def compute_integral_ir(itg_data,
form_data,
form_id,
parameters):
"Compute intermediate represention of integral."
info("Computing quadrature representation")
# Initialise representation
ir = initialize_integral_ir("quadrature", itg_data, form_data, form_id)
# Sort integrals into a dict with number of integral points as key
sorted_integrals = _sort_integrals(itg_data.integrals, itg_data.metadata, form_data)
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quad_weights = \
_tabulate_basis(sorted_integrals, itg_data.domain_type, form_data)
# Save tables for quadrature weights and points
ir["quadrature_weights"] = quad_weights
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements]
# Create and save the optisation parameters.
ir["optimise_parameters"] = _parse_optimise_parameters(parameters)
# Create transformer.
if ir["optimise_parameters"]["optimisation"]:
QuadratureTransformerClass = QuadratureTransformerOpt
else:
QuadratureTransformerClass = QuadratureTransformer
transformer = QuadratureTransformerClass(psi_tables,
quad_weights,
form_data.geometric_dimension,
form_data.topological_dimension,
ir["entitytype"],
form_data.function_replace_map,
ir["optimise_parameters"])
# Transform integrals.
ir["trans_integrals"] = _transform_integrals_by_type(ir, transformer, integrals_dict,
itg_data.domain_type, form_data.cell)
# Save tables populated by transformer
ir["name_map"] = transformer.name_map
ir["unique_tables"] = transformer.unique_tables # Basis values?
# Save tables map, to extract table names for optimisation option -O.
ir["psi_tables_map"] = transformer.psi_tables_map
ir["additional_includes_set"] = transformer.additional_includes_set
# Insert empty data which will be populated if optimization is turned on
ir["geo_consts"] = {}
return ir
def compute_integral_ir(itg_data,
form_data,
form_id,
element_numbers,
parameters):
"Compute intermediate represention of integral."
info("Computing tensor representation")
# Extract monomial representation
integrands = [itg.integrand() for itg in itg_data.integrals]
monomial_form = extract_monomial_form(integrands, form_data.function_replace_map)
# Transform monomial form to reference element
transform_monomial_form(monomial_form)
# Get some integral properties
integral_type = itg_data.integral_type
quadrature_degree = itg_data.metadata["quadrature_degree"]
quadrature_rule = itg_data.metadata["quadrature_rule"]
# Get some cell properties
cell = itg_data.domain.ufl_cell()
num_facets = cell.num_facets()
# Helper to simplify code below
compute_terms = lambda i, j: _compute_terms(monomial_form,
i, j,
integral_type,
quadrature_degree,
quadrature_rule,
cell)
# Compute representation of cell tensor
if integral_type == "cell":
# Compute sum of tensor representations
terms = compute_terms(None, None)
elif integral_type == "exterior_facet":
# Compute sum of tensor representations for each facet
terms = [compute_terms(i, None) for i in range(num_facets)]
elif integral_type == "interior_facet":
# Compute sum of tensor representations for each facet-facet pair
terms = [[compute_terms(i, j) for j in range(num_facets)] for i in range(num_facets)]
for i in range(num_facets):
for j in range(num_facets):
reorder_entries(terms[i][j])
else:
error("Unhandled domain type: " + str(integral_type))
# Initialize representation and store terms
ir = initialize_integral_ir("tensor", itg_data, form_data, form_id)
ir["AK"] = terms
return ir
def compute_integral_ir(itg_data, form_data, form_id, parameters):
"Compute intermediate represention of integral."
info("Computing quadrature representation")
# Initialise representation
ir = initialize_integral_ir("quadrature", itg_data, form_data, form_id)
# Sort integrals into a dict with number of integral points as key
sorted_integrals = _sort_integrals(itg_data.integrals, itg_data.metadata,
form_data)
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quad_weights = \
_tabulate_basis(sorted_integrals, itg_data.domain_type, form_data)
# Save tables for quadrature weights and points
ir["quadrature_weights"] = quad_weights
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements
]
# Create and save the optisation parameters.
ir["optimise_parameters"] = _parse_optimise_parameters(parameters)
# Create transformer.
if ir["optimise_parameters"]["optimisation"]:
QuadratureTransformerClass = QuadratureTransformerOpt
else:
QuadratureTransformerClass = QuadratureTransformer
transformer = QuadratureTransformerClass(psi_tables, quad_weights,
form_data.geometric_dimension,
form_data.topological_dimension,
ir["entitytype"],
form_data.function_replace_map,
ir["optimise_parameters"])
# Transform integrals.
ir["trans_integrals"] = _transform_integrals_by_type(
ir, transformer, integrals_dict, itg_data.domain_type, form_data.cell)
# Save tables populated by transformer
ir["name_map"] = transformer.name_map
ir["unique_tables"] = transformer.unique_tables # Basis values?
