font = {
'family': 'Arial',
'weight': 'regular',
'size': 20
}
pl.rc('font', **font)
plot_results = False
if plot_results:
pl.figure(figsize=(30, 20))
tp_gt, tp_comp, fn_gt, fp_comp, performance_cons_off = compare_components(
gt_estimate,
cnm2.estimates,
Cn=Cn_orig,
thresh_cost=.8,
min_dist=10,
print_assignment=False,
labels=['GT', 'Offline'],
plot_results=False)
print(fname_new + str({
a: b.astype(np.float16)
for a, b in performance_cons_off.items()
}))
cnm2.estimates.A_thr = scipy.sparse.csc_matrix(
cnm2.estimates.A_thr)
performance_cons_off['fname_new'] = fname_new
performance_tmp = performance_cons_off.copy()
performance_tmp['tp_gt'] = tp_gt
pl.close('all')
params_display = {'downsample_ratio': .2, 'thr_plot': 0.8}
pl.rcParams['pdf.fonttype'] = 42
font = {'family': 'Arial', 'weight': 'regular', 'size': 20}
pl.rc('font', **font)
plot_results = False
if plot_results:
pl.figure(figsize=(30, 20))
tp_gt, tp_comp, fn_gt, fp_comp, performance_suite2p = compare_components(
gt_estimate,
s2p_estimate,
Cn=Cn_orig,
thresh_cost=.8,
min_dist=10,
print_assignment=False,
labels=['GT', 'Suite_2p'],
plot_results=True)
print(params_movie['fname'])
print({
a: b.astype(np.float16)
for a, b in performance_suite2p.items()
})
if onlycell:
name_to_load = os.path.join(
base_folder_,
os.path.split(fname_new)[1][:-4] +
'_comparison_GT_only_cell.npz')
else:
