def _entity_support_dofs(self):
esd = {}
for entity_dim in self.cell.sub_entities.keys():
beta = self.get_indices()
zeta = self.get_value_indices()
entity_cell = self.cell.construct_subelement(entity_dim)
quad = make_quadrature(entity_cell, (2*numpy.array(self.degree)).tolist())
eps = 1.e-8 # Is this a safe value?
result = {}
for f in self.entity_dofs()[entity_dim].keys():
# Tabulate basis functions on the facet
vals, = self.basis_evaluation(0, quad.point_set, entity=(entity_dim, f)).values()
# Integrate the square of the basis functions on the facet.
ints = gem.IndexSum(
gem.Product(gem.IndexSum(gem.Product(gem.Indexed(vals, beta + zeta),
gem.Indexed(vals, beta + zeta)), zeta),
quad.weight_expression),
quad.point_set.indices
)
evaluation, = evaluate([gem.ComponentTensor(ints, beta)])
ints = evaluation.arr.flatten()
assert evaluation.fids == ()
result[f] = [dof for dof, i in enumerate(ints) if i > eps]
esd[entity_dim] = result
return esd
def _entity_support_dofs(self):
esd = {}
for entity_dim in self.cell.sub_entities.keys():
beta = self.get_indices()
zeta = self.get_value_indices()
entity_cell = self.cell.construct_subelement(entity_dim)
quad = make_quadrature(entity_cell,
(2 * numpy.array(self.degree)).tolist())
eps = 1.e-8 # Is this a safe value?
result = {}
for f in self.entity_dofs()[entity_dim].keys():
# Tabulate basis functions on the facet
vals, = self.basis_evaluation(0,
quad.point_set,
entity=(entity_dim, f)).values()
# Integrate the square of the basis functions on the facet.
ints = gem.IndexSum(
gem.Product(
gem.IndexSum(
gem.Product(gem.Indexed(vals, beta + zeta),
gem.Indexed(vals, beta + zeta)), zeta),
quad.weight_expression), quad.point_set.indices)
evaluation, = evaluate([gem.ComponentTensor(ints, beta)])
ints = evaluation.arr.flatten()
assert evaluation.fids == ()
result[f] = [dof for dof, i in enumerate(ints) if i > eps]
esd[entity_dim] = result
return esd
def make_quadrature_element(fiat_ref_cell, degree, scheme="default"):
"""Construct a :class:`QuadratureElement` from a given a reference
element, degree and scheme.
:param fiat_ref_cell: The FIAT reference cell to build the
:class:`QuadratureElement` on.
:param degree: The degree of polynomial that the rule should
integrate exactly.
:param scheme: The quadrature scheme to use - e.g. "default",
"canonical" or "KMV".
:returns: The appropriate :class:`QuadratureElement`
"""
rule = make_quadrature(fiat_ref_cell, degree, scheme)
return QuadratureElement(fiat_ref_cell, rule)
def entity_support_dofs(elem, entity_dim):
"""Return the map of entity id to the degrees of freedom for which
the corresponding basis functions take non-zero values.
:arg elem: FInAT finite element
:arg entity_dim: Dimension of the cell subentity.
"""
if not hasattr(elem, "_entity_support_dofs"):
elem._entity_support_dofs = {}
cache = elem._entity_support_dofs
try:
return cache[entity_dim]
except KeyError:
pass
beta = elem.get_indices()
zeta = elem.get_value_indices()
entity_cell = elem.cell.construct_subelement(entity_dim)
quad = make_quadrature(entity_cell,
(2 * numpy.array(elem.degree)).tolist())
eps = 1.e-8 # Is this a safe value?
result = {}
for f in elem.entity_dofs()[entity_dim].keys():
# Tabulate basis functions on the facet
vals, = itervalues(
elem.basis_evaluation(0, quad.point_set, entity=(entity_dim, f)))
