"+y+\", \"+w+\")\",\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\";else{for(var L=[],z=0;z<4;z++)L.push(y+z),v.attributes.push(c.extend({},p,{getValue:a(p,[T[z]]),isFunction:!0,name:y+z})),v.vertexPragmas.define[b]+=[\"attribute\",u,h,y+z].join(\" \")+\";\\n\";v.vertexPragmas.initialize[b]=[b,\" = \",\"evaluate_zoom_function_4(\"+L.join(\", \")+\", \"+w+\")\",\"/\",p.multiplier.toFixed(1)].join(\" \")+\";\\n\"}}}}}return e}function a(t,e){return function(r,n,i){if(1===e.length)return t.getValue(r,c.extend({},n,{zoom:e[0]}),i);for(var a=[],o=0;o<e.length;o++){var s=e[o];a.push(t.getValue(r,c.extend({},n,{zoom:s}),i)[0])}return a}}function o(t,e){return function(r,n){var i=r.getPaintInterpolationT(t.paintProperty,n.zoom);return[Math.max(0,Math.min(4,i-e))]}}var s=t(\"feature-filter\"),l=t(\"./array_group\"),u=t(\"./buffer_group\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"assert\");e.exports=n,n.create=function(e){var r={fill:t(\"./bucket/fill_bucket\"),line:t(\"./bucket/line_bucket\"),circle:t(\"./bucket/circle_bucket\"),symbol:t(\"./bucket/symbol_bucket\")};return new r[e.layer.type](e)},n.EXTENT=8192,n.prototype.populateArrays=function(){this.createArrays(),this.recalculateStyleLayers();for(var t=0;t<this.features.length;t++)this.addFeature(this.features[t]);this.trimArrays()},n.prototype.prepareArrayGroup=function(t,e){var r=this.arrayGroups[t],n=r.length&&r[r.length-1];return n&&n.hasCapacityFor(e)||(n=new l({layoutVertexArrayType:this.programInterfaces[t].layoutVertexArrayType,elementArrayType:this.programInterfaces[t].elementArrayType,elementArrayType2:this.programInterfaces[t].elementArrayType2,paintVertexArrayTypes:this.paintVertexArrayTypes[t]}),n.index=r.length,r.push(n)),n},n.prototype.createArrays=function(){this.arrayGroups={},this.paintVertexArrayTypes={};for(var t in this.programInterfaces){this.arrayGroups[t]=[];var e=this.paintVertexArrayTypes[t]={},r=this.paintAttributes[t];for(var i in r)e[i]=new n.VertexArrayType(r[i].attributes)}},n.prototype.destroy=function(t){for(var e in this.bufferGroups)for(var r=this.bufferGroups[e],n=0;n<r.length;n++)r[n].destroy(t)},n.prototype.trimArrays=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)e[r].trim()},n.prototype.isEmpty=function(){for(var t in this.arrayGroups)for(var e=this.arrayGroups[t],r=0;r<e.length;r++)if(!e[r].isEmpty())return!1;return!0},n.prototype.getTransferables=function(t){for(var e in this.arrayGroups)for(var r=this.arrayGroups[e],n=0;n<r.length;n++)r[n].getTransferables(t)},n.prototype.setUniforms=function(t,e,r,n,i){for(var a=this.paintAttributes[e][n.id].uniforms,o=0;o<a.length;o++){var s=a[o],l=r[s.name];t[\"uniform\"+s.components+\"fv\"](l,s.getValue(n,i))}},n.prototype.serialize=function(){return{layerId:this.layer.id,zoom:this.zoom,arrays:c.mapObject(this.arrayGroups,function(t){return t.map(function(t){return t.serialize()})}),paintVertexArrayTypes:c.mapObject(this.paintVertexArrayTypes,function(t){return c.mapObject(t,function(t){return t.serialize()})}),childLayerIds:this.childLayers.map(function(t){return t.id})}},n.prototype.createFilter=function(){this.filter||(this.filter=s(this.layer.filter))};var d={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};n.prototype.recalculateStyleLayers=function(){for(var t=0;t<this.childLayers.length;t++)this.childLayers[t].recalculate(this.zoom,d)},n.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a=0;a<this.childLayers.length;a++)for(var o=this.childLayers[a],s=this.arrayGroups[t],l=n.index;l<s.length;l++){var u=s[l],c=u.layoutVertexArray.length,h=u.paintVertexArrays[o.id];h.resize(c);for(var f=this.paintAttributes[t][o.id].attributes,d=0;d<f.length;d++)for(var p=f[d],g=p.getValue(o,e,r),m=p.multiplier||1,v=p.components||1,y=l===n.index?i:0,x=y;x<c;x++)for(var b=h.get(x),_=0;_<v;_++){var w=v>1?p.name+_:p.name;b[w]=g[_]*m}}},n.VertexArrayType=function(t){return new h({members:t,alignment:4})},n.ElementArrayType=function(t){return new h({members:[{type:\"Uint16\",name:\"vertices\",components:t||3}]})}},{\"../util/struct_array\":401,\"../util/util\":403,\"./array_group\":289,\"./bucket/circle_bucket\":291,\"./bucket/fill_bucket\":292,\"./bucket/line_bucket\":293,\"./bucket/symbol_bucket\":294,\"./buffer_group\":296,assert:34,\"feature-filter\":105}],291:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addCircleVertex=function(t,e,r,n,i){return t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)},n.prototype.programInterfaces={circle:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType,paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"circle-color\",e,r)},multiplier:255,paintProperty:\"circle-color\"},{name:\"a_radius\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-radius\",e,r)]},multiplier:10,paintProperty:\"circle-radius\"},{name:\"a_blur\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-blur\",e,r)]},multiplier:10,paintProperty:\"circle-blur\"},{name:\"a_opacity\",components:1,type:\"Uint16\",isLayerConstant:!1,getValue:function(t,e,r){return[t.getPaintValue(\"circle-opacity\",e,r)]},multiplier:255,paintProperty:\"circle-opacity\"}]}},n.prototype.addFeature=function(t){for(var e={zoom:this.zoom},r=o(t),n=this.prepareArrayGroup(\"circle\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)for(var l=0;l<r[a].length;l++){var u=r[a][l].x,c=r[a][l].y;if(!(u<0||u>=s||c<0||c>=s)){var h=this.prepareArrayGroup(\"circle\",4),f=h.layoutVertexArray,d=this.addCircleVertex(f,u,c,-1,-1);this.addCircleVertex(f,u,c,1,-1),this.addCircleVertex(f,u,c,1,1),this.addCircleVertex(f,u,c,-1,1),h.elementArray.emplaceBack(d,d+1,d+2),h.elementArray.emplaceBack(d,d+3,d+2)}}this.populatePaintArrays(\"circle\",e,t.properties,n,i)}},{\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298}],292:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=t(\"earcut\"),l=t(\"../../util/classify_rings\"),u=500;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.programInterfaces={fill:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"}]),elementArrayType:new i.ElementArrayType(1),elementArrayType2:new i.ElementArrayType(2),paintAttributes:[{name:\"a_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-color\",e,r)},multiplier:255,paintProperty:\"fill-color\"},{name:\"a_outline_color\",components:4,type:\"Uint8\",getValue:function(t,e,r){return t.getPaintValue(\"fill-outline-color\",e,r)},multiplier:255,paintProperty:\"fill-outline-color\"},{name:\"a_opacity\",components:1,type:\"Uint8\",getValue:function(t,e,r){return[t.getPaintValue(\"fill-opacity\",e,r)]},multiplier:255,paintProperty:\"fill-opacity\"}]}},n.prototype.addFeature=function(t){for(var e=o(t),r=l(e,u),n=this.prepareArrayGroup(\"fill\",0),i=n.layoutVertexArray.length,a=0;a<r.length;a++)this.addPolygon(r[a]);this.populatePaintArrays(\"fill\",{zoom:this.zoom},t.properties,n,i)},n.prototype.addPolygon=function(t){for(var e=0,r=0;r<t.length;r++)e+=t[r].length;for(var n=this.prepareArrayGroup(\"fill\",e),i=[],a=[],o=n.layoutVertexArray.length,l=0;l<t.length;l++){var u=t[l];l>0&&a.push(i.length/2);for(var c=0;c<u.length;c++){var h=u[c],f=n.layoutVertexArray.emplaceBack(h.x,h.y);c>=1&&n.elementArray2.emplaceBack(f-1,f),i.push(h.x),i.push(h.y)}}for(var d=s(i,a),p=0;p<d.length;p++)n.elementArray.emplaceBack(d[p]+o)}},{\"../../util/classify_rings\":391,\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298,earcut:99}],293:[function(t,e,r){\"use strict\";function n(){i.apply(this,arguments)}var i=t(\"../bucket\"),a=t(\"../../util/util\"),o=t(\"../load_geometry\"),s=i.EXTENT,l=63,u=Math.cos(37.5*(Math.PI/180)),c=15,h=15,f=.5,d=Math.pow(2,h-1)/f;e.exports=n,n.prototype=a.inherit(i,{}),n.prototype.addLineVertex=function(t,e,r,n,i,a,o){return t.emplaceBack(e.x<<1|n,e.y<<1|i,Math.round(l*r.x)+128,Math.round(l*r.y)+128,(0===a?0:a<0?-1:1)+1|(o*f&63)<<2,o*f>>6)},n.prototype.programInterfaces={line:{layoutVertexArrayType:new i.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),elementArrayType:new i.ElementArrayType}},n.prototype.addFeature=function(t){for(var e=o(t,h),r=0;r<e.length;r++)this.addLine(e[r],this.layer.layout[\"line-join\"],this.layer.layout[\"line-cap\"],this.layer.layout[\"line-miter-limit\"],this.layer.layout[\"line-round-limit\"])},n.prototype.addLine=function(t,e,r,n,i){for(var a=t.length;a>2&&t[a-1].equals(t[a-2]);)a--;if(!(t.length<2)){\"bevel\"===e&&(n=1.05);var o=c*(s/(512*this.overscaling)),l=t[0],h=t[a-1],f=l.equals(h);if(this.prepareArrayGroup(\"line\",10*a),2!==a||!f){this.distance=0;var d,p,g,m,v,y,x,b=r,_=f?\"butt\":r,w=!0;this.e1=this.e2=this.e3=-1,f&&(d=t[a-2],v=l.sub(d)._unit()._perp());for(var M=0;M<a;M++)if(g=f&&M===a-1?t[1]:t[M+1],!g||!t[M].equals(g)){v&&(m=v),d&&(p=d),d=t[M],v=g?g.sub(d)._unit()._perp():m,m=m||v;var A=m.add(v)._unit(),k=A.x*v.x+A.y*v.y,T=1/k,E=k<u&&p&&g;if(E&&M>0){var S=d.dist(p);if(S>2*o){var L=d.sub(d.sub(p)._mult(o/S)._round());this.distance+=L.dist(p),this.addCurrentVertex(L,this.distance,m.mult(1),0,0,!1),p=L}}var z=p&&g,C=z?e:g?b:_;if(z&&\"round\"===C&&(T<i?C=\"miter\":T<=2&&(C=\"fakeround\")),\"miter\"===C&&T>n&&(C=\"bevel\"),\"bevel\"===C&&(T>2&&(C=\"flipbevel\"),T<n&&(C=\"miter\")),p&&(this.distance+=d.dist(p)),\"miter\"===C)A._mult(T),this.addCurrentVertex(d,this.distance,A,0,0,!1);else if(\"flipbevel\"===C){if(T>100)A=v.clone();else{var I=m.x*v.y-m.y*v.x>0?-1:1,P=T*m.add(v).mag()/m.sub(v).mag();A._perp()._mult(P*I)}this.addCurrentVertex(d,this.distance,A,0,0,!1),this.addCurrentVertex(d,this.distance,A.mult(-1),0,0,!1)}else if(\"bevel\"===C||\"fakeround\"===C){var D=m.x*v.y-m.y*v.x>0,R=-Math.sqrt(T*T-1);if(D?(x=0,y=R):(y=0,x=R),w||this.addCurrentVertex(d,this.distance,m,y,x,!1),\"fakeround\"===C){for(var O,F=Math.floor(8*(.5-(k-.5))),j=0;j<F;j++)O=v.mult((j+1)/(F+1))._add(m)._unit(),this.addPieSliceVertex(d,this.distance,O,D);this.addPieSliceVertex(d,this.distance,A,D);for(var N=F-1;N>=0;N--)O=m.mult((N+1)/(F+1))._add(v)._unit(),this.addPieSliceVertex(d,this.distance,O,D)}g&&this.addCurrentVertex(d,this.distance,v,-y,-x,!1)}else\"butt\"===C?(w||this.addCurrentVertex(d,this.distance,m,0,0,!1),g&&this.addCurrentVertex(d,this.distance,v,0,0,!1)):\"square\"===C?(w||(this.addCurrentVertex(d,this.distance,m,1,1,!1),this.e1=this.e2=-1),g&&this.addCurrentVertex(d,this.distance,v,-1,-1,!1)):\"round\"===C&&(w||(this.addCurrentVertex(d,this.distance,m,0,0,!1),this.addCurrentVertex(d,this.distance,m,1,1,!0),this.e1=this.e2=-1),g&&(this.addCurrentVertex(d,this.distance,v,-1,-1,!0),this.addCurrentVertex(d,this.distance,v,0,0,!1)));if(E&&M<a-1){var B=d.dist(g);if(B>2*o){var U=d.add(g.sub(d)._mult(o/B)._round());this.distance+=U.dist(d),this.addCurrentVertex(U,this.distance,v.mult(1),0,0,!1),d=U}}w=!1}}}},n.prototype.addCurrentVertex=function(t,e,r,n,i,a){var o,s=a?1:0,l=this.arrayGroups.line[this.arrayGroups.line.length-1],u=l.layoutVertexArray,c=l.elementArray;o=r.clone(),n&&o._sub(r.perp()._mult(n)),this.e3=this.addLineVertex(u,t,o,s,0,n,e),this.e1>=0&&this.e2>=0&&c.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,o=r.mult(-1),i&&o._sub(r.perp()._mult(i)),this.e3=this.addLineVertex(u,t,o,s,1,-i,e),this.e1>=0&&this.e2>=0&&c.emplaceBack(this.e1,this.e2,this.e3),this.e1=this.e2,this.e2=this.e3,e>d/2&&(this.distance=0,this.addCurrentVertex(t,this.distance,r,n,i,a))},n.prototype.addPieSliceVertex=function(t,e,r,n){var i=n?1:0;r=r.mult(n?-1:1);var a=this.arrayGroups.line[this.arrayGroups.line.length-1],o=a.layoutVertexArray,s=a.elementArray;this.e3=this.addLineVertex(o,t,r,0,i,0,e),this.e1>=0&&this.e2>=0&&s.emplaceBack(this.e1,this.e2,this.e3),n?this.e2=this.e3:this.e1=this.e3}},{\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298}],294:[function(t,e,r){\"use strict\";function n(t){o.apply(this,arguments),this.showCollisionBoxes=t.showCollisionBoxes,this.overscaling=t.overscaling,this.collisionBoxArray=t.collisionBoxArray,this.symbolQuadsArray=t.symbolQuadsArray,this.symbolInstancesArray=t.symbolInstancesArray,this.sdfIcons=t.sdfIcons,this.iconsNeedLinear=t.iconsNeedLinear,this.adjustedTextSize=t.adjustedTextSize,this.adjustedIconSize=t.adjustedIconSize,this.fontstack=t.fontstack}function i(t,e,r,n,i,a,o,s,l,u,c){return t.emplaceBack(e,r,Math.round(64*n),Math.round(64*i),a/4,o/4,10*(u||0),c,10*(s||0),10*Math.min(l||25,25))}var a=t(\"point-geometry\"),o=t(\"../bucket\"),s=t(\"../../symbol/anchor\"),l=t(\"../../symbol/get_anchors\"),u=t(\"../../util/token\"),c=t(\"../../symbol/quads\"),h=t(\"../../symbol/shaping\"),f=t(\"../../symbol/resolve_text\"),d=t(\"../../symbol/mergelines\"),p=t(\"../../symbol/clip_line\"),g=t(\"../../util/util\"),m=t(\"../load_geometry\"),v=t(\"../../symbol/collision_feature\"),y=h.shapeText,x=h.shapeIcon,b=c.getGlyphQuads,_=c.getIconQuads,w=o.EXTENT;e.exports=n,n.MAX_QUADS=65535,n.prototype=g.inherit(o,{}),n.prototype.serialize=function(){var t=o.prototype.serialize.apply(this);return t.sdfIcons=this.sdfIcons,t.iconsNeedLinear=this.iconsNeedLinear,t.adjustedTextSize=this.adjustedTextSize,t.adjustedIconSize=this.adjustedIconSize,t.fontstack=this.fontstack,t};var M=new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_offset\",components:2,type:\"Int16\"},{name:\"a_texture_pos\",components:2,type:\"Uint16\"},{name:\"a_data\",components:4,type:\"Uint8\"}]),A=new o.ElementArrayType;n.prototype.addCollisionBoxVertex=function(t,e,r,n,i){return t.emplaceBack(e.x,e.y,Math.round(r.x),Math.round(r.y),10*n,10*i)},n.prototype.programInterfaces={glyph:{layoutVertexArrayType:M,elementArrayType:A},icon:{layoutVertexArrayType:M,elementArrayType:A},collisionBox:{layoutVertexArrayType:new o.VertexArrayType([{name:\"a_pos\",components:2,type:\"Int16\"},{name:\"a_extrude\",components:2,type:\"Int16\"},{name:\"a_data\",components:2,type:\"Uint8\"}])}},n.prototype.populateArrays=function(t,e,r){var n={lastIntegerZoom:1/0,lastIntegerZoomTime:0,lastZoom:0};this.adjustedTextMaxSize=this.layer.getLayoutValue(\"text-size\",{zoom:18,zoomHistory:n}),this.adjustedTextSize=this.layer.getLayoutValue(\"text-size\",{zoom:this.zoom+1,zoomHistory:n}),this.adjustedIconMaxSize=this.layer.getLayoutValue(\"icon-size\",{zoom:18,zoomHistory:n}),this.adjustedIconSize=this.layer.getLayoutValue(\"icon-size\",{zoom:this.zoom+1,zoomHistory:n});var i=512*this.overscaling;this.tilePixelRatio=w/i,this.compareText={},this.iconsNeedLinear=!1,this.symbolInstancesStartIndex=this.symbolInstancesArray.length;var a=this.layer.layout,o=this.features,s=this.textFeatures,l=.5,c=.5;switch(a[\"text-anchor\"]){case\"right\":case\"top-right\":case\"bottom-right\":l=1;break;case\"left\":case\"top-left\":case\"bottom-left\":l=0}switch(a[\"text-anchor\"]){case\"bottom\":case\"bottom-right\":case\"bottom-left\":c=1;break;case\"top\":case\"top-right\":case\"top-left\":c=0}for(var h=\"right\"===a[\"text-justify\"]?1:\"left\"===a[\"text-justify\"]?0:.5,f=24,p=a[\"text-line-height\"]*f,v=\"line\"!==a[\"symbol-placement\"]?a[\"text-max-width\"]*f:0,b=a[\"text-letter-spacing\"]*f,_=[a[\"text-offset\"][0]*f,a[\"text-offset\"][1]*f],M=this.fontstack=a[\"text-font\"].join(\",\"),A=[],k=0;k<o.length;k++)A.push(m(o[k]));if(\"line\"===a[\"symbol-placement\"]){var T=d(o,s,A);A=T.geometries,o=T.features,s=T.textFeatures}for(var E,S,L=0;L<o.length;L++)if(A[L]){if(E=s[L]?y(s[L],e[M],v,p,l,c,h,b,_):null,a[\"icon-image\"]){var z=u(o[L].properties,a[\"icon-image\"]),C=r[z];S=x(C,a),C&&(void 0===this.sdfIcons?this.sdfIcons=C.sdf:this.sdfIcons!==C.sdf&&g.warnOnce(\"Style sheet warning: Cannot mix SDF and non-SDF icons in one buffer\"),1!==C.pixelRatio?this.iconsNeedLinear=!0:0===a[\"icon-rotate\"]&&this.layer.isLayoutValueFeatureConstant(\"icon-rotate\")||(this.iconsNeedLinear=!0))}else S=null;(E||S)&&this.addFeature(A[L],E,S,o[L])}this.symbolInstancesEndIndex=this.symbolInstancesArray.length,this.placeFeatures(t,this.showCollisionBoxes),this.trimArrays()},n.prototype.addFeature=function(t,e,r,n){var i=this.layer.layout,a=24,o=this.adjustedTextSize/a,u=void 0!==this.adjustedTextMaxSize?this.adjustedTextMaxSize:this.adjustedTextSize,c=this.tilePixelRatio*o,h=this.tilePixelRatio*u/a,f=this.tilePixelRatio*this.adjustedIconSize,d=this.tilePixelRatio*i[\"symbol-spacing\"],g=i[\"symbol-avoid-edges\"],m=i[\"text-padding\"]*this.tilePixelRatio,v=i[\"icon-padding\"]*this.tilePixelRatio,y=i[\"text-max-angle\"]/180*Math.PI,x=\"map\"===i[\"text-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],b=\"map\"===i[\"icon-rotation-alignment\"]&&\"line\"===i[\"symbol-placement\"],_=i[\"text-allow-overlap\"]||i[\"icon-allow-overlap\"]||i[\"text-ignore-placement\"]||i[\"icon-ignore-placement\"],M=\"line\"===i[\"symbol-placement\"],A=d/2;M&&(t=p(t,0,0,w,w));for(var k=0;k<t.length;k++){var T,E=t[k];T=M?l(E,d,y,e,r,a,h,this.overscaling,w):[new s(E[0].x,E[0].y,0)];for(var S=0,L=T.length;S<L;S++){var z=T[S];if(!(e&&M&&this.anchorIsTooClose(e.text,A,z))){var C=!(z.x<0||z.x>w||z.y<0||z.y>w);if(!g||C){var I=C||_;this.addSymbolInstance(z,E,e,r,this.layer,I,this.symbolInstancesArray.length,this.collisionBoxArray,n.index,this.sourceLayerIndex,this.index,c,m,x,f,v,b,{zoom:this.zoom},n.properties)}}}}},n.prototype.anchorIsTooClose=function(t,e,r){var n=this.compareText;if(t in n){for(var i=n[t],a=i.length-1;a>=0;a--)if(r.dist(i[a])<e)return!0}else n[t]=[];return n[t].push(r),!1},n.prototype.placeFeatures=function(t,e){this.recalculateStyleLayers(),this.createArrays();var r=this.layer.layout,n=t.maxScale,i=\"map\"===r[\"text-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"],a=\"map\"===r[\"icon-rotation-alignment\"]&&\"line\"===r[\"symbol-placement\"],o=r[\"text-allow-overlap\"]||r[\"icon-allow-overlap\"]||r[\"text-ignore-placement\"]||r[\"icon-ignore-placement\"];if(o){var s=this.symbolInstancesArray.toArray(this.symbolInstancesStartIndex,this.symbolInstancesEndIndex),l=t.angle,u=Math.sin(l),c=Math.cos(l);this.sortedSymbolInstances=s.sort(function(t,e){var r=u*t.anchorPointX+c*t.anchorPointY|0,n=u*e.anchorPointX+c*e.anchorPointY|0;return r-n||e.index-t.index})}for(var h=this.symbolInstancesStartIndex;h<this.symbolInstancesEndIndex;h++){var f=this.sortedSymbolInstances?this.sortedSymbolInstances[h-this.symbolInstancesStartIndex]:this.symbolInstancesArray.get(h),d={boxStartIndex:f.textBoxStartIndex,boxEndIndex:f.textBoxEndIndex},p={boxStartIndex:f.iconBoxStartIndex,boxEndIndex:f.iconBoxEndIndex},g=!(f.textBoxStartIndex===f.textBoxEndIndex),m=!(f.iconBoxStartIndex===f.iconBoxEndIndex),v=r[\"text-optional\"]||!g,y=r[\"icon-optional\"]||!m,x=g?t.placeCollisionFeature(d,r[\"text-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale,b=m?t.placeCollisionFeature(p,r[\"icon-allow-overlap\"],r[\"symbol-avoid-edges\"]):t.minScale;v||y?!y&&x?x=Math.max(b,x):!v&&b&&(b=Math.max(b,x)):b=x=Math.max(b,x),g&&(t.insertCollisionFeature(d,x,r[\"text-ignore-placement\"]),x<=n&&this.addSymbols(\"glyph\",f.glyphQuadStartIndex,f.glyphQuadEndIndex,x,r[\"text-keep-upright\"],i,t.angle)),m&&(t.insertCollisionFeature(p,b,r[\"icon-ignore-placement\"]),b<=n&&this.addSymbols(\"icon\",f.iconQuadStartIndex,f.iconQuadEndIndex,b,r[\"icon-keep-upright\"],a,t.angle))}e&&this.addToDebugBuffers(t)},n.prototype.addSymbols=function(t,e,r,n,a,o,s){for(var l=this.prepareArrayGroup(t,4*(r-e)),u=l.elementArray,c=l.layoutVertexArray,h=this.zoom,f=Math.max(Math.log(n)/Math.LN2+h,0),d=e;d<r;d++){var p=this.symbolQuadsArray.get(d).SymbolQuad,g=(p.anchorAngle+s+Math.PI)%(2*Math.PI);if(!(a&&o&&(g<=Math.PI/2||g>3*Math.PI/2))){var m=p.tl,v=p.tr,y=p.bl,x=p.br,b=p.tex,_=p.anchorPoint,w=Math.max(h+Math.log(p.minScale)/Math.LN2,f),M=Math.min(h+Math.log(p.maxScale)/Math.LN2,25);if(!(M<=w)){w===f&&(w=0);var A=Math.round(p.glyphAngle/(2*Math.PI)*256),k=i(c,_.x,_.y,m.x,m.y,b.x,b.y,w,M,f,A);i(c,_.x,_.y,v.x,v.y,b.x+b.w,b.y,w,M,f,A),i(c,_.x,_.y,y.x,y.y,b.x,b.y+b.h,w,M,f,A),i(c,_.x,_.y,x.x,x.y,b.x+b.w,b.y+b.h,w,M,f,A),u.emplaceBack(k,k+1,k+2),u.emplaceBack(k+1,k+2,k+3)}}}},n.prototype.updateIcons=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"icon-image\"];if(e)for(var r=0;r<this.features.length;r++){var n=u(this.features[r].properties,e);n&&(t[n]=!0)}},n.prototype.updateFont=function(t){this.recalculateStyleLayers();var e=this.layer.layout[\"text-font\"],r=t[e]=t[e]||{};this.textFeatures=f(this.features,this.layer.layout,r)},n.prototype.addToDebugBuffers=function(t){for(var e=this.prepareArrayGroup(\"collisionBox\",0),r=e.layoutVertexArray,n=-t.angle,i=t.yStretch,o=this.symbolInstancesStartIndex;o<this.symbolInstancesEndIndex;o++){var s=this.symbolInstancesArray.get(o);s.textCollisionFeature={boxStartIndex:s.textBoxStartIndex,boxEndIndex:s.textBoxEndIndex},s.iconCollisionFeature={boxStartIndex:s.iconBoxStartIndex,boxEndIndex:s.iconBoxEndIndex};for(var l=0;l<2;l++){var u=s[0===l?\"textCollisionFeature\":\"iconCollisionFeature\"];if(u)for(var c=u.boxStartIndex;c<u.boxEndIndex;c++){var h=this.collisionBoxArray.get(c),f=h.anchorPoint,d=new a(h.x1,h.y1*i)._rotate(n),p=new a(h.x2,h.y1*i)._rotate(n),g=new a(h.x1,h.y2*i)._rotate(n),m=new a(h.x2,h.y2*i)._rotate(n),v=Math.max(0,Math.min(25,this.zoom+Math.log(h.maxScale)/Math.LN2)),y=Math.max(0,Math.min(25,this.zoom+Math.log(h.placementScale)/Math.LN2));this.addCollisionBoxVertex(r,f,d,v,y),this.addCollisionBoxVertex(r,f,p,v,y),this.addCollisionBoxVertex(r,f,p,v,y),this.addCollisionBoxVertex(r,f,m,v,y),this.addCollisionBoxVertex(r,f,m,v,y),this.addCollisionBoxVertex(r,f,g,v,y),this.addCollisionBoxVertex(r,f,g,v,y),this.addCollisionBoxVertex(r,f,d,v,y)}}}},n.prototype.addSymbolInstance=function(t,e,r,i,a,o,s,l,u,c,h,f,d,p,m,y,x,w,M){var A,k,T,E,S,L,z,C;if(r&&(z=o?b(t,r,f,e,a,p):[],S=new v(l,e,t,u,c,h,r,f,d,p,!1)),A=this.symbolQuadsArray.length,z&&z.length)for(var I=0;I<z.length;I++)this.addSymbolQuad(z[I]);k=this.symbolQuadsArray.length;var P=S?S.boxStartIndex:this.collisionBoxArray.length,D=S?S.boxEndIndex:this.collisionBoxArray.length;i&&(C=o?_(t,i,m,e,a,x,r,w,M):[],L=new v(l,e,t,u,c,h,i,m,y,x,!0)),T=this.symbolQuadsArray.length,C&&1===C.length&&this.addSymbolQuad(C[0]),E=this.symbolQuadsArray.length;var R=L?L.boxStartIndex:this.collisionBoxArray.length,O=L?L.boxEndIndex:this.collisionBoxArray.length;return E>n.MAX_QUADS&&g.warnOnce(\"Too many symbols being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),k>n.MAX_QUADS&&g.warnOnce(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),this.symbolInstancesArray.emplaceBack(P,D,R,O,A,k,T,E,t.x,t.y,s)},n.prototype.addSymbolQuad=function(t){return this.symbolQuadsArray.emplaceBack(t.anchorPoint.x,t.anchorPoint.y,t.tl.x,t.tl.y,t.tr.x,t.tr.y,t.bl.x,t.bl.y,t.br.x,t.br.y,t.tex.h,t.tex.w,t.tex.x,t.tex.y,t.anchorAngle,t.glyphAngle,t.maxScale,t.minScale)}},{\"../../symbol/anchor\":352,\"../../symbol/clip_line\":354,\"../../symbol/collision_feature\":356,\"../../symbol/get_anchors\":358,\"../../symbol/mergelines\":361,\"../../symbol/quads\":362,\"../../symbol/resolve_text\":363,\"../../symbol/shaping\":364,\"../../util/token\":402,\"../../util/util\":403,\"../bucket\":290,\"../load_geometry\":298,\"point-geometry\":442}],295:[function(t,e,r){\"use strict\";function n(t,e,r){this.arrayBuffer=t.arrayBuffer,\n",
+       "this.length=t.length,this.attributes=e.members,this.itemSize=e.bytesPerElement,this.type=r,this.arrayType=e}e.exports=n,n.prototype.bind=function(t){var e=t[this.type];this.buffer?t.bindBuffer(e,this.buffer):(this.buffer=t.createBuffer(),t.bindBuffer(e,this.buffer),t.bufferData(e,this.arrayBuffer,t.STATIC_DRAW),this.arrayBuffer=null)};var i={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\"};n.prototype.setVertexAttribPointers=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=this.attributes[r],a=e[n.name];void 0!==a&&t.vertexAttribPointer(a,n.components,t[i[n.type]],!1,this.arrayType.bytesPerElement,n.offset)}},n.prototype.destroy=function(t){this.buffer&&t.deleteBuffer(this.buffer)},n.BufferType={VERTEX:\"ARRAY_BUFFER\",ELEMENT:\"ELEMENT_ARRAY_BUFFER\"}},{}],296:[function(t,e,r){\"use strict\";function n(t,e){this.layoutVertexBuffer=new a(t.layoutVertexArray,e.layoutVertexArrayType,a.BufferType.VERTEX),t.elementArray&&(this.elementBuffer=new a(t.elementArray,e.elementArrayType,a.BufferType.ELEMENT));var r,n=this.vaos={};t.elementArray2&&(this.elementBuffer2=new a(t.elementArray2,e.elementArrayType2,a.BufferType.ELEMENT),r=this.secondVaos={}),this.paintVertexBuffers=i.mapObject(t.paintVertexArrays,function(i,s){return n[s]=new o,t.elementArray2&&(r[s]=new o),new a(i,e.paintVertexArrayTypes[s],a.BufferType.VERTEX)})}var i=t(\"../util/util\"),a=t(\"./buffer\"),o=t(\"../render/vertex_array_object\");e.exports=n,n.prototype.destroy=function(t){this.layoutVertexBuffer.destroy(t),this.elementBuffer&&this.elementBuffer.destroy(t),this.elementBuffer2&&this.elementBuffer2.destroy(t);for(var e in this.paintVertexBuffers)this.paintVertexBuffers[e].destroy(t);for(var r in this.vaos)this.vaos[r].destroy(t);for(var n in this.secondVaos)this.secondVaos[n].destroy(t)}},{\"../render/vertex_array_object\":318,\"../util/util\":403,\"./buffer\":295}],297:[function(t,e,r){\"use strict\";function n(t,e,r){if(t.grid){var n=t,i=e;t=n.coord,e=n.overscaling,this.grid=new p(n.grid),this.featureIndexArray=new A(n.featureIndexArray),this.rawTileData=i,this.bucketLayerIDs=n.bucketLayerIDs}else this.grid=new p(h,16,0),this.featureIndexArray=new A;this.coord=t,this.overscaling=e,this.x=t.x,this.y=t.y,this.z=t.z-Math.log(e)/Math.LN2,this.setCollisionTile(r)}function i(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function a(t,e){return e-t}function o(t){return t[\"line-gap-width\"]>0?t[\"line-gap-width\"]+2*t[\"line-width\"]:t[\"line-width\"]}function s(t,e,r,n,i){if(!e[0]&&!e[1])return t;e=u.convert(e),\"viewport\"===r&&e._rotate(-n);for(var a=[],o=0;o<t.length;o++){for(var s=t[o],l=[],c=0;c<s.length;c++)l.push(s[c].sub(e._mult(i)));a.push(l)}return a}function l(t,e){for(var r=[],n=new u(0,0),i=0;i<t.length;i++){for(var a=t[i],o=[],s=0;s<a.length;s++){var l=a[s-1],c=a[s],h=a[s+1],f=0===s?n:c.sub(l)._unit()._perp(),d=s===a.length-1?n:h.sub(c)._unit()._perp(),p=f._add(d)._unit(),g=p.x*d.x+p.y*d.y;p._mult(1/g),o.push(p._mult(e)._add(c))}r.push(o)}return r}var u=t(\"point-geometry\"),c=t(\"./load_geometry\"),h=t(\"./bucket\").EXTENT,f=t(\"feature-filter\"),d=t(\"../util/struct_array\"),p=t(\"grid-index\"),g=t(\"../util/dictionary_coder\"),m=t(\"vector-tile\"),v=t(\"pbf\"),y=t(\"../util/vectortile_to_geojson\"),x=t(\"../util/util\").arraysIntersect,b=t(\"../util/intersection_tests\"),_=b.multiPolygonIntersectsBufferedMultiPoint,w=b.multiPolygonIntersectsMultiPolygon,M=b.multiPolygonIntersectsBufferedMultiLine,A=new d({members:[{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"}]});e.exports=n,n.prototype.insert=function(t,e,r,n){var i=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(e,r,n);for(var a=c(t),o=0;o<a.length;o++){for(var s=a[o],l=[1/0,1/0,-(1/0),-(1/0)],u=0;u<s.length;u++){var h=s[u];l[0]=Math.min(l[0],h.x),l[1]=Math.min(l[1],h.y),l[2]=Math.max(l[2],h.x),l[3]=Math.max(l[3],h.y)}this.grid.insert(i,l[0],l[1],l[2],l[3])}},n.prototype.setCollisionTile=function(t){this.collisionTile=t},n.prototype.serialize=function(){var t={coord:this.coord,overscaling:this.overscaling,grid:this.grid.toArrayBuffer(),featureIndexArray:this.featureIndexArray.serialize(),bucketLayerIDs:this.bucketLayerIDs};return{data:t,transferables:[t.grid,t.featureIndexArray.arrayBuffer]}},n.prototype.query=function(t,e){this.vtLayers||(this.vtLayers=new m.VectorTile(new v(new Uint8Array(this.rawTileData))).layers,this.sourceLayerCoder=new g(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"]));var r={},n=t.params||{},s=h/t.tileSize/t.scale,l=f(n.filter),c=0;for(var d in e){var p=e[d],y=p.paint,x=0;\"line\"===p.type?x=o(y)/2+Math.abs(y[\"line-offset\"])+i(y[\"line-translate\"]):\"fill\"===p.type?x=i(y[\"fill-translate\"]):\"circle\"===p.type&&(x=y[\"circle-radius\"]+i(y[\"circle-translate\"])),c=Math.max(c,x*s)}for(var b=t.queryGeometry.map(function(t){return t.map(function(t){return new u(t.x,t.y)})}),_=1/0,w=1/0,M=-(1/0),A=-(1/0),k=0;k<b.length;k++)for(var T=b[k],E=0;E<T.length;E++){var S=T[E];_=Math.min(_,S.x),w=Math.min(w,S.y),M=Math.max(M,S.x),A=Math.max(A,S.y)}var L=this.grid.query(_-c,w-c,M+c,A+c);L.sort(a),this.filterMatching(r,L,this.featureIndexArray,b,l,n.layers,e,t.bearing,s);var z=this.collisionTile.queryRenderedSymbols(_,w,M,A,t.scale);return z.sort(),this.filterMatching(r,z,this.collisionTile.collisionBoxArray,b,l,n.layers,e,t.bearing,s),r},n.prototype.filterMatching=function(t,e,r,n,i,a,u,h,f){for(var d,p=0;p<e.length;p++){var g=e[p];if(g!==d){d=g;var m=r.get(g),v=this.bucketLayerIDs[m.bucketIndex];if(!a||x(a,v)){var b=this.sourceLayerCoder.decode(m.sourceLayerIndex),A=this.vtLayers[b],k=A.feature(m.featureIndex);if(i(k))for(var T=null,E=0;E<v.length;E++){var S=v[E];if(!(a&&a.indexOf(S)<0)){var L=u[S];if(L){var z;if(\"symbol\"!==L.type){T||(T=c(k));var C=L.paint;if(\"line\"===L.type){z=s(n,C[\"line-translate\"],C[\"line-translate-anchor\"],h,f);var I=o(C)/2*f;if(C[\"line-offset\"]&&(T=l(T,C[\"line-offset\"]*f)),!M(z,T,I))continue}else if(\"fill\"===L.type){if(z=s(n,C[\"fill-translate\"],C[\"fill-translate-anchor\"],h,f),!w(z,T))continue}else if(\"circle\"===L.type){z=s(n,C[\"circle-translate\"],C[\"circle-translate-anchor\"],h,f);var P=C[\"circle-radius\"]*f;if(!_(z,T,P))continue}}var D=new y(k,this.z,this.x,this.y);D.layer=L.serialize({includeRefProperties:!0});var R=t[S];void 0===R&&(R=t[S]=[]),R.push(D)}}}}}}}},{\"../util/dictionary_coder\":393,\"../util/intersection_tests\":398,\"../util/struct_array\":401,\"../util/util\":403,\"../util/vectortile_to_geojson\":404,\"./bucket\":290,\"./load_geometry\":298,\"feature-filter\":105,\"grid-index\":252,pbf:436,\"point-geometry\":442,\"vector-tile\":505}],298:[function(t,e,r){\"use strict\";function n(t){return{min:-1*Math.pow(2,t-1),max:Math.pow(2,t-1)-1}}var i=t(\"../util/util\"),a=t(\"./bucket\").EXTENT,o=t(\"assert\"),s={15:n(15),16:n(16)};e.exports=function(t,e){var r=s[e||16];o(r);for(var n=a/t.extent,l=t.loadGeometry(),u=0;u<l.length;u++)for(var c=l[u],h=0;h<c.length;h++){var f=c[h];f.x=Math.round(f.x*n),f.y=Math.round(f.y*n),(f.x<r.min||f.x>r.max||f.y<r.min||f.y>r.max)&&i.warnOnce(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\")}return l}},{\"../util/util\":403,\"./bucket\":290,assert:34}],299:[function(t,e,r){\"use strict\";function n(t,e,r){this.column=t,this.row=e,this.zoom=r}e.exports=n,n.prototype={clone:function(){return new n(this.column,this.row,this.zoom)},zoomTo:function(t){return this.clone()._zoomTo(t)},sub:function(t){return this.clone()._sub(t)},_zoomTo:function(t){var e=Math.pow(2,t-this.zoom);return this.column*=e,this.row*=e,this.zoom=t,this},_sub:function(t){return t=t.zoomTo(this.zoom),this.column-=t.column,this.row-=t.row,this}}},{}],300:[function(t,e,r){\"use strict\";function n(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")}e.exports=n;var i=t(\"../util/util\").wrap;n.prototype.wrap=function(){return new n(i(this.lng,-180,180),this.lat)},n.prototype.toArray=function(){return[this.lng,this.lat]},n.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},n.convert=function(t){return t instanceof n?t:Array.isArray(t)?new n(t[0],t[1]):t}},{\"../util/util\":403}],301:[function(t,e,r){\"use strict\";function n(t,e){t&&(e?this.extend(t).extend(e):4===t.length?this.extend([t[0],t[1]]).extend([t[2],t[3]]):this.extend(t[0]).extend(t[1]))}e.exports=n;var i=t(\"./lng_lat\");n.prototype={extend:function(t){var e,r,a=this._sw,o=this._ne;if(t instanceof i)e=t,r=t;else{if(!(t instanceof n))return t?this.extend(i.convert(t)||n.convert(t)):this;if(e=t._sw,r=t._ne,!e||!r)return this}return a||o?(a.lng=Math.min(e.lng,a.lng),a.lat=Math.min(e.lat,a.lat),o.lng=Math.max(r.lng,o.lng),o.lat=Math.max(r.lat,o.lat)):(this._sw=new i(e.lng,e.lat),this._ne=new i(r.lng,r.lat)),this},getCenter:function(){return new i((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},getSouthWest:function(){return this._sw},getNorthEast:function(){return this._ne},getNorthWest:function(){return new i(this.getWest(),this.getNorth())},getSouthEast:function(){return new i(this.getEast(),this.getSouth())},getWest:function(){return this._sw.lng},getSouth:function(){return this._sw.lat},getEast:function(){return this._ne.lng},getNorth:function(){return this._ne.lat},toArray:function(){return[this._sw.toArray(),this._ne.toArray()]},toString:function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"}},n.convert=function(t){return!t||t instanceof n?t:new n(t)}},{\"./lng_lat\":300}],302:[function(t,e,r){\"use strict\";function n(t,e){this.tileSize=512,this._minZoom=t||0,this._maxZoom=e||22,this.latRange=[-85.05113,85.05113],this.width=0,this.height=0,this._center=new i(0,0),this.zoom=0,this.angle=0,this._altitude=1.5,this._pitch=0,this._unmodified=!0}var i=t(\"./lng_lat\"),a=t(\"point-geometry\"),o=t(\"./coordinate\"),s=t(\"../util/util\").wrap,l=t(\"../util/interpolate\"),u=t(\"../source/tile_coord\"),c=t(\"../data/bucket\").EXTENT,h=t(\"gl-matrix\"),f=h.vec4,d=h.mat4,p=h.mat2;e.exports=n,n.prototype={get minZoom(){return this._minZoom},set minZoom(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},get maxZoom(){return this._maxZoom},set maxZoom(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},get worldSize(){return this.tileSize*this.scale},get centerPoint(){return this.size._div(2)},get size(){return new a(this.width,this.height)},get bearing(){return-this.angle/Math.PI*180},set bearing(t){var e=-s(t,-180,180)*Math.PI/180;this.angle!==e&&(this._unmodified=!1,this.angle=e,this._calcMatrices(),this.rotationMatrix=p.create(),p.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},get pitch(){return this._pitch/Math.PI*180},set pitch(t){var e=Math.min(60,t)/180*Math.PI;this._pitch!==e&&(this._unmodified=!1,this._pitch=e,this._calcMatrices())},get altitude(){return this._altitude},set altitude(t){var e=Math.max(.75,t);this._altitude!==e&&(this._unmodified=!1,this._altitude=e,this._calcMatrices())},get zoom(){return this._zoom},set zoom(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._calcMatrices(),this._constrain())},get center(){return this._center},set center(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._calcMatrices(),this._constrain())},coveringZoomLevel:function(t){return(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize))},coveringTiles:function(t){var e=this.coveringZoomLevel(t),r=e;if(e<t.minzoom)return[];e>t.maxzoom&&(e=t.maxzoom);var n=this,i=n.locationCoordinate(n.center)._zoomTo(e),o=new a(i.column-.5,i.row-.5);return u.cover(e,[n.pointCoordinate(new a(0,0))._zoomTo(e),n.pointCoordinate(new a(n.width,0))._zoomTo(e),n.pointCoordinate(new a(n.width,n.height))._zoomTo(e),n.pointCoordinate(new a(0,n.height))._zoomTo(e)],t.reparseOverscaled?r:e).sort(function(t,e){return o.dist(t)-o.dist(e)})},resize:function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._calcMatrices(),this._constrain()},get unmodified(){return this._unmodified},zoomScale:function(t){return Math.pow(2,t)},scaleZoom:function(t){return Math.log(t)/Math.LN2},project:function(t,e){return new a(this.lngX(t.lng,e),this.latY(t.lat,e))},unproject:function(t,e){return new i(this.xLng(t.x,e),this.yLat(t.y,e))},get x(){return this.lngX(this.center.lng)},get y(){return this.latY(this.center.lat)},get point(){return new a(this.x,this.y)},lngX:function(t,e){return(180+t)*(e||this.worldSize)/360},latY:function(t,e){var r=180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360));return(180-r)*(e||this.worldSize)/360},xLng:function(t,e){return 360*t/(e||this.worldSize)-180},yLat:function(t,e){var r=180-360*t/(e||this.worldSize);return 360/Math.PI*Math.atan(Math.exp(r*Math.PI/180))-90},panBy:function(t){var e=this.centerPoint._add(t);this.center=this.pointLocation(e)},setLocationAtPoint:function(t,e){var r=this.locationCoordinate(t),n=this.pointCoordinate(e),i=this.pointCoordinate(this.centerPoint),a=n._sub(r);this._unmodified=!1,this.center=this.coordinateLocation(i._sub(a))},locationPoint:function(t){return this.coordinatePoint(this.locationCoordinate(t))},pointLocation:function(t){return this.coordinateLocation(this.pointCoordinate(t))},locationCoordinate:function(t){var e=this.zoomScale(this.tileZoom)/this.worldSize,r=i.convert(t);return new o(this.lngX(r.lng)*e,this.latY(r.lat)*e,this.tileZoom)},coordinateLocation:function(t){var e=this.zoomScale(t.zoom);return new i(this.xLng(t.column,e),this.yLat(t.row,e))},pointCoordinate:function(t){var e=0,r=[t.x,t.y,0,1],n=[t.x,t.y,1,1];f.transformMat4(r,r,this.pixelMatrixInverse),f.