removed bigos diagnostic

app.py

@@ -95,15 +95,20 @@ with analysis_bigos:
         st.dataframe(df_metrics_subset_size)
         df_metrics_subset_features = extract_stats_for_dataset_card(df_multindex_for_agg, subset, metrics_features, add_total=False)
         st.dataframe(df_metrics_subset_features)
-
-with analysis_bigos_diagnostic:
-    dataset_name = "amu-cai/pl-asr-bigos-v2-diagnostic"
-    dataset_short_name = "BIGOS diagnostic"
-    dataset_version = "V2"
     
-    dataset_configs = get_dataset_config_names(dataset_name,trust_remote_code=True)
+#########################################PELCRA################################################
+with analysis_bigos_pelcra:
+
+    dataset_name = "pelcra/pl-asr-pelcra-for-bigos"
+    dataset_short_name = "PELCRA"
+
+    # local version with granted gated access
+    #dataset_configs = get_dataset_config_names(dataset_name,trust_remote_code=True)
     # remove "all" subset, which is always the last config type
-    dataset_configs.pop()
+    #dataset_configs.pop()
+    
+    # remote version with hardcoded access
+    dataset_configs = ['ul-diabiz_poleval-22', 'ul-spokes_mix_emo-18', 'ul-spokes_mix_luz-18', 'ul-spokes_mix_parl-18', 'ul-spokes_biz_bio-23', 'ul-spokes_biz_int-23', 'ul-spokes_biz_luz-23', 'ul-spokes_biz_pod-23', 'ul-spokes_biz_pres-23', 'ul-spokes_biz_vc-23', 'ul-spokes_biz_vc2-23', 'ul-spokes_biz_wyw-23']
     print(dataset_configs)
     # read the reports for public and secret datasets
     [stats_dict_public, contents_dict_public] = read_reports(dataset_name)
@@ -116,7 +121,6 @@ with analysis_bigos_diagnostic:
     # extract metrics from dictionary and convert to various dataframes for easier analysis and visualization
     #st.header("Summary statistics")
 
-
     st.header("Dataset level metrics")
     df_sum_stats_agg = extract_stats_to_agg(df_multindex_for_agg, metrics_size)
 
@@ -155,20 +159,15 @@ with analysis_bigos_diagnostic:
         df_metrics_subset_features = extract_stats_for_dataset_card(df_multindex_for_agg, subset, metrics_features, add_total=False)
         st.dataframe(df_metrics_subset_features)
 
+"""
+with analysis_bigos_diagnostic:
+    dataset_name = "amu-cai/pl-asr-bigos-v2-diagnostic"
+    dataset_short_name = "BIGOS diagnostic"
+    dataset_version = "V2"
     
-#########################################PELCRA################################################
-with analysis_bigos_pelcra:
-
-    dataset_name = "pelcra/pl-asr-pelcra-for-bigos"
-    dataset_short_name = "PELCRA"
-
-    # local version with granted gated access
-    #dataset_configs = get_dataset_config_names(dataset_name,trust_remote_code=True)
+    dataset_configs = get_dataset_config_names(dataset_name,trust_remote_code=True)
     # remove "all" subset, which is always the last config type
-    #dataset_configs.pop()
-    
-    # remote version with hardcoded access
-    dataset_configs = ['ul-diabiz_poleval-22', 'ul-spokes_mix_emo-18', 'ul-spokes_mix_luz-18', 'ul-spokes_mix_parl-18', 'ul-spokes_biz_bio-23', 'ul-spokes_biz_int-23', 'ul-spokes_biz_luz-23', 'ul-spokes_biz_pod-23', 'ul-spokes_biz_pres-23', 'ul-spokes_biz_vc-23', 'ul-spokes_biz_vc2-23', 'ul-spokes_biz_wyw-23']
+    dataset_configs.pop()
     print(dataset_configs)
     # read the reports for public and secret datasets
     [stats_dict_public, contents_dict_public] = read_reports(dataset_name)
@@ -181,6 +180,7 @@ with analysis_bigos_pelcra:
     # extract metrics from dictionary and convert to various dataframes for easier analysis and visualization
     #st.header("Summary statistics")
 
+
     st.header("Dataset level metrics")
     df_sum_stats_agg = extract_stats_to_agg(df_multindex_for_agg, metrics_size)
 
@@ -218,3 +218,4 @@ with analysis_bigos_pelcra:
         st.dataframe(df_metrics_subset_size)
         df_metrics_subset_features = extract_stats_for_dataset_card(df_multindex_for_agg, subset, metrics_features, add_total=False)
         st.dataframe(df_metrics_subset_features)
+"""