# Save tables map, to extract table names for optimisation option -O.
ir["psi_tables_map"] = transformer.psi_tables_map
ir["additional_includes_set"] = transformer.additional_includes_set
# Insert empty data which will be populated if optimization is turned on
ir["geo_consts"] = {}
return ir
def compute_integral_ir(itg_data, form_data, form_id, element_numbers,
parameters):
"Compute intermediate represention of integral."
info("Computing tensor representation")
# Extract monomial representation
integrands = [itg.integrand() for itg in itg_data.integrals]
monomial_form = extract_monomial_form(integrands,
form_data.function_replace_map)
# Transform monomial form to reference element
transform_monomial_form(monomial_form)
# Get some integral properties
integral_type = itg_data.integral_type
quadrature_degree = itg_data.metadata["quadrature_degree"]
quadrature_rule = itg_data.metadata["quadrature_rule"]
# Get some cell properties
cell = itg_data.domain.cell()
cellname = cell.cellname()
facet_cellname = cell.facet_cellname()
num_facets = cell.num_facets()
# Helper to simplify code below
compute_terms = lambda i, j: _compute_terms(
monomial_form, i, j, integral_type, quadrature_degree, quadrature_rule,
cellname, facet_cellname)
# Compute representation of cell tensor
if integral_type == "cell":
# Compute sum of tensor representations
terms = compute_terms(None, None)
elif integral_type == "exterior_facet":
# Compute sum of tensor representations for each facet
terms = [compute_terms(i, None) for i in range(num_facets)]
elif integral_type == "interior_facet":
# Compute sum of tensor representations for each facet-facet pair
terms = [[compute_terms(i, j) for j in range(num_facets)]
for i in range(num_facets)]
for i in range(num_facets):
for j in range(num_facets):
reorder_entries(terms[i][j])
else:
error("Unhandled domain type: " + str(integral_type))
# Initialize representation and store terms
ir = initialize_integral_ir("tensor", itg_data, form_data, form_id)
ir["AK"] = terms
return ir
def compute_integral_ir(itg_data, form_data, form_id, element_numbers,
parameters):
"Compute intermediate represention of integral."
info("Computing uflacs representation")
# Initialise representation
ir = initialize_integral_ir("uflacs", itg_data, form_data, form_id)
# Sort integrals into a dict with quadrature degree and rule as key
sorted_integrals = sort_integrals(itg_data.integrals,
itg_data.metadata["quadrature_degree"],
itg_data.metadata["quadrature_rule"])
# TODO: Might want to create the uflacs ir first and then create the tables we need afterwards!
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quadrature_rules = \
tabulate_basis(sorted_integrals, form_data, itg_data)
# Store element numbers, needed for classnames
ir["element_numbers"] = element_numbers
# Delegate to flacs to build its intermediate representation and add to ir
uflacs_ir = compute_uflacs_integral_ir(psi_tables, ir["entitytype"],
integrals_dict, form_data,
parameters)
# Store uflacs generated part separately
ir["uflacs"] = uflacs_ir
# Create and save the optisation parameters # TODO: Define uflacs specific optimization parameters instead
#ir["optimise_parameters"] = parse_optimise_parameters(parameters)
# Save tables for quadrature weights and points
ir["quadrature_rules"] = quadrature_rules
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements
]
# Added for uflacs, not sure if this is the best way to get this:
ir["coeff_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.coefficient_elements
]
return ir
def compute_integral_ir(integral_data, form_data, form_id, element_numbers,
classnames, parameters):
"Compute intermediate represention of integral."
info("Computing tsfc representation")
# Initialise representation
ir = initialize_integral_ir("tsfc", integral_data, form_data, form_id)
# TSFC treats None and unset differently, so remove None values.
parameters = {k: v for k, v in parameters.items() if v is not None}
# Delay TSFC compilation
ir["compile_integral"] = (integral_data, form_data, None, parameters)
return ir
def compute_integral_ir(itg_data,
form_data,
form_id,
element_numbers,
parameters):
"Compute intermediate represention of integral."
