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/* The Next Great Finite Element Library. */
/* Copyright (C) 2004 Benjamin S. Kirk, John W. Peterson */
/* This library is free software; you can redistribute it and/or */
/* modify it under the terms of the GNU Lesser General Public */
/* License as published by the Free Software Foundation; either */
/* version 2.1 of the License, or (at your option) any later version. */
/* This library is distributed in the hope that it will be useful, */
/* but WITHOUT ANY WARRANTY; without even the implied warranty of */
/* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU */
/* Lesser General Public License for more details. */
/* You should have received a copy of the GNU Lesser General Public */
/* License along with this library; if not, write to the Free Software */
/* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */
// <h1>Adaptivity Example 3 - Laplace Equation in the L-Shaped Domain</h1>
//
// This example solves the Laplace equation on the classic "L-shaped"
// domain with adaptive mesh refinement. In this case, the exact
// solution is u(r,\theta) = r^{2/3} * \sin ( (2/3) * \theta), but
// the standard Kelly error indicator is used to estimate the error.
// The initial mesh contains three QUAD9 elements which represent the
// standard quadrants I, II, and III of the domain [-1,1]x[-1,1],
// i.e.
// Element 0: [-1,0]x[ 0,1]
// Element 1: [ 0,1]x[ 0,1]
// Element 2: [-1,0]x[-1,0]
// The mesh is provided in the standard libMesh ASCII format file
// named "lshaped.xda". In addition, an input file named "adaptivity_ex3.in"
// is provided which allows the user to set several parameters for
// the solution so that the problem can be re-run without a
// re-compile. The solution technique employed is to have a
// refinement loop with a linear solve inside followed by a
// refinement of the grid and projection of the solution to the new grid
// In the final loop iteration, there is no additional
// refinement after the solve. In the input file "adaptivity_ex3.in",
// the variable "max_r_steps" controls the number of refinement steps,
// "max_r_level" controls the maximum element refinement level, and
// "refine_percentage" / "coarsen_percentage" determine the number of
// elements which will be refined / coarsened at each step.
// LibMesh include files.
#include "libmesh/mesh.h"
#include "libmesh/equation_systems.h"
#include "libmesh/linear_implicit_system.h"
#include "libmesh/exodusII_io.h"
#include "libmesh/tecplot_io.h"
#include "libmesh/fe.h"
#include "libmesh/quadrature_gauss.h"
#include "libmesh/dense_matrix.h"
#include "libmesh/dense_vector.h"
#include "libmesh/sparse_matrix.h"
#include "libmesh/mesh_refinement.h"
#include "libmesh/error_vector.h"
#include "libmesh/exact_error_estimator.h"
#include "libmesh/kelly_error_estimator.h"
#include "libmesh/patch_recovery_error_estimator.h"
#include "libmesh/uniform_refinement_estimator.h"
#include "libmesh/hp_coarsentest.h"
#include "libmesh/hp_singular.h"
#include "libmesh/mesh_generation.h"
#include "libmesh/mesh_modification.h"
#include "libmesh/perf_log.h"
#include "libmesh/getpot.h"
#include "libmesh/exact_solution.h"
#include "libmesh/dof_map.h"
#include "libmesh/numeric_vector.h"
#include "libmesh/elem.h"
#include "libmesh/string_to_enum.h"
// Bring in everything from the libMesh namespace
using namespace libMesh;
// Function prototype. This is the function that will assemble
// the linear system for our Laplace problem. Note that the
// function will take the \p EquationSystems object and the
// name of the system we are assembling as input. From the
// \p EquationSystems object we have acess to the \p Mesh and
// other objects we might need.
void assemble_laplace(EquationSystems& es,
const std::string& system_name);
// Prototype for calculation of the exact solution. Useful
// for setting boundary conditions.
Number exact_solution(const Point& p,
const Parameters&, // EquationSystem parameters, not needed
const std::string&, // sys_name, not needed
const std::string&); // unk_name, not needed);
// Prototype for calculation of the gradient of the exact solution.
Gradient exact_derivative(const Point& p,
const Parameters&, // EquationSystems parameters, not needed
const std::string&, // sys_name, not needed
const std::string&); // unk_name, not needed);
// These are non-const because the input file may change it,
// It is global because our exact_* functions use it.
// Set the dimensionality of the mesh
unsigned int dim = 2;
// Choose whether or not to use the singular solution
bool singularity = true;
int main(int argc, char** argv)
{
// Initialize libMesh.
