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* split CacheFriendlyProduct into multiple smaller files

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* add an efficient selfadjoint * vector implementation (= blas symv)
  perf are inbetween MKL and GOTO
  => the interface is still missing (have to be rethougth)
This commit is contained in:
Gael Guennebaud
2009-02-21 20:20:38 +00:00
parent 3d86dcf473
commit de014efdaf
6 changed files with 663 additions and 385 deletions
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1
test/CMakeLists.txt
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@@ -114,6 +114,7 @@ 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(adjoint)
ei_add_test(submatrices)
ei_add_test(miscmatrices)

70
test/product_selfadjoint.cpp Normal file
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@@ -0,0 +1,70 @@
// 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 <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 product_selfadjoint(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);
VectorType v1 = VectorType::Random(rows),
v2 = VectorType::Random(rows);
m1 = m1.adjoint()*m1;
// col-lower
m2.setZero();
m2.template part<LowerTriangular>() = m1;
ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangularBit>
(cols,m2.data(),cols, v1.data(), v2.data());
VERIFY_IS_APPROX(v2, m1 * v1);
// col-upper
m2.setZero();
m2.template part<UpperTriangular>() = m1;
ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,UpperTriangularBit>(cols,m2.data(),cols, v1.data(), v2.data());
VERIFY_IS_APPROX(v2, m1 * v1);
}
void test_product_selfadjoint()
{
for(int i = 0; i < g_repeat ; i++) {
CALL_SUBTEST( product_selfadjoint(Matrix<float, 1, 1>()) );
CALL_SUBTEST( product_selfadjoint(Matrix<float, 2, 2>()) );
CALL_SUBTEST( product_selfadjoint(Matrix3d()) );
CALL_SUBTEST( product_selfadjoint(MatrixXcf(4, 4)) );
CALL_SUBTEST( product_selfadjoint(MatrixXcd(21,21)) );
CALL_SUBTEST( product_selfadjoint(MatrixXd(17,17)) );
CALL_SUBTEST( product_selfadjoint(Matrix<float,Dynamic,Dynamic,RowMajor>(18,18)) );
CALL_SUBTEST( product_selfadjoint(Matrix<std::complex<double>,Dynamic,Dynamic,RowMajor>(19, 19)) );
}
}