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'))