[136] | 1 | // This file is part of Eigen, a lightweight C++ template library
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| 2 | // for linear algebra.
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| 3 | //
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| 4 | // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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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 "sparse.h"
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| 11 |
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| 12 | template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
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| 13 |
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| 14 | template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
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| 15 | static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
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| 16 | typedef typename SparseMatrixType::Index Index;
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| 17 | Index c = internal::random<Index>(0,m2.cols()-1);
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| 18 | Index c1 = internal::random<Index>(0,m2.cols()-1);
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| 19 | VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
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| 20 | VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
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| 21 | }
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| 22 | };
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| 23 |
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| 24 | template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
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| 25 | static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
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| 26 | typedef typename SparseMatrixType::Index Index;
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| 27 | Index r = internal::random<Index>(0,m2.rows()-1);
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| 28 | Index c1 = internal::random<Index>(0,m2.cols()-1);
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| 29 | VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
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| 30 | VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
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| 31 | }
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| 32 | };
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| 33 |
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| 34 | // (m2,m4,refMat2,refMat4,dv1);
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| 35 | // VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
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| 36 | // VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
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| 37 |
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| 38 | template<typename SparseMatrixType> void sparse_product()
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| 39 | {
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| 40 | typedef typename SparseMatrixType::Index Index;
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| 41 | Index n = 100;
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| 42 | const Index rows = internal::random<Index>(1,n);
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| 43 | const Index cols = internal::random<Index>(1,n);
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| 44 | const Index depth = internal::random<Index>(1,n);
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| 45 | typedef typename SparseMatrixType::Scalar Scalar;
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| 46 | enum { Flags = SparseMatrixType::Flags };
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| 47 |
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| 48 | double density = (std::max)(8./(rows*cols), 0.1);
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| 49 | typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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| 50 | typedef Matrix<Scalar,Dynamic,1> DenseVector;
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| 51 | typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
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| 52 | typedef SparseVector<Scalar,0,Index> ColSpVector;
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| 53 | typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
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| 54 |
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| 55 | Scalar s1 = internal::random<Scalar>();
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| 56 | Scalar s2 = internal::random<Scalar>();
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| 57 |
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| 58 | // test matrix-matrix product
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| 59 | {
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| 60 | DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth);
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| 61 | DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows);
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| 62 | DenseMatrix refMat3 = DenseMatrix::Zero(depth, cols);
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| 63 | DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth);
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| 64 | DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols);
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| 65 | DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows);
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| 66 | DenseMatrix refMat5 = DenseMatrix::Random(depth, cols);
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| 67 | DenseMatrix refMat6 = DenseMatrix::Random(rows, rows);
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| 68 | DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
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| 69 | // DenseVector dv1 = DenseVector::Random(rows);
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| 70 | SparseMatrixType m2 (rows, depth);
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| 71 | SparseMatrixType m2t(depth, rows);
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| 72 | SparseMatrixType m3 (depth, cols);
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| 73 | SparseMatrixType m3t(cols, depth);
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| 74 | SparseMatrixType m4 (rows, cols);
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| 75 | SparseMatrixType m4t(cols, rows);
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| 76 | SparseMatrixType m6(rows, rows);
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| 77 | initSparse(density, refMat2, m2);
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| 78 | initSparse(density, refMat2t, m2t);
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| 79 | initSparse(density, refMat3, m3);
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| 80 | initSparse(density, refMat3t, m3t);
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| 81 | initSparse(density, refMat4, m4);
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| 82 | initSparse(density, refMat4t, m4t);
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| 83 | initSparse(density, refMat6, m6);
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| 84 |
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| 85 | // int c = internal::random<int>(0,depth-1);
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| 86 |
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| 87 | // sparse * sparse
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| 88 | VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
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| 89 | VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
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| 90 | VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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| 91 | VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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| 92 |
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| 93 | VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
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| 94 | VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
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| 95 | VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
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| 96 |
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| 97 | VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
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| 98 | VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
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| 99 | VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
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| 100 | VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
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| 101 |
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| 102 | // test aliasing
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| 103 | m4 = m2; refMat4 = refMat2;
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| 104 | VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
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| 105 |
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| 106 | // sparse * dense
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| 107 | VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
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| 108 | VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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| 109 | VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
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| 110 | VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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| 111 |
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| 112 | VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
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| 113 | VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
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| 114 |
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| 115 | // dense * sparse
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| 116 | VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
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| 117 | VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
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| 118 | VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
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| 119 | VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
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| 120 |
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| 121 | // sparse * dense and dense * sparse outer product
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| 122 | test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
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| 123 |
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| 124 | VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
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| 125 |
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| 126 | // sparse matrix * sparse vector
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| 127 | ColSpVector cv0(cols), cv1;
