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split and add unit tests for symm and syrk,

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the .rank*update() functions now returns a reference to *this
This commit is contained in:
Gael Guennebaud 2009-07-23 21:22:51 +02:00
parent b67abe22b3
commit 82c5438c95
7 changed files with 195 additions and 76 deletions
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10
Eigen/src/Core/SelfAdjointView.h
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@ -120,23 +120,25 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
/** Perform a symmetric rank 2 update of the selfadjoint matrix \c *this:
* \f$ this = this + \alpha ( u v^* + v u^*) \f$
* \returns a reference to \c *this
*
* The vectors \a u and \c v \b must be column vectors, however they can be
* a adjoint expression without any overhead. Only the meaningful triangular
* part of the matrix is updated, the rest is left unchanged.
*/
template<typename DerivedU, typename DerivedV>
void rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1));
SelfAdjointView& rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1));
/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
* \f$ this = this + \alpha ( u u^* ) \f$
* where \a u is a vector or matrix.
* \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
*
* \returns a reference to \c *this
*
* Note that to perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
* call this function with u.adjoint().
*/
template<typename DerivedU>
void rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
SelfAdjointView& rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
/////////// Cholesky module ///////////

4
Eigen/src/Core/products/SelfadjointProduct.h
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@ -126,7 +126,7 @@ struct ei_selfadjoint_product<Scalar,MatStorageOrder, ColMajor, AAT, UpLo>
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU>
void SelfAdjointView<MatrixType,UpLo>
SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
::rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha)
{
typedef ei_blas_traits<DerivedU> UBlasTraits;
@ -144,6 +144,8 @@ void SelfAdjointView<MatrixType,UpLo>
!UBlasTraits::NeedToConjugate, UpLo>
::run(_expression().cols(), actualU.cols(), &actualU.coeff(0,0), actualU.stride(),
const_cast<Scalar*>(_expression().data()), _expression().stride(), actualAlpha);
return *this;
}

4
Eigen/src/Core/products/SelfadjointRank2Update.h
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@ -69,7 +69,7 @@ template<bool Cond, typename T> struct ei_conj_expr_if
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU, typename DerivedV>
void SelfAdjointView<MatrixType,UpLo>
SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
::rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha)
{
typedef ei_blas_traits<DerivedU> UBlasTraits;
@ -91,6 +91,8 @@ void SelfAdjointView<MatrixType,UpLo>
typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret,
(IsRowMajor ? (UpLo==UpperTriangular ? LowerTriangular : UpperTriangular) : UpLo)>
::run(const_cast<Scalar*>(_expression().data()),_expression().stride(),actualU,actualV,actualAlpha);
return *this;
}
#endif // EIGEN_SELFADJOINTRANK2UPTADE_H

6
test/CMakeLists.txt
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@ -97,8 +97,10 @@ ei_add_test(cwiseop)
ei_add_test(redux)
ei_add_test(product_small)
ei_add_test(product_large ${EI_OFLAG})
ei_add_test(product_selfadjoint)
ei_add_test(product_extra)
ei_add_test(product_extra ${EI_OFLAG})
ei_add_test(product_selfadjoint ${EI_OFLAG})
ei_add_test(product_symm ${EI_OFLAG})
ei_add_test(product_syrk ${EI_OFLAG})
ei_add_test(diagonalmatrices)
ei_add_test(adjoint)
ei_add_test(submatrices)

