Newest pull has get_t_value_timecourses method:
That method does return values of variables that were manually added before the running the GroupResponseFitter but does not return their column labels. get_timecourses method in contrast does that.
Example:
df is 2D fMRI data
df['run'] = 1
df['subject'] = 1
g_model = nideconv.GroupResponseFitter(df, design, 1/TR, concatenate_runs=False, confounds=confounds_all)
# I added some events here
tc_t = g_model.get_t_value_timecourses()
tc_t.head()
Pic1: Notice how instead of column/indices for run and subject on the left hand side, there are just blanks above the values.
Pic2: The same for retrieving normal PSC timecourse when doing g_model.get_timecourses()
Setting the indices manually like so
tc_t.index.names = ['subject', 'run', 'event type', 'covariate', 'time']
fixes it. But I guess it would still be better if the function sets the index for you in the proper way.
Newest pull has get_t_value_timecourses method: That method does return values of variables that were manually added before the running the GroupResponseFitter but does not return their column labels. get_timecourses method in contrast does that.
Example: df is 2D fMRI data
g_model.get_timecourses()Setting the indices manually like so
tc_t.index.names = ['subject', 'run', 'event type', 'covariate', 'time']fixes it. But I guess it would still be better if the function sets the index for you in the proper way.