Upload app.py

app.py

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+import streamlit as st
+import h5py
+import numpy as np
+import pandas as pd
+import plotly.express as px
+import os
+
+filename = r'C:\\Users\\Lenovo\\Desktop\\Machine-Learning\\Soil Moisture\\Reduced_SMAP_L4_SM_aup.h5'
+
+@st.cache_data
+def load_h5_data(filename):
+    if not os.path.isfile(filename):
+        raise FileNotFoundError(f"File not found: {filename}")
+    
+    with h5py.File(filename, 'r') as h5:
+        soil_moisture = h5['Analysis_Data/sm_surface_analysis'][:]
+        lat = h5['cell_lat'][:]
+        lon = h5['cell_lon'][:]
+        return lat, lon, soil_moisture
+
+try:
+    lat, lon, soil_moisture = load_h5_data(filename)
+    
+    df = pd.DataFrame({
+        'Latitude': lat.flatten(),
+        'Longitude': lon.flatten(),
+        'Soil Moisture': soil_moisture.flatten()
+    })
+    
+    st.title("Soil Moisture Data Dashboard")
+    st.write("This dashboard displays soil moisture levels based on latitude and longitude.")
+    
+    min_lat, max_lat = st.slider("Select Latitude Range", float(df['Latitude'].min()), float(df['Latitude'].max()), (float(df['Latitude'].min()), float(df['Latitude'].max())))
+    min_lon, max_lon = st.slider("Select Longitude Range", float(df['Longitude'].min()), float(df['Longitude'].max()), (float(df['Longitude'].min()), float(df['Longitude'].max())))
+    
+    filtered_data = df[(df['Latitude'] >= min_lat) & (df['Latitude'] <= max_lat) & (df['Longitude'] >= min_lon) & (df['Longitude'] <= max_lon)]
+    
+    st.write(f"Displaying data for Latitude between {min_lat} and {max_lat} and Longitude between {min_lon} and {max_lon}")
+    st.dataframe(filtered_data)
+    
+    if not filtered_data.empty:
+        fig = px.scatter_mapbox(filtered_data, lat='Latitude', lon='Longitude', color='Soil Moisture',
+                                color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=3)
+        fig.update_layout(mapbox_style="open-street-map")
+        fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
+        st.plotly_chart(fig)
+    else:
+        st.write("No data available in the selected range.")
+    
+except FileNotFoundError as e:
+    st.error(str(e))
+except Exception as e:
+    st.error(f"An error occurred: {str(e)}")