GitHub-Proxy/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-04-19 08:09:36 +08:00
Code Issues Packages Projects Releases Wiki Activity

add a unit test for permutation applied to sparse objects

Browse Source
This commit is contained in:
Gael Guennebaud 2011-10-11 13:45:27 +02:00
parent 3172749f32
commit cd3c2451b6
4 changed files with 155 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
test/CMakeLists.txt
View File

@ -129,6 +129,7 @@ ei_add_test(householder)
ei_add_test(swap)
ei_add_test(conservative_resize)
ei_add_test(permutationmatrices)
ei_add_test(sparse_permutations)
ei_add_test(eigen2support)
ei_add_test(nullary)
ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}")

17
test/main.h
View File

@ -355,6 +355,23 @@ void createRandomPIMatrixOfRank(typename MatrixType::Index desired_rank, typenam
m = qra.householderQ() * d * qrb.householderQ();
}
template<typename PermutationVectorType>
void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size)
{
typedef typename PermutationVectorType::Index Index;
typedef typename PermutationVectorType::Scalar Scalar;
v.resize(size);
for(Index i = 0; i < size; ++i) v(i) = Scalar(i);
if(size == 1) return;
for(Index n = 0; n < 3 * size; ++n)
{
Index i = internal::random<Index>(0, size-1);
Index j;
do j = internal::random<Index>(0, size-1); while(j==i);
std::swap(v(i), v(j));
}
}
} // end namespace Eigen
template<typename T> struct GetDifferentType;

17
test/permutationmatrices.cpp
View File

@ -24,23 +24,6 @@
#include "main.h"
template<typename PermutationVectorType>
void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size)
{
typedef typename PermutationVectorType::Index Index;
typedef typename PermutationVectorType::Scalar Scalar;
v.resize(size);
for(Index i = 0; i < size; ++i) v(i) = Scalar(i);
if(size == 1) return;
for(Index n = 0; n < 3 * size; ++n)
{
Index i = internal::random<Index>(0, size-1);
Index j;
do j = internal::random<Index>(0, size-1); while(j==i);
std::swap(v(i), v(j));
}
}
using namespace std;
template<typename MatrixType> void permutationmatrices(const MatrixType& m)
{

137
test/sparse_permutations.cpp Normal file
View File

@ -0,0 +1,137 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// Eigen 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 3 of the License, or (at your option) any later version.
//
// Alternatively, 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 2 of
// the License, or (at your option) any later version.
//
// Eigen 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 or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse.h"
template<typename SparseMatrixType> void sparse_permutations(const SparseMatrixType& ref)
{
typedef typename SparseMatrixType::Index Index;
const Index rows = ref.rows();
const Index cols = ref.cols();
typedef typename SparseMatrixType::Scalar Scalar;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<int,Dynamic,1> VectorI;
double density = (std::max)(8./(rows*cols), 0.01);
SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols), res;
DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d;
initSparse<Scalar>(density, mat_d, mat, 0);
up = mat.template triangularView<Upper>();
lo = mat.template triangularView<Lower>();
up_sym_d = mat_d.template selfadjointView<Upper>();
lo_sym_d = mat_d.template selfadjointView<Lower>();
VERIFY_IS_APPROX(mat, mat_d);
VERIFY_IS_APPROX(up, DenseMatrix(mat_d.template triangularView<Upper>()));
VERIFY_IS_APPROX(lo, DenseMatrix(mat_d.template triangularView<Lower>()));
PermutationMatrix<Dynamic> p, p_null;
VectorI pi;
randomPermutationVector(pi, cols);
p.indices() = pi;
res = mat.template selfadjointView<Upper>().twistedBy(p_null);
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
res = mat.template selfadjointView<Lower>().twistedBy(p_null);
res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
res = up.template selfadjointView<Upper>().twistedBy(p_null);
res_d = up_sym_d;
VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
res = lo.template selfadjointView<Lower>().twistedBy(p_null);
res_d = lo_sym_d;
VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to upper");
res.template selfadjointView<Upper>() = mat.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to upper");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to lower");
res.template selfadjointView<Lower>() = mat.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to lower");
res.template selfadjointView<Upper>() = up.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to upper");
res.template selfadjointView<Upper>() = lo.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Upper>();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to upper");
res.template selfadjointView<Lower>() = lo.template selfadjointView<Lower>().twistedBy(p);
res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to lower");
res.template selfadjointView<Lower>() = up.template selfadjointView<Upper>().twistedBy(p);
res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView<Lower>();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower");
res = mat.template selfadjointView<Upper>().twistedBy(p);
res_d = (p * up_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full");
res = mat.template selfadjointView<Lower>().twistedBy(p);
res_d = (p * lo_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full");
res = up.template selfadjointView<Upper>().twistedBy(p);
res_d = (p * up_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full");
res = lo.template selfadjointView<Lower>().twistedBy(p);
res_d = (p * lo_sym_d) * p.inverse();
VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full");
}
void test_sparse_permutations()
{
for(int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1,50);
CALL_SUBTEST_1(( sparse_permutations(SparseMatrix<double>(8, 8)) ));
CALL_SUBTEST_2(( sparse_permutations(SparseMatrix<std::complex<double> >(s, s)) ));
CALL_SUBTEST_1(( sparse_permutations(SparseMatrix<double>(s, s)) ));
}
}