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MilesCranmer · Dec 25, 2023 · 573126d · 573126d
1 parent 79c61e4
commit 573126d
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Showing 4 changed files with 14 additions and 7 deletions.
diff --git a/src/CheckConstraints.jl b/src/CheckConstraints.jl
@@ -43,7 +43,7 @@ function count_max_nestedness(tree, degree, op)
         t -> 0,  # Leafs
         t -> (t.degree == degree && t.op == op) ? 1 : 0,  # Branches
         (p, c...) -> p + max(c...),  # Reduce
-        tree,
+        tree;
         break_sharing=Val(true),
     )
     # Remove count of self:

diff --git a/src/Configure.jl b/src/Configure.jl
@@ -251,7 +251,9 @@ function import_module_on_workers(procs, filename::String, options::Options, ver
     end
 end
 
-function test_module_on_workers(procs, options::Options, verbosity, ::Type{N}) where {N<:AbstractExpressionNode}
+function test_module_on_workers(
+    procs, options::Options, verbosity, ::Type{N}
+) where {N<:AbstractExpressionNode}
     verbosity > 0 && @info "Testing module on workers..."
     futures = []
     for proc in procs

diff --git a/src/HallOfFame.jl b/src/HallOfFame.jl
@@ -1,7 +1,6 @@
 module HallOfFameModule
 
-import DynamicExpressions:
-    AbstractExpressionNode, Node, constructorof, string_tree
+import DynamicExpressions: AbstractExpressionNode, Node, constructorof, string_tree
 import DynamicExpressions.EquationModule: with_type_parameters
 import ..UtilsModule: split_string
 import ..CoreModule: MAX_DEGREE, Options, Dataset, DATA_TYPE, LOSS_TYPE, relu

diff --git a/src/SymbolicRegression.jl b/src/SymbolicRegression.jl
@@ -589,8 +589,15 @@ function _equation_search(
     verbosity,
     progress,
     ::Val{RETURN_STATE},
-) where {T<:DATA_TYPE,L<:LOSS_TYPE,D<:Dataset{T,L},N<:AbstractExpressionNode{T},PARALLELISM,RETURN_STATE,DIM_OUT}
-
+) where {
+    T<:DATA_TYPE,
+    L<:LOSS_TYPE,
+    D<:Dataset{T,L},
+    N<:AbstractExpressionNode{T},
+    PARALLELISM,
+    RETURN_STATE,
+    DIM_OUT,
+}
     stdin_reader = watch_stream(stdin)
 
     if options.define_helper_functions
@@ -631,7 +638,6 @@ function _equation_search(
     # Best 10 members from each population for migration:
     bestSubPops = init_dummy_pops(options.populations, datasets, options, N)
 
-
     # Pointers to populations on each worker:
     worker_output = [WorkerOutputType[] for j in 1:nout]
     # Initialize storage for workers