info("Computing uflacs representation")
# Initialise representation
ir = initialize_integral_ir("uflacs", itg_data, form_data, form_id)
# Sort integrals into a dict with quadrature degree and rule as key
sorted_integrals = sort_integrals(itg_data.integrals,
itg_data.metadata["quadrature_degree"],
itg_data.metadata["quadrature_rule"])
# TODO: Might want to create the uflacs ir first and then create the tables we need afterwards!
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quadrature_rules = \
tabulate_basis(sorted_integrals, form_data, itg_data)
# Store element numbers, needed for classnames
ir["element_numbers"] = element_numbers
# Delegate to flacs to build its intermediate representation and add to ir
uflacs_ir = compute_uflacs_integral_ir(psi_tables, ir["entitytype"], integrals_dict, form_data, parameters)
# Store uflacs generated part separately
ir["uflacs"] = uflacs_ir
# Create and save the optisation parameters # TODO: Define uflacs specific optimization parameters instead
#ir["optimise_parameters"] = parse_optimise_parameters(parameters)
# Save tables for quadrature weights and points
ir["quadrature_rules"] = quadrature_rules
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements]
# Added for uflacs, not sure if this is the best way to get this:
ir["coeff_idims"] = [create_element(ufl_element).space_dimension()
for ufl_element in form_data.coefficient_elements]
return ir
def compute_integral_ir(itg_data, form_data, form_id, parameters):
"Compute intermediate represention of integral."
info("Computing uflacs representation")
# Initialise representation
ir = initialize_integral_ir("uflacs", itg_data, form_data, form_id)
# Sort integrals into a dict with number of integral points as key
sorted_integrals = _sort_integrals(itg_data.integrals, itg_data.metadata,
form_data)
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quad_weights = \
_tabulate_basis(sorted_integrals, itg_data.domain_type, form_data)
# Save tables for quadrature weights and points
ir["quadrature_weights"] = quad_weights
# Save tables for basis function values
ir["psi_tables"] = psi_tables
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements
]
# Added for uflacs, not sure if this is the best way to get this:
ir["coeff_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.coefficient_elements
]
# Create and save the optisation parameters.
ir["optimise_parameters"] = _parse_optimise_parameters(parameters)
# Delegate to flacs to build its intermediate representation and add to ir
import uflacs.backends.ffc
uir = uflacs.backends.ffc.compute_tabulate_tensor_ir(
ir, integrals_dict, form_data, parameters)
ir.update(uir)
return ir
def compute_integral_ir(integral_data,
form_data,
form_id,
element_numbers,
classnames,
parameters):
"Compute intermediate represention of integral."
info("Computing tsfc representation")
# Initialise representation
ir = initialize_integral_ir("tsfc", integral_data, form_data, form_id)
# TSFC treats None and unset differently, so remove None values.
parameters = {k: v for k, v in parameters.items() if v is not None}
# Delay TSFC compilation
ir["compile_integral"] = (integral_data, form_data, None, parameters)
return ir
def compute_integral_ir(itg_data, form_data, form_id, element_numbers,
parameters):
"Compute intermediate represention of integral."
info("Computing quadrature representation")
# Initialise representation
ir = initialize_integral_ir("quadrature", itg_data, form_data, form_id)
# Create and save the optisation parameters.
ir["optimise_parameters"] = parse_optimise_parameters(parameters, itg_data)
# Sort integrals into a dict with quadrature degree and rule as key
sorted_integrals = sort_integrals(itg_data.integrals,
itg_data.metadata["quadrature_degree"],
itg_data.metadata["quadrature_rule"])
# Tabulate quadrature points and basis function values in these points
integrals_dict, psi_tables, quadrature_rules = \
tabulate_basis(sorted_integrals, form_data, itg_data)
# Save tables for quadrature weights and points
ir["quadrature_weights"] = quadrature_rules # TODO: Rename this ir entry to quadrature_rules
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [
create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements
]
# Select transformer
if ir["optimise_parameters"]["optimisation"] or parameters["pyop2-ir"]:
QuadratureTransformerClass = QuadratureTransformerOpt
else:
QuadratureTransformerClass = QuadratureTransformer
# Create transformer
transformer = QuadratureTransformerClass(
psi_tables, quadrature_rules, itg_data.domain.geometric_dimension(),
itg_data.domain.topological_dimension(), ir["entitytype"],
form_data.function_replace_map, ir["optimise_parameters"], parameters)
# Transform integrals.
cell = itg_data.domain.ufl_cell()
ir["trans_integrals"] = _transform_integrals_by_type(
ir, transformer, integrals_dict, itg_data.integral_type)
# Save tables populated by transformer
ir["name_map"] = transformer.name_map
ir["unique_tables"] = transformer.unique_tables # Basis values?
