eigen/test/linearstructure.cpp
Gael Guennebaud f0394edfa7 * bugfix in SolveTriangular found by Timothy Hunter (did not compiled for very small fixed size matrices)
* bugfix in Dot unroller
* added special random generator for the unit tests and reduced the tolerance threshold by an order of magnitude
  this fixes issues with sum.cpp but other tests still failed sometimes, this have to be carefully checked...
2008-08-22 17:48:36 +00:00

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C++

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra. Eigen itself is part of the KDE project.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob@math.jussieu.fr>
//
// 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 linearStructure(const MatrixType& m)
{
/* this test covers the following files:
Sum.h Difference.h Opposite.h ScalarMultiple.h
*/
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
int rows = m.rows();
int cols = m.cols();
// this test relies a lot on Random.h, and there's not much more that we can do
// to test it, hence I consider that we will have tested Random.h
MatrixType m1 = test_random_matrix<MatrixType>(rows, cols),
m2 = test_random_matrix<MatrixType>(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Identity(rows, rows),
square = test_random_matrix<Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> >(rows, rows);
VectorType v1 = test_random_matrix<VectorType>(rows),
v2 = test_random_matrix<VectorType>(rows),
vzero = VectorType::Zero(rows);
Scalar s1 = test_random<Scalar>();
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(0, cols-1);
VERIFY_IS_APPROX(-(-m1), m1);
VERIFY_IS_APPROX(m1+m1, 2*m1);
VERIFY_IS_APPROX(m1+m2-m1, m2);
VERIFY_IS_APPROX(-m2+m1+m2, m1);
VERIFY_IS_APPROX(m1*s1, s1*m1);
VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2);
m3 = m2; m3 += m1;
VERIFY_IS_APPROX(m3, m1+m2);
m3 = m2; m3 -= m1;
VERIFY_IS_APPROX(m3, m2-m1);
m3 = m2; m3 *= s1;
VERIFY_IS_APPROX(m3, s1*m2);
if(NumTraits<Scalar>::HasFloatingPoint)
{
m3 = m2; m3 /= s1;
VERIFY_IS_APPROX(m3, m2/s1);
}
// again, test operator() to check const-qualification
VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
if(NumTraits<Scalar>::HasFloatingPoint)
VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
// use .block to disable vectorization and compare to the vectorized version
VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
}
void test_linearstructure()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( linearStructure(Matrix<float, 1, 1>()) );
CALL_SUBTEST( linearStructure(Matrix2f()) );
CALL_SUBTEST( linearStructure(Matrix4d()) );
CALL_SUBTEST( linearStructure(MatrixXcf(3, 3)) );
CALL_SUBTEST( linearStructure(MatrixXf(8, 12)) );
CALL_SUBTEST( linearStructure(MatrixXi(8, 12)) );
CALL_SUBTEST( linearStructure(MatrixXcd(20, 20)) );
}
}