# Integrate the square of the basis functions on the facet.
ints = gem.IndexSum(
gem.Product(
gem.IndexSum(
gem.Product(gem.Indexed(vals, beta + zeta),
gem.Indexed(vals, beta + zeta)), zeta),
quad.weight_expression), quad.point_set.indices)
ints = aggressive_unroll(gem.ComponentTensor(ints,
beta)).array.flatten()
result[f] = [dof for dof, i in enumerate(ints) if i > eps]
cache[entity_dim] = result
return result
def dg_injection_kernel(Vf, Vc, ncell):
from firedrake import Tensor, AssembledVector, TestFunction, TrialFunction
from firedrake.slate.slac import compile_expression
macro_builder = MacroKernelBuilder(ScalarType_c, ncell)
f = ufl.Coefficient(Vf)
macro_builder.set_coefficients([f])
macro_builder.set_coordinates(Vf.mesh())
Vfe = create_element(Vf.ufl_element())
macro_quadrature_rule = make_quadrature(
Vfe.cell, estimate_total_polynomial_degree(ufl.inner(f, f)))
index_cache = {}
parameters = default_parameters()
integration_dim, entity_ids = lower_integral_type(Vfe.cell, "cell")
macro_cfg = dict(interface=macro_builder,
ufl_cell=Vf.ufl_cell(),
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
index_cache=index_cache,
quadrature_rule=macro_quadrature_rule)
fexpr, = fem.compile_ufl(f, **macro_cfg)
X = ufl.SpatialCoordinate(Vf.mesh())
C_a, = fem.compile_ufl(X, **macro_cfg)
detJ = ufl_utils.preprocess_expression(
abs(ufl.JacobianDeterminant(f.ufl_domain())))
macro_detJ, = fem.compile_ufl(detJ, **macro_cfg)
Vce = create_element(Vc.ufl_element())
coarse_builder = firedrake_interface.KernelBuilder("cell", "otherwise", 0,
ScalarType_c)
coarse_builder.set_coordinates(Vc.mesh())
argument_multiindices = (Vce.get_indices(), )
argument_multiindex, = argument_multiindices
return_variable, = coarse_builder.set_arguments((ufl.TestFunction(Vc), ),
argument_multiindices)
integration_dim, entity_ids = lower_integral_type(Vce.cell, "cell")
# Midpoint quadrature for jacobian on coarse cell.
quadrature_rule = make_quadrature(Vce.cell, 0)
coarse_cfg = dict(interface=coarse_builder,
ufl_cell=Vc.ufl_cell(),
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
index_cache=index_cache,
quadrature_rule=quadrature_rule)
X = ufl.SpatialCoordinate(Vc.mesh())
K = ufl_utils.preprocess_expression(ufl.JacobianInverse(Vc.mesh()))
C_0, = fem.compile_ufl(X, **coarse_cfg)
K, = fem.compile_ufl(K, **coarse_cfg)
i = gem.Index()
j = gem.Index()
C_0 = gem.Indexed(C_0, (j, ))
C_0 = gem.index_sum(C_0, quadrature_rule.point_set.indices)
C_a = gem.Indexed(C_a, (j, ))
X_a = gem.Sum(C_0, gem.Product(gem.Literal(-1), C_a))
K_ij = gem.Indexed(K, (i, j))
K_ij = gem.index_sum(K_ij, quadrature_rule.point_set.indices)
X_a = gem.index_sum(gem.Product(K_ij, X_a), (j, ))
C_0, = quadrature_rule.point_set.points
C_0 = gem.Indexed(gem.Literal(C_0), (i, ))
