update irm qmd files

Author: SvenKlaassen

doc/_quarto-dev.yml

@@ -15,6 +15,7 @@ website:
     - irm/irm_cate.qmd
     - irm/apo.qmd
     - irm/qte.qmd
+    - irm/iivm.qmd
     # PLM
     - plm/plr.qmd
     - plm/plr_gate.qmd

doc/_website.yml

@@ -18,6 +18,7 @@ website:
           - irm/irm_cate.qmd
           - irm/apo.qmd
           - irm/qte.qmd
+          - irm/iivm.qmd
       - text: "PLM"
         menu:
           - plm/plr.qmd

doc/irm/apo.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)
 ```
 
 ## APO Pointwise Coverage
@@ -78,31 +40,41 @@ print(metadata_df.T.to_string(header=False))
 ```{python}
 #| echo: false
 
-# set up data and rename columns
-df = pd.read_csv("../../results/irm/irm_apo_coverage_apo.csv", index_col=None)
+# set up data
+df_apo = pd.read_csv("../../results/irm/irm_apo_coverage_apo.csv", index_col=None)
 
-assert df["repetition"].nunique() == 1
-n_rep = df["repetition"].unique()[0]
+assert df_apo["repetition"].nunique() == 1
+n_rep_apo = df_apo["repetition"].unique()[0]
 
-display_columns = ["Learner g", "Learner m", "Treatment Level", "Bias", "CI Length", "Coverage"]
+display_columns_apo = ["Learner g", "Learner m", "Treatment Level", "Bias", "CI Length", "Coverage"]
 ```
 
 
 ```{python}
 #| echo: false
 
-level = 0.95
-df_ate_95 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_apo,
+    filters={"level": 0.95},
+    display_cols=display_columns_apo,
+    n_rep=n_rep_apo,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 
 ```{python}
 #| echo: false
 
-level = 0.9
-df_ate_9 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_apo,
+    filters={"level": 0.9},
+    display_cols=display_columns_apo,
+    n_rep=n_rep_apo,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 
@@ -126,80 +98,40 @@ print(metadata_df.T.to_string(header=False))
 ```{python}
 #| echo: false
 
-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", "Uniform Coverage"])
-    styled_df = styled_df.apply(
-        highlight_range,
-        level=level,
-        dist=0.1,
-        props='color:black;background-color:yellow',
-        subset=["Coverage", "Uniform Coverage"])
-    styled_df = styled_df.apply(
-        highlight_range,
-        level=level,
-        dist=0.05,
-        props='color:white;background-color:darkgreen',
-        subset=["Coverage", "Uniform Coverage"])
-
-    # set all coverage values to bold
-    styled_df = styled_df.set_properties(
-        **{'font-weight': 'bold'},
-        subset=["Coverage", "Uniform 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)
-```
-
-```{python}
-#| echo: false
-
-# set up data and rename columns
-df = pd.read_csv("../../results/irm/irm_apo_coverage_apos.csv", index_col=None)
+# set up data
+df_apos = pd.read_csv("../../results/irm/irm_apo_coverage_apos.csv", index_col=None)
 
-assert df["repetition"].nunique() == 1
-n_rep = df["repetition"].unique()[0]
+assert df_apos["repetition"].nunique() == 1
+n_rep_apos = df_apos["repetition"].unique()[0]
 
-display_columns = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
+display_columns_apos = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
 ```
 
 ```{python}
 #| echo: false
 
-level = 0.95
-df_ate_95 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_apos,
+    filters={"level": 0.95},
+    display_cols=display_columns_apos,
+    n_rep=n_rep_apos,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
 ```
 
 
 ```{python}
 #| echo: false
 
-level = 0.9
-df_ate_9 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_apos,
+    filters={"level": 0.9},
+    display_cols=display_columns_apos,
+    n_rep=n_rep_apos,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
 ```
 
 ## Causal Contrast Coverage
@@ -222,28 +154,38 @@ print(metadata_df.T.to_string(header=False))
 ```{python}
 #| echo: false
 
-# set up data and rename columns
-df = pd.read_csv("../../results/irm/irm_apo_coverage_apos_contrast.csv", index_col=None)
+# set up data
+df_contrast = pd.read_csv("../../results/irm/irm_apo_coverage_apos_contrast.csv", index_col=None)
 
-assert df["repetition"].nunique() == 1
-n_rep = df["repetition"].unique()[0]
+assert df_contrast["repetition"].nunique() == 1
+n_rep_contrast = df_contrast["repetition"].unique()[0]
 
-display_columns = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
+display_columns_contrast = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage", "Uniform CI Length", "Uniform Coverage"]
 ```
 
 ```{python}
 #| echo: false
 
-level = 0.95
-df_ate_95 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_contrast,
+    filters={"level": 0.95},
+    display_cols=display_columns_contrast,
+    n_rep=n_rep_contrast,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
 ```
 
 
 ```{python}
 #| echo: false
 
-level = 0.9
-df_ate_9 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df_contrast,
+    filters={"level": 0.9},
+    display_cols=display_columns_contrast,
+    n_rep=n_rep_contrast,
+    level_col="level",
+    coverage_highlight_cols=["Coverage", "Uniform Coverage"]
+)
 ```

doc/irm/iivm.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
@@ -91,16 +53,26 @@ display_columns = ["Learner g", "Learner m", "Bias", "CI Length", "Coverage"]
 ```{python}
 #| echo: false
 
-level = 0.95
-df_ate_95 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_95, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df,
+    filters={"level": 0.95},
+    display_cols=display_columns,
+    n_rep=n_rep,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```
 
 
 ```{python}
 #| echo: false
 
-level = 0.9
-df_ate_9 = df[df['level'] == level][display_columns]
-make_pretty(df_ate_9, level, n_rep)
+generate_and_show_styled_table(
+    main_df=df,
+    filters={"level": 0.9},
+    display_cols=display_columns,
+    n_rep=n_rep,
+    level_col="level",
+    coverage_highlight_cols=["Coverage"]
+)
 ```