|  | // 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> | 
|  | // | 
|  | // Eigen is free software; you can redistribute it and/or | 
|  | // modify it under the terms of the GNU Lesser General Public | 
|  | // License as published by the Free Software Foundation; either | 
|  | // version 3 of the License, or (at your option) any later version. | 
|  | // | 
|  | // Alternatively, you can redistribute it and/or | 
|  | // modify it under the terms of the GNU General Public License as | 
|  | // published by the Free Software Foundation; either version 2 of | 
|  | // the License, or (at your option) any later version. | 
|  | // | 
|  | // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY | 
|  | // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS | 
|  | // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the | 
|  | // GNU General Public License for more details. | 
|  | // | 
|  | // You should have received a copy of the GNU Lesser General Public | 
|  | // License and a copy of the GNU General Public License along with | 
|  | // Eigen. If not, see <http://www.gnu.org/licenses/>. | 
|  |  | 
|  | #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; | 
|  |  | 
|  | 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), | 
|  | identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> | 
|  | ::Identity(rows, rows), | 
|  | square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows); | 
|  | VectorType v1 = VectorType::Random(rows), | 
|  | v2 = VectorType::Random(rows), | 
|  | vzero = VectorType::Zero(rows); | 
|  |  | 
|  | Scalar x = ei_random<Scalar>(); | 
|  |  | 
|  | Index r = ei_random<Index>(0, rows-1), | 
|  | c = ei_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); | 
|  | if(!NumTraits<Scalar>::IsInteger) | 
|  | VERIFY_IS_MUCH_SMALLER_THAN(  vzero, v1.norm()); | 
|  | 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)); | 
|  | } | 
|  |  | 
|  | 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 = ei_random<Scalar>(), | 
|  | s2 = ei_random<Scalar>(); | 
|  |  | 
|  | VERIFY(ei_real(s1)==ei_real_ref(s1)); | 
|  | VERIFY(ei_imag(s1)==ei_imag_ref(s1)); | 
|  | ei_real_ref(s1) = ei_real(s2); | 
|  | ei_imag_ref(s1) = ei_imag(s2); | 
|  | VERIFY(ei_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 | 
|  |  | 
|  | 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(3, 3)) ); | 
|  | CALL_SUBTEST_4( basicStuff(MatrixXi(8, 12)) ); | 
|  | CALL_SUBTEST_5( basicStuff(MatrixXcd(20, 20)) ); | 
|  | CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) ); | 
|  | CALL_SUBTEST_7( basicStuff(Matrix<long double,Dynamic,Dynamic>(10,10)) ); | 
|  |  | 
|  | CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(21, 17)) ); | 
|  | CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(2, 3)) ); | 
|  | } | 
|  |  | 
|  | CALL_SUBTEST_2(casting()); | 
|  | } |