update app.py

app.py

@@ -4,6 +4,7 @@ import json
 import ee
 import os
 import pandas as pd
+import numpy as np
 import geopandas as gpd
 from datetime import datetime
 import leafmap.foliumap as leafmap
@@ -521,6 +522,46 @@ st.markdown("<hr><h5><b>Earth Engine Index Calculator</b></h5>", unsafe_allow_ht
 if main_selection and sub_selection:
     dataset_bands = data[main_selection]["bands"].get(sub_selection, [])
     st.write(f"Available Bands for {sub_options[sub_selection]}: {', '.join(dataset_bands)}")
+    
+
+    # Fetch nominal scales for all bands in the selected dataset
+    if dataset_id:
+        try:
+            # Fetch the first image from the collection to extract band information
+            collection = ee.ImageCollection(dataset_id)
+            first_image = collection.first()
+            band_names = first_image.bandNames().getInfo()
+    
+            # Extract scales for all bands
+            band_scales = []
+            for band in band_names:
+                band_scale = first_image.select(band).projection().nominalScale().getInfo()
+                band_scales.append(band_scale)
+    
+            # Identify unique scales using np.unique
+            unique_scales = np.unique(band_scales)
+    
+            # Display the unique scales to the user
+            st.write(f"Nominal Scales for Bands: {band_scales}")
+            st.write(f"Unique Scales in Dataset: {unique_scales}")
+    
+            # If there are multiple unique scales, allow the user to choose one
+            if len(unique_scales) > 1:
+                selected_scale = st.selectbox(
+                    "Select a Scale for Calculation (meters)",
+                    options=unique_scales,
+                    index=0,
+                    help="Choose a scale from the unique scales available in the dataset."
+                )
+                default_scale = selected_scale
+            else:
+                default_scale = unique_scales[0]
+                st.write(f"Default Scale for Dataset: {default_scale} meters")
+    
+        except Exception as e:
+            st.error(f"Error fetching band scales: {str(e)}")
+            default_scale = 30  # Fallback to 30 meters if an error occurs
+        
     selected_bands = st.multiselect(
         "Select 1 or 2 Bands for Calculation",
         options=dataset_bands,
@@ -614,8 +655,16 @@ elif shape_type.lower() == "polygon":
         help="Check to include pixels on the polygon boundary; uncheck to exclude them."
     )
 
+# st.markdown("<h5>Calculation Scale</h5>", unsafe_allow_html=True)
+# default_scale = ee.ImageCollection(dataset_id).first().select(0).projection().nominalScale().getInfo()
+# user_scale = st.number_input(
+#     "Enter Calculation Scale (meters) [Leave blank to use dataset's default scale]",
+#     min_value=1.0,
+#     value=float(default_scale),
+#     help=f"Default scale for this dataset is {default_scale} meters. Adjust if needed."
+# )
+
 st.markdown("<h5>Calculation Scale</h5>", unsafe_allow_html=True)
-default_scale = ee.ImageCollection(dataset_id).first().select(0).projection().nominalScale().getInfo()
 user_scale = st.number_input(
     "Enter Calculation Scale (meters) [Leave blank to use dataset's default scale]",
     min_value=1.0,