eigen/test/basicstuff.cpp
2008-02-28 15:44:45 +00:00

96 lines
3.9 KiB
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"
namespace Eigen {
template<typename MatrixType> void basicStuff(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::Traits::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 = MatrixType::random(rows, cols),
m2 = MatrixType::random(rows, cols),
m3(rows, cols),
mzero = MatrixType::zero(rows, cols),
identity = Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, MatrixType::Traits::RowsAtCompileTime>
::identity(rows, rows),
square = Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, MatrixType::Traits::RowsAtCompileTime>
::random(rows, rows);
VectorType v1 = VectorType::random(rows),
v2 = VectorType::random(rows),
vzero = VectorType::zero(rows);
int r = ei_random<int>(0, rows-1),
c = ei_random<int>(0, cols-1);
VERIFY_IS_APPROX( v1, v1);
VERIFY_IS_NOT_APPROX( v1, 2*v1);
VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1);
if(NumTraits<Scalar>::HasFloatingPoint)
VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1.norm());
VERIFY_IS_NOT_MUCH_SMALLER_THAN(v1, v1);
VERIFY_IS_APPROX( vzero, v1-v1);
VERIFY_IS_APPROX( m1, m1);
VERIFY_IS_NOT_APPROX( m1, 2*m1);
VERIFY_IS_MUCH_SMALLER_THAN( mzero, m1);
VERIFY_IS_NOT_MUCH_SMALLER_THAN(m1, m1);
VERIFY_IS_APPROX( mzero, m1-m1);
// always test operator() on each read-only expression class,
// in order to check const-qualifiers.
// indeed, if an expression class (here Zero) is meant to be read-only,
// hence has no _write() method, the corresponding MatrixBase method (here zero())
// should return a const-qualified object so that it is the const-qualified
// operator() that gets called, which in turn calls _read().
VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::zero(rows,cols)(r,c), static_cast<Scalar>(1));
// now test copying a row-vector into a (column-)vector and conversely.
square.col(r) = square.row(r).eval();
Matrix<Scalar, 1, MatrixType::Traits::RowsAtCompileTime> rv(rows);
Matrix<Scalar, MatrixType::Traits::RowsAtCompileTime, 1> cv(rows);
rv = square.col(r);
cv = square.row(r);
VERIFY_IS_APPROX(rv, cv.transpose());
}
void EigenTest::testBasicStuff()
{
for(int i = 0; i < m_repeat; i++) {
basicStuff(Matrix<float, 1, 1>());
basicStuff(Matrix4d());
basicStuff(MatrixXcf(3, 3));
basicStuff(MatrixXi(8, 12));
basicStuff(MatrixXcd(20, 20));
}
}
} // namespace Eigen