Dear all,
I am trying out some new preprocessing tricks recommended by some
collaborators, which involves bandstop filtering my data to the frequencies
of electrical artifact (60, 120, 180 Hz, etc), and subtracting the
resulting time courses from the true data. (Their claim is that this
preserves coherence.) To do so, I have been trying the RawArray function,
but am having trouble passing it an Info instance. Even using the following
code produces the error reproduced below. This is surprising, as I'm only
translating an instance of raw to a PANDAS dataframe, and then a Numpy
array. Any advice?
raw = mne.io.Raw('some_data.fif', preload=True)
raw_df = raw.as_data_frame()
raw_mat = raw_df.as_matrix()
new_raw = mne.io.RawArray(raw_mat, raw.info)
ValueError Traceback (most recent call
last)<ipython-input-162-10b3fdc10c23> in <module>() 1 raw_mat =
raw.as_data_frame() 2 raw_mat = raw_mat.as_matrix()----> 3
new_raw = mne.io.RawArray(raw_mat, raw.info)
/mne/io/array/array.pyc in __init__(self, data, info, verbose)
/mne/utils.pyc in verbose(function, *args, **kwargs) 549
return ret 550 else:--> 551 ret = function(*args,
**kwargs) 552 return ret 553
/usr/pubsw/packages/python/anaconda/lib/python2.7/site-packages/mne/io/array/array.pyc
in __init__(self, data, info, verbose) 39 40 if
len(data) != len(info['ch_names']):---> 41 raise
ValueError('len(data) does not match len(info["ch_names"])') 42
assert len(info['ch_names']) == info['nchan'] 43
ValueError: len(data) does not match len(info["ch_names"])
Best,
Sam Zorowitz
Clinical Research Coordinator
Department of Psychiatry: Neurosciences
Division of Neurotherapeutics
Massachusetts General Hospital
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