# fine quad points in coarse reference space.
X_a = gem.Sum(C_0, gem.Product(gem.Literal(-1), X_a))
X_a = gem.ComponentTensor(X_a, (i, ))
# Coarse basis function evaluated at fine quadrature points
phi_c = fem.fiat_to_ufl(
Vce.point_evaluation(0, X_a, (Vce.cell.get_dimension(), 0)), 0)
tensor_indices = tuple(gem.Index(extent=d) for d in f.ufl_shape)
phi_c = gem.Indexed(phi_c, argument_multiindex + tensor_indices)
fexpr = gem.Indexed(fexpr, tensor_indices)
quadrature_weight = macro_quadrature_rule.weight_expression
expr = gem.Product(gem.IndexSum(gem.Product(phi_c, fexpr), tensor_indices),
gem.Product(macro_detJ, quadrature_weight))
quadrature_indices = macro_builder.indices + macro_quadrature_rule.point_set.indices
reps = spectral.Integrals([expr], quadrature_indices,
argument_multiindices, parameters)
assignments = spectral.flatten([(return_variable, reps)], index_cache)
return_variables, expressions = zip(*assignments)
expressions = impero_utils.preprocess_gem(expressions,
**spectral.finalise_options)
assignments = list(zip(return_variables, expressions))
impero_c = impero_utils.compile_gem(assignments,
quadrature_indices +
argument_multiindex,
remove_zeros=True)
index_names = []
def name_index(index, name):
index_names.append((index, name))
if index in index_cache:
for multiindex, suffix in zip(index_cache[index],
string.ascii_lowercase):
name_multiindex(multiindex, name + suffix)
def name_multiindex(multiindex, name):
if len(multiindex) == 1:
name_index(multiindex[0], name)
else:
for i, index in enumerate(multiindex):
name_index(index, name + str(i))
name_multiindex(quadrature_indices, 'ip')
for multiindex, name in zip(argument_multiindices, ['j', 'k']):
name_multiindex(multiindex, name)
index_names.extend(zip(macro_builder.indices, ["entity"]))
body = generate_coffee(impero_c, index_names, parameters["precision"],
ScalarType_c)
retarg = ast.Decl(ScalarType_c,
ast.Symbol("R", rank=(Vce.space_dimension(), )))
local_tensor = coarse_builder.local_tensor
local_tensor.init = ast.ArrayInit(
numpy.zeros(Vce.space_dimension(), dtype=ScalarType_c))
body.children.insert(0, local_tensor)
args = [retarg] + macro_builder.kernel_args + [
macro_builder.coordinates_arg, coarse_builder.coordinates_arg
]
# Now we have the kernel that computes <f, phi_c>dx_c
# So now we need to hit it with the inverse mass matrix on dx_c
u = TrialFunction(Vc)
v = TestFunction(Vc)
expr = Tensor(ufl.inner(u, v) * ufl.dx).inv * AssembledVector(
ufl.Coefficient(Vc))
Ainv, = compile_expression(expr)
Ainv = Ainv.kinfo.kernel
A = ast.Symbol(local_tensor.sym.symbol)
R = ast.Symbol("R")
body.children.append(
ast.FunCall(Ainv.name, R, coarse_builder.coordinates_arg.sym, A))
from coffee.base import Node
assert isinstance(Ainv._code, Node)
return op2.Kernel(ast.Node([
Ainv._code,
ast.FunDecl("void",
"pyop2_kernel_injection_dg",
args,
body,
pred=["static", "inline"])
]),
name="pyop2_kernel_injection_dg",
cpp=True,
include_dirs=Ainv._include_dirs,
headers=Ainv._headers)
def quadrature_rule(self):
integration_cell = self.fiat_cell.construct_subelement(
self.integration_dim)
return make_quadrature(integration_cell, self.quadrature_degree)
def compile_integral(integral_data, form_data, prefix, parameters,
interface=firedrake_interface):
"""Compiles a UFL integral into an assembly kernel.
:arg integral_data: UFL integral data
:arg form_data: UFL form data
:arg prefix: kernel name will start with this string
:arg parameters: parameters object
:arg interface: backend module for the kernel interface
:returns: a kernel constructed by the kernel interface
"""
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# Remove these here, they're handled below.
if parameters.get("quadrature_degree") in ["auto", "default", None, -1, "-1"]:
del parameters["quadrature_degree"]
if parameters.get("quadrature_rule") in ["auto", "default", None]:
del parameters["quadrature_rule"]
integral_type = integral_data.integral_type
interior_facet = integral_type.startswith("interior_facet")
mesh = integral_data.domain
cell = integral_data.domain.ufl_cell()
arguments = form_data.preprocessed_form.arguments()
kernel_name = "%s_%s_integral_%s" % (prefix, integral_type, integral_data.subdomain_id)
# Handle negative subdomain_id
kernel_name = kernel_name.replace("-", "_")
fiat_cell = as_fiat_cell(cell)
integration_dim, entity_ids = lower_integral_type(fiat_cell, integral_type)
quadrature_indices = []
# Dict mapping domains to index in original_form.ufl_domains()
domain_numbering = form_data.original_form.domain_numbering()
builder = interface.KernelBuilder(integral_type, integral_data.subdomain_id,
domain_numbering[integral_data.domain])
argument_multiindices = tuple(builder.create_element(arg.ufl_element()).get_indices()
for arg in arguments)
return_variables = builder.set_arguments(arguments, argument_multiindices)
builder.set_coordinates(mesh)
builder.set_coefficients(integral_data, form_data)
