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compute_mca.py 698 B
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  • import numpy as np
    from supersvd import supersvd
    import matplotlib.pyplot as plt
    
    ts = np.fromfile('ts.std', dtype=np.float32).reshape(1147, 28, 31)
    ps = np.fromfile('ps.std', dtype=np.float32).reshape(1147, 28, 31)
    
    
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    w = np.zeros((28, 31), dtype=np.float32)
    lat = np.deg2rad(35 + 1.5 * np.arange(31))
    w[:, :] = np.cos(lat).reshape(1, -1)
    
    svd = supersvd(ts, ps, 4, WX=w, WY=w)
    
    
    first_mode_ts = svd.x_vect[0]
    
    plt.matshow(first_mode_ts)
    plt.savefig('first_mode_ts.png')
    
    first_ps_timeseries = svd.x_coeff[0]
    
    plt.figure()
    plt.plot(first_ps_timeseries)
    plt.savefig('first_ps_timeseries.png')
    
    
    print('Correlation coefficient between first_ts_timeseries and first_ps_timeseries:', svd.corrcoeff[0])