| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. Eigen itself is part of the KDE project. |
| // |
| // 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/. |
| |
| #include "main.h" |
| |
| template<typename MatrixType> void linearStructure(const MatrixType& m) |
| { |
| /* this test covers the following files: |
| Sum.h Difference.h Opposite.h ScalarMultiple.h |
| */ |
| |
| typedef typename MatrixType::Scalar Scalar; |
| typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; |
| |
| int rows = m.rows(); |
| int 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); |
| |
| Scalar s1 = ei_random<Scalar>(); |
| while (ei_abs(s1)<1e-3) s1 = ei_random<Scalar>(); |
| |
| int r = ei_random<int>(0, rows-1), |
| c = ei_random<int>(0, cols-1); |
| |
| VERIFY_IS_APPROX(-(-m1), m1); |
| VERIFY_IS_APPROX(m1+m1, 2*m1); |
| VERIFY_IS_APPROX(m1+m2-m1, m2); |
| VERIFY_IS_APPROX(-m2+m1+m2, m1); |
| VERIFY_IS_APPROX(m1*s1, s1*m1); |
| VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2); |
| VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2); |
| m3 = m2; m3 += m1; |
| VERIFY_IS_APPROX(m3, m1+m2); |
| m3 = m2; m3 -= m1; |
| VERIFY_IS_APPROX(m3, m2-m1); |
| m3 = m2; m3 *= s1; |
| VERIFY_IS_APPROX(m3, s1*m2); |
| if(NumTraits<Scalar>::HasFloatingPoint) |
| { |
| m3 = m2; m3 /= s1; |
| VERIFY_IS_APPROX(m3, m2/s1); |
| } |
| |
| // again, test operator() to check const-qualification |
| VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c))); |
| VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c))); |
| VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c))); |
| VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c))); |
| VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1); |
| if(NumTraits<Scalar>::HasFloatingPoint) |
| VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1); |
| |
| // use .block to disable vectorization and compare to the vectorized version |
| VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1); |
| VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1); |
| VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1); |
| VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1); |
| } |
| |
| void test_eigen2_linearstructure() |
| { |
| for(int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) ); |
| CALL_SUBTEST_2( linearStructure(Matrix2f()) ); |
| CALL_SUBTEST_3( linearStructure(Vector3d()) ); |
| CALL_SUBTEST_4( linearStructure(Matrix4d()) ); |
| CALL_SUBTEST_5( linearStructure(MatrixXcf(3, 3)) ); |
| CALL_SUBTEST_6( linearStructure(MatrixXf(8, 12)) ); |
| CALL_SUBTEST_7( linearStructure(MatrixXi(8, 12)) ); |
| CALL_SUBTEST_8( linearStructure(MatrixXcd(20, 20)) ); |
| } |
| } |