def testcase(self, dur=3, fs=100, blksize=10):
    '[summary]\n\n        Args:\n            dur (int, optional): [description]. Defaults to 3.\n            fs (int, optional): [description]. Defaults to 100.\n            blksize (int, optional): [description]. Defaults to 10.\n        '
    import numpy as np
    import matplotlib.pyplot as plt
    from mindaffectBCI.decoder.preprocess import plot_grand_average_spectrum
    fs = 100
    X = np.random.standard_normal((2, (fs * dur), 2))
    X = (X[:, :(- 1), :] + X[:, 1:, :])
    print('X={}'.format(X.shape))
    plt.figure(1)
    plot_grand_average_spectrum(X, fs)
    plt.suptitle('Raw')
    plt.show(block=False)
    tdc = temporal_decorrelator()
    wX = np.zeros(X.shape, X.dtype)
    for i in range(0, X.shape[(- 1)], blksize):
        idx = range(i, (i + blksize))
        wX[idx, :] = tdc.transform(X[idx, :])
    plt.figure(2)
    plot_grand_average_spectrum(wX, fs)
    plt.suptitle('Decorrelated')
    plt.show()
[summary]

Args:
    dur (int, optional): [description]. Defaults to 3.
    fs (int, optional): [description]. Defaults to 100.
    blksize (int, optional): [description]. Defaults to 10.
def testcase(self, dur=3, fs=100, blksize=10):
    '[summary]\n\n        Args:\n            dur (int, optional): [description]. Defaults to 3.\n            fs (int, optional): [description]. Defaults to 100.\n            blksize (int, optional): [description]. Defaults to 10.\n        '
    import numpy as np
    import matplotlib.pyplot as plt
    from mindaffectBCI.decoder.preprocess import plot_grand_average_spectrum
    fs = 100
    X = np.random.standard_normal((2, (fs * dur), 2))
    X = (X[:, :(- 1), :] + X[:, 1:, :])
    print('X={}'.format(X.shape))
    plt.figure(1)
    plot_grand_average_spectrum(X, fs)
    plt.suptitle('Raw')
    plt.show(block=False)
    tdc = temporal_decorrelator()
    wX = np.zeros(X.shape, X.dtype)
    for i in range(0, X.shape[(- 1)], blksize):
        idx = range(i, (i + blksize))
        wX[idx, :] = tdc.transform(X[idx, :])
    plt.figure(2)
    plot_grand_average_spectrum(wX, fs)
    plt.suptitle('Decorrelated')
    plt.show()