m2=m.copy() m2.IPCA_denoise(components = 100, batch = 1000) m2.playMovie(frate=.05,magnification=4,gain=10.0) #%% #%% compute spatial components via NMF initTime=time.time() space_spcomps,time_comps=m.NonnegativeMatrixFactorization(n_components=20,beta=1,tol=5e-7); print 'elapsed time:' + str(time.time()-initTime) matrixMontage(np.asarray(space_spcomps),cmap=plt.cm.gray) # visualize components #%% compute spatial components via ICA PCA initTime=time.time() spcomps=m.IPCA_stICA(components=10,mu=.5); print 'elapsed time:' + str(time.time()-initTime) matrixMontage(spcomps,cmap=plt.cm.gray) # visualize components #%% extract ROIs from spatial components #_masks,masks_grouped=m.extractROIsFromPCAICA(spcomps, numSTD=6, gaussiansigmax=2 , gaussiansigmay=2) _masks,_=m.extractROIsFromPCAICA(spcomps, numSTD=10.0, gaussiansigmax=1 , gaussiansigmay=1) matrixMontage(np.asarray(_masks),cmap=plt.cm.gray) #%% extract single ROIs from each mask minPixels=5; maxPixels=2500; masks_tmp=[]; for mask in _masks: numPixels=np.sum(np.array(mask)); if (numPixels>minPixels and numPixels<maxPixels):