update app.py

app.py

@@ -354,74 +354,74 @@ if file_upload:
                 else:
                     st.warning(f"No value calculated for {location_name}.")
                     
-    
-    # Check if polygons_df is populated for polygons
-    if polygons_df is not None:
-        st.write("Preview of the uploaded polygons data:")
-        st.dataframe(polygons_df.head())
 
-        m = leafmap.Map(center=[polygons_df.geometry.centroid.y.mean(), polygons_df.geometry.centroid.x.mean()], zoom=10)
+ # Check if polygons_df is populated for polygons
+if polygons_df is not None:
+    st.write("Preview of the uploaded polygons data:")
+    st.dataframe(polygons_df.head())
+
+    m = leafmap.Map(center=[polygons_df.geometry.centroid.y.mean(), polygons_df.geometry.centroid.x.mean()], zoom=10)
 
-        for _, row in polygons_df.iterrows():
-            polygon = row['geometry']
+    for _, row in polygons_df.iterrows():
+        polygon = row['geometry']
             if polygon.is_valid:
                 gdf = gpd.GeoDataFrame([row], geometry=[polygon], crs=polygons_df.crs)
                 m.add_gdf(gdf=gdf, layer_name=row.get('name', 'Unnamed Polygon'))
 
-        st.write("Map of Uploaded Polygons:")
-        m.to_streamlit()
-        st.session_state.map_data = m
+    st.write("Map of Uploaded Polygons:")
+    m.to_streamlit()
+    st.session_state.map_data = m
 
-        for idx, row in polygons_df.iterrows():
-            polygon = row['geometry']
-            location_name = row.get('name', f"Polygon_{idx}")
+    for idx, row in polygons_df.iterrows():
+        polygon = row['geometry']
+        location_name = row.get('name', f"Polygon_{idx}")
 
-            try:
-                roi = convert_to_ee_geometry(polygon)
-            except ValueError as e:
-                st.error(str(e))
-                continue
+        try:
+            roi = convert_to_ee_geometry(polygon)
+        except ValueError as e:
+            st.error(str(e))
+            continue
 
-            collection = ee.ImageCollection(sub_options[sub_selection]) \
-                .filterDate(ee.Date(start_date_str), ee.Date(end_date_str)) \
-                .filterBounds(roi)
+        collection = ee.ImageCollection(sub_options[sub_selection]) \
+            .filterDate(ee.Date(start_date_str), ee.Date(end_date_str)) \
+            .filterBounds(roi)
 
-            image = get_most_recent_image(collection)
+        image = get_most_recent_image(collection)
 
-            if not image:
-                st.warning(f"No images found for {location_name}.")
-            else:
-                st.write(f"Found an image for {location_name}.")
-                result = None
-                if index_choice.lower() == 'ndvi':
-                    result = calculate_ndvi(image, roi)
-                elif index_choice.lower() == 'ndwi':
-                    result = calculate_ndwi(image, roi)
-                elif index_choice.lower() == 'average no₂':
-                    if 'NO2' in image.bandNames().getInfo():
-                        result = calculate_avg_no2_sentinel5p(image, roi)
-                    else:
-                        st.warning(f"No NO2 band found for {location_name}. Please use Sentinel-5P for NO₂ data.")
-                elif index_choice.lower() == 'custom formula' and custom_formula:
-                    result = process_custom_formula(image, roi, custom_formula)
+        if not image:
+            st.warning(f"No images found for {location_name}.")
+        else:
+            st.write(f"Found an image for {location_name}.")
+            result = None
+            if index_choice.lower() == 'ndvi':
+                result = calculate_ndvi(image, roi)
+            elif index_choice.lower() == 'ndwi':
+                result = calculate_ndwi(image, roi)
+            elif index_choice.lower() == 'average no₂':
+                if 'NO2' in image.bandNames().getInfo():
+                    result = calculate_avg_no2_sentinel5p(image, roi)
+                else:
+                    st.warning(f"No NO2 band found for {location_name}. Please use Sentinel-5P for NO₂ data.")
+            elif index_choice.lower() == 'custom formula' and custom_formula:
+                result = process_custom_formula(image, roi, custom_formula)
 
-                if result is not None:
-                    # Initialize the calculated_value as None
-                    calculated_value = None
+            if result is not None:
+                # Initialize the calculated_value as None
+                calculated_value = None
     
-                # Check if the result is a dictionary (e.g., custom formula result)
-                if isinstance(result, dict) and 'CustomResult' in result:
-                    calculated_value = result['CustomResult']  # Extract the numeric value from the dictionary
-                # If the result is a numeric value (e.g., NDVI, NDWI, or NO2)
-                elif isinstance(result, (int, float)):
-                    calculated_value = result
+            # Check if the result is a dictionary (e.g., custom formula result)
+            if isinstance(result, dict) and 'CustomResult' in result:
+                calculated_value = result['CustomResult']  # Extract the numeric value from the dictionary
+            # If the result is a numeric value (e.g., NDVI, NDWI, or NO2)
+            elif isinstance(result, (int, float)):
+                calculated_value = result
     
-                # If a valid calculated_value is found, append the result to session_state
-                if calculated_value is not None:
-                    st.session_state.results.append({
-                        'Location Name': location_name,
-                        'Calculated Value': calculated_value
-                    })
+            # If a valid calculated_value is found, append the result to session_state
+            if calculated_value is not None:
+                st.session_state.results.append({
+                    'Location Name': location_name,
+                    'Calculated Value': calculated_value
+                })
 
 # After processing, show the results
 if st.session_state.results: