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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
98 lines
4.1 KiB
C++
98 lines
4.1 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) 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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template<typename MatrixType> void adjoint(const MatrixType& m)
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{
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/* this test covers the following files:
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Transpose.h Conjugate.h Dot.h
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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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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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v3 = VectorType::random(rows),
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vzero = VectorType::zero(rows);
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Scalar s1 = ei_random<Scalar>(),
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s2 = ei_random<Scalar>();
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// check basic compatibility of adjoint, transpose, conjugate
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VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
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VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);
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// check multiplicative behavior
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VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(), m2.adjoint() * m1);
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VERIFY_IS_APPROX((s1 * m1).adjoint(), ei_conj(s1) * m1.adjoint());
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// check basic properties of dot, norm, norm2
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typedef typename NumTraits<Scalar>::Real RealScalar;
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VERIFY_IS_APPROX((s1 * v1 + s2 * v2).dot(v3), s1 * v1.dot(v3) + s2 * v2.dot(v3));
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VERIFY_IS_APPROX(v3.dot(s1 * v1 + s2 * v2), ei_conj(s1)*v3.dot(v1)+ei_conj(s2)*v3.dot(v2));
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VERIFY_IS_APPROX(ei_conj(v1.dot(v2)), v2.dot(v1));
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VERIFY_IS_APPROX(ei_abs(v1.dot(v1)), v1.norm2());
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if(NumTraits<Scalar>::HasFloatingPoint)
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VERIFY_IS_APPROX(v1.norm2(), v1.norm() * v1.norm());
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VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.dot(v1)), static_cast<RealScalar>(1));
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if(NumTraits<Scalar>::HasFloatingPoint)
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VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
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// check compatibility of dot and adjoint
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VERIFY_IS_APPROX(v1.dot(square * v2), (square.adjoint() * v1).dot(v2));
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// like in testBasicStuff, test operator() to check const-qualification
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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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VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
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VERIFY_IS_APPROX(m1.adjoint()(c,r), ei_conj(m1(r,c)));
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}
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void test_adjoint()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST( adjoint(Matrix<float, 1, 1>()) );
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CALL_SUBTEST( adjoint(Matrix4d()) );
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CALL_SUBTEST( adjoint(MatrixXcf(3, 3)) );
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CALL_SUBTEST( adjoint(MatrixXi(8, 12)) );
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CALL_SUBTEST( adjoint(MatrixXcd(20, 20)) );
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}
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// test a large matrix only once
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CALL_SUBTEST( adjoint(Matrix<float, 100, 100>()) );
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}
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