update plm websites

Author: SvenKlaassen

doc/plm/pliv.qmd

@@ -9,55 +9,17 @@ jupyter: python3
 
 import numpy as np
 import pandas as pd
-from itables import init_notebook_mode, show, options
+from itables import init_notebook_mode
+import os
+import sys
 
-init_notebook_mode(all_interactive=True)
+doc_dir = os.path.abspath(os.path.join(os.getcwd(), ".."))
+if doc_dir not in sys.path:
+    sys.path.append(doc_dir)
+
+from utils.style_tables import generate_and_show_styled_table
 
-def highlight_range(s, level=0.95, dist=0.05, props=''):
-    color_grid = np.where((s >= level-dist) &
-                          (s <= level+dist), props, '')
-    return color_grid
-
-
-def color_coverage(df, level):
-    # color coverage column order is important
-    styled_df = df.apply(
-        highlight_range,
-        level=level,
-        dist=1.0,
-        props='color:black;background-color:red',
-        subset=["Coverage"])
-    styled_df = styled_df.apply(
-        highlight_range,
-        level=level,
-        dist=0.1,
-        props='color:black;background-color:yellow',
-        subset=["Coverage"])
-    styled_df = styled_df.apply(
-        highlight_range,
-        level=level,
-        dist=0.05,
-        props='color:white;background-color:darkgreen',
-        subset=["Coverage"])
-
-    # set all coverage values to bold
-    styled_df = styled_df.set_properties(
-        **{'font-weight': 'bold'},
-        subset=["Coverage"])
-    return styled_df
-
-
-def make_pretty(df, level, n_rep):
-    styled_df = df.style.hide(axis="index")
-    # Format only float columns
-    float_cols = df.select_dtypes(include=['float']).columns
-    styled_df = styled_df.format({col: "{:.3f}" for col in float_cols})
-
-    # color coverage column order is important
-    styled_df = color_coverage(styled_df, level)
-    caption = f"Coverage for {level*100}%-Confidence Interval over {n_rep} Repetitions"
-
-    return show(styled_df, caption=caption, allow_html=True)
+init_notebook_mode(all_interactive=True)
 ```
 
 ## LATE Coverage
@@ -79,34 +41,46 @@ print(metadata_df.T.to_string(header=False))
 #| echo: false
 
 # set up data and rename columns
-df = pd.read_csv("../../results/plm/pliv_late_coverage.csv", index_col=None)
+df_coverage_pliv = pd.read_csv("../../results/plm/pliv_late_coverage.csv", index_col=None)
 
-assert df["repetition"].nunique() == 1
-n_rep = df["repetition"].unique()[0]
+if "repetition" in df_coverage_pliv.columns and df_coverage_pliv["repetition"].nunique() == 1:
+    n_rep_pliv = df_coverage_pliv["repetition"].unique()[0]
+elif "n_rep" in df_coverage_pliv.columns and df_coverage_pliv["n_rep"].nunique() == 1:
+    n_rep_pliv = df_coverage_pliv["n_rep"].unique()[0]
+else:
+    n_rep_pliv = "N/A"
 
-display_columns = ["Learner g", "Learner m", "Learner r", "Bias", "CI Length", "Coverage"]
+display_columns_pliv = ["Learner g", "Learner m", "Learner r", "Bias", "CI Length", "Coverage"]
 ```
 