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],s=r[0]/i,u=n[0]/a,c=r[1]/i,h=n[1]/a,d=r[2]/i,p=n[2]/a,g=d===p?0:(e-d)/(p-d),m=this.worldSize/this.zoomScale(this.tileZoom);return new o(l(s,u,g)/m,l(c,h,g)/m,this.tileZoom)},coordinatePoint:function(t){var e=this.worldSize/this.zoomScale(t.zoom),r=[t.column*e,t.row*e,0,1];return f.transformMat4(r,r,this.pixelMatrix),new a(r[0]/r[3],r[1]/r[3])},calculatePosMatrix:function(t,e){void 0===e&&(e=1/0),t instanceof u&&(t=t.toCoordinate(e));var r=Math.min(t.zoom,e),n=this.worldSize/Math.pow(2,r),i=new Float64Array(16);return d.identity(i),d.translate(i,i,[t.column*n,t.row*n,0]),d.scale(i,i,[n/c,n/c,1]),d.multiply(i,this.projMatrix,i),new Float32Array(i)},_constrain:function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var t,e,r,n,i,o,s,l,u=this.size,c=this._unmodified;this.latRange&&(t=this.latY(this.latRange[1]),e=this.latY(this.latRange[0]),i=e-t<u.y?u.y/(e-t):0),this.lngRange&&(r=this.lngX(this.lngRange[0]),n=this.lngX(this.lngRange[1]),o=n-r<u.x?u.x/(n-r):0);var h=Math.max(o||0,i||0);if(h)return this.center=this.unproject(new a(o?(n+r)/2:this.x,i?(e+t)/2:this.y)),this.zoom+=this.scaleZoom(h),this._unmodified=c,void(this._constraining=!1);if(this.latRange){var f=this.y,d=u.y/2;f-d<t&&(l=t+d),f+d>e&&(l=e-d)}if(this.lngRange){var p=this.x,g=u.x/2;p-g<r&&(s=r+g),p+g>n&&(s=n-g)}void 0===s&&void 0===l||(this.center=this.unproject(new a(void 0!==s?s:this.x,void 0!==l?l:this.y))),this._unmodified=c,this._constraining=!1}},_calcMatrices:function(){if(this.height){var t=Math.atan(.5/this.altitude),e=Math.sin(t)*this.altitude/Math.sin(Math.PI/2-this._pitch-t),r=Math.cos(Math.PI/2-this._pitch)*e+this.altitude,n=new Float64Array(16);if(d.perspective(n,2*Math.atan(this.height/2/this.altitude),this.width/this.height,.1,r),d.translate(n,n,[0,0,-this.altitude]),d.scale(n,n,[1,-1,1/this.height]),d.rotateX(n,n,this._pitch),d.rotateZ(n,n,this.angle),d.translate(n,n,[-this.x,-this.y,0]),this.projMatrix=n,n=d.create(),d.scale(n,n,[this.width/2,-this.height/2,1]),d.translate(n,n,[1,-1,0]),this.pixelMatrix=d.multiply(new Float64Array(16),n,this.projMatrix),n=d.invert(new Float64Array(16),this.pixelMatrix),!n)throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=n}}}},{\"../data/bucket\":290,\"../source/tile_coord\":330,\"../util/interpolate\":397,\"../util/util\":403,\"./coordinate\":299,\"./lng_lat\":300,\"gl-matrix\":161,\"point-geometry\":442}],303:[function(t,e,r){\"use strict\";var n={\" \":[16,[]],\"!\":[10,[5,21,5,7,-1,-1,5,2,4,1,5,0,6,1,5,2]],'\"':[16,[4,21,4,14,-1,-1,12,21,12,14]],\"#\":[21,[11,25,4,-7,-1,-1,17,25,10,-7,-1,-1,4,12,18,12,-1,-1,3,6,17,6]],$:[20,[8,25,8,-4,-1,-1,12,25,12,-4,-1,-1,17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],\"%\":[24,[21,21,3,0,-1,-1,8,21,10,19,10,17,9,15,7,14,5,14,3,16,3,18,4,20,6,21,8,21,10,20,13,19,16,19,19,20,21,21,-1,-1,17,7,15,6,14,4,14,2,16,0,18,0,20,1,21,3,21,5,19,7,17,7]],\"&\":[26,[23,12,23,13,22,14,21,14,20,13,19,11,17,6,15,3,13,1,11,0,7,0,5,1,4,2,3,4,3,6,4,8,5,9,12,13,13,14,14,16,14,18,13,20,11,21,9,20,8,18,8,16,9,13,11,10,16,3,18,1,20,0,22,0,23,1,23,2]],\"'\":[10,[5,19,4,20,5,21,6,20,6,18,5,16,4,15]],\"(\":[14,[11,25,9,23,7,20,5,16,4,11,4,7,5,2,7,-2,9,-5,11,-7]],\")\":[14,[3,25,5,23,7,20,9,16,10,11,10,7,9,2,7,-2,5,-5,3,-7]],\"*\":[16,[8,21,8,9,-1,-1,3,18,13,12,-1,-1,13,18,3,12]],\"+\":[26,[13,18,13,0,-1,-1,4,9,22,9]],\",\":[10,[6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"-\":[26,[4,9,22,9]],\".\":[10,[5,2,4,1,5,0,6,1,5,2]],\"/\":[22,[20,25,2,-7]],0:[20,[9,21,6,20,4,17,3,12,3,9,4,4,6,1,9,0,11,0,14,1,16,4,17,9,17,12,16,17,14,20,11,21,9,21]],1:[20,[6,17,8,18,11,21,11,0]],2:[20,[4,16,4,17,5,19,6,20,8,21,12,21,14,20,15,19,16,17,16,15,15,13,13,10,3,0,17,0]],3:[20,[5,21,16,21,10,13,13,13,15,12,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],4:[20,[13,21,3,7,18,7,-1,-1,13,21,13,0]],5:[20,[15,21,5,21,4,12,5,13,8,14,11,14,14,13,16,11,17,8,17,6,16,3,14,1,11,0,8,0,5,1,4,2,3,4]],6:[20,[16,18,15,20,12,21,10,21,7,20,5,17,4,12,4,7,5,3,7,1,10,0,11,0,14,1,16,3,17,6,17,7,16,10,14,12,11,13,10,13,7,12,5,10,4,7]],7:[20,[17,21,7,0,-1,-1,3,21,17,21]],8:[20,[8,21,5,20,4,18,4,16,5,14,7,13,11,12,14,11,16,9,17,7,17,4,16,2,15,1,12,0,8,0,5,1,4,2,3,4,3,7,4,9,6,11,9,12,13,13,15,14,16,16,16,18,15,20,12,21,8,21]],9:[20,[16,14,15,11,13,9,10,8,9,8,6,9,4,11,3,14,3,15,4,18,6,20,9,21,10,21,13,20,15,18,16,14,16,9,15,4,13,1,10,0,8,0,5,1,4,3]],\":\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,5,2,4,1,5,0,6,1,5,2]],\";\":[10,[5,14,4,13,5,12,6,13,5,14,-1,-1,6,1,5,0,4,1,5,2,6,1,6,-1,5,-3,4,-4]],\"<\":[24,[20,18,4,9,20,0]],\"=\":[26,[4,12,22,12,-1,-1,4,6,22,6]],\">\":[24,[4,18,20,9,4,0]],\"?\":[18,[3,16,3,17,4,19,5,20,7,21,11,21,13,20,14,19,15,17,15,15,14,13,13,12,9,10,9,7,-1,-1,9,2,8,1,9,0,10,1,9,2]],\"@\":[27,[18,13,17,15,15,16,12,16,10,15,9,14,8,11,8,8,9,6,11,5,14,5,16,6,17,8,-1,-1,12,16,10,14,9,11,9,8,10,6,11,5,-1,-1,18,16,17,8,17,6,19,5,21,5,23,7,24,10,24,12,23,15,22,17,20,19,18,20,15,21,12,21,9,20,7,19,5,17,4,15,3,12,3,9,4,6,5,4,7,2,9,1,12,0,15,0,18,1,20,2,21,3,-1,-1,19,16,18,8,18,6,19,5]],A:[18,[9,21,1,0,-1,-1,9,21,17,0,-1,-1,4,7,14,7]],B:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,-1,-1,4,11,13,11,16,10,17,9,18,7,18,4,17,2,16,1,13,0,4,0]],C:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5]],D:[21,[4,21,4,0,-1,-1,4,21,11,21,14,20,16,18,17,16,18,13,18,8,17,5,16,3,14,1,11,0,4,0]],E:[19,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11,-1,-1,4,0,17,0]],F:[18,[4,21,4,0,-1,-1,4,21,17,21,-1,-1,4,11,12,11]],G:[21,[18,16,17,18,15,20,13,21,9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,18,8,-1,-1,13,8,18,8]],H:[22,[4,21,4,0,-1,-1,18,21,18,0,-1,-1,4,11,18,11]],I:[8,[4,21,4,0]],J:[16,[12,21,12,5,11,2,10,1,8,0,6,0,4,1,3,2,2,5,2,7]],K:[21,[4,21,4,0,-1,-1,18,21,4,7,-1,-1,9,12,18,0]],L:[17,[4,21,4,0,-1,-1,4,0,16,0]],M:[24,[4,21,4,0,-1,-1,4,21,12,0,-1,-1,20,21,12,0,-1,-1,20,21,20,0]],N:[22,[4,21,4,0,-1,-1,4,21,18,0,-1,-1,18,21,18,0]],O:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21]],P:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,14,17,12,16,11,13,10,4,10]],Q:[22,[9,21,7,20,5,18,4,16,3,13,3,8,4,5,5,3,7,1,9,0,13,0,15,1,17,3,18,5,19,8,19,13,18,16,17,18,15,20,13,21,9,21,-1,-1,12,4,18,-2]],R:[21,[4,21,4,0,-1,-1,4,21,13,21,16,20,17,19,18,17,18,15,17,13,16,12,13,11,4,11,-1,-1,11,11,18,0]],S:[20,[17,18,15,20,12,21,8,21,5,20,3,18,3,16,4,14,5,13,7,12,13,10,15,9,16,8,17,6,17,3,15,1,12,0,8,0,5,1,3,3]],T:[16,[8,21,8,0,-1,-1,1,21,15,21]],U:[22,[4,21,4,6,5,3,7,1,10,0,12,0,15,1,17,3,18,6,18,21]],V:[18,[1,21,9,0,-1,-1,17,21,9,0]],W:[24,[2,21,7,0,-1,-1,12,21,7,0,-1,-1,12,21,17,0,-1,-1,22,21,17,0]],X:[20,[3,21,17,0,-1,-1,17,21,3,0]],Y:[18,[1,21,9,11,9,0,-1,-1,17,21,9,11]],Z:[20,[17,21,3,0,-1,-1,3,21,17,21,-1,-1,3,0,17,0]],\"[\":[14,[4,25,4,-7,-1,-1,5,25,5,-7,-1,-1,4,25,11,25,-1,-1,4,-7,11,-7]],\"\\\\\":[14,[0,21,14,-3]],\"]\":[14,[9,25,9,-7,-1,-1,10,25,10,-7,-1,-1,3,25,10,25,-1,-1,3,-7,10,-7]],\"^\":[16,[6,15,8,18,10,15,-1,-1,3,12,8,17,13,12,-1,-1,8,17,8,0]],_:[16,[0,-2,16,-2]],\"`\":[10,[6,21,5,20,4,18,4,16,5,15,6,16,5,17]],a:[19,[15,14,15,0,-1,-1,15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],b:[19,[4,21,4,0,-1,-1,4,11,6,13,8,14,11,14,13,13,15,11,16,8,16,6,15,3,13,1,11,0,8,0,6,1,4,3]],c:[18,[15,11,13,13,11,14,8,14,6,13,4,11,3,8,3,6,4,3,6,1,8,0,11,0,13,1,15,3]],d:[19,[15,21,15,0,-1,-1,15,11,13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a,o,s,l,u,c,h,f,d=[];for(a=0,o=t.length;a<o;a++)if(u=n[t[a]]){for(f=null,s=0,l=u[1].length;s<l;s+=2)u[1][s]===-1&&u[1][s+1]===-1?f=null:(c=e+u[1][s]*i,h=r-u[1][s+1]*i,f&&d.push(f.x,f.y,c,h),f={x:c,y:h});e+=u[0]*i}return d}},{}],304:[function(t,e,r){\"use strict\";var n=e.exports={};n.version=t(\"../package.json\").version,n.Map=t(\"./ui/map\"),n.Control=t(\"./ui/control/control\"),n.Navigation=t(\"./ui/control/navigation\"),n.Geolocate=t(\"./ui/control/geolocate\"),n.Attribution=t(\"./ui/control/attribution\"),n.Popup=t(\"./ui/popup\"),n.Marker=t(\"./ui/marker\"),n.Style=t(\"./style/style\"),n.LngLat=t(\"./geo/lng_lat\"),n.LngLatBounds=t(\"./geo/lng_lat_bounds\"),n.Point=t(\"point-geometry\"),n.Evented=t(\"./util/evented\"),n.util=t(\"./util/util\"),n.supported=t(\"./util/browser\").supported;var i=t(\"./util/ajax\");n.util.getJSON=i.getJSON,n.util.getArrayBuffer=i.getArrayBuffer;var a=t(\"./util/config\");n.config=a,Object.defineProperty(n,\"accessToken\",{get:function(){return a.ACCESS_TOKEN},set:function(t){a.ACCESS_TOKEN=t}})},{\"../package.json\":405,\"./geo/lng_lat\":300,\"./geo/lng_lat_bounds\":301,\"./style/style\":339,\"./ui/control/attribution\":370,\"./ui/control/control\":371,\"./ui/control/geolocate\":372,\"./ui/control/navigation\":373,\"./ui/map\":382,\"./ui/marker\":383,\"./ui/popup\":384,\"./util/ajax\":386,\"./util/browser\":387,\"./util/config\":392,\"./util/evented\":395,\"./util/util\":403,\"point-geometry\":442}],305:[function(t,e,r){\"use strict\";var n=t(\"assert\");e.exports=function(t){for(var e={define:{},initialize:{}},r=0;r<t.length;r++){var i=t[r];n(\"u_\"===i.name.slice(0,2));var a=\"{precision} \"+(1===i.components?\"float\":\"vec\"+i.components);e.define[i.name.slice(2)]=\"uniform \"+a+\" \"+i.name+\";\\n\",e.initialize[i.name.slice(2)]=a+\" \"+i.name.slice(2)+\" = \"+i.name+\";\\n\"}return e}},{assert:34}],306:[function(t,e,r){\"use strict\";function n(t,e,r){var n,s=t.gl,l=t.transform,u=r.paint[\"background-color\"],c=r.paint[\"background-pattern\"],h=r.paint[\"background-opacity\"],f=c?t.spriteAtlas.getPosition(c.from,!0):null,d=c?t.spriteAtlas.getPosition(c.to,!0):null;if(t.setDepthSublayer(0),f&&d){if(t.isOpaquePass)return;n=t.useProgram(\"pattern\"),s.uniform1i(n.u_image,0),s.uniform2fv(n.u_pattern_tl_a,f.tl),s.uniform2fv(n.u_pattern_br_a,f.br),s.uniform2fv(n.u_pattern_tl_b,d.tl),s.uniform2fv(n.u_pattern_br_b,d.br),s.uniform1f(n.u_opacity,h),s.uniform1f(n.u_mix,c.t),s.uniform2fv(n.u_pattern_size_a,f.size),s.uniform2fv(n.u_pattern_size_b,d.size),s.uniform1f(n.u_scale_a,c.fromScale),s.uniform1f(n.u_scale_b,c.toScale),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),t.tileExtentPatternVAO.bind(s,n,t.tileExtentBuffer)}else{if(t.isOpaquePass!==(1===u[3]))return;var p=a([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]);n=t.useProgram(\"fill\",[],p,p),s.uniform4fv(n.u_color,u),s.uniform1f(n.u_opacity,h),t.tileExtentVAO.bind(s,n,t.tileExtentBuffer)}s.disable(s.STENCIL_TEST);for(var g=l.coveringTiles({tileSize:o}),m=0;m<g.length;m++){var v=g[m];if(f&&d){var y={coord:v,tileSize:o};s.uniform1f(n.u_tile_units_to_pixels,1/i(y,1,t.transform.tileZoom));var x=y.tileSize*Math.pow(2,t.transform.tileZoom-y.coord.z),b=x*(y.coord.x+v.w*Math.pow(2,y.coord.z)),_=x*y.coord.y;s.uniform2f(n.u_pixel_coord_upper,b>>16,_>>16),s.uniform2f(n.u_pixel_coord_lower,65535&b,65535&_)}s.uniformMatrix4fv(n.u_matrix,!1,t.transform.calculatePosMatrix(v)),s.drawArrays(s.TRIANGLE_STRIP,0,t.tileExtentBuffer.length)}s.stencilMask(0),s.stencilFunc(s.EQUAL,128,128)}var i=t(\"../source/pixels_to_tile_units\"),a=t(\"./create_uniform_pragmas\"),o=512;e.exports=n},{\"../source/pixels_to_tile_units\":324,\"./create_uniform_pragmas\":305}],307:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;t.setDepthSublayer(0),t.depthMask(!1),a.disable(a.STENCIL_TEST);for(var o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.circle;if(c){var h=u.paintAttributes.circle[r.id],f=t.useProgram(\"circle\",h.defines,h.vertexPragmas,h.fragmentPragmas);\"map\"===r.paint[\"circle-pitch-scale\"]?(a.uniform1i(f.u_scale_with_map,!0),a.uniform2f(f.u_extrude_scale,t.transform.pixelsToGLUnits[0]*t.transform.altitude,t.transform.pixelsToGLUnits[1]*t.transform.altitude)):(a.uniform1i(f.u_scale_with_map,!1),a.uniform2fv(f.u_extrude_scale,t.transform.pixelsToGLUnits)),a.uniform1f(f.u_devicepixelratio,i.devicePixelRatio),a.uniformMatrix4fv(f.u_matrix,!1,t.translatePosMatrix(s.posMatrix,l,r.paint[\"circle-translate\"],r.paint[\"circle-translate-anchor\"])),u.setUniforms(a,\"circle\",f,r,{zoom:t.transform.zoom});for(var d=0;d<c.length;d++){var p=c[d];p.vaos[r.id].bind(a,f,p.layoutVertexBuffer,p.elementBuffer,p.paintVertexBuffers[r.id]),a.drawElements(a.TRIANGLES,3*p.elementBuffer.length,a.UNSIGNED_SHORT,0)}}}}}}var i=t(\"../util/browser\");e.exports=n},{\"../util/browser\":387}],308:[function(t,e,r){\"use strict\";function n(t,e,r,n){var i=t.gl;i.enable(i.STENCIL_TEST);for(var a=t.useProgram(\"collisionbox\"),o=0;o<n.length;o++){var s=n[o],l=e.getTile(s),u=l.getBucket(r);if(u){var c=u.bufferGroups.collisionBox;if(c&&c.length){var h=c[0];0!==h.layoutVertexBuffer.length&&(i.uniformMatrix4fv(a.u_matrix,!1,s.posMatrix),t.enableTileClippingMask(s),t.lineWidth(1),i.uniform1f(a.u_scale,Math.pow(2,t.transform.zoom-l.coord.z)),i.uniform1f(a.u_zoom,10*t.transform.zoom),i.uniform1f(a.u_maxzoom,10*(l.coord.z+1)),h.vaos[r.id].bind(i,a,h.layoutVertexBuffer),i.drawArrays(i.LINES,0,h.layoutVertexBuffer.length))}}}}e.exports=n},{}],309:[function(t,e,r){\"use strict\";function n(t,e,r){if(!t.isOpaquePass&&t.options.debug)for(var n=0;n<r.length;n++)i(t,e,r[n])}function i(t,e,r){var n=t.gl;n.disable(n.STENCIL_TEST),t.lineWidth(1*o.devicePixelRatio);var i=r.posMatrix,h=t.useProgram(\"debug\");n.uniformMatrix4fv(h.u_matrix,!1,i),n.uniform4f(h.u_color,1,0,0,1),t.debugVAO.bind(n,h,t.debugBuffer),n.drawArrays(n.LINE_STRIP,0,t.debugBuffer.length);for(var f=a(r.toString(),50,200,5),d=new t.PosArray,p=0;p<f.length;p+=2)d.emplaceBack(f[p],f[p+1]);var g=new u(d.serialize(),t.PosArray.serialize(),u.BufferType.VERTEX),m=new c;m.bind(n,h,g),n.uniform4f(h.u_color,1,1,1,1);for(var v=e.getTile(r).tileSize,y=l/(Math.pow(2,t.transform.zoom-r.z)*v),x=[[-1,-1],[-1,1],[1,-1],[1,1]],b=0;b<x.length;b++){var _=x[b];n.uniformMatrix4fv(h.u_matrix,!1,s.translate([],i,[y*_[0],y*_[1],0])),n.drawArrays(n.LINES,0,g.length)}n.uniform4f(h.u_color,0,0,0,1),n.uniformMatrix4fv(h.u_matrix,!1,i),n.drawArrays(n.LINES,0,g.length)}var a=t(\"../lib/debugtext\"),o=t(\"../util/browser\"),s=t(\"gl-matrix\").mat4,l=t(\"../data/bucket\").EXTENT,u=t(\"../data/buffer\"),c=t(\"./vertex_array_object\");e.exports=n},{\"../data/bucket\":290,\"../data/buffer\":295,\"../lib/debugtext\":303,\"../util/browser\":387,\"./vertex_array_object\":318,\"gl-matrix\":161}],310:[function(t,e,r){\"use strict\";function n(t,e,r,n){var o=t.gl;o.enable(o.STENCIL_TEST);var s;if(s=!r.paint[\"fill-pattern\"]&&(r.isPaintValueFeatureConstant(\"fill-color\")&&r.isPaintValueFeatureConstant(\"fill-opacity\")&&1===r.paint[\"fill-color\"][3]&&1===r.paint[\"fill-opacity\"]),t.isOpaquePass===s){t.setDepthSublayer(1);for(var l=0;l<n.length;l++)i(t,e,r,n[l])}if(!t.isOpaquePass&&r.paint[\"fill-antialias\"]){t.lineWidth(2),t.depthMask(!1);var u=r.getPaintProperty(\"fill-outline-color\");(u||!r.paint[\"fill-pattern\"])&&u?t.setDepthSublayer(2):t.setDepthSublayer(0);for(var c=0;c<n.length;c++)a(t,e,r,n[c])}}function i(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s=a.bufferGroups.fill;if(s){var l,u=t.gl,c=r.paint[\"fill-pattern\"];if(c)l=t.useProgram(\"pattern\"),o(c,r.paint[\"fill-opacity\"],i,n,t,l),u.activeTexture(u.TEXTURE0),t.spriteAtlas.bind(u,!0);else{var h=a.paintAttributes.fill[r.id];l=t.useProgram(\"fill\",h.defines,h.vertexPragmas,h.fragmentPragmas),a.setUniforms(u,\"fill\",l,r,{zoom:t.transform.zoom})}u.uniformMatrix4fv(l.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),t.enableTileClippingMask(n);for(var f=0;f<s.length;f++){var d=s[f];d.vaos[r.id].bind(u,l,d.layoutVertexBuffer,d.elementBuffer,d.paintVertexBuffers[r.id]),u.drawElements(u.TRIANGLES,d.elementBuffer.length,u.UNSIGNED_SHORT,0)}}}}function a(t,e,r,n){var i=e.getTile(n),a=i.getBucket(r);if(a){var s,l=t.gl,u=a.bufferGroups.fill,c=r.paint[\"fill-pattern\"],h=r.paint[\"fill-opacity\"],f=r.getPaintProperty(\"fill-outline-color\");if(c&&!f)s=t.useProgram(\"outlinepattern\"),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight);else{var d=a.paintAttributes.fill[r.id];s=t.useProgram(\"outline\",d.defines,d.vertexPragmas,d.fragmentPragmas),l.uniform2f(s.u_world,l.drawingBufferWidth,l.drawingBufferHeight),l.uniform1f(s.u_opacity,h),a.setUniforms(l,\"fill\",s,r,{zoom:t.transform.zoom})}l.uniformMatrix4fv(s.u_matrix,!1,t.translatePosMatrix(n.posMatrix,i,r.paint[\"fill-translate\"],r.paint[\"fill-translate-anchor\"])),\n",
+       "c&&o(c,h,i,n,t,s),t.enableTileClippingMask(n);for(var p=0;p<u.length;p++){var g=u[p];g.secondVaos[r.id].bind(l,s,g.layoutVertexBuffer,g.elementBuffer2,g.paintVertexBuffers[r.id]),l.drawElements(l.LINES,2*g.elementBuffer2.length,l.UNSIGNED_SHORT,0)}}}function o(t,e,r,n,i,a){var o=i.gl,l=i.spriteAtlas.getPosition(t.from,!0),u=i.spriteAtlas.getPosition(t.to,!0);if(l&&u){o.uniform1i(a.u_image,0),o.uniform2fv(a.u_pattern_tl_a,l.tl),o.uniform2fv(a.u_pattern_br_a,l.br),o.uniform2fv(a.u_pattern_tl_b,u.tl),o.uniform2fv(a.u_pattern_br_b,u.br),o.uniform1f(a.u_opacity,e),o.uniform1f(a.u_mix,t.t),o.uniform1f(a.u_tile_units_to_pixels,1/s(r,1,i.transform.tileZoom)),o.uniform2fv(a.u_pattern_size_a,l.size),o.uniform2fv(a.u_pattern_size_b,u.size),o.uniform1f(a.u_scale_a,t.fromScale),o.uniform1f(a.u_scale_b,t.toScale);var c=r.tileSize*Math.pow(2,i.transform.tileZoom-r.coord.z),h=c*(r.coord.x+n.w*Math.pow(2,r.coord.z)),f=c*r.coord.y;o.uniform2f(a.u_pixel_coord_upper,h>>16,f>>16),o.uniform2f(a.u_pixel_coord_lower,65535&h,65535&f),o.activeTexture(o.TEXTURE0),i.spriteAtlas.bind(o,!0)}}var s=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":324}],311:[function(t,e,r){\"use strict\";var n=t(\"../util/browser\"),i=t(\"gl-matrix\").mat2,a=t(\"../source/pixels_to_tile_units\");e.exports=function(t,e,r,o){if(!t.isOpaquePass){t.setDepthSublayer(0),t.depthMask(!1);var s=t.gl;if(s.enable(s.STENCIL_TEST),!(r.paint[\"line-width\"]<=0)){var l=1/n.devicePixelRatio,u=r.paint[\"line-blur\"]+l,c=r.paint[\"line-color\"],h=t.transform,f=i.create();i.scale(f,f,[1,Math.cos(h._pitch)]),i.rotate(f,f,t.transform.angle);var d,p,g,m,v,y=Math.sqrt(h.height*h.height/4*(1+h.altitude*h.altitude)),x=h.height/2*Math.tan(h._pitch),b=(y+x)/y-1,_=r.paint[\"line-dasharray\"],w=r.paint[\"line-pattern\"];if(_)d=t.useProgram(\"linesdfpattern\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),p=t.lineAtlas.getDash(_.from,\"round\"===r.layout[\"line-cap\"]),g=t.lineAtlas.getDash(_.to,\"round\"===r.layout[\"line-cap\"]),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.lineAtlas.bind(s),s.uniform1f(d.u_tex_y_a,p.y),s.uniform1f(d.u_tex_y_b,g.y),s.uniform1f(d.u_mix,_.t),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f);else if(w){if(m=t.spriteAtlas.getPosition(w.from,!0),v=t.spriteAtlas.getPosition(w.to,!0),!m||!v)return;d=t.useProgram(\"linepattern\"),s.uniform1i(d.u_image,0),s.activeTexture(s.TEXTURE0),t.spriteAtlas.bind(s,!0),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform2fv(d.u_pattern_tl_a,m.tl),s.uniform2fv(d.u_pattern_br_a,m.br),s.uniform2fv(d.u_pattern_tl_b,v.tl),s.uniform2fv(d.u_pattern_br_b,v.br),s.uniform1f(d.u_fade,w.t),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f)}else d=t.useProgram(\"line\"),s.uniform1f(d.u_linewidth,r.paint[\"line-width\"]/2),s.uniform1f(d.u_gapwidth,r.paint[\"line-gap-width\"]/2),s.uniform1f(d.u_antialiasing,l/2),s.uniform1f(d.u_blur,u),s.uniform1f(d.u_extra,b),s.uniform1f(d.u_offset,-r.paint[\"line-offset\"]),s.uniformMatrix2fv(d.u_antialiasingmatrix,!1,f),s.uniform4fv(d.u_color,c),s.uniform1f(d.u_opacity,r.paint[\"line-opacity\"]);for(var M=0;M<o.length;M++){var A=o[M],k=e.getTile(A),T=k.getBucket(r);if(T){var E=T.bufferGroups.line;if(E){t.enableTileClippingMask(A);var S=t.translatePosMatrix(A.posMatrix,k,r.paint[\"line-translate\"],r.paint[\"line-translate-anchor\"]);s.uniformMatrix4fv(d.u_matrix,!1,S);var L=1/a(k,1,t.transform.zoom);if(_){var z=p.width*_.fromScale,C=g.width*_.toScale,I=[1/a(k,z,t.transform.tileZoom),-p.height/2],P=[1/a(k,C,t.transform.tileZoom),-g.height/2],D=t.lineAtlas.width/(256*Math.min(z,C)*n.devicePixelRatio)/2;s.uniform1f(d.u_ratio,L),s.uniform2fv(d.u_patternscale_a,I),s.uniform2fv(d.u_patternscale_b,P),s.uniform1f(d.u_sdfgamma,D)}else w?(s.uniform1f(d.u_ratio,L),s.uniform2fv(d.u_pattern_size_a,[a(k,m.size[0]*w.fromScale,t.transform.tileZoom),v.size[1]]),s.uniform2fv(d.u_pattern_size_b,[a(k,v.size[0]*w.toScale,t.transform.tileZoom),v.size[1]])):s.uniform1f(d.u_ratio,L);for(var R=0;R<E.length;R++){var O=E[R];O.vaos[r.id].bind(s,d,O.layoutVertexBuffer,O.elementBuffer),s.drawElements(s.TRIANGLES,3*O.elementBuffer.length,s.UNSIGNED_SHORT,0)}}}}}}}},{\"../source/pixels_to_tile_units\":324,\"../util/browser\":387,\"gl-matrix\":161}],312:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=t.gl;a.enable(a.DEPTH_TEST),t.depthMask(!0),a.depthFunc(a.LESS);for(var o=n.length&&n[0].z,s=0;s<n.length;s++){var l=n[s];t.setDepthSublayer(l.z-o),i(t,e,r,l)}a.depthFunc(a.LEQUAL)}}function i(t,e,r,n){var i=t.gl;i.disable(i.STENCIL_TEST);var u=e.getTile(n),c=t.transform.calculatePosMatrix(n,e.maxzoom),h=t.useProgram(\"raster\");i.uniformMatrix4fv(h.u_matrix,!1,c),i.uniform1f(h.u_brightness_low,r.paint[\"raster-brightness-min\"]),i.uniform1f(h.u_brightness_high,r.paint[\"raster-brightness-max\"]),i.uniform1f(h.u_saturation_factor,s(r.paint[\"raster-saturation\"])),i.uniform1f(h.u_contrast_factor,o(r.paint[\"raster-contrast\"])),i.uniform3fv(h.u_spin_weights,a(r.paint[\"raster-hue-rotate\"]));var f,d,p=u.source&&u.source.findLoadedParent(n,0,{}),g=l(u,p,r,t.transform);i.activeTexture(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,u.texture),i.activeTexture(i.TEXTURE1),p?(i.bindTexture(i.TEXTURE_2D,p.texture),f=Math.pow(2,p.coord.z-u.coord.z),d=[u.coord.x*f%1,u.coord.y*f%1]):(i.bindTexture(i.TEXTURE_2D,u.texture),g[1]=0),i.uniform2fv(h.u_tl_parent,d||[0,0]),i.uniform1f(h.u_scale_parent,f||1),i.uniform1f(h.u_buffer_scale,1),i.uniform1f(h.u_opacity0,g[0]),i.uniform1f(h.u_opacity1,g[1]),i.uniform1i(h.u_image0,0),i.uniform1i(h.u_image1,1);var m=u.boundsBuffer||t.rasterBoundsBuffer,v=u.boundsVAO||t.rasterBoundsVAO;v.bind(i,h,m),i.drawArrays(i.TRIANGLE_STRIP,0,m.length)}function a(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}function o(t){return t>0?1/(1-t):1+t}function s(t){return t>0?1-1/(1.001-t):-t}function l(t,e,r,n){var i=[1,0],a=r.paint[\"raster-fade-duration\"];if(t.source&&a>0){var o=(new Date).getTime(),s=(o-t.timeAdded)/a,l=e?(o-e.timeAdded)/a:-1,c=n.coveringZoomLevel(t.source),h=!!e&&Math.abs(e.coord.z-c)>Math.abs(t.coord.z-c);!e||h?(i[0]=u.clamp(s,0,1),i[1]=1-i[0]):(i[0]=u.clamp(1-l,0,1),i[1]=1-i[0])}var f=r.paint[\"raster-opacity\"];return i[0]*=f,i[1]*=f,i}var u=t(\"../util/util\"),c=t(\"../util/struct_array\");e.exports=n,n.RasterBoundsArray=new c({members:[{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]})},{\"../util/struct_array\":401,\"../util/util\":403}],313:[function(t,e,r){\"use strict\";function n(t,e,r,n){if(!t.isOpaquePass){var a=!(r.layout[\"text-allow-overlap\"]||r.layout[\"icon-allow-overlap\"]||r.layout[\"text-ignore-placement\"]||r.layout[\"icon-ignore-placement\"]),o=t.gl;a?o.disable(o.STENCIL_TEST):o.enable(o.STENCIL_TEST),t.setDepthSublayer(0),t.depthMask(!1),o.disable(o.DEPTH_TEST),i(t,e,r,n,!1,r.paint[\"icon-translate\"],r.paint[\"icon-translate-anchor\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-rotation-alignment\"],r.layout[\"icon-size\"],r.paint[\"icon-halo-width\"],r.paint[\"icon-halo-color\"],r.paint[\"icon-halo-blur\"],r.paint[\"icon-opacity\"],r.paint[\"icon-color\"]),i(t,e,r,n,!0,r.paint[\"text-translate\"],r.paint[\"text-translate-anchor\"],r.layout[\"text-rotation-alignment\"],r.layout[\"text-pitch-alignment\"],r.layout[\"text-size\"],r.paint[\"text-halo-width\"],r.paint[\"text-halo-color\"],r.paint[\"text-halo-blur\"],r.paint[\"text-opacity\"],r.paint[\"text-color\"]),o.enable(o.DEPTH_TEST),e.map.showCollisionBoxes&&s(t,e,r,n)}}function i(t,e,r,n,i,o,s,l,u,c,h,f,d,p,g){for(var m=0;m<n.length;m++){var v=e.getTile(n[m]),y=v.getBucket(r);if(y){var x=y.bufferGroups,b=i?x.glyph:x.icon;b.length&&(t.enableTileClippingMask(n[m]),a(t,r,n[m].posMatrix,v,y,b,i,i||y.sdfIcons,!i&&y.iconsNeedLinear,i?y.adjustedTextSize:y.adjustedIconSize,y.fontstack,o,s,l,u,c,h,f,d,p,g))}}}function a(t,e,r,n,i,a,s,u,c,h,f,d,p,g,m,v,y,x,b,_,w){var M,A,k,T=t.gl,E=t.transform,S=\"map\"===g,L=\"map\"===m,z=s?24:1,C=v/z;if(L?(A=l(n,1,t.transform.zoom)*C,k=1/Math.cos(E._pitch),M=[A,A]):(A=t.transform.altitude*C,k=1,M=[E.pixelsToGLUnits[0]*A,E.pixelsToGLUnits[1]*A]),s||t.style.sprite.loaded()){var I=t.useProgram(u?\"sdf\":\"icon\");if(T.uniformMatrix4fv(I.u_matrix,!1,t.translatePosMatrix(r,n,d,p)),T.uniform1i(I.u_rotate_with_map,S),T.uniform1i(I.u_pitch_with_map,L),T.uniform2fv(I.u_extrude_scale,M),T.activeTexture(T.TEXTURE0),T.uniform1i(I.u_texture,0),s){var P=f&&t.glyphSource.getGlyphAtlas(f);if(!P)return;P.updateTexture(T),T.uniform2f(I.u_texsize,P.width/4,P.height/4)}else{var D=t.options.rotating||t.options.zooming,R=1!==C||o.devicePixelRatio!==t.spriteAtlas.pixelRatio||c,O=L||t.transform.pitch;t.spriteAtlas.bind(T,u||D||R||O),T.uniform2f(I.u_texsize,t.spriteAtlas.width/4,t.spriteAtlas.height/4)}var F=Math.log(v/h)/Math.LN2||0;T.uniform1f(I.u_zoom,10*(t.transform.zoom-F)),T.activeTexture(T.TEXTURE1),t.frameHistory.bind(T),T.uniform1i(I.u_fadetexture,1);var j;if(u){var N=8,B=1.19,U=6,V=.105*z/v/o.devicePixelRatio;if(y){T.uniform1f(I.u_gamma,(b*B/C/N+V)*k),T.uniform4fv(I.u_color,x),T.uniform1f(I.u_opacity,_),T.uniform1f(I.u_buffer,(U-y/C)/N);for(var q=0;q<a.length;q++)j=a[q],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}T.uniform1f(I.u_gamma,V*k),T.uniform4fv(I.u_color,w),T.uniform1f(I.u_opacity,_),T.uniform1f(I.u_buffer,.75),T.uniform1f(I.u_pitch,E.pitch/360*2*Math.PI),T.uniform1f(I.u_bearing,E.bearing/360*2*Math.PI),T.uniform1f(I.u_aspect_ratio,E.width/E.height);for(var H=0;H<a.length;H++)j=a[H],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}else{T.uniform1f(I.u_opacity,_);for(var G=0;G<a.length;G++)j=a[G],j.vaos[e.id].bind(T,I,j.layoutVertexBuffer,j.elementBuffer),T.drawElements(T.TRIANGLES,3*j.elementBuffer.length,T.UNSIGNED_SHORT,0)}}}var o=t(\"../util/browser\"),s=t(\"./draw_collision_debug\"),l=t(\"../source/pixels_to_tile_units\");e.exports=n},{\"../source/pixels_to_tile_units\":324,\"../util/browser\":387,\"./draw_collision_debug\":308}],314:[function(t,e,r){\"use strict\";function n(){this.changeTimes=new Float64Array(256),this.changeOpacities=new Uint8Array(256),this.opacities=new Uint8ClampedArray(256),this.array=new Uint8Array(this.opacities.buffer),this.fadeDuration=300,this.previousZoom=0,this.firstFrame=!0}e.exports=n,n.prototype.record=function(t){var e=Date.now();this.firstFrame&&(e=0,this.firstFrame=!1),t=Math.floor(10*t);var r;if(t<this.previousZoom)for(r=t+1;r<=this.previousZoom;r++)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];else for(r=t;r>this.previousZoom;r--)this.changeTimes[r]=e,this.changeOpacities[r]=this.opacities[r];for(r=0;r<256;r++){var n=e-this.changeTimes[r],i=n/this.fadeDuration*255;r<=t?this.opacities[r]=this.changeOpacities[r]+i:this.opacities[r]=this.changeOpacities[r]-i}this.changed=!0,this.previousZoom=t},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.changed&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,256,1,t.ALPHA,t.UNSIGNED_BYTE,this.array),this.changed=!1)):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,256,1,0,t.ALPHA,t.UNSIGNED_BYTE,this.array))}},{}],315:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.nextRow=0,this.bytes=4,this.data=new Uint8Array(this.width*this.height*this.bytes),this.positions={}}var i=t(\"../util/util\");e.exports=n,n.prototype.setSprite=function(t){this.sprite=t},n.prototype.getDash=function(t,e){var r=t.join(\",\")+e;return this.positions[r]||(this.positions[r]=this.addDash(t,e)),this.positions[r]},n.prototype.addDash=function(t,e){var r=e?7:0,n=2*r+1,a=128;if(this.nextRow+n>this.height)return i.warnOnce(\"LineAtlas out of space\"),null;for(var o=0,s=0;s<t.length;s++)o+=t[s];for(var l=this.width/o,u=l/2,c=t.length%2===1,h=-r;h<=r;h++)for(var f=this.nextRow+r+h,d=this.width*f,p=c?-t[t.length-1]:0,g=t[0],m=1,v=0;v<this.width;v++){for(;g<v/l;)p=g,g+=t[m],c&&m===t.length-1&&(g+=t[0]),m++;var y,x=Math.abs(v-p*l),b=Math.abs(v-g*l),_=Math.min(x,b),w=m%2===1;if(e){var M=r?h/r*(u+1):0;if(w){var A=u-Math.abs(M);y=Math.sqrt(_*_+A*A)}else y=u-Math.sqrt(_*_+M*M)}else y=(w?1:-1)*_;this.data[3+4*(d+v)]=Math.max(0,Math.min(255,y+a))}var k={y:(this.nextRow+r+.5)/this.height,height:2*r/this.height,width:o};return this.nextRow+=n,this.dirty=!0,k},n.prototype.bind=function(t){this.texture?(t.bindTexture(t.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.RGBA,t.UNSIGNED_BYTE,this.data))):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.REPEAT),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width,this.height,0,t.RGBA,t.UNSIGNED_BYTE,this.data))}},{\"../util/util\":403}],316:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.transform=e,this.reusableTextures={},this.preFbos={},this.frameHistory=new o,this.setup(),this.numSublayers=s.maxUnderzooming+s.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.lineWidthRange=t.getParameter(t.ALIASED_LINE_WIDTH_RANGE)}var i=t(\"../util/browser\"),a=t(\"gl-matrix\").mat4,o=t(\"./frame_history\"),s=t(\"../source/source_cache\"),l=t(\"../data/bucket\").EXTENT,u=t(\"../source/pixels_to_tile_units\"),c=t(\"../util/util\"),h=t(\"../util/struct_array\"),f=t(\"../data/buffer\"),d=t(\"./vertex_array_object\"),p=t(\"./draw_raster\").RasterBoundsArray,g=t(\"./create_uniform_pragmas\");e.exports=n,c.extend(n.prototype,t(\"./painter/use_program\")),n.prototype.resize=function(t,e){var r=this.gl;this.width=t*i.devicePixelRatio,this.height=e*i.devicePixelRatio,r.viewport(0,0,this.width,this.height)},n.prototype.setup=function(){var t=this.gl;t.verbose=!0,t.enable(t.BLEND),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.enable(t.STENCIL_TEST),t.enable(t.DEPTH_TEST),t.depthFunc(t.LEQUAL),this._depthMask=!1,t.depthMask(!1);var e=this.PosArray=new h({members:[{name:\"a_pos\",type:\"Int16\",components:2}]}),r=new e;r.emplaceBack(0,0),r.emplaceBack(l,0),r.emplaceBack(0,l),r.emplaceBack(l,l),this.tileExtentBuffer=new f(r.serialize(),e.serialize(),f.BufferType.VERTEX),this.tileExtentVAO=new d,this.tileExtentPatternVAO=new d;var n=new e;n.emplaceBack(0,0),n.emplaceBack(l,0),n.emplaceBack(l,l),n.emplaceBack(0,l),n.emplaceBack(0,0),this.debugBuffer=new f(n.serialize(),e.serialize(),f.BufferType.VERTEX),this.debugVAO=new d;var i=new p;i.emplaceBack(0,0,0,0),i.emplaceBack(l,0,32767,0),i.emplaceBack(0,l,0,32767),i.emplaceBack(l,l,32767,32767),this.rasterBoundsBuffer=new f(i.serialize(),p.serialize(),f.BufferType.VERTEX),this.rasterBoundsVAO=new d},n.prototype.clearColor=function(){var t=this.gl;t.clearColor(0,0,0,0),t.clear(t.COLOR_BUFFER_BIT)},n.prototype.clearStencil=function(){var t=this.gl;t.clearStencil(0),t.stencilMask(255),t.clear(t.STENCIL_BUFFER_BIT)},n.prototype.clearDepth=function(){var t=this.gl;t.clearDepth(1),this.depthMask(!0),t.clear(t.DEPTH_BUFFER_BIT)},n.prototype._renderTileClippingMasks=function(t){var e=this.gl;e.colorMask(!1,!1,!1,!1),this.depthMask(!1),e.disable(e.DEPTH_TEST),e.enable(e.STENCIL_TEST),e.stencilMask(248),e.stencilOp(e.KEEP,e.KEEP,e.REPLACE);var r=1;this._tileClippingMaskIDs={};for(var n=0;n<t.length;n++){var i=t[n],a=this._tileClippingMaskIDs[i.id]=r++<<3;e.stencilFunc(e.ALWAYS,a,248);var o=g([{name:\"u_color\",components:4},{name:\"u_opacity\",components:1}]),s=this.useProgram(\"fill\",[],o,o);e.uniformMatrix4fv(s.u_matrix,!1,i.posMatrix),this.tileExtentVAO.bind(e,s,this.tileExtentBuffer),e.drawArrays(e.TRIANGLE_STRIP,0,this.tileExtentBuffer.length)}e.stencilMask(0),e.colorMask(!0,!0,!0,!0),this.depthMask(!0),e.enable(e.DEPTH_TEST)},n.prototype.enableTileClippingMask=function(t){var e=this.gl;e.stencilFunc(e.EQUAL,this._tileClippingMaskIDs[t.id],248)},n.prototype.prepareBuffers=function(){},n.prototype.bindDefaultFramebuffer=function(){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,null)};var m={symbol:t(\"./draw_symbol\"),circle:t(\"./draw_circle\"),line:t(\"./draw_line\"),fill:t(\"./draw_fill\"),raster:t(\"./draw_raster\"),background:t(\"./draw_background\"),debug:t(\"./draw_debug\")};n.prototype.render=function(t,e){this.style=t,this.options=e,this.lineAtlas=t.lineAtlas,this.spriteAtlas=t.spriteAtlas,this.spriteAtlas.setSprite(t.sprite),this.glyphSource=t.glyphSource,this.frameHistory.record(this.transform.zoom),this.prepareBuffers(),this.clearColor(),this.clearDepth(),this.showOverdrawInspector(e.showOverdrawInspector),this.depthRange=(t._order.length+2)*this.numSublayers*this.depthEpsilon,this.renderPass({isOpaquePass:!0}),this.renderPass({isOpaquePass:!1})},n.prototype.renderPass=function(t){var e=this.style._groups,r=t.isOpaquePass;this.currentLayer=r?this.style._order.length:-1;for(var n=0;n<e.length;n++){var i,a=e[r?e.length-1-n:n],o=this.style.sources[a.source],s=[];if(o){for(s=o.getVisibleCoordinates(),i=0;i<s.length;i++)s[i].posMatrix=this.transform.calculatePosMatrix(s[i],o.maxzoom);this.clearStencil(),o.prepare&&o.prepare(),o.isTileClipped&&this._renderTileClippingMasks(s)}for(r?(this._showOverdrawInspector||this.gl.disable(this.gl.BLEND),this.isOpaquePass=!0):(this.gl.enable(this.gl.BLEND),this.isOpaquePass=!1,s.reverse()),i=0;i<a.length;i++){var l=a[r?a.length-1-i:i];this.currentLayer+=r?-1:1,this.renderLayer(this,o,l,s)}o&&m.debug(this,o,s)}},n.prototype.depthMask=function(t){t!==this._depthMask&&(this._depthMask=t,this.gl.depthMask(t))},n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||n.length)&&(this.id=r.id,m[r.type](t,e,r,n))},n.prototype.setDepthSublayer=function(t){var e=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon,r=e-1+this.depthRange;this.gl.depthRange(r,e)},n.prototype.translatePosMatrix=function(t,e,r,n){if(!r[0]&&!r[1])return t;if(\"viewport\"===n){var i=Math.sin(-this.transform.angle),o=Math.cos(-this.transform.angle);r=[r[0]*o-r[1]*i,r[0]*i+r[1]*o]}var s=[u(e,r[0],this.transform.zoom),u(e,r[1],this.transform.zoom),0],l=new Float32Array(16);return a.translate(l,t,s),l},n.prototype.saveTexture=function(t){var e=this.reusableTextures[t.size];e?e.push(t):this.reusableTextures[t.size]=[t]},n.prototype.getTexture=function(t){var e=this.reusableTextures[t];return e&&e.length>0?e.pop():null},n.prototype.lineWidth=function(t){this.gl.lineWidth(c.clamp(t,this.lineWidthRange[0],this.lineWidthRange[1]))},n.prototype.showOverdrawInspector=function(t){if(t||this._showOverdrawInspector){this._showOverdrawInspector=t;var e=this.gl;if(t){e.blendFunc(e.CONSTANT_COLOR,e.ONE);var r=8,n=1/r;e.blendColor(n,n,n,0),e.clearColor(0,0,0,1),e.clear(e.COLOR_BUFFER_BIT)}else e.blendFunc(e.ONE,e.ONE_MINUS_SRC_ALPHA)}}},{\"../data/bucket\":290,\"../data/buffer\":295,\"../source/pixels_to_tile_units\":324,\"../source/source_cache\":328,\"../util/browser\":387,\"../util/struct_array\":401,\"../util/util\":403,\"./create_uniform_pragmas\":305,\"./draw_background\":306,\"./draw_circle\":307,\"./draw_debug\":309,\"./draw_fill\":310,\"./draw_line\":311,\"./draw_raster\":312,\"./draw_symbol\":313,\"./frame_history\":314,\"./painter/use_program\":317,\"./vertex_array_object\":318,\"gl-matrix\":161}],317:[function(t,e,r){\"use strict\";function n(t,e){return t.replace(/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,function(t,r,n,i,a){return e[r][a].replace(/{type}/g,i).replace(/{precision}/g,n)})}var i=t(\"assert\"),a=t(\"../../util/util\"),o=t(\"mapbox-gl-shaders\"),s=o.util;e.exports._createProgram=function(t,e,r,l){for(var u=this.gl,c=u.createProgram(),h=o[t],f=\"#define MAPBOX_GL_JS;\\n\",d=0;d<e.length;d++)f+=\"#define \"+e[d]+\";\\n\";var p=u.createShader(u.FRAGMENT_SHADER);u.shaderSource(p,n(f+h.fragmentSource,l)),u.compileShader(p),i(u.getShaderParameter(p,u.COMPILE_STATUS),u.getShaderInfoLog(p)),u.attachShader(c,p);var g=u.createShader(u.VERTEX_SHADER);u.shaderSource(g,n(f+s+h.vertexSource,r)),u.compileShader(g),i(u.getShaderParameter(g,u.COMPILE_STATUS),u.getShaderInfoLog(g)),u.attachShader(c,g),u.linkProgram(c),i(u.getProgramParameter(c,u.LINK_STATUS),u.getProgramInfoLog(c));for(var m={},v=u.getProgramParameter(c,u.ACTIVE_ATTRIBUTES),y=0;y<v;y++){var x=u.getActiveAttrib(c,y);m[x.name]=u.getAttribLocation(c,x.name)}for(var b={},_=u.getProgramParameter(c,u.ACTIVE_UNIFORMS),w=0;w<_;w++){var M=u.getActiveUniform(c,w);b[M.name]=u.getUniformLocation(c,M.name)}return a.extend({program:c,definition:h,attributes:m,numAttributes:v},m,b)},e.exports._createProgramCached=function(t,e,r,n){this.cache=this.cache||{};var i=JSON.stringify({name:t,defines:e,vertexPragmas:r,fragmentPragmas:n});return this.cache[i]||(this.cache[i]=this._createProgram(t,e,r,n)),this.cache[i]},e.exports.useProgram=function(t,e,r,n){var i=this.gl;e=e||[],this._showOverdrawInspector&&(e=e.concat(\"OVERDRAW_INSPECTOR\"));var a=this._createProgramCached(t,e,r,n),o=this.currentProgram;return o!