# Map from UFL FiniteElement objects to multiindices. This is
# so we reuse Index instances when evaluating the same coefficient
# multiple times with the same table.
#
# We also use the same dict for the unconcatenate index cache,
# which maps index objects to tuples of multiindices. These two
# caches shall never conflict as their keys have different types
# (UFL finite elements vs. GEM index objects).
index_cache = {}
kernel_cfg = dict(interface=builder,
ufl_cell=cell,
integral_type=integral_type,
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
argument_multiindices=argument_multiindices,
index_cache=index_cache)
mode_irs = collections.OrderedDict()
for integral in integral_data.integrals:
params = parameters.copy()
params.update(integral.metadata()) # integral metadata overrides
if params.get("quadrature_rule") == "default":
del params["quadrature_rule"]
mode = pick_mode(params["mode"])
mode_irs.setdefault(mode, collections.OrderedDict())
integrand = ufl.replace(integral.integrand(), form_data.function_replace_map)
integrand = ufl_utils.split_coefficients(integrand, builder.coefficient_split)
# Check if the integral has a quad degree attached, otherwise use
# the estimated polynomial degree attached by compute_form_data
quadrature_degree = params.get("quadrature_degree",
params["estimated_polynomial_degree"])
try:
quadrature_degree = params["quadrature_degree"]
except KeyError:
quadrature_degree = params["estimated_polynomial_degree"]
functions = list(arguments) + [builder.coordinate(mesh)] + list(integral_data.integral_coefficients)
function_degrees = [f.ufl_function_space().ufl_element().degree() for f in functions]
if all((asarray(quadrature_degree) > 10 * asarray(degree)).all()
for degree in function_degrees):
logger.warning("Estimated quadrature degree %s more "
"than tenfold greater than any "
"argument/coefficient degree (max %s)",
quadrature_degree, max_degree(function_degrees))
try:
quad_rule = params["quadrature_rule"]
except KeyError:
integration_cell = fiat_cell.construct_subelement(integration_dim)
quad_rule = make_quadrature(integration_cell, quadrature_degree)
if not isinstance(quad_rule, AbstractQuadratureRule):
raise ValueError("Expected to find a QuadratureRule object, not a %s" %
type(quad_rule))
quadrature_multiindex = quad_rule.point_set.indices
quadrature_indices.extend(quadrature_multiindex)
config = kernel_cfg.copy()
config.update(quadrature_rule=quad_rule)
expressions = fem.compile_ufl(integrand,
interior_facet=interior_facet,
**config)
reps = mode.Integrals(expressions, quadrature_multiindex,
argument_multiindices, params)
for var, rep in zip(return_variables, reps):
mode_irs[mode].setdefault(var, []).append(rep)
# Finalise mode representations into a set of assignments
assignments = []
for mode, var_reps in mode_irs.items():
assignments.extend(mode.flatten(var_reps.items(), index_cache))
if assignments:
return_variables, expressions = zip(*assignments)
else:
return_variables = []
expressions = []
# Need optimised roots for COFFEE
options = dict(reduce(operator.and_,
[mode.finalise_options.items()
for mode in mode_irs.keys()]))
expressions = impero_utils.preprocess_gem(expressions, **options)
assignments = list(zip(return_variables, expressions))
# Look for cell orientations in the IR
if builder.needs_cell_orientations(expressions):
builder.require_cell_orientations()
# Construct ImperoC
split_argument_indices = tuple(chain(*[var.index_ordering()
for var in return_variables]))
index_ordering = tuple(quadrature_indices) + split_argument_indices
try:
impero_c = impero_utils.compile_gem(assignments, index_ordering, remove_zeros=True)
except impero_utils.NoopError:
# No operations, construct empty kernel
return builder.construct_empty_kernel(kernel_name)
# Generate COFFEE
index_names = []
def name_index(index, name):
index_names.append((index, name))
if index in index_cache:
for multiindex, suffix in zip(index_cache[index],
string.ascii_lowercase):
name_multiindex(multiindex, name + suffix)
def name_multiindex(multiindex, name):
if len(multiindex) == 1:
name_index(multiindex[0], name)
else:
for i, index in enumerate(multiindex):
name_index(index, name + str(i))
name_multiindex(quadrature_indices, 'ip')
for multiindex, name in zip(argument_multiindices, ['j', 'k']):
name_multiindex(multiindex, name)
# Construct kernel
body = generate_coffee(impero_c, index_names, parameters["precision"], expressions, split_argument_indices)
return builder.construct_kernel(kernel_name, body)
def compile_integral(integral_data, form_data, prefix, parameters,
interface=firedrake_interface):
"""Compiles a UFL integral into an assembly kernel.
