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46fe7a3d9e
few bits left of the comma and for floating-point types will never return zero. This replaces the custom functions in test/main.h, so one does not anymore need to think about that when writing tests.
133 lines
5.2 KiB
C++
133 lines
5.2 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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#include <functional>
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#include <Eigen/Array>
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using namespace std;
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template<typename Scalar> struct AddIfNull {
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const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
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enum { Cost = NumTraits<Scalar>::AddCost };
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};
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template<typename MatrixType> void cwiseops(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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int rows = m.rows();
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int cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols),
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m2 = MatrixType::Random(rows, cols),
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m3(rows, cols),
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mzero = MatrixType::Zero(rows, cols),
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mones = MatrixType::Ones(rows, cols),
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identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
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::Identity(rows, rows),
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square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
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VectorType v1 = VectorType::Random(rows),
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v2 = VectorType::Random(rows),
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vzero = VectorType::Zero(rows);
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int r = ei_random<int>(0, rows-1),
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c = ei_random<int>(0, cols-1);
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m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
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VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
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VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
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VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
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VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
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VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
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m3 = m1; m3.cwise() += 1;
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VERIFY_IS_APPROX(m1 + mones, m3);
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m3 = m1; m3.cwise() -= 1;
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VERIFY_IS_APPROX(m1 - mones, m3);
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VERIFY_IS_APPROX(m2, m2.cwise() * mones);
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VERIFY_IS_APPROX(m1.cwise() * m2, m2.cwise() * m1);
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VERIFY_IS_APPROX(mones, m2.cwise()/m2);
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if(NumTraits<Scalar>::HasFloatingPoint)
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{
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VERIFY_IS_APPROX(m1.cwise() / m2, m1.cwise() * (m2.cwise().inverse()));
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m3 = m1.cwise().abs().cwise().sqrt();
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VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
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VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
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VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
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// VERIFY_IS_APPROX(m1.cwise().pow(-1), m1.cwise().inverse());
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// VERIFY_IS_APPROX(m1.cwise().pow(0.5), m1.cwise().sqrt());
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// VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
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VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
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}
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// check min
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VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
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VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
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VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
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// check max
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VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
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VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
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VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
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VERIFY( (m1.cwise() == m1).all() );
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VERIFY( (m1.cwise() != m2).any() );
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VERIFY(!(m1.cwise() == (m1+mones)).any() );
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if (rows*cols>1)
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{
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m3 = m1;
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m3(r,c) += 1;
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VERIFY( (m1.cwise() == m3).any() );
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VERIFY( !(m1.cwise() == m3).all() );
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}
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VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
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VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
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VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
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VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
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VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
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VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
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VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
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}
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void test_cwiseop()
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{
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for(int i = 0; i < g_repeat ; i++) {
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CALL_SUBTEST( cwiseops(Matrix<float, 1, 1>()) );
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CALL_SUBTEST( cwiseops(Matrix4d()) );
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CALL_SUBTEST( cwiseops(MatrixXf(3, 3)) );
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CALL_SUBTEST( cwiseops(MatrixXf(22, 22)) );
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CALL_SUBTEST( cwiseops(MatrixXi(8, 12)) );
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CALL_SUBTEST( cwiseops(MatrixXd(20, 20)) );
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}
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}
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