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233 lines
8.4 KiB
C++
233 lines
8.4 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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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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#define EIGEN_NO_STATIC_ASSERT
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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::Index Index;
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
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Index rows = m.rows();
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Index 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>::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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SquareMatrixType sm1 = SquareMatrixType::Random(rows,rows), sm2(rows,rows);
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Scalar x = internal::random<Scalar>();
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Index r = internal::random<Index>(0, rows-1),
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c = internal::random<Index>(0, cols-1);
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m1.coeffRef(r,c) = x;
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VERIFY_IS_APPROX(x, m1.coeff(r,c));
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m1(r,c) = x;
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VERIFY_IS_APPROX(x, m1(r,c));
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v1.coeffRef(r) = x;
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VERIFY_IS_APPROX(x, v1.coeff(r));
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v1(r) = x;
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VERIFY_IS_APPROX(x, v1(r));
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v1[r] = x;
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VERIFY_IS_APPROX(x, v1[r]);
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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>::IsInteger)
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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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if(cols!=1 && rows!=1)
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{
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VERIFY_RAISES_ASSERT(m1[0]);
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VERIFY_RAISES_ASSERT((m1+m1)[0]);
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}
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VERIFY_IS_APPROX(m3 = m1,m1);
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MatrixType m4;
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VERIFY_IS_APPROX(m4 = m1,m1);
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m3.real() = m1.real();
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), static_cast<const MatrixType&>(m1).real());
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), m1.real());
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// check == / != operators
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VERIFY(m1==m1);
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VERIFY(m1!=m2);
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VERIFY(!(m1==m2));
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VERIFY(!(m1!=m1));
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m1 = m2;
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VERIFY(m1==m2);
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VERIFY(!(m1!=m2));
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// check automatic transposition
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sm2.setZero();
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for(typename MatrixType::Index i=0;i<rows;++i)
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sm2.col(i) = sm1.row(i);
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VERIFY_IS_APPROX(sm2,sm1.transpose());
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sm2.setZero();
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for(typename MatrixType::Index i=0;i<rows;++i)
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sm2.col(i).noalias() = sm1.row(i);
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VERIFY_IS_APPROX(sm2,sm1.transpose());
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sm2.setZero();
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for(typename MatrixType::Index i=0;i<rows;++i)
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sm2.col(i).noalias() += sm1.row(i);
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VERIFY_IS_APPROX(sm2,sm1.transpose());
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sm2.setZero();
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for(typename MatrixType::Index i=0;i<rows;++i)
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sm2.col(i).noalias() -= sm1.row(i);
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VERIFY_IS_APPROX(sm2,-sm1.transpose());
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}
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template<typename MatrixType> void basicStuffComplex(const MatrixType& m)
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{
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typedef typename MatrixType::Index Index;
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> RealMatrixType;
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Index rows = m.rows();
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Index cols = m.cols();
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Scalar s1 = internal::random<Scalar>(),
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s2 = internal::random<Scalar>();
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VERIFY(internal::real(s1)==internal::real_ref(s1));
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VERIFY(internal::imag(s1)==internal::imag_ref(s1));
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internal::real_ref(s1) = internal::real(s2);
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internal::imag_ref(s1) = internal::imag(s2);
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VERIFY(internal::isApprox(s1, s2, NumTraits<RealScalar>::epsilon()));
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// extended precision in Intel FPUs means that s1 == s2 in the line above is not guaranteed.
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RealMatrixType rm1 = RealMatrixType::Random(rows,cols),
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rm2 = RealMatrixType::Random(rows,cols);
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MatrixType cm(rows,cols);
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cm.real() = rm1;
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cm.imag() = rm2;
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
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rm1.setZero();
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rm2.setZero();
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rm1 = cm.real();
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rm2 = cm.imag();
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
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VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
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cm.real().setZero();
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VERIFY(static_cast<const MatrixType&>(cm).real().isZero());
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VERIFY(!static_cast<const MatrixType&>(cm).imag().isZero());
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}
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#ifdef EIGEN_TEST_PART_2
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void casting()
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{
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Matrix4f m = Matrix4f::Random(), m2;
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Matrix4d n = m.cast<double>();
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VERIFY(m.isApprox(n.cast<float>()));
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m2 = m.cast<float>(); // check the specialization when NewType == Type
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VERIFY(m.isApprox(m2));
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}
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#endif
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template <typename Scalar>
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void fixedSizeMatrixConstruction()
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{
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const Scalar raw[3] = {1,2,3};
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Matrix<Scalar,3,1> m(raw);
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Array<Scalar,3,1> a(raw);
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VERIFY(m(0) == 1);
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VERIFY(m(1) == 2);
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VERIFY(m(2) == 3);
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VERIFY(a(0) == 1);
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VERIFY(a(1) == 2);
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VERIFY(a(2) == 3);
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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_1( basicStuff(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( basicStuff(Matrix4d()) );
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CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random<int>(1,100), internal::random<int>(1,100))) );
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CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random<int>(1,100), internal::random<int>(1,100))) );
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CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random<int>(1,100), internal::random<int>(1,100))) );
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CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) );
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CALL_SUBTEST_7( basicStuff(Matrix<long double,Dynamic,Dynamic>(internal::random<int>(1,100),internal::random<int>(1,100))) );
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CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random<int>(1,100), internal::random<int>(1,100))) );
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CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random<int>(1,100), internal::random<int>(1,100))) );
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}
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
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CALL_SUBTEST_2(casting());
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}
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