Update app.py

app.py

@@ -40,38 +40,38 @@ def geocode(address):
     return pd.DataFrame({'Lat': lat, 'Lon': lon}, index=[0])
 
 
-# def get_data(row, col, radius=8):
-#     files = [
-#         "data/2023_hail.h5",
-#         "data/2022_hail.h5",
-#         "data/2021_hail.h5",
-#         "data/2020_hail.h5"
-#     ]
-#     all_data = []
-#     all_dates = []
-#     for f in files:
-#         with h5py.File(f, 'r') as f:
-#             data = f['hail'][:, row - radius: row + radius+ 1,   col-radius: col+radius+1]
-#             dates = f['dates'][:]
-#             all_data.append(data)
-#             all_dates.append(dates)
-
-#     data_mat = np.concatenate(all_data)
-#     data_mat = np.where(data_mat < 0, 0, data_mat)*0.0393701
-#     dates_mat = np.concatenate(all_dates)
-
-#     data_actual = [i[radius, radius] for i in data_mat]
-#     data_max = np.max(data_mat, axis=(1, 2))
-#     data_max_2 = np.max(data_mat, axis=0)
-
-#     df = pd.DataFrame({'Date': dates_mat,
-#                        'Actual': data_actual,
-#                       'Max': data_max})
-
-#     df['Date'] = pd.to_datetime(df['Date'], format='%Y%m%d')
-#     df['Date']=df['Date']+pd.Timedelta(days=1)
-
-#     return df, data_max_2
+def get_data(row, col, radius=8):
+    files = [
+        "data/2023_hail.h5",
+        "data/2022_hail.h5",
+        "data/2021_hail.h5",
+        "data/2020_hail.h5"
+    ]
+    all_data = []
+    all_dates = []
+    for f in files:
+        with h5py.File(f, 'r') as f:
+            data = f['hail'][:, row - radius: row + radius+ 1,   col-radius: col+radius+1]
+            dates = f['dates'][:]
+            all_data.append(data)
+            all_dates.append(dates)
+
+    data_mat = np.concatenate(all_data)
+    data_mat = np.where(data_mat < 0, 0, data_mat)*0.0393701
+    dates_mat = np.concatenate(all_dates)
+
+    data_actual = [i[radius, radius] for i in data_mat]
+    data_max = np.max(data_mat, axis=(1, 2))
+    data_max_2 = np.max(data_mat, axis=0)
+
+    df = pd.DataFrame({'Date': dates_mat,
+                       'Actual': data_actual,
+                      'Max': data_max})
+
+    df['Date'] = pd.to_datetime(df['Date'], format='%Y%m%d')
+    df['Date']=df['Date']+pd.Timedelta(days=1)
+
+    return df, data_max_2
 
 
 def map_folium(lat, lon,files_dates_selected, within_days ):
@@ -206,6 +206,7 @@ crs_dic = pickle.load(open('data/mrms_hail_crs.pkl', 'rb'))
 transform = crs_dic['affine']
 
 row, col = rasterio.transform.rowcol(transform, lon, lat)
+row, col =int(row), int(col)
 st.write(row,col)
 
 # center=row,col
@@ -221,12 +222,11 @@ files = [
 all_data = []
 all_dates = []
 for i in files:
-    with h5py.File(i, 'r') as f:
-        data = f['hail'][:, 100 - radius:100 + radius+ 1,
-                100-radius: 100+radius+1]
-        dates = f['dates'][:]
-        all_data.append(data)
-        all_dates.append(dates)
+    with h5py.File(f, 'r') as f:
+            data = f['hail'][:, row - radius: row + radius+ 1,   col-radius: col+radius+1]
+            dates = f['dates'][:]
+            all_data.append(data)
+            all_dates.append(dates)
 
 
 
@@ -237,8 +237,8 @@ files_dates_selected = [i for i in files if any(
 
 
 
-# # Get Data
-# df_data, max_values = get_data(row, col, radius)
+# Get Data
+df_data, max_values = get_data(row, col, radius)
 
 # df_data = df_data.query(f"'{start_date}'<=Date<='{end_date}'")
 # df_data['Max'] = df_data['Max'].round(3)