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

[Alexandre Gramfort]

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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