m2 = MOHGP(X,Kf,Ky,Y, K=Nclust, prior_Z = 'DP', alpha=alpha)
m2.ensure_default_constraints()
m2.checkgrad(verbose=1)
m2.randomize()
m2.optimize()
m2.systematic_splits()
m2.systematic_splits()
m2.plot(1,1,1,0,0,1)
#construct a MOG model (can't recover the clusters)
Y_ = Y.copy()
Y_ -= Y_.mean(0)
Y_ /= Y_.std(0)
m3 = MOG(Y_, prior_Z='DP', alpha=alpha)
m3.randomize()
m3.optimize()
m3.systematic_splits()
m3.systematic_splits()
pb.figure()
pb.subplot(2,2,1)
pb.imshow(ground_truth_phi,aspect='auto',cmap=pb.cm.gray)
pb.title('ground truth')
pb.subplot(2,2,2)
pb.imshow(m.phi,aspect='auto',cmap=pb.cm.gray)
pb.title('structured GP-DP')
pb.subplot(2,2,3)
pb.imshow(m2.phi,aspect='auto',cmap=pb.cm.gray)
pb.title('unstructured GP-DP')
pb.subplot(2,2,4)
pb.imshow(m3.phi,aspect='auto',cmap=pb.cm.gray)
m2 = MOHGP(X, Kf, Ky, Y, K=Nclust, prior_Z='DP', alpha=alpha)
m2.ensure_default_constraints()
m2.checkgrad(verbose=1)
m2.randomize()
m2.optimize()
m2.systematic_splits()
m2.systematic_splits()
m2.plot(1, 1, 1, 0, 0, 1)
#construct a MOG model (can't recover the clusters)
Y_ = Y.copy()
Y_ -= Y_.mean(0)
Y_ /= Y_.std(0)
m3 = MOG(Y_, prior_Z='DP', alpha=alpha)
m3.randomize()
m3.optimize()
m3.systematic_splits()
m3.systematic_splits()
pb.figure()
pb.subplot(2, 2, 1)
pb.imshow(ground_truth_phi, aspect='auto', cmap=pb.cm.gray)
pb.title('ground truth')
pb.subplot(2, 2, 2)
pb.imshow(m.phi, aspect='auto', cmap=pb.cm.gray)
pb.title('structured GP-DP')
pb.subplot(2, 2, 3)
pb.imshow(m2.phi, aspect='auto', cmap=pb.cm.gray)
pb.title('unstructured GP-DP')
pb.subplot(2, 2, 4)
pb.imshow(m3.phi, aspect='auto', cmap=pb.cm.gray)
