def test_notch_filters():
    """Test notch filters
    """
    # let's use an ugly, prime sfreq for fun
    sfreq = 487.0
    sig_len_secs = 20
    t = np.arange(0, int(sig_len_secs * sfreq)) / sfreq
    freqs = np.arange(60, 241, 60)

    # make a "signal"
    a = rng.randn(int(sig_len_secs * sfreq))
    orig_power = np.sqrt(np.mean(a ** 2))
    # make line noise
    a += np.sum([np.sin(2 * np.pi * f * t) for f in freqs], axis=0)

    # only allow None line_freqs with 'spectrum_fit' mode
    assert_raises(ValueError, notch_filter, a, sfreq, None, 'fft')
    assert_raises(ValueError, notch_filter, a, sfreq, None, 'iir')
    methods = ['spectrum_fit', 'spectrum_fit', 'fft', 'fft', 'iir']
    filter_lengths = [None, None, None, 8192, None]
    line_freqs = [None, freqs, freqs, freqs, freqs]
    tols = [2, 1, 1, 1]
    for meth, lf, fl, tol in zip(methods, line_freqs, filter_lengths, tols):
        with catch_logging() as log_file:
            b = notch_filter(a, sfreq, lf, filter_length=fl, method=meth,
                             verbose='INFO')

        if lf is None:
            out = log_file.getvalue().split('\n')[:-1]
            if len(out) != 2 and len(out) != 3:  # force_serial: len(out) == 3
                raise ValueError('Detected frequencies not logged properly')
            out = np.fromstring(out[-1], sep=', ')
            assert_array_almost_equal(out, freqs)
        new_power = np.sqrt(b.size / sum_squared(b))
        assert_almost_equal(new_power, orig_power, tol)
dataset/ETHPy150Open mne-tools/mne-python/mne/tests/test_filter.py/test_notch_filters/swapped operands of `/`