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8463b7d3f4
* added some tests for product and swap * overload .swap() for dynamic-sized matrix of same size
104 lines
4.2 KiB
C++
104 lines
4.2 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 basicStuff(const MatrixType& m)
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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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// this test relies a lot on Random.h, and there's not much more that we can do
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// to test it, hence I consider that we will have tested Random.h
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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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vzero = VectorType::zero(rows);
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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( v1, v1);
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VERIFY_IS_NOT_APPROX( v1, 2*v1);
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VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1);
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if(NumTraits<Scalar>::HasFloatingPoint)
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VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1.norm());
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VERIFY_IS_NOT_MUCH_SMALLER_THAN(v1, v1);
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VERIFY_IS_APPROX( vzero, v1-v1);
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VERIFY_IS_APPROX( m1, m1);
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VERIFY_IS_NOT_APPROX( m1, 2*m1);
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VERIFY_IS_MUCH_SMALLER_THAN( mzero, m1);
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VERIFY_IS_NOT_MUCH_SMALLER_THAN(m1, m1);
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VERIFY_IS_APPROX( mzero, m1-m1);
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// always test operator() on each read-only expression class,
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// in order to check const-qualifiers.
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// indeed, if an expression class (here Zero) is meant to be read-only,
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// hence has no _write() method, the corresponding MatrixBase method (here zero())
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// should return a const-qualified object so that it is the const-qualified
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// operator() that gets called, which in turn calls _read().
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VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::zero(rows,cols)(r,c), static_cast<Scalar>(1));
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// now test copying a row-vector into a (column-)vector and conversely.
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square.col(r) = square.row(r).eval();
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Matrix<Scalar, 1, MatrixType::RowsAtCompileTime> rv(rows);
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Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> cv(rows);
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rv = square.row(r);
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cv = square.col(r);
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VERIFY_IS_APPROX(rv, cv.transpose());
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if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
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{
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VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)));
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}
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// test swap
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m3 = m1;
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m1.swap(m2);
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VERIFY_IS_APPROX(m3, m2);
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VERIFY_IS_NOT_APPROX(m3, m1);
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}
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void test_basicstuff()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST( basicStuff(Matrix<float, 1, 1>()) );
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CALL_SUBTEST( basicStuff(Matrix4d()) );
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CALL_SUBTEST( basicStuff(MatrixXcf(3, 3)) );
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CALL_SUBTEST( basicStuff(MatrixXi(8, 12)) );
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CALL_SUBTEST( basicStuff(MatrixXcd(20, 20)) );
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CALL_SUBTEST( basicStuff(Matrix<float, 100, 100>()) );
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}
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}
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