From b9a473dcb4f2b2b014a603129edffca0c1d10369 Mon Sep 17 00:00:00 2001
From: Dominic Kempf <dominic.kempf@iwr.uni-heidelberg.de>
Date: Wed, 12 Oct 2016 10:27:06 +0200
Subject: [PATCH] Fix neumann boundary poisson and symdiff
---
python/dune/perftool/pdelab/localoperator.py | 90 ++++++++++---------
.../extract_accumulation_terms.py | 3 +-
2 files changed, 50 insertions(+), 43 deletions(-)
diff --git a/python/dune/perftool/pdelab/localoperator.py b/python/dune/perftool/pdelab/localoperator.py
index 77cebcf0..006685f1 100644
--- a/python/dune/perftool/pdelab/localoperator.py
+++ b/python/dune/perftool/pdelab/localoperator.py
@@ -267,10 +267,14 @@ class AccumulationSpace(Record):
return (self.restriction,)
-def determine_accumulation_space(expr, number):
+def determine_accumulation_space(expr, number, measure):
from dune.perftool.ufl.modified_terminals import extract_modified_arguments
args = extract_modified_arguments(expr, argnumber=number)
+ if measure == 'exterior_facet':
+ for ma in args:
+ ma.restriction = Restriction.NEGATIVE
+
# If this is a residual term we return a dummy object
if len(args) == 0:
return AccumulationSpace()
@@ -308,42 +312,44 @@ def determine_accumulation_space(expr, number):
)
-def boundary_predicates():
- # # Maybe wrap this instruction into a condiditional. This mostly happens with mixed boundary conditions
- # if self.subdomain_id not in ['everywhere', 'otherwise']:
- # # We need to reconstruct the subdomain_data parameter of the measure
- # # I am *totally* confused as to why this information is not at hand anyway,
- # # but conversation with Martin pointed me to dolfin.fem.assembly where this
- # # is done in preprocessing with the limitation of only one possible type of
- # # modified measure per integral type.
- #
- # # Get the original form and inspect the present measures
- # from dune.perftool.generation import get_global_context_value
- # original_form = get_global_context_value("formdata").original_form
- #
- # sd = original_form.subdomain_data()
- # assert len(sd) == 1
- # subdomains, = list(sd.values())
- # domain, = list(sd.keys())
- # for k in list(subdomains.keys()):
- # if subdomains[k] is None:
- # del subdomains[k]
- #
- # # Finally extract the original subdomain_data (which needs to be present!)
- # assert self.measure in subdomains
- # subdomain_data = subdomains[self.measure]
- #
- # # Determine the name of the parameter function
- # name = get_global_context_value("data").object_names[id(subdomain_data)]
- #
- # # Trigger the generation of code for this thing in the parameter class
- # from ufl.checks import is_cellwise_constant
- # cellwise_constant = is_cellwise_constant(o)
- # from dune.perftool.pdelab.parameter import intersection_parameter_function
- # intersection_parameter_function(name, subdomain_data, cellwise_constant, t='int')
- #
- # predicates = predicates.union(['{} == {}'.format(name, self.subdomain_id)])
- return frozenset([])
+def boundary_predicates(expr, measure, subdomain_id):
+ predicates = frozenset([])
+
+ if subdomain_id not in ['everywhere', 'otherwise']:
+ # We need to reconstruct the subdomain_data parameter of the measure
+ # I am *totally* confused as to why this information is not at hand anyway,
+ # but conversation with Martin pointed me to dolfin.fem.assembly where this
+ # is done in preprocessing with the limitation of only one possible type of
+ # modified measure per integral type.
+
+ # Get the original form and inspect the present measures
+ from dune.perftool.generation import get_global_context_value
+ original_form = get_global_context_value("formdata").original_form
+
+ sd = original_form.subdomain_data()
+ assert len(sd) == 1
+ subdomains, = list(sd.values())
+ domain, = list(sd.keys())
+ for k in list(subdomains.keys()):
+ if subdomains[k] is None:
+ del subdomains[k]
+
+ # Finally extract the original subdomain_data (which needs to be present!)
+ assert measure in subdomains
+ subdomain_data = subdomains[measure]
+
+ # Determine the name of the parameter function
+ name = get_global_context_value("data").object_names[id(subdomain_data)]
+
+ # Trigger the generation of code for this thing in the parameter class
+ from ufl.checks import is_cellwise_constant
+ cellwise_constant = is_cellwise_constant(expr)
+ from dune.perftool.pdelab.parameter import intersection_parameter_function
+ intersection_parameter_function(name, subdomain_data, cellwise_constant, t='int')
+
+ predicates = predicates.union(['{} == {}'.format(name, subdomain_id)])
+
+ return predicates
@iname
@@ -355,7 +361,7 @@ def grad_iname(ma):
return name
-def generate_accumulation_instruction(visitor, accterm):
+def generate_accumulation_instruction(visitor, accterm, measure, subdomain_id):
# First we do the tree traversal to get a pymbolic expression representing this expression
pymbolic_expr = visitor(accterm.term)
@@ -376,14 +382,14 @@ def generate_accumulation_instruction(visitor, accterm):
pymbolic_expr = Product((pymbolic_expr, test_expr))
# Collect the lfs and lfs indices for the accumulate call
- test_lfs = determine_accumulation_space(accterm.argument.expr, 0)
+ test_lfs = determine_accumulation_space(accterm.argument.expr, 0, measure)
# In the jacobian case, also determine the space for the ansatz space
- ansatz_lfs = determine_accumulation_space(accterm.term, 1)
+ ansatz_lfs = determine_accumulation_space(accterm.term, 1, measure)
from dune.perftool.pdelab.argument import name_accumulation_variable
accumvar = name_accumulation_variable((ansatz_lfs.get_restriction() + test_lfs.get_restriction()))
- predicates = boundary_predicates()
+ predicates = boundary_predicates(accterm.term, measure, subdomain_id)
rank = 1 if ansatz_lfs.lfs is None else 2
@@ -447,7 +453,7 @@ def generate_kernel(integrals):
# Iterate over the terms and generate a kernel
for term in accterms:
- generate_accumulation_instruction(visitor, term)
+ generate_accumulation_instruction(visitor, term, measure, subdomain_id)
# Extract the information, which is needed to create a loopy kernel.
# First extracting it, might be useful to alter it before kernel generation.
diff --git a/python/dune/perftool/ufl/transformations/extract_accumulation_terms.py b/python/dune/perftool/ufl/transformations/extract_accumulation_terms.py
index c16b19fe..3fe9d182 100644
--- a/python/dune/perftool/ufl/transformations/extract_accumulation_terms.py
+++ b/python/dune/perftool/ufl/transformations/extract_accumulation_terms.py
@@ -58,7 +58,8 @@ def split_into_accumulation_terms(expr):
# 4) Further split according to trial function in jacobian terms
if all_jacobian_args:
for jac_arg in all_jacobian_args:
- pass
+ if not isinstance(replace_expr, Zero):
+ ret.append(AccumulationTerm(replace_expr, test_arg))
else:
if not isinstance(replace_expr, Zero):
ret.append(AccumulationTerm(replace_expr, test_arg))
--
GitLab