def __init__(self, order, multipleSimulations, matricesDir, memLayout, numberOfMechanisms):
super().__init__(order, multipleSimulations, matricesDir)
self.numberOfMechanisms = numberOfMechanisms
clones = {
'star': ['star(0)', 'star(1)', 'star(2)'],
}
self.db.update( parseXMLMatrixFile('{}/matrices_viscoelastic.xml'.format(matricesDir), clones) )
memoryLayoutFromFile(memLayout, self.db, clones)
self._qShapeExtended = (self.numberOf3DBasisFunctions(), self.numberOfExtendedQuantities())
self._qShapeAnelastic = (self.numberOf3DBasisFunctions(), self.numberOfAnelasticQuantities(), self.numberOfMechanisms)
self.Qext = OptionalDimTensor('Qext', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeExtended, alignStride=True)
self.Qane = OptionalDimTensor('Qane', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeAnelastic, alignStride=True)
self.Iane = OptionalDimTensor('Iane', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeAnelastic, alignStride=True)
self.E = Tensor('E', (self.numberOfAnelasticQuantities(), self.numberOfMechanisms, self.numberOfQuantities()))
self.w = Tensor('w', (self.numberOfMechanisms,))
self.W = Tensor('W', (self.numberOfMechanisms, self.numberOfMechanisms), np.eye(self.numberOfMechanisms, dtype=bool), CSCMemoryLayout)
selectElaSpp = np.zeros((self.numberOfExtendedQuantities(), self.numberOfQuantities()))
selectElaSpp[0:self.numberOfQuantities(),0:self.numberOfQuantities()] = np.eye(self.numberOfQuantities())
self.selectEla = Tensor('selectEla', (self.numberOfExtendedQuantities(), self.numberOfQuantities()), selectElaSpp, CSCMemoryLayout)
selectAneSpp = np.zeros((self.numberOfExtendedQuantities(), self.numberOfAnelasticQuantities()))
selectAneSpp[self.numberOfQuantities():self.numberOfExtendedQuantities(),0:self.numberOfAnelasticQuantities()] = np.eye(self.numberOfAnelasticQuantities())
self.selectAne = Tensor('selectAne', (self.numberOfExtendedQuantities(), self.numberOfAnelasticQuantities()), selectAneSpp, CSCMemoryLayout)
def __init__(self, order, multipleSimulations, matricesDir, memLayout):
super().__init__(order, multipleSimulations, matricesDir)
clones = {
'star': ['star(0)', 'star(1)', 'star(2)'],
}
self.db.update( parseXMLMatrixFile('{}/star.xml'.format(matricesDir), clones) )
memoryLayoutFromFile(memLayout, self.db, clones)
def __init__(self, order, multipleSimulations, matricesDir, memLayout,
numberOfMechanisms, **kwargs):
super().__init__(order, multipleSimulations, matricesDir)
clones = {
'star': ['star(0)', 'star(1)', 'star(2)'],
}
self.db.update(
parseXMLMatrixFile(
'{}/matrices_poroelastic.xml'.format(matricesDir), clones))
self.db.update(
parseJSONMatrixFile('{}/stp_{}.json'.format(matricesDir, order),
clones))
memoryLayoutFromFile(memLayout, self.db, clones)
def __init__(self, order, multipleSimulations, matricesDir, memLayout,
numberOfMechanisms, **kwargs):
self.numberOfMechanisms = numberOfMechanisms
self.numberOfElasticQuantities = 9
super().__init__(order, multipleSimulations, matricesDir)
clones = {
'star': ['star(0)', 'star(1)', 'star(2)'],
}
self.db.update(
parseXMLMatrixFile(
'{}/matrices_viscoelastic.xml'.format(matricesDir), clones))
star_spp = self.db.star[0].spp().as_ndarray()
star_rows, star_cols = star_spp.shape
aniso_cols = star_cols - self.numberOfElasticQuantities
star_spp_new = np.zeros(
(self.numberOfQuantities(), self.numberOfQuantities()), dtype=bool)
star_spp_new[0:star_rows, 0:star_cols] = star_spp
''' The last 6 columns of star_spp contain the prototype sparsity pattern for
a mechanism. Therefore, the spp is repeated for every mechanism. '''
for mech in range(1, numberOfMechanisms):
offset0 = self.numberOfElasticQuantities
offsetm = self.numberOfElasticQuantities + mech * aniso_cols
star_spp_new[0:star_rows, offsetm:offsetm +
aniso_cols] = star_spp[0:star_rows,
offset0:offset0 + aniso_cols]
for dim in range(3):
self.db.star[dim] = Tensor(self.db.star[dim].name(),
star_spp_new.shape,
spp=star_spp_new)
source_spp = np.zeros(
(self.numberOfQuantities(), self.numberOfQuantities()), dtype=bool)
ET_spp = self.db['ET'].spp().as_ndarray()
''' ET is a prototype sparsity pattern for a mechanism. Therefore, repeated for every
mechanism. See Kaeser and Dumbser 2006, III. Viscoelastic attenuation.
