def test_find_bad_by_ransac(raw=raw):
"""Test find_bad_by_ransac."""
# For now, simply see if it runs
# Need better data to test properly
nd = Noisydata(raw)
nd.find_all_bads(ransac=True) # equivalent to nd.find_bad_by_ransac()
bads = nd.bad_by_ransac
assert (bads == []) or (len(bads) > 0)
def test_get_bads(raw=raw):
"""Find all bads and then get them."""
# Make sure that in the example, none are bad per se.
nd = Noisydata(raw)
# Do not test ransac yet ... need better data to confirm
nd.find_all_bads(ransac=False)
bads = nd.get_bads(verbose=True) # also test the printout
assert bads == []
ch_types=["eeg"] * n_chans) time = np.arange(0, 60, 1.0 / sfreq) # 60 seconds of recording X = np.random.random((n_chans, time.shape[0])) raw = mne.io.RawArray(X, info) print(raw) ############################################################################### # Assign the mne object to the :class:`Noisydata` class. The resulting object # will be the place where all following methods are performed. nd = Noisydata(raw) ############################################################################### # Find all bad channels and print a summary nd.find_all_bads(ransac=False) bads = nd.get_bads(verbose=True) ############################################################################### # Now the bad channels are saved in `bads` and we can continue processing our # `raw` object. For more information, we can access attributes of the ``nd`` # instance: # Check the high frequency noise per channel print(nd._channel_hf_noise) # and so on ... ############################################################################### # For finding bad epochs, it is recommended to highpass the data or apply # baseline correction. Furthermore, bad channels should be identified and
def get_bad_channels(self, rawData, sfreq=128, n_chans=14):
nd = Noisydata(rawData)
nd.find_all_bads(ransac=False)
bads = nd.get_bads(verbose=False)
return bads
def get_bad_channels(self,rawData,sfreq = 128,n_chans = 14):
nd = Noisydata(rawData)
nd.find_all_bads(ransac=False)
bads = nd.get_bads(verbose=False)
return bads