test/basicstuff.cpp - mirror - Git at Google

 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

 #define EIGEN_NO_STATIC_ASSERT

 #include "main.h"

 template<typename MatrixType> void basicStuff(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;

   Index rows = m.rows();
   Index 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),
              square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
   VectorType v1 = VectorType::Random(rows),
              vzero = VectorType::Zero(rows);
   SquareMatrixType sm1 = SquareMatrixType::Random(rows,rows), sm2(rows,rows);

   Scalar x = 0;
   while(x == Scalar(0)) x = internal::random<Scalar>();

   Index r = internal::random<Index>(0, rows-1),
         c = internal::random<Index>(0, cols-1);

   m1.coeffRef(r,c) = x;
   VERIFY_IS_APPROX(x, m1.coeff(r,c));
   m1(r,c) = x;
   VERIFY_IS_APPROX(x, m1(r,c));
   v1.coeffRef(r) = x;
   VERIFY_IS_APPROX(x, v1.coeff(r));
   v1(r) = x;
   VERIFY_IS_APPROX(x, v1(r));
   v1[r] = x;
   VERIFY_IS_APPROX(x, v1[r]);

   VERIFY_IS_APPROX(               v1,    v1);
   VERIFY_IS_NOT_APPROX(           v1,    2*v1);
   VERIFY_IS_MUCH_SMALLER_THAN(    vzero, v1);
   VERIFY_IS_MUCH_SMALLER_THAN(  vzero, v1.squaredNorm());
   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::RowsAtCompileTime> rv(rows);
   Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> cv(rows);
   rv = square.row(r);
   cv = square.col(r);

   VERIFY_IS_APPROX(rv, cv.transpose());

   if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
   {
     VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)));
   }

   if(cols!=1 && rows!=1)
   {
     VERIFY_RAISES_ASSERT(m1[0]);
     VERIFY_RAISES_ASSERT((m1+m1)[0]);
   }

   VERIFY_IS_APPROX(m3 = m1,m1);
   MatrixType m4;
   VERIFY_IS_APPROX(m4 = m1,m1);

   m3.real() = m1.real();
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), static_cast<const MatrixType&>(m1).real());
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), m1.real());

   // check == / != operators
   VERIFY(m1==m1);
   VERIFY(m1!=m2);
   VERIFY(!(m1==m2));
   VERIFY(!(m1!=m1));
   m1 = m2;
   VERIFY(m1==m2);
   VERIFY(!(m1!=m2));

   // check automatic transposition
   sm2.setZero();
   for(typename MatrixType::Index i=0;i<rows;++i)
     sm2.col(i) = sm1.row(i);
   VERIFY_IS_APPROX(sm2,sm1.transpose());

   sm2.setZero();
   for(typename MatrixType::Index i=0;i<rows;++i)
     sm2.col(i).noalias() = sm1.row(i);
   VERIFY_IS_APPROX(sm2,sm1.transpose());

   sm2.setZero();
   for(typename MatrixType::Index i=0;i<rows;++i)
     sm2.col(i).noalias() += sm1.row(i);
   VERIFY_IS_APPROX(sm2,sm1.transpose());

   sm2.setZero();
   for(typename MatrixType::Index i=0;i<rows;++i)
     sm2.col(i).noalias() -= sm1.row(i);
   VERIFY_IS_APPROX(sm2,-sm1.transpose());
 }

 template<typename MatrixType> void basicStuffComplex(const MatrixType& m)
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> RealMatrixType;

   Index rows = m.rows();
   Index cols = m.cols();

   Scalar s1 = internal::random<Scalar>(),
          s2 = internal::random<Scalar>();

   VERIFY(numext::real(s1)==numext::real_ref(s1));
   VERIFY(numext::imag(s1)==numext::imag_ref(s1));
   numext::real_ref(s1) = numext::real(s2);
   numext::imag_ref(s1) = numext::imag(s2);
   VERIFY(internal::isApprox(s1, s2, NumTraits<RealScalar>::epsilon()));
   // extended precision in Intel FPUs means that s1 == s2 in the line above is not guaranteed.

