# TSU-WAVE CHI Model
import numpy as np

def predict_chi(wcc, kpr, hfsi, becf, sdb, sbsp, smvi):
    """Simple CHI prediction model"""
    weights = {
        'wcc': 0.12, 'kpr': 0.19, 'hfsi': 0.24,
        'becf': 0.21, 'sdb': 0.08, 'sbsp': 0.11, 'smvi': 0.05
    }
    
    # Normalize parameters (simplified)
    params = {
        'wcc': min(wcc/1.58, 1.0),
        'kpr': min(kpr/2.0, 1.0),
        'hfsi': 1 - min(hfsi/1.0, 1.0),
        'becf': min(becf/6.0, 1.0),
        'sdb': 1 - min(sdb/3.5, 1.0),
        'sbsp': min(sbsp/1.2, 1.0),
        'smvi': min(smvi/0.6, 1.0)
    }
    
    chi = sum(weights[p] * params[p] for p in weights)
    return chi

if __name__ == '__main__':
    # Tōhoku 2011 example
    chi = predict_chi(1.56, 1.89, 0.31, 7.3, 0.8, 1.18, 0.38)
    print(f'CHI: {chi:.3f}')