GCC Code Coverage Report

Directory: Bembel/src/
File: Laplace/SingleLayerOperator.hpp
Date: 2024-12-18 07:36:36
Exec Total Coverage
Lines: 36 36 100.0%
Functions: 4 4 100.0%
Branches: 38 76 50.0%
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1 // This file is part of Bembel, the higher order C++ boundary element library.
2 //
3 // Copyright (C) 2022 see <http://www.bembel.eu>
4 //
5 // It was written as part of a cooperation of J. Doelz, H. Harbrecht, S. Kurz,
6 // M. Multerer, S. Schoeps, and F. Wolf at Technische Universitaet Darmstadt,
7 // Universitaet Basel, and Universita della Svizzera italiana, Lugano. This
8 // source code is subject to the GNU General Public License version 3 and
9 // provided WITHOUT ANY WARRANTY, see <http://www.bembel.eu> for further
10 // information.
11 //
12 #ifndef BEMBEL_SRC_LAPLACE_SINGLELAYEROPERATOR_HPP_
13 #define BEMBEL_SRC_LAPLACE_SINGLELAYEROPERATOR_HPP_
14
15 namespace Bembel {
16 // forward declaration of class LaplaceSingleLayerOperator in order to define
17 // traits
18 class LaplaceSingleLayerOperator;
19 /**
20 * \brief Specification of the LinerOperatorTraits for Laplace.
21 */
22 template <>
23 struct LinearOperatorTraits<LaplaceSingleLayerOperator> {
24 typedef Eigen::VectorXd EigenType;
25 typedef Eigen::VectorXd::Scalar Scalar;
26 enum {
27 OperatorOrder = -1,
28 Form = DifferentialForm::Discontinuous,
29 NumberOfFMMComponents = 1
30 };
31 };
32
33 /**
34 * \ingroup Laplace
35 * \brief This class implements the specification of the integration for the
36 * single layer operator for Laplace.
37 */
38 class LaplaceSingleLayerOperator
39 : public LinearOperatorBase<LaplaceSingleLayerOperator> {
40 // implementation of the kernel evaluation, which may be based on the
41 // information available from the superSpace
42 public:
43 2 LaplaceSingleLayerOperator() {}
44 template <class T>
45 795097 void evaluateIntegrand_impl(
46 const T &super_space, const SurfacePoint &p1, const SurfacePoint &p2,
47 Eigen::Matrix<
48 typename LinearOperatorTraits<LaplaceSingleLayerOperator>::Scalar,
49 Eigen::Dynamic, Eigen::Dynamic> *intval) const {
50 795097 auto polynomial_degree = super_space.get_polynomial_degree();
51 795097 auto polynomial_degree_plus_one_squared =
52 795097 (polynomial_degree + 1) * (polynomial_degree + 1);
53
54 // get evaluation points on unit square
55
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 795097 auto s = p1.segment<2>(0);
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 795097 auto t = p2.segment<2>(0);
57
58 // get quadrature weights
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 795097 auto ws = p1(2);
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 795097 auto wt = p2(2);
61
62 // get points on geometry and tangential derivatives
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 795097 auto x_f = p1.segment<3>(3);
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 795097 auto x_f_dx = p1.segment<3>(6);
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 795097 auto x_f_dy = p1.segment<3>(9);
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 795097 auto y_f = p2.segment<3>(3);
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 795097 auto y_f_dx = p2.segment<3>(6);
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 795097 auto y_f_dy = p2.segment<3>(9);
69
70 // compute surface measures from tangential derivatives
71
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 795097 auto x_kappa = x_f_dx.cross(x_f_dy).norm();
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 795097 auto y_kappa = y_f_dx.cross(y_f_dy).norm();
73
74 // integrand without basis functions
75
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 795097 auto integrand = evaluateKernel(x_f, y_f) * x_kappa * y_kappa * ws * wt;
76
77 // multiply basis functions with integrand and add to intval, this is an
78 // efficient implementation of
79 // (*intval) += super_space.basisInteraction(s, t) * evaluateKernel(x_f,
80 // y_f)
81 // * x_kappa * y_kappa * ws * wt;
82
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 795097 super_space.addScaledBasisInteraction(intval, integrand, s, t);
83
84 1590194 return;
85 }
86
87 1259712 Eigen::Matrix<double, 1, 1> evaluateFMMInterpolation_impl(
88 const SurfacePoint &p1, const SurfacePoint &p2) const {
89 // get evaluation points on unit square
90
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 1259712 auto s = p1.segment<2>(0);
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 1259712 auto t = p2.segment<2>(0);
92
93 // get points on geometry and tangential derivatives
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 1259712 auto x_f = p1.segment<3>(3);
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 1259712 auto x_f_dx = p1.segment<3>(6);
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 1259712 auto x_f_dy = p1.segment<3>(9);
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 1259712 auto y_f = p2.segment<3>(3);
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 1259712 auto y_f_dx = p2.segment<3>(6);
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 1259712 auto y_f_dy = p2.segment<3>(9);
100
101 // compute surface measures from tangential derivatives
102
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 1259712 auto x_kappa = x_f_dx.cross(x_f_dy).norm();
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 1259712 auto y_kappa = y_f_dx.cross(y_f_dy).norm();
104
105 // interpolation
106
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 1259712 Eigen::Matrix<double, 1, 1> intval;
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 1259712 intval(0) = evaluateKernel(x_f, y_f) * x_kappa * y_kappa;
108
109 2519424 return intval;
110 }
111
112 /**
113 * \brief Fundamental solution of Laplace problem
114 */
115 2054809 double evaluateKernel(const Eigen::Vector3d &x,
116 const Eigen::Vector3d &y) const {
117
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 2054809 return 1. / 4. / BEMBEL_PI / (x - y).norm();
118 }
119 };
120
121 } // namespace Bembel
122 #endif // BEMBEL_SRC_LAPLACE_SINGLELAYEROPERATOR_HPP_
123