"""
Advanced Time Series Example

Author: RSK World
Website: https://rskworld.in
Email: help@rskworld.in
Phone: +91 93305 39277
"""

import numpy as np
import pandas as pd
import sys
import os

# Add parent directory to path
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from advanced_time_series import SARIMAModel, AutoARIMA, StationarityTests


def main():
    print("Advanced Time Series Example")
    print("=" * 70)
    
    # Generate sample seasonal data
    np.random.seed(42)
    dates = pd.date_range('2020-01-01', periods=200, freq='D')
    trend = np.linspace(0, 10, 200)
    seasonal = 5 * np.sin(2 * np.pi * np.arange(200) / 30)  # Monthly seasonality
    noise = np.random.randn(200) * 0.5
    data = pd.Series(trend + seasonal + noise, index=dates)
    
    # SARIMA model
    print("\nSARIMA Model:")
    print("=" * 70)
    sarima = SARIMAModel()
    sarima.fit(data, order=(1, 1, 1), seasonal_order=(1, 1, 1, 30))
    sarima.summary()
    
    # Auto ARIMA
    print("\n" + "=" * 70)
    print("Auto ARIMA Selection:")
    print("=" * 70)
    auto_arima = AutoARIMA()
    best_model = auto_arima.auto_select(data, max_p=2, max_d=1, max_q=2, seasonal=False)
    
    # Stationarity tests
    print("\n" + "=" * 70)
    print("Stationarity Tests:")
    print("=" * 70)
    StationarityTests.comprehensive_test(data)


if __name__ == "__main__":
    main()