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267 lines
10 KiB
C++
267 lines
10 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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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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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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square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
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VectorType v1 = 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 = 0;
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while(x == Scalar(0)) 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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VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1.squaredNorm());
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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(numext::real(s1)==numext::real_ref(s1));
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VERIFY(numext::imag(s1)==numext::imag_ref(s1));
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numext::real_ref(s1) = numext::real(s2);
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numext::imag_ref(s1) = numext::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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Scalar raw[4];
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for(int k=0; k<4; ++k)
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raw[k] = internal::random<Scalar>();
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{
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Matrix<Scalar,4,1> m(raw);
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Array<Scalar,4,1> a(raw);
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for(int k=0; k<4; ++k) VERIFY(m(k) == raw[k]);
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for(int k=0; k<4; ++k) VERIFY(a(k) == raw[k]);
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VERIFY_IS_EQUAL(m,(Matrix<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3])));
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VERIFY((a==(Array<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3]))).all());
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}
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{
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Matrix<Scalar,3,1> m(raw);
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Array<Scalar,3,1> a(raw);
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for(int k=0; k<3; ++k) VERIFY(m(k) == raw[k]);
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for(int k=0; k<3; ++k) VERIFY(a(k) == raw[k]);
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VERIFY_IS_EQUAL(m,(Matrix<Scalar,3,1>(raw[0],raw[1],raw[2])));
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VERIFY((a==Array<Scalar,3,1>(raw[0],raw[1],raw[2])).all());
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}
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{
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Matrix<Scalar,2,1> m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
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Array<Scalar,2,1> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
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for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
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for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
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VERIFY_IS_EQUAL(m,(Matrix<Scalar,2,1>(raw[0],raw[1])));
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VERIFY((a==Array<Scalar,2,1>(raw[0],raw[1])).all());
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for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
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for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
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}
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{
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Matrix<Scalar,1,2> m(raw),
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m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ),
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m3( (int(raw[0])), (int(raw[1])) ),
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m4( (float(raw[0])), (float(raw[1])) );
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Array<Scalar,1,2> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
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for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
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for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
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VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,2>(raw[0],raw[1])));
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VERIFY((a==Array<Scalar,1,2>(raw[0],raw[1])).all());
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for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
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for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
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for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k]));
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for(int k=0; k<2; ++k) VERIFY((m4(k)) == Scalar(float(raw[k])));
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}
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{
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Matrix<Scalar,1,1> m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) );
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Array<Scalar,1,1> a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) );
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VERIFY(m(0) == raw[0]);
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VERIFY(a(0) == raw[0]);
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VERIFY(m1(0) == raw[0]);
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VERIFY(a1(0) == raw[0]);
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VERIFY(m2(0) == DenseIndex(raw[0]));
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VERIFY(a2(0) == DenseIndex(raw[0]));
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VERIFY(m3(0) == int(raw[0]));
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VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,1>(raw[0])));
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VERIFY((a==Array<Scalar,1,1>(raw[0])).all());
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}
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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,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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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,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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}
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<float>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<int>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<long int>());
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CALL_SUBTEST_1(fixedSizeMatrixConstruction<std::ptrdiff_t>());
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CALL_SUBTEST_2(casting());
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}
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