tests working locally

Project.toml

@@ -6,7 +6,6 @@ version = "0.11.4"
 [deps]
 AbstractDifferentiation = "c29ec348-61ec-40c8-8164-b8c60e9d9f3d"
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
-Configurations = "5218b696-f38b-4ac9-8b61-a12ec717816d"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a"
 HypothesisTests = "09f84164-cd44-5f33-b23f-e6b0d136a0d5"
@@ -27,7 +26,6 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 [compat]
 AbstractDifferentiation = "0.4, 0.5"
 CategoricalArrays = "0.10"
-Configurations = "0.17"
 Distributions = "0.25"
 GLM = "1.8.2"
 HypothesisTests = "0.10"
@@ -36,10 +34,10 @@ MLJBase = "0.19, 0.20, 0.21"
 MLJGLMInterface = "0.3.4"
 MLJModels = "0.15, 0.16"
 Missings = "1.0"
+PrecompileTools = "1.1.1"
 PrettyTables = "2.2"
 TableOperations = "1.2"
 Tables = "1.6"
 YAML = "0.4"
 Zygote = "0.6"
-PrecompileTools = "1.1.1"
 julia = "1.6, 1.7, 1"

src/TMLE.jl

@@ -14,7 +14,6 @@ using Distributions
 using Zygote
 using LogExpFunctions
 using YAML
-using Configurations
 using PrecompileTools
 using PrettyTables
 using Random
@@ -44,7 +43,6 @@ include("estimands.jl")
 include("utils.jl")
 include("estimation.jl")
 include("estimate.jl")
-include("configuration.jl")
 
 # #############################################################################
 # PRECOMPILATION WORKLOAD

src/estimands.jl

@@ -63,14 +63,17 @@ CM₂ = CM(
 )
 ```
 """
-@option struct ConditionalMean <: Estimand
+struct ConditionalMean <: Estimand
     scm::StructuralCausalModel
     outcome::Symbol
     treatment::NamedTuple
 end
 
 const CM = ConditionalMean
 
+CM(;scm, outcome, treatment) = CM(scm, outcome, treatment)
+CM(scm; outcome, treatment) = CM(scm, outcome, treatment)
+
 name(::Type{CM}) = "CM"
 
 #####################################################################
@@ -110,14 +113,17 @@ ATE₂ = ATE(
 )
 ```
 """
-@option struct AverageTreatmentEffect <: Estimand
+struct AverageTreatmentEffect <: Estimand
     scm::StructuralCausalModel
     outcome::Symbol
     treatment::NamedTuple
 end
 
 const ATE = AverageTreatmentEffect
 
+ATE(;scm, outcome, treatment) = ATE(scm, outcome, treatment)
+ATE(scm; outcome, treatment) = ATE(scm, outcome, treatment)
+
 name(::Type{ATE}) = "ATE"
 