# Save tables map, to extract table names for optimisation option -O.
ir["psi_tables_map"] = transformer.psi_tables_map
ir["additional_includes_set"] = transformer.additional_includes_set
# Insert empty data which will be populated if optimization is turned on
ir["geo_consts"] = {}
# Add local tensor entry dimensions
ir["tensor_entry_size"] = tuple([1] * form_data.rank)
# Add number of coefficients
ir["num_coefficients"] = form_data.num_coefficients
# Extract element data for psi_tables, needed for runtime quadrature.
# This is used by integral type custom_integral.
ir["element_data"] = _extract_element_data(transformer.element_map,
element_numbers)
return ir
def compute_integral_ir(itg_data,
form_data,
form_id,
element_numbers,
classnames,
parameters):
"Compute intermediate represention of integral."
info("Computing uflacs representation")
# Initialise representation
ir = initialize_integral_ir("uflacs", itg_data, form_data, form_id)
# Store element classnames
ir["classnames"] = classnames
# Get element space dimensions
unique_elements = element_numbers.keys()
ir["element_dimensions"] = { ufl_element: create_element(ufl_element).space_dimension()
for ufl_element in unique_elements }
# Create dimensions of primary indices, needed to reset the argument 'A'
# given to tabulate_tensor() by the assembler.
argument_dimensions = [ir["element_dimensions"][ufl_element]
for ufl_element in form_data.argument_elements]
# Compute shape of element tensor
if ir["integral_type"] == "interior_facet":
ir["tensor_shape"] = [2 * dim for dim in argument_dimensions]
else:
ir["tensor_shape"] = argument_dimensions
integral_type = itg_data.integral_type
cell = itg_data.domain.ufl_cell()
if integral_type in custom_integral_types:
# Set quadrature degree to twice the highest element degree, to get
# enough points to identify basis functions via table computations
max_element_degree = max([1] + [ufl_element.degree() for ufl_element in unique_elements])
rules = [("default", 2*max_element_degree)]
quadrature_integral_type = "cell"
else:
# Collect which quadrature rules occur in integrals
default_scheme = itg_data.metadata["quadrature_degree"]
default_degree = itg_data.metadata["quadrature_rule"]
rules = collect_quadrature_rules(
itg_data.integrals, default_scheme, default_degree)
quadrature_integral_type = integral_type
# Compute actual points and weights
quadrature_rules, quadrature_rule_sizes = compute_quadrature_rules(
rules, quadrature_integral_type, cell)
# Store quadrature rules in format { num_points: (points, weights) }
ir["quadrature_rules"] = quadrature_rules
# Store the fake num_points for analysis in custom integrals
if integral_type in custom_integral_types:
ir["fake_num_points"], = quadrature_rules.keys()
# Group and accumulate integrals on the format { num_points: integral data }
sorted_integrals = accumulate_integrals(itg_data, quadrature_rule_sizes)
# Build coefficient numbering for UFC interface here, to avoid
# renumbering in UFL and application of replace mapping
if True:
# Using the mapped coefficients, numbered by UFL
coefficient_numbering = {}
sorted_coefficients = sorted_by_count(form_data.function_replace_map.keys())
for i, f in enumerate(sorted_coefficients):
g = form_data.function_replace_map[f]
coefficient_numbering[g] = i
assert i == g.count()
# Replace coefficients so they all have proper element and domain for what's to come
# TODO: We can avoid the replace call when proper Expression support is in place
# and element/domain assignment is removed from compute_form_data.
integrands = {
num_points: replace(sorted_integrals[num_points].integrand(), form_data.function_replace_map)
for num_points in sorted(sorted_integrals)
}
else:
pass
#coefficient_numbering = {}
#coefficient_element = {}
#coefficient_domain = {}
#sorted_coefficients = sorted_by_count(form_data.function_replace_map.keys())
#for i, f in enumerate(sorted_coefficients):
# g = form_data.function_replace_map[f]
# coefficient_numbering[f] = i
# coefficient_element[f] = g.ufl_element()
# coefficient_domain[f] = g.ufl_domain()
#integrands = {
# num_points: sorted_integrals[num_points].integrand()
# for num_points in sorted(sorted_integrals)
# }
# then pass coefficient_element and coefficient_domain to the uflacs ir as well
# Build the more uflacs-specific intermediate representation
uflacs_ir = build_uflacs_ir(itg_data.domain.ufl_cell(),
itg_data.integral_type,
ir["entitytype"],
integrands,
ir["tensor_shape"],
coefficient_numbering,
quadrature_rules,
parameters)
ir.update(uflacs_ir)
return ir
def compute_integral_ir(itg_data,
form_data,
form_id,
element_numbers,
classnames,
parameters):
"Compute intermediate represention of integral."
