Update main.py

main.py

@@ -56,17 +56,13 @@ def get_data(address, start_date, end_date, radius_miles, get_max):
         years = [pd.Timestamp(start_date).year]
     
     # Geocode Address
-    try:
-        lat, lon= geocode_address(address)
-    except:
-        lat, lon= None,None
+    lat, lon= geocode_address(address)
+
 
-    
     # Convert Lat Lon to row & col on Array
-    try:
-        row, col = lat_lon_to_row_col(lat, lon)
-    except:
-        row=col=None
+ 
+    row, col = lat_lon_to_row_col(lat, lon)
+
    
 
     files = [
@@ -80,33 +76,33 @@ def get_data(address, start_date, end_date, radius_miles, get_max):
     files_choosen = [i for i in files if any(i for j in years if str(j) in i)]
 
 
-    # # Query and Collect H5 Data
-    # all_data = []
-    # all_dates = []
-    # for file in files_choosen:
-    #     with h5py.File(file, 'r') as f:
-    #         # Get Dates from H5
-    #         dates = f['date_time_hr'][:]
-    #         date_idx = np.where((dates >= int(start_date))
-    #                             & (dates <= int(end_date)))[0]
+    # Query and Collect H5 Data
+    all_data = []
+    all_dates = []
+    for file in files_choosen:
+        with h5py.File(file, 'r') as f:
+            # Get Dates from H5
+            dates = f['date_time_hr'][:]
+            date_idx = np.where((dates >= int(start_date))
+                                & (dates <= int(end_date)))[0]
 
-    #         # Select Data by Date and Radius
-    #         dates = dates[date_idx]
-    #         data = f['APCP'][date_idx, row-radius_miles:row +
-    #                          radius_miles+1, col-radius_miles:col+radius_miles+1]
+            # Select Data by Date and Radius
+            dates = dates[date_idx]
+            data = f['APCP'][date_idx, row-radius_miles:row +
+                             radius_miles+1, col-radius_miles:col+radius_miles+1]
 
-    #         all_data.append(data)
-    #         all_dates.append(dates)
+            all_data.append(data)
+            all_dates.append(dates)
 
-    # data_all = np.vstack(all_data)
-    # dates_all = np.concatenate(all_dates)
+    data_all = np.vstack(all_data)
+    dates_all = np.concatenate(all_dates)
 
-    # # Convert to Inches
-    # data_mat = np.where(data_all < 0, 0, data_all)*0.0393701
+    # Convert to Inches
+    data_mat = np.where(data_all < 0, 0, data_all)*0.0393701
 
-    # # Get Radius of Data
-    # disk_mask = np.where(disk(radius_miles) == 1, True, False)
-    # data_mat = np.where(disk_mask, data_mat, -1).round(3)
+    # Get Radius of Data
+    disk_mask = np.where(disk(radius_miles) == 1, True, False)
+    data_mat = np.where(disk_mask, data_mat, -1).round(3)
 
     # # Process to DataFrame
     # # Find Max of Data