def test_prec_solve_2D(arpack_eigs, interface, x, num_evs, tol, atol, interactive=False):
from fvm import JadaHYMLSInterface
from jadapy import EpetraInterface
from jadapy import jdqz
numpy.random.seed(1234)
jac_op = EpetraInterface.CrsMatrix(interface.jacobian(x))
mass_op = EpetraInterface.CrsMatrix(interface.mass_matrix())
jada_interface = JadaHYMLSInterface.JadaHYMLSInterface(interface.map, interface, preconditioned_solve=True)
alpha, beta = jdqz.jdqz(jac_op, mass_op, num_evs, tol=tol, subspace_dimensions=[20, 40],
interface=jada_interface)
jdqz_eigs = numpy.array(sorted(alpha / beta, key=lambda x: abs(x)))
assert_allclose(jdqz_eigs.real, arpack_eigs.real, rtol=0, atol=atol)
assert_allclose(abs(jdqz_eigs.imag), abs(arpack_eigs.imag), rtol=0, atol=atol)
if not interactive:
return x
fig, ax = plt.subplots()
ax.scatter(jdqz_eigs.real, jdqz_eigs.imag, marker='+')
plt.show()
def solve(self, op, rhs, tol, maxit):
solver_parameters = self.parameters.sublist('Solver')
iterative_solver_parameters = solver_parameters.sublist(
'Iterative Solver')
iterative_solver_parameters.set('Convergence Tolerance',
tol if maxit > 1 else 1e-3)
# iterative_solver_parameters.set('Maximum Iterations', maxit)
if rhs.shape[1] == 2:
solver_parameters.set('Complex', True)
else:
solver_parameters.set('Complex', False)
solver_parameters.set('Use Bordering', True)
out = EpetraInterface.Vector(rhs)
epetra_op = EpetraInterface.Operator(ShiftedOperator(op))
if self.preconditioned_solve:
solver = HYMLS.Solver(epetra_op, self.interface.preconditioner,
self.parameters)
solver.SetBorder(op.Z, op.Q)
self.interface.preconditioner.Compute()
solver.ApplyInverse(rhs, out)
solver.UnsetBorder()
else:
raise Exception('Not implemented')
return out
def solve(self, op, rhs, tol, maxit):
solver_parameters = self.parameters.sublist('Solver')
iterative_solver_parameters = solver_parameters.sublist(
'Iterative Solver')
iterative_solver_parameters.set('Convergence Tolerance',
tol if maxit > 1 else 1e-3)
# iterative_solver_parameters.set('Maximum Iterations', maxit)
if rhs.shape[1] == 2:
solver_parameters.set('Complex', True)
else:
solver_parameters.set('Complex', False)
out = EpetraInterface.Vector(rhs)
epetra_op = EpetraInterface.Operator(op)
if self.preconditioned_solve:
epetra_precop = JadaHYMLSPrecOp(op, self.interface.preconditioner)
solver = HYMLS.Solver(epetra_op, epetra_precop, self.parameters)
else:
solver = HYMLS.Solver(epetra_op, epetra_op, self.parameters)
solver.ApplyInverse(rhs, out)
return out
def solve(self, op, rhs, tol, maxit):
solver_parameters = self.parameters.sublist('Solver')
iterative_solver_parameters = solver_parameters.sublist(
'Iterative Solver')
iterative_solver_parameters.set('Convergence Tolerance',
tol if maxit > 1 else 1e-3)
# iterative_solver_parameters.set('Maximum Iterations', maxit)
solver_parameters.set('Complex', True)
x = EpetraInterface.Vector(rhs.real.Map(), 2)
y = EpetraInterface.Vector(rhs.real.Map(), 2)
x[:, 0] = rhs.real
x[:, 1] = rhs.imag
epetra_op = ComplexEpetraInterface.Operator(op)
if self.preconditioned_solve:
epetra_precop = ComplexJadaHYMLSPrecOp(
op, self.interface.preconditioner)
solver = HYMLS.Solver(epetra_op, epetra_precop, self.parameters)
else:
solver = HYMLS.Solver(epetra_op, epetra_op, self.parameters)
solver.ApplyInverse(x, y)
out = ComplexEpetraInterface.ComplexVector(y[:, 0], y[:, 1])
return out
def prec(self, x, *args):
y = EpetraInterface.Vector(x.real.Map(), 2)
z = EpetraInterface.Vector(x.real.Map(), 2)
y[:, 0] = x.real
y[:, 1] = x.imag
self.interface.preconditioner.ApplyInverse(y, z)
out = ComplexEpetraInterface.ComplexVector(z[:, 0], z[:, 1])
return out
def Apply(self, x, y):
