def cell_orientation(self, restriction):
"""Cell orientation as a GEM expression."""
f = {None: 0, '+': 0, '-': 1}[restriction]
# Assume self._cell_orientations tuple is set up at this point.
co_int = self._cell_orientations[f]
return gem.Conditional(
gem.Comparison("==", co_int, gem.Literal(1)), gem.Literal(-1),
gem.Conditional(gem.Comparison("==", co_int, gem.Zero()),
gem.Literal(1), gem.Literal(numpy.nan)))
def basis_evaluation(self, order, ps, entity=None):
'''Return code for evaluating the element at known points on the
reference element.
:param order: return derivatives up to this order.
:param ps: the point set.
:param entity: the cell entity on which to tabulate.
'''
space_dimension = self._element.space_dimension()
value_size = np.prod(self._element.value_shape(), dtype=int)
fiat_result = self._element.tabulate(order, ps.points, entity)
result = {}
for alpha, fiat_table in iteritems(fiat_result):
if isinstance(fiat_table, Exception):
result[alpha] = gem.Failure(
self.index_shape + self.value_shape, fiat_table)
continue
derivative = sum(alpha)
table_roll = fiat_table.reshape(space_dimension, value_size,
len(ps.points)).transpose(1, 2, 0)
exprs = []
for table in table_roll:
if derivative < self.degree:
point_indices = ps.indices
point_shape = tuple(index.extent
for index in point_indices)
exprs.append(
gem.partial_indexed(
gem.Literal(
table.reshape(point_shape + self.index_shape)),
point_indices))
elif derivative == self.degree:
# Make sure numerics satisfies theory
assert np.allclose(table, table.mean(axis=0,
keepdims=True))
exprs.append(gem.Literal(table[0]))
else:
# Make sure numerics satisfies theory
assert np.allclose(table, 0.0)
exprs.append(gem.Zero(self.index_shape))
if self.value_shape:
beta = self.get_indices()
zeta = self.get_value_indices()
result[alpha] = gem.ComponentTensor(
gem.Indexed(
gem.ListTensor(
np.array([
gem.Indexed(expr, beta) for expr in exprs
]).reshape(self.value_shape)), zeta), beta + zeta)
else:
expr, = exprs
result[alpha] = expr
return result
def select_hcurl_transformer(element):
# Assume: something x interval
assert len(element.factors) == 2
assert element.factors[1].cell.get_shape() == LINE
# Globally consistent edge orientations of the reference
# quadrilateral: rightward horizontally, upward vertically.
# Tangential vectors interpret these as the positive direction.
dim = element.cell.get_spatial_dimension()
ks = tuple(fe.formdegree for fe in element.factors)
if element.mapping == "affine":
if ks == (1, 0):
# Can only be 2D. Make the scalar value the
# rightward-pointing tangential on the x-aligned edges.
return lambda v: [v, gem.Zero()]
elif ks == (0, 1):
# Can be any spatial dimension. Make the scalar value the
# upward-pointing tangential.
return lambda v: [gem.Zero()] * (dim - 1) + [v]
else:
assert False
elif element.mapping == "covariant piola":
# Second factor must be continuous interval. Just padding.
return lambda v: [
gem.Indexed(v, (0, )),
gem.Indexed(v, (1, )),
gem.Zero()
]
elif element.mapping == "contravariant piola":
# Second factor must be continuous interval. Rotate the
# 2-vector tangential component on the "base" cell 90 degrees
# clockwise into a 3-vector and pad.
return lambda v: [
gem.Product(gem.Literal(-1), gem.Indexed(v, (1, ))),
gem.Indexed(v, (0, )),
gem.Zero()
]
else:
assert False, "Unexpected original mapping!"
def Integrals(expressions, quadrature_multiindex, argument_multiindices,
parameters):
# Concatenate
expressions = concatenate(expressions)
# Unroll
max_extent = parameters["unroll_indexsum"]
if max_extent:
def predicate(index):
return index.extent <= max_extent
expressions = unroll_indexsum(expressions, predicate=predicate)
# Refactorise
def classify(quadrature_indices, expression):
if not quadrature_indices.intersection(expression.free_indices):
return OTHER
elif isinstance(expression, gem.Indexed) and isinstance(
expression.children[0], gem.Literal):
return ATOMIC
else:
return COMPOUND
classifier = partial(classify, set(quadrature_multiindex))
result = []
for expr, monomial_sum in zip(expressions,
collect_monomials(expressions, classifier)):
# Select quadrature indices that are present
quadrature_indices = set(index for index in quadrature_multiindex
if index in expr.free_indices)
products = []
for sum_indices, factors, rest in monomial_sum:
# Collapse quadrature literals for each monomial
if factors or quadrature_indices:
replacement = einsum(remove_componenttensors(factors),
quadrature_indices)
else:
replacement = gem.Literal(1)
# Rebuild expression
products.append(
gem.IndexSum(gem.Product(replacement, rest), sum_indices))
result.append(reduce(gem.Sum, products, gem.Zero()))
return result
def select_hdiv_transformer(element):
# Assume: something x interval
assert len(element.factors) == 2
assert element.factors[1].cell.get_shape() == LINE
# Globally consistent edge orientations of the reference
# quadrilateral: rightward horizontally, upward vertically.
# Their rotation by 90 degrees anticlockwise is interpreted as the
# positive direction for normal vectors.
ks = tuple(fe.formdegree for fe in element.factors)
if ks == (0, 1):
# Make the scalar value the leftward-pointing normal on the
# y-aligned edges.
return lambda v: [gem.Product(gem.Literal(-1), v), gem.Zero()]
elif ks == (1, 0):
# Make the scalar value the upward-pointing normal on the
# x-aligned edges.
return lambda v: [gem.Zero(), v]
elif ks == (2, 0):
# Same for 3D, so z-plane.
return lambda v: [gem.Zero(), gem.Zero(), v]
elif ks == (1, 1):
if element.mapping == "contravariant piola":
# Pad the 2-vector normal on the "base" cell into a
# 3-vector, maintaining direction.
return lambda v: [
gem.Indexed(v, (0, )),
gem.Indexed(v, (1, )),
gem.Zero()
]
elif element.mapping == "covariant piola":
# Rotate the 2-vector tangential component on the "base"
# cell 90 degrees anticlockwise into a 3-vector and pad.
return lambda v: [
gem.Indexed(v, (1, )),
gem.Product(gem.Literal(-1), gem.Indexed(v, (0, ))),
gem.Zero()
]
else:
assert False, "Unexpected original mapping!"
else:
assert False, "Unexpected form degree combination!"
def basis_evaluation(self,
order,
ps,
entity=None,
coordinate_mapping=None):
'''Return code for evaluating the element at known points on the
reference element.
:param order: return derivatives up to this order.
:param ps: the point set.
:param entity: the cell entity on which to tabulate.
'''
space_dimension = self._element.space_dimension()
value_size = np.prod(self._element.value_shape(), dtype=int)
fiat_result = self._element.tabulate(order, ps.points, entity)
result = {}
# In almost all cases, we have
# self.space_dimension() == self._element.space_dimension()
# But for Bell, FIAT reports 21 basis functions,
# but FInAT only 18 (because there are actually 18
# basis functions, and the additional 3 are for
# dealing with transformations between physical
# and reference space).
index_shape = (self._element.space_dimension(), )
for alpha, fiat_table in fiat_result.items():
if isinstance(fiat_table, Exception):
result[alpha] = gem.Failure(
self.index_shape + self.value_shape, fiat_table)
continue
derivative = sum(alpha)
table_roll = fiat_table.reshape(space_dimension, value_size,
len(ps.points)).transpose(1, 2, 0)
exprs = []
for table in table_roll:
if derivative < self.degree:
point_indices = ps.indices
point_shape = tuple(index.extent
for index in point_indices)
exprs.append(
gem.partial_indexed(
gem.Literal(
table.reshape(point_shape + index_shape)),
point_indices))
elif derivative == self.degree:
# Make sure numerics satisfies theory
exprs.append(gem.Literal(table[0]))
else:
# Make sure numerics satisfies theory
assert np.allclose(table, 0.0)
exprs.append(gem.Zero(self.index_shape))
if self.value_shape:
# As above, this extent may be different from that
# advertised by the finat element.
beta = tuple(gem.Index(extent=i) for i in index_shape)
assert len(beta) == len(self.get_indices())
zeta = self.get_value_indices()
result[alpha] = gem.ComponentTensor(
gem.Indexed(
gem.ListTensor(
np.array([
gem.Indexed(expr, beta) for expr in exprs
]).reshape(self.value_shape)), zeta), beta + zeta)
else:
expr, = exprs
result[alpha] = expr
return result
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 _transform(self, v):
u = [gem.Zero()] * self.size
for j, zeta in enumerate(numpy.ndindex(self.element.value_shape)):
u[self.offset + j] = gem.Indexed(v, zeta)
return u
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 test_listtensor(protocol):
expr = gem.ListTensor([gem.Variable('x', ()), gem.Zero()])
unpickled = pickle.loads(pickle.dumps(expr, protocol))
assert expr == unpickled
