update app.py

app.py

@@ -106,7 +106,7 @@ def convert_to_ee_geometry(geometry):
     else:
         raise ValueError("Unsupported geometry input type. Supported types are Shapely, GeoJSON, and KML.")
 
-# Function to calculate custom formula with dynamic scale handling and normalization
+# Function to calculate custom formula with dynamic scale handling
 def calculate_custom_formula(image, geometry, selected_bands, custom_formula, reducer_choice, dataset_id, user_scale=None):
     try:
         # Fetch the nominal scales of the selected bands
@@ -446,7 +446,9 @@ elif imagery_base == "Custom Input":
             if custom_dataset_id.startswith("ee.ImageCollection("):
                 custom_dataset_id = custom_dataset_id.replace("ee.ImageCollection('", "").replace("')", "")
             collection = ee.ImageCollection(custom_dataset_id)
-            band_names = collection.first().bandNames().getInfo()
+            first_image = collection.first()
+            default_scale = first_image.projection().nominalScale().getInfo()
+            band_names = first_image.bandNames().getInfo()
             data = {
                 f"Custom Dataset: {custom_dataset_id}": {
                     "sub_options": {custom_dataset_id: f"Custom Dataset ({custom_dataset_id})"},
@@ -454,6 +456,7 @@ elif imagery_base == "Custom Input":
                 }
             }
             st.write(f"Fetched bands for {custom_dataset_id}: {', '.join(band_names)}")
+            st.write(f"Default Scale for Dataset: {default_scale} meters")
         except Exception as e:
             st.error(f"Error fetching dataset: {str(e)}. Please check the dataset ID and ensure it's valid in Google Earth Engine.")
             data = {}
@@ -463,6 +466,7 @@ elif imagery_base == "Custom Input":
 if not data:
     st.error("No valid dataset available. Please check your inputs.")
     st.stop()
+
 st.markdown("<hr><h5><b>{}</b></h5>".format(imagery_base), unsafe_allow_html=True)
 main_selection = st.selectbox(f"Select {imagery_base} Dataset Category", list(data.keys()))
 sub_selection = None
@@ -474,6 +478,16 @@ if main_selection:
         st.write(f"You selected: {main_selection} -> {sub_options[sub_selection]}")
         st.write(f"Dataset ID: {sub_selection}")
         dataset_id = sub_selection
+
+        # Print default scale for the selected dataset
+        try:
+            collection = ee.ImageCollection(dataset_id)
+            first_image = collection.first()
+            default_scale = first_image.projection().nominalScale().getInfo()
+            st.write(f"Default Scale for Selected Dataset: {default_scale} meters")
+        except Exception as e:
+            st.error(f"Error fetching default scale: {str(e)}")
+
 st.markdown("<hr><h5><b>Earth Engine Index Calculator</b></h5>", unsafe_allow_html=True)
 if main_selection and sub_selection:
     dataset_bands = data[main_selection]["bands"].get(sub_selection, [])
@@ -516,6 +530,7 @@ if main_selection and sub_selection:
             st.warning("Please enter a custom formula to proceed.")
             st.stop()
         st.write(f"Custom Formula: {custom_formula}")
+        
 reducer_choice = st.selectbox(
     "Select Reducer (e.g, mean , sum , median , min , max , count)",
     ['mean', 'sum', 'median', 'min', 'max', 'count'],
@@ -572,6 +587,7 @@ user_scale = st.number_input(
     value=float(default_scale),
     help=f"Default scale for this dataset is {default_scale} meters. Adjust if needed."
 )
+
 file_upload = st.file_uploader(f"Upload your {shape_type} data (CSV, GeoJSON, KML)", type=["csv", "geojson", "kml"])
 locations_df = pd.DataFrame()
 original_lat_col = None