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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.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 "main.h"
#include <functional>
#include <Eigen/Array>
using namespace std;
template<typename Scalar> struct AddIfNull {
const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
enum { Cost = NumTraits<Scalar>::AddCost };
};
template<typename MatrixType> void cwiseops(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
mones = MatrixType::Ones(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Identity(rows, rows),
square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Random(rows, rows);
VectorType v1 = VectorType::Random(rows),
v2 = VectorType::Random(rows),
vzero = VectorType::Zero(rows);
m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
VERIFY_IS_APPROX( mzero, m1-m1);
VERIFY_IS_APPROX( m2, m1+m2-m1);
#ifdef EIGEN_VECTORIZE
if(NumTraits<Scalar>::HasFloatingPoint)
#endif
{
VERIFY_IS_APPROX( mones, m2.cwise()/m2);
}
VERIFY_IS_APPROX( m1.cwise() * m2, m2.cwise() * m1);
VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
//VERIFY_IS_APPROX( m1, m2.cwiseProduct(m1).cwiseQuotient(m2));
// VERIFY_IS_APPROX( cwiseMin(m1,m2), cwiseMin(m2,m1) );
// VERIFY_IS_APPROX( cwiseMin(m1,m1+mones), m1 );
// VERIFY_IS_APPROX( cwiseMin(m1,m1-mones), m1-mones );
}
void test_cwiseop()
{
for(int i = 0; i < g_repeat ; i++) {
CALL_SUBTEST( cwiseops(Matrix<float, 1, 1>()) );
CALL_SUBTEST( cwiseops(Matrix4d()) );
CALL_SUBTEST( cwiseops(MatrixXf(3, 3)) );
CALL_SUBTEST( cwiseops(MatrixXi(8, 12)) );
CALL_SUBTEST( cwiseops(MatrixXd(20, 20)) );
}
}
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