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// 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()); // check ternary usage
{ bool b = internal::random<int>(0,10)>5; m3 = b ? m1 : m2; if(b) VERIFY_IS_APPROX(m3,m1); else VERIFY_IS_APPROX(m3,m2); m3 = b ? -m1 : m2; if(b) VERIFY_IS_APPROX(m3,-m1); else VERIFY_IS_APPROX(m3,m2); m3 = b ? m1 : -m2; if(b) VERIFY_IS_APPROX(m3,m1); else VERIFY_IS_APPROX(m3,-m2); } }
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()); }
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