Merge pull request #325 from MilesCranmer/testitem

Refactor tests to use TestItems.jl

src/DimensionalAnalysis.jl

@@ -194,14 +194,11 @@ function violates_dimensional_constraints(
 end
 function violates_dimensional_constraints(
     tree::AbstractExpressionNode{T},
-    X_units::Union{AbstractVector{<:Quantity},Nothing},
+    X_units::AbstractVector{<:Quantity},
     y_units::Union{Quantity,Nothing},
     x::AbstractVector{T},
     options::Options,
 ) where {T}
-    if X_units === nothing && y_units === nothing
-        return false
-    end
     allow_wildcards = !(options.dimensionless_constants_only)
     dimensional_output = violates_dimensional_constraints_dispatch(
         tree, X_units, x, options.operators, allow_wildcards
@@ -217,5 +214,15 @@ function violates_dimensional_constraints(
     end
     return violates
 end
+function violates_dimensional_constraints(
+    ::AbstractExpressionNode{T}, ::Nothing, ::Quantity, ::AbstractVector{T}, ::Options
+) where {T}
+    return error("This should never happen. Please submit a bug report.")
+end
+function violates_dimensional_constraints(
+    ::AbstractExpressionNode{T}, ::Nothing, ::Nothing, ::AbstractVector{T}, ::Options
+) where {T}
+    return false
+end
 
 end

src/InterfaceDynamicExpressions.jl

@@ -129,10 +129,10 @@ end
 Evaluate an expression tree in a way that can be auto-differentiated.
 """
 function differentiable_eval_tree_array(
-    tree::AbstractExpressionNode, X::AbstractArray, options::Options; kws...
+    tree::AbstractExpressionNode, X::AbstractArray, options::Options
 )
     A = expected_array_type(X)
-    return differentiable_eval_tree_array(tree, X, options.operators; kws...)::Tuple{A,Bool}
+    return differentiable_eval_tree_array(tree, X, options.operators)::Tuple{A,Bool}
 end
 
 const WILDCARD_UNIT_STRING = "[?]"

src/LossFunctions.jl

@@ -13,7 +13,7 @@ using ..DimensionalAnalysisModule: violates_dimensional_constraints
 function _loss(
     x::AbstractArray{T}, y::AbstractArray{T}, loss::LT
 ) where {T<:DATA_TYPE,LT<:Union{Function,SupervisedLoss}}
-    if LT <: SupervisedLoss
+    if loss isa SupervisedLoss
         return LossFunctions.mean(loss, x, y)
     else
         l(i) = loss(x[i], y[i])
@@ -24,7 +24,7 @@ end
 function _weighted_loss(
     x::AbstractArray{T}, y::AbstractArray{T}, w::AbstractArray{T}, loss::LT
 ) where {T<:DATA_TYPE,LT<:Union{Function,SupervisedLoss}}
-    if LT <: SupervisedLoss
+    if loss isa SupervisedLoss
         return LossFunctions.sum(loss, x, y, w; normalize=true)
     else
         l(i) = loss(x[i], y[i], w[i])

src/Operators.jl

@@ -96,7 +96,7 @@ function logical_and(x, y)
 end
 
 # Deprecated operations:
-@deprecate pow safe_pow
-@deprecate pow_abs safe_pow
+@deprecate pow(x, y) safe_pow(x, y)
+@deprecate pow_abs(x, y) safe_pow(x, y)
 
 end

src/Options.jl

@@ -549,10 +549,16 @@ $(OPTION_DESCRIPTIONS)
         )
     end
 
+    is_testing = parse(Bool, get(ENV, "SYMBOLIC_REGRESSION_IS_TESTING", "false"))
+
     if output_file === nothing
         # "%Y-%m-%d_%H%M%S.%f"
         date_time_str = Dates.format(Dates.now(), "yyyy-mm-dd_HHMMSS.sss")
         output_file = "hall_of_fame_" * date_time_str * ".csv"
+        if is_testing
+            tmpdir = mktempdir()
+            output_file = joinpath(tmpdir, output_file)
+        end
     end
 