68
test/product_selfadjoint.cpp
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@ -94,65 +94,6 @@ template<typename MatrixType> void product_selfadjoint(const MatrixType& m)
}
}
template<typename MatrixType> void symm(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols);
m1 = (m1+m1.adjoint()).eval();
Rhs1 rhs1 = Rhs1::Random(cols, ei_random<int>(1,320)), rhs12, rhs13;
Rhs2 rhs2 = Rhs2::Random(ei_random<int>(1,320), rows), rhs22, rhs23;
Rhs3 rhs3 = Rhs3::Random(cols, ei_random<int>(1,320)), rhs32, rhs33;
Scalar s1 = ei_random<Scalar>(),
s2 = ei_random<Scalar>();
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs1),
rhs13 = (s1*m1) * (s2*rhs1));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1),
rhs13 = (s1*m1) * (s2*rhs1));
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1.adjoint()) * (s2*rhs2.adjoint()));
// test row major = <...>
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs32 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3),
rhs33 = (s1*m1) * (s2 * rhs3));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs32 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate(),
rhs33 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
// test matrix * selfadjoint
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<LowerTriangular>(),
rhs23 = (rhs2) * (m1));
VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<LowerTriangular>(),
rhs23 = (s2*rhs2) * (s1*m1));
}
void test_product_selfadjoint()
{
for(int i = 0; i < g_repeat ; i++) {
@ -165,13 +106,4 @@ void test_product_selfadjoint()
CALL_SUBTEST( product_selfadjoint(Matrix<float,Dynamic,Dynamic,RowMajor>(17,17)) );
CALL_SUBTEST( product_selfadjoint(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(19, 19)) );
}
for(int i = 0; i < g_repeat ; i++)
{
int s;
s = ei_random<int>(10,320);
CALL_SUBTEST( symm(MatrixXf(s, s)) );
s = ei_random<int>(10,320);
CALL_SUBTEST( symm(MatrixXcd(s, s)) );
}
}

96
test/product_symm.cpp Normal file
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@ -0,0 +1,96 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@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"
template<typename MatrixType> void symm(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols);
m1 = (m1+m1.adjoint()).eval();
Rhs1 rhs1 = Rhs1::Random(cols, ei_random<int>(1,320)), rhs12, rhs13;
Rhs2 rhs2 = Rhs2::Random(ei_random<int>(1,320), rows), rhs22, rhs23;
Rhs3 rhs3 = Rhs3::Random(cols, ei_random<int>(1,320)), rhs32, rhs33;
Scalar s1 = ei_random<Scalar>(),
s2 = ei_random<Scalar>();
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs1),
rhs13 = (s1*m1) * (s2*rhs1));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1),
rhs13 = (s1*m1) * (s2*rhs1));
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs22 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
rhs23 = (s1*m1.adjoint()) * (s2*rhs2.adjoint()));
// test row major = <...>
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs32 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3),
rhs33 = (s1*m1) * (s2 * rhs3));
m2 = m1.template triangularView<UpperTriangular>();
VERIFY_IS_APPROX(rhs32 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate(),
rhs33 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
// test matrix * selfadjoint
m2 = m1.template triangularView<LowerTriangular>();
VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<LowerTriangular>(),
rhs23 = (rhs2) * (m1));
VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<LowerTriangular>(),
rhs23 = (s2*rhs2) * (s1*m1));
}
void test_product_symm()
{
for(int i = 0; i < g_repeat ; i++)
{
int s;
s = ei_random<int>(10,320);
CALL_SUBTEST( symm(MatrixXf(s, s)) );
s = ei_random<int>(10,320);
CALL_SUBTEST( symm(MatrixXcd(s, s)) );
}
}

83
test/product_syrk.cpp Normal file
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@ -0,0 +1,83 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@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"
template<typename MatrixType> void syrk(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols);
Rhs1 rhs1 = Rhs1::Random(ei_random<int>(1,320), cols);
Rhs2 rhs2 = Rhs2::Random(rows, ei_random<int>(1,320));
Rhs3 rhs3 = Rhs3::Random(ei_random<int>(1,320), rows);
Scalar s1 = ei_random<Scalar>(),
s2 = ei_random<Scalar>();
m2.setZero();
VERIFY_IS_APPROX((m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs2,s1)._expression()),
((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<LowerTriangular>().toDense()));
m2.setZero();
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs2,s1)._expression(),
(s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<UpperTriangular>().toDense());
m2.setZero();
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs1.adjoint(),s1)._expression(),
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<LowerTriangular>().toDense());
m2.setZero();
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs1.adjoint(),s1)._expression(),
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<UpperTriangular>().toDense());
m2.setZero();
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs3.adjoint(),s1)._expression(),
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<LowerTriangular>().toDense());
m2.setZero();
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs3.adjoint(),s1)._expression(),
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<UpperTriangular>().toDense());
}
void test_product_syrk()
{
for(int i = 0; i < g_repeat ; i++)
{
int s;
s = ei_random<int>(10,320);
CALL_SUBTEST( syrk(MatrixXf(s, s)) );
s = ei_random<int>(10,320);
CALL_SUBTEST( syrk(MatrixXcd(s, s)) );
}
}