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: