threed-beam-fea/ext/eigen-3.2.4/test/sparse_vector.cpp

111 lines
3.6 KiB
C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.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/.
#include "sparse.h"
template<typename Scalar,typename Index> void sparse_vector(int rows, int cols)
{
double densityMat = (std::max)(8./(rows*cols), 0.01);
double densityVec = (std::max)(8./float(rows), 0.1);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseVector<Scalar,0,Index> SparseVectorType;
typedef SparseMatrix<Scalar,0,Index> SparseMatrixType;
Scalar eps = 1e-6;
SparseMatrixType m1(rows,rows);
SparseVectorType v1(rows), v2(rows), v3(rows);
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
DenseVector refV1 = DenseVector::Random(rows),
refV2 = DenseVector::Random(rows),
refV3 = DenseVector::Random(rows);
std::vector<int> zerocoords, nonzerocoords;
initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
initSparse<Scalar>(densityMat, refM1, m1);
initSparse<Scalar>(densityVec, refV2, v2);
initSparse<Scalar>(densityVec, refV3, v3);
Scalar s1 = internal::random<Scalar>();
// test coeff and coeffRef
for (unsigned int i=0; i<zerocoords.size(); ++i)
{
VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
//VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
}
{
VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
int j=0;
for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
{
VERIFY(nonzerocoords[j]==it.index());
VERIFY(it.value()==v1.coeff(it.index()));
VERIFY(it.value()==refV1.coeff(it.index()));
}
}
VERIFY_IS_APPROX(v1, refV1);
v1.coeffRef(nonzerocoords[0]) = Scalar(5);
refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
VERIFY_IS_APPROX(v1, refV1);
VERIFY_IS_APPROX(v1+v2, refV1+refV2);
VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2));
VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2));
VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2));
int i = internal::random<int>(0,rows-1);
VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i)));
VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
VERIFY_IS_APPROX(v1.blueNorm(), refV1.blueNorm());
// test aliasing
VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
// sparse matrix to sparse vector
SparseMatrixType mv1;
VERIFY_IS_APPROX((mv1=v1),v1);
VERIFY_IS_APPROX(mv1,(v1=mv1));
VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
// check copy to dense vector with transpose
refV3.resize(0);
VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense());
VERIFY_IS_APPROX(DenseVector(v1),v1.toDense());
}
void test_sparse_vector()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(( sparse_vector<double,int>(8, 8) ));
CALL_SUBTEST_2(( sparse_vector<std::complex<double>, int>(16, 16) ));
CALL_SUBTEST_1(( sparse_vector<double,long int>(299, 535) ));
CALL_SUBTEST_1(( sparse_vector<double,short>(299, 535) ));
}
}