fix metadata paths

Author: SvenKlaassen

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))
 ```

doc/rdd/rdd.qmd

@@ -31,7 +31,7 @@ The simulations are based on the [make_simple_rdd_data](https://docs.doubleml.or
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/rdd/rdd_sharp_coverage_metadata.csv'
+metadata_file = '../../results/rdd/rdd_sharp_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```
@@ -83,7 +83,7 @@ The simulations are based on the [make_simple_rdd_data](https://docs.doubleml.or
 
 ```{python}
 #| echo: false
-metadata_file = '../../results/rdd/rdd_fuzzy_coverage_metadata.csv'
+metadata_file = '../../results/rdd/rdd_fuzzy_metadata.csv'
 metadata_df = pd.read_csv(metadata_file)
 print(metadata_df.T.to_string(header=False))
 ```