# predict_location.py
import subprocess
import joblib
import pandas as pd

# Function to scan Wi-Fi networks (same as in wifi_scan.py)
def get_wifi_signal():
    scan_output = subprocess.check_output(['sudo', 'iwlist', 'wlan0', 'scan']).decode('utf-8')
    return scan_output

# Function to parse signal strength from scan output
def parse_signal_strength(scan_output):
    signal_strengths = []
    for line in scan_output.split('\n'):
        if "Signal level=" in line:
            strength = line.split("Signal level=")[1].split(" ")[0]
            signal_strengths.append(int(strength))
    return signal_strengths

# Load the pre-trained model
model = joblib.load('wifi_model.pkl')

# Predict the location based on real-time signal strengths
def predict_location():
    scan_output = get_wifi_signal()
    signal_strengths = parse_signal_strength(scan_output)

    # Prepare the input as a DataFrame with the correct feature name
    for strength in signal_strengths:
        data = pd.DataFrame([[strength]], columns=['SignalStrength'])  # Use the feature name 'SignalStrength'
        predicted_location = model.predict(data)
        print(f'Predicted Location: {predicted_location[0]}')

# Run the prediction
predict_location()