Update app.py

app.py

@@ -1,5 +1,9 @@
 # -*- coding: utf-8 -*-
-"""app.ipynb"""
+"""app.ipynb
+Automatically generated by Colab.
+Original file is located at
+    https://colab.research.google.com/drive/1I5SzMTkFWVzSyzaZNkQcYqUi7F9Nzxpx
+"""
 
 import gradio as gr
 import xarray as xr
@@ -12,6 +16,7 @@ from datetime import datetime
 import fsspec
 
 # Filepath for NASA POWER data
+# FILEPATH = 'https://power-analysis-ready-datastore.s3.amazonaws.com/power_901_monthly_radiation_utc.zarr'
 FILEPATH = 'https://nasa-power.s3.amazonaws.com/syn1deg/temporal/power_syn1deg_monthly_temporal_lst.zarr'
 
 # Load dataset
@@ -67,34 +72,31 @@ def predict_forecast(lat, lon, start_date, end_date, forecast_steps):
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Gradio interface function
-def gradio_interface(location, start_date, end_date, forecast_steps):
-    if location is None or len(location) != 2:
-        return "Please select a location on the map.", None, None
-    lat, lon = location
+# Gradio app
+def gradio_interface(lat, lon, start_date, end_date, forecast_steps):
     result = predict_forecast(lat, lon, start_date, end_date, forecast_steps)
     if isinstance(result, dict):  # If successful
-        return f"RMSE: {result['RMSE']:.2f}", str(result["Forecast"]), result["Plot"]
+        return result["RMSE"], result["Forecast"], result["Plot"]
     else:  # If error
         return result, None, None
 
-# Gradio UI
 interface = gr.Interface(
     fn=gradio_interface,
     inputs=[
-        gr.Map(label="Select Location on Map"),
-        gr.Textbox(label="Start Date (YYYY-MM-DD)", value="2019-01-01"),
-        gr.Textbox(label="End Date (YYYY-MM-DD)", value="2024-12-31"),
-        gr.Number(label="Forecast Steps (e.g., 12 for 1 year)", value=12)
+        gr.Number(label="Latitude"),
+        gr.Number(label="Longitude"),
+        gr.Textbox(label="Start Date (YYYY-MM-DD)", placeholder="2019-01-01"),
+        gr.Textbox(label="End Date (YYYY-MM-DD)", placeholder="2024-12-31"),
+        gr.Number(label="Forecast Steps (e.g., 12 for 1 year)")
     ],
     outputs=[
         gr.Textbox(label="RMSE"),
         gr.Textbox(label="Forecast Values"),
         gr.Image(label="Forecast Plot")
     ],
-    title="🌞 Solar Radiation Forecast using SARIMA",
-    description="Click on the map to select a location, then enter a date range and forecast steps. The model will forecast solar radiation using SARIMA based on NASA POWER data."
+    title="Solar Radiation Forecast with SARIMA",
+    description="Enter location and time range to forecast solar radiation using SARIMA."
 )
 
 # Launch the app
-interface.launch()
+interface.launch()