update app.py

app.py

@@ -34,18 +34,11 @@ st.write(
     """,
     unsafe_allow_html=True,
 )
-# Initialize session state for storing results if not already done
-if 'results' not in st.session_state:
-    st.session_state.results = []
-if 'last_params' not in st.session_state:
-    st.session_state.last_params = {}
-if 'map_data' not in st.session_state:
-    st.session_state.map_data = None  # Initialize map_data
 
-# Initialize Earth Engine with secret credentials
+# Authenticate and initialize Earth Engine
 earthengine_credentials = os.environ.get("EE_Authentication")
 
-# Initialize Earth Engine with credentials
+# Initialize Earth Engine with secret credentials
 os.makedirs(os.path.expanduser("~/.config/earthengine/"), exist_ok=True)
 with open(os.path.expanduser("~/.config/earthengine/credentials"), "w") as f:
     f.write(earthengine_credentials)
@@ -101,35 +94,6 @@ def read_kml(file_path):
     gdf = gpd.read_file(file_path, driver='KML')
     return gdf
 
-# Function to standardize column names
-def standardize_column_names(df):
-    # Define a mapping of common variations to standardized column names
-    column_mapping = {
-        'latitude': ['latitude', 'lat', 'Latitude', 'Lat'],
-        'longitude': ['longitude', 'lon', 'Longitude', 'Lon'],
-        'name': ['name', 'Name']
-    }
-    
-    # Normalize column names
-    df.columns = [col.strip().lower() for col in df.columns]  # Convert all column names to lowercase and strip any extra spaces
-    
-    # Rename columns based on the mapping
-    for standard_col, variations in column_mapping.items():
-        for variation in variations:
-            if variation.lower() in df.columns:
-                df = df.rename(columns={variation.lower(): standard_col})
-                break
-    
-    return df
-
-# Function to sanitize descriptions (location names)
-def sanitize_description(description):
-    # Replace spaces and other invalid characters with underscores
-    sanitized = re.sub(r'[^a-zA-Z0-9._-]', '_', description)
-    # Ensure the description is no longer than 100 characters
-    sanitized = sanitized[:100]
-    return sanitized
-
 # Ask user whether they want to process 'Point' or 'Polygon' data
 shape_type = st.selectbox("Do you want to process 'Point' or 'Polygon' data?", ["Point", "Polygon"])
 
@@ -144,13 +108,13 @@ end_date = st.date_input("End Date", value=pd.to_datetime('2020-12-31'))
 start_date_str = start_date.strftime('%Y-%m-%d')
 end_date_str = end_date.strftime('%Y-%m-%d')
 
-# # Initialize session state for storing results if not already done
-# if 'results' not in st.session_state:
-#     st.session_state.results = []
-# if 'last_params' not in st.session_state:
-#     st.session_state.last_params = {}
-# if 'map_data' not in st.session_state:
-#     st.session_state.map_data = None  # Initialize map_data
+# Initialize session state for storing results if not already done
+if 'results' not in st.session_state:
+    st.session_state.results = []
+if 'last_params' not in st.session_state:
+    st.session_state.last_params = {}
+if 'map_data' not in st.session_state:
+    st.session_state.map_data = None  # Initialize map_data
 
 # Function to check if parameters have changed
 def parameters_changed():
@@ -209,6 +173,14 @@ def calculate_custom_formula(image, geometry, formula):
     )
     return result.get('Custom Index')
 
+# Function to sanitize the description for export
+def sanitize_description(description):
+    # Replace spaces and other invalid characters with underscores
+    sanitized = re.sub(r'[^a-zA-Z0-9._-]', '_', description)
+    # Ensure the description is no longer than 100 characters
+    sanitized = sanitized[:100]
+    return sanitized
+
 # Process each point
 if file_upload:
     locations_df = None  # Initialize locations_df to None
@@ -235,9 +207,6 @@ if file_upload:
             st.error("Unsupported file type. Please upload a GeoJSON or KML file for polygons.")
 
     if locations_df is not None:
-        # Standardize column names for consistency
-        locations_df = standardize_column_names(locations_df)
-
         # Display a preview of the points data
         st.write("Preview of the uploaded points data:")
         st.dataframe(locations_df.head())
@@ -353,3 +322,20 @@ if file_upload:
                 data=export_image.getDownloadURL(),
                 file_name=f'{sanitized_location_name}_image.tif'
             )
+
+# After processing, show the results
+if st.session_state.results:
+    # Convert the results to a DataFrame for better visualization
+    result_df = pd.DataFrame(st.session_state.results)
+
+    # Show the results in a table format
+    st.write("Processed Results Table:")
+    st.dataframe(result_df[['Location Name', 'Latitude', 'Longitude', 'Calculated Value']])
+
+    # Allow downloading of the results as CSV
+    st.download_button(
+        label="Download results as CSV",
+        data=result_df.to_csv(index=False).encode('utf-8'),
+        file_name="calculated_results.csv",
+        mime='text/csv'
+    )