LibMeshInit init (argc, argv);
// Skip adaptive examples on a non-adaptive libMesh build
#ifndef LIBMESH_ENABLE_AMR
libmesh_example_assert(false, "--enable-amr");
#else
// Parse the input file
GetPot input_file("adaptivity_ex3.in");
// Read in parameters from the input file
const unsigned int max_r_steps = input_file("max_r_steps", 3);
const unsigned int max_r_level = input_file("max_r_level", 3);
const Real refine_percentage = input_file("refine_percentage", 0.5);
const Real coarsen_percentage = input_file("coarsen_percentage", 0.5);
const unsigned int uniform_refine = input_file("uniform_refine",0);
const std::string refine_type = input_file("refinement_type", "h");
const std::string approx_type = input_file("approx_type", "LAGRANGE");
const unsigned int approx_order = input_file("approx_order", 1);
const std::string element_type = input_file("element_type", "tensor");
const int extra_error_quadrature = input_file("extra_error_quadrature", 0);
const int max_linear_iterations = input_file("max_linear_iterations", 5000);
const bool output_intermediate = input_file("output_intermediate", false);
dim = input_file("dimension", 2);
const std::string indicator_type = input_file("indicator_type", "kelly");
singularity = input_file("singularity", true);
// Skip higher-dimensional examples on a lower-dimensional libMesh build
libmesh_example_assert(dim <= LIBMESH_DIM, "2D/3D support");
// Output file for plotting the error as a function of
// the number of degrees of freedom.
std::string approx_name = "";
if (element_type == "tensor")
approx_name += "bi";
if (approx_order == 1)
approx_name += "linear";
else if (approx_order == 2)
approx_name += "quadratic";
else if (approx_order == 3)
approx_name += "cubic";
else if (approx_order == 4)
approx_name += "quartic";
std::string output_file = approx_name;
output_file += "_";
output_file += refine_type;
if (uniform_refine == 0)
output_file += "_adaptive.m";
else
output_file += "_uniform.m";
std::ofstream out (output_file.c_str());
out << "% dofs L2-error H1-error" << std::endl;
out << "e = [" << std::endl;
// Create a mesh.
Mesh mesh;
// Read in the mesh
if (dim == 1)
MeshTools::Generation::build_line(mesh,1,-1.,0.);
else if (dim == 2)
mesh.read("lshaped.xda");
else
mesh.read("lshaped3D.xda");
// Use triangles if the config file says so
if (element_type == "simplex")
MeshTools::Modification::all_tri(mesh);
// We used first order elements to describe the geometry,
// but we may need second order elements to hold the degrees
// of freedom
if (approx_order > 1 || refine_type != "h")
mesh.all_second_order();
// Mesh Refinement object
MeshRefinement mesh_refinement(mesh);
mesh_refinement.refine_fraction() = refine_percentage;
mesh_refinement.coarsen_fraction() = coarsen_percentage;
mesh_refinement.max_h_level() = max_r_level;
// Create an equation systems object.
EquationSystems equation_systems (mesh);
// Declare the system and its variables.
// Creates a system named "Laplace"
LinearImplicitSystem& system =
equation_systems.add_system<LinearImplicitSystem> ("Laplace");
// Adds the variable "u" to "Laplace", using
// the finite element type and order specified
// in the config file
system.add_variable("u", static_cast<Order>(approx_order),
Utility::string_to_enum<FEFamily>(approx_type));
// Give the system a pointer to the matrix assembly
// function.
system.attach_assemble_function (assemble_laplace);
// Initialize the data structures for the equation system.
equation_systems.init();
// Set linear solver max iterations
equation_systems.parameters.set<unsigned int>("linear solver maximum iterations")
= max_linear_iterations;
// Linear solver tolerance.
equation_systems.parameters.set<Real>("linear solver tolerance") =
std::pow(TOLERANCE, 2.5);
// Prints information about the system to the screen.
equation_systems.print_info();
// Construct ExactSolution object and attach solution functions
ExactSolution exact_sol(equation_systems);
exact_sol.attach_exact_value(exact_solution);
exact_sol.attach_exact_deriv(exact_derivative);
// Use higher quadrature order for more accurate error results
exact_sol.extra_quadrature_order(extra_error_quadrature);
// A refinement loop.
for (unsigned int r_step=0; r_step<max_r_steps; r_step++)
{
std::cout << "Beginning Solve " << r_step << std::endl;
// Solve the system "Laplace", just like example 2.
system.solve();
std::cout << "System has: " << equation_systems.n_active_dofs()
<< " degrees of freedom."