   RealMatrixType rm1 = RealMatrixType::Random(rows,cols),
                  rm2 = RealMatrixType::Random(rows,cols);
   MatrixType cm(rows,cols);
   cm.real() = rm1;
   cm.imag() = rm2;
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
   rm1.setZero();
   rm2.setZero();
   rm1 = cm.real();
   rm2 = cm.imag();
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
   VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
   cm.real().setZero();
   VERIFY(static_cast<const MatrixType&>(cm).real().isZero());
   VERIFY(!static_cast<const MatrixType&>(cm).imag().isZero());
 }

 #ifdef EIGEN_TEST_PART_2
 void casting()
 {
   Matrix4f m = Matrix4f::Random(), m2;
   Matrix4d n = m.cast<double>();
   VERIFY(m.isApprox(n.cast<float>()));
   m2 = m.cast<float>(); // check the specialization when NewType == Type
   VERIFY(m.isApprox(m2));
 }
 #endif

 template <typename Scalar>
 void fixedSizeMatrixConstruction()
 {
   Scalar raw[4];
   for(int k=0; k<4; ++k)
     raw[k] = internal::random<Scalar>();

   {
     Matrix<Scalar,4,1> m(raw);
     Array<Scalar,4,1> a(raw);
     for(int k=0; k<4; ++k) VERIFY(m(k) == raw[k]);
     for(int k=0; k<4; ++k) VERIFY(a(k) == raw[k]);
     VERIFY_IS_EQUAL(m,(Matrix<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3])));
     VERIFY((a==(Array<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3]))).all());
   }
   {
     Matrix<Scalar,3,1> m(raw);
     Array<Scalar,3,1> a(raw);
     for(int k=0; k<3; ++k) VERIFY(m(k) == raw[k]);
     for(int k=0; k<3; ++k) VERIFY(a(k) == raw[k]);
     VERIFY_IS_EQUAL(m,(Matrix<Scalar,3,1>(raw[0],raw[1],raw[2])));
     VERIFY((a==Array<Scalar,3,1>(raw[0],raw[1],raw[2])).all());
   }
   {
     Matrix<Scalar,2,1> m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
     Array<Scalar,2,1> a(raw),  a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
     for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
     for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
     VERIFY_IS_EQUAL(m,(Matrix<Scalar,2,1>(raw[0],raw[1])));
     VERIFY((a==Array<Scalar,2,1>(raw[0],raw[1])).all());
     for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
     for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
   }
   {
     Matrix<Scalar,1,2> m(raw),
                        m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ),
                        m3( (int(raw[0])), (int(raw[1])) ),
                        m4( (float(raw[0])), (float(raw[1])) );
     Array<Scalar,1,2> a(raw),  a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
     for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
     for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
     VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,2>(raw[0],raw[1])));
     VERIFY((a==Array<Scalar,1,2>(raw[0],raw[1])).all());
     for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
     for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
     for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k]));
     for(int k=0; k<2; ++k) VERIFY((m4(k)) == Scalar(float(raw[k])));
   }
   {
     Matrix<Scalar,1,1> m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) );
     Array<Scalar,1,1> a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) );
     VERIFY(m(0) == raw[0]);
     VERIFY(a(0) == raw[0]);
     VERIFY(m1(0) == raw[0]);
     VERIFY(a1(0) == raw[0]);
     VERIFY(m2(0) == DenseIndex(raw[0]));
     VERIFY(a2(0) == DenseIndex(raw[0]));
     VERIFY(m3(0) == int(raw[0]));
     VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,1>(raw[0])));
     VERIFY((a==Array<Scalar,1,1>(raw[0])).all());
   }
 }

 void test_basicstuff()
 {
   for(int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1( basicStuff(Matrix<float, 1, 1>()) );
     CALL_SUBTEST_2( basicStuff(Matrix4d()) );
     CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) );
     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))) );

     CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }

   CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<float>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<int>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<long int>());
   CALL_SUBTEST_1(fixedSizeMatrixConstruction<std::ptrdiff_t>());

   CALL_SUBTEST_2(casting());
 }
	// This file is part of Eigen, a lightweight C++ template library
	// for linear algebra.
	//
	// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
	//
	// This Source Code Form is subject to the terms of the Mozilla
	// Public License v. 2.0. If a copy of the MPL was not distributed
	// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

	#define EIGEN_NO_STATIC_ASSERT

	#include "main.h"

	template<typename MatrixType> void basicStuff(const MatrixType& m)
	{
	typedef typename MatrixType::Index Index;
	typedef typename MatrixType::Scalar Scalar;
	typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
	typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;

