def test_02(self): N = 16 M = 4 K = 8 X = np.random.randn(M, K) S = np.random.randn(N, K) try: b = cmod.CnstrMOD(X, S) b.solve() except Exception as e: print(e) assert 0
def test_03(self): N = 16 M = 4 K = 8 X = np.random.randn(M, K) S = np.random.randn(N, K) opt = cmod.CnstrMOD.Options({ 'Verbose': False, 'MaxMainIter': 200, 'RelStopTol': 1e-4, 'L': 100.0 }) b = cmod.CnstrMOD(X, S, (N, M), opt=opt) b.solve() assert np.array(b.getitstat().Rsdl).min() < 1e-4
def test_06(self): N = 16 M = 4 K = 8 X = np.random.randn(M, K) S = np.random.randn(N, K) dt = np.float64 opt = cmod.CnstrMOD.Options({ 'Verbose': False, 'MaxMainIter': 20, 'DataType': dt }) b = cmod.CnstrMOD(X, S, opt=opt) b.solve() assert b.X.dtype == dt assert b.Y.dtype == dt
def test_10(self): N = 16 M = 4 K = 8 X = np.random.randn(M, K) S = np.random.randn(N, K) opt = cmod.CnstrMOD.Options({ 'Verbose': False, 'MaxMainIter': 100, 'RelStopTol': 1e-4, 'L': 10.0, 'StepSizePolicy': StepSizePolicyCauchy() }) try: b = cmod.CnstrMOD(X, S, (N, M), opt=opt) b.solve() except Exception as e: print(e) assert 0
'L': 100, 'Backtrack': BacktrackRobust() }) b = bpdn.BPDN(D0, S, lmbda, opt) X = b.solve() """ Update dictionary for training image set using PGM with Cauchy step size policy :cite:`yuan-2008-stepsize`. """ opt = cmod.CnstrMOD.Options({ 'Verbose': True, 'MaxMainIter': 100, 'L': 50, 'StepSizePolicy': StepSizePolicyCauchy() }) c1 = cmod.CnstrMOD(X, S, None, opt) D11 = c1.solve() print("CMOD solve time: %.2fs" % c1.timer.elapsed('solve')) """ Update dictionary for training image set using PGM with Barzilai-Borwein step size policy :cite:`barzilai-1988-stepsize`. """ opt = cmod.CnstrMOD.Options({ 'Verbose': True, 'MaxMainIter': 100, 'L': 50, 'StepSizePolicy': StepSizePolicyBB() }) c2 = cmod.CnstrMOD(X, S, None, opt) D12 = c2.solve() print("CMOD solve time: %.2fs" % c2.timer.elapsed('solve'))