<< std::endl;
std::cout << "Linear solver converged at step: "
<< system.n_linear_iterations()
<< ", final residual: "
<< system.final_linear_residual()
<< std::endl;
#ifdef LIBMESH_HAVE_EXODUS_API
// After solving the system write the solution
// to a ExodusII-formatted plot file.
if (output_intermediate)
{
std::ostringstream outfile;
outfile << "lshaped_" << r_step << ".e";
ExodusII_IO (mesh).write_equation_systems (outfile.str(),
equation_systems);
}
#endif // #ifdef LIBMESH_HAVE_EXODUS_API
// Compute the error.
exact_sol.compute_error("Laplace", "u");
// Print out the error values
std::cout << "L2-Error is: "
<< exact_sol.l2_error("Laplace", "u")
<< std::endl;
std::cout << "H1-Error is: "
<< exact_sol.h1_error("Laplace", "u")
<< std::endl;
// Print to output file
out << equation_systems.n_active_dofs() << " "
<< exact_sol.l2_error("Laplace", "u") << " "
<< exact_sol.h1_error("Laplace", "u") << std::endl;
// Possibly refine the mesh
if (r_step+1 != max_r_steps)
{
std::cout << " Refining the mesh..." << std::endl;
if (uniform_refine == 0)
{
// The \p ErrorVector is a particular \p StatisticsVector
// for computing error information on a finite element mesh.
ErrorVector error;
if (indicator_type == "exact")
{
// The \p ErrorEstimator class interrogates a
// finite element solution and assigns to each
// element a positive error value.
// This value is used for deciding which elements to
// refine and which to coarsen.
// For these simple test problems, we can use
// numerical quadrature of the exact error between
// the approximate and analytic solutions.
// However, for real problems, we would need an error
// indicator which only relies on the approximate
// solution.
ExactErrorEstimator error_estimator;
error_estimator.attach_exact_value(exact_solution);
error_estimator.attach_exact_deriv(exact_derivative);
// We optimize in H1 norm, the default
// error_estimator.error_norm = H1;
// Compute the error for each active element using
// the provided indicator. Note in general you
// will need to provide an error estimator
// specifically designed for your application.
error_estimator.estimate_error (system, error);
}
else if (indicator_type == "patch")
{
// The patch recovery estimator should give a
// good estimate of the solution interpolation
// error.
PatchRecoveryErrorEstimator error_estimator;
error_estimator.estimate_error (system, error);
}
else if (indicator_type == "uniform")
{
// Error indication based on uniform refinement
// is reliable, but very expensive.
UniformRefinementEstimator error_estimator;
error_estimator.estimate_error (system, error);
}
else
{
libmesh_assert_equal_to (indicator_type, "kelly");
// The Kelly error estimator is based on
// an error bound for the Poisson problem
// on linear elements, but is useful for
// driving adaptive refinement in many problems
KellyErrorEstimator error_estimator;
error_estimator.estimate_error (system, error);
}
// Write out the error distribution
std::ostringstream ss;
ss << r_step;
#ifdef LIBMESH_HAVE_EXODUS_API
std::string error_output = "error_"+ss.str()+".e";
#else
std::string error_output = "error_"+ss.str()+".gmv";
#endif
error.plot_error( error_output, mesh );
// This takes the error in \p error and decides which elements
// will be coarsened or refined. Any element within 20% of the
// maximum error on any element will be refined, and any
// element within 10% of the minimum error on any element might
// be coarsened. Note that the elements flagged for refinement
// will be refined, but those flagged for coarsening _might_ be
// coarsened.
mesh_refinement.flag_elements_by_error_fraction (error);
// If we are doing adaptive p refinement, we want
// elements flagged for that instead.
if (refine_type == "p")
mesh_refinement.switch_h_to_p_refinement();
// If we are doing "matched hp" refinement, we
// flag elements for both h and p
if (refine_type == "matchedhp")
mesh_refinement.add_p_to_h_refinement();
// If we are doing hp refinement, we
// try switching some elements from h to p
if (refine_type == "hp")
{
HPCoarsenTest hpselector;
hpselector.select_refinement(system);
}
// If we are doing "singular hp" refinement, we
// try switching most elements from h to p
if (refine_type == "singularhp")
{
// This only differs from p refinement for
// the singular problem
libmesh_assert (singularity);
HPSingularity hpselector;
// Our only singular point is at the origin
hpselector.singular_points.push_back(Point());
hpselector.select_refinement(system);
}
// This call actually refines and coarsens the flagged
// elements.