==a&&(i.useProgram(a.program),this.currentProgram=a),a}},{\"../../util/util\":403,assert:34,\"mapbox-gl-shaders\":264}],318:[function(t,e,r){\"use strict\";function n(){this.boundProgram=null,this.boundVertexBuffer=null,this.boundVertexBuffer2=null,this.boundElementBuffer=null,this.vao=null}var i=t(\"assert\");e.exports=n,n.prototype.bind=function(t,e,r,n,i){void 0===t.extVertexArrayObject&&(t.extVertexArrayObject=t.getExtension(\"OES_vertex_array_object\"));var a=!this.vao||this.boundProgram!==e||this.boundVertexBuffer!==r||this.boundVertexBuffer2!==i||this.boundElementBuffer!==n;!t.extVertexArrayObject||a?this.freshBind(t,e,r,n,i):t.extVertexArrayObject.bindVertexArrayOES(this.vao)},n.prototype.freshBind=function(t,e,r,n,a){var o,s=e.numAttributes;if(t.extVertexArrayObject)this.vao&&this.destroy(t),this.vao=t.extVertexArrayObject.createVertexArrayOES(),t.extVertexArrayObject.bindVertexArrayOES(this.vao),o=0,this.boundProgram=e,this.boundVertexBuffer=r,this.boundVertexBuffer2=a,this.boundElementBuffer=n;else{o=t.currentNumAttributes||0;for(var l=s;l<o;l++)i(0!==l),t.disableVertexAttribArray(l)}for(var u=o;u<s;u++)t.enableVertexAttribArray(u);r.bind(t),r.setVertexAttribPointers(t,e),a&&(a.bind(t),a.setVertexAttribPointers(t,e)),n&&n.bind(t),t.currentNumAttributes=s},n.prototype.unbind=function(t){var e=t.extVertexArrayObject;e&&e.bindVertexArrayOES(null)},n.prototype.destroy=function(t){var e=t.extVertexArrayObject;e&&this.vao&&(e.deleteVertexArrayOES(this.vao),this.vao=null)}},{assert:34}],319:[function(t,e,r){\"use strict\";function n(t,e,r){e=e||{},this.id=t,this.dispatcher=r,this._data=e.data,void 0!==e.maxzoom&&(this.maxzoom=e.maxzoom),e.type&&(this.type=e.type);var n=s/this.tileSize;this.workerOptions=a.extend({source:this.id,cluster:e.cluster||!1,geojsonVtOptions:{buffer:(void 0!==e.buffer?e.buffer:128)*n,tolerance:(void 0!==e.tolerance?e.tolerance:.375)*n,extent:s,maxZoom:this.maxzoom},superclusterOptions:{maxZoom:Math.min(e.clusterMaxZoom,this.maxzoom-1)||this.maxzoom-1,extent:s,radius:(e.clusterRadius||50)*n,log:!1}},e.workerOptions),this._updateWorkerData(function(t){return t?void this.fire(\"error\",{error:t}):void this.fire(\"load\")}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"resolve-url\"),s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype=a.inherit(i,{type:\"geojson\",minzoom:0,maxzoom:18,tileSize:512,isTileClipped:!0,reparseOverscaled:!0,onAdd:function(t){this.map=t},setData:function(t){return this._data=t,this._updateWorkerData(function(t){return t?this.fire(\"error\",{error:t}):void this.fire(\"change\")}.bind(this)),this},_updateWorkerData:function(t){var e=a.extend({},this.workerOptions),r=this._data;\"string\"==typeof r?e.url=\"undefined\"!=typeof window?o(window.location.href,r):r:e.data=JSON.stringify(r),this.workerID=this.dispatcher.send(this.type+\".loadData\",e,function(e){this._loaded=!0,t(e)}.bind(this))},loadTile:function(t,e){var r=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,n={type:this.type,uid:t.uid,coord:t.coord,zoom:t.coord.z,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,overscaling:r,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID=this.dispatcher.send(\"load tile\",n,function(r,n){if(t.unloadVectorData(this.map.painter),!t.aborted)return r?e(r):(t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null))}.bind(this),this.workerID)},abortTile:function(t){t.aborted=!0},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},function(){},t.workerID)},serialize:function(){return{type:this.type,data:this._data}}})},{\"../data/bucket\":290,\"../util/evented\":395,\"../util/util\":403,\"resolve-url\":458}],320:[function(t,e,r){\"use strict\";function n(t,e,r){r&&(this.loadGeoJSON=r),h.call(this,t,e)}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"geojson-rewind\"),s=t(\"./geojson_wrapper\"),l=t(\"vt-pbf\"),u=t(\"supercluster\"),c=t(\"geojson-vt\"),h=t(\"./vector_tile_worker_source\");e.exports=n,n.prototype=i.inherit(h,{_geoJSONIndexes:{},loadVectorData:function(t,e){var r=t.source,n=t.coord;if(!this._geoJSONIndexes[r])return e(null,null);var i=this._geoJSONIndexes[r].getTile(Math.min(n.z,t.maxZoom),n.x,n.y);if(!i)return e(null,null);var a=new s(i.features);a.name=\"_geojsonTileLayer\";var o=l({layers:{_geojsonTileLayer:a}});0===o.byteOffset&&o.byteLength===o.buffer.byteLength||(o=new Uint8Array(o)),e(null,{tile:a,rawTileData:o.buffer})},loadData:function(t,e){var r=function(r,n){return r?e(r):\"object\"!=typeof n?e(new Error(\"Input data is not a valid GeoJSON object.\")):(o(n,!0),void this._indexData(n,t,function(r,n){return r?e(r):(this._geoJSONIndexes[t.source]=n,void e(null))}.bind(this)))}.bind(this);this.loadGeoJSON(t,r)},loadGeoJSON:function(t,e){if(t.url)a.getJSON(t.url,e);else{if(\"string\"!=typeof t.data)return e(new Error(\"Input data is not a valid GeoJSON object.\"));try{return e(null,JSON.parse(t.data))}catch(t){return e(new Error(\"Input data is not a valid GeoJSON object.\"))}}},_indexData:function(t,e,r){try{e.cluster?r(null,u(e.superclusterOptions).load(t.features)):r(null,c(t,e.geojsonVtOptions))}catch(t){return r(t)}}})},{\"../util/ajax\":386,\"../util/util\":403,\"./geojson_wrapper\":321,\"./vector_tile_worker_source\":332,\"geojson-rewind\":110,\"geojson-vt\":114,supercluster:485,\"vt-pbf\":511}],321:[function(t,e,r){\"use strict\";function n(t){this.features=t,this.length=t.length,this.extent=s}function i(t){if(this.type=t.type,1===t.type){this.rawGeometry=[];for(var e=0;e<t.geometry.length;e++)this.rawGeometry.push([t.geometry[e]])}else this.rawGeometry=t.geometry;this.properties=t.tags,this.extent=s}var a=t(\"point-geometry\"),o=t(\"vector-tile\").VectorTileFeature,s=t(\"../data/bucket\").EXTENT;e.exports=n,n.prototype.feature=function(t){return new i(this.features[t])},i.prototype.loadGeometry=function(){var t=this.rawGeometry;this.geometry=[];for(var e=0;e<t.length;e++){for(var r=t[e],n=[],i=0;i<r.length;i++)n.push(new a(r[i][0],r[i][1]));this.geometry.push(n)}return this.geometry},i.prototype.bbox=function(){this.geometry||this.loadGeometry();for(var t=this.geometry,e=1/0,r=-(1/0),n=1/0,i=-(1/0),a=0;a<t.length;a++)for(var o=t[a],s=0;s<o.length;s++){var l=o[s];e=Math.min(e,l.x),r=Math.max(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.y)}return[e,n,r,i]},i.prototype.toGeoJSON=o.prototype.toGeoJSON},{\"../data/bucket\":290,\"point-geometry\":442,\"vector-tile\":505}],322:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,this.url=e.url,this.coordinates=e.coordinates,u.getImage(e.url,function(t,r){return t?this.fire(\"error\",{error:t}):(this.image=r,this.image.addEventListener(\"load\",function(){this.map._rerender()}.bind(this)),this._loaded=!0,this.fire(\"load\"),void(this.map&&this.setCoordinates(e.coordinates)))}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,onAdd:function(t){this.map=t,this.image&&this.setCoordinates(this.coordinates)},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=32767,r=new h;r.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),r.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,e,0),r.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,e),r.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,e,e),this.tile.buckets={},this.tile.boundsBuffer=new f(r.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(this._loaded&&this.image&&this.image.complete&&this.tile){var t=this.map.painter,e=t.gl;this._prepared?(e.bindTexture(e.TEXTURE_2D,this.tile.texture),e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,this.image)):(this.tile.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.tile.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,this.image))}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"image\",urls:this.url,coordinates:this.coordinates}}})},{\"../data/bucket\":290,\"../data/buffer\":295,\"../geo/lng_lat\":300,\"../render/draw_raster\":312,\"../render/vertex_array_object\":318,\"../util/ajax\":386,\"../util/evented\":395,\"../util/util\":403,\"./tile_coord\":330,\"point-geometry\":442}],323:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/ajax\"),a=t(\"../util/browser\"),o=t(\"../util/mapbox\").normalizeSourceURL;e.exports=function(t,e){var r=function(t,r){if(t)return e(t);var i=n.pick(r,[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\"]);r.vector_layers&&(i.vectorLayers=r.vector_layers,i.vectorLayerIds=i.vectorLayers.map(function(t){return t.id})),e(null,i)};t.url?i.getJSON(o(t.url),r):a.frame(r.bind(null,null,t))}},{\"../util/ajax\":386,\"../util/browser\":387,\"../util/mapbox\":400,\"../util/util\":403}],324:[function(t,e,r){\"use strict\";var n=t(\"../data/bucket\");e.exports=function(t,e,r){return e*(n.EXTENT/(t.tileSize*Math.pow(2,r-t.coord.z)))}},{\"../data/bucket\":290}],325:[function(t,e,r){\"use strict\";function n(t,e){var r=t.coord,n=e.coord;return r.z-n.z||r.y-n.y||r.w-n.w||r.x-n.x}function i(t){for(var e=t[0]||{},r=1;r<t.length;r++){var n=t[r];for(var i in n){var a=n[i],o=e[i];if(void 0===o)o=e[i]=a;else for(var s=0;s<a.length;s++)o.push(a[s]);\n",
+       "}}return e}var a=t(\"./tile_coord\");r.rendered=function(t,e,r,a,o,s){var l=t.tilesIn(r);l.sort(n);for(var u=[],c=0;c<l.length;c++){var h=l[c];h.tile.featureIndex&&u.push(h.tile.featureIndex.query({queryGeometry:h.queryGeometry,scale:h.scale,tileSize:h.tile.tileSize,bearing:s,params:a},e))}return i(u)},r.source=function(t,e){for(var r=t.getRenderableIds().map(function(e){return t.getTileByID(e)}),n=[],i={},o=0;o<r.length;o++){var s=r[o],l=new a(Math.min(s.sourceMaxZoom,s.coord.z),s.coord.x,s.coord.y,0).id;i[l]||(i[l]=!0,s.querySourceFeatures(n,e))}return n}},{\"./tile_coord\":330}],326:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r,i.extend(this,i.pick(e,[\"url\",\"scheme\",\"tileSize\"])),s(e,function(t,e){return t?this.fire(\"error\",t):(i.extend(this,e),void this.fire(\"load\"))}.bind(this))}var i=t(\"../util/util\"),a=t(\"../util/ajax\"),o=t(\"../util/evented\"),s=t(\"./load_tilejson\"),l=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=i.inherit(o,{minzoom:0,maxzoom:22,roundZoom:!0,scheme:\"xyz\",tileSize:512,_loaded:!1,onAdd:function(t){this.map=t},serialize:function(){return{type:\"raster\",url:this.url,tileSize:this.tileSize}},loadTile:function(t,e){function r(r,n){if(delete t.request,!t.aborted){if(r)return e(r);var i=this.map.painter.gl;t.texture=this.map.painter.getTexture(n.width),t.texture?(i.bindTexture(i.TEXTURE_2D,t.texture),i.texSubImage2D(i.TEXTURE_2D,0,0,0,i.RGBA,i.UNSIGNED_BYTE,n)):(t.texture=i.createTexture(),i.bindTexture(i.TEXTURE_2D,t.texture),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MIN_FILTER,i.LINEAR_MIPMAP_NEAREST),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MAG_FILTER,i.LINEAR),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_S,i.CLAMP_TO_EDGE),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_T,i.CLAMP_TO_EDGE),i.pixelStorei(i.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0),i.texImage2D(i.TEXTURE_2D,0,i.RGBA,i.RGBA,i.UNSIGNED_BYTE,n),t.texture.size=n.width),i.generateMipmap(i.TEXTURE_2D),this.map.animationLoop.set(this.map.style.rasterFadeDuration),t.state=\"loaded\",e(null)}}var n=l(t.coord.url(this.tiles,null,this.scheme),this.url,this.tileSize);t.request=a.getImage(n,r.bind(this))},abortTile:function(t){t.request&&(t.request.abort(),delete t.request)},unloadTile:function(t){t.texture&&this.map.painter.saveTexture(t.texture)}})},{\"../util/ajax\":386,\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./load_tilejson\":323}],327:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i={vector:t(\"../source/vector_tile_source\"),raster:t(\"../source/raster_tile_source\"),geojson:t(\"../source/geojson_source\"),video:t(\"../source/video_source\"),image:t(\"../source/image_source\")};r.create=function(t,e,r){if(e=new i[e.type](t,e,r),e.id!==t)throw new Error(\"Expected Source id to be \"+t+\" instead of \"+e.id);return n.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],e),e},r.getType=function(t){return i[t]},r.setType=function(t,e){i[t]=e}},{\"../source/geojson_source\":319,\"../source/image_source\":322,\"../source/raster_tile_source\":326,\"../source/vector_tile_source\":331,\"../source/video_source\":333,\"../util/util\":403}],328:[function(t,e,r){\"use strict\";function n(t,e,r){this.id=t,this.dispatcher=r;var n=this._source=o.create(t,e,r).on(\"load\",function(){this.map&&this._source.onAdd&&this._source.onAdd(this.map),this._sourceLoaded=!0,this.tileSize=n.tileSize,this.minzoom=n.minzoom,this.maxzoom=n.maxzoom,this.roundZoom=n.roundZoom,this.reparseOverscaled=n.reparseOverscaled,this.isTileClipped=n.isTileClipped,this.attribution=n.attribution,this.vectorLayerIds=n.vectorLayerIds,this.fire(\"load\")}.bind(this)).on(\"error\",function(t){this._sourceErrored=!0,this.fire(\"error\",t)}.bind(this)).on(\"change\",function(){this.reload(),this.transform&&this.update(this.transform,this.map&&this.map.style.rasterFadeDuration),this.fire(\"change\")}.bind(this));this._tiles={},this._cache=new c(0,this.unloadTile.bind(this)),this._isIdRenderable=this._isIdRenderable.bind(this)}function i(t,e,r){var n=r.zoomTo(Math.min(t.z,e));return{x:(n.column-(t.x+t.w*Math.pow(2,t.z)))*d,y:(n.row-t.y)*d}}function a(t,e){return t%32-e%32}var o=t(\"./source\"),s=t(\"./tile\"),l=t(\"../util/evented\"),u=t(\"./tile_coord\"),c=t(\"../util/lru_cache\"),h=t(\"../geo/coordinate\"),f=t(\"../util/util\"),d=t(\"../data/bucket\").EXTENT;e.exports=n,n.maxOverzooming=10,n.maxUnderzooming=3,n.prototype=f.inherit(l,{onAdd:function(t){this.map=t,this._source&&this._source.onAdd&&this._source.onAdd(t)},loaded:function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},getSource:function(){return this._source},loadTile:function(t,e){return this._source.loadTile(t,e)},unloadTile:function(t){if(this._source.unloadTile)return this._source.unloadTile(t)},abortTile:function(t){if(this._source.abortTile)return this._source.abortTile(t)},serialize:function(){return this._source.serialize()},prepare:function(){if(this._sourceLoaded&&this._source.prepare)return this._source.prepare()},getIds:function(){return Object.keys(this._tiles).map(Number).sort(a)},getRenderableIds:function(){return this.getIds().filter(this._isIdRenderable)},_isIdRenderable:function(t){return this._tiles[t].isRenderable()&&!this._coveredTiles[t]},reload:function(){this._cache.reset();for(var t in this._tiles){var e=this._tiles[t];\"loading\"!==e.state&&(e.state=\"reloading\"),this.loadTile(this._tiles[t],this._tileLoaded.bind(this,this._tiles[t]))}},_tileLoaded:function(t,e){return e?(t.state=\"errored\",this.fire(\"tile.error\",{tile:t,error:e}),void this._source.fire(\"tile.error\",{tile:t,error:e})):(t.source=this,t.timeAdded=(new Date).getTime(),this.fire(\"tile.load\",{tile:t}),void this._source.fire(\"tile.load\",{tile:t}))},getTile:function(t){return this.getTileByID(t.id)},getTileByID:function(t){return this._tiles[t]},getZoom:function(t){return t.zoom+t.scaleZoom(t.tileSize/this.tileSize)},findLoadedChildren:function(t,e,r){var n=!1;for(var i in this._tiles){var a=this._tiles[i];if(!(r[i]||!a.isRenderable()||a.coord.z<=t.z||a.coord.z>e)){var o=Math.pow(2,Math.min(a.coord.z,this.maxzoom)-Math.min(t.z,this.maxzoom));if(Math.floor(a.coord.x/o)===t.x&&Math.floor(a.coord.y/o)===t.y)for(r[i]=!0,n=!0;a&&a.coord.z-1>t.z;){var s=a.coord.parent(this.maxzoom).id;a=this._tiles[s],a&&a.isRenderable()&&(delete r[i],r[s]=!0)}}}return n},findLoadedParent:function(t,e,r){for(var n=t.z-1;n>=e;n--){t=t.parent(this.maxzoom);var i=this._tiles[t.id];if(i&&i.isRenderable())return r[t.id]=!0,i;if(this._cache.has(t.id))return this.addTile(t),r[t.id]=!0,this._tiles[t.id]}},updateCacheSize:function(t){var e=Math.ceil(t.width/t.tileSize)+1,r=Math.ceil(t.height/t.tileSize)+1,n=e*r,i=5;this._cache.setMaxSize(Math.floor(n*i))},update:function(t,e){if(this._sourceLoaded){var r,i,a;this.updateCacheSize(t);var o=(this.roundZoom?Math.round:Math.floor)(this.getZoom(t)),s=Math.max(o-n.maxOverzooming,this.minzoom),l=Math.max(o+n.maxUnderzooming,this.minzoom),c={},h=(new Date).getTime();this._coveredTiles={};var d=this.used?t.coveringTiles(this._source):[];for(r=0;r<d.length;r++)i=d[r],a=this.addTile(i),c[i.id]=!0,a.isRenderable()||this.findLoadedChildren(i,l,c)||this.findLoadedParent(i,s,c);for(var p={},g=Object.keys(c),m=0;m<g.length;m++){var v=g[m];i=u.fromID(v),a=this._tiles[v],a&&a.timeAdded>h-(e||0)&&(this.findLoadedChildren(i,l,c)&&(c[v]=!0),this.findLoadedParent(i,s,p))}var y;for(y in p)c[y]||(this._coveredTiles[y]=!0);for(y in p)c[y]=!0;var x=f.keysDifference(this._tiles,c);for(r=0;r<x.length;r++)this.removeTile(+x[r]);this.transform=t}},addTile:function(t){var e=this._tiles[t.id];if(e)return e;var r=t.wrapped();if(e=this._tiles[r.id],e||(e=this._cache.get(r.id),e&&this._redoPlacement&&this._redoPlacement(e)),!e){var n=t.z,i=n>this.maxzoom?Math.pow(2,n-this.maxzoom):1;e=new s(r,this.tileSize*i,this.maxzoom),this.loadTile(e,this._tileLoaded.bind(this,e))}return e.uses++,this._tiles[t.id]=e,this.fire(\"tile.add\",{tile:e}),this._source.fire(\"tile.add\",{tile:e}),e},removeTile:function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this.fire(\"tile.remove\",{tile:e}),this._source.fire(\"tile.remove\",{tile:e}),e.uses>0||(e.isRenderable()?this._cache.add(e.coord.wrapped().id,e):(e.aborted=!0,this.abortTile(e),this.unloadTile(e))))},clearTiles:function(){for(var t in this._tiles)this.removeTile(t);this._cache.reset()},tilesIn:function(t){for(var e={},r=this.getIds(),n=1/0,a=1/0,o=-(1/0),s=-(1/0),l=t[0].zoom,c=0;c<t.length;c++){var f=t[c];n=Math.min(n,f.column),a=Math.min(a,f.row),o=Math.max(o,f.column),s=Math.max(s,f.row)}for(var p=0;p<r.length;p++){var g=this._tiles[r[p]],m=u.fromID(r[p]),v=[i(m,g.sourceMaxZoom,new h(n,a,l)),i(m,g.sourceMaxZoom,new h(o,s,l))];if(v[0].x<d&&v[0].y<d&&v[1].x>=0&&v[1].y>=0){for(var y=[],x=0;x<t.length;x++)y.push(i(m,g.sourceMaxZoom,t[x]));var b=e[g.coord.id];void 0===b&&(b=e[g.coord.id]={tile:g,coord:m,queryGeometry:[],scale:Math.pow(2,this.transform.zoom-g.coord.z)}),b.queryGeometry.push(y)}}var _=[];for(var w in e)_.push(e[w]);return _},redoPlacement:function(){for(var t=this.getIds(),e=0;e<t.length;e++){var r=this.getTileByID(t[e]);r.redoPlacement(this)}},getVisibleCoordinates:function(){return this.getRenderableIds().map(u.fromID)}})},{\"../data/bucket\":290,\"../geo/coordinate\":299,\"../util/evented\":395,\"../util/lru_cache\":399,\"../util/util\":403,\"./source\":327,\"./tile\":329,\"./tile_coord\":330}],329:[function(t,e,r){\"use strict\";function n(t,e,r){this.coord=t,this.uid=a.uniqueId(),this.uses=0,this.tileSize=e,this.sourceMaxZoom=r,this.buckets={},this.state=\"loading\"}function i(t,e){if(e){for(var r={},n=0;n<t.length;n++){var i=e.getLayer(t[n].layerId);if(i){var s=o.create(a.extend({layer:i,childLayers:t[n].childLayerIds.map(e.getLayer.bind(e)).filter(function(t){return t})},t[n]));r[s.id]=s}}return r}}var a=t(\"../util/util\"),o=t(\"../data/bucket\"),s=t(\"../data/feature_index\"),l=t(\"vector-tile\"),u=t(\"pbf\"),c=t(\"../util/vectortile_to_geojson\"),h=t(\"feature-filter\"),f=t(\"../symbol/collision_tile\"),d=t(\"../symbol/collision_box\"),p=t(\"../symbol/symbol_instances\"),g=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype={loadVectorData:function(t,e){this.state=\"loaded\",t&&(this.collisionBoxArray=new d(t.collisionBoxArray),this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.symbolInstancesArray=new p(t.symbolInstancesArray),this.symbolQuadsArray=new g(t.symbolQuadsArray),this.featureIndex=new s(t.featureIndex,t.rawTileData,this.collisionTile),this.rawTileData=t.rawTileData,this.buckets=i(t.buckets,e))},reloadSymbolData:function(t,e,r){if(\"unloaded\"!==this.state){this.collisionTile=new f(t.collisionTile,this.collisionBoxArray),this.featureIndex.setCollisionTile(this.collisionTile);for(var n in this.buckets){var o=this.buckets[n];\"symbol\"===o.type&&(o.destroy(e.gl),delete this.buckets[n])}a.extend(this.buckets,i(t.buckets,r))}},unloadVectorData:function(t){for(var e in this.buckets){var r=this.buckets[e];r.destroy(t.gl)}this.collisionBoxArray=null,this.symbolQuadsArray=null,this.symbolInstancesArray=null,this.collisionTile=null,this.featureIndex=null,this.rawTileData=null,this.buckets=null,this.state=\"unloaded\"},redoPlacement:function(t){function e(e,r){this.reloadSymbolData(r,t.map.painter,t.map.style),t.fire(\"tile.load\",{tile:this}),this.state=\"loaded\",this.redoWhenDone&&(this.redoPlacement(t),this.redoWhenDone=!1)}return\"loaded\"!==this.state||\"reloading\"===this.state?void(this.redoWhenDone=!0):(this.state=\"reloading\",void t.dispatcher.send(\"redo placement\",{uid:this.uid,source:t.id,angle:t.map.transform.angle,pitch:t.map.transform.pitch,showCollisionBoxes:t.map.showCollisionBoxes},e.bind(this),this.workerID))},getBucket:function(t){return this.buckets&&this.buckets[t.ref||t.id]},querySourceFeatures:function(t,e){if(this.rawTileData){this.vtLayers||(this.vtLayers=new l.VectorTile(new u(new Uint8Array(this.rawTileData))).layers);var r=this.vtLayers._geojsonTileLayer||this.vtLayers[e.sourceLayer];if(r)for(var n=h(e.filter),i={z:this.coord.z,x:this.coord.x,y:this.coord.y},a=0;a<r.length;a++){var o=r.feature(a);if(n(o)){var s=new c(o,this.coord.z,this.coord.x,this.coord.y);s.tile=i,t.push(s)}}}},isRenderable:function(){return\"loaded\"===this.state||\"reloading\"===this.state}}},{\"../data/bucket\":290,\"../data/feature_index\":297,\"../symbol/collision_box\":355,\"../symbol/collision_tile\":357,\"../symbol/symbol_instances\":366,\"../symbol/symbol_quads\":367,\"../util/util\":403,\"../util/vectortile_to_geojson\":404,\"feature-filter\":105,pbf:436,\"vector-tile\":505}],330:[function(t,e,r){\"use strict\";function n(t,e,r,n){l(!isNaN(t)&&t>=0&&t%1===0),l(!isNaN(e)&&e>=0&&e%1===0),l(!isNaN(r)&&r>=0&&r%1===0),isNaN(n)&&(n=0),this.z=+t,this.x=+e,this.y=+r,this.w=+n,n*=2,n<0&&(n=n*-1-1);var i=1<<this.z;this.id=32*(i*i*n+i*this.y+this.x)+this.z,this.posMatrix=null}function i(t,e,r){for(var n,i=\"\",a=t;a>0;a--)n=1<<a-1,i+=(e&n?1:0)+(r&n?2:0);return i}function a(t,e){if(t.row>e.row){var r=t;t=e,e=r}return{x0:t.column,y0:t.row,x1:e.column,y1:e.row,dx:e.column-t.column,dy:e.row-t.row}}function o(t,e,r,n,i){var a=Math.max(r,Math.floor(e.y0)),o=Math.min(n,Math.ceil(e.y1));if(t.x0===e.x0&&t.y0===e.y0?t.x0+e.dy/t.dy*t.dx<e.x1:t.x1-e.dy/t.dy*t.dx<e.x0){var s=t;t=e,e=s}for(var l=t.dx/t.dy,u=e.dx/e.dy,c=t.dx>0,h=e.dx<0,f=a;f<o;f++){var d=l*Math.max(0,Math.min(t.dy,f+c-t.y0))+t.x0,p=u*Math.max(0,Math.min(e.dy,f+h-e.y0))+e.x0;i(Math.floor(p),Math.ceil(d),f)}}function s(t,e,r,n,i,s){var l,u=a(t,e),c=a(e,r),h=a(r,t);u.dy>c.dy&&(l=u,u=c,c=l),u.dy>h.dy&&(l=u,u=h,h=l),c.dy>h.dy&&(l=c,c=h,h=l),u.dy&&o(h,u,n,i,s),c.dy&&o(h,c,n,i,s)}var l=t(\"assert\"),u=t(\"whoots-js\"),c=t(\"../geo/coordinate\");e.exports=n,n.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y},n.prototype.toCoordinate=function(t){var e=Math.min(this.z,t),r=Math.pow(2,e),n=this.y,i=this.x+r*this.w;return new c(i,n,e)},n.fromID=function(t){var e=t%32,r=1<<e,i=(t-e)/32,a=i%r,o=(i-a)/r%r,s=Math.floor(i/(r*r));return s%2!==0&&(s=s*-1-1),s/=2,new n(e,a,o,s)},n.prototype.url=function(t,e,r){var n=u.getTileBBox(this.x,this.y,this.z),a=i(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",Math.min(this.z,e||this.z)).replace(\"{x}\",this.x).replace(\"{y}\",\"tms\"===r?Math.pow(2,this.z)-this.y-1:this.y).replace(\"{quadkey}\",a).replace(\"{bbox-epsg-3857}\",n)},n.prototype.parent=function(t){return 0===this.z?null:this.z>t?new n(this.z-1,this.x,this.y,this.w):new n(this.z-1,Math.floor(this.x/2),Math.floor(this.y/2),this.w)},n.prototype.wrapped=function(){return new n(this.z,this.x,this.y,0)},n.prototype.children=function(t){if(this.z>=t)return[new n(this.z+1,this.x,this.y,this.w)];var e=this.z+1,r=2*this.x,i=2*this.y;return[new n(e,r,i,this.w),new n(e,r+1,i,this.w),new n(e,r,i+1,this.w),new n(e,r+1,i+1,this.w)]},n.cover=function(t,e,r){function i(t,e,i){var s,l,u;if(i>=0&&i<=a)for(s=t;s<e;s++)l=(s%a+a)%a,u=new n(r,l,i,Math.floor(s/a)),o[u.id]=u}var a=1<<t,o={};return s(e[0],e[1],e[2],0,a,i),s(e[2],e[3],e[0],0,a,i),Object.keys(o).map(function(t){return o[t]})}},{\"../geo/coordinate\":299,assert:34,\"whoots-js\":521}],331:[function(t,e,r){\"use strict\";function n(t,e,r){if(this.id=t,this.dispatcher=r,a.extend(this,a.pick(e,[\"url\",\"scheme\",\"tileSize\"])),this._options=a.extend({type:\"vector\"},e),512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");o(e,function(t,e){return t?void this.fire(\"error\",t):(a.extend(this,e),void this.fire(\"load\"))}.bind(this))}var i=t(\"../util/evented\"),a=t(\"../util/util\"),o=t(\"./load_tilejson\"),s=t(\"../util/mapbox\").normalizeTileURL;e.exports=n,n.prototype=a.inherit(i,{minzoom:0,maxzoom:22,scheme:\"xyz\",tileSize:512,reparseOverscaled:!0,isTileClipped:!0,onAdd:function(t){this.map=t},serialize:function(){return a.extend({},this._options)},loadTile:function(t,e){function r(r,n){if(!t.aborted){if(r)return e(r);t.loadVectorData(n,this.map.style),t.redoWhenDone&&(t.redoWhenDone=!1,t.redoPlacement(this)),e(null),t.reloadCallback&&(this.loadTile(t,t.reloadCallback),t.reloadCallback=null)}}var n=t.coord.z>this.maxzoom?Math.pow(2,t.coord.z-this.maxzoom):1,i={url:s(t.coord.url(this.tiles,this.maxzoom,this.scheme),this.url),uid:t.uid,coord:t.coord,zoom:t.coord.z,tileSize:this.tileSize*n,source:this.id,overscaling:n,angle:this.map.transform.angle,pitch:this.map.transform.pitch,showCollisionBoxes:this.map.showCollisionBoxes};t.workerID?\"loading\"===t.state?t.reloadCallback=e:(i.rawTileData=t.rawTileData,this.dispatcher.send(\"reload tile\",i,r.bind(this),t.workerID)):t.workerID=this.dispatcher.send(\"load tile\",i,r.bind(this))},abortTile:function(t){this.dispatcher.send(\"abort tile\",{uid:t.uid,source:this.id},null,t.workerID)},unloadTile:function(t){t.unloadVectorData(this.map.painter),this.dispatcher.send(\"remove tile\",{uid:t.uid,source:this.id},null,t.workerID)}})},{\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./load_tilejson\":323}],332:[function(t,e,r){\"use strict\";function n(t,e,r){this.actor=t,this.styleLayers=e,r&&(this.loadVectorData=r),this.loading={},this.loaded={}}var i=t(\"../util/ajax\"),a=t(\"vector-tile\"),o=t(\"pbf\"),s=t(\"./worker_tile\");e.exports=n,n.prototype={loadTile:function(t,e){function r(t,r){return delete this.loading[n][i],t?e(t):r?(a.data=r.tile,a.parse(a.data,this.styleLayers.getLayerFamilies(),this.actor,r.rawTileData,e),this.loaded[n]=this.loaded[n]||{},void(this.loaded[n][i]=a)):e(null,null)}var n=t.source,i=t.uid;this.loading[n]||(this.loading[n]={});var a=this.loading[n][i]=new s(t);a.abort=this.loadVectorData(t,r.bind(this))},reloadTile:function(t,e){var r=this.loaded[t.source],n=t.uid;if(r&&r[n]){var i=r[n];i.parse(i.data,this.styleLayers.getLayerFamilies(),this.actor,t.rawTileData,e)}},abortTile:function(t){var e=this.loading[t.source],r=t.uid;e&&e[r]&&e[r].abort&&(e[r].abort(),delete e[r])},removeTile:function(t){var e=this.loaded[t.source],r=t.uid;e&&e[r]&&delete e[r]},loadVectorData:function(t,e){function r(t,r){if(t)return e(t);var n=new a.VectorTile(new o(new Uint8Array(r)));e(t,{tile:n,rawTileData:r})}var n=i.getArrayBuffer(t.url,r.bind(this));return function(){n.abort()}},redoPlacement:function(t,e){var r=this.loaded[t.source],n=this.loading[t.source],i=t.uid;if(r&&r[i]){var a=r[i],o=a.redoPlacement(t.angle,t.pitch,t.showCollisionBoxes);o.result&&e(null,o.result,o.transferables)}else n&&n[i]&&(n[i].angle=t.angle)}}},{\"../util/ajax\":386,\"./worker_tile\":335,pbf:436,\"vector-tile\":505}],333:[function(t,e,r){\"use strict\";function n(t,e){this.id=t,this.urls=e.urls,this.coordinates=e.coordinates,u.getVideo(e.urls,function(t,r){if(t)return this.fire(\"error\",{error:t});this.video=r,this.video.loop=!0;var n;this.video.addEventListener(\"playing\",function(){n=this.map.style.animationLoop.set(1/0),this.map._rerender()}.bind(this)),this.video.addEventListener(\"pause\",function(){this.map.style.animationLoop.cancel(n)}.bind(this)),this.map&&(this.video.play(),this.setCoordinates(e.coordinates)),this.fire(\"load\")}.bind(this))}var i=t(\"../util/util\"),a=t(\"./tile_coord\"),o=t(\"../geo/lng_lat\"),s=t(\"point-geometry\"),l=t(\"../util/evented\"),u=t(\"../util/ajax\"),c=t(\"../data/bucket\").EXTENT,h=t(\"../render/draw_raster\").RasterBoundsArray,f=t(\"../data/buffer\"),d=t(\"../render/vertex_array_object\");e.exports=n,n.prototype=i.inherit(l,{minzoom:0,maxzoom:22,tileSize:512,roundZoom:!0,getVideo:function(){return this.video},onAdd:function(t){this.map||(this.map=t,this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},setCoordinates:function(t){this.coordinates=t;var e=this.map,r=t.map(function(t){return e.transform.locationCoordinate(o.convert(t)).zoomTo(0)}),n=this.centerCoord=i.getCoordinatesCenter(r);return n.column=Math.round(n.column),n.row=Math.round(n.row),this.minzoom=this.maxzoom=n.zoom,this._coord=new a(n.zoom,n.column,n.row),this._tileCoords=r.map(function(t){var e=t.zoomTo(n.zoom);return new s(Math.round((e.column-n.column)*c),Math.round((e.row-n.row)*c))}),this.fire(\"change\"),this},_setTile:function(t){this._prepared=!1,this.tile=t;var e=32767,r=new h;r.emplaceBack(this._tileCoords[0].x,this._tileCoords[0].y,0,0),r.emplaceBack(this._tileCoords[1].x,this._tileCoords[1].y,e,0),r.emplaceBack(this._tileCoords[3].x,this._tileCoords[3].y,0,e),r.emplaceBack(this._tileCoords[2].x,this._tileCoords[2].y,e,e),this.tile.buckets={},this.tile.boundsBuffer=new f(r.serialize(),h.serialize(),f.BufferType.VERTEX),this.tile.boundsVAO=new d,this.tile.state=\"loaded\"},prepare:function(){if(!(this.video.readyState<2)&&this.tile){var t=this.map.painter.gl;this._prepared?(t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texSubImage2D(t.TEXTURE_2D,0,0,0,t.RGBA,t.UNSIGNED_BYTE,this.video)):(this._prepared=!0,this.tile.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.tile.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texImage2D(t.TEXTURE_2D,0,t.RGBA,t.RGBA,t.UNSIGNED_BYTE,this.video)),this._currentTime=this.video.currentTime}},loadTile:function(t,e){this._coord&&this._coord.toString()===t.coord.toString()?(this._setTile(t),e(null)):(t.state=\"errored\",e(null))},serialize:function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}}})},{\"../data/bucket\":290,\"../data/buffer\":295,\"../geo/lng_lat\":300,\"../render/draw_raster\":312,\"../render/vertex_array_object\":318,\"../util/ajax\":386,\"../util/evented\":395,\"../util/util\":403,\"./tile_coord\":330,\"point-geometry\":442}],334:[function(t,e,r){\"use strict\";function n(t){this.self=t,this.actor=new a(t,this);var e={getLayers:function(){return this.layers}.bind(this),getLayerFamilies:function(){return this.layerFamilies}.bind(this)};this.workerSources={vector:new l(this.actor,e),geojson:new u(this.actor,e)},this.self.registerWorkerSource=function(t,r){if(this.workerSources[t])throw new Error('Worker source with name \"'+t+'\" already registered.');this.workerSources[t]=new r(this.actor,e)}.bind(this)}function i(t){var e={};for(var r in t){var n=t[r],i=n.ref||n.id,a=t[i];a.layout&&\"none\"===a.layout.visibility||(e[i]=e[i]||[],r===i?e[i].unshift(n):e[i].push(n))}return e}var a=t(\"../util/actor\"),o=t(\"../style/style_layer\"),s=t(\"../util/util\"),l=t(\"./vector_tile_worker_source\"),u=t(\"./geojson_worker_source\");e.exports=function(t){return new n(t)},s.extend(n.prototype,{\"set layers\":function(t){function e(t){var e=o.create(t,t.ref&&r.layers[t.ref]);e.updatePaintTransitions({},{transition:!1}),r.layers[e.id]=e}this.layers={};for(var r=this,n=[],a=0;a<t.length;a++){var s=t[a];\"fill\"!==s.type&&\"line\"!==s.type&&\"circle\"!==s.type&&\"symbol\"!==s.type||(s.ref?n.push(a):e(s))}for(var l=0;l<n.length;l++)e(t[n[l]]);this.layerFamilies=i(this.layers)},\"update layers\":function(t){function e(t){var e=a.layers[t.ref];a.layers[t.id]?a.layers[t.id].set(t,e):a.layers[t.id]=o.create(t,e),a.layers[t.id].updatePaintTransitions({},{transition:!1})}var r,n,a=this;for(r in t)n=t[r],n.ref&&e(n);for(r in t)n=t[r],n.ref||e(n);this.layerFamilies=i(this.layers)},\"load tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].loadTile(t,e)},\"reload tile\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].reloadTile(t,e)},\"abort tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].abortTile(t)},\"remove tile\":function(t){var e=t.type||\"vector\";this.workerSources[e].removeTile(t)},\"redo placement\":function(t,e){var r=t.type||\"vector\";this.workerSources[r].redoPlacement(t,e)},\"load worker source\":function(t,e){try{this.self.importScripts(t.url),e()}catch(t){e(t)}}})},{\"../style/style_layer\":342,\"../util/actor\":385,\"../util/util\":403,\"./geojson_worker_source\":320,\"./vector_tile_worker_source\":332}],335:[function(t,e,r){\"use strict\";function n(t){this.coord=t.coord,this.uid=t.uid,this.zoom=t.zoom,this.tileSize=t.tileSize,this.source=t.source,this.overscaling=t.overscaling,this.angle=t.angle,this.pitch=t.pitch,this.showCollisionBoxes=t.showCollisionBoxes}function i(t){return!t.isEmpty()}function a(t){return t.serialize()}function o(t){var e=[];for(var r in t)t[r].getTransferables(e);return e}function s(t){return t.id}var l=t(\"../data/feature_index\"),u=t(\"../symbol/collision_tile\"),c=t(\"../data/bucket\"),h=t(\"../symbol/collision_box\"),f=t(\"../util/dictionary_coder\"),d=t(\"../util/util\"),p=t(\"../symbol/symbol_instances\"),g=t(\"../symbol/symbol_quads\");e.exports=n,n.prototype.parse=function(t,e,r,n,m){function v(t,e){for(var r=0;r<t.length;r++){var n=t.feature(r);n.index=r;for(var i in e)e[i].filter(n)&&e[i].features.push(n)}}function y(t){if(t)return m(t);if(N++,2===N){for(var e=D.length-1;e>=0;e--)x(S,D[e]);b()}}function x(t,e){if(e.populateArrays(k,j,F),\"symbol\"!