plt.colorbar() plt.scatter(x=center[:,1], y=center[:,0], c='m', s=40) crd = cse.plot_contours(coo_matrix(Ain[:,::-1]),Cn,thr=0.9) plt.axis((-0.5,d2-0.5,-0.5,d1-0.5)) plt.gca().invert_yaxis() pl.show() #%% t1 = time() A,b,Cin = cse.update_spatial_components_parallel(Yr, Cin, f_in, Ain, sn=sn, **spatial_params) t_elSPATIAL = time() - t1 print t_elSPATIAL crd = cse.plot_contours(A,Cn,thr=0.9) #%% update_temporal_components t1 = time() C,f,Y_res,S,bl,c1,neurons_sn,g = cse.update_temporal_components_parallel(Yr,A,b,Cin,f_in,bl=None,c1=None,sn=None,g=None,**temporal_params) t_elTEMPORAL2 = time() - t1 print t_elTEMPORAL2 # took 98 sec #%% merge components corresponding to the same neuron t1 = time() A_m,C_m,nr_m,merged_ROIs,S_m,bl_m,c1_m,sn_m,g_m=cse.mergeROIS_parallel(Y_res,A,b,C,f,S,sn,temporal_params, spatial_params, bl=bl, c1=c1, sn=neurons_sn, g=g, thr=0.8, mx=50) t_elMERGE = time() - t1 print t_elMERGE #%% view results. Notice that in order to scroll components you need to click on the plot A_or, C_or, srt = cse.order_components(A_m,C_m) cse.view_patches(Yr,coo_matrix(A_or),C_or,b,f, d1,d2,secs=0) #%% crd = cse.plot_contours(A_m,Cn,thr=0.9) #%% refine spatial and temporal t1 = time() A2,b2,C2 = cse.update_spatial_components_parallel(Yr, C_m, f, A_m, sn=sn, **spatial_params)
A, b, Cin = cse.update_spatial_components_parallel(Yr, Cin, f_in, Ain, sn=sn, **spatial_params) t_elSPATIAL = time() - t1 print t_elSPATIAL #%% update_temporal_components t1 = time() C, f, Y_res, S, bl, c1, neurons_sn, g = cse.update_temporal_components_parallel( Yr, A, b, Cin, f_in, bl=None, c1=None, sn=None, g=None, **temporal_params) t_elTEMPORAL2 = time() - t1 print t_elTEMPORAL2 # took 98 sec #%% merge components corresponding to the same neuron t1 = time() A_m, C_m, nr_m, merged_ROIs, S_m, bl_m, c1_m, sn_m, g_m = cse.mergeROIS_parallel( Y_res, A, b, C, f,
} #%% PREPROCESS DATA t1 = time() Yr,sn,g=cse.preprocess_data(Yr,**preprocess_params) Ain, Cin, b_in, f_in, center=cse.initialize_components(Y, **init_params) print time() - t1 #%% t1 = time() A,b,Cin = cse.update_spatial_components_parallel(Yr, Cin, f_in, Ain, sn=sn, **spatial_params) t_elSPATIAL = time() - t1 print t_elSPATIAL #%% update_temporal_components t1 = time() C,f,Y_res,S,bl,c1,neurons_sn,g = cse.update_temporal_components_parallel(Yr,A,b,Cin,f_in,bl=None,c1=None,sn=None,g=None,**temporal_params) t_elTEMPORAL2 = time() - t1 print t_elTEMPORAL2 # took 98 sec #%% merge components corresponding to the same neuron t1 = time() A_m,C_m,nr_m,merged_ROIs,S_m,bl_m,c1_m,sn_m,g_m=cse.mergeROIS_parallel(Y_res,A,b,C,f,S,sn,temporal_params, spatial_params, bl=bl, c1=c1, sn=neurons_sn, g=g, thr=0.8, mx=50) t_elMERGE = time() - t1 print t_elMERGE except: print 'test failed' raise #%% STOP CLUSTER finally: print "Stopping Cluster...." sys.stdout.flush() proc_2=subprocess.Popen(["ipcluster stop"],shell=True)