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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.benoit.1@gmail.com>
//
// 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 typename NumTraits<Scalar>::Real RealScalar;
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),
m4(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);
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(0, cols-1);
Scalar s1 = ei_random<Scalar>();
// test Zero, Ones, Constant, and the set* variants
m3 = MatrixType::Constant(rows, cols, s1);
for (int j=0; j<cols; ++j)
for (int i=0; i<rows; ++i)
{
VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
VERIFY_IS_APPROX(mones(i,j), Scalar(1));
VERIFY_IS_APPROX(m3(i,j), s1);
}
VERIFY_IS_APPROX(m4.setConstant(s1), m3);
VERIFY_IS_APPROX(m4.setZero(), mzero);
VERIFY_IS_APPROX(m4.setOnes(), mones);
m4.fill(s1);
VERIFY_IS_APPROX(m4, m3);
m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
m3 = m1; m3.cwise() += 1;
VERIFY_IS_APPROX(m1 + mones, m3);
m3 = m1; m3.cwise() -= 1;
VERIFY_IS_APPROX(m1 - mones, m3);
VERIFY_IS_APPROX(m2, m2.cwise() * mones);
VERIFY_IS_APPROX(m1.cwise() * m2, m2.cwise() * m1);
m3 = m1;
m3.cwise() *= m2;
VERIFY_IS_APPROX(m3, m1.cwise() * m2);
VERIFY_IS_APPROX(mones, m2.cwise()/m2);
if(NumTraits<Scalar>::HasFloatingPoint)
{
VERIFY_IS_APPROX(m1.cwise() / m2, m1.cwise() * (m2.cwise().inverse()));
m3 = m1.cwise().abs().cwise().sqrt();
VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
m3 = m1.cwise().abs();
VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
// VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
m3 = m1;
m3.cwise() /= m2;
VERIFY_IS_APPROX(m3, m1.cwise() / m2);
}
// check min
VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
// check max
VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
VERIFY( (m1.cwise() == m1).all() );
VERIFY( (m1.cwise() != m2).any() );
VERIFY(!(m1.cwise() == (m1+mones)).any() );
if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
VERIFY( (m1.cwise() == m3).any() );
VERIFY( !(m1.cwise() == m3).all() );
}
VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
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() );
}
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(MatrixXf(22, 22)) );
CALL_SUBTEST( cwiseops(MatrixXi(8, 12)) );
CALL_SUBTEST( cwiseops(MatrixXd(20, 20)) );
}
}
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