"""
Time Series Analysis 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 time_series_analysis import TimeSeriesModel


def main():
    print("Time Series Analysis Example")
    print("=" * 70)
    
    # Generate sample time series data
    np.random.seed(42)
    dates = pd.date_range('2020-01-01', periods=100, freq='D')
    trend = np.linspace(0, 10, 100)
    seasonal = 2 * np.sin(2 * np.pi * np.arange(100) / 7)
    noise = np.random.randn(100) * 0.5
    data = pd.Series(trend + seasonal + noise, index=dates)
    
    # Create time series model
    ts_model = TimeSeriesModel()
    ts_model.data = data
    
    # Test stationarity
    print("\nStationarity Test:")
    print("=" * 70)
    ts_model.test_stationarity()
    
    # Fit ARIMA model
    print("\n" + "=" * 70)
    print("ARIMA Model:")
    print("=" * 70)
    ts_model.fit_arima(data, order=(1, 1, 1))
    ts_model.summary()
    
    # Check residuals
    print("\n" + "=" * 70)
    print("Residual Analysis:")
    print("=" * 70)
    ts_model.check_residuals()
    
    # Generate forecast
    print("\n" + "=" * 70)
    print("Forecast:")
    print("=" * 70)
    forecast, conf_int = ts_model.forecast(steps=10)
    print(f"Forecast values:\n{forecast}")
    print(f"\nConfidence intervals:\n{conf_int}")


if __name__ == "__main__":
    main()