Code Editor for app.py

import streamlit as st
import numpy as np
import pandas as pd

st.title('Facility Location Optimization')

st.write('This application helps you optimize the location of facilities based on given coordinates.')

# Input for number of facilities
#num_facilities = st.number_input('Enter the number of facilities:', min_value=1, max_value=10)

import streamlit as st
import numpy as np
import pandas as pd

st.title('Facility Location Optimization')

st.write('This application helps you optimize the location of facilities based on given coordinates.')

# Input for number of facilities
num_facilities = st.number_input('Enter the number of facilities:', min_value=1, max_value=10)

# Add a button to generate random coordinates
if st.button('Generate Random Coordinates'):
    # Generate random coordinates between 0 and 100 for example
    coordinates = []
    for i in range(num_facilities):
        x = np.random.uniform(0, 100)  # Random x between 0 and 100
        y = np.random.uniform(0, 100)  # Random y between 0 and 100
        coordinates.append((x, y))
    
    # Display the random coordinates
    st.write('Generated Coordinates:')
    for i, (x, y) in enumerate(coordinates):
        st.write(f'Facility {i+1}: ({x:.2f}, {y:.2f})')
    
    # Calculate optimal location
    optimal_x = np.mean([coord[0] for coord in coordinates])
    optimal_y = np.mean([coord[1] for coord in coordinates])
    st.success(f'Optimal Location is at: ({optimal_x:.2f}, {optimal_y:.2f})')

# Keep the manual input option
st.write('Or enter coordinates manually:')
manual_coordinates = []
for i in range(num_facilities):
    st.subheader(f'Facility {i+1} Coordinates')
    x = st.number_input(f'X-coordinate for Facility {i+1}', key=f'fac_x_{i}')
    y = st.number_input(f'Y-coordinate for Facility {i+1}', key=f'fac_y_{i}')
    manual_coordinates.append((x, y))

# Button for calculating optimal location with manual coordinates
if st.button('Calculate Optimal Location (Manual)'):
    optimal_x = np.mean([coord[0] for coord in manual_coordinates])
    optimal_y = np.mean([coord[1] for coord in manual_coordinates])
    st.success(f'Optimal Location is at: ({optimal_x}, {optimal_y})')