mesh_refinement.refine_and_coarsen_elements();
}
else if (uniform_refine == 1)
{
if (refine_type == "h" || refine_type == "hp" ||
refine_type == "matchedhp")
mesh_refinement.uniformly_refine(1);
if (refine_type == "p" || refine_type == "hp" ||
refine_type == "matchedhp")
mesh_refinement.uniformly_p_refine(1);
}
// This call reinitializes the \p EquationSystems object for
// the newly refined mesh. One of the steps in the
// reinitialization is projecting the \p solution,
// \p old_solution, etc... vectors from the old mesh to
// the current one.
equation_systems.reinit ();
}
}
#ifdef LIBMESH_HAVE_EXODUS_API
// Write out the solution
// After solving the system write the solution
// to a ExodusII-formatted plot file.
ExodusII_IO (mesh).write_equation_systems ("lshaped.e",
equation_systems);
#endif // #ifdef LIBMESH_HAVE_EXODUS_API
// Close up the output file.
out << "];" << std::endl;
out << "hold on" << std::endl;
out << "plot(e(:,1), e(:,2), 'bo-');" << std::endl;
out << "plot(e(:,1), e(:,3), 'ro-');" << std::endl;
// out << "set(gca,'XScale', 'Log');" << std::endl;
// out << "set(gca,'YScale', 'Log');" << std::endl;
out << "xlabel('dofs');" << std::endl;
out << "title('" << approx_name << " elements');" << std::endl;
out << "legend('L2-error', 'H1-error');" << std::endl;
// out << "disp('L2-error linear fit');" << std::endl;
// out << "polyfit(log10(e(:,1)), log10(e(:,2)), 1)" << std::endl;
// out << "disp('H1-error linear fit');" << std::endl;
// out << "polyfit(log10(e(:,1)), log10(e(:,3)), 1)" << std::endl;
#endif // #ifndef LIBMESH_ENABLE_AMR
// All done.
return 0;
}
// We now define the exact solution, being careful
// to obtain an angle from atan2 in the correct
// quadrant.
Number exact_solution(const Point& p,
const Parameters&, // parameters, not needed
const std::string&, // sys_name, not needed
const std::string&) // unk_name, not needed
{
const Real x = p(0);
const Real y = (dim > 1) ? p(1) : 0.;
if (singularity)
{
// The exact solution to the singular problem,
// u_exact = r^(2/3)*sin(2*theta/3).
Real theta = atan2(y,x);
// Make sure 0 <= theta <= 2*pi
if (theta < 0)
theta += 2. * libMesh::pi;
// Make the 3D solution similar
const Real z = (dim > 2) ? p(2) : 0;
return pow(x*x + y*y, 1./3.)*sin(2./3.*theta) + z;
}
else
{
// The exact solution to a nonsingular problem,
// good for testing ideal convergence rates
const Real z = (dim > 2) ? p(2) : 0;
return cos(x) * exp(y) * (1. - z);
}
}
// We now define the gradient of the exact solution, again being careful
// to obtain an angle from atan2 in the correct
// quadrant.
Gradient exact_derivative(const Point& p,
const Parameters&, // parameters, not needed
const std::string&, // sys_name, not needed
const std::string&) // unk_name, not needed
{
// Gradient value to be returned.
Gradient gradu;
// x and y coordinates in space
const Real x = p(0);
const Real y = dim > 1 ? p(1) : 0.;
if (singularity)
{
// We can't compute the gradient at x=0, it is not defined.
libmesh_assert_not_equal_to (x, 0.);
// For convenience...
const Real tt = 2./3.;
const Real ot = 1./3.;
// The value of the radius, squared
const Real r2 = x*x + y*y;
// The boundary value, given by the exact solution,
// u_exact = r^(2/3)*sin(2*theta/3).
