it seems to work now, show plots again

app.py

@@ -39,9 +39,9 @@ def update_all_plots(frequency, split_name):
 
 print(f"Defining blocks...")
 # Create Gradio interface
-with gr.Blocks(title="Interactive Wave Plotter") as demo:
-    gr.Markdown("## Interactive Wave Plotter")
-    gr.Markdown("Adjust the slider to change the frequency of all waves simultaneously.")
+with gr.Blocks(title="BGC Keyword Plotter") as demo:
+    gr.Markdown("## BGC Keyword Plotter")
+    gr.Markdown("Select the model name and minimal number of domains in Antismash-db subset.")
     
     with gr.Row():
         frequency_slider = gr.Slider(

mpl_data_plotter.py

@@ -14,17 +14,14 @@ class MatplotlibDataPlotter:
 
         self.num_domains_in_region_df = num_domains_in_region_df
 
-        #self.single_domains_fig = plt.figure(figsize=(5, 10))
-        #self.pair_domains_fig = plt.figure(figsize=(5, 10))
+        self.single_domains_fig = plt.figure(figsize=(5, 10))
+        self.pair_domains_fig = plt.figure(figsize=(5, 10))
 
     def plot_single_domains(self, num_domains, split_name):
-        return plt.gcf()
-        # selected_region_ids = self.num_domains_in_region_df.loc[
-        #     self.num_domains_in_region_df.num_domains >= num_domains, 
-        #     'cds_region_id'].values
-        # single_df_subset = self.single_df.loc[self.single_df.cds_region_id.isin(selected_region_ids)]
-        
-        
+        selected_region_ids = self.num_domains_in_region_df.loc[
+            self.num_domains_in_region_df.num_domains >= num_domains, 
+            'cds_region_id'].values
+        single_df_subset = self.single_df.loc[self.single_df.cds_region_id.isin(selected_region_ids)]
         # split_name = 'stratified'
         column_name = f'cosine_similarity_{split_name}'
         # single_df_subset = single_df.loc[single_df.dom_location_len >= num_domains]
@@ -64,11 +61,10 @@ class MatplotlibDataPlotter:
         return fig # plt.gcf()
 
     def plot_pair_domains(self, num_domains, split_name):
-        return plt.gcf()
-        # selected_region_ids = self.num_domains_in_region_df.loc[
-        #     self.num_domains_in_region_df.num_domains >= num_domains, 
-        #     'cds_region_id'].values
-        # pair_df_subset = self.pair_df.loc[self.pair_df.cds_region_id.isin(selected_region_ids)]
+        selected_region_ids = self.num_domains_in_region_df.loc[
+            self.num_domains_in_region_df.num_domains >= num_domains, 
+            'cds_region_id'].values
+        pair_df_subset = self.pair_df.loc[self.pair_df.cds_region_id.isin(selected_region_ids)]
         # split_name = 'stratified'
         column_name = f'cosine_similarity_{split_name}'
         # pair_df_subset = pair_df.loc[pair_df.dom_location_len >= num_domains]