visual

import streamlit as st
import matplotlib.pyplot as plt

# Title and description
st.title('EarthCosmos Predict')
st.write('An integrated system for predicting earthquakes and cosmic weather events.')

# Sidebar for user input
st.sidebar.header('Input Parameters')
solar_flare_input = st.sidebar.slider('Solar Flare Intensity', 0.0, 10.0, 5.0)
geomagnetic_input = st.sidebar.slider('Geomagnetic Index', 0.0, 100.0, 50.0)
cosmic_ray_input = st.sidebar.slider('Cosmic Ray Flux', 0.0, 1000.0, 500.0)

# Predict with the models
input_data = np.array([[solar_flare_input, geomagnetic_input, cosmic_ray_input]])
pca_input = pca.transform(input_data)
earthquake_prediction = earthquake_model.predict(pca_input)
cosmic_weather_prediction = cosmic_weather_model.predict(pca_input)

# Display predictions
st.write(f'Predicted Earthquake Magnitude: {earthquake_prediction[0]:.2f}')
st.write(f'Predicted Geomagnetic Index: {cosmic_weather_prediction[0]:.2f}')

# Visualizing the data
fig, ax = plt.subplots()
ax.plot(combined_data['timestamp'], combined_data['magnitude'], label='Actual Magnitude')
ax.plot(combined_data['timestamp'][:len(y_earthquake_pred)], y_earthquake_pred, label='Predicted Magnitude', linestyle='--')
ax.set_xlabel('Timestamp')
ax.set_ylabel('Earthquake Magnitude')
ax.legend()
st.pyplot(fig)