(no subject)

[system]

fig = ica.plot_scores(scores, exclude=eog_inds)
                file_end= 'scores.png'
                filename = directory+subjects[s]+sessions[x]+file_end
                plt.savefig(filename)
                print 1
                plt.close(fig)
                print 2

fig=ica.plot_sources(epochs_bp,eog_inds)
                file_end = 'sources.png'
                filename = directory+subjects[s]+sessions[x]+file_end
                plt.savefig(filename)
                print 3
                plt.close(fig)
                print 4
                #del fig
                fig=ica.plot_components(eog_inds, colorbar=True)
                file_end = 'components.png'
                filename = directory+subjects[s]+sessions[x]+file_end
                plt.savefig(filename)
                print 5
                plt.close(fig)
                print 6
                #del fig
                ica.exclude += eog_inds[:1]

eog_evoked = eog_epochs.average()
                fig=ica.plot_sources(eog_evoked)
                file_end='reconstructed_latent_sources.png'
                filename = directory+subjects[s]+sessions[x]+file_end
                plt.savefig(filename)
                print 7
                plt.close(fig)
                print 8
                #del fig
                fig=ica.plot_overlay(eog_evoked)
                file_end='signal_before_and_after_ica.png'
                filename = directory+subjects[s]+sessions[x]+file_end
                plt.savefig(filename)
                print 9
                plt.close(fig)
                print 10
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[system]

Sorry, the previous email was sent by mistake!

Regards,
Maria

2014-08-16 15:04 GMT+03:00 Maria Hakonen <maria.hakonen at gmail.com>:

               fig = ica.plot_scores(scores, exclude=eog_inds)
                file_end= 'scores.png'
                filename = directory+subjects[s]+sessions+file_end
                plt.savefig(filename)
                print 1
                plt.close(fig)
                print 2

fig=ica.plot_sources(epochs_bp,eog_inds)
                file_end = 'sources.png'
                filename = directory+subjects[s]+sessions+file_end
                plt.savefig(filename)
                print 3
                plt.close(fig)
                print 4
                #del fig
                fig=ica.plot_components(eog_inds, colorbar=True)
                file_end = 'components.png'
                filename = directory+subjects[s]+sessions+file_end
                plt.savefig(filename)
                print 5
                plt.close(fig)
                print 6
                #del fig
                ica.exclude += eog_inds[:1]

eog_evoked = eog_epochs.average()
                fig=ica.plot_sources(eog_evoked)
                file_end='reconstructed_latent_sources.png'
                filename = directory+subjects[s]+sessions+file_end
                plt.savefig(filename)
                print 7
                plt.close(fig)
                print 8
                #del fig
                fig=ica.plot_overlay(eog_evoked)
                file_end='signal_before_and_after_ica.png'
                filename = directory+subjects[s]+sessions+file_end
                plt.savefig(filename)
                print 9
                plt.close(fig)
                print 10

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