:arg integral_data: UFL integral data
:arg form_data: UFL form data
:arg prefix: kernel name will start with this string
:arg parameters: parameters object
:arg interface: backend module for the kernel interface
:returns: a kernel constructed by the kernel interface
"""
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# Remove these here, they're handled below.
if parameters.get("quadrature_degree") in ["auto", "default", None, -1, "-1"]:
del parameters["quadrature_degree"]
if parameters.get("quadrature_rule") in ["auto", "default", None]:
del parameters["quadrature_rule"]
integral_type = integral_data.integral_type
interior_facet = integral_type.startswith("interior_facet")
mesh = integral_data.domain
cell = integral_data.domain.ufl_cell()
arguments = form_data.preprocessed_form.arguments()
fiat_cell = as_fiat_cell(cell)
integration_dim, entity_ids = lower_integral_type(fiat_cell, integral_type)
argument_indices = tuple(tuple(gem.Index(extent=e)
for e in create_element(arg.ufl_element()).index_shape)
for arg in arguments)
flat_argument_indices = tuple(chain(*argument_indices))
quadrature_indices = []
# Dict mapping domains to index in original_form.ufl_domains()
domain_numbering = form_data.original_form.domain_numbering()
builder = interface.KernelBuilder(integral_type, integral_data.subdomain_id,
domain_numbering[integral_data.domain])
return_variables = builder.set_arguments(arguments, argument_indices)
coordinates = ufl_utils.coordinate_coefficient(mesh)
builder.set_coordinates(coordinates)
builder.set_coefficients(integral_data, form_data)
# Map from UFL FiniteElement objects to Index instances. This is
# so we reuse Index instances when evaluating the same coefficient
# multiple times with the same table. Occurs, for example, if we
# have multiple integrals here (and the affine coordinate
# evaluation can be hoisted).
index_cache = collections.defaultdict(gem.Index)
kernel_cfg = dict(interface=builder,
ufl_cell=cell,
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
argument_indices=argument_indices,
index_cache=index_cache)
kernel_cfg["facetarea"] = facetarea_generator(mesh, coordinates, kernel_cfg, integral_type)
kernel_cfg["cellvolume"] = cellvolume_generator(mesh, coordinates, kernel_cfg)
irs = []
for integral in integral_data.integrals:
params = {}
# Record per-integral parameters
params.update(integral.metadata())
if params.get("quadrature_rule") == "default":
del params["quadrature_rule"]
# parameters override per-integral metadata
params.update(parameters)
integrand = ufl_utils.replace_coordinates(integral.integrand(), coordinates)
integrand = ufl_utils.split_coefficients(integrand, builder.coefficient_split)
# Check if the integral has a quad degree attached, otherwise use
# the estimated polynomial degree attached by compute_form_data
quadrature_degree = params.get("quadrature_degree",
params["estimated_polynomial_degree"])
try:
quad_rule = params["quadrature_rule"]
except KeyError:
integration_cell = fiat_cell.construct_subelement(integration_dim)
quad_rule = make_quadrature(integration_cell, quadrature_degree)
if not isinstance(quad_rule, AbstractQuadratureRule):
raise ValueError("Expected to find a QuadratureRule object, not a %s" %
type(quad_rule))
quadrature_multiindex = quad_rule.point_set.indices
quadrature_indices += quadrature_multiindex
config = kernel_cfg.copy()
config.update(quadrature_rule=quad_rule)
ir = fem.compile_ufl(integrand, interior_facet=interior_facet, **config)
if parameters["unroll_indexsum"]:
def predicate(index):
return index.extent <= parameters["unroll_indexsum"]
ir = opt.unroll_indexsum(ir, predicate=predicate)
ir = [gem.index_sum(expr, quadrature_multiindex) for expr in ir]
irs.append(ir)
# Sum the expressions that are part of the same restriction
ir = list(reduce(gem.Sum, e, gem.Zero()) for e in zip(*irs))
# Need optimised roots for COFFEE
ir = impero_utils.preprocess_gem(ir)
# Look for cell orientations in the IR
if builder.needs_cell_orientations(ir):
builder.require_cell_orientations()
impero_c = impero_utils.compile_gem(return_variables, ir,
tuple(quadrature_indices) + flat_argument_indices,
remove_zeros=True)
# Generate COFFEE
index_names = [(si, name + str(n))
for index, name in zip(argument_indices, ['j', 'k'])
for n, si in enumerate(index)]
if len(quadrature_indices) == 1:
index_names.append((quadrature_indices[0], 'ip'))
else:
for i, quadrature_index in enumerate(quadrature_indices):
index_names.append((quadrature_index, 'ip_%d' % i))
body = generate_coffee(impero_c, index_names, parameters["precision"], ir, flat_argument_indices)
kernel_name = "%s_%s_integral_%s" % (prefix, integral_type, integral_data.subdomain_id)
return builder.construct_kernel(kernel_name, body)
def quadrature_rule(self):
integration_cell = self.fiat_cell.construct_subelement(self.integration_dim)
return make_quadrature(integration_cell, self.quadrature_degree)
def compile_integral(integral_data,
form_data,
prefix,
parameters,
interface=firedrake_interface):
"""Compiles a UFL integral into an assembly kernel.