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| 128 | DenseVector dcv0(cols), dcv1;
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| 129 | initSparse(2*density,dcv0, cv0);
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| 130 |
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| 131 | RowSpVector rv0(depth), rv1;
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| 132 | RowDenseVector drv0(depth), drv1(rv1);
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| 133 | initSparse(2*density,drv0, rv0);
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| 134 |
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| 135 | VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
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| 136 | VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
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| 137 | VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
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| 138 | VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
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| 139 | VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
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| 140 | }
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| 141 |
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| 142 | // test matrix - diagonal product
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| 143 | {
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| 144 | DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
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| 145 | DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
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| 146 | DenseMatrix d3 = DenseMatrix::Zero(rows, cols);
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| 147 | DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(cols));
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| 148 | DiagonalMatrix<Scalar,Dynamic> d2(DenseVector::Random(rows));
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| 149 | SparseMatrixType m2(rows, cols);
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| 150 | SparseMatrixType m3(rows, cols);
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| 151 | initSparse<Scalar>(density, refM2, m2);
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| 152 | initSparse<Scalar>(density, refM3, m3);
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| 153 | VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
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| 154 | VERIFY_IS_APPROX(m3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
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| 155 | VERIFY_IS_APPROX(m3=d2*m2, refM3=d2*refM2);
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| 156 | VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose());
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| 157 |
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| 158 | // also check with a SparseWrapper:
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| 159 | DenseVector v1 = DenseVector::Random(cols);
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| 160 | DenseVector v2 = DenseVector::Random(rows);
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| 161 | VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
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| 162 | VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
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| 163 | VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
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| 164 | VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
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| 165 |
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| 166 | VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
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| 167 |
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| 168 | // evaluate to a dense matrix to check the .row() and .col() iterator functions
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| 169 | VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
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| 170 | VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
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| 171 | VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2);
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| 172 | VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
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| 173 | }
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| 174 |
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| 175 | // test self adjoint products
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| 176 | {
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| 177 | DenseMatrix b = DenseMatrix::Random(rows, rows);
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| 178 | DenseMatrix x = DenseMatrix::Random(rows, rows);
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| 179 | DenseMatrix refX = DenseMatrix::Random(rows, rows);
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| 180 | DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
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| 181 | DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
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| 182 | DenseMatrix refS = DenseMatrix::Zero(rows, rows);
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| 183 | SparseMatrixType mUp(rows, rows);
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| 184 | SparseMatrixType mLo(rows, rows);
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| 185 | SparseMatrixType mS(rows, rows);
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| 186 | do {
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| 187 | initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
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| 188 | } while (refUp.isZero());
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| 189 | refLo = refUp.adjoint();
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| 190 | mLo = mUp.adjoint();
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| 191 | refS = refUp + refLo;
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| 192 | refS.diagonal() *= 0.5;
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| 193 | mS = mUp + mLo;
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| 194 | // TODO be able to address the diagonal....
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| 195 | for (int k=0; k<mS.outerSize(); ++k)
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| 196 | for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
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| 197 | if (it.index() == k)
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| 198 | it.valueRef() *= 0.5;
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| 199 |
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| 200 | VERIFY_IS_APPROX(refS.adjoint(), refS);
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| 201 | VERIFY_IS_APPROX(mS.adjoint(), mS);
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| 202 | VERIFY_IS_APPROX(mS, refS);
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| 203 | VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
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| 204 |
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| 205 | VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
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| 206 | VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
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| 207 | VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
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| 208 |
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| 209 | // sparse selfadjointView * sparse
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| 210 | SparseMatrixType mSres(rows,rows);
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| 211 | VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
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| 212 | refX = refLo.template selfadjointView<Lower>()*refS);
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| 213 | // sparse * sparse selfadjointview
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| 214 | VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
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| 215 | refX = refS * refLo.template selfadjointView<Lower>());
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| 216 | }
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| 217 |
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| 218 | }
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| 219 |
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| 220 | // New test for Bug in SparseTimeDenseProduct
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| 221 | template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test()
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| 222 | {
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| 223 | // This code does not compile with afflicted versions of the bug
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| 224 | SparseMatrixType sm1(3,2);
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| 225 | DenseMatrixType m2(2,2);
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| 226 | sm1.setZero();
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| 227 | m2.setZero();
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| 228 |
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| 229 | DenseMatrixType m3 = sm1*m2;
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| 230 |
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| 231 |
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| 232 | // This code produces a segfault with afflicted versions of another SparseTimeDenseProduct
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| 233 | // bug
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| 234 |
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| 235 | SparseMatrixType sm2(20000,2);
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| 236 | sm2.setZero();
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| 237 | DenseMatrixType m4(sm2*m2);
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| 238 |
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| 239 | VERIFY_IS_APPROX( m4(0,0), 0.0 );
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| 240 | }
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| 241 |
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| 242 | void test_sparse_product()
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| 243 | {
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| 244 | for(int i = 0; i < g_repeat; i++) {
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| 245 | CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
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| 246 | CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
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| 247 | CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
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| 248 | CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
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| 249 | CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
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| 250 | CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) );
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| 251 | }
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| 252 | }
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