assert x.NumVectors() == 2
# Create a view here because this is an Epetra.MultiVector.
x = EpetraInterface.Vector(Epetra.View, x, 0, x.NumVectors())
y = EpetraInterface.Vector(Epetra.View, y, 0, y.NumVectors())
x = ComplexVector(x[:, 0], x[:, 1])
z = self.op.matvec(x)
ret = y[:, 0].Update(1.0, z.real, 0.0)
ret += y[:, 1].Update(1.0, z.imag, 0.0)
return ret
def __matmul__(self, x):
if isinstance(x, numpy.ndarray):
local_map = Epetra.LocalMap(x.shape[0], 0, self.Comm())
x = ComplexVector(EpetraInterface.Vector(local_map, x.T.real), EpetraInterface.Vector(local_map, x.T.imag))
tmp = ComplexVector(self.real.Map(), x.shape[1])
tmp.real.Multiply('N', 'N', 1.0, self.real, x.real, 0.0)
tmp.real.Multiply('N', 'N', -1.0, self.imag, x.imag, 1.0)
tmp.imag.Multiply('N', 'N', 1.0, self.real, x.imag, 0.0)
tmp.imag.Multiply('N', 'N', 1.0, self.imag, x.real, 1.0)
return tmp
def test_Epetra_lowdim():
try:
from PyTrilinos import Epetra
from jadapy import EpetraInterface
except ImportError:
pytest.skip("Trilinos not found")
dtype = numpy.float64
numpy.random.seed(1234)
tol = numpy.finfo(dtype).eps * 1e3
atol = tol * 10
n = 20
k = 2
comm = Epetra.PyComm()
map = Epetra.Map(n, 0, comm)
a1, a2 = generate_Epetra_test_matrix(map, [n, n], dtype)
interface = EpetraInterface.EpetraInterface(map)
alpha = jdqr.jdqr(a2, k, Target.LargestMagnitude, tol=tol, subspace_dimensions=[10, 18], interface=interface)
jdqr_eigs = numpy.array(sorted(alpha, key=lambda x: -abs(x)))
eigs = scipy.linalg.eigvals(a1)
eigs = numpy.array(sorted(eigs, key=lambda x: -abs(x)))
eigs = eigs[:k]
assert_allclose(jdqr_eigs.real, eigs.real, rtol=0, atol=atol)
assert_allclose(abs(jdqr_eigs.imag), abs(eigs.imag), rtol=0, atol=atol)
def ApplyInverse(self, x, y):
self.prec.ApplyInverse(x, y)
# Create a view here because this is an Epetra.MultiVector.
z = EpetraInterface.Vector(Epetra.View, y, 0, y.NumVectors())
z = self.op.proj(z)
return y.Update(1.0, z, 0.0)
def test_Epetra():
try:
from PyTrilinos import Epetra
from jadapy import EpetraInterface
except ImportError:
pytest.skip("Trilinos not found")
dtype = numpy.float64
numpy.random.seed(1234)
tol = numpy.finfo(dtype).eps * 1e3
atol = tol * 10
n = 20
k = 5
comm = Epetra.PyComm()
map = Epetra.Map(n, 0, comm)
a1, a2 = generate_Epetra_test_matrix(map, [n, n], dtype)
b1, b2 = generate_Epetra_test_matrix(map, [n, n], dtype)
interface = EpetraInterface.EpetraInterface(map)
alpha, beta = jdqz.jdqz(a2, b2, k, tol=tol, interface=interface)
jdqz_eigs = numpy.array(sorted(alpha / beta, key=lambda x: abs(x)))
eigs = scipy.linalg.eigvals(a1, b1)
eigs = numpy.array(sorted(eigs, key=lambda x: abs(x)))
eigs = eigs[:k]
assert_allclose(jdqz_eigs.real, eigs.real, rtol=0, atol=atol)
assert_allclose(abs(jdqz_eigs.imag), abs(eigs.imag), rtol=0, atol=atol)
def ApplyInverse(self, x, y):
self.prec.ApplyInverse(x, y)