:arg integral_data: UFL integral data
:arg form_data: UFL form data
:arg prefix: kernel name will start with this string
:arg parameters: parameters object
:arg interface: backend module for the kernel interface
:returns: a kernel constructed by the kernel interface
"""
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# Remove these here, they're handled below.
if parameters.get("quadrature_degree") in [
"auto", "default", None, -1, "-1"
]:
del parameters["quadrature_degree"]
if parameters.get("quadrature_rule") in ["auto", "default", None]:
del parameters["quadrature_rule"]
integral_type = integral_data.integral_type
interior_facet = integral_type.startswith("interior_facet")
mesh = integral_data.domain
cell = integral_data.domain.ufl_cell()
arguments = form_data.preprocessed_form.arguments()
kernel_name = "%s_%s_integral_%s" % (prefix, integral_type,
integral_data.subdomain_id)
fiat_cell = as_fiat_cell(cell)
integration_dim, entity_ids = lower_integral_type(fiat_cell, integral_type)
argument_multiindices = tuple(
create_element(arg.ufl_element()).get_indices() for arg in arguments)
argument_indices = tuple(chain(*argument_multiindices))
quadrature_indices = []
# Dict mapping domains to index in original_form.ufl_domains()
domain_numbering = form_data.original_form.domain_numbering()
builder = interface.KernelBuilder(integral_type,
integral_data.subdomain_id,
domain_numbering[integral_data.domain])
return_variables = builder.set_arguments(arguments, argument_multiindices)
coordinates = ufl_utils.coordinate_coefficient(mesh)
builder.set_coordinates(coordinates)
builder.set_coefficients(integral_data, form_data)
# Map from UFL FiniteElement objects to multiindices. This is
# so we reuse Index instances when evaluating the same coefficient
# multiple times with the same table.
index_cache = {}
kernel_cfg = dict(interface=builder,
ufl_cell=cell,
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
argument_multiindices=argument_multiindices,
index_cache=index_cache)
kernel_cfg["facetarea"] = facetarea_generator(mesh, coordinates,
kernel_cfg, integral_type)
kernel_cfg["cellvolume"] = cellvolume_generator(mesh, coordinates,
kernel_cfg)
mode_irs = collections.OrderedDict()
for integral in integral_data.integrals:
params = parameters.copy()
params.update(integral.metadata()) # integral metadata overrides
if params.get("quadrature_rule") == "default":
del params["quadrature_rule"]
mode = pick_mode(params["mode"])
mode_irs.setdefault(mode, collections.OrderedDict())
integrand = ufl_utils.replace_coordinates(integral.integrand(),
coordinates)
integrand = ufl.replace(integrand, form_data.function_replace_map)
integrand = ufl_utils.split_coefficients(integrand,
builder.coefficient_split)
# Check if the integral has a quad degree attached, otherwise use
# the estimated polynomial degree attached by compute_form_data
quadrature_degree = params.get("quadrature_degree",
params["estimated_polynomial_degree"])
try:
quad_rule = params["quadrature_rule"]
except KeyError:
integration_cell = fiat_cell.construct_subelement(integration_dim)
quad_rule = make_quadrature(integration_cell, quadrature_degree)
if not isinstance(quad_rule, AbstractQuadratureRule):
raise ValueError(
"Expected to find a QuadratureRule object, not a %s" %
type(quad_rule))