==e.type)for(var r=0;r<e.features.length;r++){var n=e.features[r];T.insert(n,n.index,e.sourceLayerIndex,e.index)}e.features=null}function b(){S.status=\"done\",S.redoPlacementAfterDone&&(S.redoPlacement(S.angle,S.pitch,null),S.redoPlacementAfterDone=!1);var t=T.serialize(),e=k.serialize(),r=S.collisionBoxArray.serialize(),s=S.symbolInstancesArray.serialize(),l=S.symbolQuadsArray.serialize(),u=[n].concat(t.transferables).concat(e.transferables),c=P.filter(i);m(null,{buckets:c.map(a),featureIndex:t.data,collisionTile:e.data,collisionBoxArray:r,symbolInstancesArray:s,symbolQuadsArray:l,rawTileData:n},o(c).concat(u))}this.status=\"parsing\",this.data=t,this.collisionBoxArray=new h,this.symbolInstancesArray=new p,this.symbolQuadsArray=new g;var _,w,M,A,k=new u(this.angle,this.pitch,this.collisionBoxArray),T=new l(this.coord,this.overscaling,k,t.layers),E=new f(t.layers?Object.keys(t.layers).sort():[\"_geojsonTileLayer\"]),S=this,L={},z={},C=0;for(var I in e)w=e[I][0],w.source===this.source&&(w.ref||w.minzoom&&this.zoom<w.minzoom||w.maxzoom&&this.zoom>=w.maxzoom||w.layout&&\"none\"===w.layout.visibility||t.layers&&!t.layers[w.sourceLayer]||(A=c.create({layer:w,index:C++,childLayers:e[I],zoom:this.zoom,overscaling:this.overscaling,showCollisionBoxes:this.showCollisionBoxes,collisionBoxArray:this.collisionBoxArray,symbolQuadsArray:this.symbolQuadsArray,symbolInstancesArray:this.symbolInstancesArray,sourceLayerIndex:E.encode(w.sourceLayer||\"_geojsonTileLayer\")}),A.createFilter(),L[w.id]=A,t.layers&&(M=w.sourceLayer,z[M]=z[M]||{},z[M][w.id]=A)));if(t.layers)for(M in z)1===w.version&&d.warnOnce('Vector tile source \"'+this.source+'\" layer \"'+M+'\" does not use vector tile spec v2 and therefore may have some rendering errors.'),w=t.layers[M],w&&v(w,z[M]);else v(t,L);var P=[],D=this.symbolBuckets=[],R=[];T.bucketLayerIDs={};for(var O in L)A=L[O],0!==A.features.length&&(T.bucketLayerIDs[A.index]=A.childLayers.map(s),P.push(A),\"symbol\"===A.type?D.push(A):R.push(A));var F={},j={},N=0;if(D.length>0){for(_=D.length-1;_>=0;_--)D[_].updateIcons(F),D[_].updateFont(j);for(var B in j)j[B]=Object.keys(j[B]).map(Number);F=Object.keys(F),r.send(\"get glyphs\",{uid:this.uid,stacks:j},function(t,e){j=e,y(t)}),F.length?r.send(\"get icons\",{icons:F},function(t,e){F=e,y(t)}):y()}for(_=R.length-1;_>=0;_--)x(this,R[_]);if(0===D.length)return b()},n.prototype.redoPlacement=function(t,e,r){if(\"done\"!==this.status)return this.redoPlacementAfterDone=!0,this.angle=t,{};for(var n=new u(t,e,this.collisionBoxArray),s=this.symbolBuckets,l=s.length-1;l>=0;l--)s[l].placeFeatures(n,r);var c=n.serialize(),h=s.filter(i);return{result:{buckets:h.map(a),collisionTile:c.data},transferables:o(h).concat(c.transferables)}}},{\"../data/bucket\":290,\"../data/feature_index\":297,\"../symbol/collision_box\":355,\"../symbol/collision_tile\":357,\"../symbol/symbol_instances\":366,\"../symbol/symbol_quads\":367,\"../util/dictionary_coder\":393,\"../util/util\":403}],336:[function(t,e,r){\"use strict\";function n(){this.n=0,this.times=[]}e.exports=n,n.prototype.stopped=function(){return this.times=this.times.filter(function(t){return t.time>=(new Date).getTime()}),!this.times.length},n.prototype.set=function(t){return this.times.push({id:this.n,time:t+(new Date).getTime()}),this.n++},n.prototype.cancel=function(t){this.times=this.times.filter(function(e){return e.id!==t})}},{}],337:[function(t,e,r){\"use strict\";function n(t){this.base=t,this.retina=s.devicePixelRatio>1;var e=this.retina?\"@2x\":\"\";o.getJSON(l(t,e,\".json\"),function(t,e){return t?void this.fire(\"error\",{error:t}):(this.data=e,void(this.img&&this.fire(\"load\")))}.bind(this)),o.getImage(l(t,e,\".png\"),function(t,e){if(t)return void this.fire(\"error\",{error:t});for(var r=e.getData(),n=e.data=new Uint8Array(r.length),i=0;i<r.length;i+=4){var a=r[i+3]/255;n[i+0]=r[i+0]*a,n[i+1]=r[i+1]*a,n[i+2]=r[i+2]*a,n[i+3]=r[i+3]}this.img=e,this.data&&this.fire(\"load\")}.bind(this))}function i(){}var a=t(\"../util/evented\"),o=t(\"../util/ajax\"),s=t(\"../util/browser\"),l=t(\"../util/mapbox\").normalizeSpriteURL;e.exports=n,n.prototype=Object.create(a),n.prototype.toJSON=function(){return this.base},n.prototype.loaded=function(){return!(!this.data||!this.img)},n.prototype.resize=function(){if(s.devicePixelRatio>1!==this.retina){var t=new n(this.base);t.on(\"load\",function(){this.img=t.img,this.data=t.data,this.retina=t.retina}.bind(this))}},i.prototype={x:0,y:0,width:0,height:0,pixelRatio:1,sdf:!1},n.prototype.getSpritePosition=function(t){if(!this.loaded())return new i;var e=this.data&&this.data[t];return e&&this.img?e:new i}},{\"../util/ajax\":386,\"../util/browser\":387,\"../util/evented\":395,\"../util/mapbox\":400}],338:[function(t,e,r){\"use strict\";var n=t(\"csscolorparser\").parseCSSColor,i=t(\"../util/util\"),a=t(\"./style_function\"),o={};e.exports=function t(e){if(a.isFunctionDefinition(e))return i.extend({},e,{stops:e.stops.map(function(e){return[e[0],t(e[1])]})});if(\"string\"==typeof e){if(!o[e]){var r=n(e);if(!r)throw new Error(\"Invalid color \"+e);o[e]=[r[0]/255*r[3],r[1]/255*r[3],r[2]/255*r[3],r[3]]}return o[e]}throw new Error(\"Invalid color \"+e)}},{\"../util/util\":403,\"./style_function\":341,csscolorparser:89}],339:[function(t,e,r){\"use strict\";function n(t,e,r){this.animationLoop=e||new g,this.dispatcher=new p(r||1,this),this.spriteAtlas=new l(1024,1024),this.lineAtlas=new u(256,512),this._layers={},this._order=[],this._groups=[],this.sources={},this.zoomHistory={},c.bindAll([\"_forwardSourceEvent\",\"_forwardTileEvent\",\"_forwardLayerEvent\",\"_redoPlacement\"],this),this._resetUpdates();var n=function(t,e){if(t)return void this.fire(\"error\",{error:t});if(!m.emitErrors(this,m(e))){this._loaded=!0,this.stylesheet=e,this.updateClasses();var r=e.sources;for(var n in r)this.addSource(n,r[n]);e.sprite&&(this.sprite=new o(e.sprite),this.sprite.on(\"load\",this.fire.bind(this,\"change\"))),this.glyphSource=new s(e.glyphs),this._resolve(),this.fire(\"load\")}}.bind(this);\"string\"==typeof t?h.getJSON(f(t),n):d.frame(n.bind(this,null,t)),this.on(\"source.load\",function(t){var e=t.source;if(e&&e.vectorLayerIds)for(var r in this._layers){var n=this._layers[r];n.source===e.id&&this._validateLayer(n)}})}var i=t(\"../util/evented\"),a=t(\"./style_layer\"),o=t(\"./image_sprite\"),s=t(\"../symbol/glyph_source\"),l=t(\"../symbol/sprite_atlas\"),u=t(\"../render/line_atlas\"),c=t(\"../util/util\"),h=t(\"../util/ajax\"),f=t(\"../util/mapbox\").normalizeStyleURL,d=t(\"../util/browser\"),p=t(\"../util/dispatcher\"),g=t(\"./animation_loop\"),m=t(\"./validate_style\"),v=t(\"../source/source\"),y=t(\"../source/query_features\"),x=t(\"../source/source_cache\"),b=t(\"./style_spec\"),_=t(\"./style_function\");e.exports=n,n.prototype=c.inherit(i,{_loaded:!1,_validateLayer:function(t){var e=this.sources[t.source];t.sourceLayer&&e&&e.vectorLayerIds&&e.vectorLayerIds.indexOf(t.sourceLayer)===-1&&this.fire(\"error\",{error:new Error('Source layer \"'+t.sourceLayer+'\" does not exist on source \"'+e.id+'\" as specified by style layer \"'+t.id+'\"')})},loaded:function(){if(!this._loaded)return!1;if(Object.keys(this._updates.sources).length)return!1;for(var t in this.sources)if(!this.sources[t].loaded())return!1;return!(this.sprite&&!this.sprite.loaded())},_resolve:function(){var t,e;this._layers={},this._order=this.stylesheet.layers.map(function(t){return t.id});for(var r=0;r<this.stylesheet.layers.length;r++)e=this.stylesheet.layers[r],\n",
+       "e.ref||(t=a.create(e),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent));for(var n=0;n<this.stylesheet.layers.length;n++)if(e=this.stylesheet.layers[n],e.ref){var i=this.getLayer(e.ref);t=a.create(e,i),this._layers[t.id]=t,t.on(\"error\",this._forwardLayerEvent)}this._groupLayers(),this._updateWorkerLayers()},_groupLayers:function(){var t;this._groups=[];for(var e=0;e<this._order.length;++e){var r=this._layers[this._order[e]];t&&r.source===t.source||(t=[],t.source=r.source,this._groups.push(t)),t.push(r)}},_updateWorkerLayers:function(t){this.dispatcher.broadcast(t?\"update layers\":\"set layers\",this._serializeLayers(t))},_serializeLayers:function(t){t=t||this._order;for(var e=[],r={includeRefProperties:!0},n=0;n<t.length;n++)e.push(this._layers[t[n]].serialize(r));return e},_applyClasses:function(t,e){if(this._loaded){t=t||[],e=e||{transition:!0};var r=this.stylesheet.transition||{},n=this._updates.allPaintProps?this._layers:this._updates.paintProps;for(var i in n){var a=this._layers[i],o=this._updates.paintProps[i];if(this._updates.allPaintProps||o.all)a.updatePaintTransitions(t,e,r,this.animationLoop);else for(var s in o)this._layers[i].updatePaintTransition(s,t,e,r,this.animationLoop)}}},_recalculate:function(t){for(var e in this.sources)this.sources[e].used=!1;this._updateZoomHistory(t),this.rasterFadeDuration=300;for(var r in this._layers){var n=this._layers[r];n.recalculate(t,this.zoomHistory),!n.isHidden(t)&&n.source&&(this.sources[n.source].used=!0)}var i=300;Math.floor(this.z)!==Math.floor(t)&&this.animationLoop.set(i),this.z=t,this.fire(\"zoom\")},_updateZoomHistory:function(t){var e=this.zoomHistory;void 0===e.lastIntegerZoom&&(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=0,e.lastZoom=t),Math.floor(e.lastZoom)<Math.floor(t)?(e.lastIntegerZoom=Math.floor(t),e.lastIntegerZoomTime=Date.now()):Math.floor(e.lastZoom)>Math.floor(t)&&(e.lastIntegerZoom=Math.floor(t+1),e.lastIntegerZoomTime=Date.now()),e.lastZoom=t},_checkLoaded:function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},update:function(t,e){if(!this._updates.changed)return this;if(this._updates.allLayers)this._groupLayers(),this._updateWorkerLayers();else{var r=Object.keys(this._updates.layers);r.length&&this._updateWorkerLayers(r)}var n,i=Object.keys(this._updates.sources);for(n=0;n<i.length;n++)this._reloadSource(i[n]);for(n=0;n<this._updates.events.length;n++){var a=this._updates.events[n];this.fire(a[0],a[1])}return this._applyClasses(t,e),this._updates.changed&&this.fire(\"change\"),this._resetUpdates(),this},_resetUpdates:function(){this._updates={events:[],layers:{},sources:{},paintProps:{}}},addSource:function(t,e){if(this._checkLoaded(),void 0!==this.sources[t])throw new Error(\"There is already a source with this ID\");if(!e.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(e)+\".\");var r=[\"vector\",\"raster\",\"geojson\",\"video\",\"image\"],n=r.indexOf(e.type)>=0;return n&&this._handleErrors(m.source,\"sources.\"+t,e)?this:(e=new x(t,e,this.dispatcher),this.sources[t]=e,e.style=this,e.on(\"load\",this._forwardSourceEvent).on(\"error\",this._forwardSourceEvent).on(\"change\",this._forwardSourceEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.load\",this._forwardTileEvent).on(\"tile.error\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.add\",{source:e}]),this._updates.changed=!0,this)},removeSource:function(t){if(this._checkLoaded(),void 0===this.sources[t])throw new Error(\"There is no source with this ID\");var e=this.sources[t];return delete this.sources[t],delete this._updates.sources[t],e.off(\"load\",this._forwardSourceEvent).off(\"error\",this._forwardSourceEvent).off(\"change\",this._forwardSourceEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.load\",this._forwardTileEvent).off(\"tile.error\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent),this._updates.events.push([\"source.remove\",{source:e}]),this._updates.changed=!0,this},getSource:function(t){return this.sources[t]&&this.sources[t].getSource()},addLayer:function(t,e){if(this._checkLoaded(),!(t instanceof a)){if(this._handleErrors(m.layer,\"layers.\"+t.id,t,!1,{arrayIndex:-1}))return this;var r=t.ref&&this.getLayer(t.ref);t=a.create(t,r)}return this._validateLayer(t),t.on(\"error\",this._forwardLayerEvent),this._layers[t.id]=t,this._order.splice(e?this._order.indexOf(e):1/0,0,t.id),this._updates.allLayers=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.events.push([\"layer.add\",{layer:t}]),this.updateClasses(t.id)},removeLayer:function(t){this._checkLoaded();var e=this._layers[t];if(void 0===e)throw new Error(\"There is no layer with this ID\");for(var r in this._layers)this._layers[r].ref===t&&this.removeLayer(r);return e.off(\"error\",this._forwardLayerEvent),delete this._layers[t],delete this._updates.layers[t],delete this._updates.paintProps[t],this._order.splice(this._order.indexOf(t),1),this._updates.allLayers=!0,this._updates.events.push([\"layer.remove\",{layer:e}]),this._updates.changed=!0,this},getLayer:function(t){return this._layers[t]},getReferentLayer:function(t){var e=this.getLayer(t);return e.ref&&(e=this.getLayer(e.ref)),e},setLayerZoomRange:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return n.minzoom===e&&n.maxzoom===r?this:(null!=e&&(n.minzoom=e),null!=r&&(n.maxzoom=r),this._updateLayer(n))},setFilter:function(t,e){this._checkLoaded();var r=this.getReferentLayer(t);return null!==e&&this._handleErrors(m.filter,\"layers.\"+r.id+\".filter\",e)?this:c.deepEqual(r.filter,e)?this:(r.filter=c.clone(e),this._updateLayer(r))},getFilter:function(t){return this.getReferentLayer(t).filter},setLayoutProperty:function(t,e,r){this._checkLoaded();var n=this.getReferentLayer(t);return c.deepEqual(n.getLayoutProperty(e),r)?this:(n.setLayoutProperty(e,r),this._updateLayer(n))},getLayoutProperty:function(t,e){return this.getReferentLayer(t).getLayoutProperty(e)},setPaintProperty:function(t,e,r,n){this._checkLoaded();var i=this.getLayer(t);if(c.deepEqual(i.getPaintProperty(e,n),r))return this;var a=i.isPaintValueFeatureConstant(e);i.setPaintProperty(e,r,n);var o=!(r&&_.isFunctionDefinition(r)&&\"$zoom\"!==r.property&&void 0!==r.property);return o&&a||(this._updates.layers[t]=!0,i.source&&(this._updates.sources[i.source]=!0)),this.updateClasses(t,e)},getPaintProperty:function(t,e,r){return this.getLayer(t).getPaintProperty(e,r)},updateClasses:function(t,e){if(this._updates.changed=!0,t){var r=this._updates.paintProps;r[t]||(r[t]={}),r[t][e||\"all\"]=!0}else this._updates.allPaintProps=!0;return this},serialize:function(){return c.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:c.mapObject(this.sources,function(t){return t.serialize()}),layers:this._order.map(function(t){return this._layers[t].serialize()},this)},function(t){return void 0!==t})},_updateLayer:function(t){return this._updates.layers[t.id]=!0,t.source&&(this._updates.sources[t.source]=!0),this._updates.changed=!0,this},_flattenRenderedFeatures:function(t){for(var e=[],r=this._order.length-1;r>=0;r--)for(var n=this._order[r],i=0;i<t.length;i++){var a=t[i][n];if(a)for(var o=0;o<a.length;o++)e.push(a[o])}return e},queryRenderedFeatures:function(t,e,r,n){e&&e.filter&&this._handleErrors(m.filter,\"queryRenderedFeatures.filter\",e.filter,!0);var i={};if(e&&e.layers)for(var a=0;a<e.layers.length;a++){var o=e.layers[a];i[this._layers[o].source]=!0}var s=[];for(var l in this.sources)if(!e.layers||i[l]){var u=this.sources[l],c=y.rendered(u,this._layers,t,e,r,n);s.push(c)}return this._flattenRenderedFeatures(s)},querySourceFeatures:function(t,e){e&&e.filter&&this._handleErrors(m.filter,\"querySourceFeatures.filter\",e.filter,!0);var r=this.sources[t];return r?y.source(r,e):[]},addSourceType:function(t,e,r){return v.getType(t)?r(new Error('A source type called \"'+t+'\" already exists.')):(v.setType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"load worker source\",{name:t,url:e.workerSourceURL},r):r(null,null))},_handleErrors:function(t,e,r,n,i){var a=n?m.throwErrors:m.emitErrors,o=t.call(m,c.extend({key:e,style:this.serialize(),value:r,styleSpec:b},i));return a.call(m,this,o)},_remove:function(){this.dispatcher.remove()},_reloadSource:function(t){this.sources[t].reload()},_updateSources:function(t){for(var e in this.sources)this.sources[e].update(t)},_redoPlacement:function(){for(var t in this.sources)this.sources[t].redoPlacement&&this.sources[t].redoPlacement()},_forwardSourceEvent:function(t){this.fire(\"source.\"+t.type,c.extend({source:t.target.getSource()},t))},_forwardTileEvent:function(t){this.fire(t.type,c.extend({source:t.target},t))},_forwardLayerEvent:function(t){this.fire(\"layer.\"+t.type,c.extend({layer:{id:t.target.id}},t))},\"get sprite json\":function(t,e){var r=this.sprite;r.loaded()?e(null,{sprite:r.data,retina:r.retina}):r.on(\"load\",function(){e(null,{sprite:r.data,retina:r.retina})})},\"get icons\":function(t,e){var r=this.sprite,n=this.spriteAtlas;r.loaded()?(n.setSprite(r),n.addIcons(t.icons,e)):r.on(\"load\",function(){n.setSprite(r),n.addIcons(t.icons,e)})},\"get glyphs\":function(t,e){function r(t,r,n){t&&console.error(t),a[n]=r,i--,0===i&&e(null,a)}var n=t.stacks,i=Object.keys(n).length,a={};for(var o in n)this.glyphSource.getSimpleGlyphs(o,n[o],t.uid,r)}})},{\"../render/line_atlas\":315,\"../source/query_features\":325,\"../source/source\":327,\"../source/source_cache\":328,\"../symbol/glyph_source\":360,\"../symbol/sprite_atlas\":365,\"../util/ajax\":386,\"../util/browser\":387,\"../util/dispatcher\":394,\"../util/evented\":395,\"../util/mapbox\":400,\"../util/util\":403,\"./animation_loop\":336,\"./image_sprite\":337,\"./style_function\":341,\"./style_layer\":342,\"./style_spec\":349,\"./validate_style\":351}],340:[function(t,e,r){\"use strict\";function n(t,e){this.value=s.clone(e),this.isFunction=a.isFunctionDefinition(e),this.json=JSON.stringify(this.value);var r=\"color\"===t.type&&this.value?o(this.value):e;if(this.calculate=a[t.function||\"piecewise-constant\"](r),this.isFeatureConstant=this.calculate.isFeatureConstant,this.isZoomConstant=this.calculate.isZoomConstant,\"piecewise-constant\"===t.function&&t.transition&&(this.calculate=i(this.calculate)),!this.isFeatureConstant&&!this.isZoomConstant){this.stopZoomLevels=[];for(var n=[],l=this.value.stops,u=0;u<this.value.stops.length;u++){var c=l[u][0].zoom;this.stopZoomLevels.indexOf(c)<0&&(this.stopZoomLevels.push(c),n.push([c,n.length]))}this.calculateInterpolationT=a.interpolated({stops:n,base:e.base})}}function i(t){return function(e,r){var n,i,a,o=e.zoom,s=e.zoomHistory,l=e.duration,u=o%1,c=Math.min((Date.now()-s.lastIntegerZoomTime)/l,1),h=1,f=1;return o>s.lastIntegerZoom?(n=u+(1-u)*c,h*=2,i=t({zoom:o-1},r),a=t({zoom:o},r)):(n=1-(1-c)*u,a=t({zoom:o},r),i=t({zoom:o+1},r),h/=2),void 0===i||void 0===a?void 0:{from:i,fromScale:h,to:a,toScale:f,t:n}}}var a=t(\"./style_function\"),o=t(\"./parse_color\"),s=t(\"../util/util\");e.exports=n},{\"../util/util\":403,\"./parse_color\":338,\"./style_function\":341}],341:[function(t,e,r){\"use strict\";var n=t(\"mapbox-gl-function\");r.interpolated=function(t){var e=n.interpolated(t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r[\"piecewise-constant\"]=function(t){var e=n[\"piecewise-constant\"](t),r=function(t,r){return e(t&&t.zoom,r||{})};return r.isFeatureConstant=e.isFeatureConstant,r.isZoomConstant=e.isZoomConstant,r},r.isFunctionDefinition=n.isFunctionDefinition},{\"mapbox-gl-function\":263}],342:[function(t,e,r){\"use strict\";function n(t,e){this.set(t,e)}function i(t){return t.value}var a=t(\"../util/util\"),o=t(\"./style_transition\"),s=t(\"./style_declaration\"),l=t(\"./style_spec\"),u=t(\"./validate_style\"),c=t(\"./parse_color\"),h=t(\"../util/evented\");e.exports=n;var f=\"-transition\";n.create=function(e,r){var n={background:t(\"./style_layer/background_style_layer\"),circle:t(\"./style_layer/circle_style_layer\"),fill:t(\"./style_layer/fill_style_layer\"),line:t(\"./style_layer/line_style_layer\"),raster:t(\"./style_layer/raster_style_layer\"),symbol:t(\"./style_layer/symbol_style_layer\")};return new n[(r||e).type](e,r)},n.prototype=a.inherit(h,{set:function(t,e){this.id=t.id,this.ref=t.ref,this.metadata=t.metadata,this.type=(e||t).type,this.source=(e||t).source,this.sourceLayer=(e||t)[\"source-layer\"],this.minzoom=(e||t).minzoom,this.maxzoom=(e||t).maxzoom,this.filter=(e||t).filter,this.paint={},this.layout={},this._paintSpecifications=l[\"paint_\"+this.type],this._layoutSpecifications=l[\"layout_\"+this.type],this._paintTransitions={},this._paintTransitionOptions={},this._paintDeclarations={},this._layoutDeclarations={},this._layoutFunctions={};var r,n;for(var i in t){var a=i.match(/^paint(?:\\.(.*))?$/);if(a){var o=a[1]||\"\";for(r in t[i])this.setPaintProperty(r,t[i][r],o)}}if(this.ref)this._layoutDeclarations=e._layoutDeclarations;else for(n in t.layout)this.setLayoutProperty(n,t.layout[n]);for(r in this._paintSpecifications)this.paint[r]=this.getPaintValue(r);for(n in this._layoutSpecifications)this._updateLayoutValue(n)},setLayoutProperty:function(t,e){if(null==e)delete this._layoutDeclarations[t];else{var r=\"layers.\"+this.id+\".layout.\"+t;if(this._handleErrors(u.layoutProperty,r,t,e))return;this._layoutDeclarations[t]=new s(this._layoutSpecifications[t],e)}this._updateLayoutValue(t)},getLayoutProperty:function(t){return this._layoutDeclarations[t]&&this._layoutDeclarations[t].value},getLayoutValue:function(t,e,r){var n=this._layoutSpecifications[t],i=this._layoutDeclarations[t];return i?i.calculate(e,r):n.default},setPaintProperty:function(t,e,r){var n=\"layers.\"+this.id+(r?'[\"paint.'+r+'\"].':\".paint.\")+t;if(a.endsWith(t,f))if(this._paintTransitionOptions[r||\"\"]||(this._paintTransitionOptions[r||\"\"]={}),null===e||void 0===e)delete this._paintTransitionOptions[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintTransitionOptions[r||\"\"][t]=e}else if(this._paintDeclarations[r||\"\"]||(this._paintDeclarations[r||\"\"]={}),null===e||void 0===e)delete this._paintDeclarations[r||\"\"][t];else{if(this._handleErrors(u.paintProperty,n,t,e))return;this._paintDeclarations[r||\"\"][t]=new s(this._paintSpecifications[t],e)}},getPaintProperty:function(t,e){return e=e||\"\",a.endsWith(t,f)?this._paintTransitionOptions[e]&&this._paintTransitionOptions[e][t]:this._paintDeclarations[e]&&this._paintDeclarations[e][t]&&this._paintDeclarations[e][t].value},getPaintValue:function(t,e,r){var n=this._paintSpecifications[t],i=this._paintTransitions[t];return i?i.calculate(e,r):\"color\"===n.type&&n.default?c(n.default):n.default},getPaintValueStopZoomLevels:function(t){var e=this._paintTransitions[t];return e?e.declaration.stopZoomLevels:[]},getPaintInterpolationT:function(t,e){var r=this._paintTransitions[t];return r.declaration.calculateInterpolationT({zoom:e})},isPaintValueFeatureConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isFeatureConstant},isLayoutValueFeatureConstant:function(t){var e=this._layoutDeclarations[t];return!e||e.isFeatureConstant},isPaintValueZoomConstant:function(t){var e=this._paintTransitions[t];return!e||e.declaration.isZoomConstant},isHidden:function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||(\"none\"===this.layout.visibility||0===this.paint[this.type+\"-opacity\"]))},updatePaintTransitions:function(t,e,r,n){for(var i=a.extend({},this._paintDeclarations[\"\"]),o=0;o<t.length;o++)a.extend(i,this._paintDeclarations[t[o]]);var s;for(s in i)this._applyPaintDeclaration(s,i[s],e,r,n);for(s in this._paintTransitions)s in i||this._applyPaintDeclaration(s,null,e,r,n)},updatePaintTransition:function(t,e,r,n,i){for(var a=this._paintDeclarations[\"\"][t],o=0;o<e.length;o++){var s=this._paintDeclarations[e[o]];s&&s[t]&&(a=s[t])}this._applyPaintDeclaration(t,a,r,n,i)},recalculate:function(t,e){for(var r in this._paintTransitions)this.paint[r]=this.getPaintValue(r,{zoom:t,zoomHistory:e});for(var n in this._layoutFunctions)this.layout[n]=this.getLayoutValue(n,{zoom:t,zoomHistory:e})},serialize:function(t){var e={id:this.id,ref:this.ref,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom};for(var r in this._paintDeclarations){var n=\"\"===r?\"paint\":\"paint.\"+r;e[n]=a.mapObject(this._paintDeclarations[r],i)}return(!this.ref||t&&t.includeRefProperties)&&a.extend(e,{type:this.type,source:this.source,\"source-layer\":this.sourceLayer,filter:this.filter,layout:a.mapObject(this._layoutDeclarations,i)}),a.filterObject(e,function(t,e){return void 0!==t&&!(\"layout\"===e&&!Object.keys(t).length)})},_applyPaintDeclaration:function(t,e,r,n,i){var l=r.transition?this._paintTransitions[t]:void 0,u=this._paintSpecifications[t];if(null!==e&&void 0!==e||(e=new s(u,u.default)),!l||l.declaration.json!==e.json){var c=a.extend({duration:300,delay:0},n,this.getPaintProperty(t+f)),h=this._paintTransitions[t]=new o(u,e,l,c);h.instant()||(h.loopID=i.set(h.endTime-Date.now())),l&&i.cancel(l.loopID)}},_updateLayoutValue:function(t){var e=this._layoutDeclarations[t];e&&e.isFunction?this._layoutFunctions[t]=!0:(delete this._layoutFunctions[t],this.layout[t]=this.getLayoutValue(t))},_handleErrors:function(t,e,r,n){return u.emitErrors(this,t.call(u,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:l,style:{glyphs:!0,sprite:!0}}))}})},{\"../util/evented\":395,\"../util/util\":403,\"./parse_color\":338,\"./style_declaration\":340,\"./style_layer/background_style_layer\":343,\"./style_layer/circle_style_layer\":344,\"./style_layer/fill_style_layer\":345,\"./style_layer/line_style_layer\":346,\"./style_layer/raster_style_layer\":347,\"./style_layer/symbol_style_layer\":348,\"./style_spec\":349,\"./style_transition\":350,\"./validate_style\":351}],343:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],344:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],345:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValue.call(this,\"fill-color\",e,r):a.prototype.getPaintValue.call(this,t,e,r)},getPaintValueStopZoomLevels:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintValueStopZoomLevels.call(this,\"fill-color\"):a.prototype.getPaintValueStopZoomLevels.call(this,arguments)},getPaintInterpolationT:function(t,e){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.getPaintInterpolationT.call(this,\"fill-color\",e):a.prototype.getPaintInterpolationT.call(this,t,e)},isPaintValueFeatureConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueFeatureConstant.call(this,\"fill-color\"):a.prototype.isPaintValueFeatureConstant.call(this,t)},isPaintValueZoomConstant:function(t){return\"fill-outline-color\"===t&&void 0===this.getPaintProperty(\"fill-outline-color\")?a.prototype.isPaintValueZoomConstant.call(this,\"fill-color\"):a.prototype.isPaintValueZoomConstant.call(this,t)}}),e.exports=n},{\"../../util/util\":403,\"../style_layer\":342}],346:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{getPaintValue:function(t,e,r){var n=a.prototype.getPaintValue.apply(this,arguments);if(n&&\"line-dasharray\"===t){var i=Math.floor(e.zoom);this._flooredZoom!==i&&(this._flooredZoom=i,this._flooredLineWidth=this.getPaintValue(\"line-width\",e,r)),n.fromScale*=this._flooredLineWidth,n.toScale*=this._flooredLineWidth}return n}})},{\"../../util/util\":403,\"../style_layer\":342}],347:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{})},{\"../../util/util\":403,\"../style_layer\":342}],348:[function(t,e,r){\"use strict\";function n(){a.apply(this,arguments)}var i=t(\"../../util/util\"),a=t(\"../style_layer\");e.exports=n,n.prototype=i.inherit(a,{isHidden:function(){if(a.prototype.isHidden.apply(this,arguments))return!0;var t=0===this.paint[\"text-opacity\"]||!this.layout[\"text-field\"],e=0===this.paint[\"icon-opacity\"]||!this.layout[\"icon-image\"];return!(!t||!e)},getLayoutValue:function(t,e,r){return(\"text-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"text-rotation-alignment\"))&&(\"icon-rotation-alignment\"!==t||\"line\"!==this.getLayoutValue(\"symbol-placement\",e,r)||this.getLayoutProperty(\"icon-rotation-alignment\"))?\"text-pitch-alignment\"!==t||this.getLayoutProperty(\"text-pitch-alignment\")?a.prototype.getLayoutValue.apply(this,arguments):this.getLayoutValue(\"text-rotation-alignment\"):\"map\"}})},{\"../../util/util\":403,\"../style_layer\":342}],349:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/reference/latest.min\")},{\"mapbox-gl-style-spec/reference/latest.min\":286}],350:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.declaration=e,this.startTime=this.endTime=(new Date).getTime(),\"piecewise-constant\"===t.function&&t.transition?this.interp=i:this.interp=o[t.type],this.oldTransition=r,this.duration=n.duration||0,this.delay=n.delay||0,this.instant()||(this.endTime=this.startTime+this.duration+this.delay,this.ease=a.easeCubicInOut),r&&r.endTime<=this.startTime&&delete r.oldTransition}function i(t,e,r){return void 0===(t&&t.to)||void 0===(e&&e.to)?void 0:{from:t.to,fromScale:t.toScale,to:e.to,toScale:e.toScale,t:r}}var a=t(\"../util/util\"),o=t(\"../util/interpolate\");e.exports=n,n.prototype.instant=function(){return!this.oldTransition||!this.interp||0===this.duration&&0===this.delay},n.prototype.calculate=function(t,e){var r=this.declaration.calculate(a.extend({},t,{duration:this.duration}),e);if(this.instant())return r;var n=t.time||Date.now();if(n<this.endTime){var i=this.oldTransition.calculate(a.extend({},t,{time:this.startTime}),e),o=this.ease((n-this.startTime-this.delay)/this.duration);r=this.interp(i,r,o)}return r}},{\"../util/interpolate\":397,\"../util/util\":403}],351:[function(t,e,r){\"use strict\";e.exports=t(\"mapbox-gl-style-spec/lib/validate_style.min\"),e.exports.emitErrors=function(t,e){if(e&&e.length){for(var r=0;r<e.length;r++)t.fire(\"error\",{error:new Error(e[r].message)});return!0}return!1},e.exports.throwErrors=function(t,e){if(e)for(var r=0;r<e.length;r++)throw new Error(e[r].message)}},{\"mapbox-gl-style-spec/lib/validate_style.min\":285}],352:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.x=t,this.y=e,this.angle=r,void 0!==n&&(this.segment=n)}var i=t(\"point-geometry\");e.exports=n,n.prototype=Object.create(i.prototype),n.prototype.clone=function(){return new n(this.x,this.y,this.angle,this.segment)}},{\"point-geometry\":442}],353:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){if(void 0===e.segment)return!0;for(var a=e,o=e.segment+1,s=0;s>-r/2;){if(o--,o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;for(var l=[],u=0;s<r/2;){var c=t[o-1],h=t[o],f=t[o+1];if(!f)return!1;var d=c.angleTo(h)-h.angleTo(f);for(d=Math.abs((d+3*Math.PI)%(2*Math.PI)-Math.PI),l.push({distance:s,angleDelta:d}),u+=d;s-l[0].distance>n;)u-=l.shift().angleDelta;if(u>i)return!1;o++,s+=h.dist(f)}return!0}e.exports=n},{}],354:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){for(var o=[],s=0;s<t.length;s++)for(var l,u=t[s],c=0;c<u.length-1;c++){var h=u[c],f=u[c+1];h.x<e&&f.x<e||(h.x<e?h=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round():f.x<e&&(f=new i(e,h.y+(f.y-h.y)*((e-h.x)/(f.x-h.x)))._round()),h.y<r&&f.y<r||(h.y<r?h=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round():f.y<r&&(f=new i(h.x+(f.x-h.x)*((r-h.y)/(f.y-h.y)),r)._round()),h.x>=n&&f.x>=n||(h.x>=n?h=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round():f.x>=n&&(f=new i(n,h.y+(f.y-h.y)*((n-h.x)/(f.x-h.x)))._round()),h.y>=a&&f.y>=a||(h.y>=a?h=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round():f.y>=a&&(f=new i(h.x+(f.x-h.x)*((a-h.y)/(f.y-h.y)),a)._round()),l&&h.equals(l[l.length-1])||(l=[h],o.push(l)),l.push(f)))))}return o}var i=t(\"point-geometry\");e.exports=n},{\"point-geometry\":442}],355:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int16\",name:\"x1\"},{type:\"Int16\",name:\"y1\"},{type:\"Int16\",name:\"x2\"},{type:\"Int16\",name:\"y2\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Uint32\",name:\"featureIndex\"},{type:\"Uint16\",name:\"sourceLayerIndex\"},{type:\"Uint16\",name:\"bucketIndex\"},{type:\"Int16\",name:\"bbox0\"},{type:\"Int16\",name:\"bbox1\"},{type:\"Int16\",name:\"bbox2\"},{type:\"Int16\",name:\"bbox3\"},{type:\"Float32\",name:\"placementScale\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"point-geometry\":442}],356:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u,c){var h=o.top*s-l,f=o.bottom*s+l,d=o.left*s-l,p=o.right*s+l;if(this.boxStartIndex=t.length,u){var g=f-h,m=p-d;if(g>0)if(g=Math.max(10*s,g),c){var v=e[r.segment+1].sub(e[r.segment])._unit()._mult(m),y=[r.sub(v),r.add(v)];this._addLineCollisionBoxes(t,y,r,0,m,g,n,i,a)}else this._addLineCollisionBoxes(t,e,r,r.segment,m,g,n,i,a)}else t.emplaceBack(r.x,r.y,d,h,p,f,1/0,n,i,a,0,0,0,0,0);this.boxEndIndex=t.length}e.exports=n,n.prototype._addLineCollisionBoxes=function(t,e,r,n,i,a,o,s,l){var u=a/2,c=Math.floor(i/u),h=-a/2,f=this.boxes,d=r,p=n+1,g=h;do{if(p--,p<0)return f;g-=e[p].dist(d),d=e[p]}while(g>-i/2);for(var m=e[p].dist(e[p+1]),v=0;v<c;v++){for(var y=-i/2+v*u;g+m<y;){if(g+=m,p++,p+1>=e.length)return f;m=e[p].dist(e[p+1])}var x=y-g,b=e[p],_=e[p+1],w=_.sub(b)._unit()._mult(x)._add(b)._round(),M=Math.max(Math.abs(y-h)-u/2,0),A=i/2/M;t.emplaceBack(w.x,w.y,-a/2,-a/2,a/2,a/2,A,o,s,l,0,0,0,0,0)}return f}},{}],357:[function(t,e,r){\"use strict\";function n(t,e,r){if(\"object\"==typeof t){var n=t;r=e,t=n.angle,e=n.pitch,this.grid=new o(n.grid),this.ignoredGrid=new o(n.ignoredGrid)}else this.grid=new o(a,12,6),this.ignoredGrid=new o(a,12,0);this.angle=t,this.pitch=e;var i=Math.sin(t),s=Math.cos(t);if(this.rotationMatrix=[s,-i,i,s],this.reverseRotationMatrix=[s,i,-i,s],this.yStretch=1/Math.cos(e/180*Math.PI),this.yStretch=Math.pow(this.yStretch,1.3),this.collisionBoxArray=r,0===r.length){r.emplaceBack();var l=32767;r.emplaceBack(0,0,0,-l,0,l,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(a,0,0,-l,0,l,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,0,-l,0,l,0,l,0,0,0,0,0,0,0,0,0),r.emplaceBack(0,a,-l,0,l,0,l,0,0,0,0,0,0,0,0,0)}this.tempCollisionBox=r.get(0),this.edges=[r.get(1),r.get(2),r.get(3),r.get(4)]}var i=t(\"point-geometry\"),a=t(\"../data/bucket\").EXTENT,o=t(\"grid-index\");e.exports=n,n.prototype.serialize=function(){var t={angle:this.angle,pitch:this.pitch,grid:this.grid.toArrayBuffer(),ignoredGrid:this.ignoredGrid.toArrayBuffer()};return{data:t,transferables:[t.grid,t.ignoredGrid]}},n.prototype.minScale=.25,n.prototype.maxScale=2,n.prototype.placeCollisionFeature=function(t,e,r){for(var n=this.collisionBoxArray,a=this.minScale,o=this.rotationMatrix,s=this.yStretch,l=t.boxStartIndex;l<t.boxEndIndex;l++){var u=n.get(l),c=u.anchorPoint._matMult(o),h=c.x,f=c.y,d=h+u.x1,p=f+u.y1*s,g=h+u.x2,m=f+u.y2*s;if(u.bbox0=d,u.bbox1=p,u.bbox2=g,u.bbox3=m,!e)for(var v=this.grid.query(d,p,g,m),y=0;y<v.length;y++){var x=n.get(v[y]),b=x.anchorPoint._matMult(o);if(a=this.getPlacementScale(a,c,u,b,x),a>=this.maxScale)return a}if(r){var _;if(this.angle){var w=this.reverseRotationMatrix,M=new i(u.x1,u.y1).matMult(w),A=new i(u.x2,u.y1).matMult(w),k=new i(u.x1,u.y2).matMult(w),T=new i(u.x2,u.y2).matMult(w);_=this.tempCollisionBox,_.anchorPointX=u.anchorPoint.x,_.anchorPointY=u.anchorPoint.y,_.x1=Math.min(M.x,A.x,k.x,T.x),_.y1=Math.min(M.y,A.x,k.x,T.x),_.x2=Math.max(M.x,A.x,k.x,T.x),_.y2=Math.max(M.y,A.x,k.x,T.x),_.maxScale=u.maxScale}else _=u;for(var E=0;E<this.edges.length;E++){var S=this.edges[E];if(a=this.getPlacementScale(a,u.anchorPoint,_,S.anchorPoint,S),a>=this.maxScale)return a}}}return a},n.prototype.queryRenderedSymbols=function(t,e,r,n,a){var o={},s=[],l=this.collisionBoxArray,u=this.rotationMatrix,c=new i(t,e)._matMult(u),h=this.tempCollisionBox;h.anchorX=c.x,h.anchorY=c.y,h.x1=0,h.y1=0,h.x2=r-t,h.y2=n-e,h.maxScale=a,a=h.maxScale;for(var f=[c.x+h.x1/a,c.y+h.y1/a*this.yStretch,c.x+h.x2/a,c.y+h.y2/a*this.yStretch],d=this.grid.query(f[0],f[1],f[2],f[3]),p=this.ignoredGrid.query(f[0],f[1],f[2],f[3]),g=0;g<p.length;g++)d.push(p[g]);for(var m=0;m<d.length;m++){var v=l.get(d[m]),y=v.sourceLayerIndex,x=v.featureIndex;if(void 0===o[y]&&(o[y]={}),!o[y][x]){var b=v.anchorPoint.matMult(u),_=this.getPlacementScale(this.minScale,c,h,b,v);_>=a&&(o[y][x]=!0,s.push(d[m]))}}return s},n.prototype.getPlacementScale=function(t,e,r,n,i){var a=e.x-n.x,o=e.y-n.y,s=(i.x1-r.x2)/a,l=(i.x2-r.x1)/a,u=(i.y1-r.y2)*this.yStretch/o,c=(i.y2-r.y1)*this.yStretch/o;(isNaN(s)||isNaN(l))&&(s=l=1),(isNaN(u)||isNaN(c))&&(u=c=1);var h=Math.min(Math.max(s,l),Math.max(u,c)),f=i.maxScale,d=r.maxScale;return h>f&&(h=f),h>d&&(h=d),h>t&&h>=i.placementScale&&(t=h),t},n.prototype.insertCollisionFeature=function(t,e,r){for(var n=r?this.ignoredGrid:this.grid,i=this.collisionBoxArray,a=t.boxStartIndex;a<t.boxEndIndex;a++){var o=i.get(a);o.placementScale=e,e<this.maxScale&&n.insert(a,o.bbox0,o.bbox1,o.bbox2,o.bbox3)}}},{\"../data/bucket\":290,\"grid-index\":252,\"point-geometry\":442}],358:[function(t,e,r){\"use strict\";function n(t,e,r,n,a,o,s,l,u){var c=n?.6*o*s:0,h=Math.max(n?n.right-n.left:0,a?a.right-a.left:0),f=0===t[0].x||t[0].x===u||0===t[0].y||t[0].y===u;e-h*s<e/4&&(e=h*s+e/4);var d=2*o,p=f?e/2*l%e:(h/2+d)*s*l%e;return i(t,p,e,c,r,h*s,f,!1,u)}function i(t,e,r,n,l,u,c,h,f){for(var d=u/2,p=0,g=0;g<t.length-1;g++)p+=t[g].dist(t[g+1]);for(var m=0,v=e-r,y=[],x=0;x<t.length-1;x++){for(var b=t[x],_=t[x+1],w=b.dist(_),M=_.angleTo(b);v+r<m+w;){v+=r;var A=(v-m)/w,k=a(b.x,_.x,A),T=a(b.y,_.y,A);if(k>=0&&k<f&&T>=0&&T<f&&v-d>=0&&v+d<=p){var E=new o(k,T,M,x)._round();n&&!s(t,E,u,n,l)||y.push(E)}}m+=w}return h||y.length||c||(y=i(t,m/2,r,n,l,u,c,!0,f)),y}var a=t(\"../util/interpolate\"),o=t(\"../symbol/anchor\"),s=t(\"./check_max_angle\");e.exports=n},{\"../symbol/anchor\":352,\"../util/interpolate\":397,\"./check_max_angle\":353}],359:[function(t,e,r){\"use strict\";function n(){this.width=s,this.height=s,this.bin=new i(this.width,this.height),this.index={},this.ids={},this.data=new Uint8Array(this.width*this.height)}var i=t(\"shelf-pack\"),a=t(\"../util/util\"),o=4,s=128,l=2048;e.exports=n,n.prototype.getGlyphs=function(){var t,e,r,n={};for(var i in this.ids)t=i.split(\"#\"),e=t[0],r=t[1],n[e]||(n[e]=[]),n[e].push(r);return n},n.prototype.getRects=function(){var t,e,r,n={};for(var i in this.ids)t=i.split(\"#\"),e=t[0],r=t[1],n[e]||(n[e]={}),n[e][r]=this.index[i];return n},n.prototype.addGlyph=function(t,e,r,n){if(!r)return null;var i=e+\"#\"+r.id;if(this.index[i])return this.ids[i].indexOf(t)<0&&this.ids[i].push(t),this.index[i];if(!r.bitmap)return null;var o=r.width+2*n,s=r.height+2*n,l=1,u=o+2*l,c=s+2*l;u+=4-u%4,c+=4-c%4;var h=this.bin.packOne(u,c);if(h||(this.resize(),h=this.bin.packOne(u,c)),!h)return a.warnOnce(\"glyph bitmap overflow\"),null;this.index[i]=h,this.ids[i]=[t];for(var f=this.data,d=r.bitmap,p=0;p<s;p++)for(var g=this.width*(h.y+p+l)+h.x+l,m=o*p,v=0;v<o;v++)f[g+v]=d[m+v];return this.dirty=!0,\n",
