Merge pull request #21 from DoubleML/s-update-plm-scripts

update plm scripts

Author: SvenKlaassen

.github/workflows/pliv_sim.yml

@@ -17,7 +17,7 @@ jobs:
     strategy:
       matrix:
         script: [
-          'scripts/plm/pliv_late_coverage.py',
+          'scripts/plm/pliv_late.py',
         ]
 
     steps:
@@ -47,28 +47,37 @@ jobs:
       with:
         ref: ${{ env.TARGET_BRANCH }}
 
+    - name: Install uv
+      uses: astral-sh/setup-uv@v5
+      with:
+        version: "0.7.8"
+
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: '3.12'
+        python-version-file: "monte-cover/pyproject.toml"
 
-    - name: Install dependencies
+    - name: Install Monte-Cover
       run: |
-        python -m pip install --upgrade pip
-        pip install -r requirements.txt
-
+        cd monte-cover
+        uv venv
+        uv sync
+  
     - name: Install DoubleML from correct branch
       run: |
-        pip uninstall -y doubleml
-        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
+        source monte-cover/.venv/bin/activate
+        uv pip uninstall doubleml
+        uv pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
         git config --global user.name 'github-actions'
         git config --global user.email '[email protected]'
 
     - name: Run scripts
-      run: python ${{ matrix.script }}
+      run: |
+        source monte-cover/.venv/bin/activate
+        uv run ${{ matrix.script }}
 
     - name: Commit any existing changes
       run: |

.github/workflows/plr_sim.yml

@@ -17,10 +17,10 @@ jobs:
     strategy:
       matrix:
         script: [
-          'scripts/plm/plr_ate_coverage.py',
+          'scripts/plm/plr_ate.py',
           'scripts/plm/plr_ate_sensitivity.py',
-          'scripts/plm/plr_cate_coverage.py',
-          'scripts/plm/plr_gate_coverage.py',
+          'scripts/plm/plr_cate.py',
+          'scripts/plm/plr_gate.py',
         ]
 
     steps:
@@ -53,7 +53,7 @@ jobs:
     - name: Install uv
       uses: astral-sh/setup-uv@v5
       with:
-        version: "0.6.11"
+        version: "0.7.8"
 
     - name: Set up Python
       uses: actions/setup-python@v5

doc/plm/pliv.qmd

@@ -60,7 +60,7 @@ display_columns_pliv = ["Learner g", "Learner m", "Learner r", "Bias", "CI Lengt
 
 generate_and_show_styled_table(
     main_df=df_coverage_pliv,
-    filters={"level": 0.95, "score": "partialling out"},
+    filters={"level": 0.95, "Score": "partialling out"},
     display_cols=display_columns_pliv,
     n_rep=n_rep_pliv,
     level_col="level",
@@ -74,7 +74,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_coverage_pliv,
-    filters={"level": 0.90, "score": "partialling out"},
+    filters={"level": 0.90, "Score": "partialling out"},
     display_cols=display_columns_pliv,
     n_rep=n_rep_pliv,
     level_col="level",
@@ -92,7 +92,7 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 generate_and_show_styled_table(
     main_df=df_coverage_pliv,
-    filters={"level": 0.95, "score": "IV-type"},
+    filters={"level": 0.95, "Score": "IV-type"},
     display_cols=display_columns_pliv,
     n_rep=n_rep_pliv,
     level_col="level",
@@ -105,7 +105,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_coverage_pliv,
-    filters={"level": 0.9, "score": "IV-type"},
+    filters={"level": 0.9, "Score": "IV-type"},
     display_cols=display_columns_pliv,
     n_rep=n_rep_pliv,
     level_col="level",

doc/plm/plr.qmd

@@ -60,7 +60,7 @@ display_columns_coverage = ["Learner g", "Learner m", "Bias", "CI Length", "Cove
 
 generate_and_show_styled_table(
     main_df=df_coverage,
-    filters={"level": 0.95, "score": "partialling out"},
+    filters={"level": 0.95, "Score": "partialling out"},
     display_cols=display_columns_coverage,
     n_rep=n_rep_coverage,
     level_col="level",
@@ -74,7 +74,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_coverage,
-    filters={"level": 0.9, "score": "partialling out"},
+    filters={"level": 0.9, "Score": "partialling out"},
     display_cols=display_columns_coverage,
     n_rep=n_rep_coverage,
     level_col="level",
@@ -92,7 +92,7 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 generate_and_show_styled_table(
     main_df=df_coverage,
-    filters={"level": 0.95, "score": "IV-type"},
+    filters={"level": 0.95, "Score": "IV-type"},
     display_cols=display_columns_coverage,
     n_rep=n_rep_coverage,
     level_col="level",
@@ -105,7 +105,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_coverage,
-    filters={"level": 0.9, "score": "IV-type"},
+    filters={"level": 0.9, "Score": "IV-type"},
     display_cols=display_columns_coverage,
     n_rep=n_rep_coverage,
     level_col="level",
@@ -135,7 +135,7 @@ print(metadata_df_sens.T.to_string(header=False))
 #| echo: false
 
