def facetarea():
from ufl import Measure
assert integral_type != 'cell'
integrand, degree = ufl_utils.one_times(Measure(integral_type, domain=domain))
integrand = ufl_utils.replace_coordinates(integrand, coordinate_coefficient)
config = kernel_config.copy()
config.update(quadrature_degree=degree)
expr, = fem.compile_ufl(integrand, point_sum=True, **config)
return expr
def cellvolume(restriction):
from ufl import dx
integrand, degree = ufl_utils.one_times(dx(domain=domain))
integrand = ufl_utils.replace_coordinates(integrand, coordinate_coefficient)
interface = CellVolumeKernelInterface(kernel_config["interface"], restriction)
config = {k: v for k, v in kernel_config.items()
if k in ["ufl_cell", "precision", "index_cache"]}
config.update(interface=interface, quadrature_degree=degree)
expr, = fem.compile_ufl(integrand, point_sum=True, **config)
return expr
def facetarea():
from ufl import Measure
assert integral_type != 'cell'
integrand, degree = ufl_utils.one_times(Measure(integral_type, domain=domain))
integrand = ufl_utils.replace_coordinates(integrand, coordinate_coefficient)
quadrature_index = gem.Index(name='q')
config = kernel_config.copy()
config.update(quadrature_degree=degree, point_index=quadrature_index)
expr, = fem.compile_ufl(integrand, **config)
if quadrature_index in expr.free_indices:
expr = gem.IndexSum(expr, quadrature_index)
return expr
def cellvolume(restriction):
from ufl import dx
integrand, degree = ufl_utils.one_times(dx(domain=domain))
integrand = ufl_utils.replace_coordinates(integrand, coordinate_coefficient)
interface = CellVolumeKernelInterface(kernel_config["interface"], restriction)
quadrature_index = gem.Index(name='q')
config = {k: v for k, v in kernel_config.items()
if k in ["ufl_cell", "precision", "index_cache"]}
config.update(interface=interface,
quadrature_degree=degree,
point_index=quadrature_index)
expr, = fem.compile_ufl(integrand, **config)
if quadrature_index in expr.free_indices:
expr = gem.IndexSum(expr, quadrature_index)
return expr
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 compile_ufl_kernel(expression, to_pts, to_element, fs):
import collections
from ufl.algorithms.apply_function_pullbacks import apply_function_pullbacks
from ufl.algorithms.apply_algebra_lowering import apply_algebra_lowering
from ufl.algorithms.apply_derivatives import apply_derivatives
from ufl.algorithms.apply_geometry_lowering import apply_geometry_lowering
from ufl.algorithms import extract_arguments, extract_coefficients
from gem import gem, impero_utils
from tsfc import fem, ufl_utils
from tsfc.coffee import generate as generate_coffee
from tsfc.kernel_interface import (KernelBuilderBase,
needs_cell_orientations,
cell_orientations_coffee_arg)
# Imitate the compute_form_data processing pipeline
#
# Unfortunately, we cannot call compute_form_data here, since
# we only have an expression, not a form
expression = apply_algebra_lowering(expression)
expression = apply_derivatives(expression)
expression = apply_function_pullbacks(expression)
expression = apply_geometry_lowering(expression)
expression = apply_derivatives(expression)
expression = apply_geometry_lowering(expression)
expression = apply_derivatives(expression)
# Replace coordinates (if any)
if expression.ufl_domain():
assert fs.mesh() == expression.ufl_domain()
expression = ufl_utils.replace_coordinates(expression, fs.mesh().coordinates)
if extract_arguments(expression):
return ValueError("Cannot interpolate UFL expression with Arguments!")
