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mpi_test_projection_small.cc
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rMUSPECTRE µSpectre
mpi_test_projection_small.cc
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/**
* @file test_projection_small.cc
*
* @author Till Junge <till.junge@altermail.ch>
*
* @date 16 Jan 2018
*
* @brief tests for standard small strain projection operator
*
* Copyright © 2018 Till Junge
*
* µSpectre is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License as
* published by the Free Software Foundation, either version 3, or (at
* your option) any later version.
*
* µSpectre 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
* General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with GNU Emacs; see the file COPYING. If not, write to the
* Free Software Foundation, Inc., 59 Temple Place - Suite 330,
* Boston, MA 02111-1307, USA.
*/
#include "fft/projection_small_strain.hh"
#include "mpi_test_projection.hh"
#include "fft/fft_utils.hh"
#include <Eigen/Dense>
#if 0
namespace muSpectre {
BOOST_AUTO_TEST_SUITE(mpi_projection_small_strain);
using fixlist = boost::mpl::list<
ProjectionFixture<twoD, twoD, Squares<twoD>,
ProjectionSmallStrain<twoD, twoD>>,
ProjectionFixture<threeD, threeD, Squares<threeD>,
ProjectionSmallStrain<threeD, threeD>>,
ProjectionFixture<twoD, twoD, Sizes<twoD>,
ProjectionSmallStrain<twoD, twoD>>,
ProjectionFixture<threeD, threeD, Sizes<threeD>,
ProjectionSmallStrain<threeD, threeD>>>;
/* ---------------------------------------------------------------------- */
BOOST_FIXTURE_TEST_CASE_TEMPLATE(constructor_test, fix, fixlist, fix) {
BOOST_CHECK_NO_THROW(fix::projector.initialise(FFT_PlanFlags::estimate));
}
/* ---------------------------------------------------------------------- */
BOOST_FIXTURE_TEST_CASE_TEMPLATE(Gradient_preservation_test,
fix, fixlist, fix) {
// create a gradient field with a zero mean gradient and verify
// that the projection preserves it
constexpr Dim_t dim{fix::sdim}, sdim{fix::sdim}, mdim{fix::mdim};
static_assert(dim == fix::mdim,
"These tests assume that the material and spatial dimension are "
"identical");
using Fields = GlobalFieldCollection<sdim>;
using FieldT = TensorField<Fields, Real, secondOrder, mdim>;
using FieldMap = MatrixFieldMap<Fields, Real, mdim, mdim>;
using Vector = Eigen::Matrix<Real, dim, 1>;
Fields fields{};
FieldT & f_grad{make_field<FieldT>("strain", fields)};
FieldT & f_var{make_field<FieldT>("working field", fields)};
FieldMap grad(f_grad);
FieldMap var(f_var);
fields.initialise(fix::projector.get_resolutions());
Vector k;
for (Dim_t i = 0; i < dim; ++i) {
// the wave vector has to be such that it leads to an integer
// number of periods in each length of the domain
k(i) = (i+1)*2*pi/fix::projector.get_lengths()[i];
}
for (auto && tup: akantu::zip(fields, grad, var)) {
auto & ccoord = std::get<0>(tup);
auto & g = std::get<1>(tup);
auto & v = std::get<2>(tup);
Vector vec = CcoordOps::get_vector(ccoord,
fix::projector.get_lengths()/
fix::projector.get_resolutions());
g.row(0) << k.transpose() * cos(k.dot(vec));
// We need to add I to the term, because this field has a net
// zero gradient, which leads to a net -I strain
g = 0.5*((g-g.Identity()).transpose() + (g-g.Identity())).eval()+g.Identity();
v = g;
}
fix::projector.initialise(FFT_PlanFlags::estimate);
fix::projector.apply_projection(f_var);
constexpr bool verbose{false};
for (auto && tup: akantu::zip(fields, grad, var)) {
auto & ccoord = std::get<0>(tup);
auto & g = std::get<1>(tup);
auto & v = std::get<2>(tup);
Vector vec = CcoordOps::get_vector(ccoord,
fix::projector.get_lengths()/
fix::projector.get_resolutions());
Real error = (g-v).norm();
BOOST_CHECK_LT(error, tol);
if ((error >=tol) || verbose) {
std::cout << std::endl << "grad_ref :" << std::endl << g << std::endl;
std::cout << std::endl << "grad_proj :" << std::endl << v << std::endl;
std::cout << std::endl << "ccoord :" << std::endl << ccoord << std::endl;
std::cout << std::endl << "vector :" << std::endl << vec.transpose() << std::endl;
std::cout << "means:" << std::endl
<< "<strain>:" << std::endl
<< grad.mean() << std::endl
<< "<proj>:" << std::endl
<< var.mean();
}
}
}
BOOST_AUTO_TEST_SUITE_END();
} // muSpectre
#endif
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