Merge pull request #76 from JuliaTrustworthyAI/74-updates-for-thesis

removed redundant deps

Author: pat-alt

.github/workflows/CI.yml

@@ -18,10 +18,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.7'
-          - '1.8'
-          - '~1.9.0-0'
-          - 'nightly'
+          - '1.9'
         os:
           - ubuntu-latest
         arch:
@@ -48,7 +45,7 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@v1
         with:
-          version: '1'
+          version: '1.9'
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-docdeploy@v1
         env:

Project.toml

@@ -1,44 +1,38 @@
 name = "AlgorithmicRecourseDynamics"
 uuid = "3d1ede72-abb8-4340-bf8e-2ae06849b5ec"
 authors = ["Patrick Altmeyer"]
-version = "0.1.3"
+version = "0.1.4"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 CounterfactualExplanations = "2f13d31b-18db-44c1-bc43-ebaf2cff0be0"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
-Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
 KernelFunctions = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
 LazyArtifacts = "4af54fe1-eca0-43a8-85a7-787d91b784e3"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
-RCall = "6f49c342-dc21-5d91-9882-a32aef131414"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
 CSV = "0.10"
-CounterfactualExplanations = "0.1"
+CounterfactualExplanations = "=0.1.6"
 DataFrames = "1"
 Distances = "0.10"
-Flux = "0.13"
-Images = "0.25"
+Flux = "0.13 - 0.14"
 KernelFunctions = "0.10"
 MLJBase = "0.21.3"
-MLUtils = "0.3.1, 0.4"
+MLUtils = "0.3.1 - 0.4"
 Parameters = "0.12"
-Plots = "1.37.2"
 ProgressMeter = "1"
-RCall = "0.13.14"
 StatsBase = "0.33"
 julia = "1.7, 1.8, 1.9"
 

README.qmd

@@ -12,17 +12,17 @@ crossref:
   fig-prefix: Figure
   tbl-prefix: Table
 bibliography: bib.bib
-jupyter: julia-1.8
+engine: julia
+julia:
+  exeflags: ["+1.9"]
 ---
 
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://juliatrustworthyai.github.io/AlgorithmicRecourseDynamics.jl/stable) 
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://juliatrustworthyai.github.io/AlgorithmicRecourseDynamics.jl/dev) 
 [![Build Status](https://github.com/juliatrustworthyai/AlgorithmicRecourseDynamics.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/juliatrustworthyai/AlgorithmicRecourseDynamics.jl/actions/workflows/CI.yml?query=branch%3Amain) 
 [![Coverage](https://codecov.io/gh/juliatrustworthyai/AlgorithmicRecourseDynamics.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/juliatrustworthyai/AlgorithmicRecourseDynamics.jl) 
 [![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle) 
-[![ColPrac: Contributor’s Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet.png)](https://github.com/SciML/ColPrac) 
-[![Twitter Badge](https://img.shields.io/twitter/url/https/twitter.com/paltmey.svg?style=social&label=Follow%20%40paltmey)](https://twitter.com/paltmey)
 
 # AlgorithmicRecourseDynamics
 
-{{< include docs/src/_intro.qmd >}}
+{{< include docs/src/_intro.qmd >}}

_quarto.yml

@@ -14,7 +14,6 @@ execute:
   echo: true
   output: false
 
-jupyter: julia-1.8
-
-
-
+engines: ['julia']
+julia:
+  exeflags: ["+1.9"]

src/experiments/functions.jl

@@ -172,14 +172,15 @@ function update_experiment!(experiment::Experiment, recourse_system::RecourseSys
         indices_ = rand(1:experiment.num_counterfactuals, length(results)) # randomly draw from generated counterfactuals
         X′ = reduce(hcat, @.(selectdim(counterfactual(results), 3, indices_)))
         y′ = reduce(hcat, @.(selectdim(counterfactual_label(results), 3, indices_)))
+        y′ = [y[1] for y in y′]
 
-    # If for any counterfactuals the returned label is NaN, this is considered as invalid and the current label is not updated:
-    valid_ces = vec(.!(isnan.(y′)))
-    chosen_individuals = chosen_individuals[valid_ces]
+        # If for any counterfactuals the returned label is NaN, this is considered as invalid and the current label is not updated:
+        valid_ces = vec(.!(isnan.(y′)))
+        chosen_individuals = chosen_individuals[valid_ces]
 
-    # Update data:
-    X[:, chosen_individuals] = X′[:, valid_ces]
-    y[:, chosen_individuals] = y′[:, valid_ces]
+        # Update data:
+        X[:, chosen_individuals] = X′[:, valid_ces]
+        y[:, chosen_individuals] = y′[:, valid_ces]
 
         # Generative model:
         gen_mod = deepcopy(counterfactual_data.generative_model)

test/Project.toml

@@ -6,3 +6,8 @@ MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[compat]
+CounterfactualExplanations = "=0.1.6"
+Flux = "0.13 - 0.14"
+

test/runtests.jl

@@ -26,6 +26,6 @@ using Test
     generators = Dict(:wachter => generator)
     experiment = set_up_experiment(data_train, data_test, models, generators)
 
-    run!(experiment)
+    run!(experiment, n_folds=1, n_rounds=5)
 
 end