finally more or less sorted

experiments/Project.toml

+[deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+CounterfactualExplanations = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+ECCCo = "0232c203-4013-4b0d-ad96-43e3e11ac3bf"
+JointEnergyModels = "48c56d24-211d-4463-bbc0-7a701b291131"
+LazyArtifacts = "4af54fe1-eca0-43a8-85a7-787d91b784e3"
+MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
+MLJEnsembles = "50ed68f4-41fd-4504-931a-ed422449fee0"
+MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"

experiments/circles.jl

-n_obs = Int(1000 / (1.0 - test_size))
-counterfactual_data, test_data = train_test_split(load_circles(n_obs; noise=0.05, factor=0.5); test_size=test_size)
+n_obs = Int(1000 / (1.0 - TEST_SIZE))
+counterfactual_data, test_data = train_test_split(load_circles(n_obs; noise=0.05, factor=0.5); TEST_SIZE=TEST_SIZE)
 run_experiment!(
     counterfactual_data, test_data; dataname="Circles",
     n_hidden=32,

experiments/setup.jl → experiments/experiment.jl

-# General setup:
-include("$(pwd())/notebooks/setup.jl")
-eval(setup_notebooks)
-
-test_size = 0.2
-
-# Constants:
-const DEFAULT_OUTPUT_PATH = "$(pwd())/results"
-const RETRAIN = "retrain" ∈ ARGS ? true : false
-
-"Default model performance measures."
-const MODEL_MEASURES = Dict(
-    :f1score => multiclass_f1score,
-    :acc => accuracy,
-    :precision => multiclass_precision
-)
-
-"Default coverage rate."
-const DEFAULT_COVERAGE = 0.95
-
-"The default benchmarking measures."
-const CE_MEASURES = [
-    CounterfactualExplanations.distance,
-    ECCCo.distance_from_energy,
-    ECCCo.distance_from_targets,
-    CounterfactualExplanations.Evaluation.validity,
-    CounterfactualExplanations.Evaluation.redundancy,
-    ECCCo.set_size_penalty
-]
-
-# Pre-trained models:
-function pretrained_path()
-    @info "Models were pre-trained on `julia-1.8.5` and may not work on other versions."
-    return joinpath(artifact"results-paper-submission-1.8.5", "results-paper-submission-1.8.5")
-end
-
 "Sets up the experiment."
 Base.@kwdef struct Experiment
     counterfactual_data::CounterfactualData

experiments/gmsc.jl

-counterfactual_data, test_data = train_test_split(load_gmsc(nothing); test_size=test_size)
+counterfactual_data, test_data = train_test_split(load_gmsc(nothing); TEST_SIZE=TEST_SIZE)
 run_experiment!(
     counterfactual_data, test_data; dataname="GMSC",
     n_hidden=128,

experiments/linearly_separable.jl

-n_obs = Int(1000 / (1.0 - test_size))
+n_obs = Int(1000 / (1.0 - TEST_SIZE))
 counterfactual_data, test_data = train_test_split(
     load_blobs(n_obs; cluster_std=0.1, center_box=(-1.0 => 1.0));
-    test_size=test_size
+    TEST_SIZE=TEST_SIZE
 )
 run_experiment!(counterfactual_data, test_data; dataname="Linearly Separable")
\ No newline at end of file

experiments/moons.jl

-n_obs = Int(2500 / (1.0 - test_size))
-counterfactual_data, test_data = train_test_split(load_moons(n_obs); test_size=test_size)
+n_obs = Int(2500 / (1.0 - TEST_SIZE))
+counterfactual_data, test_data = train_test_split(load_moons(n_obs); TEST_SIZE=TEST_SIZE)
 run_experiment!(
     counterfactual_data, test_data; dataname="Moons",
     epochs=500,

experiments/run_experiments.jl

-include("setup.jl")
+include("setup_env.jl")
+include("experiment.jl")
 
 # User inputs:
 if "run-all" in ARGS

experiments/setup_env.jl

+using Pkg
+Pkg.activate(@__DIR__)
+
+# Deps:
+using CounterfactualExplanations
+using CounterfactualExplanations.Data
+using CounterfactualExplanations.DataPreprocessing: train_test_split
+using CounterfactualExplanations.Evaluation: benchmark, evaluate, Benchmark
+using CounterfactualExplanations.Generators: JSMADescent
+using CounterfactualExplanations.Models: load_mnist_mlp, load_fashion_mnist_mlp, train, probs
+using CounterfactualExplanations.Objectives
+using CSV
+using Distributions
+using ECCCo
+using JointEnergyModels
+using LazyArtifacts
+using MLJBase: multiclass_f1score, accuracy, multiclass_precision
+using MLJEnsembles
+using MLJFlux
+
+# Constants:
+const LATEST_VERSION = "1.8.5"
+const ARTIFACT_NAME = "results-paper-submission-$(LATEST_VERSION)"
+artifact_toml = LazyArtifacts.find_artifacts_toml(".")
+_hash = artifact_hash(ARTIFACT_NAME, artifact_toml)
+const LATEST_ARTIFACT_PATH = artifact_path(_hash)
+
+# Pre-trained models:
+function pretrained_path()
+    @info "Models were pre-trained on `julia-$(LATEST_VERSION)` and may not work on other versions."
+    return LATEST_ARTIFACT_PATH
+end
+
+"Default output path."
+const DEFAULT_OUTPUT_PATH = "$(pwd())/results"
+
+"Boolean flag to retrain models."
+const RETRAIN = "retrain" ∈ ARGS ? true : false
+
+"Default model performance measures."
+const MODEL_MEASURES = Dict(
+    :f1score => multiclass_f1score,
+    :acc => accuracy,
+    :precision => multiclass_precision
+)
+
+"Default coverage rate."
+const DEFAULT_COVERAGE = 0.95
+
+"The default benchmarking measures."
+const CE_MEASURES = [
+    CounterfactualExplanations.distance,
+    ECCCo.distance_from_energy,
+    ECCCo.distance_from_targets,
+    CounterfactualExplanations.Evaluation.validity,
+    CounterfactualExplanations.Evaluation.redundancy,
+    ECCCo.set_size_penalty
+]
+
+"Test set proportion."
+const TEST_SIZE = 0.2
\ No newline at end of file