Update app.py

app.py

@@ -36,7 +36,7 @@ TYPHOON_DATA_PATH = os.path.join(DATA_PATH, 'processed_typhoon_data.csv')
 LOCAL_iBtrace_PATH = os.path.join(DATA_PATH, 'ibtracs.ALL.list.v04r01.csv') 
 iBtrace_uri = 'https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r01/access/csv/ibtracs.ALL.list.v04r01.csv'
 CACHE_FILE = 'ibtracs_cache.pkl'
-CACHE_EXPIRY_DAYS = 1
+CACHE_EXPIRY_DAYS = 0  # Force refresh for testing
 
 # Color maps for Plotly (RGB)
 color_map = {
@@ -130,11 +130,9 @@ def load_ibtracs_data():
         with open(CACHE_FILE, 'rb') as f:
             return pickle.load(f)
     
-    # Define the path for the all basins file
     all_basins_path = os.path.join(DATA_PATH, 'ibtracs.ALL.list.v04r01.csv')
     
     try:
-        # Try to load all basins file first
         if os.path.exists(all_basins_path):
             print("Loading ALL basins file...")
             ibtracs = tracks.TrackDataset(source='ibtracs', ibtracs_url=all_basins_path)
@@ -145,10 +143,9 @@ def load_ibtracs_data():
             with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.csv') as temp_file:
                 temp_file.write(response.text)
                 shutil.move(temp_file.name, all_basins_path)
-            # Load the full ALL dataset
+            print(f"Downloaded {all_basins_path}. Verify it contains all basins.")
             ibtracs = tracks.TrackDataset(source='ibtracs', ibtracs_url=all_basins_path)
         
-        # Save to cache
         with open(CACHE_FILE, 'wb') as f:
             pickle.dump(ibtracs, f)
         
@@ -156,7 +153,6 @@ def load_ibtracs_data():
         
     except Exception as e:
         print(f"Error loading IBTrACS data: {e}")
-        # As a fallback, try loading just the default data that comes with tropycal
         print("Attempting to load default dataset...")
         ibtracs = tracks.TrackDataset(basin='all')
         with open(CACHE_FILE, 'wb') as f:
@@ -208,6 +204,9 @@ def process_typhoon_data(typhoon_data):
     typhoon_data['USA_WIND'] = pd.to_numeric(typhoon_data['USA_WIND'], errors='coerce')
     typhoon_data['USA_PRES'] = pd.to_numeric(typhoon_data['USA_PRES'], errors='coerce')
     typhoon_data['LON'] = pd.to_numeric(typhoon_data['LON'], errors='coerce')
+    # Debug: Check unique basins
+    unique_basins = typhoon_data['SID'].str[:2].unique()
+    print(f"Unique basins in typhoon_data: {unique_basins}")
     typhoon_max = typhoon_data.groupby('SID').agg({
         'USA_WIND': 'max', 'USA_PRES': 'min', 'ISO_TIME': 'first', 'SEASON': 'first', 'NAME': 'first',
         'LAT': 'first', 'LON': 'first'