'''
for mech in range(numberOfMechanisms):
offset = self.numberOfElasticQuantities + mech * aniso_cols
r = slice(offset, offset + aniso_cols)
source_spp[r, 0:aniso_cols] = ET_spp
source_spp[r, r] = np.identity(aniso_cols, dtype=bool)
self.db.ET = Tensor('ET', source_spp.shape, spp=source_spp)
memoryLayoutFromFile(memLayout, self.db, clones)
def __init__(self, order, multipleSimulations, matricesDir, memLayout, numberOfMechanisms, **kwargs):
super().__init__(order, multipleSimulations, matricesDir)
self.numberOfMechanisms = numberOfMechanisms
clones = {
'star': ['star(0)', 'star(1)', 'star(2)'],
}
self.db.update( parseXMLMatrixFile('{}/matrices_viscoelastic.xml'.format(matricesDir), clones) )
memoryLayoutFromFile(memLayout, self.db, clones)
self._qShapeExtended = (self.numberOf3DBasisFunctions(), self.numberOfExtendedQuantities())
self._qShapeAnelastic = (self.numberOf3DBasisFunctions(), self.numberOfAnelasticQuantities(), self.numberOfMechanisms)
self.Qext = OptionalDimTensor('Qext', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeExtended, alignStride=True)
self.Qane = OptionalDimTensor('Qane', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeAnelastic, alignStride=True)
self.Iane = OptionalDimTensor('Iane', self.Q.optName(), self.Q.optSize(), self.Q.optPos(), self._qShapeAnelastic, alignStride=True)
self.E = Tensor('E', (self.numberOfAnelasticQuantities(), self.numberOfMechanisms, self.numberOfQuantities()))
self.w = Tensor('w', (self.numberOfMechanisms,))
self.W = Tensor('W', (self.numberOfMechanisms, self.numberOfMechanisms), np.eye(self.numberOfMechanisms, dtype=bool), CSCMemoryLayout)
selectElaSpp = np.zeros((self.numberOfExtendedQuantities(), self.numberOfQuantities()))
selectElaSpp[0:self.numberOfQuantities(),0:self.numberOfQuantities()] = np.eye(self.numberOfQuantities())
self.selectEla = Tensor('selectEla', (self.numberOfExtendedQuantities(), self.numberOfQuantities()), selectElaSpp, CSCMemoryLayout)
selectAneSpp = np.zeros((self.numberOfExtendedQuantities(), self.numberOfAnelasticQuantities()))
selectAneSpp[self.numberOfQuantities():self.numberOfExtendedQuantities(),0:self.numberOfAnelasticQuantities()] = np.eye(self.numberOfAnelasticQuantities())
self.selectAne = Tensor('selectAne', (self.numberOfExtendedQuantities(), self.numberOfAnelasticQuantities()), selectAneSpp, CSCMemoryLayout)
self.db.update(
parseJSONMatrixFile('{}/nodal/nodalBoundary_matrices_{}.json'.format(matricesDir,
self.order),
{},
alignStride=self.alignStride,
transpose=self.transpose,
namespace='nodal')
)
numberOfQuantities = 3
qShape = (numberOf1DBasisFunctions, numberOf1DBasisFunctions,
numberOfQuantities)
qShape1 = (numberOf1DBasisFunctions, numberOfQuantities)
clones = {'kDivM': ['kDivM', 'kDivMT'], 'kTDivM': ['kTDivM', 'kTDivMT']}
transpose = {'kDivMT', 'kTDivMT'}
alignStride = {'kDivM', 'kTDivM'}
db = parseJSONMatrixFile('{}/matrices_{}.json'.format(cmdLineArgs.matricesDir,
degree),
clones,
transpose=transpose,
alignStride=alignStride)
db.update(parseJSONMatrixFile('{}/star.json'.format(cmdLineArgs.matricesDir)))
memoryLayoutFromFile(cmdLineArgs.memLayout, db, dict())
Q = Tensor('Q', qShape)
Q1 = Tensor('Q1', qShape1)
Q1Neighbour = Tensor('Q1Neighbour', qShape1)
dQ0 = Tensor('dQ(0)', qShape)
I = Tensor('I', qShape)
phi = [
Tensor('phi({})'.format(i), (numberOf1DBasisFunctions, )) for i in range(2)
]
phiDivM = [
Tensor('phiDivM({})'.format(i), (numberOf1DBasisFunctions, ))
for i in range(2)
]
source = Tensor('source', (numberOfQuantities, ))