 ### Partialling out
 
 ```{python}
 #| echo: false
-score = "partialling out"
-level = 0.95
 
-df_ate_95 = df[(df['level'] == level) & (df["score"] == score)][display_columns]
-df_ate_95.rename(columns={"Learner g": "Learner l"}, inplace=True)
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_coverage_pliv,
+    filters={"level": 0.95, "score": "partialling out"},
+    display_cols=display_columns_pliv,
+    n_rep=n_rep_pliv,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ```{python}
 #| echo: false
-score = "partialling out"
-level = 0.9
 
-df_ate_9 = df[(df['level'] == level) & (df["score"] == score)][display_columns]
-df_ate_9.rename(columns={"Learner g": "Learner l"}, inplace=True)
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_coverage_pliv,
+    filters={"level": 0.90, "score": "partialling out"},
+    display_cols=display_columns_pliv,
+    n_rep=n_rep_pliv,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ### IV-type
@@ -115,18 +89,26 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 ```{python}
 #| echo: false
-score = "IV-type"
-level = 0.95
 
-df_ate_95 = df[(df['level'] == level) & (df["score"] == score)][display_columns]
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_coverage_pliv,
+    filters={"level": 0.95, "score": "IV-type"},
+    display_cols=display_columns_pliv,
+    n_rep=n_rep_pliv,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ```{python}
 #| echo: false
-score = "IV-type"
-level = 0.9
 
-df_ate_9 = df[(df['level'] == level) & (df["score"] == score)][display_columns]
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_coverage_pliv,
+    filters={"level": 0.9, "score": "IV-type"},
+    display_cols=display_columns_pliv,
+    n_rep=n_rep_pliv,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```

doc/plm/plr.qmd

@@ -9,15 +9,15 @@ jupyter: python3
 
 import numpy as np
 import pandas as pd
-from itables import init_notebook_mode, show, options
+from itables import init_notebook_mode
 import os
 import sys
 
 doc_dir = os.path.abspath(os.path.join(os.getcwd(), ".."))
 if doc_dir not in sys.path:
     sys.path.append(doc_dir)
 
-from utils.style_tables import create_styled_table
+from utils.style_tables import generate_and_show_styled_table
 
 init_notebook_mode(all_interactive=True)
 ```
@@ -57,25 +57,30 @@ display_columns_coverage = ["Learner g", "Learner m", "Bias", "CI Length", "Cove
 
 ```{python}
 # | echo: false
-score_po = "partialling out"
-level_95 = 0.95
 
-df_po_95 = df_coverage[(df_coverage["level"] == level_95) & (df_coverage["score"] == score_po)][display_columns_coverage].copy()
-df_po_95.rename(columns={"Learner g": "Learner l"}, inplace=True)
-
-styled_table_po_95 = create_styled_table(df_po_95, level_95, n_rep_coverage, coverage_cols=["Coverage"])
-show(styled_table_po_95, allow_html=True)
+generate_and_show_styled_table(
+    main_df=df_coverage,
+    filters={"level": 0.95, "score": "partialling out"},
+    display_cols=display_columns_coverage,
+    n_rep=n_rep_coverage,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ```{python}
 #| echo: false
-level_90 = 0.9
 
-df_po_90 = df_coverage[(df_coverage['level'] == level_90) & (df_coverage["score"] == score_po)][display_columns_coverage].copy()
-df_po_90.rename(columns={"Learner g": "Learner l"}, inplace=True)
-
-styled_table_po_90 = create_styled_table(df_po_90, level_90, n_rep_coverage, coverage_cols=["Coverage"])
-show(styled_table_po_90, allow_html=True)
+generate_and_show_styled_table(
+    main_df=df_coverage,
+    filters={"level": 0.9, "score": "partialling out"},
+    display_cols=display_columns_coverage,
+    n_rep=n_rep_coverage,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ### IV-type
@@ -84,23 +89,28 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 ```{python}
 #| echo: false
-score_iv = "IV-type"
-# level_95 is already defined
 
-df_iv_95 = df_coverage[(df_coverage['level'] == level_95) & (df_coverage["score"] == score_iv)][display_columns_coverage]
-
-styled_table_iv_95 = create_styled_table(df_iv_95, level_95, n_rep_coverage, coverage_cols=["Coverage"])
-show(styled_table_iv_95, allow_html=True)
+generate_and_show_styled_table(
+    main_df=df_coverage,
+    filters={"level": 0.95, "score": "IV-type"},
+    display_cols=display_columns_coverage,
+    n_rep=n_rep_coverage,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ```{python}
 #| echo: false
-# level_90 is already defined
-
-df_iv_90 = df_coverage[(df_coverage['level'] == level_90) & (df_coverage["score"] == score_iv)][display_columns_coverage]
 
-styled_table_iv_90 = create_styled_table(df_iv_90, level_90, n_rep_coverage, coverage_cols=["Coverage"])
-show(styled_table_iv_90, allow_html=True)
+generate_and_show_styled_table(
+    main_df=df_coverage,
+    filters={"level": 0.9, "score": "IV-type"},
+    display_cols=display_columns_coverage,
+    n_rep=n_rep_coverage,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 ## ATE Sensitivity
@@ -143,34 +153,30 @@ display_columns_sensitivity = [
 