builder = KernelBuilderBase()
args = []
coefficients = extract_coefficients(expression)
for i, coefficient in enumerate(coefficients):
args.append(builder.coefficient(coefficient, "w_%d" % i))
point_index = gem.Index(name='p')
ir = fem.compile_ufl(expression,
cell=fs.mesh().ufl_cell(),
points=to_pts,
point_index=point_index,
coefficient_mapper=builder.coefficient_mapper)
assert len(ir) == 1
# Deal with non-scalar expressions
tensor_indices = ()
if fs.shape:
tensor_indices = tuple(gem.Index() for s in fs.shape)
ir = [gem.Indexed(ir[0], tensor_indices)]
# Build kernel body
return_var = gem.Variable('A', (len(to_pts),) + fs.shape)
return_expr = gem.Indexed(return_var, (point_index,) + tensor_indices)
impero_c = impero_utils.compile_gem([return_expr], ir, [point_index])
body = generate_coffee(impero_c, index_names={point_index: 'p'})
oriented = needs_cell_orientations(ir)
if oriented:
args.insert(0, cell_orientations_coffee_arg)
# Build kernel
args.insert(0, ast.Decl("double", ast.Symbol('A', rank=(len(to_pts),) + fs.shape)))
kernel_code = builder.construct_kernel("expression_kernel", args, body)
return op2.Kernel(kernel_code, kernel_code.name), oriented, coefficients
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_expression_at_points(expression, points, coordinates, parameters=None):
"""Compiles a UFL expression to be evaluated at compile-time known
reference points. Useful for interpolating UFL expressions onto
function spaces with only point evaluation nodes.
:arg expression: UFL expression
:arg points: reference coordinates of the evaluation points
:arg coordinates: the coordinate function
:arg parameters: parameters object
"""
import coffee.base as ast
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# No arguments, please!
if extract_arguments(expression):
return ValueError("Cannot interpolate UFL expression with Arguments!")
# Apply UFL preprocessing
expression = ufl_utils.preprocess_expression(expression)
# Initialise kernel builder
builder = firedrake_interface.ExpressionKernelBuilder()
# Replace coordinates (if any)
domain = expression.ufl_domain()
if domain:
assert coordinates.ufl_domain() == domain
builder.domain_coordinate[domain] = coordinates
# Collect required coefficients
coefficients = extract_coefficients(expression)
if has_type(expression, GeometricQuantity):
coefficients = [coordinates] + coefficients
builder.set_coefficients(coefficients)
# Split mixed coefficients
expression = ufl_utils.split_coefficients(expression, builder.coefficient_split)
# Translate to GEM
point_set = PointSet(points)
config = dict(interface=builder,
ufl_cell=coordinates.ufl_domain().ufl_cell(),
precision=parameters["precision"],
point_set=point_set)
ir, = fem.compile_ufl(expression, point_sum=False, **config)
# Deal with non-scalar expressions
value_shape = ir.shape
tensor_indices = tuple(gem.Index() for s in value_shape)
if value_shape:
ir = gem.Indexed(ir, tensor_indices)
# Build kernel body
return_shape = (len(points),) + value_shape
return_indices = point_set.indices + tensor_indices
return_var = gem.Variable('A', return_shape)
return_arg = ast.Decl(SCALAR_TYPE, ast.Symbol('A', rank=return_shape))
return_expr = gem.Indexed(return_var, return_indices)
ir, = impero_utils.preprocess_gem([ir])
impero_c = impero_utils.compile_gem([(return_expr, ir)], return_indices)
point_index, = point_set.indices
body = generate_coffee(impero_c, {point_index: 'p'}, parameters["precision"])
# Handle cell orientations
if builder.needs_cell_orientations([ir]):
builder.require_cell_orientations()
# Build kernel tuple
return builder.construct_kernel(return_arg, 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 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 compile_expression_at_points(expression,
points,
coordinates,
interface=None,
parameters=None,
coffee=True):
"""Compiles a UFL expression to be evaluated at compile-time known
reference points. Useful for interpolating UFL expressions onto
function spaces with only point evaluation nodes.
