State dependent rates (#35)

* rate functions can be a function of the current state and time

* version bump

* Added backwards compatibility with old method of just time dependent rate function

* Made tagbot run more frequently

* bump documentation julia version

* Fix typo in github actions

* Added install of compose to hopefully get the latest version

* grasping at straws now...

.github/workflows/TagBot.yml

@@ -1,7 +1,7 @@
 name: TagBot
 on:
   schedule:
-    - cron: 0 0 * * *
+    - cron: 0 * * * *
 jobs:
   TagBot:
     runs-on: ubuntu-latest

.github/workflows/docs.yml

@@ -10,13 +10,13 @@ jobs:
       - name: "Set up Julia"
         uses: julia-actions/setup-julia@latest
         with:
-          version: '1.4'
+          version: '1.5'
       - name: "Install system dependencies"
         run: |
           sudo apt-get update
           sudo apt-get install graphviz ttf-dejavu
       - name: "Install Julia dependencies"
-        run: julia --project=docs -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate();'
+        run: julia --project=docs -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate(); Pkg.update();'
       - name: "Build and deploy docs"
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

Project.toml

@@ -1,7 +1,7 @@
 name = "Petri"
 uuid = "4259d249-1051-49fa-8328-3f8ab9391c33"
 authors = ["Micah Halter <[email protected]>", "James Fairbanks <[email protected]>"]
-version = "1.1.1"
+version = "1.2"
 
 [deps]
 AutoHashEquals = "15f4f7f2-30c1-5605-9d31-71845cf9641f"

examples/epidemiology.jl

@@ -32,7 +32,10 @@ Graph(sir)
 
 u0 = LVector(S=990.0, I=10.0, R=0.0)
 tspan = (0.0,40.0)
-β = LVector(inf=0.5/sum(u0), rec=0.25);
+# add a dynamic transition rate for infection
+# where the rate of infection decreases over time
+# as is dependent on the current state of the system
+β = LVector(inf=((u,t)->((3/sum(u))/(t+1))), rec=0.25);
 
 # Petri.jl provides interfaces to StochasticDiffEq.jl, DiffEqJump.jl, and
 # OrdinaryDiffEq.jl Here, we call the `JumpProblem` function that returns an

src/solvers.jl

@@ -11,11 +11,11 @@ import StochasticDiffEq: SDEProblem
 import DiffEqJump: JumpProblem
 
 funcindex!(list, key, f, vals...) = list[key] = f(list[key],vals...)
-valueat(x::Number, t) = x
-valueat(f::Function, t) = f(t)
+valueat(x::Number, u, t) = x
+valueat(f::Function, u, t) = try f(u,t) catch e f(t) end
 transitionrate(S, T, k, rate, t) = exp(reduce((x,y)->x+log(S[y] <= 0 ? 0 : S[y]),
                                        keys(first(T[k]));
-                                       init=log(valueat(rate[k],t))))
+                                       init=log(valueat(rate[k],S,t))))
 
 """ vectorfield(m::Model)