	Index rows = m.rows();
	Index 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),
	square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
	VectorType v1 = VectorType::Random(rows),
	vzero = VectorType::Zero(rows);
	SquareMatrixType sm1 = SquareMatrixType::Random(rows,rows), sm2(rows,rows);

	Scalar x = 0;
	while(x == Scalar(0)) x = internal::random<Scalar>();

	Index r = internal::random<Index>(0, rows-1),
	c = internal::random<Index>(0, cols-1);

	m1.coeffRef(r,c) = x;
	VERIFY_IS_APPROX(x, m1.coeff(r,c));
	m1(r,c) = x;
	VERIFY_IS_APPROX(x, m1(r,c));
	v1.coeffRef(r) = x;
	VERIFY_IS_APPROX(x, v1.coeff(r));
	v1(r) = x;
	VERIFY_IS_APPROX(x, v1(r));
	v1[r] = x;
	VERIFY_IS_APPROX(x, v1[r]);

	VERIFY_IS_APPROX( v1, v1);
	VERIFY_IS_NOT_APPROX( v1, 2*v1);
	VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1);
	VERIFY_IS_MUCH_SMALLER_THAN( vzero, v1.squaredNorm());
	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::RowsAtCompileTime> rv(rows);
	Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> cv(rows);
	rv = square.row(r);
	cv = square.col(r);

	VERIFY_IS_APPROX(rv, cv.transpose());

	if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
	{
	VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)));
	}

	if(cols!=1 && rows!=1)
	{
	VERIFY_RAISES_ASSERT(m1[0]);
	VERIFY_RAISES_ASSERT((m1+m1)[0]);
	}

	VERIFY_IS_APPROX(m3 = m1,m1);
	MatrixType m4;
	VERIFY_IS_APPROX(m4 = m1,m1);

	m3.real() = m1.real();
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), static_cast<const MatrixType&>(m1).real());
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(m3).real(), m1.real());

	// check == / != operators
	VERIFY(m1==m1);
	VERIFY(m1!=m2);
	VERIFY(!(m1==m2));
	VERIFY(!(m1!=m1));
	m1 = m2;
	VERIFY(m1==m2);
	VERIFY(!(m1!=m2));

	// check automatic transposition
	sm2.setZero();
	for(typename MatrixType::Index i=0;i<rows;++i)
	sm2.col(i) = sm1.row(i);
	VERIFY_IS_APPROX(sm2,sm1.transpose());

	sm2.setZero();
	for(typename MatrixType::Index i=0;i<rows;++i)
	sm2.col(i).noalias() = sm1.row(i);
	VERIFY_IS_APPROX(sm2,sm1.transpose());

	sm2.setZero();
	for(typename MatrixType::Index i=0;i<rows;++i)
	sm2.col(i).noalias() += sm1.row(i);
	VERIFY_IS_APPROX(sm2,sm1.transpose());

	sm2.setZero();
	for(typename MatrixType::Index i=0;i<rows;++i)
	sm2.col(i).noalias() -= sm1.row(i);
	VERIFY_IS_APPROX(sm2,-sm1.transpose());
	}

	template<typename MatrixType> void basicStuffComplex(const MatrixType& m)
	{
	typedef typename MatrixType::Index Index;
	typedef typename MatrixType::Scalar Scalar;
	typedef typename NumTraits<Scalar>::Real RealScalar;
	typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> RealMatrixType;

	Index rows = m.rows();
	Index cols = m.cols();

	Scalar s1 = internal::random<Scalar>(),
	s2 = internal::random<Scalar>();

	VERIFY(numext::real(s1)==numext::real_ref(s1));
	VERIFY(numext::imag(s1)==numext::imag_ref(s1));
	numext::real_ref(s1) = numext::real(s2);
	numext::imag_ref(s1) = numext::imag(s2);
	VERIFY(internal::isApprox(s1, s2, NumTraits<RealScalar>::epsilon()));
	// extended precision in Intel FPUs means that s1 == s2 in the line above is not guaranteed.