 ```{python}
 #| echo: false
-# score_po and level_95 are defined above
-
-df_sens_po_95 = df_sensitivity[(df_sensitivity['level'] == level_95) & (df_sensitivity["score"] == score_po)][display_columns_sensitivity].copy()
-df_sens_po_95.rename(columns={"Learner g": "Learner l"}, inplace=True)
 
-styled_sens_po_95 = create_styled_table(
-    df_sens_po_95,
-    level_95,
-    n_rep_sensitivity,
-    coverage_cols=["Coverage", "Coverage (Upper)"] # Highlight both
+generate_and_show_styled_table(
+    main_df=df_sensitivity,
+    filters={"level": 0.95, "score": "partialling out"},
+    display_cols=display_columns_sensitivity,
+    n_rep=n_rep_sensitivity,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Coverage (Upper)"]
 )
-show(styled_sens_po_95, allow_html=True)
 ```
 
 ```{python}
 #| echo: false
-# score_po and level_90 are defined above
-
-df_sens_po_90 = df_sensitivity[(df_sensitivity['level'] == level_90) & (df_sensitivity["score"] == score_po)][display_columns_sensitivity].copy()
-df_sens_po_90.rename(columns={"Learner g": "Learner l"}, inplace=True)
-
-styled_sens_po_90 = create_styled_table(
-    df_sens_po_90,
-    level_90,
-    n_rep_sensitivity,
-    coverage_cols=["Coverage", "Coverage (Upper)"]
+#| 
+generate_and_show_styled_table(
+    main_df=df_sensitivity,
+    filters={"level": 0.9, "score": "partialling out"},
+    display_cols=display_columns_sensitivity,
+    n_rep=n_rep_sensitivity,
+    level_col="level",
+    rename_map={"Learner g": "Learner l"},
+    coverage_highlight_cols=["Coverage", "Coverage (Upper)"]
 )
-show(styled_sens_po_90, allow_html=True)
 ```
 
 ### IV-type
@@ -179,30 +185,26 @@ For the IV-type score, the learners `ml_l` and `ml_g` are both set to the same t
 
 ```{python}
 #| echo: false
-# score_iv and level_95 are defined above
-
-df_sens_iv_95 = df_sensitivity[(df_sensitivity['level'] == level_95) & (df_sensitivity["score"] == score_iv)][display_columns_sensitivity]
 
-styled_sens_iv_95 = create_styled_table(
-    df_sens_iv_95,
-    level_95,
-    n_rep_sensitivity,
-    coverage_cols=["Coverage", "Coverage (Upper)"]
+generate_and_show_styled_table(
+    main_df=df_sensitivity,
+    filters={"level": 0.95, "score": "IV-type"},
+    display_cols=display_columns_sensitivity,
+    n_rep=n_rep_sensitivity,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Coverage (Upper)"]
 )
-show(styled_sens_iv_95, allow_html=True)
 ```
 
 ```{python}
 #| echo: false
-# score_iv and level_90 are defined above
-
-df_sens_iv_90 = df_sensitivity[(df_sensitivity['level'] == level_90) & (df_sensitivity["score"] == score_iv)][display_columns_sensitivity]
 
-styled_sens_iv_90 = create_styled_table(
-    df_sens_iv_90,
-    level_90,
-    n_rep_sensitivity,
-    coverage_cols=["Coverage", "Coverage (Upper)"]
+generate_and_show_styled_table(
+    main_df=df_sensitivity,
+    filters={"level": 0.9, "score": "IV-type"},
+    display_cols=display_columns_sensitivity,
+    n_rep=n_rep_sensitivity,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Coverage (Upper)"]
 )
-show(styled_sens_iv_90, allow_html=True)
 ```