| 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra. Eigen itself is part of the KDE project.
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| 3 | //
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| 4 | // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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| 5 | //
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| 6 | // This Source Code Form is subject to the terms of the Mozilla
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| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed
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| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 9 |
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| 10 | #include "main.h"
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| 11 |
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| 12 | template<typename MatrixType> void linearStructure(const MatrixType& m)
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| 13 | {
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| 14 | /* this test covers the following files:
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| 15 | Sum.h Difference.h Opposite.h ScalarMultiple.h
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| 16 | */
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| 17 |
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| 18 | typedef typename MatrixType::Scalar Scalar;
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| 19 | typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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| 20 |
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| 21 | int rows = m.rows();
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| 22 | int cols = m.cols();
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| 23 |
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| 24 | // this test relies a lot on Random.h, and there's not much more that we can do
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| 25 | // to test it, hence I consider that we will have tested Random.h
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| 26 | MatrixType m1 = MatrixType::Random(rows, cols),
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| 27 | m2 = MatrixType::Random(rows, cols),
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| 28 | m3(rows, cols);
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| 29 |
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| 30 | Scalar s1 = ei_random<Scalar>();
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| 31 | while (ei_abs(s1)<1e-3) s1 = ei_random<Scalar>();
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| 32 |
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| 33 | int r = ei_random<int>(0, rows-1),
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| 34 | c = ei_random<int>(0, cols-1);
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| 35 |
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| 36 | VERIFY_IS_APPROX(-(-m1), m1);
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| 37 | VERIFY_IS_APPROX(m1+m1, 2*m1);
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| 38 | VERIFY_IS_APPROX(m1+m2-m1, m2);
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| 39 | VERIFY_IS_APPROX(-m2+m1+m2, m1);
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| 40 | VERIFY_IS_APPROX(m1*s1, s1*m1);
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| 41 | VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2);
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| 42 | VERIFY_IS_APPROX((-m1+m2)*s1, -s1*m1+s1*m2);
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| 43 | m3 = m2; m3 += m1;
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| 44 | VERIFY_IS_APPROX(m3, m1+m2);
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| 45 | m3 = m2; m3 -= m1;
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| 46 | VERIFY_IS_APPROX(m3, m2-m1);
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| 47 | m3 = m2; m3 *= s1;
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| 48 | VERIFY_IS_APPROX(m3, s1*m2);
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| 49 | if(NumTraits<Scalar>::HasFloatingPoint)
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| 50 | {
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| 51 | m3 = m2; m3 /= s1;
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| 52 | VERIFY_IS_APPROX(m3, m2/s1);
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| 53 | }
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| 54 |
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| 55 | // again, test operator() to check const-qualification
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| 56 | VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
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| 57 | VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
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| 58 | VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
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| 59 | VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
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| 60 | VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
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| 61 | if(NumTraits<Scalar>::HasFloatingPoint)
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| 62 | VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
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| 63 |
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| 64 | // use .block to disable vectorization and compare to the vectorized version
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| 65 | VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
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| 66 | VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
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| 67 | VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
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| 68 | VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
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| 69 | }
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| 70 |
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| 71 | void test_eigen2_linearstructure()
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| 72 | {
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| 73 | for(int i = 0; i < g_repeat; i++) {
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| 74 | CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) );
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| 75 | CALL_SUBTEST_2( linearStructure(Matrix2f()) );
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| 76 | CALL_SUBTEST_3( linearStructure(Vector3d()) );
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| 77 | CALL_SUBTEST_4( linearStructure(Matrix4d()) );
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| 78 | CALL_SUBTEST_5( linearStructure(MatrixXcf(3, 3)) );
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| 79 | CALL_SUBTEST_6( linearStructure(MatrixXf(8, 12)) );
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| 80 | CALL_SUBTEST_7( linearStructure(MatrixXi(8, 12)) );
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| 81 | CALL_SUBTEST_8( linearStructure(MatrixXcd(20, 20)) );
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| 82 | }
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| 83 | }
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