assert x.NumVectors() == 2
# Create a view here because this is an Epetra.MultiVector.
y = EpetraInterface.Vector(Epetra.View, y, 0, y.NumVectors())
y = ComplexEpetraInterface.ComplexVector(y[:, 0], y[:, 1])
z = self.op.proj(y)
y *= 0.0
y += z
return 0
def __init__(self, *args, **kwargs):
self.real = None
self.imag = None
if len(args) > 1 and isinstance(args[0],
EpetraInterface.Vector) and isinstance(
args[1], EpetraInterface.Vector):
self.real = args[0]
self.imag = args[1]
elif len(args) > 0 and isinstance(args[0], ComplexVector):
self.real = EpetraInterface.Vector(args[0].real, *args[1:],
**kwargs)
self.imag = EpetraInterface.Vector(args[0].imag, *args[1:],
**kwargs)
elif len(args) > 1 and isinstance(args[1], ComplexVector):
self.real = EpetraInterface.Vector(args[0], args[1].real,
*args[1:], **kwargs)
self.imag = EpetraInterface.Vector(args[0], args[1].imag,
*args[1:], **kwargs)
else:
self.real = EpetraInterface.Vector(*args, **kwargs)
self.imag = EpetraInterface.Vector(*args, **kwargs)
self.shape = self.real.shape
self.dtype = numpy.dtype(self.real.dtype.char.upper())
def solve(self, op, rhs, tol, maxit):
solver_parameters = self.parameters.sublist('Solver')
iterative_solver_parameters = solver_parameters.sublist(
'Iterative Solver')
iterative_solver_parameters.set('Convergence Tolerance',
tol if maxit > 1 else 1e-3)
# iterative_solver_parameters.set('Maximum Iterations', maxit)
solver_parameters.set('Complex', True)
solver_parameters.set('Use Bordering', True)
x = EpetraInterface.Vector(rhs.real.Map(), 2)
y = EpetraInterface.Vector(rhs.real.Map(), 2)
x[:, 0] = rhs.real
x[:, 1] = rhs.imag
m = op.Q.real.NumVectors()
Q = EpetraInterface.Vector(rhs.real.Map(), m * 2)
Q[:, 0:m] = op.Q.real
Q[:, m:2 * m] = op.Q.imag
Z = EpetraInterface.Vector(rhs.real.Map(), m * 2)
Z[:, 0:m] = op.Z.real
Z[:, m:2 * m] = op.Z.imag
epetra_op = ComplexEpetraInterface.Operator(ShiftedOperator(op))
if self.preconditioned_solve:
solver = HYMLS.Solver(epetra_op, self.interface.preconditioner,
self.parameters)
solver.SetBorder(Z, Q)
self.interface.preconditioner.Compute()
solver.ApplyInverse(x, y)
solver.UnsetBorder()
else:
raise Exception('Not implemented')
out = ComplexEpetraInterface.ComplexVector(y[:, 0], y[:, 1])
return out
def test_Epetra_eigenvectors():
try:
from PyTrilinos import Epetra
from jadapy import EpetraInterface
except ImportError:
pytest.skip("Trilinos not found")
dtype = numpy.float64
numpy.random.seed(1234)
tol = numpy.finfo(dtype).eps * 1e3
atol = tol * 10
n = 20
k = 5
comm = Epetra.PyComm()
map = Epetra.Map(n, 0, comm)
a1, a2 = generate_Epetra_test_matrix(map, [n, n], dtype)
b1, b2 = generate_Epetra_test_matrix(map, [n, n], dtype)
interface = EpetraInterface.EpetraInterface(map)
alpha, beta, v = jdqz.jdqz(a2,
b2,
num=k,
tol=tol,
return_eigenvectors=True,
interface=interface)
jdqz_eigs = numpy.array(sorted(alpha / beta, key=lambda x: abs(x)))
jdqz_eigs = jdqz_eigs[:k]
eigs = scipy.linalg.eigvals(a1, b1)
eigs = numpy.array(sorted(eigs, key=lambda x: abs(x)))
eigs = eigs[:k]
assert_allclose(jdqz_eigs.real, eigs.real, rtol=0, atol=atol)
assert_allclose(abs(jdqz_eigs.imag), abs(eigs.imag), rtol=0, atol=atol)
i = 0
while i < k:
if alpha[i].imag:
assert norm(a2 @ v[:, i] * beta[i].real -
b2 @ v[:, i] * alpha[i].real +
b2 @ v[:, i + 1] * alpha[i].imag) < atol
assert norm(a2 @ v[:, i + 1] * beta[i].real -
b2 @ v[:, i] * alpha[i].imag -
b2 @ v[:, i + 1] * alpha[i].real) < atol
i += 2
else:
assert norm(a2 @ v[:, i] * beta[i].real -
b2 @ v[:, i] * alpha[i].real) < atol
i += 1
def generate_Epetra_test_matrix(map, shape, dtype):
try:
from PyTrilinos import Epetra
from jadapy import EpetraInterface
except ImportError:
pytest.skip("Trilinos not found")
a1 = generate_test_matrix(shape, dtype)
a2 = EpetraInterface.CrsMatrix(Epetra.Copy, map, shape[1])
for i in range(shape[0]):
for j in range(shape[1]):
a2[i, j] = a1[i, j]
a2.FillComplete()
return a1, a2
def test_orthonormalization_multiple_vectors_epetra(otype):
try:
from PyTrilinos import Epetra
from jadapy import EpetraInterface
except ImportError:
pytest.skip("Trilinos not found")
dtype = numpy.float64
atol = numpy.finfo(dtype).eps * 100
n = 20
k = 5
comm = Epetra.PyComm()
map = Epetra.Map(n, 0, comm)
x = EpetraInterface.Vector(map, k)
x.Random()
orthogonalization.orthonormalize(x, method=otype)
for i in range(k):
for j in range(k):
if i == j:
continue
assert_allclose(x[:, i].dot(x[:, j]), 0, rtol=0, atol=atol)
assert_allclose(norm(x[:, i]), 1, rtol=0, atol=atol)
def prec(self, x, *args):
out = EpetraInterface.Vector(x)
self.interface.preconditioner.ApplyInverse(x, out)
return out
