fixed checkbox logic

app.py

@@ -40,12 +40,8 @@ globaldf.sort_values(by=['Modality', 'Type'], inplace=True)
 
 # Path: taxonomy.py
 
-def filter_modality(filteredtable, modality_filter):
-    filteredtable = filteredtable[filteredtable['Modality'].isin(modality_filter)]
-    return filteredtable
-
-def filter_type(filteredtable, modality_filter):
-    filteredtable = filteredtable[filteredtable['Type'].isin(modality_filter)]
+def filter_modality_type(fulltable, modality_filter, type_filter):
+    filteredtable = fulltable[fulltable['Modality'].isin(modality_filter) & fulltable['Type'].isin(type_filter)]
     return filteredtable
 
 def showmodal(evt: gr.SelectData):
@@ -123,10 +119,10 @@ The following categories are high-level, non-exhaustive, and present a synthesis
                                                 #  info="Which modality to show."
                                                  )
             with gr.Row():
-                biastable_full = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=False, interactive=False)
-                biastable_filtered = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=True, interactive=False)
-                modality_filter.change(filter_modality, inputs=[biastable_filtered, modality_filter], outputs=biastable_filtered)
-                type_filter.change(filter_type, inputs=[biastable_filtered, type_filter], outputs=biastable_filtered)
+                table_full = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=False, interactive=False)
+                table_filtered = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=True, interactive=False)
+                modality_filter.change(filter_modality_type, inputs=[table_full, modality_filter, type_filter], outputs=table_filtered)
+                type_filter.change(filter_modality_type, inputs=[table_full, modality_filter, type_filter], outputs=table_filtered)
 
 
                 with Modal(visible=False) as modal:
@@ -136,7 +132,7 @@ The following categories are high-level, non-exhaustive, and present a synthesis
                     abstractmd = gr.Markdown(visible=False)
                     datasetmd = gr.Markdown(visible=False)
                     gallery = gr.Gallery(visible=False)
-                biastable_filtered.select(showmodal, None, [modal, titlemd, authormd, tagsmd, abstractmd, datasetmd, gallery])
+                table_filtered.select(showmodal, None, [modal, titlemd, authormd, tagsmd, abstractmd, datasetmd, gallery])
 
 
 
@@ -161,10 +157,10 @@ The following categories are high-level, non-exhaustive, and present a synthesis
                                                 #  info="Which modality to show."
                                                  )
             with gr.Row():
-                biastable_full = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=False, interactive=False)
-                biastable_filtered = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=True, interactive=False)
-                modality_filter.change(filter_modality, inputs=[biastable_filtered, modality_filter], outputs=biastable_filtered)
-                type_filter.change(filter_type, inputs=[biastable_filtered, type_filter], outputs=biastable_filtered)
+                table_full = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=False, interactive=False)
+                table_filtered = gr.DataFrame(value=fulltable, wrap=True, datatype="markdown", visible=True, interactive=False)
+                modality_filter.change(filter_modality_type, inputs=[table_full, modality_filter, type_filter], outputs=table_filtered)
+                type_filter.change(filter_modality_type, inputs=[table_full, modality_filter, type_filter], outputs=table_filtered)
 
 
                 with Modal(visible=False) as modal:
@@ -174,7 +170,8 @@ The following categories are high-level, non-exhaustive, and present a synthesis
                     abstractmd = gr.Markdown(visible=False)
                     datasetmd = gr.Markdown(visible=False)
                     gallery = gr.Gallery(visible=False)
-                biastable_filtered.select(showmodal, None, [modal, titlemd, authormd, tagsmd, abstractmd, datasetmd, gallery])
+                table_filtered.select(showmodal, None, [modal, titlemd, authormd, tagsmd, abstractmd, datasetmd, gallery])
+            
 
 
         # with gr.TabItem("Disparate Performance"):