You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
148 lines
5.2 KiB
148 lines
5.2 KiB
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
|
|
//
|
|
// This Source Code Form is subject to the terms of the Mozilla
|
|
// Public License v. 2.0. If a copy of the MPL was not distributed
|
|
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
|
|
|
|
|
|
// import basic and product tests for deprectaed DynamicSparseMatrix
|
|
#define EIGEN_NO_DEPRECATED_WARNING
|
|
#include "sparse_basic.cpp"
|
|
#include "sparse_product.cpp"
|
|
#include <Eigen/SparseExtra>
|
|
|
|
template<typename SetterType,typename DenseType, typename Scalar, int Options>
|
|
bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
|
|
{
|
|
{
|
|
sm.setZero();
|
|
SetterType w(sm);
|
|
std::vector<Vector2i> remaining = nonzeroCoords;
|
|
while(!remaining.empty())
|
|
{
|
|
int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
|
|
w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
|
|
remaining[i] = remaining.back();
|
|
remaining.pop_back();
|
|
}
|
|
}
|
|
return sm.isApprox(ref);
|
|
}
|
|
|
|
template<typename SetterType,typename DenseType, typename T>
|
|
bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
|
|
{
|
|
sm.setZero();
|
|
std::vector<Vector2i> remaining = nonzeroCoords;
|
|
while(!remaining.empty())
|
|
{
|
|
int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
|
|
sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
|
|
remaining[i] = remaining.back();
|
|
remaining.pop_back();
|
|
}
|
|
return sm.isApprox(ref);
|
|
}
|
|
|
|
template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& ref)
|
|
{
|
|
const Index rows = ref.rows();
|
|
const Index cols = ref.cols();
|
|
typedef typename SparseMatrixType::Scalar Scalar;
|
|
enum { Flags = SparseMatrixType::Flags };
|
|
|
|
double density = (std::max)(8./(rows*cols), 0.01);
|
|
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
|
|
typedef Matrix<Scalar,Dynamic,1> DenseVector;
|
|
Scalar eps = 1e-6;
|
|
|
|
SparseMatrixType m(rows, cols);
|
|
DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
|
|
DenseVector vec1 = DenseVector::Random(rows);
|
|
|
|
std::vector<Vector2i> zeroCoords;
|
|
std::vector<Vector2i> nonzeroCoords;
|
|
initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
|
|
|
|
if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
|
|
return;
|
|
|
|
// test coeff and coeffRef
|
|
for (int i=0; i<(int)zeroCoords.size(); ++i)
|
|
{
|
|
VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
|
|
if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
|
|
VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
|
|
}
|
|
VERIFY_IS_APPROX(m, refMat);
|
|
|
|
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
|
|
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
|
|
|
|
VERIFY_IS_APPROX(m, refMat);
|
|
|
|
// random setter
|
|
// {
|
|
// m.setZero();
|
|
// VERIFY_IS_NOT_APPROX(m, refMat);
|
|
// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
|
|
// std::vector<Vector2i> remaining = nonzeroCoords;
|
|
// while(!remaining.empty())
|
|
// {
|
|
// int i = internal::random<int>(0,remaining.size()-1);
|
|
// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
|
|
// remaining[i] = remaining.back();
|
|
// remaining.pop_back();
|
|
// }
|
|
// }
|
|
// VERIFY_IS_APPROX(m, refMat);
|
|
|
|
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
|
|
#ifdef EIGEN_UNORDERED_MAP_SUPPORT
|
|
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
|
|
#endif
|
|
#ifdef _DENSE_HASH_MAP_H_
|
|
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
|
|
#endif
|
|
#ifdef _SPARSE_HASH_MAP_H_
|
|
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
|
|
#endif
|
|
|
|
|
|
// test RandomSetter
|
|
/*{
|
|
SparseMatrixType m1(rows,cols), m2(rows,cols);
|
|
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
|
|
initSparse<Scalar>(density, refM1, m1);
|
|
{
|
|
Eigen::RandomSetter<SparseMatrixType > setter(m2);
|
|
for (int j=0; j<m1.outerSize(); ++j)
|
|
for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
|
|
setter(i.index(), j) = i.value();
|
|
}
|
|
VERIFY_IS_APPROX(m1, m2);
|
|
}*/
|
|
|
|
|
|
}
|
|
|
|
void test_sparse_extra()
|
|
{
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
int s = Eigen::internal::random<int>(1,50);
|
|
CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(8, 8)) );
|
|
CALL_SUBTEST_2( sparse_extra(SparseMatrix<std::complex<double> >(s, s)) );
|
|
CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(s, s)) );
|
|
|
|
CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix<double>(s, s)) );
|
|
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double>(s, s)) ));
|
|
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double,ColMajor,long int>(s, s)) ));
|
|
|
|
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, ColMajor> >()) );
|
|
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, RowMajor> >()) );
|
|
}
|
|
}
|