[Mne_analysis] Type Error in adaptation of example plot_source_space_time_frequency.py

[Martin Luessi]

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


On 03/09/14 03:49, Alexandre Gramfort wrote:
> hi David,
> 
> can you reproduce the problem with the sample data?
> could you share a gist on https://gist.github.com/ ?
> 
> thanks
> Alex
> 
> 
> On Sat, Mar 8, 2014 at 9:47 PM, David Leitman
> <leitman at mail.med.upenn.edu> wrote:
>> Hi all,
>>
>>  I get the following error when I try the following using my constructed ROI labels : Any pointers would be much appreciated :)
>>
>> 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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-- 
Martin Luessi, Ph.D.

Research Fellow

Department of Radiology
Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School
149 13th Street
Charlestown, MA 02129

Fax: +1 617 726-7422