info("Computing quadrature representation")
issue_deprecation_warning()
set_float_formatting(parameters["precision"])
# Initialise representation
ir = initialize_integral_ir("quadrature", itg_data, form_data, form_id)
# Create and save the optisation parameters.
ir["optimise_parameters"] = parse_optimise_parameters(parameters, itg_data)
# Sort integrals into a dict with quadrature degree and rule as
# key
sorted_integrals = sort_integrals(itg_data.integrals,
itg_data.metadata["quadrature_degree"],
itg_data.metadata["quadrature_rule"])
# Tabulate quadrature points and basis function values in these
# points
integrals_dict, psi_tables, quadrature_rules = \
tabulate_basis(sorted_integrals, form_data, itg_data)
# Save tables for quadrature weights and points
ir["quadrature_rules"] = quadrature_rules
# Create dimensions of primary indices, needed to reset the
# argument 'A' given to tabulate_tensor() by the assembler.
ir["prim_idims"] = [create_element(ufl_element).space_dimension()
for ufl_element in form_data.argument_elements]
# Select transformer
if ir["optimise_parameters"]["optimisation"]:
QuadratureTransformerClass = QuadratureTransformerOpt
else:
QuadratureTransformerClass = QuadratureTransformer
# Create transformer
transformer = QuadratureTransformerClass(psi_tables,
quadrature_rules,
itg_data.domain.geometric_dimension(),
itg_data.domain.topological_dimension(),
ir["entitytype"],
form_data.function_replace_map,
ir["optimise_parameters"])
# Transform integrals.
cell = itg_data.domain.ufl_cell()
ir["trans_integrals"] = _transform_integrals_by_type(ir, transformer,
integrals_dict,
itg_data.integral_type,
cell)
# Save tables populated by transformer
ir["name_map"] = transformer.name_map
ir["unique_tables"] = transformer.unique_tables # Basis values?
# Save tables map, to extract table names for optimisation option
# -O.
ir["psi_tables_map"] = transformer.psi_tables_map
ir["additional_includes_set"] = transformer.additional_includes_set
# Insert empty data which will be populated if optimization is
# turned on
ir["geo_consts"] = {}
# Extract element data for psi_tables, needed for runtime
# quadrature. This is used by integral type custom_integral.
ir["element_data"] = _extract_element_data(transformer.element_map, classnames)
return ir
def compute_integral_ir(itg_data,
form_data,
form_id,
parameters):
"Compute intermediate represention of integral."
info("Computing tensor representation")
# Extract monomial representation
monomial_form = extract_monomial_form(itg_data.integrals, form_data.function_replace_map)
# Transform monomial form to reference element
transform_monomial_form(monomial_form)
# Get some cell properties
cell = form_data.cell
cellname = cell.cellname()
facet_cellname = cell.facet_cellname()
num_facets = cellname_to_num_entities[cellname][-2]
# Initialize representation
ir = initialize_integral_ir("tensor", itg_data, form_data, form_id)
ir["rank"] = form_data.rank
# Compute representation of cell tensor
quadrature_degree = itg_data.metadata["quadrature_degree"]
quadrature_rule = itg_data.metadata["quadrature_rule"]
if itg_data.domain_type == "cell":
# Compute sum of tensor representations
ir["AK"] = _compute_terms(monomial_form,
None, None,
itg_data.domain_type,
quadrature_degree,
quadrature_rule,
cellname,
facet_cellname)
elif itg_data.domain_type == "exterior_facet":
# Compute sum of tensor representations for each facet
terms = [None for i in range(num_facets)]
for i in range(num_facets):
terms[i] = _compute_terms(monomial_form,
i, None,
itg_data.domain_type,
quadrature_degree,
quadrature_rule,
cellname,
facet_cellname)
ir["AK"] = terms
elif itg_data.domain_type == "interior_facet":
# Compute sum of tensor representations for each facet-facet pair
terms = [[None for j in range(num_facets)] for i in range(num_facets)]
for i in range(num_facets):
for j in range(num_facets):
terms[i][j] = _compute_terms(monomial_form,
i, j,
itg_data.domain_type,
quadrature_degree,
quadrature_rule,
cellname,
facet_cellname)
reorder_entries(terms[i][j])
ir["AK"] = terms
else:
error("Unhandled domain type: " + str(itg_data.domain_type))
return ir