 # set up data and rename columns
-df_sensitivity = pd.read_csv("../../results/plm/plr_ate_sensitivity.csv", index_col=None)
+df_sensitivity = pd.read_csv("../../results/plm/plr_ate_sensitivity_coverage.csv", index_col=None)
 
 if "repetition" in df_sensitivity.columns and df_sensitivity["repetition"].nunique() == 1:
     n_rep_sensitivity = df_sensitivity["repetition"].unique()[0]
@@ -156,7 +156,7 @@ display_columns_sensitivity = [
 
 generate_and_show_styled_table(
     main_df=df_sensitivity,
-    filters={"level": 0.95, "score": "partialling out"},
+    filters={"level": 0.95, "Score": "partialling out"},
     display_cols=display_columns_sensitivity,
     n_rep=n_rep_sensitivity,
     level_col="level",
@@ -167,10 +167,10 @@ generate_and_show_styled_table(
 
 ```{python}
 #| echo: false
-#| 
+#|
 generate_and_show_styled_table(
     main_df=df_sensitivity,
-    filters={"level": 0.9, "score": "partialling out"},
+    filters={"level": 0.9, "Score": "partialling out"},
     display_cols=display_columns_sensitivity,
     n_rep=n_rep_sensitivity,
     level_col="level",
@@ -188,7 +188,7 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 generate_and_show_styled_table(
     main_df=df_sensitivity,
-    filters={"level": 0.95, "score": "IV-type"},
+    filters={"level": 0.95, "Score": "IV-type"},
     display_cols=display_columns_sensitivity,
     n_rep=n_rep_sensitivity,
     level_col="level",
@@ -201,7 +201,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_sensitivity,
-    filters={"level": 0.9, "score": "IV-type"},
+    filters={"level": 0.9, "Score": "IV-type"},
     display_cols=display_columns_sensitivity,
     n_rep=n_rep_sensitivity,
     level_col="level",

doc/plm/plr_cate.qmd

@@ -57,12 +57,28 @@ else:
 display_columns_cate = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
 ```
 
+### Partialling out
+
+```{python}
+#| echo: false
+
+generate_and_show_styled_table(
+    main_df=df_cate,
+    filters={"level": 0.95, "Score": "partialling out"},
+    display_cols=display_columns_cate,
+    n_rep=n_rep_cate,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
+```
+
 ```{python}
 #| echo: false
 
 generate_and_show_styled_table(
     main_df=df_cate,
-    filters={"level": 0.95},
+    filters={"level": 0.9, "Score": "partialling out"},
     display_cols=display_columns_cate,
     n_rep=n_rep_cate,
     level_col="level",
@@ -71,16 +87,33 @@ generate_and_show_styled_table(
 )
 ```
 
+
+### IV-type
+
 ```{python}
 #| echo: false
 
 generate_and_show_styled_table(
     main_df=df_cate,
-    filters={"level": 0.9},
+    filters={"level": 0.95, "Score": "IV-type"},
     display_cols=display_columns_cate,
     n_rep=n_rep_cate,
     level_col="level",
     rename_map={"Learner g": "Learner l"},
     coverage_highlight_cols=["Coverage", "Uniform Coverage"]
 )
 ```
+
+```{python}
+#| echo: false
+
+generate_and_show_styled_table(
+    main_df=df_cate,
+    filters={"level": 0.9, "Score": "IV-type"},
+    display_cols=display_columns_cate,
+    n_rep=n_rep_cate,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
+```

doc/plm/plr_gate.qmd

@@ -56,12 +56,44 @@ else:
 display_columns_gate = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
 ```
 
+### Partialling out
+
+```{python}
+#| echo: false
+
+generate_and_show_styled_table(
+    main_df=df_gate,
+    filters={"level": 0.95, "Score": "partialling out"},
+    display_cols=display_columns_gate,
+    n_rep=n_rep_gate,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
+```
+
+```{python}
+#| echo: false
+
+generate_and_show_styled_table(
+    main_df=df_gate,
+    filters={"level": 0.9, "Score": "partialling out"},
+    display_cols=display_columns_gate,
+    n_rep=n_rep_gate,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
+```
+
+### IV-type
+
 ```{python}
 #| echo: false
 
 generate_and_show_styled_table(
     main_df=df_gate,
-    filters={"level": 0.95},
+    filters={"level": 0.95, "Score": "IV-type"},
     display_cols=display_columns_gate,
     n_rep=n_rep_gate,
     level_col="level",
@@ -75,7 +107,7 @@ generate_and_show_styled_table(
 
 generate_and_show_styled_table(
     main_df=df_gate,
-    filters={"level": 0.9},
+    filters={"level": 0.9, "Score": "IV-type"},
     display_cols=display_columns_gate,
     n_rep=n_rep_gate,
     level_col="level",

monte-cover/pyproject.toml

@@ -9,7 +9,7 @@ authors = [
 requires-python = ">=3.12"
 dependencies = [
     "black>=25.1.0",
-    "doubleml[rdd]>=0.9.3",
+    "doubleml[rdd]>=0.10.0",
     "ipykernel>=6.29.5",
     "itables>=2.2.5",
     "joblib>=1.4.2",
@@ -19,6 +19,7 @@ dependencies = [
     "pyyaml>=6.0.2",
     "ruff>=0.11.0",
     "scikit-learn>=1.5.2",
+    "pre-commit>=4.2.0",
 ]
 
 [project.scripts]