import streamlit as st
import pandas as pd
import numpy as np
from geopy.distance import geodesic

# Create a DataFrame with sample data
data = pd.DataFrame({
    'lat': np.random.uniform(-90, 90, 1000),
    'lon': np.random.uniform(-180, 180, 1000),
    'value': np.random.rand(1000) * 100
})

# Function to calculate distance in meters between two coordinates
def calculate_distance(lat1, lon1, lat2, lon2):
    coords_1 = (lat1, lon1)
    coords_2 = (lat2, lon2)
    return geodesic(coords_1, coords_2).meters

# Display a title
st.title('Geospatial Dashboard')

# Dropdown to select specific coordinates
selected_coords = st.selectbox('Select Coordinates', ['Random', 'Custom'])
if selected_coords == 'Custom':
    custom_lat = st.number_input('Enter Latitude', value=0.0)
    custom_lon = st.number_input('Enter Longitude', value=0.0)
else:
    custom_lat, custom_lon = 0.0, 0.0

# Slider for setting the zoom level
zoom_level = st.slider('Zoom Level', min_value=1, max_value=15, value=5)

# Slider to set the radius in meters
radius_in_meters = st.slider('Select Radius (in meters)', min_value=100, max_value=5000, value=1000)

# Filter data based on the radius
if selected_coords == 'Custom':
    filtered_data = data[data.apply(lambda x: calculate_distance(x['lat'], x['lon'], custom_lat, custom_lon), axis=1) <= radius_in_meters]
    st.map(filtered_data, zoom=zoom_level, use_container_width=True)
else:
    st.map(data, zoom=zoom_level, use_container_width=True)