a166085a7f9965a96012b4907419053a660ab9a4,nisl/signals.py,,clean,#Any#Any#Any#Any#Any#Any#Any#Any#,26

Before Change

        n = signals.shape[-1]
        freq = fftpack.fftfreq(n, d=t_r)
        for s in signals:
            fft = fftpack.fft(s)
            if low_pass:
                fft[np.abs(freq) > low_pass] = 0
            if high_pass:
                fft[np.abs(freq) < high_pass] = 0
            s[:] = fftpack.ifft(fft)

    if detrend:
        // This is faster than scipy.detrend and equivalent
        regressor = np.arange(signals.shape[1]).astype(np.float)

After Change

                         " would result in a blank signal"
                         % (high_pass, low_pass))

    if low_pass is not None or high_pass is not None:
        for s in signals:
            s[:] = butterworth(s, sampling_rate=1. / t_r,
                               low_pass=low_pass, high_pass=high_pass)

    if detrend:
        // This is faster than scipy.detrend and equivalent
        regressor = np.arange(signals.shape[1]).astype(np.float)
        regressor -= regressor.mean()

Instances