Update app.py

app.py

@@ -897,7 +897,6 @@ def update_route_clusters(start_year, start_month, end_year, end_month, enso_val
     cluster_info_text = "\n".join(cluster_info_lines)
     return fig_tsne, fig_routes, fig_stats, cluster_info_text
 
-# Gradio Interface
 # Gradio Interface
 with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
     gr.Markdown("# Typhoon Analysis Dashboard")
@@ -913,7 +912,7 @@ with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
         - **Wind Analysis**: Examine wind speed vs ONI relationships
         - **Pressure Analysis**: Analyze pressure vs ONI relationships
         - **Longitude Analysis**: Study typhoon generation longitude vs ONI
-        - **Path Animation**: Watch animated typhoon paths with wind radius visualization
+        - **Path Animation**: Watch animated tropical cyclone paths with wind radius visualization
         - **TSNE Cluster**: Perform t-SNE clustering on typhoon routes with mean routes and region analysis
         
         Select a tab above to begin your analysis.
@@ -1067,9 +1066,23 @@ with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
             outputs=[regression_plot, slopes_text, lon_regression_results]
         )
     
-    with gr.Tab("Typhoon Path Animation"):
+    with gr.Tab("Tropical Cyclone Path Animation"):
         with gr.Row():
             year_dropdown = gr.Dropdown(label="Year", choices=[str(y) for y in range(1950, 2025)], value="2000")
+            basin_dropdown = gr.Dropdown(
+                label="Basin", 
+                choices=[
+                    "All Basins",
+                    "NA - North Atlantic",
+                    "EP - Eastern North Pacific",
+                    "WP - Western North Pacific",
+                    "NI - North Indian",
+                    "SI - South Indian",
+                    "SP - Southern Pacific",
+                    "SA - South Atlantic"
+                ],
+                value="WP - Western North Pacific"
+            )
             typhoon_dropdown = gr.Dropdown(label="Tropical Cyclone")
             standard_dropdown = gr.Dropdown(label="Classification Standard", choices=['atlantic', 'taiwan'], value='atlantic')
         
@@ -1077,7 +1090,7 @@ with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
         path_video = gr.Video(label="Tropical Cyclone Path Animation", elem_id="path_video")
         animation_info = gr.Markdown("""
         ### Animation Instructions
-        1. Select a year from the dropdown
+        1. Select a year and basin from the dropdowns
         2. Choose a tropical cyclone from the populated list
         3. Select a classification standard (Atlantic or Taiwan)
         4. Click "Generate Animation"
@@ -1092,18 +1105,36 @@ with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
         Different agencies use different wind speed averaging periods: USA (1-min), JTWC (1-min), JMA (10-min), IMD (3-min).
         """)
         
-        def update_typhoon_options(year):
+        # Define the mapping from basin labels to ID prefixes
+        basin_to_prefix = {
+            "All Basins": None,
+            "NA - North Atlantic": "AL",
+            "EP - Eastern North Pacific": "EP",
+            "WP - Western North Pacific": "WP",
+            "NI - North Indian": ["IO", "BB", "AS"],  # Multiple prefixes for North Indian
+            "SI - South Indian": "SI",
+            "SP - Southern Pacific": "SP",
+            "SA - South Atlantic": "SL"
+        }
+        
+        def update_typhoon_options(year, basin):
             try:
                 season = ibtracs.get_season(int(year))
                 storm_summary = season.summary()
                 
-                # Simply get all storms for the year
+                # Get the prefix for filtering
+                prefix = basin_to_prefix.get(basin)
+                
+                # Get all storms for the year
                 options = []
                 for i in range(len(storm_summary)):
                     try:
                         name = storm_summary['name'][i] if not pd.isna(storm_summary['name'][i]) else "Unnamed"
                         storm_id = storm_summary['id'][i]
-                        options.append(f"{name} ({storm_id})")
+                        
+                        # Filter by basin if a specific basin is selected
+                        if prefix is None or (isinstance(prefix, list) and any(storm_id.startswith(p) for p in prefix)) or (not isinstance(prefix, list) and storm_id.startswith(prefix)):
+                            options.append(f"{name} ({storm_id})")
                     except:
                         continue
                 
@@ -1112,19 +1143,20 @@ with gr.Blocks(title="Typhoon Analysis Dashboard") as demo:
                 print(f"Error updating typhoon options: {e}")
                 return gr.update(choices=[], value=None)
         
-        year_dropdown.change(fn=update_typhoon_options, inputs=year_dropdown, outputs=typhoon_dropdown)
+        year_dropdown.change(fn=update_typhoon_options, inputs=[year_dropdown, basin_dropdown], outputs=typhoon_dropdown)
+        basin_dropdown.change(fn=update_typhoon_options, inputs=[year_dropdown, basin_dropdown], outputs=typhoon_dropdown)
         
-        def simplified_track_video(year, typhoon, standard):
+        def simplified_track_video(year, basin, typhoon, standard):
             if not typhoon:
                 return None
             
             # Extract storm ID and generate video
             typhoon_id = typhoon.split('(')[-1].strip(')')
-            return generate_track_video(year, "All", typhoon, standard)  # Pass "All" as basin
+            return generate_track_video(year, "All", typhoon, standard)  # Pass "All" as basin parameter for compatibility
             
         animate_btn.click(
             fn=simplified_track_video,
-            inputs=[year_dropdown, typhoon_dropdown, standard_dropdown],
+            inputs=[year_dropdown, basin_dropdown, typhoon_dropdown, standard_dropdown],
             outputs=path_video
         )