:arg expression: UFL expression
:arg points: reference coordinates of the evaluation points
:arg coordinates: the coordinate function
:arg interface: backend module for the kernel interface
:arg parameters: parameters object
:arg coffee: compile coffee kernel instead of loopy kernel
"""
import coffee.base as ast
import loopy as lp
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# Determine whether in complex mode
complex_mode = is_complex(parameters["scalar_type"])
# Apply UFL preprocessing
expression = ufl_utils.preprocess_expression(expression,
complex_mode=complex_mode)
# Initialise kernel builder
if interface is None:
if coffee:
import tsfc.kernel_interface.firedrake as firedrake_interface_coffee
interface = firedrake_interface_coffee.ExpressionKernelBuilder
else:
# Delayed import, loopy is a runtime dependency
import tsfc.kernel_interface.firedrake_loopy as firedrake_interface_loopy
interface = firedrake_interface_loopy.ExpressionKernelBuilder
builder = interface(parameters["scalar_type"])
arguments = extract_arguments(expression)
argument_multiindices = tuple(
builder.create_element(arg.ufl_element()).get_indices()
for arg in arguments)
# Replace coordinates (if any)
domain = expression.ufl_domain()
if domain:
assert coordinates.ufl_domain() == domain
builder.domain_coordinate[domain] = coordinates
builder.set_cell_sizes(domain)
# Collect required coefficients
coefficients = extract_coefficients(expression)
if has_type(expression, GeometricQuantity) or any(
fem.needs_coordinate_mapping(c.ufl_element())
for c in coefficients):
coefficients = [coordinates] + coefficients
builder.set_coefficients(coefficients)
# Split mixed coefficients
expression = ufl_utils.split_coefficients(expression,
builder.coefficient_split)
# Translate to GEM
point_set = PointSet(points)
config = dict(interface=builder,
ufl_cell=coordinates.ufl_domain().ufl_cell(),
precision=parameters["precision"],
point_set=point_set,
argument_multiindices=argument_multiindices)
ir, = fem.compile_ufl(expression, point_sum=False, **config)
# Deal with non-scalar expressions
value_shape = ir.shape
tensor_indices = tuple(gem.Index() for s in value_shape)
if value_shape:
ir = gem.Indexed(ir, tensor_indices)
# Build kernel body
return_indices = point_set.indices + tensor_indices + tuple(
chain(*argument_multiindices))
return_shape = tuple(i.extent for i in return_indices)
return_var = gem.Variable('A', return_shape)
if coffee:
return_arg = ast.Decl(parameters["scalar_type"],
ast.Symbol('A', rank=return_shape))
else:
return_arg = lp.GlobalArg("A",
dtype=parameters["scalar_type"],
shape=return_shape)
return_expr = gem.Indexed(return_var, return_indices)
ir, = impero_utils.preprocess_gem([ir])
impero_c = impero_utils.compile_gem([(return_expr, ir)], return_indices)
point_index, = point_set.indices
# Handle kernel interface requirements
builder.register_requirements([ir])
# Build kernel tuple
return builder.construct_kernel(return_arg, impero_c,
parameters["precision"],
{point_index: 'p'})
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 compile_expression_dual_evaluation(expression,
to_element,
*,
domain=None,
interface=None,
parameters=None,
coffee=False):
"""Compile a UFL expression to be evaluated against a compile-time known reference element's dual basis.
Useful for interpolating UFL expressions into e.g. N1curl spaces.
:arg expression: UFL expression
:arg to_element: A FInAT element for the target space
:arg domain: optional UFL domain the expression is defined on (required when expression contains no domain).
:arg interface: backend module for the kernel interface
:arg parameters: parameters object
:arg coffee: compile coffee kernel instead of loopy kernel
"""
import coffee.base as ast
import loopy as lp
# Just convert FInAT element to FIAT for now.
# Dual evaluation in FInAT will bring a thorough revision.
to_element = to_element.fiat_equivalent
if any(len(dual.deriv_dict) != 0 for dual in to_element.dual_basis()):
raise NotImplementedError(
"Can only interpolate onto dual basis functionals without derivative evaluation, sorry!"