     nuna = length(unary_operators)

src/SearchUtils.jl

@@ -37,6 +37,9 @@ Base.@kwdef struct RuntimeOptions{PARALLELISM,DIM_OUT,RETURN_STATE}
     runtests::Bool
     verbosity::Int64
     progress::Bool
+    parallelism::Val{PARALLELISM}
+    dim_out::Val{DIM_OUT}
+    return_state::Val{RETURN_STATE}
 end
 @unstable @inline function Base.getproperty(
     roptions::RuntimeOptions{P,D,R}, name::Symbol
@@ -108,8 +111,8 @@ macro sr_spawner(expr, kws...)
     @assert all(ex -> ex.head == :(=), kws)
     @assert any(ex -> ex.args[1] == :parallelism, kws)
     @assert any(ex -> ex.args[1] == :worker_idx, kws)
-    parallelism = kws[findfirst(ex -> ex.args[1] == :parallelism, kws)].args[2]
-    worker_idx = kws[findfirst(ex -> ex.args[1] == :worker_idx, kws)].args[2]
+    parallelism = kws[findfirst(ex -> ex.args[1] == :parallelism, kws)::Int].args[2]
+    worker_idx = kws[findfirst(ex -> ex.args[1] == :worker_idx, kws)::Int].args[2]
     return quote
         if $(parallelism) == :serial
             $(expr)

src/SymbolicRegression.jl

@@ -570,7 +570,7 @@ function equation_search(
     # Underscores here mean that we have mutated the variable
     return _equation_search(
         datasets,
-        RuntimeOptions{concurrency,dim_out,_return_state}(;
+        RuntimeOptions(;
             niterations=niterations,
             total_cycles=options.populations * niterations,
             numprocs=_numprocs,
@@ -580,6 +580,9 @@ function equation_search(
             runtests=runtests,
             verbosity=_verbosity,
             progress=_progress,
+            parallelism=Val(concurrency),
+            dim_out=Val(dim_out),
+            return_state=Val(_return_state),
         ),
         options,
         saved_state,

src/Utils.jl

@@ -6,7 +6,7 @@ using MacroTools: splitdef, combinedef
 
 const pseudo_time = Ref(0)
 
-function get_birth_order(; deterministic=false)::Int
+function get_birth_order(; deterministic::Bool=false)::Int
     """deterministic gives a birth time with perfect resolution, but is not thread safe."""
     if deterministic
         global pseudo_time

src/deprecates.jl

@@ -5,11 +5,11 @@ import .MutationFunctionsModule: gen_random_tree, gen_random_tree_fixed_size
 
 @deprecate(
     gen_random_tree(length::Int, options::Options, nfeatures::Int, t::Type),
-    gen_random_tree(length, options, nfeatures, t, Node)
+    gen_random_tree(length, options, nfeatures, t)
 )
 @deprecate(
     gen_random_tree_fixed_size(node_count::Int, options::Options, nfeatures::Int, t::Type),
-    gen_random_tree_fixed_size(node_count, options, nfeatures, t, Node)
+    gen_random_tree_fixed_size(node_count, options, nfeatures, t)
 )
 
 @deprecate(

src/precompile.jl

@@ -85,7 +85,7 @@ function do_precompilation(::Val{mode}) where {mode}
                     return_state=false,
                     verbosity=0,
                 )
-                nout == 1 && calculate_pareto_frontier(hof)
+                nout == 1 && calculate_pareto_frontier(hof::HallOfFame)
             end
         end
     end

test/Project.toml

@@ -6,6 +6,7 @@ Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 DynamicExpressions = "a40a106e-89c9-4ca8-8020-a735e8728b6b"
 DynamicQuantities = "06fc5a27-2a28-4c7c-a15d-362465fb6821"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
 LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"