+       "h},n.prototype.resize=function(){var t=this.width,e=this.height;if(!(t>=l||e>=l)){this.texture&&(this.gl&&this.gl.deleteTexture(this.texture),this.texture=null),this.width*=o,this.height*=o,this.bin.resize(this.width,this.height);for(var r=new ArrayBuffer(this.width*this.height),n=0;n<e;n++){var i=new Uint8Array(this.data.buffer,e*n,t),a=new Uint8Array(r,e*n*o,t);a.set(i)}this.data=new Uint8Array(r)}},n.prototype.bind=function(t){this.gl=t,this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.LINEAR),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),t.texImage2D(t.TEXTURE_2D,0,t.ALPHA,this.width,this.height,0,t.ALPHA,t.UNSIGNED_BYTE,null))},n.prototype.updateTexture=function(t){this.bind(t),this.dirty&&(t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width,this.height,t.ALPHA,t.UNSIGNED_BYTE,this.data),this.dirty=!1)}},{\"../util/util\":403,\"shelf-pack\":471}],360:[function(t,e,r){\"use strict\";function n(t){this.url=t&&o(t),this.atlases={},this.stacks={},this.loading={}}function i(t,e,r){var n=1;this.advance=t.advance,this.left=t.left-r-n,this.top=t.top+r+n,this.rect=e}function a(t,e,r,n){return n=n||\"abc\",r.replace(\"{s}\",n[t.length%n.length]).replace(\"{fontstack}\",t).replace(\"{range}\",e)}var o=t(\"../util/mapbox\").normalizeGlyphsURL,s=t(\"../util/ajax\").getArrayBuffer,l=t(\"../util/glyphs\"),u=t(\"../symbol/glyph_atlas\"),c=t(\"pbf\");e.exports=n,n.prototype.getSimpleGlyphs=function(t,e,r,n){void 0===this.stacks[t]&&(this.stacks[t]={}),void 0===this.atlases[t]&&(this.atlases[t]=new u);for(var a,o={},s=this.stacks[t],l=this.atlases[t],c=3,h={},f=0,d=0;d<e.length;d++){var p=e[d];if(a=Math.floor(p/256),s[a]){var g=s[a].glyphs[p],m=l.addGlyph(r,t,g,c);g&&(o[p]=new i(g,m,c))}else void 0===h[a]&&(h[a]=[],f++),h[a].push(p)}f||n(void 0,o,t);var v=function(e,a,s){if(!e)for(var u=this.stacks[t][a]=s.stacks[0],d=0;d<h[a].length;d++){var p=h[a][d],g=u.glyphs[p],m=l.addGlyph(r,t,g,c);g&&(o[p]=new i(g,m,c))}f--,f||n(void 0,o,t)}.bind(this);for(var y in h)this.loadRange(t,y,v)},n.prototype.loadRange=function(t,e,r){if(256*e>65535)return r(\"glyphs > 65535 not supported\");void 0===this.loading[t]&&(this.loading[t]={});var n=this.loading[t];if(n[e])n[e].push(r);else{n[e]=[r];var i=256*e+\"-\"+(256*e+255),o=a(t,i,this.url);s(o,function(t,r){for(var i=!t&&new l(new c(new Uint8Array(r))),a=0;a<n[e].length;a++)n[e][a](t,e,i);delete n[e]})}},n.prototype.getGlyphAtlas=function(t){return this.atlases[t]}},{\"../symbol/glyph_atlas\":359,\"../util/ajax\":386,\"../util/glyphs\":396,\"../util/mapbox\":400,pbf:436}],361:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){function n(n){c.push(t[n]),h.push(r[n]),f.push(e[n]),d++}function i(t,e,r){var n=u[t];return delete u[t],u[e]=n,h[n][0].pop(),h[n][0]=h[n][0].concat(r[0]),n}function a(t,e,r){var n=l[e];return delete l[e],l[t]=n,h[n][0].shift(),h[n][0]=r[0].concat(h[n][0]),n}function o(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}var s,l={},u={},c=[],h=[],f=[],d=0;for(s=0;s<t.length;s++){var p=r[s],g=e[s];if(g){var m=o(g,p),v=o(g,p,!0);if(m in u&&v in l&&u[m]!==l[v]){var y=a(m,v,p),x=i(m,v,h[y]);delete l[m],delete u[v],u[o(g,h[x],!0)]=x,h[y]=null}else m in u?i(m,v,p):v in l?a(m,v,p):(n(s),l[m]=d-1,u[v]=d-1)}else n(s)}return{features:c,textFeatures:f,geometries:h}}},{}],362:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s,l,u){this.anchorPoint=t,this.tl=e,this.tr=r,this.bl=n,this.br=i,this.tex=a,this.anchorAngle=o,this.glyphAngle=s,this.minScale=l,this.maxScale=u}function i(t,e,r,i,a,o,u,c,h){var f,d,p,g,m=e.image.rect,v=a.layout,y=1,x=e.left-y,b=x+m.w/e.image.pixelRatio,_=e.top-y,w=_+m.h/e.image.pixelRatio;if(\"none\"!==v[\"icon-text-fit\"]&&u){var M=b-x,A=w-_,k=v[\"text-size\"]/24,T=u.left*k,E=u.right*k,S=u.top*k,L=u.bottom*k,z=E-T,C=L-S,I=v[\"icon-text-fit-padding\"][0],P=v[\"icon-text-fit-padding\"][1],D=v[\"icon-text-fit-padding\"][2],R=v[\"icon-text-fit-padding\"][3],O=\"width\"===v[\"icon-text-fit\"]?.5*(C-A):0,F=\"height\"===v[\"icon-text-fit\"]?.5*(z-M):0,j=\"width\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?z:M,N=\"height\"===v[\"icon-text-fit\"]||\"both\"===v[\"icon-text-fit\"]?C:A;f=new s(T+F-R,S+O-I),d=new s(T+F+P+j,S+O-I),p=new s(T+F+P+j,S+O+D+N),g=new s(T+F-R,S+O+D+N)}else f=new s(x,_),d=new s(b,_),p=new s(b,w),g=new s(x,w);var B=a.getLayoutValue(\"icon-rotate\",c,h)*Math.PI/180;if(o){var U=i[t.segment];if(t.y===U.y&&t.x===U.x&&t.segment+1<i.length){var V=i[t.segment+1];B+=Math.atan2(t.y-V.y,t.x-V.x)+Math.PI}else B+=Math.atan2(t.y-U.y,t.x-U.x)}if(B){var q=Math.sin(B),H=Math.cos(B),G=[H,-q,q,H];f=f.matMult(G),d=d.matMult(G),g=g.matMult(G),p=p.matMult(G)}return[new n(new s(t.x,t.y),f,d,g,p,e.image.rect,0,0,l,1/0)]}function a(t,e,r,i,a,u){for(var c=a.layout[\"text-rotate\"]*Math.PI/180,h=a.layout[\"text-keep-upright\"],f=e.positionedGlyphs,d=[],p=0;p<f.length;p++){var g=f[p],m=g.glyph,v=m.rect;if(v){var y,x=(g.x+m.advance/2)*r,b=l;u?(y=[],b=o(y,t,x,i,t.segment,!0),h&&(b=Math.min(b,o(y,t,x,i,t.segment,!1)))):y=[{anchorPoint:new s(t.x,t.y),offset:0,angle:0,maxScale:1/0,minScale:l}];for(var _=g.x+m.left,w=g.y-m.top,M=_+v.w,A=w+v.h,k=new s(_,w),T=new s(M,w),E=new s(_,A),S=new s(M,A),L=0;L<y.length;L++){var z=y[L],C=k,I=T,P=E,D=S;if(c){var R=Math.sin(c),O=Math.cos(c),F=[O,-R,R,O];C=C.matMult(F),I=I.matMult(F),P=P.matMult(F),D=D.matMult(F)}var j=Math.max(z.minScale,b),N=(t.angle+z.offset+2*Math.PI)%(2*Math.PI),B=(z.angle+z.offset+2*Math.PI)%(2*Math.PI);d.push(new n(z.anchorPoint,C,I,P,D,v,N,B,j,z.maxScale))}}}return d}function o(t,e,r,n,i,a){var o=!a;r<0&&(a=!a),a&&i++;var u=new s(e.x,e.y),c=n[i],h=1/0;r=Math.abs(r);for(var f=l;;){var d=u.dist(c),p=r/d,g=Math.atan2(c.y-u.y,c.x-u.x);if(a||(g+=Math.PI),t.push({anchorPoint:u,offset:o?Math.PI:0,minScale:p,maxScale:h,angle:(g+2*Math.PI)%(2*Math.PI)}),p<=f)break;for(u=c;u.equals(c);)if(i+=a?1:-1,c=n[i],!c)return p;var m=c.sub(u)._unit();u=u.sub(m._mult(d)),h=p}return f}var s=t(\"point-geometry\");e.exports={getIconQuads:i,getGlyphQuads:a,SymbolQuad:n};var l=.5},{\"point-geometry\":442}],363:[function(t,e,r){\"use strict\";function n(t,e,r){for(var n=[],a=0,o=t.length;a<o;a++){var s=i(t[a].properties,e[\"text-field\"]);if(s){s=s.toString();var l=e[\"text-transform\"];\"uppercase\"===l?s=s.toLocaleUpperCase():\"lowercase\"===l&&(s=s.toLocaleLowerCase());for(var u=0;u<s.length;u++)r[s.charCodeAt(u)]=!0;n[a]=s}else n[a]=null}return n}var i=t(\"../util/token\");e.exports=n},{\"../util/token\":402}],364:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.codePoint=t,this.x=e,this.y=r,this.glyph=n}function i(t,e,r,n,i,a){this.positionedGlyphs=t,this.text=e,this.top=r,this.bottom=n,this.left=i,this.right=a}function a(t,e,r,a,s,l,u,c,h){for(var f=[],d=new i(f,t,h[1],h[1],h[0],h[0]),p=-17,g=0,m=p,v=0;v<t.length;v++){var y=t.charCodeAt(v),x=e[y];x&&(f.push(new n(y,g,m,x)),g+=x.advance+c)}return!!f.length&&(o(d,e,a,r,s,l,u,h),d)}function o(t,e,r,n,i,a,o,u){var c=null,d=0,p=0,g=0,m=0,v=t.positionedGlyphs;if(n)for(var y=0;y<v.length;y++){var x=v[y];if(x.x-=d,x.y+=r*g,x.x>n&&null!==c){var b=v[c+1].x;m=Math.max(b,m);for(var _=c+1;_<=y;_++)v[_].y+=r,v[_].x-=b;if(o){var w=c;h[v[c].codePoint]&&w--,s(v,e,p,w,o)}p=c+1,c=null,d+=b,g++}f[x.codePoint]&&(c=y)}var M=v[v.length-1],A=M.x+e[M.codePoint].advance;m=Math.max(m,A);var k=(g+1)*r;s(v,e,p,v.length-1,o),l(v,o,i,a,m,r,g,u),t.top+=-a*k,t.bottom=t.top+k,t.left+=-i*m,t.right=t.left+m}function s(t,e,r,n,i){for(var a=e[t[n].codePoint].advance,o=(t[n].x+a)*i,s=r;s<=n;s++)t[s].x-=o}function l(t,e,r,n,i,a,o,s){for(var l=(e-r)*i+s[0],u=(-n*(o+1)+.5)*a+s[1],c=0;c<t.length;c++)t[c].x+=l,t[c].y+=u}function u(t,e){if(!t||!t.rect)return null;var r=e[\"icon-offset\"][0],n=e[\"icon-offset\"][1],i=r-t.width/2,a=i+t.width,o=n-t.height/2,s=o+t.height;return new c(t,o,s,i,a)}function c(t,e,r,n,i){this.image=t,this.top=e,this.bottom=r,this.left=n,this.right=i}e.exports={shapeText:a,shapeIcon:u};var h={32:!0,8203:!0},f={32:!0,38:!0,43:!0,45:!0,47:!0,173:!0,183:!0,8203:!0,8208:!0,8211:!0}},{}],365:[function(t,e,r){\"use strict\";function n(t,e){this.width=t,this.height=e,this.bin=new o(t,e),this.images={},this.data=!1,this.texture=0,this.filter=0,this.pixelRatio=1,this.dirty=!0}function i(t,e,r,n,i,a,o,s,l,u,c){var h,f,d=n*e+r,p=s*a+o;if(c)for(p-=a,f=-1;f<=u;f++,d=((f+u)%u+n)*e+r,p+=a)for(h=-1;h<=l;h++)i[p+h]=t[d+(h+l)%l];else for(f=0;f<u;f++,d+=e,p+=a)for(h=0;h<l;h++)i[p+h]=t[d+h]}function a(t,e,r,n,i){this.rect=t,this.width=e,this.height=r,this.sdf=n,this.pixelRatio=i}var o=t(\"shelf-pack\"),s=t(\"../util/browser\"),l=t(\"../util/util\");e.exports=n,n.prototype.allocateImage=function(t,e){t/=this.pixelRatio,e/=this.pixelRatio;var r=2,n=t+r+(4-(t+r)%4),i=e+r+(4-(e+r)%4),a=this.bin.packOne(n,i);return a?a:(l.warnOnce(\"SpriteAtlas out of space.\"),null)},n.prototype.getImage=function(t,e){if(this.images[t])return this.images[t];if(!this.sprite)return null;var r=this.sprite.getSpritePosition(t);if(!r.width||!r.height)return null;var n=this.allocateImage(r.width,r.height);if(!n)return null;var i=new a(n,r.width/r.pixelRatio,r.height/r.pixelRatio,r.sdf,r.pixelRatio/this.pixelRatio);return this.images[t]=i,this.copy(n,r,e),i},n.prototype.getPosition=function(t,e){var r=this.getImage(t,e),n=r&&r.rect;if(!n)return null;var i=r.width*r.pixelRatio,a=r.height*r.pixelRatio,o=1;return{size:[r.width,r.height],tl:[(n.x+o)/this.width,(n.y+o)/this.height],br:[(n.x+o+i)/this.width,(n.y+o+a)/this.height]}},n.prototype.allocate=function(){if(!this.data){var t=Math.floor(this.width*this.pixelRatio),e=Math.floor(this.height*this.pixelRatio);this.data=new Uint32Array(t*e);for(var r=0;r<this.data.length;r++)this.data[r]=0}},n.prototype.copy=function(t,e,r){if(this.sprite.img.data){var n=new Uint32Array(this.sprite.img.data.buffer);this.allocate();var a=this.data,o=1;i(n,this.sprite.img.width,e.x,e.y,a,this.width*this.pixelRatio,(t.x+o)*this.pixelRatio,(t.y+o)*this.pixelRatio,e.width,e.height,r),this.dirty=!0}},n.prototype.setSprite=function(t){t&&(this.pixelRatio=s.devicePixelRatio>1?2:1,this.canvas&&(this.canvas.width=this.width*this.pixelRatio,this.canvas.height=this.height*this.pixelRatio)),this.sprite=t},n.prototype.addIcons=function(t,e){for(var r=0;r<t.length;r++)this.getImage(t[r]);e(null,this.images)},n.prototype.bind=function(t,e){var r=!1;this.texture?t.bindTexture(t.TEXTURE_2D,this.texture):(this.texture=t.createTexture(),t.bindTexture(t.TEXTURE_2D,this.texture),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),r=!0);var n=e?t.LINEAR:t.NEAREST;n!==this.filter&&(t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,n),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,n),this.filter=n),this.dirty&&(this.allocate(),r?t.texImage2D(t.TEXTURE_2D,0,t.RGBA,this.width*this.pixelRatio,this.height*this.pixelRatio,0,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)):t.texSubImage2D(t.TEXTURE_2D,0,0,0,this.width*this.pixelRatio,this.height*this.pixelRatio,t.RGBA,t.UNSIGNED_BYTE,new Uint8Array(this.data.buffer)),this.dirty=!1)}},{\"../util/browser\":387,\"../util/util\":403,\"shelf-pack\":471}],366:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=e.exports=new n({members:[{type:\"Uint16\",name:\"textBoxStartIndex\"},{type:\"Uint16\",name:\"textBoxEndIndex\"},{type:\"Uint16\",name:\"iconBoxStartIndex\"},{type:\"Uint16\",name:\"iconBoxEndIndex\"},{type:\"Uint16\",name:\"glyphQuadStartIndex\"},{type:\"Uint16\",name:\"glyphQuadEndIndex\"},{type:\"Uint16\",name:\"iconQuadStartIndex\"},{type:\"Uint16\",name:\"iconQuadEndIndex\"},{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Int8\",name:\"index\"}]});i.extendAll(o.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"point-geometry\":442}],367:[function(t,e,r){\"use strict\";var n=t(\"../util/struct_array\"),i=t(\"../util/util\"),a=t(\"point-geometry\"),o=t(\"./quads\").SymbolQuad,s=e.exports=new n({members:[{type:\"Int16\",name:\"anchorPointX\"},{type:\"Int16\",name:\"anchorPointY\"},{type:\"Float32\",name:\"tlX\"},{type:\"Float32\",name:\"tlY\"},{type:\"Float32\",name:\"trX\"},{type:\"Float32\",name:\"trY\"},{type:\"Float32\",name:\"blX\"},{type:\"Float32\",name:\"blY\"},{type:\"Float32\",name:\"brX\"},{type:\"Float32\",name:\"brY\"},{type:\"Int16\",name:\"texH\"},{type:\"Int16\",name:\"texW\"},{type:\"Int16\",name:\"texX\"},{type:\"Int16\",name:\"texY\"},{type:\"Float32\",name:\"anchorAngle\"},{type:\"Float32\",name:\"glyphAngle\"},{type:\"Float32\",name:\"maxScale\"},{type:\"Float32\",name:\"minScale\"}]});i.extendAll(s.prototype.StructType.prototype,{get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)},get SymbolQuad(){return new o(this.anchorPoint,new a(this.tlX,this.tlY),new a(this.trX,this.trY),new a(this.blX,this.blY),new a(this.brX,this.brY),{x:this.texX,y:this.texY,h:this.texH,w:this.texW,height:this.texH,width:this.texW},this.anchorAngle,this.glyphAngle,this.minScale,this.maxScale)}})},{\"../util/struct_array\":401,\"../util/util\":403,\"./quads\":362,\"point-geometry\":442}],368:[function(t,e,r){\"use strict\";var n=t(\"../util/dom\"),i=t(\"point-geometry\"),a={scrollZoom:t(\"./handler/scroll_zoom\"),boxZoom:t(\"./handler/box_zoom\"),dragRotate:t(\"./handler/drag_rotate\"),dragPan:t(\"./handler/drag_pan\"),keyboard:t(\"./handler/keyboard\"),doubleClickZoom:t(\"./handler/dblclick_zoom\"),touchZoomRotate:t(\"./handler/touch_zoom_rotate\")};e.exports=function(t,e){function r(t){v(\"mouseout\",t)}function o(e){t.stop(),_=n.mousePos(x,e),v(\"mousedown\",e)}function s(e){var r=t.dragRotate&&t.dragRotate.isActive();b&&!r&&v(\"contextmenu\",b),b=null,v(\"mouseup\",e)}function l(e){if(!(t.dragPan&&t.dragPan.isActive()||t.dragRotate&&t.dragRotate.isActive())){for(var r=e.toElement||e.target;r&&r!==x;)r=r.parentNode;r===x&&v(\"mousemove\",e)}}function u(e){t.stop(),y(\"touchstart\",e),!e.touches||e.touches.length>1||(w?(clearTimeout(w),w=null,v(\"dblclick\",e)):w=setTimeout(d,300))}function c(t){y(\"touchmove\",t)}function h(t){y(\"touchend\",t)}function f(t){y(\"touchcancel\",t)}function d(){w=null}function p(t){var e=n.mousePos(x,t);e.equals(_)&&v(\"click\",t)}function g(t){v(\"dblclick\",t),t.preventDefault()}function m(t){b=t,t.preventDefault()}function v(e,r){var i=n.mousePos(x,r);return t.fire(e,{lngLat:t.unproject(i),point:i,originalEvent:r})}function y(e,r){var a=n.touchPos(x,r),o=a.reduce(function(t,e,r,n){return t.add(e.div(n.length))},new i(0,0));return t.fire(e,{lngLat:t.unproject(o),point:o,lngLats:a.map(function(e){return t.unproject(e)},this),points:a,originalEvent:r})}var x=t.getCanvasContainer(),b=null,_=null,w=null;for(var M in a)t[M]=new a[M](t,e),e.interactive&&e[M]&&t[M].enable();x.addEventListener(\"mouseout\",r,!1),x.addEventListener(\"mousedown\",o,!1),x.addEventListener(\"mouseup\",s,!1),x.addEventListener(\"mousemove\",l,!1),x.addEventListener(\"touchstart\",u,!1),x.addEventListener(\"touchend\",h,!1),x.addEventListener(\"touchmove\",c,!1),x.addEventListener(\"touchcancel\",f,!1),x.addEventListener(\"click\",p,!1),x.addEventListener(\"dblclick\",g,!1),x.addEventListener(\"contextmenu\",m,!1)}},{\"../util/dom\":389,\"./handler/box_zoom\":374,\"./handler/dblclick_zoom\":375,\"./handler/drag_pan\":376,\"./handler/drag_rotate\":377,\"./handler/keyboard\":378,\"./handler/scroll_zoom\":379,\"./handler/touch_zoom_rotate\":380,\"point-geometry\":442}],369:[function(t,e,r){\"use strict\";var n=t(\"../util/util\"),i=t(\"../util/interpolate\"),a=t(\"../util/browser\"),o=t(\"../geo/lng_lat\"),s=t(\"../geo/lng_lat_bounds\"),l=t(\"point-geometry\"),u=e.exports=function(){};n.extend(u.prototype,{getCenter:function(){return this.transform.center},setCenter:function(t,e){return this.jumpTo({center:t},e),this},panBy:function(t,e,r){return this.panTo(this.transform.center,n.extend({offset:l.convert(t).mult(-1)},e),r),this},panTo:function(t,e,r){return this.easeTo(n.extend({center:t},e),r)},getZoom:function(){return this.transform.zoom},setZoom:function(t,e){return this.jumpTo({zoom:t},e),this},zoomTo:function(t,e,r){return this.easeTo(n.extend({zoom:t},e),r)},zoomIn:function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},zoomOut:function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},getBearing:function(){return this.transform.bearing},setBearing:function(t,e){return this.jumpTo({bearing:t},e),this},rotateTo:function(t,e,r){return this.easeTo(n.extend({bearing:t},e),r)},resetNorth:function(t,e){return this.rotateTo(0,n.extend({duration:1e3},t),e),this},snapToNorth:function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},getPitch:function(){return this.transform.pitch},setPitch:function(t,e){return this.jumpTo({pitch:t},e),this},fitBounds:function(t,e,r){e=n.extend({padding:0,offset:[0,0],maxZoom:1/0},e),t=s.convert(t);var i=l.convert(e.offset),a=this.transform,o=a.project(t.getNorthWest()),u=a.project(t.getSouthEast()),c=u.sub(o),h=(a.width-2*e.padding-2*Math.abs(i.x))/c.x,f=(a.height-2*e.padding-2*Math.abs(i.y))/c.y;return e.center=a.unproject(o.add(u).div(2)),e.zoom=Math.min(a.scaleZoom(a.scale*Math.min(h,f)),e.maxZoom),e.bearing=0,e.linear?this.easeTo(e,r):this.flyTo(e,r)},jumpTo:function(t,e){this.stop();var r=this.transform,n=!1,i=!1,a=!1;return\"zoom\"in t&&r.zoom!==+t.zoom&&(n=!0,r.zoom=+t.zoom),\"center\"in t&&(r.center=o.convert(t.center)),\"bearing\"in t&&r.bearing!==+t.bearing&&(i=!0,r.bearing=+t.bearing),\"pitch\"in t&&r.pitch!==+t.pitch&&(a=!0,r.pitch=+t.pitch),this.fire(\"movestart\",e).fire(\"move\",e),n&&this.fire(\"zoomstart\",e).fire(\"zoom\",e).fire(\"zoomend\",e),i&&this.fire(\"rotate\",e),a&&this.fire(\"pitch\",e),this.fire(\"moveend\",e)},easeTo:function(t,e){this.stop(),t=n.extend({offset:[0,0],duration:500,easing:n.ease},t);var r,a,s=this.transform,u=l.convert(t.offset),c=this.getZoom(),h=this.getBearing(),f=this.getPitch(),d=\"zoom\"in t?+t.zoom:c,p=\"bearing\"in t?this._normalizeBearing(t.bearing,h):h,g=\"pitch\"in t?+t.pitch:f;\"center\"in t?(r=o.convert(t.center),a=s.centerPoint.add(u)):\"around\"in t?(r=o.convert(t.around),a=s.locationPoint(r)):(a=s.centerPoint.add(u),r=s.pointLocation(a));var m=s.locationPoint(r);return t.animate===!1&&(t.duration=0),this.zooming=d!==c,this.rotating=h!==p,this.pitching=g!==f,t.noMoveStart||this.fire(\"movestart\",e),this.zooming&&this.fire(\"zoomstart\",e),clearTimeout(this._onEaseEnd),this._ease(function(t){this.zooming&&(s.zoom=i(c,d,t)),this.rotating&&(s.bearing=i(h,p,t)),this.pitching&&(s.pitch=i(f,g,t)),s.setLocationAtPoint(r,m.add(a.sub(m)._mult(t))),this.fire(\"move\",e),this.zooming&&this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){t.delayEndEvents?this._onEaseEnd=setTimeout(this._easeToEnd.bind(this,e),t.delayEndEvents):this._easeToEnd(e)}.bind(this),t),this},_easeToEnd:function(t){var e=this.zooming;this.zooming=!1,this.rotating=!1,this.pitching=!1,e&&this.fire(\"zoomend\",t),this.fire(\"moveend\",t)},flyTo:function(t,e){function r(t){var e=(k*k-A*A+(t?-1:1)*L*L*T*T)/(2*(t?k:A)*L*T);return Math.log(Math.sqrt(e*e+1)-e)}function a(t){return(Math.exp(t)-Math.exp(-t))/2}function s(t){return(Math.exp(t)+Math.exp(-t))/2}function u(t){return a(t)/s(t)}this.stop(),t=n.extend({offset:[0,0],speed:1.2,curve:1.42,easing:n.ease},t);var c=this.transform,h=l.convert(t.offset),f=this.getZoom(),d=this.getBearing(),p=this.getPitch(),g=\"center\"in t?o.convert(t.center):this.getCenter(),m=\"zoom\"in t?+t.zoom:f,v=\"bearing\"in t?this._normalizeBearing(t.bearing,d):d,y=\"pitch\"in t?+t.pitch:p;Math.abs(c.center.lng)+Math.abs(g.lng)>180&&(c.center.lng>0&&g.lng<0?g.lng+=360:c.center.lng<0&&g.lng>0&&(g.lng-=360));var x=c.zoomScale(m-f),b=c.point,_=\"center\"in t?c.project(g).sub(h.div(x)):b,w=c.worldSize,M=t.curve,A=Math.max(c.width,c.height),k=A/x,T=_.sub(b).mag();if(\"minZoom\"in t){var E=n.clamp(Math.min(t.minZoom,f,m),c.minZoom,c.maxZoom),S=A/c.zoomScale(E-f);M=Math.sqrt(S/T*2)}var L=M*M,z=r(0),C=function(t){return s(z)/s(z+M*t)},I=function(t){return A*((s(z)*u(z+M*t)-a(z))/L)/T},P=(r(1)-z)/M;if(Math.abs(T)<1e-6){if(Math.abs(A-k)<1e-6)return this.easeTo(t);var D=k<A?-1:1;P=Math.abs(Math.log(k/A))/M,I=function(){return 0},C=function(t){return Math.exp(D*M*t)}}if(\"duration\"in t)t.duration=+t.duration;else{var R=\"screenSpeed\"in t?+t.screenSpeed/M:+t.speed;t.duration=1e3*P/R}return this.zooming=!0,d!==v&&(this.rotating=!0),p!==y&&(this.pitching=!0),this.fire(\"movestart\",e),this.fire(\"zoomstart\",e),this._ease(function(t){var r=t*P,n=I(r);c.zoom=f+c.scaleZoom(1/C(r)),c.center=c.unproject(b.add(_.sub(b).mult(n)),w),this.rotating&&(c.bearing=i(d,v,t)),this.pitching&&(c.pitch=i(p,y,t)),this.fire(\"move\",e),this.fire(\"zoom\",e),this.rotating&&this.fire(\"rotate\",e),this.pitching&&this.fire(\"pitch\",e)},function(){this.zooming=!1,this.rotating=!1,this.pitching=!1,this.fire(\"zoomend\",e),this.fire(\"moveend\",e)},t),this},isEasing:function(){return!!this._abortFn},stop:function(){return this._abortFn&&(this._abortFn(),this._finishEase()),this},_ease:function(t,e,r){this._finishFn=e,this._abortFn=a.timed(function(e){t.call(this,r.easing(e)),1===e&&this._finishEase()},r.animate===!1?0:r.duration,this)},_finishEase:function(){delete this._abortFn;var t=this._finishFn;delete this._finishFn,t.call(this)},_normalizeBearing:function(t,e){t=n.wrap(t,-180,180);var r=Math.abs(t-e);return Math.abs(t-360-e)<r&&(t-=360),Math.abs(t+360-e)<r&&(t+=360),t},_updateEasing:function(t,e,r){var i;if(this.ease){var a=this.ease,o=(Date.now()-a.start)/a.duration,s=a.easing(o+.01)-a.easing(o),l=.27/Math.sqrt(s*s+1e-4)*.01,u=Math.sqrt(.0729-l*l);i=n.bezier(l,u,.25,1)}else i=r?n.bezier.apply(n,r):n.ease;return this.ease={start:(new Date).getTime(),to:Math.pow(2,e),duration:t,easing:i},i}})},{\"../geo/lng_lat\":300,\"../geo/lng_lat_bounds\":301,\"../util/browser\":387,\"../util/interpolate\":397,\"../util/util\":403,\"point-geometry\":442}],370:[function(t,e,r){\"use strict\";function n(t){o.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/dom\"),o=t(\"../../util/util\");e.exports=n,n.createAttributionString=function(t){var e=[];for(var r in t){var n=t[r];n.attribution&&e.indexOf(n.attribution)<0&&e.push(n.attribution)}return e.sort(function(t,e){return t.length-e.length}),e=e.filter(function(t,r){for(var n=r+1;n<e.length;n++)if(e[n].indexOf(t)>=0)return!1;return!0}),e.join(\" | \")},n.prototype=o.inherit(i,{options:{position:\"bottom-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl-attrib\",r=this._container=a.create(\"div\",e,t.getContainer());return this._update(),t.on(\"source.load\",this._update.bind(this)),t.on(\"source.change\",this._update.bind(this)),t.on(\"source.remove\",this._update.bind(this)),t.on(\"moveend\",this._updateEditLink.bind(this)),r},_update:function(){this._map.style&&(this._container.innerHTML=n.createAttributionString(this._map.style.sources)),this._editLink=this._container.getElementsByClassName(\"mapbox-improve-map\")[0],this._updateEditLink()},_updateEditLink:function(){if(this._editLink){var t=this._map.getCenter();this._editLink.href=\"https://www.mapbox.com/map-feedback/#/\"+t.lng+\"/\"+t.lat+\"/\"+Math.round(this._map.getZoom()+1)}}})},{\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],371:[function(t,e,r){\"use strict\";function n(){}var i=t(\"../../util/util\"),a=t(\"../../util/evented\");e.exports=n,n.prototype={addTo:function(t){this._map=t;var e=this._container=this.onAdd(t);if(this.options&&this.options.position){var r=this.options.position,n=t._controlCorners[r];e.className+=\" mapboxgl-ctrl\",r.indexOf(\"bottom\")!==-1?n.insertBefore(e,n.firstChild):n.appendChild(e)}return this},remove:function(){return this._container.parentNode.removeChild(this._container),this.onRemove&&this.onRemove(this._map),this._map=null,this}},i.extend(n.prototype,a)},{\"../../util/evented\":395,\"../../util/util\":403}],372:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}var i=t(\"./control\"),a=t(\"../../util/browser\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n;var l={enableHighAccuracy:!1,timeout:6e3};n.prototype=s.inherit(i,{options:{position:\"top-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl\",r=this._container=o.create(\"div\",e+\"-group\",t.getContainer());return a.supportsGeolocation?(this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._geolocateButton=o.create(\"button\",e+\"-icon \"+e+\"-geolocate\",this._container),this._geolocateButton.type=\"button\",this._geolocateButton.addEventListener(\"click\",this._onClickGeolocate.bind(this)),r):r},_onContextMenu:function(t){t.preventDefault()},_onClickGeolocate:function(){navigator.geolocation.getCurrentPosition(this._success.bind(this),this._error.bind(this),l),this._timeoutId=setTimeout(this._finish.bind(this),1e4)},_success:function(t){this._map.jumpTo({center:[t.coords.longitude,t.coords.latitude],zoom:17,bearing:0,pitch:0}),this.fire(\"geolocate\",t),this._finish()},_error:function(t){this.fire(\"error\",t),this._finish()},_finish:function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0}})},{\"../../util/browser\":387,\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],373:[function(t,e,r){\"use strict\";function n(t){s.setOptions(this,t)}function i(t){return new MouseEvent(t.type,{button:2,buttons:2,bubbles:!0,cancelable:!0,detail:t.detail,view:t.view,screenX:t.screenX,screenY:t.screenY,clientX:t.clientX,clientY:t.clientY,movementX:t.movementX,movementY:t.movementY,ctrlKey:t.ctrlKey,shiftKey:t.shiftKey,altKey:t.altKey,metaKey:t.metaKey})}var a=t(\"./control\"),o=t(\"../../util/dom\"),s=t(\"../../util/util\");e.exports=n,n.prototype=s.inherit(a,{options:{position:\"top-right\"},onAdd:function(t){var e=\"mapboxgl-ctrl\",r=this._container=o.create(\"div\",e+\"-group\",t.getContainer());return this._container.addEventListener(\"contextmenu\",this._onContextMenu.bind(this)),this._zoomInButton=this._createButton(e+\"-icon \"+e+\"-zoom-in\",t.zoomIn.bind(t)),this._zoomOutButton=this._createButton(e+\"-icon \"+e+\"-zoom-out\",t.zoomOut.bind(t)),this._compass=this._createButton(e+\"-icon \"+e+\"-compass\",t.resetNorth.bind(t)),this._compassArrow=o.create(\"div\",\"arrow\",this._compass),this._compass.addEventListener(\"mousedown\",this._onCompassDown.bind(this)),this._onCompassMove=this._onCompassMove.bind(this),this._onCompassUp=this._onCompassUp.bind(this),t.on(\"rotate\",this._rotateCompassArrow.bind(this)),this._rotateCompassArrow(),this._el=t.getCanvasContainer(),r},_onContextMenu:function(t){t.preventDefault()},_onCompassDown:function(t){0===t.button&&(o.disableDrag(),document.addEventListener(\"mousemove\",this._onCompassMove),document.addEventListener(\"mouseup\",this._onCompassUp),this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassMove:function(t){0===t.button&&(this._el.dispatchEvent(i(t)),t.stopPropagation())},_onCompassUp:function(t){0===t.button&&(document.removeEventListener(\"mousemove\",this._onCompassMove),document.removeEventListener(\"mouseup\",this._onCompassUp),o.enableDrag(),this._el.dispatchEvent(i(t)),t.stopPropagation())},_createButton:function(t,e){var r=o.create(\"button\",t,this._container);return r.type=\"button\",r.addEventListener(\"click\",function(){e()}),r},_rotateCompassArrow:function(){var t=\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassArrow.style.transform=t}})},{\"../../util/dom\":389,\"../../util/util\":403,\"./control\":371}],374:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../geo/lng_lat_bounds\"),o=t(\"../../util/util\");e.exports=n,n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onMouseDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onMouseDown),this._enabled=!1)},_onMouseDown:function(t){t.shiftKey&&0===t.button&&(document.addEventListener(\"mousemove\",this._onMouseMove,!1),document.addEventListener(\"keydown\",this._onKeyDown,!1),document.addEventListener(\"mouseup\",this._onMouseUp,!1),i.disableDrag(),this._startPos=i.mousePos(this._el,t),this._active=!0)},_onMouseMove:function(t){var e=this._startPos,r=i.mousePos(this._el,t);this._box||(this._box=i.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var n=Math.min(e.x,r.x),a=Math.max(e.x,r.x),o=Math.min(e.y,r.y),s=Math.max(e.y,r.y);i.setTransform(this._box,\"translate(\"+n+\"px,\"+o+\"px)\"),this._box.style.width=a-n+\"px\",this._box.style.height=s-o+\"px\"},_onMouseUp:function(t){if(0===t.button){var e=this._startPos,r=i.mousePos(this._el,t),n=new a(this._map.unproject(e),this._map.unproject(r));this._finish(),e.x===r.x&&e.y===r.y?this._fireEvent(\"boxzoomcancel\",t):this._map.fitBounds(n,{linear:!0}).fire(\"boxzoomend\",{originalEvent:t,boxZoomBounds:n})}},_onKeyDown:function(t){27===t.keyCode&&(this._finish(),this._fireEvent(\"boxzoomcancel\",t))},_finish:function(){this._active=!1,document.removeEventListener(\"mousemove\",this._onMouseMove,!1),document.removeEventListener(\"keydown\",this._onKeyDown,!1),document.removeEventListener(\"mouseup\",this._onMouseUp,!1),this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(this._box.parentNode.removeChild(this._box),this._box=null),i.enableDrag()},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})}}},{\"../../geo/lng_lat_bounds\":301,\"../../util/dom\":389,\"../../util/util\":403}],375:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._onDblClick=this._onDblClick.bind(this)}e.exports=n,n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._map.on(\"dblclick\",this._onDblClick),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._map.off(\"dblclick\",this._onDblClick),this._enabled=!1)},_onDblClick:function(t){this._map.zoomTo(this._map.getZoom()+(t.originalEvent.shiftKey?-1:1),{around:t.lngLat},t)}}},{}],376:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=.3,s=a.bezier(0,0,o,1),l=1400,u=2500;n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._el.addEventListener(\"touchstart\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._el.removeEventListener(\"touchstart\",this._onDown),this._enabled=!1)},_onDown:function(t){this._ignoreEvent(t)||this.isActive()||(t.touches?(document.addEventListener(\"touchmove\",this._onMove),document.addEventListener(\"touchend\",this._onTouchEnd)):(document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onMouseUp)),this._active=!1,this._startPos=this._pos=i.mousePos(this._el,t),this._inertia=[[Date.now(),this._pos]])},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"dragstart\",t),this._fireEvent(\"movestart\",t));var e=i.mousePos(this._el,t),r=this._map;r.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),e]),r.transform.setLocationAtPoint(r.transform.pointLocation(this._pos),e),this._fireEvent(\"drag\",t),this._fireEvent(\"move\",t),this._pos=e,t.preventDefault()}},_onUp:function(t){if(this.isActive()){this._active=!1,this._fireEvent(\"dragend\",t),this._drainInertiaBuffer();var e=function(){this._fireEvent(\"moveend\",t)}.bind(this),r=this._inertia;if(r.length<2)return void e();var n=r[r.length-1],i=r[0],a=n[1].sub(i[1]),c=(n[0]-i[0])/1e3;if(0===c||n[1].equals(i[1]))return void e();var h=a.mult(o/c),f=h.mag();f>l&&(f=l,h._unit()._mult(f));var d=f/(u*o),p=h.mult(-d/2);this._map.panBy(p,{duration:1e3*d,easing:s,noMoveStart:!0},{originalEvent:t})}},_onMouseUp:function(t){this._ignoreEvent(t)||(this._onUp(t),\n",
