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3b94436d2f
* make the conj functor vectorizable: it is just identity in real case, and complex doesn't use the vectorized path anyway. * fix bug in Block: a 3x1 block in a 4x4 matrix (all fixed-size) should not be vectorizable, since in fixed-size we are assuming the size to be a multiple of packet size. (Or would you prefer Vector3d to be flagged "packetaccess" even though no packet access is possible on vectors of that type?) * rename: isOrtho for vectors ---> isOrthogonal isOrtho for matrices ---> isUnitary * add normalize() * reimplement normalized with quotient1 functor
90 lines
3.5 KiB
C++
90 lines
3.5 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 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>
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::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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m2 = m2.template cwise<AddIfNull<Scalar> >(mones);
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VERIFY_IS_APPROX( mzero, m1-m1);
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VERIFY_IS_APPROX( m2, m1+m2-m1);
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#ifdef EIGEN_VECTORIZE
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if(NumTraits<Scalar>::HasFloatingPoint)
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#endif
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{
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VERIFY_IS_APPROX( mones, m2.cwiseQuotient(m2));
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}
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VERIFY_IS_APPROX( m1.cwiseProduct(m2), m2.cwiseProduct(m1));
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VERIFY( m1.cwiseLessThan(m1.cwise(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
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VERIFY( !m1.cwiseLessThan(m1.cwise(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
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VERIFY( !m1.cwiseGreaterThan(m1.cwise(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
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//VERIFY_IS_APPROX( m1, m2.cwiseProduct(m1).cwiseQuotient(m2));
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// VERIFY_IS_APPROX( cwiseMin(m1,m2), cwiseMin(m2,m1) );
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// VERIFY_IS_APPROX( cwiseMin(m1,m1+mones), m1 );
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// VERIFY_IS_APPROX( cwiseMin(m1,m1-mones), m1-mones );
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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(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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