quadrature_multiindex = quad_rule.point_set.indices
quadrature_indices.extend(quadrature_multiindex)
config = kernel_cfg.copy()
config.update(quadrature_rule=quad_rule)
expressions = fem.compile_ufl(integrand,
interior_facet=interior_facet,
**config)
reps = mode.Integrals(expressions, quadrature_multiindex,
argument_multiindices, params)
for var, rep in zip(return_variables, reps):
mode_irs[mode].setdefault(var, []).append(rep)
# Finalise mode representations into a set of assignments
assignments = []
for mode, var_reps in iteritems(mode_irs):
assignments.extend(mode.flatten(viewitems(var_reps)))
if assignments:
return_variables, expressions = zip(*assignments)
else:
return_variables = []
expressions = []
# Need optimised roots for COFFEE
options = dict(
reduce(
operator.and_,
[viewitems(mode.finalise_options) for mode in iterkeys(mode_irs)]))
expressions = impero_utils.preprocess_gem(expressions, **options)
assignments = list(zip(return_variables, expressions))
# Look for cell orientations in the IR
if builder.needs_cell_orientations(expressions):
builder.require_cell_orientations()
# Construct ImperoC
index_ordering = tuple(quadrature_indices) + argument_indices
try:
impero_c = impero_utils.compile_gem(assignments,
index_ordering,
remove_zeros=True)
except impero_utils.NoopError:
# No operations, construct empty kernel
return builder.construct_empty_kernel(kernel_name)
# Generate COFFEE
index_names = [(si, name + str(n))
for index, name in zip(argument_multiindices, ['j', 'k'])
for n, si in enumerate(index)]
if len(quadrature_indices) == 1:
index_names.append((quadrature_indices[0], 'ip'))
else:
for i, quadrature_index in enumerate(quadrature_indices):
index_names.append((quadrature_index, 'ip_%d' % i))
# Construct kernel
body = generate_coffee(impero_c, index_names, parameters["precision"],
expressions, argument_indices)
return builder.construct_kernel(kernel_name, body)
def dg_injection_kernel(Vf, Vc, ncell):
from firedrake import Tensor, AssembledVector, TestFunction, TrialFunction
from firedrake.slate.slac import compile_expression
macro_builder = MacroKernelBuilder(ncell)
f = ufl.Coefficient(Vf)
macro_builder.set_coefficients([f])
macro_builder.set_coordinates(Vf.mesh())
Vfe = create_element(Vf.ufl_element())
macro_quadrature_rule = make_quadrature(Vfe.cell, estimate_total_polynomial_degree(ufl.inner(f, f)))
index_cache = {}
parameters = default_parameters()
integration_dim, entity_ids = lower_integral_type(Vfe.cell, "cell")
macro_cfg = dict(interface=macro_builder,
ufl_cell=Vf.ufl_cell(),
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
index_cache=index_cache,
quadrature_rule=macro_quadrature_rule)
fexpr, = fem.compile_ufl(f, **macro_cfg)
X = ufl.SpatialCoordinate(Vf.mesh())
C_a, = fem.compile_ufl(X, **macro_cfg)
detJ = ufl_utils.preprocess_expression(abs(ufl.JacobianDeterminant(f.ufl_domain())))
macro_detJ, = fem.compile_ufl(detJ, **macro_cfg)
Vce = create_element(Vc.ufl_element())
coarse_builder = firedrake_interface.KernelBuilder("cell", "otherwise", 0)
coarse_builder.set_coordinates(Vc.mesh())
argument_multiindices = (Vce.get_indices(), )
argument_multiindex, = argument_multiindices
return_variable, = coarse_builder.set_arguments((ufl.TestFunction(Vc), ), argument_multiindices)
integration_dim, entity_ids = lower_integral_type(Vce.cell, "cell")
