def testPoisson2D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
h = 1.0 / n
lmbd_min = 4.0 / h / h * (sin(pi * h / 2.0)**2 +
sin(pi * h / 2.0)**2)
lmbd_max = 4.0 / h / h * (sin((n - 1) * pi * h / 2.0)**2 + sin(
(n - 1) * pi * h / 2.0)**2)
cond = lmbd_max / lmbd_min
tol = cond * self.eps
n2 = n * n
A = LinearOperator(n2,
n2,
lambda x: Poisson2dMatvec(x),
symmetric=True)
e = np.ones(n2)
rhs = A * e
cg = CG(A, matvec_max=2 * n2, outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e - cg.bestSolution) / n
sys.stderr.write(self.fmt % (n2, cg.nMatvec, cg.residNorm, err))
# Adjust tol because allclose() uses infinity norm
self.assertTrue(np.allclose(e, cg.bestSolution, rtol=err * n))
def __init__(self, k, s, w=None, niter=10, **kwargs):
"""
TODO: empty docsting
"""
# get geometry
ncoils = len(s)
ndims = s[0].ndim
ngrid = s[0].shape
nknots = k.size / ndims
k = k.reshape([nknots, ndims])
# set shared plan for each ForFT and AdjFT operations
self._plan = get_plan(nknots, ngrid)
self._plan.precompute(k)
# define linear operators for iterative SENSE algo
if w is not None:
D_block = DiagonalOperator(diag=w.ravel())
else:
D_block = IdentityOperator(nargin=nknots)
blocks = [D_block] * ncoils
D = BlockDiagonalLinearOperator(blocks=blocks)
diag = np.sqrt(np.sum([_s**2 for _s in s], axis=0))
I = DiagonalOperator(diag=diag.ravel())
F = LinearOperator(
nargin=self._plan.N_total,
nargout=self._plan.M,
matvec=lambda u: self._plan.forward(f_hat=u),
matvec_transp=lambda u: self._plan.adjoint(f=u).ravel(),
dtype=np.complex128,
)
blocks = [[F * DiagonalOperator(diag=_s.ravel())] for _s in s]
E = BlockLinearOperator(blocks=blocks)
self.D = D
self.E = E
self.I = I
self.m = None
self.rhs = None
self.shape = (ngrid, nknots * ncoils)
self.solution = None
self.solver = CG(op=I * E.T * D * E * I, matvec_max=niter)
def testPoisson1D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
lmbd_min = 4.0 * sin(pi/2.0/n) ** 2
lmbd_max = 4.0 * sin((n-1)*pi/2.0/n) ** 2
cond = lmbd_max/lmbd_min
tol = cond * self.eps
e = np.ones(n)
rhs = Poisson1dMatvec(e)
cg = CG(Poisson1dMatvec,
matvec_max=2*n,
outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e-cg.bestSolution)/sqrt(n)
sys.stderr.write(self.fmt % (n, cg.nMatvec, cg.residNorm, err))
self.failUnless(np.allclose(e, cg.bestSolution, rtol=tol))
def testPoisson1D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
lmbd_min = 4.0 * sin(pi/2.0/n) ** 2
lmbd_max = 4.0 * sin((n-1)*pi/2.0/n) ** 2
cond = lmbd_max/lmbd_min
tol = cond * self.eps
A = LinearOperator(n, n,
lambda x: Poisson1dMatvec(x),
symmetric=True)
e = np.ones(n)
rhs = A * e
cg = CG(A, matvec_max=2*n, outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e-cg.bestSolution)/sqrt(n)
sys.stderr.write(self.fmt % (n, cg.nMatvec, cg.residNorm, err))
self.assertTrue(np.allclose(e, cg.bestSolution, rtol=tol))
def testPoisson1D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
lmbd_min = 4.0 * sin(pi / 2.0 / n)**2
lmbd_max = 4.0 * sin((n - 1) * pi / 2.0 / n)**2
cond = lmbd_max / lmbd_min
tol = cond * self.eps
A = LinearOperator(n,
n,
lambda x: Poisson1dMatvec(x),
symmetric=True)
e = np.ones(n)
rhs = A * e
cg = CG(A, matvec_max=2 * n, outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e - cg.bestSolution) / sqrt(n)
sys.stderr.write(self.fmt % (n, cg.nMatvec, cg.residNorm, err))
self.assertTrue(np.allclose(e, cg.bestSolution, rtol=tol))
def testPoisson2D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
h = 1.0/n
lmbd_min = 4.0/h/h*(sin(pi*h/2.0)**2 + sin(pi*h/2.0)**2)
lmbd_max = 4.0/h/h*(sin((n-1)*pi*h/2.0)**2 + sin((n-1)*pi*h/2.0)**2)
cond = lmbd_max/lmbd_min
tol = cond * self.eps
n2 = n*n
e = np.ones(n2)
rhs = Poisson2dMatvec(e)
cg = CG(Poisson2dMatvec,
matvec_max=2*n2,
outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e-cg.bestSolution)/n
sys.stderr.write(self.fmt % (n2, cg.nMatvec, cg.residNorm, err))
# Adjust tol because allclose() uses infinity norm
self.failUnless(np.allclose(e, cg.bestSolution, rtol=err*n))
def testPoisson2D(self):
# Solve 1D Poisson systems of various sizes
for n in self.n:
h = 1.0/n
lmbd_min = 4.0/h/h*(sin(pi*h/2.0)**2 + sin(pi*h/2.0)**2)
lmbd_max = 4.0/h/h*(sin((n-1)*pi*h/2.0)**2 + sin((n-1)*pi*h/2.0)**2)
cond = lmbd_max/lmbd_min
tol = cond * self.eps
n2 = n*n
A = LinearOperator(n2, n2,
lambda x: Poisson2dMatvec(x),
symmetric=True)
e = np.ones(n2)
rhs = A * e
cg = CG(A, matvec_max=2*n2, outputStream=sys.stderr)
cg.solve(rhs)
err = np.linalg.norm(e-cg.bestSolution)/n
sys.stderr.write(self.fmt % (n2, cg.nMatvec, cg.residNorm, err))
# Adjust tol because allclose() uses infinity norm
self.assertTrue(np.allclose(e, cg.bestSolution, rtol=err*n))
