From 549877a827143b3dd6260b8dced526a7db6f94a7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ren=C3=A9=20He=C3=9F?= <rene.hess@iwr.uni-heidelberg.de>
Date: Tue, 20 Sep 2016 10:30:40 +0200
Subject: [PATCH] Create numerical nonlinear jacobian apply methods
---
python/dune/perftool/pdelab/localoperator.py | 36 +++++++++++++-------
1 file changed, 23 insertions(+), 13 deletions(-)
diff --git a/python/dune/perftool/pdelab/localoperator.py b/python/dune/perftool/pdelab/localoperator.py
index 2795d330..592e606b 100644
--- a/python/dune/perftool/pdelab/localoperator.py
+++ b/python/dune/perftool/pdelab/localoperator.py
@@ -433,33 +433,43 @@ def generate_localoperator_kernels(formdata, data):
# Maybe add numerical differentiation
if get_option("numerical_jacobian"):
+ # Include headers for numerical methods
include_file("dune/pdelab/localoperator/defaultimp.hh", filetag="operatorfile")
+ # Numerical jacobian base class
_, loptype = class_type_from_cache("operator")
which = ufl_measure_to_pdelab_measure(measure)
-
- # Numerical jacobian methods
base_class("Dune::PDELab::NumericalJacobian{}<{}>".format(which, loptype), classtag="operator")
- # Add the initializer list for that base class
+ # Numerical jacobian initializer list
ini = name_initree_member()
ini_constructor = name_initree_constructor_param()
-
- # Numerical jacobian methods
initializer_list("Dune::PDELab::NumericalJacobian{}<{}>".format(which, loptype),
["{}.get<double>(\"numerical_epsilon.{}\", 1e-9)".format(ini_constructor, ini, which.lower())],
classtag="operator",
)
+ # In the case of matrix free operator evaluation we need jacobian apply methods
if get_option("matrix_free"):
- # Numeical jacobian apply base class
- base_class("Dune::PDELab::NumericalJacobianApply{}<{}>".format(which, loptype), classtag="operator")
-
- # Numerical jacobian apply initializer list
- initializer_list("Dune::PDELab::NumericalJacobianApply{}<{}>".format(which, loptype),
- ["{}.get<double>(\"numerical_epsilon.{}\", 1e-9)".format(ini_constructor, ini, which.lower())],
- classtag="operator",
- )
+ from dune.perftool.pdelab.driver import is_linear
+ if is_linear(form):
+ # Numeical jacobian apply base class
+ base_class("Dune::PDELab::NumericalJacobianApply{}<{}>".format(which, loptype), classtag="operator")
+
+ # Numerical jacobian apply initializer list
+ initializer_list("Dune::PDELab::NumericalJacobianApply{}<{}>".format(which, loptype),
+ ["{}.get<double>(\"numerical_epsilon.{}\", 1e-9)".format(ini_constructor, ini, which.lower())],
+ classtag="operator",
+ )
+ else:
+ # Numerical nonlinear jacobian apply base class
+ base_class("Dune::PDELab::NumericalNonlinearJacobianApply{}<{}>".format(which, loptype), classtag="operator")
+
+ # Numerical nonlinear jacobian apply initializer list
+ initializer_list("Dune::PDELab::NumericalNonlinearJacobianApply{}<{}>".format(which, loptype),
+ ["{}.get<double>(\"numerical_epsilon.{}\", 1e-9)".format(ini_constructor, ini, which.lower())],
+ classtag="operator",
+ )
operator_kernels[(measure, 'residual')] = kernel
--
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