Real theta = atan2(y,x);
// Make sure 0 <= theta <= 2*pi
if (theta < 0)
theta += 2. * libMesh::pi;
// du/dx
gradu(0) = tt*x*pow(r2,-tt)*sin(tt*theta) - pow(r2,ot)*cos(tt*theta)*tt/(1.+y*y/x/x)*y/x/x;
// du/dy
if (dim > 1)
gradu(1) = tt*y*pow(r2,-tt)*sin(tt*theta) + pow(r2,ot)*cos(tt*theta)*tt/(1.+y*y/x/x)*1./x;
if (dim > 2)
gradu(2) = 1.;
}
else
{
const Real z = (dim > 2) ? p(2) : 0;
gradu(0) = -sin(x) * exp(y) * (1. - z);
if (dim > 1)
gradu(1) = cos(x) * exp(y) * (1. - z);
if (dim > 2)
gradu(2) = -cos(x) * exp(y);
}
return gradu;
}
// We now define the matrix assembly function for the
// Laplace system. We need to first compute element
// matrices and right-hand sides, and then take into
// account the boundary conditions, which will be handled
// via a penalty method.
void assemble_laplace(EquationSystems& es,
const std::string& system_name)
{
#ifdef LIBMESH_ENABLE_AMR
// It is a good idea to make sure we are assembling
// the proper system.
libmesh_assert_equal_to (system_name, "Laplace");
// Declare a performance log. Give it a descriptive
// string to identify what part of the code we are
// logging, since there may be many PerfLogs in an
// application.
PerfLog perf_log ("Matrix Assembly",false);
// Get a constant reference to the mesh object.
const MeshBase& mesh = es.get_mesh();
// The dimension that we are running
const unsigned int dim = mesh.mesh_dimension();
// Get a reference to the LinearImplicitSystem we are solving
LinearImplicitSystem& system = es.get_system<LinearImplicitSystem>("Laplace");
// A reference to the \p DofMap object for this system. The \p DofMap
// object handles the index translation from node and element numbers
// to degree of freedom numbers. We will talk more about the \p DofMap
// in future examples.
const DofMap& dof_map = system.get_dof_map();
// Get a constant reference to the Finite Element type
// for the first (and only) variable in the system.
FEType fe_type = dof_map.variable_type(0);
// Build a Finite Element object of the specified type. Since the
// \p FEBase::build() member dynamically creates memory we will
// store the object as an \p AutoPtr<FEBase>. This can be thought
// of as a pointer that will clean up after itself.
AutoPtr<FEBase> fe (FEBase::build(dim, fe_type));
AutoPtr<FEBase> fe_face (FEBase::build(dim, fe_type));
// Quadrature rules for numerical integration.
AutoPtr<QBase> qrule(fe_type.default_quadrature_rule(dim));
AutoPtr<QBase> qface(fe_type.default_quadrature_rule(dim-1));
// Tell the finite element object to use our quadrature rule.
fe->attach_quadrature_rule (qrule.get());
fe_face->attach_quadrature_rule (qface.get());
// Here we define some references to cell-specific data that
// will be used to assemble the linear system.
// We begin with the element Jacobian * quadrature weight at each
// integration point.
const std::vector<Real>& JxW = fe->get_JxW();
const std::vector<Real>& JxW_face = fe_face->get_JxW();
// The physical XY locations of the quadrature points on the element.
// These might be useful for evaluating spatially varying material
// properties or forcing functions at the quadrature points.
const std::vector<Point>& q_point = fe->get_xyz();
// The element shape functions evaluated at the quadrature points.
// For this simple problem we usually only need them on element
// boundaries.
const std::vector<std::vector<Real> >& phi = fe->get_phi();
const std::vector<std::vector<Real> >& psi = fe_face->get_phi();
// The element shape function gradients evaluated at the quadrature
// points.
const std::vector<std::vector<RealGradient> >& dphi = fe->get_dphi();
// The XY locations of the quadrature points used for face integration
const std::vector<Point>& qface_points = fe_face->get_xyz();
// Define data structures to contain the element matrix
// and right-hand-side vector contribution. Following
// basic finite element terminology we will denote these
// "Ke" and "Fe". More detail is in example 3.
DenseMatrix<Number> Ke;
DenseVector<Number> Fe;
// This vector will hold the degree of freedom indices for
// the element. These define where in the global system
// the element degrees of freedom get mapped.
std::vector<unsigned int> dof_indices;
// Now we will loop over all the elements in the mesh. We will
// compute the element matrix and right-hand-side contribution. See
// example 3 for a discussion of the element iterators. Here we use
// the \p const_active_local_elem_iterator to indicate we only want
// to loop over elements that are assigned to the local processor
// which are "active" in the sense of AMR. This allows each
// processor to compute its components of the global matrix for
// active elements while ignoring parent elements which have been
// refined.
MeshBase::const_element_iterator el = mesh.active_local_elements_begin();
const MeshBase::const_element_iterator end_el = mesh.active_local_elements_end();
for ( ; el != end_el; ++el)
{
// Start logging the shape function initialization.
