Merge pull request #24 from DoubleML/s-remove-old-scripts

Clean repository

Author: SvenKlaassen

.github/workflows/iivm_sim.yml

@@ -17,7 +17,7 @@ jobs:
     strategy:
       matrix:
         script: [
-          'scripts/irm/iivm_late_coverage.py',
+          'scripts/irm/iivm_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/ssm_sim.yml

@@ -48,28 +48,37 @@ 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/iivm.qmd

@@ -30,7 +30,7 @@ The simulations are based on the  the [make_iivm_data](https://docs.doubleml.org
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/iivm_late_coverage_metadata.csv'
+metadata_file = '../../results/irm/iivm_late_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -46,7 +46,7 @@ df = pd.read_csv("../../results/irm/iivm_late_coverage.csv", index_col=None)
 assert df["repetition"].nunique() == 1
 n_rep = df["repetition"].unique()[0]
 
-display_columns = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage"]
+display_columns = ["Learner g", "Learner m", "Learner r", "Bias", "CI Length", "Coverage"]
 ```
 
 

doc/irm/irm.qmd

@@ -30,7 +30,7 @@ The simulations are based on the  the [make_irm_data](https://docs.doubleml.org/
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/irm_ate_coverage_metadata.csv'
+metadata_file = '../../results/irm/irm_ate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```

doc/irm/irm_cate.qmd

@@ -32,7 +32,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/irm_cate_coverage_metadata.csv'
+metadata_file = '../../results/irm/irm_cate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```

doc/irm/irm_gate.qmd

@@ -32,7 +32,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/irm/irm_gate_coverage_metadata.csv'
+metadata_file = '../../results/irm/irm_gate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```

doc/plm/pliv.qmd

@@ -30,7 +30,7 @@ The simulations are based on the  the [make_pliv_CHS2015](https://docs.doubleml.
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/plm/pliv_late_coverage_metadata.csv'
+metadata_file = '../../results/plm/pliv_late_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```

doc/plm/plr.qmd

@@ -30,7 +30,7 @@ The simulations are based on the  the [make_plr_CCDDHNR2018](https://docs.double
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/plm/plr_ate_coverage_metadata.csv'
+metadata_file = '../../results/plm/plr_ate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```

doc/plm/plr_cate.qmd

@@ -32,7 +32,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/plm/plr_cate_coverage_metadata.csv'
+metadata_file = '../../results/plm/plr_cate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -116,4 +116,4 @@ generate_and_show_styled_table(
     rename_map={"Learner g": "Learner l"},
     coverage_highlight_cols=["Coverage", "Uniform Coverage"]
 )
-```
+```

doc/plm/plr_gate.qmd

@@ -32,7 +32,7 @@ The non-uniform results (coverage, ci length and bias) refer to averaged values
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/plm/plr_gate_coverage_metadata.csv'
+metadata_file = '../../results/plm/plr_gate_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```