+       "document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onMouseUp))},_onTouchEnd:function(t){this._ignoreEvent(t)||(this._onUp(t),document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onTouchEnd))},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragRotate&&e.dragRotate.isActive())return!0;if(t.touches)return t.touches.length>1;if(t.ctrlKey)return!0;var r=1,n=0;return\"mousemove\"===t.type?t.buttons&0===r:t.button!==n},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>0&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403}],377:[function(t,e,r){\"use strict\";function n(t,e){this._map=t,this._el=t.getCanvasContainer(),this._bearingSnap=e.bearingSnap,o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"point-geometry\"),o=t(\"../../util/util\");e.exports=n;var s=.25,l=o.bezier(0,0,s,1),u=180,c=720;n.prototype={_enabled:!1,_active:!1,isEnabled:function(){return this._enabled},isActive:function(){return this._active},enable:function(){this.isEnabled()||(this._el.addEventListener(\"mousedown\",this._onDown),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"mousedown\",this._onDown),this._enabled=!1)},_onDown:function(t){if(!this._ignoreEvent(t)&&!this.isActive()){document.addEventListener(\"mousemove\",this._onMove),document.addEventListener(\"mouseup\",this._onUp),this._active=!1,this._inertia=[[Date.now(),this._map.getBearing()]],this._startPos=this._pos=i.mousePos(this._el,t),this._center=this._map.transform.centerPoint;var e=this._startPos.sub(this._center),r=e.mag();r<200&&(this._center=this._startPos.add(new a(-200,0)._rotate(e.angle()))),t.preventDefault()}},_onMove:function(t){if(!this._ignoreEvent(t)){this.isActive()||(this._active=!0,this._fireEvent(\"rotatestart\",t),this._fireEvent(\"movestart\",t));var e=this._map;e.stop();var r=this._pos,n=i.mousePos(this._el,t),a=this._center,o=r.sub(a).angleWith(n.sub(a))/Math.PI*180,s=e.getBearing()-o,l=this._inertia,u=l[l.length-1];this._drainInertiaBuffer(),l.push([Date.now(),e._normalizeBearing(s,u[1])]),e.transform.bearing=s,this._fireEvent(\"rotate\",t),this._fireEvent(\"move\",t),this._pos=n}},_onUp:function(t){if(!this._ignoreEvent(t)&&(document.removeEventListener(\"mousemove\",this._onMove),document.removeEventListener(\"mouseup\",this._onUp),this.isActive())){this._active=!1,this._fireEvent(\"rotateend\",t),this._drainInertiaBuffer();var e=this._map,r=e.getBearing(),n=this._inertia,i=function(){Math.abs(r)<this._bearingSnap?e.resetNorth({noMoveStart:!0},{originalEvent:t}):this._fireEvent(\"moveend\",t)}.bind(this);if(n.length<2)return void i();var a=n[0],o=n[n.length-1],h=n[n.length-2],f=e._normalizeBearing(r,h[1]),d=o[1]-a[1],p=d<0?-1:1,g=(o[0]-a[0])/1e3;if(0===d||0===g)return void i();var m=Math.abs(d*(s/g));m>u&&(m=u);var v=m/(c*s),y=p*m*(v/2);f+=y,Math.abs(e._normalizeBearing(f,0))<this._bearingSnap&&(f=e._normalizeBearing(0,f)),e.rotateTo(f,{duration:1e3*v,easing:l,noMoveStart:!0},{originalEvent:t})}},_fireEvent:function(t,e){return this._map.fire(t,{originalEvent:e})},_ignoreEvent:function(t){var e=this._map;if(e.boxZoom&&e.boxZoom.isActive())return!0;if(e.dragPan&&e.dragPan.isActive())return!0;if(t.touches)return t.touches.length>1;var r=t.ctrlKey?1:2,n=t.ctrlKey?0:2;return\"mousemove\"===t.type?t.buttons&0===r:t.button!==n},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>0&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403,\"point-geometry\":442}],378:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),this._onKeyDown=this._onKeyDown.bind(this)}e.exports=n;var i=80,a=2,o=5;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"keydown\",this._onKeyDown,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"keydown\",this._onKeyDown),this._enabled=!1)},_onKeyDown:function(t){if(!(t.altKey||t.ctrlKey||t.metaKey)){var e=this._map,r={originalEvent:t};if(!e.isEasing())switch(t.keyCode){case 61:case 107:case 171:case 187:e.zoomTo(Math.round(e.getZoom())+(t.shiftKey?2:1),r);break;case 189:case 109:case 173:e.zoomTo(Math.round(e.getZoom())-(t.shiftKey?2:1),r);break;case 37:t.shiftKey?e.easeTo({bearing:e.getBearing()-a},r):(t.preventDefault(),e.panBy([-i,0],r));break;case 39:t.shiftKey?e.easeTo({bearing:e.getBearing()+a},r):(t.preventDefault(),e.panBy([i,0],r));break;case 38:t.shiftKey?e.easeTo({pitch:e.getPitch()+o},r):(t.preventDefault(),e.panBy([0,-i],r));break;case 40:t.shiftKey?e.easeTo({pitch:Math.max(e.getPitch()-o,0)},r):(t.preventDefault(),e.panBy([0,i],r))}}}}},{}],379:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),o.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/browser\"),o=t(\"../../util/util\");e.exports=n;var s=\"undefined\"!=typeof navigator?navigator.userAgent.toLowerCase():\"\",l=s.indexOf(\"firefox\")!==-1,u=s.indexOf(\"safari\")!==-1&&s.indexOf(\"chrom\")===-1;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"wheel\",this._onWheel,!1),this._el.addEventListener(\"mousewheel\",this._onWheel,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"wheel\",this._onWheel),this._el.removeEventListener(\"mousewheel\",this._onWheel),this._enabled=!1)},_onWheel:function(t){var e;\"wheel\"===t.type?(e=t.deltaY,l&&t.deltaMode===window.WheelEvent.DOM_DELTA_PIXEL&&(e/=a.devicePixelRatio),t.deltaMode===window.WheelEvent.DOM_DELTA_LINE&&(e*=40)):\"mousewheel\"===t.type&&(e=-t.wheelDeltaY,u&&(e/=3));var r=a.now(),n=r-(this._time||0);this._pos=i.mousePos(this._el,t),this._time=r,0!==e&&e%4.000244140625===0?(this._type=\"wheel\",e=Math.floor(e/4)):0!==e&&Math.abs(e)<4?this._type=\"trackpad\":n>400?(this._type=null,this._lastValue=e,this._timeout=setTimeout(this._onTimeout,40)):this._type||(this._type=Math.abs(n*e)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,e+=this._lastValue)),t.shiftKey&&e&&(e/=4),this._type&&this._zoom(-e,t),t.preventDefault()},_onTimeout:function(){this._type=\"wheel\",this._zoom(-this._lastValue)},_zoom:function(t,e){if(0!==t){var r=this._map,n=2/(1+Math.exp(-Math.abs(t/100)));t<0&&0!==n&&(n=1/n);var i=r.ease?r.ease.to:r.transform.scale,a=r.transform.scaleZoom(i*n);r.zoomTo(a,{duration:0,around:r.unproject(this._pos),delayEndEvents:200},{originalEvent:e})}}}},{\"../../util/browser\":387,\"../../util/dom\":389,\"../../util/util\":403}],380:[function(t,e,r){\"use strict\";function n(t){this._map=t,this._el=t.getCanvasContainer(),a.bindHandlers(this)}var i=t(\"../../util/dom\"),a=t(\"../../util/util\");e.exports=n;var o=.15,s=a.bezier(0,0,o,1),l=12,u=2.5,c=.15,h=4;n.prototype={_enabled:!1,isEnabled:function(){return this._enabled},enable:function(){this.isEnabled()||(this._el.addEventListener(\"touchstart\",this._onStart,!1),this._enabled=!0)},disable:function(){this.isEnabled()&&(this._el.removeEventListener(\"touchstart\",this._onStart),this._enabled=!1)},disableRotation:function(){this._rotationDisabled=!0},enableRotation:function(){this._rotationDisabled=!1},_onStart:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]);this._startVec=e.sub(r),this._startScale=this._map.transform.scale,this._startBearing=this._map.transform.bearing,this._gestureIntent=void 0,this._inertia=[],document.addEventListener(\"touchmove\",this._onMove,!1),document.addEventListener(\"touchend\",this._onEnd,!1)}},_onMove:function(t){if(2===t.touches.length){var e=i.mousePos(this._el,t.touches[0]),r=i.mousePos(this._el,t.touches[1]),n=e.add(r).div(2),a=e.sub(r),o=a.mag()/this._startVec.mag(),s=this._rotationDisabled?0:180*a.angleWith(this._startVec)/Math.PI,l=this._map;if(this._gestureIntent){var u={duration:0,around:l.unproject(n)};\"rotate\"===this._gestureIntent&&(u.bearing=this._startBearing+s),\"zoom\"!==this._gestureIntent&&\"rotate\"!==this._gestureIntent||(u.zoom=l.transform.scaleZoom(this._startScale*o)),l.stop(),this._drainInertiaBuffer(),this._inertia.push([Date.now(),o,n]),l.easeTo(u,{originalEvent:t})}else{var f=Math.abs(1-o)>c,d=Math.abs(s)>h;d?this._gestureIntent=\"rotate\":f&&(this._gestureIntent=\"zoom\"),this._gestureIntent&&(this._startVec=a,this._startScale=l.transform.scale,this._startBearing=l.transform.bearing)}t.preventDefault()}},_onEnd:function(t){document.removeEventListener(\"touchmove\",this._onMove),document.removeEventListener(\"touchend\",this._onEnd),this._drainInertiaBuffer();var e=this._inertia,r=this._map;if(e.length<2)return void r.snapToNorth({},{originalEvent:t});var n=e[e.length-1],i=e[0],a=r.transform.scaleZoom(this._startScale*n[1]),c=r.transform.scaleZoom(this._startScale*i[1]),h=a-c,f=(n[0]-i[0])/1e3,d=n[2];if(0===f||a===c)return void r.snapToNorth({},{originalEvent:t});var p=h*o/f;Math.abs(p)>u&&(p=p>0?u:-u);var g=1e3*Math.abs(p/(l*o)),m=a+p*g/2e3;m<0&&(m=0),r.easeTo({zoom:m,duration:g,easing:s,around:r.unproject(d)},{originalEvent:t})},_drainInertiaBuffer:function(){for(var t=this._inertia,e=Date.now(),r=160;t.length>2&&e-t[0][0]>r;)t.shift()}}},{\"../../util/dom\":389,\"../../util/util\":403}],381:[function(t,e,r){\"use strict\";function n(){i.bindAll([\"_onHashChange\",\"_updateHash\"],this)}e.exports=n;var i=t(\"../util/util\");n.prototype={addTo:function(t){return this._map=t,window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},remove:function(){return window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),delete this._map,this},_onHashChange:function(){var t=location.hash.replace(\"#\",\"\").split(\"/\");return t.length>=3&&(this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:+(t[3]||0)}),!0)},_updateHash:function(){var t=this._map.getCenter(),e=this._map.getZoom(),r=this._map.getBearing(),n=Math.max(0,Math.ceil(Math.log(e)/Math.LN2)),i=\"#\"+Math.round(100*e)/100+\"/\"+t.lat.toFixed(n)+\"/\"+t.lng.toFixed(n)+(r?\"/\"+Math.round(10*r)/10:\"\");window.history.replaceState(\"\",\"\",i)}}},{\"../util/util\":403}],382:[function(t,e,r){\"use strict\";function n(t){t.parentNode&&t.parentNode.removeChild(t)}var i=t(\"../util/canvas\"),a=t(\"../util/util\"),o=t(\"../util/browser\"),s=t(\"../util/browser\").window,l=t(\"../util/evented\"),u=t(\"../util/dom\"),c=t(\"../style/style\"),h=t(\"../style/animation_loop\"),f=t(\"../render/painter\"),d=t(\"../geo/transform\"),p=t(\"./hash\"),g=t(\"./bind_handlers\"),m=t(\"./camera\"),v=t(\"../geo/lng_lat\"),y=t(\"../geo/lng_lat_bounds\"),x=t(\"point-geometry\"),b=t(\"./control/attribution\"),_=0,w=20,M={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:_,maxZoom:w,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,bearingSnap:7,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,workerCount:Math.max(o.hardwareConcurrency-1,1)},A=e.exports=function(t){if(t=a.extend({},M,t),t.workerCount<1)throw new Error(\"workerCount must an integer greater than or equal to 1.\");this._interactive=t.interactive,this._failIfMajorPerformanceCaveat=t.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=t.preserveDrawingBuffer,this._trackResize=t.trackResize,this._workerCount=t.workerCount,this._bearingSnap=t.bearingSnap,\"string\"==typeof t.container?this._container=document.getElementById(t.container):this._container=t.container,this.animationLoop=new h,this.transform=new d(t.minZoom,t.maxZoom),t.maxBounds&&this.setMaxBounds(t.maxBounds),a.bindAll([\"_forwardStyleEvent\",\"_forwardSourceEvent\",\"_forwardLayerEvent\",\"_forwardTileEvent\",\"_onStyleLoad\",\"_onStyleChange\",\"_onSourceAdd\",\"_onSourceRemove\",\"_onSourceUpdate\",\"_onWindowOnline\",\"_onWindowResize\",\"_update\",\"_render\"],this),this._setupContainer(),this._setupPainter(),this.on(\"move\",this._update.bind(this,!1)),this.on(\"zoom\",this._update.bind(this,!0)),this.on(\"moveend\",function(){this.animationLoop.set(300),this._rerender()}.bind(this)),\"undefined\"!=typeof s&&(s.addEventListener(\"online\",this._onWindowOnline,!1),s.addEventListener(\"resize\",this._onWindowResize,!1)),g(this,t),this._hash=t.hash&&(new p).addTo(this),this._hash&&this._hash._onHashChange()||this.jumpTo({center:t.center,zoom:t.zoom,bearing:t.bearing,pitch:t.pitch}),this.stacks={},this._classes=[],this.resize(),t.classes&&this.setClasses(t.classes),t.style&&this.setStyle(t.style),t.attributionControl&&this.addControl(new b(t.attributionControl));var e=this.fire.bind(this,\"error\");this.on(\"style.error\",e),this.on(\"source.error\",e),this.on(\"tile.error\",e),this.on(\"layer.error\",e)};a.extend(A.prototype,l),a.extend(A.prototype,m.prototype),a.extend(A.prototype,{addControl:function(t){return t.addTo(this),this},addClass:function(t,e){return this._classes.indexOf(t)>=0||\"\"===t?this:(this._classes.push(t),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},removeClass:function(t,e){var r=this._classes.indexOf(t);return r<0||\"\"===t?this:(this._classes.splice(r,1),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0))},setClasses:function(t,e){for(var r={},n=0;n<t.length;n++)\"\"!==t[n]&&(r[t[n]]=!0);return this._classes=Object.keys(r),this._classOptions=e,this.style&&this.style.updateClasses(),this._update(!0)},hasClass:function(t){return this._classes.indexOf(t)>=0},getClasses:function(){return this._classes},resize:function(){var t=0,e=0;return this._container&&(t=this._container.offsetWidth||400,e=this._container.offsetHeight||300),this._canvas.resize(t,e),this.transform.resize(t,e),this.painter.resize(t,e),this.fire(\"movestart\").fire(\"move\").fire(\"resize\").fire(\"moveend\")},getBounds:function(){var t=new y(this.transform.pointLocation(new x(0,0)),this.transform.pointLocation(this.transform.size));return(this.transform.angle||this.transform.pitch)&&(t.extend(this.transform.pointLocation(new x(this.transform.size.x,0))),t.extend(this.transform.pointLocation(new x(0,this.transform.size.y)))),t},setMaxBounds:function(t){if(t){var e=y.convert(t);this.transform.lngRange=[e.getWest(),e.getEast()],this.transform.latRange=[e.getSouth(),e.getNorth()],this.transform._constrain(),this._update()}else null!==t&&void 0!==t||(this.transform.lngRange=[],this.transform.latRange=[],this._update());return this},setMinZoom:function(t){if(t=null===t||void 0===t?_:t,t>=_&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between \"+_+\" and the current maxZoom, inclusive\")},setMaxZoom:function(t){if(t=null===t||void 0===t?w:t,t>=this.transform.minZoom&&t<=w)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be between the current minZoom and \"+w+\", inclusive\")},project:function(t){return this.transform.locationPoint(v.convert(t))},unproject:function(t){return this.transform.pointLocation(x.convert(t))},queryRenderedFeatures:function(){function t(t){return t instanceof x||Array.isArray(t)}var e,r={};return 2===arguments.length?(e=arguments[0],r=arguments[1]):1===arguments.length&&t(arguments[0])?e=arguments[0]:1===arguments.length&&(r=arguments[0]),this.style.queryRenderedFeatures(this._makeQueryGeometry(e),r,this.transform.zoom,this.transform.angle)},_makeQueryGeometry:function(t){void 0===t&&(t=[x.convert([0,0]),x.convert([this.transform.width,this.transform.height])]);var e,r=t instanceof x||\"number\"==typeof t[0];if(r){var n=x.convert(t);e=[n]}else{var i=[x.convert(t[0]),x.convert(t[1])];e=[i[0],new x(i[1].x,i[0].y),i[1],new x(i[0].x,i[1].y),i[0]]}return e=e.map(function(t){return this.transform.pointCoordinate(t)}.bind(this))},querySourceFeatures:function(t,e){return this.style.querySourceFeatures(t,e)},setStyle:function(t){return this.style&&(this.style.off(\"load\",this._onStyleLoad).off(\"error\",this._forwardStyleEvent).off(\"change\",this._onStyleChange).off(\"source.add\",this._onSourceAdd).off(\"source.remove\",this._onSourceRemove).off(\"source.load\",this._onSourceUpdate).off(\"source.error\",this._forwardSourceEvent).off(\"source.change\",this._onSourceUpdate).off(\"layer.add\",this._forwardLayerEvent).off(\"layer.remove\",this._forwardLayerEvent).off(\"layer.error\",this._forwardLayerEvent).off(\"tile.add\",this._forwardTileEvent).off(\"tile.remove\",this._forwardTileEvent).off(\"tile.load\",this._update).off(\"tile.error\",this._forwardTileEvent).off(\"tile.stats\",this._forwardTileEvent)._remove(),this.off(\"rotate\",this.style._redoPlacement),this.off(\"pitch\",this.style._redoPlacement)),t?(t instanceof c?this.style=t:this.style=new c(t,this.animationLoop,this._workerCount),this.style.on(\"load\",this._onStyleLoad).on(\"error\",this._forwardStyleEvent).on(\"change\",this._onStyleChange).on(\"source.add\",this._onSourceAdd).on(\"source.remove\",this._onSourceRemove).on(\"source.load\",this._onSourceUpdate).on(\"source.error\",this._forwardSourceEvent).on(\"source.change\",this._onSourceUpdate).on(\"layer.add\",this._forwardLayerEvent).on(\"layer.remove\",this._forwardLayerEvent).on(\"layer.error\",this._forwardLayerEvent).on(\"tile.add\",this._forwardTileEvent).on(\"tile.remove\",this._forwardTileEvent).on(\"tile.load\",this._update).on(\"tile.error\",this._forwardTileEvent).on(\"tile.stats\",this._forwardTileEvent),this.on(\"rotate\",this.style._redoPlacement),this.on(\"pitch\",this.style._redoPlacement),this):(this.style=null,this)},getStyle:function(){if(this.style)return this.style.serialize()},addSource:function(t,e){return this.style.addSource(t,e),this._update(!0),this},addSourceType:function(t,e,r){return this.style.addSourceType(t,e,r)},removeSource:function(t){return this.style.removeSource(t),this._update(!0),this},getSource:function(t){return this.style.getSource(t)},addLayer:function(t,e){return this.style.addLayer(t,e),this._update(!0),this},removeLayer:function(t){return this.style.removeLayer(t),this._update(!0),this},getLayer:function(t){return this.style.getLayer(t)},setFilter:function(t,e){return this.style.setFilter(t,e),this._update(!0),this},setLayerZoomRange:function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0),this},getFilter:function(t){return this.style.getFilter(t)},setPaintProperty:function(t,e,r,n){return this.style.setPaintProperty(t,e,r,n),this._update(!0),this},getPaintProperty:function(t,e,r){return this.style.getPaintProperty(t,e,r)},setLayoutProperty:function(t,e,r){return this.style.setLayoutProperty(t,e,r),this._update(!0),this},getLayoutProperty:function(t,e){return this.style.getLayoutProperty(t,e)},getContainer:function(){return this._container},getCanvasContainer:function(){return this._canvasContainer},getCanvas:function(){return this._canvas.getElement()},_setupContainer:function(){var t=this._container;t.classList.add(\"mapboxgl-map\");var e=this._canvasContainer=u.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=new i(this,e);var r=this._controlContainer=u.create(\"div\",\"mapboxgl-control-container\",t),n=this._controlCorners={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach(function(t){n[t]=u.create(\"div\",\"mapboxgl-ctrl-\"+t,r)})},_setupPainter:function(){var t=this._canvas.getWebGLContext({failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer});return t?void(this.painter=new f(t,this.transform)):void this.fire(\"error\",{error:new Error(\"Failed to initialize WebGL\")})},_contextLost:function(t){t.preventDefault(),this._frameId&&o.cancelFrame(this._frameId),this.fire(\"webglcontextlost\",{originalEvent:t})},_contextRestored:function(t){this._setupPainter(),this.resize(),this._update(),this.fire(\"webglcontextrestored\",{originalEvent:t})},loaded:function(){return!this._styleDirty&&!this._sourcesDirty&&!(!this.style||!this.style.loaded())},_update:function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this._rerender(),this):this},_render:function(){try{this.style&&this._styleDirty&&(this._styleDirty=!1,this.style.update(this._classes,this._classOptions),this._classOptions=null,this.style._recalculate(this.transform.zoom)),this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.painter.render(this.style,{debug:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,vertices:this.vertices,rotating:this.rotating,zooming:this.zooming}),this.fire(\"render\"),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(\"load\")),this._frameId=null,this.animationLoop.stopped()||(this._styleDirty=!0),(this._sourcesDirty||this._repaint||this._styleDirty)&&this._rerender()}catch(t){this.fire(\"error\",{error:t})}return this},remove:function(){this._hash&&this._hash.remove(),o.cancelFrame(this._frameId),this.setStyle(null),\"undefined\"!=typeof s&&s.removeEventListener(\"resize\",this._onWindowResize,!1);var t=this.painter.gl.getExtension(\"WEBGL_lose_context\");t&&t.loseContext(),n(this._canvasContainer),n(this._controlContainer),this._container.classList.remove(\"mapboxgl-map\")},_rerender:function(){this.style&&!this._frameId&&(this._frameId=o.frame(this._render))},_forwardStyleEvent:function(t){this.fire(\"style.\"+t.type,a.extend({style:t.target},t))},_forwardSourceEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_forwardLayerEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_forwardTileEvent:function(t){this.fire(t.type,a.extend({style:t.target},t))},_onStyleLoad:function(t){this.transform.unmodified&&this.jumpTo(this.style.stylesheet),this.style.update(this._classes,{transition:!1}),this._forwardStyleEvent(t)},_onStyleChange:function(t){this._update(!0),this._forwardStyleEvent(t)},_onSourceAdd:function(t){var e=t.source;e.onAdd&&e.onAdd(this),this._forwardSourceEvent(t)},_onSourceRemove:function(t){var e=t.source;e.onRemove&&e.onRemove(this),this._forwardSourceEvent(t)},_onSourceUpdate:function(t){this._update(),this._forwardSourceEvent(t)},_onWindowOnline:function(){this._update()},_onWindowResize:function(){this._trackResize&&this.stop().resize()._update()}}),a.extendAll(A.prototype,{_showTileBoundaries:!1,get showTileBoundaries(){return this._showTileBoundaries},set showTileBoundaries(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},_showCollisionBoxes:!1,get showCollisionBoxes(){return this._showCollisionBoxes},set showCollisionBoxes(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,this.style._redoPlacement())},_showOverdrawInspector:!1,get showOverdrawInspector(){return this._showOverdrawInspector},set showOverdrawInspector(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},_repaint:!1,get repaint(){return this._repaint},set repaint(t){this._repaint=t,this._update()},_vertices:!1,get vertices(){return this._vertices},set vertices(t){this._vertices=t,this._update()}})},{\"../geo/lng_lat\":300,\"../geo/lng_lat_bounds\":301,\"../geo/transform\":302,\"../render/painter\":316,\"../style/animation_loop\":336,\"../style/style\":339,\"../util/browser\":387,\"../util/canvas\":388,\"../util/dom\":389,\"../util/evented\":395,\"../util/util\":403,\"./bind_handlers\":368,\"./camera\":369,\"./control/attribution\":370,\"./hash\":381,\"point-geometry\":442}],383:[function(t,e,r){\"use strict\";function n(t,e){t||(t=i.create(\"div\")),t.classList.add(\"mapboxgl-marker\"),this._el=t,this._offset=o.convert(e&&e.offset||[0,0]),this._update=this._update.bind(this)}e.exports=n;var i=t(\"../util/dom\"),a=t(\"../geo/lng_lat\"),o=t(\"point-geometry\");n.prototype={addTo:function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._el),t.on(\"move\",this._update),this._update(),this},remove:function(){this._map&&(this._map.off(\"move\",this._update),this._map=null);var t=this._el.parentNode;return t&&t.removeChild(this._el),this},getLngLat:function(){return this._lngLat},setLngLat:function(t){return this._lngLat=a.convert(t),this._update(),this},getElement:function(){return this._el},_update:function(){if(this._map){var t=this._map.project(this._lngLat)._add(this._offset);i.setTransform(this._el,\"translate(\"+t.x+\"px,\"+t.y+\"px)\")}}}},{\"../geo/lng_lat\":300,\"../util/dom\":389,\"point-geometry\":442}],384:[function(t,e,r){\"use strict\";function n(t){i.setOptions(this,t),i.bindAll([\"_update\",\"_onClickClose\"],this)}e.exports=n;var i=t(\"../util/util\"),a=t(\"../util/evented\"),o=t(\"../util/dom\"),s=t(\"../geo/lng_lat\");n.prototype=i.inherit(a,{options:{closeButton:!0,closeOnClick:!0},addTo:function(t){return this._map=t,this._map.on(\"move\",this._update),this.options.closeOnClick&&this._map.on(\"click\",this._onClickClose),this._update(),this},remove:function(){return this._content&&this._content.parentNode&&this._content.parentNode.removeChild(this._content),this._container&&(this._container.parentNode.removeChild(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"click\",this._onClickClose),delete this._map),this.fire(\"close\"),this},getLngLat:function(){return this._lngLat},setLngLat:function(t){return this._lngLat=s.convert(t),this._update(),this},setText:function(t){return this.setDOMContent(document.createTextNode(t))},setHTML:function(t){var e,r=document.createDocumentFragment(),n=document.createElement(\"body\");for(n.innerHTML=t;;){if(e=n.firstChild,!e)break;r.appendChild(e)}return this.setDOMContent(r)},setDOMContent:function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},_createContent:function(){this._content&&this._content.parentNode&&this._content.parentNode.removeChild(this._content),this._content=o.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=o.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClickClose))},_update:function(){if(this._map&&this._lngLat&&this._content){this._container||(this._container=o.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=o.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content));var t=this._map.project(this._lngLat).round(),e=this.options.anchor;if(!e){var r=this._container.offsetWidth,n=this._container.offsetHeight;e=t.y<n?[\"top\"]:t.y>this._map.transform.height-n?[\"bottom\"]:[],t.x<r/2?e.push(\"left\"):t.x>this._map.transform.width-r/2&&e.push(\"right\"),e=0===e.length?\"bottom\":e.join(\"-\")}var i={top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"},a=this._container.classList;for(var s in i)a.remove(\"mapboxgl-popup-anchor-\"+s);a.add(\"mapboxgl-popup-anchor-\"+e),o.setTransform(this._container,i[e]+\" translate(\"+t.x+\"px,\"+t.y+\"px)\")}},_onClickClose:function(){this.remove()}})},{\"../geo/lng_lat\":300,\"../util/dom\":389,\"../util/evented\":395,\"../util/util\":403}],385:[function(t,e,r){\"use strict\";function n(t,e){this.target=t,this.parent=e,this.callbacks={},this.callbackID=0,this.receive=this.receive.bind(this),this.target.addEventListener(\"message\",this.receive,!1)}e.exports=n,n.prototype.receive=function(t){function e(t,e,r){this.postMessage({type:\"<response>\",id:String(i),error:t?String(t):null,data:e},r)}var r,n=t.data,i=n.id;if(\"<response>\"===n.type)r=this.callbacks[n.id],delete this.callbacks[n.id],r&&r(n.error||null,n.data);else if(\"undefined\"!=typeof n.id&&this.parent[n.type])this.parent[n.type](n.data,e.bind(this));else if(\"undefined\"!=typeof n.id&&this.parent.workerSources){var a=n.type.split(\".\");this.parent.workerSources[a[0]][a[1]](n.data,e.bind(this))}else this.parent[n.type](n.data)},n.prototype.send=function(t,e,r,n){var i=null;r&&(this.callbacks[i=this.callbackID++]=r),this.postMessage({type:t,id:String(i),data:e},n)},n.prototype.postMessage=function(t,e){this.target.postMessage(t,e)}},{}],386:[function(t,e,r){\"use strict\";function n(t){var e=document.createElement(\"a\");return e.href=t,e.protocol===document.location.protocol&&e.host===document.location.host}r.getJSON=function(t,e){var r=new XMLHttpRequest;return r.open(\"GET\",t,!0),r.setRequestHeader(\"Accept\",\"application/json\"),r.onerror=function(t){e(t)},r.onload=function(){if(r.status>=200&&r.status<300&&r.response){var t;try{t=JSON.parse(r.response)}catch(t){return e(t)}e(null,t)}else e(new Error(r.statusText))},r.send(),r},r.getArrayBuffer=function(t,e){var r=new XMLHttpRequest;return r.open(\"GET\",t,!0),r.responseType=\"arraybuffer\",r.onerror=function(t){e(t)},r.onload=function(){r.status>=200&&r.status<300&&r.response?e(null,r.response):e(new Error(r.statusText))},r.send(),r},r.getImage=function(t,e){return r.getArrayBuffer(t,function(t,r){if(t)return e(t);var n=new Image;n.onload=function(){e(null,n),(window.URL||window.webkitURL).revokeObjectURL(n.src)};var i=new Blob([new Uint8Array(r)],{type:\"image/png\"});return n.src=(window.URL||window.webkitURL).createObjectURL(i),n.getData=function(){var t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");return t.width=n.width,t.height=n.height,e.drawImage(n,0,0),e.getImageData(0,0,n.width,n.height).data},n})},r.getVideo=function(t,e){var r=document.createElement(\"video\");r.onloadstart=function(){e(null,r)};for(var i=0;i<t.length;i++){var a=document.createElement(\"source\");n(t[i])||(r.crossOrigin=\"Anonymous\"),a.src=t[i],r.appendChild(a)}return r.getData=function(){return r},r}},{}],387:[function(t,e,r){\"use strict\";r.window=window,e.exports.now=function(){return window.performance&&window.performance.now?window.performance.now.bind(window.performance):Date.now.bind(Date)}();var n=window.requestAnimationFrame||window.mozRequestAnimationFrame||window.webkitRequestAnimationFrame||window.msRequestAnimationFrame;r.frame=function(t){return n(t)};var i=window.cancelAnimationFrame||window.mozCancelAnimationFrame||window.webkitCancelAnimationFrame||window.msCancelAnimationFrame;r.cancelFrame=function(t){i(t)},r.timed=function(t,n,i){function a(l){o||(l=e.exports.now(),l>=s+n?t.call(i,1):(t.call(i,(l-s)/n),r.frame(a)))}if(!n)return t.call(i,1),null;var o=!1,s=e.exports.now();return r.frame(a),function(){o=!0}},r.supported=t(\"mapbox-gl-supported\"),r.hardwareConcurrency=navigator.hardwareConcurrency||4,Object.defineProperty(r,\"devicePixelRatio\",{get:function(){return window.devicePixelRatio}}),r.supportsWebp=!1;var a=document.createElement(\"img\");a.onload=function(){r.supportsWebp=!0},a.src=\"data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA=\",r.supportsGeolocation=!!navigator.geolocation},{\"mapbox-gl-supported\":288}],388:[function(t,e,r){\"use strict\";function n(t,e){this.canvas=document.createElement(\"canvas\"),t&&e&&(this.canvas.style.position=\"absolute\",this.canvas.classList.add(\"mapboxgl-canvas\"),this.canvas.addEventListener(\"webglcontextlost\",t._contextLost.bind(t),!1),this.canvas.addEventListener(\"webglcontextrestored\",t._contextRestored.bind(t),!1),this.canvas.setAttribute(\"tabindex\",0),e.appendChild(this.canvas))}var i=t(\"../util\"),a=t(\"mapbox-gl-supported\");e.exports=n,n.prototype.resize=function(t,e){var r=window.devicePixelRatio||1;this.canvas.width=r*t,this.canvas.height=r*e,this.canvas.style.width=t+\"px\",this.canvas.style.height=e+\"px\"},n.prototype.getWebGLContext=function(t){return t=i.extend({},t,a.webGLContextAttributes),this.canvas.getContext(\"webgl\",t)||this.canvas.getContext(\"experimental-webgl\",t)},n.prototype.getElement=function(){return this.canvas}},{\"../util\":403,\"mapbox-gl-supported\":288}],389:[function(t,e,r){\"use strict\";function n(t){for(var e=0;e<t.length;e++)if(t[e]in s)return t[e]}function i(t){t.preventDefault(),t.stopPropagation(),\n",
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n(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.fullData=null,this.updateAxes(e),this.makeFramework(),this.glplotOptions=d(this),this.glplotOptions.merge(e),this.glplot=u(this.glplotOptions),this.camera=p(this),this.traces={},this._inputs={},this.spikes=c(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/cartesian/axes\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),f=t(\"webgl-context\"),d=t(\"./convert\"),p=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),m=t(\"../../lib/show_no_webgl_msg\"),v=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o&&(a=document.createElement(\"canvas\"),o=f({canvas:a,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}),!o))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=a,this.gl=o}else{var t=document.createElement(\"canvas\"),e=f({canvas:t,premultipliedAlpha:!0});e||m(this),this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r),r.className+=\"user-select-none\";var n=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");n.style.position=\"absolute\",n.style.top=n.style.left=\"0px\",n.style.width=n.style.height=\"100%\",n.style[\"z-index\"]=20,n.style[\"pointer-events\"]=\"none\";var i=this.mouseContainer=document.createElement(\"div\");i.style.position=\"absolute\";var s=this.container;s.appendChild(r),s.appendChild(n),s.appendChild(i)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.updateSize(this.canvas),this.glplot.setDirty(),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=n-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var u=0;u<4;++u){var c=i[4*(r*o+l)+u];i[4*(r*o+l)+u]=i[4*(r*s+l)+u],i[4*(r*s+l)+u]=c}var h=document.createElement(\"canvas\");h.width=r,h.height=n;var f=h.getContext(\"2d\"),d=f.createImageData(r,n);d.data.set(i),f.putImageData(d,0,0);var p;switch(t){case\"jpeg\":p=h.toDataURL(\"image/jpeg\");break;case\"webp\":p=h.toDataURL(\"image/webp\");break;default:p=h.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(a),p},y.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},y.computeTickMarks=function(){this.xaxis._length=this.glplot.viewBox[2]-this.glplot.viewBox[0],this.yaxis._length=this.glplot.viewBox[3]-this.glplot.viewBox[1];for(var t=[s.calcTicks(this.xaxis),s.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=g(t[e][r].text+\"\");return t},y.updateAxes=function(t){var e=s.subplotMatch,r=\"xaxis\"+this.id.match(e)[1],n=\"yaxis\"+this.id.match(e)[2];this.xaxis=t[r],this.yaxis=t[n]},y.updateFx=function(t){var e=this.fullLayout;e.dragmode=t.dragmode,e.hovermode=t.hovermode};var x=function(t){var e=t.xaxis.range,r=t.yaxis.range;t.graphDiv.layout.xaxis.autorange=t.xaxis.autorange,t.graphDiv.layout.xaxis.range=e.slice(0),t.graphDiv.layout.yaxis.autorange=t.yaxis.autorange,t.graphDiv.layout.yaxis.range=r.slice(0);var n={lastInputTime:t.camera.lastInputTime};n[t.xaxis._name]=e.slice(),n[t.yaxis._name]=r.slice(),t.graphDiv.emit(\"plotly_relayout\",n)};y.cameraChanged=function(){var t=this.camera,e=this.xaxis.range,r=this.yaxis.range;this.glplot.setDataBox([e[0],r[0],e[1],r[1]]);var n=this.computeTickMarks(),a=this.glplotOptions.ticks;i(n,a)&&(this.glplotOptions.ticks=n,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),x(this))},y.destroy=function(){var t=this.traces;t&&Object.keys(t).map(function(e){t[e].dispose(),delete t[e]}),this.glplot.dispose(),this.staticPlot||this.container.removeChild(this.canvas),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this._inputs=null,this.glplot=null,this.stopped=!0},y.plot=function(t,e,r){var n=this.glplot;this.fullLayout=r,this.updateAxes(r),this.updateTraces(t,e);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var l=r._size,u=this.xaxis.domain,c=this.yaxis.domain;o.viewBox=[l.l+u[0]*l.w,l.b+c[0]*l.h,i-l.r-(1-u[1])*l.w,a-l.t-(1-c[1])*l.h],this.mouseContainer.style.width=l.w*(u[1]-u[0])+\"px\",this.mouseContainer.style.height=l.h*(c[1]-c[0])+\"px\",this.mouseContainer.height=l.h*(c[1]-c[0]),this.mouseContainer.style.left=l.l+u[0]*l.w+\"px\",this.mouseContainer.style.top=l.t+(1-c[1])*l.h+\"px\";var h=this.bounds;h[0]=h[1]=1/0,h[2]=h[3]=-(1/0);var f,d,p=Object.keys(this.traces);for(d=0;d<p.length;++d)for(var g=this.traces[p[d]],m=0;m<2;++m)h[m]=Math.min(h[m],g.bounds[m]),h[m+2]=Math.max(h[m+2],g.bounds[m+2]);for(d=0;d<2;++d)h[d]>h[d+2]&&(h[d]=-1,h[d+2]=1),f=this[v[d]],f._length=o.viewBox[d+2]-o.viewBox[d],s.doAutoRange(f);o.ticks=this.computeTickMarks();var y=this.xaxis.range,x=this.yaxis.range;o.dataBox=[y[0],x[0],y[1],x[1]],o.merge(r),n.update(o),this.glplot.draw()},y.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if(i=t[n],i.uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r],this._inputs[i.uid]=r;var l=e[r],u=this.traces[i.uid];u?u.update(i,l):(u=i._module.plot(this,i,l),this.traces[i.uid]=u)}},y.emitPointAction=function(t,e){var r=this._inputs[t.trace.uid];this.graphDiv.emit(e,{points:[{x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r,pointNumber:t.pointIndex,data:this.fullData[r]._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis}]})},y.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a=r.x*t.pixelRatio,o=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode)this.selectBox.enabled=!0,this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],t.setDirty();else{this.selectBox.enabled=!1;var s=i._size,u=this.xaxis.domain,c=this.yaxis.domain,h=t.pick(a/t.pixelRatio+s.l+u[0]*s.w,o/t.pixelRatio-(s.t+(1-c[1])*s.h)),f=h&&h.object._trace.handlePick(h);if(f&&n&&this.emitPointAction(f,\"plotly_click\"),h&&\"skip\"!==h.object._trace.hoverinfo&&i.hovermode){if(f&&(!this.lastPickResult||this.lastPickResult.traceUid!==f.trace.uid||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var d=f;this.lastPickResult={traceUid:f.trace?f.trace.uid:null,dataCoord:f.dataCoord.slice()},this.spikes.update({center:h.dataCoord}),d.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(h.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(h.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(f,\"plotly_hover\");var p=d.hoverinfo;if(\"all\"!==p){var g=p.split(\"+\");g.indexOf(\"x\")===-1&&(d.traceCoord[0]=void 0),g.indexOf(\"y\")===-1&&(d.traceCoord[1]=void 0),g.indexOf(\"z\")===-1&&(d.traceCoord[2]=void 0),g.indexOf(\"text\")===-1&&(d.textLabel=void 0),g.indexOf(\"name\")===-1&&(d.name=void 0)}l.loneHover({x:d.screenCoord[0],y:d.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",d.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",d.traceCoord[1]),zLabel:d.traceCoord[2],text:d.textLabel,name:d.name,color:d.color},{container:this.svgContainer})}}else!h&&this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),l.loneUnhover(this.svgContainer))}t.draw()}},y.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return s.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../lib/html2unicode\":631,\"../../lib/show_no_webgl_msg\":643,\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/graph_interact\":670,\"./camera\":697,\"./convert\":698,\"gl-plot2d\":187,\"gl-select-box\":218,\"gl-spikes2d\":227,\"webgl-context\":518}],701:[function(t,e,r){\"use strict\";function n(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var n=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),l=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],u=0,c=t.clientWidth,h=t.clientHeight,f={keyBindingMode:\"rotate\",view:n,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:n.modes,tick:function(){var e=i(),r=this.delay,a=e-2*r;n.idle(e-r),n.recalcMatrix(a),n.flush(e-(100+2*r));for(var o=!0,s=n.computedMatrix,f=0;f<16;++f)o=o&&l[f]===s[f],l[f]=s[f];var d=t.clientWidth===c&&t.clientHeight===h;return c=t.clientWidth,h=t.clientHeight,o?!d:(u=Math.exp(n.computedRadius[0]),!0)},lookAt:function(t,e,r){n.lookAt(n.lastT(),t,e,r)},rotate:function(t,e,r){n.rotate(n.lastT(),t,e,r)},pan:function(t,e,r){n.pan(n.lastT(),t,e,r)},translate:function(t,e,r){n.translate(n.lastT(),t,e,r)}};Object.defineProperties(f,{matrix:{get:function(){return n.computedMatrix},set:function(t){return n.setMatrix(n.lastT(),t),n.computedMatrix},enumerable:!0},mode:{get:function(){return n.getMode()},set:function(t){var e=n.computedUp.slice(),r=n.computedEye.slice(),a=n.computedCenter.slice();if(n.setMode(t),\"turntable\"===t){var o=i();n._active.lookAt(o,r,a,e),n._active.lookAt(o+500,r,a,[0,0,1]),n._active.flush(o)}return n.getMode()},enumerable:!0},center:{get:function(){return n.computedCenter},set:function(t){return n.lookAt(n.lastT(),null,t),n.computedCenter},enumerable:!0},eye:{get:function(){return n.computedEye},set:function(t){return n.lookAt(n.lastT(),t),n.computedEye},enumerable:!0},up:{get:function(){return n.computedUp},set:function(t){return n.lookAt(n.lastT(),null,null,t),n.computedUp},enumerable:!0},distance:{get:function(){return u},set:function(t){return n.setDistance(n.