Type Error in adaptation of example plot_source_space_time_frequency.py

✉️ Mailing List Archive (read-only)
1

Hi all,

I get the following error when I try the following using my constructed ROI labels : Any pointers would be much appreciated :slight_smile:

thanks// dave

script snippet:

print __doc__

import mne
from mne import fiff

from mne.minimum_norm import source_band_induced_power
epochs=mne.read_epochs(fname_epoched, proj= True)
bands = dict(theta= [3, 8], alpha=[9, 11], beta=[18, 22], gamma=[30, 80])

stcs = source_band_induced_power(epochs, label, inverse_operator, bands, n_cycles=2,
                                 use_fft=False, n_jobs=1)

for b, stc in stcs.iteritems():
    stc.save('induced_power_%s' % b)

2

hi David,

can you reproduce the problem with the sample data?
could you share a gist on https://gist.github.com/ ?

thanks
Alex

3

Hi David,

It seems to me that you get this error because you use lists for the
bands instead of arrays. Try to use

import numpy as np
bands = dict(theta=np.array([3, 8]), alpha=np.array([9, 11]),
             beta=np.array([18, 22]), gamma=np.array([30, 80]))

If this works we will also fix the code so that it works with lists.

Best,

Martin

4

will try am not quite sure how to proceed given that I am using my subject roi labels

hi David,

can you reproduce the problem with the sample data?
could you share a gist on https://gist.github.com/ ?

thanks
Alex

Hi all,

I get the following error when I try the following using my constructed ROI labels : Any pointers would be much appreciated :slight_smile:

thanks// dave

script snippet:

print __doc__

import mne
from mne import fiff

from mne.minimum_norm import source_band_induced_power
epochs=mne.read_epochs(fname_epoched, proj= True)
bands = dict(theta= [3, 8], alpha=[9, 11], beta=[18, 22], gamma=[30, 80])

stcs = source_band_induced_power(epochs, label, inverse_operator, bands, n_cycles=2,
                                use_fft=False, n_jobs=1)

for b, stc in stcs.iteritems():
   stc.save('induced_power_%s' % b)

###############################################################################
# plot mean power
import matplotlib.pyplot as plt
plt.plot(stcs['alpha'].times, stcs['alpha'].data.mean(axis=0), label='Alpha')
plt.plot(stcs['beta'].times, stcs['beta'].data.mean(axis=0), label='Beta')
plt.plot(stcs['beta'].times, stcs['beta'].data.mean(axis=0), label='Theta')
plt.plot(stcs['beta'].times, stcs['beta'].data.mean(axis=0), label='Gamma')
plt.xlabel('Time (ms)')
plt.ylabel('Power')
plt.legend()
plt.title('Mean source induced power')
plt.show()

error:

---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-11-2aeed705510d> in <module>()
     1 bands = dict(theta=[3, 8], alpha=[9, 11], beta=[18, 22], gamma=[30, 80])
     2
----> 3 BFstcs = source_band_induced_power(epochs, label, inverse_operator, bands, n_cycles=2, use_fft=False, n_jobs=1)

/home/leitman/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/mne-0.7.1-py2.7.egg/mne/utils.pyc in dec(*args, **kwargs)
   378 return ret
   379 else:
--> 380 return function(*args, **kwargs)
   381
   382 # set __wrapped__ attribute so ?? in IPython gets the right source

/home/leitman/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/mne-0.7.1-py2.7.egg/mne/minimum_norm/time_frequency.pyc in source_band_induced_power(epochs, inverse_operator, bands, label, lambda2, method, nave, n_cycles, df, use_fft, decim, baseline, baseline_mode, pca, n_jobs, verbose)
    84
    85 frequencies = np.concatenate([np.arange(band[0], band[1] + df / 2.0, df)
---> 86 for _, band in bands.iteritems()])
    87
    88 powers, _, vertno = _source_induced_power(epochs,
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5

Hi thanks will do and will try wilth sample data when I get to work tomorrow

Dave