)
if parameters is None:
parameters = default_parameters()
else:
_ = default_parameters()
_.update(parameters)
parameters = _
# Determine whether in complex mode
complex_mode = is_complex(parameters["scalar_type"])
# Find out which mapping to apply
try:
mapping, = set(to_element.mapping())
except ValueError:
raise NotImplementedError(
"Don't know how to interpolate onto zany spaces, sorry")
expression = apply_mapping(expression, mapping, domain)
# Apply UFL preprocessing
expression = ufl_utils.preprocess_expression(expression,
complex_mode=complex_mode)
# Initialise kernel builder
if interface is None:
if coffee:
import tsfc.kernel_interface.firedrake as firedrake_interface_coffee
interface = firedrake_interface_coffee.ExpressionKernelBuilder
else:
# Delayed import, loopy is a runtime dependency
import tsfc.kernel_interface.firedrake_loopy as firedrake_interface_loopy
interface = firedrake_interface_loopy.ExpressionKernelBuilder
builder = interface(parameters["scalar_type"])
arguments = extract_arguments(expression)
argument_multiindices = tuple(
builder.create_element(arg.ufl_element()).get_indices()
for arg in arguments)
# Replace coordinates (if any) unless otherwise specified by kwarg
if domain is None:
domain = expression.ufl_domain()
assert domain is not None
# Collect required coefficients
first_coefficient_fake_coords = False
coefficients = extract_coefficients(expression)
if has_type(expression, GeometricQuantity) or any(
fem.needs_coordinate_mapping(c.ufl_element())
for c in coefficients):
# Create a fake coordinate coefficient for a domain.
coords_coefficient = ufl.Coefficient(
ufl.FunctionSpace(domain, domain.ufl_coordinate_element()))
builder.domain_coordinate[domain] = coords_coefficient
builder.set_cell_sizes(domain)
coefficients = [coords_coefficient] + coefficients
first_coefficient_fake_coords = True
builder.set_coefficients(coefficients)
# Split mixed coefficients
expression = ufl_utils.split_coefficients(expression,
builder.coefficient_split)
# Translate to GEM
kernel_cfg = dict(
interface=builder,
ufl_cell=domain.ufl_cell(),
# FIXME: change if we ever implement
# interpolation on facets.
integral_type="cell",
argument_multiindices=argument_multiindices,
index_cache={},
scalar_type=parameters["scalar_type"])
if all(
isinstance(dual, PointEvaluation)
for dual in to_element.dual_basis()):
# This is an optimisation for point-evaluation nodes which
# should go away once FInAT offers the interface properly
qpoints = []
# Everything is just a point evaluation.
for dual in to_element.dual_basis():
ptdict = dual.get_point_dict()
qpoint, = ptdict.keys()
(qweight, component), = ptdict[qpoint]
assert allclose(qweight, 1.0)
assert component == ()
qpoints.append(qpoint)
point_set = PointSet(qpoints)
config = kernel_cfg.copy()
config.update(point_set=point_set)
# Allow interpolation onto QuadratureElements to refer to the quadrature
# rule they represent
if isinstance(to_element, FIAT.QuadratureElement):
assert allclose(asarray(qpoints), asarray(to_element._points))
quad_rule = QuadratureRule(point_set, to_element._weights)
config["quadrature_rule"] = quad_rule
expr, = fem.compile_ufl(expression, **config, point_sum=False)
# In some cases point_set.indices may be dropped from expr, but nothing
# new should now appear
assert set(expr.free_indices) <= set(
chain(point_set.indices, *argument_multiindices))
shape_indices = tuple(gem.Index() for _ in expr.shape)
basis_indices = point_set.indices
ir = gem.Indexed(expr, shape_indices)
else:
# This is general code but is more unrolled than necssary.
dual_expressions = [] # one for each functional
broadcast_shape = len(expression.ufl_shape) - len(
to_element.value_shape())
shape_indices = tuple(gem.Index()
for _ in expression.ufl_shape[:broadcast_shape])
expr_cache = {} # Sharing of evaluation of the expression at points
for dual in to_element.dual_basis():
pts = tuple(sorted(dual.get_point_dict().keys()))
try:
expr, point_set = expr_cache[pts]
except KeyError:
point_set = PointSet(pts)
config = kernel_cfg.copy()
config.update(point_set=point_set)
expr, = fem.compile_ufl(expression, **config, point_sum=False)
# In some cases point_set.indices may be dropped from expr, but
# nothing new should now appear
assert set(expr.free_indices) <= set(
chain(point_set.indices, *argument_multiindices))
expr = gem.partial_indexed(expr, shape_indices)
expr_cache[pts] = expr, point_set
weights = collections.defaultdict(list)
for p in pts:
for (w, cmp) in dual.get_point_dict()[p]:
weights[cmp].append(w)
qexprs = gem.Zero()
for cmp in sorted(weights):
qweights = gem.Literal(weights[cmp])
qexpr = gem.Indexed(expr, cmp)
qexpr = gem.index_sum(
gem.Indexed(qweights, point_set.indices) * qexpr,
point_set.indices)
qexprs = gem.Sum(qexprs, qexpr)
assert qexprs.shape == ()
assert set(qexprs.free_indices) == set(
chain(shape_indices, *argument_multiindices))
dual_expressions.append(qexprs)
basis_indices = (gem.Index(), )
ir = gem.Indexed(gem.ListTensor(dual_expressions), basis_indices)
# Build kernel body
return_indices = basis_indices + shape_indices + tuple(
chain(*argument_multiindices))
return_shape = tuple(i.extent for i in return_indices)
return_var = gem.Variable('A', return_shape)
if coffee:
return_arg = ast.Decl(parameters["scalar_type"],
ast.Symbol('A', rank=return_shape))
else:
return_arg = lp.GlobalArg("A",
dtype=parameters["scalar_type"],
shape=return_shape)
return_expr = gem.Indexed(return_var, return_indices)
# TODO: one should apply some GEM optimisations as in assembly,
# but we don't for now.
ir, = impero_utils.preprocess_gem([ir])
impero_c = impero_utils.compile_gem([(return_expr, ir)], return_indices)
index_names = dict(
(idx, "p%d" % i) for (i, idx) in enumerate(basis_indices))
# Handle kernel interface requirements
builder.register_requirements([ir])
# Build kernel tuple
return builder.construct_kernel(return_arg, impero_c, index_names,
first_coefficient_fake_coords)
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(gem.Index(name=name) for arg, name in zip(arguments, ['j', 'k']))
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)
if ufl_utils.is_element_affine(mesh.ufl_coordinate_element()):
# For affine mesh geometries we prefer code generation that
# composes well with optimisations.
builder.set_coordinates(coordinates, mode='list_tensor')
else:
# Otherwise we use the approach that might be faster (?)
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)
# 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"])
integration_cell = fiat_cell.construct_subelement(integration_dim)
quad_rule = params.get("quadrature_rule",
create_quadrature(integration_cell,
quadrature_degree))
if not isinstance(quad_rule, QuadratureRule):
raise ValueError("Expected to find a QuadratureRule object, not a %s" %
type(quad_rule))
integrand = ufl_utils.replace_coordinates(integral.integrand(), coordinates)
integrand = ufl_utils.split_coefficients(integrand, builder.coefficient_split)
quadrature_index = gem.Index(name='ip')
quadrature_indices.append(quadrature_index)
config = kernel_cfg.copy()
config.update(quadrature_rule=quad_rule, point_index=quadrature_index)
ir = fem.compile_ufl(integrand, interior_facet=interior_facet, **config)
if parameters["unroll_indexsum"]:
ir = opt.unroll_indexsum(ir, max_extent=parameters["unroll_indexsum"])
irs.append([(gem.IndexSum(expr, quadrature_index)
if quadrature_index in expr.free_indices
else expr)
for expr in 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 = opt.remove_componenttensors(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) + argument_indices,
remove_zeros=True)
# Generate COFFEE
index_names = [(index, index.name) for index in argument_indices]
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, argument_indices)
kernel_name = "%s_%s_integral_%s" % (prefix, integral_type, integral_data.subdomain_id)
return builder.construct_kernel(kernel_name, body)