 #####################################################################
@@ -150,14 +156,17 @@ IATE₁ = IATE(
 )
 ```
 """
-@option struct InteractionAverageTreatmentEffect <: Estimand
+struct InteractionAverageTreatmentEffect <: Estimand
     scm::StructuralCausalModel
     outcome::Symbol
     treatment::NamedTuple
 end
 
 const IATE = InteractionAverageTreatmentEffect
 
+IATE(;scm, outcome, treatment) = IATE(scm, outcome, treatment)
+IATE(scm; outcome, treatment) = IATE(scm, outcome, treatment)
+
 name(::Type{IATE}) = "IATE"
 
 #####################################################################
@@ -166,7 +175,7 @@ name(::Type{IATE}) = "IATE"
 
 CMCompositeEstimand = Union{CM, ATE, IATE}
 
-function Base.show(io::IO, Ψ::T) where T <: CMCompositeEstimand 
+function Base.show(io::IO, ::MIME"text/plain", Ψ::T) where T <: CMCompositeEstimand 
     param_string = string(
         name(T),
         "\n-----",

src/scm.jl

@@ -21,12 +21,14 @@ SelfReferringEquationError(outcome) =
 
 NoModelError(eq::SE) = ArgumentError(string("It seems the following structural equation needs to be fitted.\n",
     " Please provide a suitable model for it :\n\t⋆ ", eq))
-
+
+fit_message(eq::SE) = string("Fitting Structural Equation corresponding to variable ", outcome(eq), ".")
+
 function MLJBase.fit!(eq::SE, dataset; verbosity=1, cache=true, force=false)
     eq.model !== nothing || throw(NoModelError(eq))
     # Fit if never fitted or if new model
     if eq.mach === nothing || eq.model != eq.mach.model
-        verbosity >= 1 && @info(string("Fitting Structural Equation corresponding to variable ", outcome(eq), "."))
+        verbosity >= 1 && @info(fit_message(eq))
         data = nomissing(dataset, vcat(parents(eq), outcome(eq)))
         X = selectcols(data, parents(eq))
         y = Tables.getcolumn(data, outcome(eq))
@@ -35,6 +37,7 @@ function MLJBase.fit!(eq::SE, dataset; verbosity=1, cache=true, force=false)
         eq.mach = mach
     # Otherwise only fit if force is true
     else
+        verbosity >= 1 && force === true && @info(fit_message(eq))
         MLJBase.fit!(eq.mach, verbosity=verbosity-1, force=force)
     end
 end
@@ -49,7 +52,7 @@ function string_repr(eq::SE; subscript="")
     return eq_string
 end
 
-Base.show(io::IO, eq::SE) = println(io, string_repr(eq))
+Base.show(io::IO, ::MIME"text/plain", eq::SE) = println(io, string_repr(eq))
 
 assign_model!(eq::SE, model::Nothing) = nothing
 assign_model!(eq::SE, model::Model) = eq.model = model
@@ -69,8 +72,10 @@ end
 
 const SCM = StructuralCausalModel
 
-StructuralCausalModel(equations::Vararg{SE}) = 
-    StructuralCausalModel(Dict(outcome(eq) => eq for eq in equations))
+SCM() = SCM(Dict{Symbol, SE}())
+
+SCM(equations::Vararg{SE}) = 
+    SCM(Dict(outcome(eq) => eq for eq in equations))
 
 
 equations(scm::SCM) = scm.equations
@@ -88,7 +93,7 @@ function string_repr(scm::SCM)
     return scm_string
 end
 
-Base.show(io::IO, scm::SCM) = println(io, string_repr(scm))
+Base.show(io::IO, ::MIME"text/plain", scm::SCM) = println(io, string_repr(scm))
 
 
 function Base.push!(scm::SCM, eq::SE)

test/double_robustness_ate.jl

@@ -235,7 +235,7 @@ end
         outcome      = :Y,
         treatment   = (T₁=(case=1., control=0.), T₂=(case=1., control=0.)),
     )
-    tmle_result, fluctuation_mach = tmle(Ψ, dataset, verbosity=1)
+    tmle_result, fluctuation_mach = tmle(Ψ, dataset, verbosity=0)
     test_coverage(tmle_result, ATE₁₁₋₀₀)
     test_fluct_decreases_risk(Ψ, fluctuation_mach)
     test_mean_inf_curve_almost_zero(tmle_result; atol=1e-10)

test/runtests.jl

@@ -1,6 +1,7 @@
 using Test
 
 @time begin
+    @test include("scm.jl")
     @test include("non_regression_test.jl")
     @test include("utils.jl")
     @test include("double_robustness_ate.jl")
@@ -11,5 +12,4 @@ using Test
     @test include("missing_management.jl")
     @test include("composition.jl")
     @test include("treatment_transformer.jl")
-    @test include("configuration.jl")
 end

test/scm.jl

@@ -113,19 +113,10 @@ end
         @test isdefined(eq.mach, :data)
     end
     # Refit will not do anything
-    nofit_log_sequence = (
-        (:info, "Structural Equation corresponding to variable Ycont already fitted, skipping. Set `force=true` to force refit."),
-        (:info, "Structural Equation corresponding to variable Ycat already fitted, skipping. Set `force=true` to force refit."),
-        (:info, "Structural Equation corresponding to variable T₁ already fitted, skipping. Set `force=true` to force refit."),
-        (:info, "Structural Equation corresponding to variable T₂ already fitted, skipping. Set `force=true` to force refit."),
-    )
+    nofit_log_sequence = ()
     @test_logs nofit_log_sequence... fit!(scm, dataset, verbosity = 1)
-    # Force refit and set cache to false
-    @test_logs fit_log_sequence... fit!(scm, dataset, verbosity = 1, force=true, cache=false)
-    for (key, eq) in equations(scm)
-        @test eq.mach isa Machine
-        @test !isdefined(eq.mach, :data)
-    end
+    # Force refit
+    @test_logs fit_log_sequence... fit!(scm, dataset, verbosity = 1, force=true)
 
     # Reset scm
     reset!(scm)