Update app.py
Browse files
app.py
CHANGED
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@@ -1,53 +1,53 @@
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import streamlit as st
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import h5py
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import numpy as np
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import pandas as pd
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import plotly.express as px
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import os
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filename = r'
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@st.cache_data
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def load_h5_data(filename):
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if not os.path.isfile(filename):
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raise FileNotFoundError(f"File not found: {filename}")
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with h5py.File(filename, 'r') as h5:
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soil_moisture = h5['Analysis_Data/sm_surface_analysis'][:]
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lat = h5['cell_lat'][:]
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lon = h5['cell_lon'][:]
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return lat, lon, soil_moisture
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try:
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lat, lon, soil_moisture = load_h5_data(filename)
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df = pd.DataFrame({
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'Latitude': lat.flatten(),
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'Longitude': lon.flatten(),
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'Soil Moisture': soil_moisture.flatten()
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})
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st.title("Soil Moisture Data Dashboard")
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st.write("This dashboard displays soil moisture levels based on latitude and longitude.")
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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())))
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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())))
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filtered_data = df[(df['Latitude'] >= min_lat) & (df['Latitude'] <= max_lat) & (df['Longitude'] >= min_lon) & (df['Longitude'] <= max_lon)]
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st.write(f"Displaying data for Latitude between {min_lat} and {max_lat} and Longitude between {min_lon} and {max_lon}")
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st.dataframe(filtered_data)
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if not filtered_data.empty:
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fig = px.scatter_mapbox(filtered_data, lat='Latitude', lon='Longitude', color='Soil Moisture',
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color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=3)
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fig.update_layout(mapbox_style="open-street-map")
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fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
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st.plotly_chart(fig)
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else:
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st.write("No data available in the selected range.")
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except FileNotFoundError as e:
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st.error(str(e))
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except Exception as e:
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st.error(f"An error occurred: {str(e)}")
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import streamlit as st
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import h5py
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import numpy as np
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import pandas as pd
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import plotly.express as px
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import os
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filename = r'Reduced_SMAP_L4_SM_aup.h5'
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@st.cache_data
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def load_h5_data(filename):
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if not os.path.isfile(filename):
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raise FileNotFoundError(f"File not found: {filename}")
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with h5py.File(filename, 'r') as h5:
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soil_moisture = h5['Analysis_Data/sm_surface_analysis'][:]
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lat = h5['cell_lat'][:]
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lon = h5['cell_lon'][:]
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return lat, lon, soil_moisture
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try:
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lat, lon, soil_moisture = load_h5_data(filename)
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df = pd.DataFrame({
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'Latitude': lat.flatten(),
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'Longitude': lon.flatten(),
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'Soil Moisture': soil_moisture.flatten()
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})
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st.title("Soil Moisture Data Dashboard")
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st.write("This dashboard displays soil moisture levels based on latitude and longitude.")
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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())))
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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())))
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filtered_data = df[(df['Latitude'] >= min_lat) & (df['Latitude'] <= max_lat) & (df['Longitude'] >= min_lon) & (df['Longitude'] <= max_lon)]
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st.write(f"Displaying data for Latitude between {min_lat} and {max_lat} and Longitude between {min_lon} and {max_lon}")
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st.dataframe(filtered_data)
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if not filtered_data.empty:
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fig = px.scatter_mapbox(filtered_data, lat='Latitude', lon='Longitude', color='Soil Moisture',
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color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=3)
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fig.update_layout(mapbox_style="open-street-map")
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fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
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st.plotly_chart(fig)
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else:
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st.write("No data available in the selected range.")
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except FileNotFoundError as e:
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st.error(str(e))
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except Exception as e:
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st.error(f"An error occurred: {str(e)}")
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