def test_09(self):
rho = 1e-1
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Z = (D.conj()*np.sum(D*X, axis=4, keepdims=True) + \
rho*X - D.conj()*S) / rho
Xslv = linalg.solvedbi_sm(D, rho, D.conj()*S + rho*Z)
assert(linalg.rrs(D.conj()*np.sum(D*Xslv, axis=4, keepdims=True) +
rho*Xslv, D.conj()*S + rho*Z) < 1e-11)
def test_09(self):
rho = 1e-1
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Z = (D.conj()*np.sum(D*X, axis=4, keepdims=True) + \
rho*X - D.conj()*S) / rho
Xslv = linalg.solvedbi_sm(D, rho, D.conj()*S + rho*Z)
assert(linalg.rrs(D.conj()*np.sum(D*Xslv, axis=4, keepdims=True) +
rho*Xslv, D.conj()*S + rho*Z) < 1e-11)
def test_10(self):
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
d = 1e-1 * (np.random.randn(N, N, 1, 1, M).astype('complex') +
np.random.randn(N, N, 1, 1, M).astype('complex') * 1.0j)
Z = (D.conj()*np.sum(D*X, axis=4, keepdims=True) +
d*X - D.conj()*S) / d
Xslv = linalg.solvedbd_sm(D, d, D.conj()*S + d*Z)
assert(linalg.rrs(D.conj()*np.sum(D*Xslv, axis=4, keepdims=True) +
d*Xslv, D.conj()*S + d*Z) < 1e-11)
def test_10(self):
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
d = 1e-1 * (np.random.randn(N, N, 1, 1, M).astype('complex') +
np.random.randn(N, N, 1, 1, M).astype('complex') * 1.0j)
Z = (D.conj()*np.sum(D*X, axis=4, keepdims=True) +
d*X - D.conj()*S) / d
Xslv = linalg.solvedbd_sm(D, d, D.conj()*S + d*Z)
assert(linalg.rrs(D.conj()*np.sum(D*Xslv, axis=4, keepdims=True) +
d*Xslv, D.conj()*S + d*Z) < 1e-11)
def test_15(self):
rho = 1e-1
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Xop = lambda x: np.sum(X * x, axis=4, keepdims=True)
XHop = lambda x: np.sum(np.conj(X) * x, axis=3, keepdims=True)
Z = (XHop(Xop(D)) + rho*D - XHop(S)) / rho
Dslv, cgit = linalg.solvemdbi_cg(X, rho, XHop(S)+rho*Z, 4, 3, tol=1e-6)
assert linalg.rrs(XHop(Xop(Dslv)) + rho*Dslv, XHop(S) + rho*Z) <= 1e-6
def test_15(self):
rho = 1e-1
N = 32
M = 16
K = 8
D = util.complex_randn(N, N, 1, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Xop = lambda x: np.sum(X * x, axis=4, keepdims=True)
XHop = lambda x: np.sum(np.conj(X) * x, axis=3, keepdims=True)
Z = (XHop(Xop(D)) + rho*D - XHop(S)) / rho
Dslv, cgit = linalg.solvemdbi_cg(X, rho, XHop(S)+rho*Z, 4, 3, tol=1e-6)
assert linalg.rrs(XHop(Xop(Dslv)) + rho*Dslv, XHop(S) + rho*Z) <= 1e-6
def test_14(self):
rho = 1e-1
N = 64
M = 32
C = 3
K = 8
D = util.complex_randn(N, N, C, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Xop = lambda x: np.sum(X * x, axis=4, keepdims=True)
XHop = lambda x: np.sum(np.conj(X) * x, axis=3, keepdims=True)
Z = (XHop(Xop(D)) + rho*D - XHop(S)) / rho
Dslv = linalg.solvemdbi_rsm(X, rho, XHop(S) + rho*Z, 3)
assert linalg.rrs(XHop(Xop(Dslv)) + rho*Dslv, XHop(S) + rho*Z) < 1e-11
def test_14(self):
rho = 1e-1
N = 64
M = 32
C = 3
K = 8
D = util.complex_randn(N, N, C, 1, M)
X = util.complex_randn(N, N, 1, K, M)
S = np.sum(D*X, axis=4, keepdims=True)
Xop = lambda x: np.sum(X * x, axis=4, keepdims=True)
XHop = lambda x: np.sum(np.conj(X) * x, axis=3, keepdims=True)
Z = (XHop(Xop(D)) + rho*D - XHop(S)) / rho
Dslv = linalg.solvemdbi_rsm(X, rho, XHop(S) + rho*Z, 3)
assert linalg.rrs(XHop(Xop(Dslv)) + rho*Dslv, XHop(S) + rho*Z) < 1e-11