# Midpoint quadrature for jacobian on coarse cell.
quadrature_rule = make_quadrature(Vce.cell, 0)
coarse_cfg = dict(interface=coarse_builder,
ufl_cell=Vc.ufl_cell(),
precision=parameters["precision"],
integration_dim=integration_dim,
entity_ids=entity_ids,
index_cache=index_cache,
quadrature_rule=quadrature_rule)
X = ufl.SpatialCoordinate(Vc.mesh())
K = ufl_utils.preprocess_expression(ufl.JacobianInverse(Vc.mesh()))
C_0, = fem.compile_ufl(X, **coarse_cfg)
K, = fem.compile_ufl(K, **coarse_cfg)
i = gem.Index()
j = gem.Index()
C_0 = gem.Indexed(C_0, (j, ))
C_0 = gem.index_sum(C_0, quadrature_rule.point_set.indices)
C_a = gem.Indexed(C_a, (j, ))
X_a = gem.Sum(C_0, gem.Product(gem.Literal(-1), C_a))
K_ij = gem.Indexed(K, (i, j))
K_ij = gem.index_sum(K_ij, quadrature_rule.point_set.indices)
X_a = gem.index_sum(gem.Product(K_ij, X_a), (j, ))
C_0, = quadrature_rule.point_set.points
C_0 = gem.Indexed(gem.Literal(C_0), (i, ))
# fine quad points in coarse reference space.
X_a = gem.Sum(C_0, gem.Product(gem.Literal(-1), X_a))
X_a = gem.ComponentTensor(X_a, (i, ))
# Coarse basis function evaluated at fine quadrature points
phi_c = fem.fiat_to_ufl(Vce.point_evaluation(0, X_a, (Vce.cell.get_dimension(), 0)), 0)
tensor_indices = tuple(gem.Index(extent=d) for d in f.ufl_shape)
phi_c = gem.Indexed(phi_c, argument_multiindex + tensor_indices)
fexpr = gem.Indexed(fexpr, tensor_indices)
quadrature_weight = macro_quadrature_rule.weight_expression
expr = gem.Product(gem.IndexSum(gem.Product(phi_c, fexpr), tensor_indices),
gem.Product(macro_detJ, quadrature_weight))
quadrature_indices = macro_builder.indices + macro_quadrature_rule.point_set.indices
reps = spectral.Integrals([expr], quadrature_indices, argument_multiindices, parameters)
assignments = spectral.flatten([(return_variable, reps)], index_cache)
return_variables, expressions = zip(*assignments)
expressions = impero_utils.preprocess_gem(expressions, **spectral.finalise_options)
assignments = list(zip(return_variables, expressions))
impero_c = impero_utils.compile_gem(assignments, quadrature_indices + argument_multiindex,
remove_zeros=True)
index_names = []
def name_index(index, name):
index_names.append((index, name))
if index in index_cache:
for multiindex, suffix in zip(index_cache[index],
string.ascii_lowercase):
name_multiindex(multiindex, name + suffix)
def name_multiindex(multiindex, name):
if len(multiindex) == 1:
name_index(multiindex[0], name)
else:
for i, index in enumerate(multiindex):
name_index(index, name + str(i))
name_multiindex(quadrature_indices, 'ip')
for multiindex, name in zip(argument_multiindices, ['j', 'k']):
name_multiindex(multiindex, name)
index_names.extend(zip(macro_builder.indices, ["entity"]))
body = generate_coffee(impero_c, index_names, parameters["precision"])
retarg = ast.Decl(SCALAR_TYPE, ast.Symbol("R", rank=(Vce.space_dimension(), )))
local_tensor = coarse_builder.local_tensor
local_tensor.init = ast.ArrayInit(numpy.zeros(Vce.space_dimension(), dtype=SCALAR_TYPE))
body.children.insert(0, local_tensor)
args = [retarg] + macro_builder.kernel_args + [macro_builder.coordinates_arg,
coarse_builder.coordinates_arg]
# Now we have the kernel that computes <f, phi_c>dx_c
# So now we need to hit it with the inverse mass matrix on dx_c
u = TrialFunction(Vc)
v = TestFunction(Vc)
expr = Tensor(ufl.inner(u, v)*ufl.dx).inv * AssembledVector(ufl.Coefficient(Vc))
Ainv, = compile_expression(expr)
Ainv = Ainv.kinfo.kernel
A = ast.Symbol(local_tensor.sym.symbol)
R = ast.Symbol("R")
body.children.append(ast.FunCall(Ainv.name, R, coarse_builder.coordinates_arg.sym, A))
from coffee.base import Node
assert isinstance(Ainv._code, Node)
return op2.Kernel(ast.Node([Ainv._code,
ast.FunDecl("void", "pyop2_kernel_injection_dg", args, body,
pred=["static", "inline"])]),
name="pyop2_kernel_injection_dg",
cpp=True,
include_dirs=Ainv._include_dirs,
headers=Ainv._headers)
def __init__(self, cell, degree, scheme="default"):
self.cell = cell
self._rule = make_quadrature(cell, degree, scheme)
