Update app.py

app.py

@@ -43,9 +43,9 @@ def geocode(address):
 def get_data(row, col, radius=8):
     files = [
         "data/2023_hail.h5",
-        # "data/2022_hail.h5",
-        # "data/2021_hail.h5",
-        # "data/2020_hail.h5"
+        "data/2022_hail.h5",
+        "data/2021_hail.h5",
+        "data/2020_hail.h5"
     ]
     all_data = []
     all_dates = []
@@ -207,6 +207,24 @@ transform = crs_dic['affine']
 
 row, col = rasterio.transform.rowcol(transform, lon, lat)
 st.write(row,col)
+
+files = [
+    "data/2023_hail.h5",
+    "data/2022_hail.h5",
+    "data/2021_hail.h5",
+    "data/2020_hail.h5"
+]
+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]
+        st.write(data)
+        dates = f['dates'][:]
+        all_data.append(data)
+        all_dates.append(dates)
+
 # center=row,col
 radius = int(np.ceil(circle_radius*1.6))
 # crop_coords = col-radius, row-radius, col+radius+1, row+radius+1
@@ -218,50 +236,50 @@ 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)
-df_data['Actual'] = df_data['Actual'].round(3)
+# df_data = df_data.query(f"'{start_date}'<=Date<='{end_date}'")
+# df_data['Max'] = df_data['Max'].round(3)
+# df_data['Actual'] = df_data['Actual'].round(3)
 
 
-# Create the bar chart
-fig = alt.Chart(df_data).mark_bar(size=3, color='red').encode(
-    x='Date:T',  # Temporal data type
-    y='Actual:Q',  # Quantitative data type
-    color='Actual:Q',  # Color based on Actual values
-    tooltip=[  # Adding tooltips
-        alt.Tooltip('Date:T', title='Date'),
-        alt.Tooltip('Actual:Q', title='Actual Value'),
-        alt.Tooltip('Max:Q', title=f'Max Value with {circle_radius} Miles')
-    ]
-).configure(
-    view=alt.ViewConfig(
-        strokeOpacity=0  # No border around the chart
-    )
-).configure_axis(
-    grid=False  # Disable grid lines
-).configure_legend(
-    fillColor='transparent',  # Ensure no legend is shown
-    strokeColor='transparent'
-)
+# # Create the bar chart
+# fig = alt.Chart(df_data).mark_bar(size=3, color='red').encode(
+#     x='Date:T',  # Temporal data type
+#     y='Actual:Q',  # Quantitative data type
+#     color='Actual:Q',  # Color based on Actual values
+#     tooltip=[  # Adding tooltips
+#         alt.Tooltip('Date:T', title='Date'),
+#         alt.Tooltip('Actual:Q', title='Actual Value'),
+#         alt.Tooltip('Max:Q', title=f'Max Value with {circle_radius} Miles')
+#     ]
+# ).configure(
+#     view=alt.ViewConfig(
+#         strokeOpacity=0  # No border around the chart
+#     )
+# ).configure_axis(
+#     grid=False  # Disable grid lines
+# ).configure_legend(
+#     fillColor='transparent',  # Ensure no legend is shown
+#     strokeColor='transparent'
+# )
 
 
 
 
 with col1:
     st.title(f'Hail')
-    try:
-        st.altair_chart(fig, use_container_width=True)
-        csv = convert_df(df_data)
-        st.download_button(
-            label="Download data as CSV",
-            data=csv,
-            file_name='data.csv',
-            mime='text/csv')
-    except:
-        pass
+    # try:
+    #     st.altair_chart(fig, use_container_width=True)
+    #     csv = convert_df(df_data)
+    #     st.download_button(
+    #         label="Download data as CSV",
+    #         data=csv,
+    #         file_name='data.csv',
+    #         mime='text/csv')
+    # except:
+    #     pass
 
 
 with col2: