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))