def get_fdr_cutoffs( tsv_file, index='networks', alphas=[.05, .01], dec_places=2 ): for a in alphas: if a < .01: raise Exception("Alphas only go to .01, easy to fix, but I have bigger fish to fry") b6 = pandas.read_csv( tsv_file , sep='\t') b6.set_index(index) cutoffs = defaultdict(dict) for alpha in alphas: for c in b6.columns: if c != index: cutoff = pval.fdr_threshold(b6[c].values, alpha=alpha) cutoffs[c][("{:.%if}"%dec_places ).format(alpha)] = cutoff return cutoffs
tsr, psr = ttest_ind(samatha[subjects.T[1] == level], rest[subjects.T[1] == level], #equal_var=False, axis=0) psr_corrected = fdr_threshold(psr[upper_mask], alpha=p_value) psr_corrected = p_value ''' tsv, psv = ttest_ind(samatha[subjects.T[1] == level], vipassana[subjects.T[1] == level], #equal_var=False, axis=0) psv_corrected = fdr_threshold(psv[upper_mask], alpha=p_value) psv_corrected = p_value ''' fields['ttest_samatha_rest_t'] = tsr fields['ttest_samatha_rest_p'] = psr fields['ttest_vipassana_rest_t'] = tvr fields['ttest_vipassana_rest_p'] = pvr ''' fields['ttest_samatha_vipassana_t'] = tsv fields['ttest_samatha_vipassana_p'] = psv ''' f, _ = plot_connectivity_circle_edited(tsr * (psr < psr_corrected), roi_names, None, n_lines=np.count_nonzero(psr < psr_corrected))