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return n.getDistanceLimits(r)},set:function(t){return n.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1});var d=0,p=0;return o(t,function(e,r,a,o){var s=\"rotate\"===f.keyBindingMode,l=\"pan\"===f.keyBindingMode,c=\"zoom\"===f.keyBindingMode,h=!!o.control,g=!!o.alt,m=!!o.shift,v=!!(1&e),y=!!(2&e),x=!!(4&e),b=1/t.clientHeight,_=b*(r-d),w=b*(a-p),M=f.flipX?1:-1,A=f.flipY?1:-1,k=i(),T=Math.PI*f.rotateSpeed;if((s&&v&&!h&&!g&&!m||v&&!h&&!g&&m)&&n.rotate(k,M*T*_,-A*T*w,0),(l&&v&&!h&&!g&&!m||y||v&&h&&!g&&!m)&&n.pan(k,-f.translateSpeed*_*u,f.translateSpeed*w*u,0),c&&v&&!h&&!g&&!m||x||v&&!h&&g&&!m){var E=-f.zoomSpeed*w/window.innerHeight*(k-n.lastT())*100;n.pan(k,0,0,u*(Math.exp(E)-1))}return d=r,p=a,!0}),s(t,function(t,e){var r=f.flipX?1:-1,a=f.flipY?1:-1,o=i();if(Math.abs(t)>Math.abs(e))n.rotate(o,0,0,-t*r*Math.PI*f.rotateSpeed/window.innerWidth);else{var s=-f.zoomSpeed*a*e/window.innerHeight*(o-n.lastT())/100;n.pan(o,0,0,u*(Math.exp(s)-1))}},!0),f}e.exports=n;var i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":27,\"mouse-change\":413,\"mouse-wheel\":415,\"right-now\":459}],702:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0;r<3;++r){var n=s[r];e[n]._gd=t}}var i=t(\"./scene\"),a=t(\"../plots\"),o=t(\"../../constants/xmlns_namespaces\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,o=a.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var s=0;s<o.length;s++){var l=o[s],u=a.getSubplotData(r,\"gl3d\",l),c=e[l],h=c._scene;void 0===h&&(n(t,c),h=new i({id:l,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),c._scene=h),h.plot(u,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=a.getSubplotIds(n,\"gl3d\"),o=0;o<i.length;o++){var s=i[o];!e[s]&&n[s]._scene&&n[s]._scene.destroy()}},r.toSVG=function(t){for(var e=t._fullLayout,r=a.getSubplotIds(e,\"gl3d\"),n=e._size,i=0;i<r.length;i++){var s=e[r[i]],l=s.domain,u=s._scene,c=u.toImage(\"png\"),h=e._glimages.append(\"svg:image\");h.attr({xmlns:o.svg,\"xlink:href\":c,x:n.l+n.w*l.x[0],y:n.t+n.h*(1-l.y[1]),width:n.w*(l.x[1]-l.x[0]),height:n.h*(l.y[1]-l.y[0]),preserveAspectRatio:\"none\"}),u.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\")},{\"../../constants/xmlns_namespaces\":618,\"../plots\":723,\"./layout/attributes\":703,\"./layout/defaults\":707,\"./layout/layout_attributes\":708,\"./scene\":712,\"./set_convert\":713}],703:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\"}}},{}],704:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:i.title,titlefont:i.titlefont,type:i.type,autorange:i.autorange,rangemode:i.rangemode,range:i.range,fixedrange:i.fixedrange,tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,separatethousands:i.separatethousands,tickformat:i.tickformat,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth}},{\"../../../components/color\":533,\"../../../lib/extend\":625,\"../../cartesian/layout_attributes\":672}],705:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/axis_defaults\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"],l=13600/187;e.exports=function(t,e,r){function u(t,e){return i.coerce(c,h,a,t,e)}for(var c,h,f=0;f<s.length;f++){var d=s[f];c=t[d]||{},h={_id:d[0]+r.scene,_name:d},e[d]=h=o(c,h,u,{font:r.font,letter:d[0],data:r.data,showGrid:!0,bgColor:r.bgColor}),u(\"gridcolor\",n(h.color,r.bgColor,l).toRgbString()),u(\"title\",d[0]),h.setScale=i.noop,u(\"showspikes\")&&(u(\"spikesides\"),u(\"spikethickness\"),u(\"spikecolor\",h.color)),u(\"showaxeslabels\"),u(\"showbackground\")&&u(\"backgroundcolor\")}}},{\"../../../lib\":632,\"../../cartesian/axis_defaults\":664,\"./axis_attributes\":704,tinycolor2:489}],706:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open 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a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;r<3;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)!==-1?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":631,\"../../../lib/str2rgbarray\":645,arraytools:33}],707:[function(t,e,r){\"use strict\";function n(t,e,r,n){for(var a=r(\"bgcolor\"),l=i.combine(a,n.paper_bgcolor),u=Object.keys(o.camera),c=0;c<u.length;c++)r(\"camera.\"+u[c]+\".x\"),r(\"camera.\"+u[c]+\".y\"),r(\"camera.\"+u[c]+\".z\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),f=h?\"manual\":\"auto\",d=r(\"aspectmode\",f);h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===d&&(e.aspectmode=\"auto\")),s(t,e,{font:n.font,scene:n.id,data:n.fullData,bgColor:l}),r(\"dragmode\",n.getDfltFromLayout(\"dragmode\")),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}var i=t(\"../../../components/color\"),a=t(\"../../subplot_defaults\"),o=t(\"./layout_attributes\"),s=t(\"./axis_defaults\");e.exports=function(t,e,r){function i(e){if(!s){var r=o[e].values.indexOf(t[e])!==-1;return r?t[e]:void 0}}var s=e._has(\"cartesian\")||e._has(\"geo\")||e._has(\"gl2d\")||e._has(\"pie\")||e._has(\"ternary\");a(t,e,r,{type:\"gl3d\",attributes:o,handleDefaults:n,font:e.font,fullData:r,getDfltFromLayout:i,paper_bgcolor:e.paper_bgcolor})}},{\"../../../components/color\":533,\"../../subplot_defaults\":730,\"./axis_defaults\":705,\"./layout_attributes\":708}],708:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\"],dflt:\"turntable\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\"},_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":625,\"./axis_attributes\":704}],709:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;e<3;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":645}],710:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,c=[[],[],[]],h=0;h<3;++h){var f=i[l[h]];if(f._length=(r[h].hi-r[h].lo)*r[h].pixelsPerDataUnit/t.dataScale[h],Math.abs(f._length)===1/0)c[h]=[];else{f.range[0]=r[h].lo/t.dataScale[h],f.range[1]=r[h].hi/t.dataScale[h],f._m=1/(t.dataScale[h]*r[h].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var d=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var p=f.nticks||o.constrain(f._length/40,4,9);a.autoTicks(f,Math.abs(f.range[1]-f.range[0])/p)}for(var g=a.calcTicks(f),m=0;m<g.length;++m)g[m].x=g[m].x*t.dataScale[h],g[m].text=s(g[m].text);c[h]=g,f.tickmode=d}}e.ticks=c;for(var h=0;h<3;++h){u[h]=.5*(t.glplot.bounds[0][h]+t.glplot.bounds[1][h]);for(var m=0;m<2;++m)e.bounds[m][h]=t.glplot.bounds[m][h]}t.contourLevels=n(c)}e.exports=i;var a=t(\"../../cartesian/axes\"),o=t(\"../../../lib\"),s=t(\"../../../lib/html2unicode\"),l=[\"xaxis\",\"yaxis\",\"zaxis\"],u=[0,0,0]},{\"../../../lib\":632,\"../../../lib/html2unicode\":631,\"../../cartesian/axes\":662}],711:[function(t,e,r){\"use 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d=r.hoverinfo,p=e(\"xaxis\",u.traceCoordinate[0]),v=e(\"yaxis\",u.traceCoordinate[1]),y=e(\"zaxis\",u.traceCoordinate[2]);if(\"all\"!==d){var x=d.split(\"+\");x.indexOf(\"x\")===-1&&(p=void 0),x.indexOf(\"y\")===-1&&(v=void 0),x.indexOf(\"z\")===-1&&(y=void 0),x.indexOf(\"text\")===-1&&(u.textLabel=void 0),x.indexOf(\"name\")===-1&&(l.name=void 0)}t.fullSceneLayout.hovermode&&m.loneHover({x:(.5+.5*f[0]/f[3])*a,y:(.5-.5*f[1]/f[3])*o,xLabel:p,yLabel:v,zLabel:y,text:u.textLabel,name:l.name,color:l.color},{container:n});var _={points:[{x:p,y:v,z:y,data:r._input,fullData:r,curveNumber:r.index,pointNumber:u.data.index}]};u.buttons&&u.distance<5?t.graphDiv.emit(\"plotly_click\",_):t.graphDiv.emit(\"plotly_hover\",_),h=_}else m.loneUnhover(n),t.graphDiv.emit(\"plotly_unhover\",h)}function i(t,e,r,i){var a={canvas:r,gl:i,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1};if(t.staticMode){if(!h&&(c=document.createElement(\"canvas\"),h=d({canvas:c,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}),!h))throw new Error(\"error creating static canvas/context for image server\");a.pixelRatio=t.pixelRatio,a.gl=h,a.canvas=c}try{t.glplot=f(a)}catch(e){y(t)}var o=function(t){var e={};e[t.id]=u(t.camera),t.saveCamera(t.graphDiv.layout),t.graphDiv.emit(\"plotly_relayout\",e)};if(t.glplot.canvas.addEventListener(\"mouseup\",o.bind(null,t)),t.glplot.canvas.addEventListener(\"wheel\",o.bind(null,t)),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(t){p.warn(\"Lost WebGL context.\"),t.preventDefault()}),!t.camera){var s=t.fullSceneLayout.camera;t.camera=x(t.container,{center:[s.center.x,s.center.y,s.center.z],eye:[s.eye.x,s.eye.y,s.eye.z],up:[s.up.x,s.up.y,s.up.z],zoomMin:.1,zoomMax:100,mode:\"orbit\"})}return t.glplot.mouseListener.enabled=!1,t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=n.bind(null,t),t.traces={},!0}function a(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=w(e[this.id]),this.spikeOptions=M(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],!i(this,e)}function o(t,e,r,n){for(var i,a=0;a<e.length;++a)if(Array.isArray(e[a]))for(var o=0;o<e[a].length;++o)i=t.d2l(e[a][o]),!isNaN(i)&&isFinite(i)&&(n[0][r]=Math.min(n[0][r],i),n[1][r]=Math.max(n[1][r],i));else i=t.d2l(e[a]),!isNaN(i)&&isFinite(i)&&(n[0][r]=Math.min(n[0][r],i),n[1][r]=Math.max(n[1][r],i))}function s(t,e,r){var n=t.fullSceneLayout;o(n.xaxis,e.x,0,r),o(n.yaxis,e.y,1,r),o(n.zaxis,e.z,2,r)}function l(t){return[[t.eye.x,t.eye.y,t.eye.z],[t.center.x,t.center.y,t.center.z],[t.up.x,t.up.y,t.up.z]]}function u(t){return{up:{x:t.up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]}}}var c,h,f=t(\"gl-plot3d\"),d=t(\"webgl-context\"),p=t(\"../../lib\"),g=t(\"../../plots/cartesian/axes\"),m=t(\"../../plots/cartesian/graph_interact\"),v=t(\"../../lib/str2rgbarray\"),y=t(\"../../lib/show_no_webgl_msg\"),x=t(\"./camera\"),b=t(\"./project\"),_=t(\"./set_convert\"),w=t(\"./layout/convert\"),M=t(\"./layout/spikes\"),A=t(\"./layout/tick_marks\"),k=a.prototype;k.recoverContext=function(){function t(){return r.isContextLost()?void requestAnimationFrame(t):i(e,e.fullLayout,n,r)?void e.plot.apply(e,e.plotArgs):void p.error(\"Catastrophic 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n=t.symbol,i=l(n.textposition,n.iconsize);s.extendFlat(e,{\"icon-image\":n.icon+\"-15\",\"icon-size\":n.iconsize/10,\"text-field\":n.text,\"text-size\":n.textfont.size,\"text-anchor\":i.anchor,\"text-offset\":i.offset}),s.extendFlat(r,{\"icon-color\":t.color,\"text-color\":n.textfont.color,\"text-opacity\":t.opacity})}return{layout:e,paint:r}}function o(t){var e,r=t.sourcetype,n=t.source,i={type:r},a=\"string\"==typeof n;return\"geojson\"===r?e=\"data\":\"vector\"===r&&(e=a?\"url\":\"tiles\"),i[e]=n,i}var s=t(\"../../lib\"),l=t(\"./convert_text_opts\"),u=n.prototype;u.update=function(t){this.visible?this.needsNewSource(t)?(this.updateLayer(t),this.updateSource(t)):this.needsNewLayer(t)&&this.updateLayer(t):(this.updateSource(t),this.updateLayer(t)),this.updateStyle(t),this.visible=i(t)},u.needsNewSource=function(t){return this.sourceType!==t.sourcetype||this.source!==t.source||this.layerType!==t.type},u.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==t.below},u.updateSource=function(t){var e=this.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,i(t)){var r=o(t);e.addSource(this.idSource,r)}},u.updateLayer=function(t){var e=this.map;if(e.getLayer(this.idLayer)&&e.removeLayer(this.idLayer),this.layerType=t.type,i(t)){e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type},t.below);var r={visibility:\"visible\"};this.mapbox.setOptions(this.idLayer,\"setLayoutProperty\",r)}},u.updateStyle=function(t){var e=a(t);i(t)&&(this.mapbox.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.mapbox.setOptions(this.idLayer,\"setPaintProperty\",e.paint))},u.dispose=function(){var t=this.map;t.removeLayer(this.idLayer),t.removeSource(this.idSource)},e.exports=function(t,e,r){var i=new n(t,e);return i.update(r),i}},{\"../../lib\":632,\"./convert_text_opts\":716}],719:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../font_attributes\"),o=t(\"../../traces/scatter/attributes\").textposition;e.exports={domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},accesstoken:{valType:\"string\",noBlank:!0,strict:!0},style:{valType:\"any\",values:[\"basic\",\"streets\",\"outdoors\",\"light\",\"dark\",\"satellite\",\"satellite-streets\"],dflt:\"basic\"},center:{lon:{valType:\"number\",dflt:0},lat:{valType:\"number\",dflt:0}},zoom:{valType:\"number\",dflt:1},bearing:{valType:\"number\",dflt:0},pitch:{valType:\"number\",dflt:0},layers:{_isLinkedToArray:!0,sourcetype:{valType:\"enumerated\",values:[\"geojson\",\"vector\"],dflt:\"geojson\"},source:{valType:\"any\"},sourcelayer:{valType:\"string\",dflt:\"\"},type:{valType:\"enumerated\",values:[\"circle\",\"line\",\"fill\",\"symbol\"],dflt:\"circle\"},below:{valType:\"string\",dflt:\"\"},color:{valType:\"color\",dflt:i},opacity:{valType:\"number\",min:0,max:1,dflt:1},circle:{radius:{valType:\"number\",dflt:15}},line:{width:{valType:\"number\",dflt:2}},fill:{outlinecolor:{valType:\"color\",dflt:i}},symbol:{icon:{valType:\"string\",dflt:\"marker\"},iconsize:{valType:\"number\",dflt:10},text:{valType:\"string\",dflt:\"\"},textfont:n.extendDeep({},a,{family:{dflt:\"Open 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a=t(\"../../lib\"),o=t(\"../subplot_defaults\"),s=t(\"./layout_attributes\");e.exports=function(t,e,r){o(t,e,r,{type:\"mapbox\",attributes:s,handleDefaults:n,partition:\"y\"})}},{\"../../lib\":632,\"../subplot_defaults\":730,\"./layout_attributes\":719}],721:[function(t,e,r){\"use strict\";function n(t){this.id=t.id,this.gd=t.gd,this.container=t.container,this.isStatic=t.staticPlot;var e=t.fullLayout;this.uid=e._uid+\"-\"+this.id,this.opts=e[this.id],this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(e),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[]}function i(t){var e=h.style.values,r=h.style.dflt,n={};return u.isPlainObject(t)?(n.id=t.id,n.style=t):\"string\"==typeof t?(n.id=t,n.style=e.indexOf(t)!==-1?a(t):t):(n.id=r,n.style=a(r)),n}function a(t){return c.styleUrlPrefix+t+\"-\"+c.styleUrlSuffix}function o(t){return[t.lon,t.lat]}var s=t(\"mapbox-gl\"),l=t(\"../cartesian/graph_interact\"),u=t(\"../../lib\"),c=t(\"./constants\"),h=t(\"./layout_attributes\"),f=t(\"./layers\"),d=n.prototype;e.exports=function(t){var e=new n(t);return e},d.plot=function(t,e,r){var n=this,i=n.opts=e[this.id];n.map&&i.accesstoken!==n.accessToken&&(n.map.remove(),n.map=null,n.styleObj=null,n.traceHash=[],n.layerList={});var a;a=n.map?new Promise(function(r,i){n.updateMap(t,e,r,i)}):new Promise(function(r,i){n.createMap(t,e,r,i)}),r.push(a)},d.createMap=function(t,e,r,n){function a(){l.loneUnhover(e._toppaper)}var h=this,f=h.gd,d=h.opts,p=h.styleObj=i(d.style);h.accessToken=d.accesstoken;var g=h.map=new 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n=e*Math.PI/180,i=t(n);return[e,i]});return i},o.util.dataFromEquation=function(t,e,r){var i=e||6,a=[],o=[];n.range(0,360+i,i).forEach(function(e,r){var n=e*Math.PI/180,i=t(n);a.push(e),o.push(i)});var s={t:a,r:o};return r&&(s.name=r),s},o.util.ensureArray=function(t,e){if(\"undefined\"==typeof t)return null;var r=[].concat(t);return n.range(e).map(function(t,e){return r[e]||r[0]})},o.util.fillArrays=function(t,e,r){return e.forEach(function(e,n){t[e]=o.util.ensureArray(t[e],r)}),t},o.util.cloneJson=function(t){return JSON.parse(JSON.stringify(t))},o.util.validateKeys=function(t,e){\"string\"==typeof e&&(e=e.split(\".\"));var r=e.shift();return t[r]&&(!e.length||objHasKeys(t[r],e))},o.util.sumArrays=function(t,e){return n.zip(t,e).map(function(t,e){return n.sum(t)})},o.util.arrayLast=function(t){return t[t.length-1]},o.util.arrayEqual=function(t,e){for(var r=Math.max(t.length,e.length,1);r-- >=0&&t[r]===e[r];);return r===-2},o.util.flattenArray=function(t){for(var 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t={data:{name:\"geom1\",t:[[1,2,3,4]],r:[[1,2,3,4]],dotType:\"circle\",dotSize:64,dotVisible:!1,barWidth:20,color:\"#ffa500\",strokeSize:1,strokeColor:\"silver\",strokeDash:\"solid\",opacity:1,index:0,visible:!0,visibleInLegend:!0},geometryConfig:{geometry:\"LinePlot\",geometryType:\"arc\",direction:\"clockwise\",orientation:0,container:\"body\",radialScale:null,angularScale:null,colorScale:n.scale.category20()}};return t},o.BarChart=function(){return o.PolyChart()},o.BarChart.defaultConfig=function(){var t={geometryConfig:{geometryType:\"bar\"}};return t},o.AreaChart=function(){return o.PolyChart()},o.AreaChart.defaultConfig=function(){var t={geometryConfig:{geometryType:\"arc\"}};return t},o.DotPlot=function(){return o.PolyChart()},o.DotPlot.defaultConfig=function(){var t={geometryConfig:{geometryType:\"dot\",dotType:\"circle\"}};return t},o.LinePlot=function(){return o.PolyChart()},o.LinePlot.defaultConfig=function(){var t={geometryConfig:{geometryType:\"line\"}};return 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r={data:[\"a\",\"b\",\"c\"],legendConfig:{elements:[{symbol:\"line\",color:\"red\"},{symbol:\"square\",color:\"yellow\"},{symbol:\"diamond\",color:\"limegreen\"}],height:150,colorBandWidth:30,fontSize:12,container:\"body\",isContinuous:null,textColor:\"grey\",reverseOrder:!1}};return r},o.tooltipPanel=function(){var t,e,r,i={container:null,hasTick:!1,fontSize:12,color:\"white\",padding:5},s=\"tooltip-\"+o.tooltipPanel.uid++,l=10,u=function(){t=i.container.selectAll(\"g.\"+s).data([0]);var n=t.enter().append(\"g\").classed(s,!0).style({\"pointer-events\":\"none\",display:\"none\"});return r=n.append(\"path\").style({fill:\"white\",\"fill-opacity\":.9}).attr({d:\"M0 0\"}),e=n.append(\"text\").attr({dx:i.padding+l,dy:.3*+i.fontSize}),u};return u.text=function(a){var o=n.hsl(i.color).l,s=o>=.5?\"#aaa\":\"white\",c=o>=.5?\"black\":\"white\",h=a||\"\";e.style({fill:c,\"font-size\":i.fontSize+\"px\"}).text(h);var 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n=a({},t),i=[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]];return i.forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",n.dotVisible===!0?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var i=o.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var n=i.indexOf(t.geometry);n!=-1&&(r.data[e].groupId=n)})}if(t.layout){var s=a({},t.layout),l=[[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]];\n",
+       "if(l.forEach(function(t,r){o.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof s.tickLength&&(s.angularaxis.ticklen=s.tickLength,delete s.tickLength),s.tickColor&&(s.angularaxis.tickcolor=s.tickColor,delete s.tickColor)):(s.angularAxis&&\"undefined\"!=typeof s.angularAxis.ticklen&&(s.tickLength=s.angularAxis.ticklen),s.angularAxis&&\"undefined\"!=typeof s.angularAxis.tickcolor&&(s.tickColor=s.angularAxis.tickcolor)),s.legend&&\"boolean\"!=typeof s.legend.reverseOrder&&(s.legend.reverseOrder=\"normal\"!=s.legend.reverseOrder),s.legend&&\"boolean\"==typeof s.legend.traceorder&&(s.legend.traceorder=s.legend.traceorder?\"reversed\":\"normal\",delete s.legend.reverseOrder),s.margin&&\"undefined\"!=typeof s.margin.t){var u=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],h={};n.entries(s.margin).forEach(function(t,e){h[c[u.indexOf(t.key)]]=t.value}),s.margin=h}e&&(delete s.needsEndSpacing,delete s.minorTickColor,delete s.minorTicks,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksStep,delete s.angularaxis.rewriteTicks,delete s.angularaxis.nticks,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksCount,delete s.radialaxis.ticksStep,delete s.radialaxis.rewriteTicks,delete s.radialaxis.nticks),r.layout=s}return r},t}},{\"../../lib\":632,d3:95}],728:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../components/color\"),o=t(\"./micropolar\"),s=t(\"./undo_manager\"),l=i.extendDeepAll,u=e.exports={};u.framework=function(t){function e(e,i){return i&&(h=i),n.select(n.select(h).node().parentNode).selectAll(\".svg-container>*:not(.chart-root)\").remove(),r=r?l(r,e):e,a||(a=o.Axis()),c=o.adapter.plotly().convert(r),a.config(c).render(h),t.data=r.data,t.layout=r.layout,u.fillLayout(t),r}var r,i,a,c,h,f=new s;return e.isPolar=!0,e.svg=function(){return a.svg()},e.getConfig=function(){return r},e.getLiveConfig=function(){return o.adapter.plotly().convert(a.getLiveConfig(),!0)},e.getLiveScales=function(){return{t:a.angularScale(),r:a.radialScale()}},e.setUndoPoint=function(){var t=this,e=o.util.cloneJson(r);!function(e,r){f.add({undo:function(){r&&t(r)},redo:function(){t(e)}})}(e,i),i=o.util.cloneJson(e)},e.undo=function(){f.undo()},e.redo=function(){f.redo()},e},u.fillLayout=function(t){var e=n.select(t).selectAll(\".plot-container\"),r=e.selectAll(\".svg-container\"),i=t.framework&&t.framework.svg&&t.framework.svg(),o={width:800,height:600,paper_bgcolor:a.background,_container:e,_paperdiv:r,_paper:i};t._fullLayout=l(o,t.layout)}},{\"../../components/color\":533,\"../../lib\":632,\"./micropolar\":727,\"./undo_manager\":729,d3:95}],729:[function(t,e,r){\"use strict\";e.exports=function(){function t(t,e){return t?(i=!0,t[e](),i=!1,this):this}var e,r=[],n=-1,i=!1;return{add:function(t){return i?this:(r.splice(n+1,r.length-n),r.push(t),n=r.length-1,this)},setCallback:function(t){e=t},undo:function(){var i=r[n];return i?(t(i,\"undo\"),n-=1,e&&e(i.undo),this):this},redo:function(){var i=r[n+1];return i?(t(i,\"redo\"),n+=1,e&&e(i.redo),this):this},clear:function(){r=[],n=-1},hasUndo:function(){return n!==-1},hasRedo:function(){return n<r.length-1},getCommands:function(){return r},getPreviousCommand:function(){return r[n-1]},getIndex:function(){return n}}}},{}],730:[function(t,e,r){\"use strict\";var n=t(\"../lib\"),i=t(\"./plots\");e.exports=function(t,e,r,a){function o(t,e){return n.coerce(s,l,c,t,e)}for(var s,l,u=a.type,c=a.attributes,h=a.handleDefaults,f=a.partition||\"x\",d=i.findSubplotIds(r,u),p=d.length,g=0;g<p;g++){var m=d[g];s=t[m]?t[m]:t[m]={},e[m]=l={},o(\"domain.\"+f,[g/p,(g+1)/p]),o(\"domain.\"+{x:\"y\",y:\"x\"}[f]),a.id=m,h(s,l,o,a)}}},{\"../lib\":632,\"./plots\":723}],731:[function(t,e,r){\"use strict\";var n=t(\"./ternary\"),i=t(\"../../plots/plots\");r.name=\"ternary\",r.attr=\"subplot\",r.idRoot=\"ternary\",r.idRegex=/^ternary([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^ternary([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"ternary\"),o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"ternary\",s),u=e[s]._subplot;void 0===u&&(u=new n({id:s,graphDiv:t,container:e._ternarylayer.node()},e),e[s]._subplot=u),u.plot(l,e,t._promises)}},r.clean=function(t,e,r,n){for(var a=i.getSubplotIds(n,\"ternary\"),o=0;o<a.length;o++){var s=a[o],l=n[s]._subplot;!e[s]&&l&&(l.plotContainer.remove(),l.clipDef.remove())}}},{\"../../plots/plots\":723,\"./layout/attributes\":732,\"./layout/defaults\":735,\"./layout/layout_attributes\":736,\"./ternary\":737}],732:[function(t,e,r){\"use strict\";e.exports={subplot:{valType:\"subplotid\",dflt:\"ternary\"}}},{}],733:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={title:n.title,titlefont:n.titlefont,color:n.color,tickmode:n.tickmode,nticks:i({},n.nticks,{dflt:6,min:1}),tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,showtickprefix:n.showtickprefix,tickprefix:n.tickprefix,showticksuffix:n.showticksuffix,ticksuffix:n.ticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,separatethousands:n.separatethousands,tickfont:n.tickfont,tickangle:n.tickangle,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:i({},n.showline,{dflt:!0}),linecolor:n.linecolor,linewidth:n.linewidth,showgrid:i({},n.showgrid,{dflt:!0}),gridcolor:n.gridcolor,gridwidth:n.gridwidth,min:{valType:\"number\",dflt:0,min:0}}},{\"../../../lib/extend\":625,\"../../cartesian/layout_attributes\":672}],734:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"./axis_attributes\"),o=t(\"../../cartesian/tick_label_defaults\"),s=t(\"../../cartesian/tick_mark_defaults\"),l=t(\"../../cartesian/tick_value_defaults\");e.exports=function(t,e,r){function u(r,n){return i.coerce(t,e,a,r,n)}e.type=\"linear\";var c=u(\"color\"),h=c===t.color?c:r.font.color,f=e._name,d=f.charAt(0).toUpperCase(),p=\"Component \"+d,g=u(\"title\",p);e._hovertitle=g===p?g:d,i.coerceFont(u,\"titlefont\",{family:r.font.family,size:Math.round(1.2*r.font.size),color:h}),u(\"min\"),l(t,e,u,\"linear\"),o(t,e,u,\"linear\",{noHover:!1}),s(t,e,u,{outerTicks:!0});var m=u(\"showticklabels\");m&&(i.coerceFont(u,\"tickfont\",{family:r.font.family,size:r.font.size,color:h}),u(\"tickangle\"),u(\"tickformat\")),u(\"hoverformat\");var v=u(\"showline\");v&&(u(\"linecolor\",c),u(\"linewidth\"));var y=u(\"showgrid\");y&&(u(\"gridcolor\",n(c,r.bgColor,60).toRgbString()),u(\"gridwidth\"))}},{\"../../../lib\":632,\"../../cartesian/tick_label_defaults\":678,\"../../cartesian/tick_mark_defaults\":679,\"../../cartesian/tick_value_defaults\":680,\"./axis_attributes\":733,tinycolor2:489}],735:[function(t,e,r){\"use strict\";function n(t,e,r,n){var a=r(\"bgcolor\"),o=r(\"sum\");n.bgColor=i.combine(a,n.paper_bgcolor);for(var u,c,h,f=0;f<l.length;f++)u=l[f],c=t[u]||{},h=e[u]={_name:u},s(c,h,n);var d=e.aaxis,p=e.baxis,g=e.caxis;d.min+p.min+g.min>=o&&(d.min=0,p.min=0,g.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}var i=t(\"../../../components/color\"),a=t(\"../../subplot_defaults\"),o=t(\"./layout_attributes\"),s=t(\"./axis_defaults\"),l=[\"aaxis\",\"baxis\",\"caxis\"];e.exports=function(t,e,r){a(t,e,r,{type:\"ternary\",attributes:o,handleDefaults:n,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../../components/color\":533,\"../../subplot_defaults\":730,\"./axis_defaults\":734,\"./layout_attributes\":736}],736:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color/attributes\"),i=t(\"./axis_attributes\");e.exports={domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:i,baxis:i,caxis:i}},{\"../../../components/color/attributes\":532,\"./axis_attributes\":733}],737:[function(t,e,r){\"use strict\";function n(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework()}function i(t){a.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}var a=t(\"d3\"),o=t(\"tinycolor2\"),s=t(\"../../plotly\"),l=t(\"../../lib\"),u=t(\"../../components/color\"),c=t(\"../../components/drawing\"),h=t(\"../cartesian/set_convert\"),f=t(\"../../lib/extend\").extendFlat,d=t(\"../cartesian/axes\"),p=t(\"../../lib/filter_visible\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/titles\"),v=t(\"../cartesian/select\"),y=t(\"../cartesian/constants\"),x=t(\"../cartesian/graph_interact\");e.exports=n;var b=n.prototype;b.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={}},b.plot=function(t,e){var r,n=this,i=e[n.id],a=e._size;l.getPlotDiv(n.plotContainer.node())!==n.graphDiv&&(n.init(n.graphDiv._fullLayout),n.makeFramework()),n.adjustLayout(i,a);var o=n.traceHash,s={};for(r=0;r<t.length;r++){var c=t[r];s[c.type]=s[c.type]||[],s[c.type].push(c)}var h=Object.keys(o),f=Object.keys(s);for(r=0;r<h.length;r++){var d=h[r];if(f.indexOf(d)===-1){var g=o[d][0];g.visible=!1,s[d]=[g]}}for(f=Object.keys(s),r=0;r<f.length;r++){var m=s[f[r]],v=m[0]._module;v.plot(n,p(m),i)}n.traceHash=s,n.layers.plotbg.select(\"path\").call(u.fill,i.bgcolor)},b.makeFramework=function(){var t=this,e=t.defs.selectAll(\"g.clips\").data([0]);e.enter().append(\"g\").classed(\"clips\",!0);var r=\"clip\"+t.layoutId+t.id;t.clipDef=e.selectAll(\"#\"+r).data([0]),t.clipDef.enter().append(\"clipPath\").attr(\"id\",r).append(\"path\").attr(\"d\",\"M0,0Z\"),t.plotContainer=t.container.selectAll(\"g.\"+t.id).data([0]),t.plotContainer.enter().append(\"g\").classed(t.id,!0),t.layers={};var n=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\",\"frontplot\",\"zoom\",\"aaxis\",\"baxis\",\"caxis\",\"axlines\"],i=t.plotContainer.selectAll(\"g.toplevel\").data(n);i.enter().append(\"g\").attr(\"class\",function(t){return\"toplevel \"+t}).each(function(e){var r=a.select(this);t.layers[e]=r,\"frontplot\"===e?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===e?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===e?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"axlines\"===e&&r.selectAll(\"path\").data([\"aline\",\"bline\",\"cline\"]).enter().append(\"path\").each(function(t){a.select(this).classed(t,!0)})});var o=t.plotContainer.select(\".grids\").selectAll(\"g.grid\").data([\"agrid\",\"bgrid\",\"cgrid\"]);o.enter().append(\"g\").attr(\"class\",function(t){return\"grid \"+t}).each(function(e){t.layers[e]=a.select(this)}),t.plotContainer.selectAll(\".backplot,.frontplot,.grids\").call(c.setClipUrl,r),t.graphDiv._context.staticPlot||t.initInteractions()};var _=Math.sqrt(4/3);b.adjustLayout=function(t,e){var r,n,i,a,o,s,l=this,c=t.domain,d=(c.x[0]+c.x[1])/2,p=(c.y[0]+c.y[1])/2,g=c.x[1]-c.x[0],m=c.y[1]-c.y[0],v=g*e.w,y=m*e.h,x=t.sum,b=t.aaxis.min,w=t.baxis.min,M=t.caxis.min;v>_*y?(a=y,i=a*_):(i=v,a=i/_),o=g*i/v,s=m*a/y,r=e.l+e.w*d-i/2,n=e.t+e.h*(1-p)-a/2,l.x0=r,l.y0=n,l.w=i,l.h=a,l.sum=x,l.xaxis={type:\"linear\",range:[b+2*M-x,x-b-2*w],domain:[d-o/2,d+o/2],_id:\"x\",_gd:l.graphDiv},h(l.xaxis),l.xaxis.setScale(),l.yaxis={type:\"linear\",range:[b,x-w-M],domain:[p-s/2,p+s/2],_id:\"y\",_gd:l.graphDiv},h(l.yaxis),l.yaxis.setScale();var A=l.yaxis.domain[0],k=l.aaxis=f({},t.aaxis,{range:[b,x-w-M],side:\"left\",_counterangle:30,tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+s*_],_axislayer:l.layers.aaxis,_gridlayer:l.layers.agrid,_pos:0,_gd:l.graphDiv,_id:\"y\",_length:i,_gridpath:\"M0,0l\"+a+\",-\"+i/2});h(k);var T=l.baxis=f({},t.baxis,{range:[x-b-M,w],side:\"bottom\",_counterangle:30,domain:l.xaxis.domain,_axislayer:l.layers.baxis,_gridlayer:l.layers.bgrid,_counteraxis:l.aaxis,_pos:0,_gd:l.graphDiv,_id:\"x\",_length:i,_gridpath:\"M0,0l-\"+i/2+\",-\"+a});h(T),k._counteraxis=T;var E=l.caxis=f({},t.caxis,{range:[x-b-w,M],side:\"right\",_counterangle:30,tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+s*_],_axislayer:l.layers.caxis,_gridlayer:l.layers.cgrid,_counteraxis:l.baxis,_pos:0,_gd:l.graphDiv,_id:\"y\",_length:i,_gridpath:\"M0,0l-\"+a+\",\"+i/2});h(E);var S=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";l.clipDef.select(\"path\").attr(\"d\",S),l.layers.plotbg.select(\"path\").attr(\"d\",S);var L=\"translate(\"+r+\",\"+n+\")\";l.plotContainer.selectAll(\".scatterlayer,.maplayer,.zoom\").attr(\"transform\",L);var z=\"translate(\"+r+\",\"+(n+a)+\")\";l.layers.baxis.attr(\"transform\",z),l.layers.bgrid.attr(\"transform\",z);var C=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(30)\";l.layers.aaxis.attr(\"transform\",C),l.layers.agrid.attr(\"transform\",C);var I=\"translate(\"+(r+i/2)+\",\"+n+\")rotate(-30)\";l.layers.caxis.attr(\"transform\",I),l.layers.cgrid.attr(\"transform\",I),l.drawAxes(!0),l.plotContainer.selectAll(\".crisp\").classed(\"crisp\",!1);var P=l.layers.axlines;P.select(\".aline\").attr(\"d\",k.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(u.stroke,k.linecolor||\"#000\").style(\"stroke-width\",(k.linewidth||0)+\"px\"),P.select(\".bline\").attr(\"d\",T.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(u.stroke,T.linecolor||\"#000\").style(\"stroke-width\",(T.linewidth||0)+\"px\"),P.select(\".cline\").attr(\"d\",E.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(u.stroke,E.linecolor||\"#000\").style(\"stroke-width\",(E.linewidth||0)+\"px\")},b.drawAxes=function(t){var 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r(t,e){return t.pxmid[1]-e.pxmid[1]}function n(t,e){return e.pxmid[1]-t.pxmid[1]}function i(t,r){r||(r={});var n,i,a,s,f,d,g=r.labelExtraY+(o?r.yLabelMax:r.yLabelMin),m=o?t.yLabelMin:t.yLabelMax,v=o?t.yLabelMax:t.yLabelMin,y=t.cyFinal+u(t.px0[1],t.px1[1]),x=g-m;if(x*h>0&&(t.labelExtraY=x),Array.isArray(e.pull))for(i=0;i<p.length;i++)a=p[i],a===t||(e.pull[t.i]||0)>=e.pull[a.i]||((t.pxmid[1]-a.pxmid[1])*h>0?(s=a.cyFinal+u(a.px0[1],a.px1[1]),x=s-m-t.labelExtraY,x*h>0&&(t.labelExtraY+=x)):(v+t.labelExtraY-y)*h>0&&(n=3*c*Math.abs(i-p.indexOf(t)),f=a.cxFinal+l(a.px0[0],a.px1[0]),d=f+n-(t.cxFinal+t.pxmid[0])-t.labelExtraX,d*c>0&&(t.labelExtraX+=d)))}var a,o,s,l,u,c,h,f,d,p,g,m,v;for(o=0;o<2;o++)for(s=o?r:n,u=o?Math.max:Math.min,h=o?1:-1,a=0;a<2;a++){for(l=a?Math.max:Math.min,c=a?1:-1,f=t[o][a],f.sort(s),d=t[1-o][a],p=d.concat(f),m=[],g=0;g<f.length;g++)void 0!==f[g].yLabelMid&&m.push(f[g]);for(v=!1,g=0;o&&g<d.length;g++)if(void 0!==d[g].yLabelMid){v=d[g];break}for(g=0;g<m.length;g++){var y=g&&m[g-1];v&&!g&&(y=v),i(m[g],y)}}}function s(t,e){var r,n,i,a,o,s,l,c,h,f,d=[];for(i=0;i<t.length;i++){if(o=t[i][0],s=o.trace,r=e.w*(s.domain.x[1]-s.domain.x[0]),n=e.h*(s.domain.y[1]-s.domain.y[0]),l=s.tiltaxis*Math.PI/180,c=s.pull,Array.isArray(c))for(c=0,a=0;a<s.pull.length;a++)s.pull[a]>c&&(c=s.pull[a]);o.r=Math.min(r/u(s.tilt,Math.sin(l),s.depth),n/u(s.tilt,Math.cos(l),s.depth))/(2+2*c),o.cx=e.l+e.w*(s.domain.x[1]+s.domain.x[0])/2,o.cy=e.t+e.h*(2-s.domain.y[1]-s.domain.y[0])/2,s.scalegroup&&d.indexOf(s.scalegroup)===-1&&d.push(s.scalegroup)}for(a=0;a<d.length;a++){for(f=1/0,h=d[a],i=0;i<t.length;i++)o=t[i][0],o.trace.scalegroup===h&&(f=Math.min(f,o.r*o.r/o.vTotal));for(i=0;i<t.length;i++)o=t[i][0],o.trace.scalegroup===h&&(o.r=Math.sqrt(f*o.vTotal))}}function l(t){function e(t){var e=h.r*Math.sin(t),r=-h.r*Math.cos(t);return d?[e*(1-s*n*n)+r*o*s,e*o*s+r*(1-s*i*i),Math.sin(a)*(r*i-e*n)]:[e,r]}var r,n,i,a,o,s,l,u,c,h=t[0],f=h.trace,d=f.tilt,p=f.rotation*Math.PI/180,g=2*Math.PI/h.vTotal,m=\"px0\",v=\"px1\";if(\"counterclockwise\"===f.direction){for(l=0;l<t.length&&t[l].hidden;l++);if(l===t.length)return;p+=g*t[l].v,g*=-1,m=\"px1\",v=\"px0\"}for(d&&(a=d*Math.PI/180,r=f.tiltaxis*Math.PI/180,o=Math.sin(r)*Math.cos(r),s=1-Math.cos(a),n=Math.sin(r),i=Math.cos(r)),c=e(p),l=0;l<t.length;l++)u=t[l],u.hidden||(u[m]=c,p+=g*u.v/2,u.pxmid=e(p),u.midangle=p,p+=g*u.v/2,c=e(p),u[v]=c,u.largeArc=u.v>h.vTotal/2?1:0)}function u(t,e,r){if(!t)return 1;var n=Math.sin(t*Math.PI/180);return Math.max(.01,r*n*Math.abs(e)+2*Math.sqrt(1-n*n*e*e))}var c=t(\"d3\"),h=t(\"../../plots/cartesian/graph_interact\"),f=t(\"../../components/color\"),d=t(\"../../components/drawing\"),p=t(\"../../lib/svg_text_utils\"),g=t(\"./helpers\");e.exports=function(t,e){var r=t._fullLayout;s(e,r._size);var u=r._pielayer.selectAll(\"g.trace\").data(e);u.enter().append(\"g\").attr({\"stroke-linejoin\":\"round\",class:\"trace\"}),u.exit().remove(),u.order(),u.each(function(e){var s=c.select(this),u=e[0],m=u.trace,v=0,y=(m.depth||0)*u.r*Math.sin(v)/2,x=m.tiltaxis||0,b=x*Math.PI/180,_=[y*Math.sin(b),y*Math.cos(b)],w=u.r*Math.cos(v),M=s.selectAll(\"g.part\").data(m.tilt?[\"top\",\"sides\"]:[\"top\"]);M.enter().append(\"g\").attr(\"class\",function(t){return t+\" part\"}),M.exit().remove(),M.order(),l(e),s.selectAll(\".top\").each(function(){var s=c.select(this).selectAll(\"g.slice\").data(e);s.enter().append(\"g\").classed(\"slice\",!0),s.exit().remove();var l=[[[],[]],[[],[]]],v=!1;s.each(function(o){function s(e){var n=t._fullLayout,a=t._fullData[m.index],s=a.hoverinfo;if(\"all\"===s&&(s=\"label+text+value+percent+name\"),!t._dragging&&n.hovermode!==!1&&\"none\"!==s&&\"skip\"!==s&&s){var l=i(o,u),c=M+o.pxmid[0]*(1-l),f=A+o.pxmid[1]*(1-l),d=r.separators,p=[];s.indexOf(\"label\")!==-1&&p.push(o.label),a.text&&a.text[o.i]&&s.indexOf(\"text\")!==-1&&p.push(a.text[o.i]),s.indexOf(\"value\")!==-1&&p.push(g.formatPieValue(o.v,d)),s.indexOf(\"percent\")!==-1&&p.push(g.formatPiePercent(o.v/u.vTotal,d)),h.loneHover({x0:c-l*u.r,x1:c+l*u.r,y:f,text:p.join(\"<br>\"),name:s.indexOf(\"name\")!==-1?a.name:void 0,color:o.color,idealAlign:o.pxmid[0]<0?