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7c38475291
-expand and improve unit-tests -various renaming and improvements
175 lines
7.3 KiB
C++
175 lines
7.3 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) 2006-2007 Benoit Jacob <jacob@math.jussieu.fr>
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//
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// Eigen is free software; you can redistribute it and/or modify it under the
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// terms of the GNU General Public License as published by the Free Software
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// Foundation; either version 2 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 General Public License for more
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// details.
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//
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// You should have received a copy of the GNU General Public License along
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// with Eigen; if not, write to the Free Software Foundation, Inc., 51
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// Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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//
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// As a special exception, if other files instantiate templates or use macros
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// or functions from this file, or you compile this file and link it
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// with other works to produce a work based on this file, this file does not
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// by itself cause the resulting work to be covered by the GNU General Public
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// License. This exception does not invalidate any other reasons why a work
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// based on this file might be covered by the GNU General Public License.
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#include "main.h"
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namespace Eigen {
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template<typename MatrixType> void basicStuff(const MatrixType& m)
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{
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/* this test covers the following files:
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1) Explicitly (see comments below):
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Random.h Zero.h Identity.h Fuzzy.h Sum.h Difference.h
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Opposite.h Product.h ScalarMultiple.h Map.h
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2) Implicitly (the core stuff):
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MatrixBase.h Matrix.h MatrixStorage.h CopyHelper.h MatrixRef.h
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NumTraits.h Util.h
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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),
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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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Scalar s1 = random<Scalar>(),
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s2 = random<Scalar>();
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int r = random<int>(0, rows-1),
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c = random<int>(0, cols-1);
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// test Fuzzy.h and Zero.h.
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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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// test the linear structure, i.e. the following files:
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// Sum.h Difference.h Opposite.h ScalarMultiple.h
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VERIFY_IS_APPROX(-(-m1), m1);
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VERIFY_IS_APPROX(m1+m1, 2*m1);
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VERIFY_IS_APPROX(m1+m2-m1, m2);
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VERIFY_IS_APPROX(-m2+m1+m2, m1);
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VERIFY_IS_APPROX(m1*s1, s1*m1);
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VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
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VERIFY_IS_APPROX((s1+s2)*m1, m1*s1+m1*s2);
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VERIFY_IS_APPROX((m1-m2)*s1, s1*m1-s1*m2);
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VERIFY_IS_APPROX((s1-s2)*m1, m1*s1-m1*s2);
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VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2);
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VERIFY_IS_APPROX((-s1+s2)*m1, -m1*s1+m1*s2);
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m3 = m2; m3 += m1;
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VERIFY_IS_APPROX(m3, m1+m2);
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m3 = m2; m3 -= m1;
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VERIFY_IS_APPROX(m3, m2-m1);
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m3 = m2; m3 *= s1;
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VERIFY_IS_APPROX(m3, s1*m2);
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if(NumTraits<Scalar>::HasFloatingPoint)
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{
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m3 = m2; m3 /= s1;
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VERIFY_IS_APPROX(m3, m2/s1);
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}
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// again, test operator() to check const-qualification
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VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
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VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
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VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
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VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
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VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
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if(NumTraits<Scalar>::HasFloatingPoint)
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VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
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// begin testing Product.h: only associativity for now
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// (we use Transpose.h but this doesn't count as a test for it)
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VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2));
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m3 = m1;
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m3 *= (m1.transpose() * m2);
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VERIFY_IS_APPROX(m3, m1*(m1.transpose()*m2));
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VERIFY_IS_APPROX(m3, m1.lazyProduct(m1.transpose()*m2));
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// continue testing Product.h: distributivity
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VERIFY_IS_APPROX(square*(m1 + m2), square*m1+square*m2);
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VERIFY_IS_APPROX(square*(m1 - m2), square*m1-square*m2);
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// continue testing Product.h: compatibility with ScalarMultiple.h
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VERIFY_IS_APPROX(s1*(square*m1), (s1*square)*m1);
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VERIFY_IS_APPROX(s1*(square*m1), square*(m1*s1));
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// continue testing Product.h: lazyProduct
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VERIFY_IS_APPROX(square.lazyProduct(m1), square*m1);
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// again, test operator() to check const-qualification
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s1 += square.lazyProduct(m1)(r,c);
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// test Product.h together with Identity.h
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VERIFY_IS_APPROX(m1, identity*m1);
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VERIFY_IS_APPROX(v1, identity*v1);
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// again, test operator() to check const-qualification
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VERIFY_IS_APPROX(MatrixType::identity(std::max(rows,cols))(r,c), static_cast<Scalar>(r==c));
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// test Map.h
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Scalar* array1 = new Scalar[rows];
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Scalar* array2 = new Scalar[rows];
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Matrix<Scalar, Dynamic, 1>::map(array1, rows) = Matrix<Scalar, Dynamic, 1>::random(rows);
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Matrix<Scalar, Dynamic, 1>::map(array2, rows)
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= Matrix<Scalar, Dynamic, 1>::map(array1, rows);
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Matrix<Scalar, Dynamic, 1> ma1 = Matrix<Scalar, Dynamic, 1>::map(array1, rows);
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Matrix<Scalar, Dynamic, 1> ma2 = Matrix<Scalar, Dynamic, 1>::map(array2, rows);
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VERIFY_IS_APPROX(ma1, ma2);
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delete[] array1;
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delete[] array2;
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}
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void EigenTest::testBasicStuff()
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{
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for(int i = 0; i < m_repeat; i++) {
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basicStuff(Matrix<float, 1, 1>());
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basicStuff(Matrix4d());
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basicStuff(MatrixXcf(3, 3));
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basicStuff(MatrixXi(8, 12));
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basicStuff(MatrixXcd(20, 20));
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}
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}
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} // namespace Eigen
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