	RealMatrixType rm1 = RealMatrixType::Random(rows,cols),
	rm2 = RealMatrixType::Random(rows,cols);
	MatrixType cm(rows,cols);
	cm.real() = rm1;
	cm.imag() = rm2;
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
	rm1.setZero();
	rm2.setZero();
	rm1 = cm.real();
	rm2 = cm.imag();
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).real(), rm1);
	VERIFY_IS_APPROX(static_cast<const MatrixType&>(cm).imag(), rm2);
	cm.real().setZero();
	VERIFY(static_cast<const MatrixType&>(cm).real().isZero());
	VERIFY(!static_cast<const MatrixType&>(cm).imag().isZero());
	}

	#ifdef EIGEN_TEST_PART_2
	void casting()
	{
	Matrix4f m = Matrix4f::Random(), m2;
	Matrix4d n = m.cast<double>();
	VERIFY(m.isApprox(n.cast<float>()));
	m2 = m.cast<float>(); // check the specialization when NewType == Type
	VERIFY(m.isApprox(m2));
	}
	#endif

	template <typename Scalar>
	void fixedSizeMatrixConstruction()
	{
	Scalar raw[4];
	for(int k=0; k<4; ++k)
	raw[k] = internal::random<Scalar>();

	{
	Matrix<Scalar,4,1> m(raw);
	Array<Scalar,4,1> a(raw);
	for(int k=0; k<4; ++k) VERIFY(m(k) == raw[k]);
	for(int k=0; k<4; ++k) VERIFY(a(k) == raw[k]);
	VERIFY_IS_EQUAL(m,(Matrix<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3])));
	VERIFY((a==(Array<Scalar,4,1>(raw[0],raw[1],raw[2],raw[3]))).all());
	}
	{
	Matrix<Scalar,3,1> m(raw);
	Array<Scalar,3,1> a(raw);
	for(int k=0; k<3; ++k) VERIFY(m(k) == raw[k]);
	for(int k=0; k<3; ++k) VERIFY(a(k) == raw[k]);
	VERIFY_IS_EQUAL(m,(Matrix<Scalar,3,1>(raw[0],raw[1],raw[2])));
	VERIFY((a==Array<Scalar,3,1>(raw[0],raw[1],raw[2])).all());
	}
	{
	Matrix<Scalar,2,1> m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
	Array<Scalar,2,1> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
	for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
	for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
	VERIFY_IS_EQUAL(m,(Matrix<Scalar,2,1>(raw[0],raw[1])));
	VERIFY((a==Array<Scalar,2,1>(raw[0],raw[1])).all());
	for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
	for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
	}
	{
	Matrix<Scalar,1,2> m(raw),
	m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ),
	m3( (int(raw[0])), (int(raw[1])) ),
	m4( (float(raw[0])), (float(raw[1])) );
	Array<Scalar,1,2> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
	for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
	for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
	VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,2>(raw[0],raw[1])));
	VERIFY((a==Array<Scalar,1,2>(raw[0],raw[1])).all());
	for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
	for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
	for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k]));
	for(int k=0; k<2; ++k) VERIFY((m4(k)) == Scalar(float(raw[k])));
	}
	{
	Matrix<Scalar,1,1> m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) );
	Array<Scalar,1,1> a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) );
	VERIFY(m(0) == raw[0]);
	VERIFY(a(0) == raw[0]);
	VERIFY(m1(0) == raw[0]);
	VERIFY(a1(0) == raw[0]);
	VERIFY(m2(0) == DenseIndex(raw[0]));
	VERIFY(a2(0) == DenseIndex(raw[0]));
	VERIFY(m3(0) == int(raw[0]));
	VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,1>(raw[0])));
	VERIFY((a==Array<Scalar,1,1>(raw[0])).all());
	}
	}

	void test_basicstuff()
	{
	for(int i = 0; i < g_repeat; i++) {
	CALL_SUBTEST_1( basicStuff(Matrix<float, 1, 1>()) );
	CALL_SUBTEST_2( basicStuff(Matrix4d()) );
	CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
	CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
	CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
	CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) );
	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))) );

	CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
	CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
	}

	CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
	CALL_SUBTEST_1(fixedSizeMatrixConstruction<float>());
	CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
	CALL_SUBTEST_1(fixedSizeMatrixConstruction<int>());
	CALL_SUBTEST_1(fixedSizeMatrixConstruction<long int>());
	CALL_SUBTEST_1(fixedSizeMatrixConstruction<std::ptrdiff_t>());

	CALL_SUBTEST_2(casting());
	}