\"left\":\"right\"},{container:n._hoverlayer.node(),outerContainer:n._paper.node()}),h.hover(t,e,\"pie\"),E=!0}}function f(e){t.emit(\"plotly_unhover\",{points:[e]}),E&&(h.loneUnhover(r._hoverlayer.node()),E=!1)}function y(){t._hoverdata=[o],t._hoverdata.trace=e.trace,h.click(t,{target:!0})}function b(t,e,r,n){return\"a\"+n*u.r+\",\"+n*w+\" \"+x+\" \"+o.largeArc+(r?\" 1 \":\" 0 \")+n*(e[0]-t[0])+\",\"+n*(e[1]-t[1])}if(o.hidden)return void c.select(this).selectAll(\"path,g\").remove();l[o.pxmid[1]<0?0:1][o.pxmid[0]<0?0:1].push(o);var M=u.cx+_[0],A=u.cy+_[1],k=c.select(this),T=k.selectAll(\"path.surface\").data([o]),E=!1;if(T.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),k.select(\"path.textline\").remove(),k.on(\"mouseover\",s).on(\"mouseout\",f).on(\"click\",y),m.pull){var S=+(Array.isArray(m.pull)?m.pull[o.i]:m.pull)||0;S>0&&(M+=S*o.pxmid[0],A+=S*o.pxmid[1])}o.cxFinal=M,o.cyFinal=A;var L=m.hole;if(o.v===u.vTotal){var z=\"M\"+(M+o.px0[0])+\",\"+(A+o.px0[1])+b(o.px0,o.pxmid,!0,1)+b(o.pxmid,o.px0,!0,1)+\"Z\";L?T.attr(\"d\",\"M\"+(M+L*o.px0[0])+\",\"+(A+L*o.px0[1])+b(o.px0,o.pxmid,!1,L)+b(o.pxmid,o.px0,!1,L)+\"Z\"+z):T.attr(\"d\",z)}else{var C=b(o.px0,o.px1,!0,1);if(L){var I=1-L;T.attr(\"d\",\"M\"+(M+L*o.px1[0])+\",\"+(A+L*o.px1[1])+b(o.px1,o.px0,!1,L)+\"l\"+I*o.px0[0]+\",\"+I*o.px0[1]+C+\"Z\")}else T.attr(\"d\",\"M\"+M+\",\"+A+\"l\"+o.px0[0]+\",\"+o.px0[1]+C+\"Z\")}var P=Array.isArray(m.textposition)?m.textposition[o.i]:m.textposition,D=k.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==P?[0]:[]);D.enter().append(\"g\").classed(\"slicetext\",!0),D.exit().remove(),D.each(function(){var t=c.select(this).selectAll(\"text\").data([0]);t.enter().append(\"text\").attr(\"data-notex\",1),t.exit().remove(),t.text(o.text).attr({class:\"slicetext\",transform:\"\",\"data-bb\":\"\",\"text-anchor\":\"middle\",x:0,y:0}).call(d.font,\"outside\"===P?m.outsidetextfont:m.insidetextfont).call(p.convertToTspans),t.selectAll(\"tspan.line\").attr({x:0,y:0});var e,r=d.bBox(t.node());\"outside\"===P?e=a(r,o):(e=n(r,o,u),\"auto\"===P&&e.scale<1&&(t.call(d.font,m.outsidetextfont),m.outsidetextfont.family===m.insidetextfont.family&&m.outsidetextfont.size===m.insidetextfont.size||(t.attr({\"data-bb\":\"\"}),r=d.bBox(t.node())),e=a(r,o)));var i=M+o.pxmid[0]*e.rCenter+(e.x||0),s=A+o.pxmid[1]*e.rCenter+(e.y||0);e.outside&&(o.yLabelMin=s-r.height/2,o.yLabelMid=s,o.yLabelMax=s+r.height/2,o.labelExtraX=0,o.labelExtraY=0,v=!0),t.attr(\"transform\",\"translate(\"+i+\",\"+s+\")\"+(e.scale<1?\"scale(\"+e.scale+\")\":\"\")+(e.rotate?\"rotate(\"+e.rotate+\")\":\"\")+\"translate(\"+-(r.left+r.right)/2+\",\"+-(r.top+r.bottom)/2+\")\")})}),v&&o(l,m),s.each(function(t){if(t.labelExtraX||t.labelExtraY){var e=c.select(this),r=e.select(\"g.slicetext text\");r.attr(\"transform\",\"translate(\"+t.labelExtraX+\",\"+t.labelExtraY+\")\"+r.attr(\"transform\"));var n=t.cxFinal+t.pxmid[0],i=t.cyFinal+t.pxmid[1],a=\"M\"+n+\",\"+i,o=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var s=t.labelExtraX*t.pxmid[1]/t.pxmid[0],l=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);a+=Math.abs(s)>Math.abs(l)?\"l\"+l*t.pxmid[0]/t.pxmid[1]+\",\"+l+\"H\"+(n+t.labelExtraX+o):\"l\"+t.labelExtraX+\",\"+s+\"v\"+(l-s)+\"h\"+o}else a+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+o;e.append(\"path\").classed(\"textline\",!0).call(f.stroke,m.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,m.outsidetextfont.size/8),d:a,fill:\"none\"})}})})}),setTimeout(function(){u.selectAll(\"tspan\").each(function(){var t=c.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))})},0)}},{\"../../components/color\":533,\"../../components/drawing\":557,\"../../lib/svg_text_utils\":646,\"../../plots/cartesian/graph_interact\":670,\"./helpers\":832,d3:95}],837:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\");e.exports=function(t){t._fullLayout._pielayer.selectAll(\".trace\").each(function(t){var e=t[0],r=e.trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\".top path.surface\").each(function(t){n.select(this).call(i,t,r)})})}},{\"./style_one\":838,d3:95}],838:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\");e.exports=function(t,e,r){var i=r.marker.line.color;Array.isArray(i)&&(i=i[e.i]||n.defaultLine);var a=r.marker.line.width||0;Array.isArray(a)&&(a=a[e.i]||0),t.style({\"stroke-width\":a,fill:e.color}).call(n.stroke,i)}},{\"../../components/color\":533}],839:[function(t,e,r){\"use strict\";var n=t(\"../scattergl/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\"},indices:{valType:\"data_array\"},xbounds:{valType:\"data_array\"},ybounds:{valType:\"data_array\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1},blend:{valType:\"boolean\",dflt:null},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5},sizemax:{valType:\"number\",min:.1,dflt:20},border:{color:{valType:\"color\",arrayOk:!1},arearatio:{valType:\"number\",min:0,max:1,dflt:0}}}}},{\"../scattergl/attributes\":880}],840:[function(t,e,r){\"use strict\";function n(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=a(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}function i(t,e){var r=new n(t,e.uid);return r.update(e),r}var a=t(\"gl-pointcloud2d\"),o=t(\"../../lib/str2rgbarray\"),s=t(\"../scatter/get_trace_color\"),l=[\"xaxis\",\"yaxis\"],u=n.prototype;u.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},u.update=function(t){this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.updateFast(t),this.color=s(t,{})},u.updateFast=function(t){var e,r,n,i,a,s,l=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,c=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,f=t.indices,d=this.bounds;if(c){if(n=c,e=c.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(s=0;s<e;s++)i=n[2*s],a=n[2*s+1],i<d[0]&&(d[0]=i),i>d[2]&&(d[2]=i),a<d[1]&&(d[1]=a),a>d[3]&&(d[3]=a);if(f)r=f;else for(r=new Int32Array(e),s=0;s<e;s++)r[s]=s}else for(e=l.length,n=new Float32Array(2*e),r=new 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r,n,i,a=e||.5,o=0;o<2;o++)r=this.scene[l[o]],n=r._min,n||(n=[]),n.push({val:t[o],pad:a}),i=r._max,i||(i=[]),i.push({val:t[o+2],pad:a})},u.dispose=function(){this.pointcloud.dispose()},e.exports=i},{\"../../lib/str2rgbarray\":645,\"../scatter/get_trace_color\":852,\"gl-pointcloud2d\":198}],841:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\");e.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),a(\"text\"),a(\"marker.color\",r),a(\"marker.opacity\"),a(\"marker.blend\"),a(\"marker.sizemin\"),a(\"marker.sizemax\"),a(\"marker.border.color\",r),a(\"marker.border.arearatio\")}},{\"../../lib\":632,\"./attributes\":839}],842:[function(t,e,r){\"use strict\";var 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u=t.opacity;if(t.marker&&t.marker.opacity&&(u*=t.marker.opacity),r={gl:o,position:l.position,color:l.scatterColor,size:l.scatterSize,glyph:l.scatterMarker,opacity:u,orthographic:!0,lineWidth:l.scatterLineWidth,lineColor:l.scatterLineColor,project:l.project,projectScale:l.projectScale,projectOpacity:l.projectOpacity},this.mode.indexOf(\"markers\")!==-1?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=p(r),this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),a={gl:o,position:l.position,glyph:l.text,color:l.textColor,size:l.textSize,angle:l.textAngle,alignment:l.textOffset,font:l.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=l.text,this.mode.indexOf(\"text\")!==-1?this.textMarkers?this.textMarkers.update(a):(this.textMarkers=p(a),this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),n={gl:o,position:l.position,color:l.errorColor,error:l.errorBounds,lineWidth:l.errorLineWidth,capSize:l.errorCapSize,opacity:t.opacity},this.errorBars?l.errorBounds?this.errorBars.update(n):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):l.errorBounds&&(this.errorBars=g(n),this.scene.glplot.add(this.errorBars)),l.delaunayAxis>=0){var f=i(l.position,l.delaunayColor,l.delaunayAxis);f.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(f):(f.gl=o,this.delaunayMesh=m(f),this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},k.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=f},{\"../../constants/gl3d_dashes\":615,\"../../constants/gl_markers\":616,\"../../lib\":632,\"../../lib/gl_format_color\":630,\"../../lib/str2rgbarray\":645,\"../scatter/make_bubble_size_func\":859,\"./calc_errors\":869,\"delaunay-triangulate\":96,\"gl-error3d\":133,\"gl-line3d\":140,\"gl-mesh3d\":173,\"gl-scatter3d\":216}],871:[function(t,e,r){\"use strict\";function n(t,e,r){var n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,h){function f(r,n){return i.coerce(t,e,c,r,n)}var d=n(t,e,f);if(!d)return void(e.visible=!1);f(\"text\"),f(\"mode\"),a.hasLines(e)&&(f(\"connectgaps\"),s(t,e,r,h,f)),a.hasMarkers(e)&&o(t,e,r,h,f),a.hasText(e)&&l(t,e,h,f);var p=(e.line||{}).color,g=(e.marker||{}).color;f(\"surfaceaxis\")>=0&&f(\"surfacecolor\",p||g);for(var m=[\"x\",\"y\",\"z\"],v=0;v<3;++v){var y=\"projection.\"+m[v];f(y+\".show\")&&(f(y+\".opacity\"),f(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":562,\"../../lib\":632,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":867}],872:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":616,\"../../plots/gl3d\":702,\n",
+       "\"../scatter/colorbar\":847,\"./attributes\":867,\"./calc\":868,\"./convert\":870,\"./defaults\":871}],873:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/colorscale/color_attributes\"),o=t(\"../../lib/extend\").extendFlat,s=n.marker,l=n.line,u=s.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\"],dflt:\"ISO-3\"},mode:o({},n.mode,{dflt:\"markers\"}),text:o({},n.text,{}),textfont:n.textfont,textposition:n.textposition,line:{color:l.color,width:l.width,dash:l.dash},connectgaps:n.connectgaps,marker:o({},{symbol:s.symbol,opacity:s.opacity,size:s.size,sizeref:s.sizeref,sizemin:s.sizemin,sizemode:s.sizemode,showscale:s.showscale,line:o({},{width:u.width},a(\"marker.line\"))},a(\"marker\")),fill:{valType:\"enumerated\",values:[\"none\",\"toself\"],dflt:\"none\"},fillcolor:n.fillcolor,hoverinfo:o({},i.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../components/colorscale/color_attributes\":541,\"../../lib/extend\":625,\"../../plots/attributes\":660,\"../scatter/attributes\":844}],874:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../scatter/colorscale_calc\");e.exports=function(t,e){for(var r=Array.isArray(e.locations),a=r?e.locations.length:e.lon.length,o=[],s=0,l=0;l<a;l++){var u,c={};if(r){var h=e.locations[l];c.loc=h,u=\"string\"!=typeof h}else{var f=e.lon[l],d=e.lat[l];c.lonlat=[+f,+d],u=!n(f)||!n(d)}u?s>0&&(o[s-1].gapAfter=!0):(s++,o.push(c))}return i(e),o}},{\"../scatter/colorscale_calc\":848,\"fast-isnumeric\":104}],875:[function(t,e,r){\"use strict\";function n(t,e,r){var n,i,a=0,o=r(\"locations\");return o?(r(\"locationmode\"),a=o.length):(n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length),a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a)}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,h){function f(r,n){return i.coerce(t,e,c,r,n)}var d=n(t,e,f);return d?(f(\"text\"),f(\"mode\"),a.hasLines(e)&&(s(t,e,r,h,f),f(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,f),a.hasText(e)&&l(t,e,h,f),f(\"fill\"),\"none\"!==e.fill&&u(t,e,r,f),void f(\"hoverinfo\",1===h._dataLength?\"lon+lat+location+text\":void 0)):void(e.visible=!1)}},{\"../../lib\":632,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":873}],876:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.location=e.lon?e.lon:null,t}},{}],877:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t){return a.tickText(r,r.c2l(t),\"hover\").text+\"\\xb0\"}var i=t.hoverinfo,o=\"all\"===i?s.hoverinfo.flags:i.split(\"+\"),l=o.indexOf(\"location\")!==-1&&Array.isArray(t.locations),u=o.indexOf(\"lon\")!==-1,c=o.indexOf(\"lat\")!==-1,h=o.indexOf(\"text\")!==-1,f=[];return l?f.push(e.loc):u&&c?f.push(\"(\"+n(e.lonlat[0])+\", \"+n(e.lonlat[1])+\")\"):u?f.push(\"lon: \"+n(e.lonlat[0])):c&&f.push(\"lat: \"+n(e.lonlat[1])),h&&f.push(e.tx||t.text),f.join(\"<br>\")}var i=t(\"../../plots/cartesian/graph_interact\"),a=t(\"../../plots/cartesian/axes\"),o=t(\"../scatter/get_trace_color\"),s=t(\"./attributes\");e.exports=function(t){function e(t){return c.projection(t)}function r(t){var r=t.lonlat;if(null===r[0]||null===r[1])return 1/0;if(c.isLonLatOverEdges(r))return 1/0;var n=e(r),i=l.c2p(),a=u.c2p(),o=Math.abs(i-n[0]),s=Math.abs(a-n[1]),h=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(o*o+s*s)-h,1-3/h)}var a=t.cd,s=a[0].trace,l=t.xa,u=t.ya,c=t.subplot;if(!a[0].placeholder&&(i.getClosest(a,r,t),t.index!==!1)){var h=a[t.index],f=h.lonlat,d=e(f),p=h.mrc||1;return t.x0=d[0]-p,t.x1=d[0]+p,t.y0=d[1]-p,t.y1=d[1]+p,t.loc=h.loc,t.lat=f[0],t.lon=f[1],t.color=o(s,h),t.extraText=n(s,h,c.mockAxis),[t]}}},{\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/graph_interact\":670,\"../scatter/get_trace_color\":852,\"./attributes\":873}],878:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\"),n.hoverPoints=t(\"./hover\"),n.eventData=t(\"./event_data\"),n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":687,\"../scatter/colorbar\":847,\"./attributes\":873,\"./calc\":874,\"./defaults\":875,\"./event_data\":876,\"./hover\":877,\"./plot\":879}],879:[function(t,e,r){\"use strict\";function n(t,e){if(!Array.isArray(t.locations))return u.identity;var r=c(t,e),n=t.locationmode;return function(t){var e=h(n,t.loc,r);return e?(t.lonlat=e.properties.ct,t):(t.lonlat=[null,null],!1)}}function i(t,e,r){function n(t,n){d(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function a(t){var e=t.framework.selectAll(\"g.trace.scattergeo\");e.style(\"opacity\",function(t){return t[0].trace.opacity}),e.each(function(t){var e=t[0].trace,r=o.select(this);r.selectAll(\"path.point\").call(s.pointStyle,e),r.selectAll(\"text\").call(s.textPointStyle,e)}),e.selectAll(\"path.js-line\").style(\"fill\",\"none\").each(function(t){var e=o.select(this),r=t.trace,n=r.line||{};e.call(l.stroke,n.color).call(s.dashLine,n.dash||\"\",n.width||0),\"none\"!==r.fill&&e.call(l.fill,r.fillcolor)})}var o=t(\"d3\"),s=t(\"../../components/drawing\"),l=t(\"../../components/color\"),u=t(\"../../lib\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,h=t(\"../../lib/geo_location_utils\").locationToFeature,f=t(\"../../lib/geojson_utils\"),d=t(\"../../lib/array_to_calc_item\"),p=t(\"../scatter/subtypes\");e.exports=function(t,e){function r(t){return t[0].trace.uid}var s=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,r);s.enter().append(\"g\").attr(\"class\",\"trace scattergeo\"),s.exit().remove(),s.selectAll(\"*\").remove(),s.each(function(e){var r=o.select(this),a=e[0].trace,s=n(a,t.topojson);e[0].placeholder&&r.remove();for(var l=[],u=0;u<e.length;u++){var c=s(e[u]);c&&(i(a,e[u],u),l.push(c))}if(p.hasLines(a)||\"none\"!==a.fill){var h=f.calcTraceToLineCoords(l),d=\"none\"!==a.fill?f.makePolygon(h,a):f.makeLine(h,a);r.selectAll(\"path.js-line\").data([d]).enter().append(\"path\").classed(\"js-line\",!0)}p.hasMarkers(a)&&r.selectAll(\"path.point\").data(l).enter().append(\"path\").classed(\"point\",!0),p.hasText(a)&&r.selectAll(\"g\").data(l).enter().append(\"g\").append(\"text\")}),a(t)}},{\"../../components/color\":533,\"../../components/drawing\":557,\"../../lib\":632,\"../../lib/array_to_calc_item\":621,\"../../lib/geo_location_utils\":628,\"../../lib/geojson_utils\":629,\"../../lib/topojson_utils\":647,\"../scatter/subtypes\":864,d3:95}],880:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../components/colorscale/color_attributes\"),a=t(\"../../constants/gl2d_dashes\"),o=t(\"../../constants/gl_markers\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../lib/extend\").extendDeep,u=n.line,c=n.marker,h=c.line;e.exports={x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,text:s({},n.text,{}),mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\"],extras:[\"none\"]},line:{color:u.color,width:u.width,dash:{valType:\"enumerated\",values:Object.keys(a),dflt:\"solid\"}},marker:l({},i(\"marker\"),{symbol:{valType:\"enumerated\",values:Object.keys(o),dflt:\"circle\",arrayOk:!0},size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,opacity:c.opacity,showscale:c.showscale,line:l({},i(\"marker.line\"),{width:h.width})}),connectgaps:n.connectgaps,fill:s({},n.fill,{values:[\"none\",\"tozeroy\",\"tozerox\"]}),fillcolor:n.fillcolor,_nestedModules:{error_x:\"ErrorBars\",error_y:\"ErrorBars\",\"marker.colorbar\":\"Colorbar\"}}},{\"../../components/colorscale/color_attributes\":541,\"../../constants/gl2d_dashes\":614,\"../../constants/gl_markers\":616,\"../../lib/extend\":625,\"../scatter/attributes\":844}],881:[function(t,e,r){\"use 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R,O=A(t),F=t.marker,j=F.opacity,N=t.opacity,B=s(F,j,N,y),U=I(F.symbol,y),V=z(F.line.width,y),q=s(F.line,j,N,y);for(D=i(O,F.size,y),u=0;u<T;++u)for(R=b[u],this.scatterOptions.sizes[u]=4*D[R],this.scatterOptions.glyphs[u]=U[R],this.scatterOptions.borderWidths[u]=.5*V[R],c=0;c<4;++c)this.scatterOptions.colors[4*u+c]=B[4*R+c],this.scatterOptions.borderColors[4*u+c]=q[4*R+c];this.fancyScatter.update(this.scatterOptions)}else this.scatterOptions.positions=new Float64Array(0),this.scatterOptions.glyphs=[],this.fancyScatter.update(this.scatterOptions);this.scatterOptions.positions=new Float64Array(0),this.scatterOptions.glyphs=[],this.scatter.update(this.scatterOptions),this.expandAxesFancy(o,l,D)},L.updateLines=function(t,e){var r;if(this.hasLines){var n=e;if(!t.connectgaps){var i=0,a=this.xData,s=this.yData;for(n=new Float64Array(2*a.length),r=0;r<a.length;++r)n[i++]=a[r],n[i++]=s[r]}this.lineOptions.positions=n;var l=o(t.line.color,t.opacity,1),u=Math.round(.5*this.lineOptions.width),c=(E[t.line.dash]||[1]).slice();for(r=0;r<c.length;++r)c[r]*=u;switch(t.fill){case\"tozeroy\":this.lineOptions.fill=[!1,!0,!1,!1];break;case\"tozerox\":this.lineOptions.fill=[!0,!1,!1,!1];break;default:this.lineOptions.fill=[!1,!1,!1,!1]}var h=b(t.fillcolor);this.lineOptions.color=l,this.lineOptions.width=2*t.line.width,this.lineOptions.dashes=c,this.lineOptions.fillColor=[h,h,h,h]}else this.lineOptions.positions=new Float64Array(0);this.line.update(this.lineOptions)},L.updateError=function(t,e,r,n){var i=this[\"error\"+t],a=e[\"error_\"+t.toLowerCase()],s=this[\"error\"+t+\"Options\"];\"x\"===t.toLowerCase()&&a.copy_ystyle&&(a=e.error_y),this[\"hasError\"+t]?(s.positions=r,s.errors=n,s.capSize=a.width,s.lineWidth=a.thickness/2,s.color=o(a.color,1,1)):s.positions=new Float64Array(0),i.update(s)},L.expandAxesFast=function(t,e){for(var r,n,i,a=e||10,o=0;o<2;o++)r=this.scene[S[o]],n=r._min,n||(n=[]),n.push({val:t[o],pad:a}),i=r._max,i||(i=[]),i.push({val:t[o+2],pad:a})},L.expandAxesFancy=function(t,e,r){var n=this.scene,i={padded:!0,ppad:r};v.expand(n.xaxis,t,i),v.expand(n.yaxis,e,i)},L.dispose=function(){this.line.dispose(),this.errorX.dispose(),this.errorY.dispose(),this.scatter.dispose(),this.fancyScatter.dispose()},e.exports=c},{\"../../components/errorbars\":563,\"../../constants/gl2d_dashes\":614,\"../../constants/gl_markers\":616,\"../../lib\":632,\"../../lib/gl_format_color\":630,\"../../lib/str2rgbarray\":645,\"../../lib/typed_array_truncate\":648,\"../../plots/cartesian/axes\":662,\"../../plots/cartesian/axis_autotype\":663,\"../scatter/get_trace_color\":852,\"../scatter/make_bubble_size_func\":859,\"../scatter/subtypes\":864,\"fast-isnumeric\":104,\"gl-error2d\":131,\"gl-line2d\":138,\"gl-scatter2d\":213,\"gl-scatter2d-fancy\":208}],882:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/xy_defaults\"),s=t(\"../scatter/marker_defaults\"),l=t(\"../scatter/line_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"../../components/errorbars/defaults\"),h=t(\"./attributes\");e.exports=function(t,e,r,f){function d(r,i){return n.coerce(t,e,h,r,i)}var p=o(t,e,d);return p?(d(\"text\"),d(\"mode\",p<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(d(\"connectgaps\"),l(t,e,r,f,d)),a.hasMarkers(e)&&s(t,e,r,f,d),d(\"fill\"),\"none\"!==e.fill&&u(t,e,r,d),c(t,e,r,{axis:\"y\"}),void c(t,e,r,{axis:\"x\",inherit:\"y\"})):void(e.visible=!1)}},{\"../../components/errorbars/defaults\":562,\"../../lib\":632,\"../scatter/constants\":849,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/xy_defaults\":866,\"./attributes\":880}],883:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"../scatter3d/calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"scattergl\",n.basePlotModule=t(\"../../plots/gl2d\"),n.categories=[\"gl2d\",\"symbols\",\"errorBarsOK\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/gl2d\":699,\"../scatter/colorbar\":847,\"../scatter3d/calc\":868,\"./attributes\":880,\"./convert\":881,\"./defaults\":882}],884:[function(t,e,r){\"use strict\";var n=t(\"../scattergeo/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/mapbox/layout_attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=n.line,u=n.marker;e.exports={lon:n.lon,lat:n.lat,mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],dflt:\"markers\",extras:[\"none\"]},text:s({},i.text,{}),line:{color:l.color,width:l.width,dash:l.dash},connectgaps:i.connectgaps,marker:{symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},opacity:s({},u.opacity,{arrayOk:!1}),size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,color:u.color,colorscale:u.colorscale,cauto:u.cauto,cmax:u.cmax,cmin:u.cmin,autocolorscale:u.autocolorscale,reversescale:u.reversescale,showscale:u.showscale},fill:n.fill,fillcolor:i.fillcolor,textfont:a.layers.symbol.textfont,textposition:a.layers.symbol.textposition,hoverinfo:s({},o.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../lib/extend\":625,\"../../plots/attributes\":660,\"../../plots/mapbox/layout_attributes\":719,\"../scatter/attributes\":844,\"../scattergeo/attributes\":873}],885:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale\"),o=t(\"../scatter/subtypes\"),s=t(\"../scatter/colorscale_calc\"),l=t(\"../scatter/make_bubble_size_func\");e.exports=function(t,e){var r=e.lon.length,u=e.marker,c=o.hasMarkers(e),h=c&&Array.isArray(u.color),f=c&&Array.isArray(u.size),d=c&&Array.isArray(u.symbol),p=Array.isArray(e.text);s(e);for(var g=a.hasColorscale(e,\"marker\")?a.makeColorScaleFunc(a.extractScale(u.colorscale,u.cmin,u.cmax)):i.identity,m=o.isBubble(e)?l(e):i.identity,v=[],y=0,x=0;x<r;x++){var b=e.lon[x],_=e.lat[x];if(n(b)&&n(_)){var w={};if(y++,w.lonlat=[+b,+_],c){if(h){var M=u.color[x];w.mc=M,w.mcc=g(M)}if(f){var A=u.size[x];w.ms=A,w.mrc=m(A)}if(d){var k=u.symbol[x];w.mx=\"string\"==typeof k?k:\"circle\"}}if(p){var T=e.text[x];w.tx=\"string\"==typeof T?T:\"\"}v.push(w)}else y>0&&(v[y-1].gapAfter=!0)}return v}},{\"../../components/colorscale\":548,\"../../lib\":632,\"../scatter/colorscale_calc\":848,\"../scatter/make_bubble_size_func\":859,\"../scatter/subtypes\":864,\"fast-isnumeric\":104}],886:[function(t,e,r){\"use strict\";function n(){return{geojson:h.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function i(t,e){function r(t,r,n,i){void 0===e[r][n]&&(e[r][n]=i),t[r]=e[r][n]}for(var n=t[0].trace,i=n.marker,a=Array.isArray(i.color),o=Array.isArray(i.size),s=[],l=0;l<t.length;l++){var u=t[l],c={};a&&r(c,p,u.mcc,l),o&&r(c,g,u.mrc,l),s.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:u.lonlat},properties:c})}return{type:\"FeatureCollection\",features:s}}function a(t){for(var e=t[0].trace,r=e.marker||{},n=r.symbol,i=e.text,a=\"circle\"!==n?l(n):u,o=f.hasText(e)?l(i):u,s=[],c=0;c<t.length;c++){var h=t[c];s.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:h.lonlat},properties:{symbol:a(h.mx),text:o(h.tx)}})}return{type:\"FeatureCollection\",features:s}}function o(t,e){var r,n=t.marker;if(Array.isArray(n.color)){for(var i=Object.keys(e[p]),a=[],o=0;o<i.length;o++){var s=i[o];a.push([e[p][s],s])}r={property:p,stops:a}}else r=n.color;return r}function s(t,e){var r,n=t.marker;if(Array.isArray(n.size)){for(var i=Object.keys(e[g]),a=[],o=0;o<i.length;o++){var s=i[o];a.push([e[g][s],+s])}a.sort(function(t,e){return t[0]-e[0]}),r={property:g,stops:a}}else r=n.size/2;return r}function l(t){return Array.isArray(t)?function(t){return t}:t?function(){return t}:u}function u(){return\"\"}var c=t(\"../../lib\"),h=t(\"../../lib/geojson_utils\"),f=t(\"../scatter/subtypes\"),d=t(\"../../plots/mapbox/convert_text_opts\"),p=\"circle-color\",g=\"circle-radius\";e.exports=function(t){var e=t[0].trace,r=e.visible===!0,l=\"none\"!==e.fill,u=f.hasLines(e),m=f.hasMarkers(e),v=f.hasText(e),y=m&&\"circle\"===e.marker.symbol,x=m&&\"circle\"!==e.marker.symbol,b=n(),_=n(),w=n(),M=n(),A={fill:b,line:_,circle:w,symbol:M};if(!r||t[0].placeholder)return A;var k;if((l||u)&&(k=h.calcTraceToLineCoords(t)),l&&(b.geojson=h.makePolygon(k),b.layout.visibility=\"visible\",c.extendFlat(b.paint,{\"fill-color\":e.fillcolor})),u&&(_.geojson=h.makeLine(k),_.layout.visibility=\"visible\",c.extendFlat(_.paint,{\"line-width\":e.line.width,\"line-color\":e.line.color,\"line-opacity\":e.opacity})),y){var T={};T[p]={},T[g]={},w.geojson=i(t,T),w.layout.visibility=\"visible\",c.extendFlat(w.paint,{\"circle-opacity\":e.opacity*e.marker.opacity,\"circle-color\":o(e,T),\"circle-radius\":s(e,T)})}if((x||v)&&(M.geojson=a(t),c.extendFlat(M.layout,{visibility:\"visible\",\"icon-image\":\"{symbol}-15\",\"text-field\":\"{text}\"}),x&&(c.extendFlat(M.layout,{\"icon-size\":e.marker.size/10}),c.extendFlat(M.paint,{\"icon-opacity\":e.opacity*e.marker.opacity,\"icon-color\":e.marker.color})),v)){var E=(e.marker||{}).size,S=d(e.textposition,E);c.extendFlat(M.layout,{\"text-size\":e.textfont.size,\"text-anchor\":S.anchor,\"text-offset\":S.offset}),c.extendFlat(M.paint,{\"text-color\":e.textfont.color,\"text-opacity\":e.opacity})}return A}},{\"../../lib\":632,\"../../lib/geojson_utils\":629,\"../../plots/mapbox/convert_text_opts\":716,\"../scatter/subtypes\":864}],887:[function(t,e,r){\"use strict\";function n(t,e,r){var n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length);return a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\"),h=t(\"../scatter/attributes\");e.exports=function(t,e,r,f){function d(r,n){return i.coerce(t,e,c,r,n)}function p(r,n){var a=r.indexOf(\".line\")===-1?c:h;return i.coerce(t,e,a,r,n)}var g=n(t,e,d);if(!g)return void(e.visible=!1);if(d(\"text\"),d(\"mode\"),a.hasLines(e)&&(s(t,e,r,f,d),d(\"connectgaps\")),a.hasMarkers(e)){o(t,e,r,f,p);var m=e.marker;\"circle\"!==m.symbol&&(Array.isArray(m.size)&&(m.size=m.size[0]),Array.isArray(m.color)&&(m.color=m.color[0]))}a.hasText(e)&&l(t,e,f,d),d(\"fill\"),\"none\"!==e.fill&&u(t,e,r,d),d(\"hoverinfo\",1===f._dataLength?\"lon+lat+text\":void 0)}},{\"../../lib\":632,\"../scatter/attributes\":844,\"../scatter/fillcolor_defaults\":851,\"../scatter/line_defaults\":855,\"../scatter/marker_defaults\":860,\"../scatter/subtypes\":864,\"../scatter/text_defaults\":865,\"./attributes\":884}],888:[function(t,e,r){\"use strict\";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t}},{}],889:[function(t,e,r){\"use strict\";function n(t,e){function r(t){return t+\"\\xb0\"}var n=t.hoverinfo.split(\"+\"),i=n.indexOf(\"all\")!==-1,a=n.indexOf(\"lon\")!==-1,o=n.indexOf(\"lat\")!==-1,s=e.lonlat,l=[];return i||a&&o?l.push(\"(\"+r(s[0])+\", \"+r(s[1])+\")\"):a?l.push(\"lon: \"+r(s[0])):o&&l.push(\"lat: \"+r(s[1])),(i||n.indexOf(\"text\")!==-1)&&l.push(e.tx||t.text),l.join(\"<br>\")}var i=t(\"../../plots/cartesian/graph_interact\"),a=t(\"../scatter/get_trace_color\");e.exports=function(t,e,r){function o(t){var e=t.lonlat,n=Math.abs(u.c2p(e)-u.c2p([d,e[1]])),i=Math.abs(c.c2p(e)-c.c2p([e[0],r])),a=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(n*n+i*i)-a,1-3/a)}var s=t.cd,l=s[0].trace,u=t.xa,c=t.ya;if(!s[0].placeholder){var h=e>=0?Math.floor((e+180)/360):Math.ceil((e-180)/360),f=360*h,d=e-f;if(i.getClosest(s,o,t),t.index!==!1){var p=s[t.index],g=p.lonlat,m=[g[0]+f,g[1]],v=u.c2p(m),y=c.c2p(m),x=p.mrc||1;return t.x0=v-x,t.x1=v+x,t.y0=y-x,t.y1=y+x,t.color=a(l,p),t.extraText=n(l,p),[t]}}}},{\"../../plots/cartesian/graph_interact\":670,\"../scatter/get_trace_color\":852}],890:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.hoverPoints=t(\"./hover\"),n.eventData=t(\"./event_data\"),n.plot=t(\"./plot\"),n.moduleType=\"trace\",n.name=\"scattermapbox\",n.basePlotModule=t(\"../../plots/mapbox\"),n.categories=[\"mapbox\",\"gl\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/mapbox\":717,\"../scatter/colorbar\":847,\"./attributes\":884,\"./calc\":885,\"./defaults\":887,\"./event_data\":888,\"./hover\":889,\"./plot\":891}],891:[function(t,e,r){\"use strict\";function n(t,e){this.mapbox=t,this.map=t.map,this.uid=e,this.idSourceFill=e+\"-source-fill\",this.idSourceLine=e+\"-source-line\",this.idSourceCircle=e+\"-source-circle\",this.idSourceSymbol=e+\"-source-symbol\",this.idLayerFill=e+\"-layer-fill\",this.idLayerLine=e+\"-layer-line\",this.idLayerCircle=e+\"-layer-circle\",this.idLayerSymbol=e+\"-layer-symbol\",this.mapbox.initSource(this.idSourceFill),this.mapbox.initSource(this.idSourceLine),this.mapbox.initSource(this.idSourceCircle),this.mapbox.initSource(this.idSourceSymbol),this.map.addLayer({id:this.idLayerFill,source:this.idSourceFill,type:\"fill\"}),this.map.addLayer({id:this.idLayerLine,source:this.idSourceLine,type:\"line\"}),this.map.addLayer({id:this.idLayerCircle,source:this.idSourceCircle,type:\"circle\"}),this.map.addLayer({id:this.idLayerSymbol,source:this.idSourceSymbol,type:\"symbol\"})}function i(t){return\"visible\"===t.layout.visibility}var a=t(\"./convert\"),o=n.prototype;o.update=function(t){var e=this.mapbox,r=a(t);e.setOptions(this.idLayerFill,\"setLayoutProperty\",r.fill.layout),e.setOptions(this.idLayerLine,\"setLayoutProperty\",r.line.layout),e.setOptions(this.idLayerCircle,\"setLayoutProperty\",r.circle.layout),e.setOptions(this.idLayerSymbol,\"setLayoutProperty\",r.symbol.layout),i(r.fill)&&(e.setSourceData(this.idSourceFill,r.fill.geojson),e.setOptions(this.idLayerFill,\"setPaintProperty\",r.fill.paint)),i(r.line)&&(e.setSourceData(this.idSourceLine,r.line.geojson),e.setOptions(this.idLayerLine,\"setPaintProperty\",r.line.paint)),i(r.circle)&&(e.setSourceData(this.idSourceCircle,r.circle.geojson),e.setOptions(this.idLayerCircle,\"setPaintProperty\",r.circle.paint)),i(r.symbol)&&(e.setSourceData(this.idSourceSymbol,r.symbol.geojson),e.setOptions(this.idLayerSymbol,\"setPaintProperty\",r.symbol.paint))},o.dispose=function(){var t=this.map;t.removeLayer(this.idLayerFill),t.removeLayer(this.idLayerLine),t.removeLayer(this.idLayerCircle),t.removeLayer(this.idLayerSymbol),t.removeSource(this.idSourceFill),t.removeSource(this.idSourceLine),t.removeSource(this.idSourceCircle),t.removeSource(this.idSourceSymbol)},e.exports=function(t,e){var r=e[0].trace,i=new n(t,r.uid);return i.update(e),i}},{\"./convert\":886}],892:[function(t,e,r){\"use strict\";var 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o=t(\"../lib\");r.moduleType=\"transform\",r.name=\"groupby\",r.attributes={enabled:{valType:\"boolean\",dflt:!0},groups:{valType:\"data_array\",dflt:[]},style:{valType:\"any\",dflt:{}}},r.supplyDefaults=function(t){function e(e,i){return o.coerce(t,n,r.attributes,e,i)}var n={},i=e(\"enabled\");return i?(e(\"groups\"),e(\"style\"),n):n},r.transform=function(t,e){for(var r=[],n=0;n<t.length;n++)r=r.concat(a(t[n],e));return r}},{\"../lib\":632}]},{},[15])(15)});\n",
+       "     });\n",
+       "     require(['plotly'], function(Plotly) {\n",
+       "         window.Plotly = Plotly;\n",
+       "     });\n",
+       " </script>\n",
+       " <p>Plotly javascript loaded.</p>\n",
+       " <p>To load again call <pre>init_notebook(true)</pre></p>\n",
+       " "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Plots.PlotlyJSBackend()"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "using Plots\n",
+    "plotlyjs()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:10:22.463525",
+     "start_time": "2016-12-05T07:10:20.647Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "mm = readcsv(\"DatosPlano/mms2.csv\")[:,1]\n",
+    "rr = readcsv(\"DatosPlano/rrs2.csv\")[:,1]\n",
+    "cs = readcsv(\"DatosPlano/ccs2.csv\")[:,1];\n",
+    "append!(mm, readcsv(\"DatosPlano/mms3.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs3.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs3.csv\")[:,1]);\n",
+    "append!(mm, readcsv(\"DatosPlano/mms1.csv\")[:,1])\n",
+    "append!(rr, readcsv(\"DatosPlano/rrs1.csv\")[:,1])\n",
+    "append!(cs, readcsv(\"DatosPlano/ccs1.csv\")[:,1]);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2016-12-05T01:10:35.775895",
+     "start_time": "2016-12-05T07:10:21.261Z"
+    },
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<html>\n",
+       "<head>\n",
+       "     <script src=\"/home/daniel/.julia/v0.5/PlotlyJS/deps/plotly-latest.min.js\"></script>\n",
+       "</head>\n",
+       "<body>\n",
+       "     <div id=\"c59b0784-cb52-4b39-84d6-0cfd22c5a459\" class=\"plotly-graph-div\"></div>\n",
+       "\n",
+       "<script>\n",
+       "    window.PLOTLYENV=window.PLOTLYENV || {};\n",
+       "    window.PLOTLYENV.BASE_URL=\"https://plot.ly\";\n",
+       "    Plotly.newPlot('c59b0784-cb52-4b39-84d6-0cfd22c5a459', 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+       "               {\"annotations\":[],\"width\":600,\"plot_bgcolor\":\"rgba(255, 255, 255, 1.000)\",\"scene\":{\"yaxis\":{\"type\":\"-\",\"titlefont\":{\"size\":15,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"title\":\"R\",\"tickfont\":{\"size\":11,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"ticks\":\"inside\",\"tickmode\":\"array\",\"showgrid\":true,\"tickvals\":[25.0,50.0,75.0,100.0],\"domain\":[0.08565726159230101,0.9901574803149606],\"ticktext\":[\"25\",\"50\",\"75\",\"100\"],\"tickangle\":0,\"zeroline\":false,\"linecolor\":\"rgba(0, 0, 0, 1.000)\",\"tickcolor\":\"rgba(0, 0, 0, 1.000)\",\"anchor\":\"x\"},\"xaxis\":{\"type\":\"-\",\"titlefont\":{\"size\":15,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"title\":\"M\",\"tickfont\":{\"size\":11,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"ticks\":\"inside\",\"tickmode\":\"array\",\"showgrid\":true,\"tickvals\":[25.0,50.0,75.0,100.0],\"domain\":[0.0830307669874599,0.9934383202099737],\"ticktext\":[\"25\",\"50\",\"75\",\"100\"],\"tickangle\":0,\"zeroline\":false,\"linecolor\":\"rgba(0, 0, 0, 1.000)\",\"tickcolor\":\"rgba(0, 0, 0, 1.000)\",\"anchor\":\"y\"},\"zaxis\":{\"type\":\"-\",\"titlefont\":{\"size\":15,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"title\":\"\",\"ticks\":\"inside\",\"tickfont\":{\"size\":11,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"tickmode\":\"array\",\"showgrid\":true,\"tickvals\":[500.0,1000.0,1500.0,2000.0],\"ticktext\":[\"500\",\"1000\",\"1500\",\"2000\"],\"tickangle\":0,\"zeroline\":false,\"linecolor\":\"rgba(0, 0, 0, 1.000)\",\"tickcolor\":\"rgba(0, 0, 0, 1.000)\"}},\"showlegend\":true,\"legend\":{\"bgcolor\":\"rgba(255, 255, 255, 1.000)\",\"font\":{\"size\":11,\"color\":\"rgba(0, 0, 0, 1.000)\",\"family\":\"Helvetica\"},\"bordercolor\":\"rgba(0, 0, 0, 1.000)\"},\"paper_bgcolor\":\"rgba(255, 255, 255, 1.000)\",\"margin\":{\"r\":0,\"l\":0,\"b\":0,\"t\":20},\"height\":400}, {showLink: false});\n",
+       "\n",
+       " </script>\n",
+       "\n",
+       "</body>\n",
+       "</html>\n"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plot(mm, rr, cs)\n",
+    "xlabel!(\"M\")\n",
+    "ylabel!(\"R\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# ¡Gracias por su atención!\n",
+    "\n",
+    "![](Figures/git.png)"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "celltoolbar": "Slideshow",
+  "kernelspec": {
+   "display_name": "Julia 0.5.0",
+   "language": "julia",
+   "name": "julia-0.5"
+  },
+  "language_info": {
+   "file_extension": ".jl",
+   "mimetype": "application/julia",
+   "name": "julia",
+   "version": "0.5.0"
+  },
+  "latex_envs": {
+   "bibliofile": "biblio.bib",
+   "cite_by": "apalike",
+   "current_citInitial": 1,
+   "eqLabelWithNumbers": true,
+   "eqNumInitial": 0
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}