// This is done through a simple function call with
// the name of the event to log.
perf_log.push("elem init");
// Store a pointer to the element we are currently
// working on. This allows for nicer syntax later.
const Elem* elem = *el;
// Get the degree of freedom indices for the
// current element. These define where in the global
// matrix and right-hand-side this element will
// contribute to.
dof_map.dof_indices (elem, dof_indices);
// Compute the element-specific data for the current
// element. This involves computing the location of the
// quadrature points (q_point) and the shape functions
// (phi, dphi) for the current element.
fe->reinit (elem);
// Zero the element matrix and right-hand side before
// summing them. We use the resize member here because
// the number of degrees of freedom might have changed from
// the last element. Note that this will be the case if the
// element type is different (i.e. the last element was a
// triangle, now we are on a quadrilateral).
Ke.resize (dof_indices.size(),
dof_indices.size());
Fe.resize (dof_indices.size());
// Stop logging the shape function initialization.
// If you forget to stop logging an event the PerfLog
// object will probably catch the error and abort.
perf_log.pop("elem init");
// Now we will build the element matrix. This involves
// a double loop to integrate the test funcions (i) against
// the trial functions (j).
//
// Now start logging the element matrix computation
perf_log.push ("Ke");
for (unsigned int qp=0; qp<qrule->n_points(); qp++)
for (unsigned int i=0; i<dphi.size(); i++)
for (unsigned int j=0; j<dphi.size(); j++)
Ke(i,j) += JxW[qp]*(dphi[i][qp]*dphi[j][qp]);
// We need a forcing function to make the 1D case interesting
if (dim == 1)
for (unsigned int qp=0; qp<qrule->n_points(); qp++)
{
Real x = q_point[qp](0);
Real f = singularity ? sqrt(3.)/9.*pow(-x, -4./3.) :
cos(x);
for (unsigned int i=0; i<dphi.size(); ++i)
Fe(i) += JxW[qp]*phi[i][qp]*f;
}
// Stop logging the matrix computation
perf_log.pop ("Ke");
// At this point the interior element integration has
// been completed. However, we have not yet addressed
// boundary conditions. For this example we will only
// consider simple Dirichlet boundary conditions imposed
// via the penalty method.
//
// This approach adds the L2 projection of the boundary
// data in penalty form to the weak statement. This is
// a more generic approach for applying Dirichlet BCs
// which is applicable to non-Lagrange finite element
// discretizations.
{
// Start logging the boundary condition computation
perf_log.push ("BCs");
// The penalty value.
const Real penalty = 1.e10;
// The following loops over the sides of the element.
// If the element has no neighbor on a side then that
// side MUST live on a boundary of the domain.
for (unsigned int s=0; s<elem->n_sides(); s++)
if (elem->neighbor(s) == NULL)
{
fe_face->reinit(elem,s);
for (unsigned int qp=0; qp<qface->n_points(); qp++)
{
const Number value = exact_solution (qface_points[qp],
es.parameters,
"null",
"void");
// RHS contribution
for (unsigned int i=0; i<psi.size(); i++)
Fe(i) += penalty*JxW_face[qp]*value*psi[i][qp];
// Matrix contribution
for (unsigned int i=0; i<psi.size(); i++)
for (unsigned int j=0; j<psi.size(); j++)
Ke(i,j) += penalty*JxW_face[qp]*psi[i][qp]*psi[j][qp];
}
}
// Stop logging the boundary condition computation
perf_log.pop ("BCs");
}
// The element matrix and right-hand-side are now built
// for this element. Add them to the global matrix and
// right-hand-side vector. The \p SparseMatrix::add_matrix()
// and \p NumericVector::add_vector() members do this for us.
// Start logging the insertion of the local (element)
// matrix and vector into the global matrix and vector
perf_log.push ("matrix insertion");
dof_map.constrain_element_matrix_and_vector(Ke, Fe, dof_indices);
system.matrix->add_matrix (Ke, dof_indices);
system.rhs->add_vector (Fe, dof_indices);
// Start logging the insertion of the local (element)
// matrix and vector into the global matrix and vector
perf_log.pop ("matrix insertion");
}
// That's it. We don't need to do anything else to the
// PerfLog. When it goes out of scope (at this function return)
// it will print its log to the screen. Pretty easy, huh?
#endif // #ifdef LIBMESH_ENABLE_AMR
}
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