update qmd and workflow for quantiles

Author: SvenKlaassen

.github/workflows/quant_sim.yml

@@ -17,9 +17,9 @@ jobs:
     strategy:
       matrix:
         script: [
-          'scripts/irm/cvar_coverage.py',
-          'scripts/irm/pq_coverage.py',
-          'scripts/irm/lpq_coverage.py',
+          'scripts/irm/cvar.py',
+          'scripts/irm/pq.py',
+          'scripts/irm/lpq.py',
         ]
 
     steps:
@@ -49,28 +49,37 @@ 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: |

doc/irm/qte.qmd

@@ -31,7 +31,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/pq_coverage_metadata.csv'
+metadata_file = '../../results/irm/pq_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -42,7 +42,7 @@ print(metadata_df.T.to_string(header=False))
 #| echo: false
 
 # set up data
-df_qte = pd.read_csv("../../results/irm/pq_coverage_qte.csv", index_col=None)
+df_qte = pd.read_csv("../../results/irm/pq_effect_coverage.csv", index_col=None)
 
 assert df_qte["repetition"].nunique() == 1
 n_rep_qte = df_qte["repetition"].unique()[0]
@@ -85,7 +85,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data
-df_pq0 = pd.read_csv("../../results/irm/pq_coverage_pq0.csv", index_col=None)
+df_pq0 = pd.read_csv("../../results/irm/pq_Y0_coverage.csv", index_col=None)
 
 assert df_pq0["repetition"].nunique() == 1
 n_rep_pq0 = df_pq0["repetition"].unique()[0]
@@ -125,7 +125,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data and rename columns
-df_pq1 = pd.read_csv("../../results/irm/pq_coverage_pq1.csv", index_col=None)
+df_pq1 = pd.read_csv("../../results/irm/pq_Y1_coverage.csv", index_col=None)
 
 assert df_pq1["repetition"].nunique() == 1
 n_rep_pq1 = df_pq1["repetition"].unique()[0]
@@ -161,15 +161,15 @@ generate_and_show_styled_table(
 
 ## LQTE
 
-The results are based on a location-scale model as described the corresponding [Example](https://docs.doubleml.org/stable/examples/py_double_ml_pq.html#Local-Potential-Quantiles-(LPQs)) with $10,000$ observations.
+The results are based on a location-scale model as described the corresponding [Example](https://docs.doubleml.org/stable/examples/py_double_ml_pq.html#Local-Potential-Quantiles-(LPQs)) with $5,000$ observations.
 
 The non-uniform results (coverage, ci length and bias) refer to averaged values over all quantiles (point-wise confidende intervals).
 
 ::: {.callout-note title="Metadata"  collapse="true"}
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/lpq_coverage_metadata.csv'
+metadata_file = '../../results/irm/lpq_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -180,7 +180,7 @@ print(metadata_df.T.to_string(header=False))
 #| echo: false
 
 # set up data
-df_lqte = pd.read_csv("../../results/irm/lpq_coverage_lqte.csv", index_col=None)
+df_lqte = pd.read_csv("../../results/irm/lpq_effect_coverage.csv", index_col=None)
 
 assert df_lqte["repetition"].nunique() == 1
 n_rep_lqte = df_lqte["repetition"].unique()[0]
@@ -222,7 +222,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data
-df_lpq0 = pd.read_csv("../../results/irm/lpq_coverage_lpq0.csv", index_col=None)
+df_lpq0 = pd.read_csv("../../results/irm/lpq_Y0_coverage.csv", index_col=None)
 
 assert df_lpq0["repetition"].nunique() == 1
 n_rep_lpq0 = df_lpq0["repetition"].unique()[0]
@@ -262,7 +262,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data
-df_lpq1 = pd.read_csv("../../results/irm/lpq_coverage_lpq1.csv", index_col=None)
+df_lpq1 = pd.read_csv("../../results/irm/lpq_Y1_coverage.csv", index_col=None)
 
 assert df_lpq1["repetition"].nunique() == 1
 n_rep_lpq1 = df_lpq1["repetition"].unique()[0]
@@ -306,7 +306,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/cvar_coverage_metadata.csv'
+metadata_file = '../../results/irm/cvar_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -317,7 +317,7 @@ print(metadata_df.T.to_string(header=False))
 #| echo: false
 
 # set up data
-df_cvar_qte = pd.read_csv("../../results/irm/cvar_coverage_qte.csv", index_col=None)
+df_cvar_qte = pd.read_csv("../../results/irm/cvar_effect_coverage.csv", index_col=None)
 
 assert df_cvar_qte["repetition"].nunique() == 1
 n_rep_cvar_qte = df_cvar_qte["repetition"].unique()[0]
@@ -359,7 +359,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data
-df_cvar_pq0 = pd.read_csv("../../results/irm/cvar_coverage_pq0.csv", index_col=None)
+df_cvar_pq0 = pd.read_csv("../../results/irm/cvar_Y0_coverage.csv", index_col=None)
 
 assert df_cvar_pq0["repetition"].nunique() == 1
 n_rep_cvar_pq0 = df_cvar_pq0["repetition"].unique()[0]
@@ -399,7 +399,7 @@ generate_and_show_styled_table(
 #| echo: false
 
 # set up data
-df_cvar_pq1 = pd.read_csv("../../results/irm/cvar_coverage_pq1.csv", index_col=None)
+df_cvar_pq1 = pd.read_csv("../../results/irm/cvar_Y1_coverage.csv", index_col=None)
 
 assert df_cvar_pq1["repetition"].nunique() == 1
 n_rep_cvar_pq1 = df_cvar_pq1["repetition"].unique()[0]