Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp
new file mode 100644
index 0000000..a2ea9d5
--- /dev/null
+++ b/test/sparse_product.cpp
@@ -0,0 +1,252 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// 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 "sparse.h"
+
+template<typename SparseMatrixType, typename DenseMatrix, bool IsRowMajor=SparseMatrixType::IsRowMajor> struct test_outer;
+
+template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,false> {
+ static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
+ typedef typename SparseMatrixType::Index Index;
+ Index c = internal::random<Index>(0,m2.cols()-1);
+ Index c1 = internal::random<Index>(0,m2.cols()-1);
+ VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose());
+ VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose());
+ }
+};
+
+template<typename SparseMatrixType, typename DenseMatrix> struct test_outer<SparseMatrixType,DenseMatrix,true> {
+ static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) {
+ typedef typename SparseMatrixType::Index Index;
+ Index r = internal::random<Index>(0,m2.rows()-1);
+ Index c1 = internal::random<Index>(0,m2.cols()-1);
+ VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose());
+ VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r));
+ }
+};
+
+// (m2,m4,refMat2,refMat4,dv1);
+// VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose());
+// VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose());
+
+template<typename SparseMatrixType> void sparse_product()
+{
+ typedef typename SparseMatrixType::Index Index;
+ Index n = 100;
+ const Index rows = internal::random<Index>(1,n);
+ const Index cols = internal::random<Index>(1,n);
+ const Index depth = internal::random<Index>(1,n);
+ typedef typename SparseMatrixType::Scalar Scalar;
+ enum { Flags = SparseMatrixType::Flags };
+
+ double density = (std::max)(8./(rows*cols), 0.1);
+ typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+ typedef Matrix<Scalar,Dynamic,1> DenseVector;
+ typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
+ typedef SparseVector<Scalar,0,Index> ColSpVector;
+ typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;
+
+ Scalar s1 = internal::random<Scalar>();
+ Scalar s2 = internal::random<Scalar>();
+
+ // test matrix-matrix product
+ {
+ DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth);
+ DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows);
+ DenseMatrix refMat3 = DenseMatrix::Zero(depth, cols);
+ DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth);
+ DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols);
+ DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows);
+ DenseMatrix refMat5 = DenseMatrix::Random(depth, cols);
+ DenseMatrix refMat6 = DenseMatrix::Random(rows, rows);
+ DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
+// DenseVector dv1 = DenseVector::Random(rows);
+ SparseMatrixType m2 (rows, depth);
+ SparseMatrixType m2t(depth, rows);
+ SparseMatrixType m3 (depth, cols);
+ SparseMatrixType m3t(cols, depth);
+ SparseMatrixType m4 (rows, cols);
+ SparseMatrixType m4t(cols, rows);
+ SparseMatrixType m6(rows, rows);
+ initSparse(density, refMat2, m2);
+ initSparse(density, refMat2t, m2t);
+ initSparse(density, refMat3, m3);
+ initSparse(density, refMat3t, m3t);
+ initSparse(density, refMat4, m4);
+ initSparse(density, refMat4t, m4t);
+ initSparse(density, refMat6, m6);
+
+// int c = internal::random<int>(0,depth-1);
+
+ // sparse * sparse
+ VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+
+ VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1);
+ VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1);
+ VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1);
+
+ VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose());
+ VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose());
+
+ // test aliasing
+ m4 = m2; refMat4 = refMat2;
+ VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3);
+
+ // sparse * dense
+ VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+
+ VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3));
+ VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5);
+
+ // dense * sparse
+ VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
+ VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose());
+ VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3);
+ VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose());
+
+ // sparse * dense and dense * sparse outer product
+ test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
+
+ VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
+
+ // sparse matrix * sparse vector
+ ColSpVector cv0(cols), cv1;
+ DenseVector dcv0(cols), dcv1;
+ initSparse(2*density,dcv0, cv0);
+
+ RowSpVector rv0(depth), rv1;
+ RowDenseVector drv0(depth), drv1(rv1);
+ initSparse(2*density,drv0, rv0);
+
+ VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
+ VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
+ VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
+ VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
+ VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
+ }
+
+ // test matrix - diagonal product
+ {
+ DenseMatrix refM2 = DenseMatrix::Zero(rows, cols);
+ DenseMatrix refM3 = DenseMatrix::Zero(rows, cols);
+ DenseMatrix d3 = DenseMatrix::Zero(rows, cols);
+ DiagonalMatrix<Scalar,Dynamic> d1(DenseVector::Random(cols));
+ DiagonalMatrix<Scalar,Dynamic> d2(DenseVector::Random(rows));
+ SparseMatrixType m2(rows, cols);
+ SparseMatrixType m3(rows, cols);
+ initSparse<Scalar>(density, refM2, m2);
+ initSparse<Scalar>(density, refM3, m3);
+ VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
+ VERIFY_IS_APPROX(m3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
+ VERIFY_IS_APPROX(m3=d2*m2, refM3=d2*refM2);
+ VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1*refM2.transpose());
+
+ // also check with a SparseWrapper:
+ DenseVector v1 = DenseVector::Random(cols);
+ DenseVector v2 = DenseVector::Random(rows);
+ VERIFY_IS_APPROX(m3=m2*v1.asDiagonal(), refM3=refM2*v1.asDiagonal());
+ VERIFY_IS_APPROX(m3=m2.transpose()*v2.asDiagonal(), refM3=refM2.transpose()*v2.asDiagonal());
+ VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2, refM3=v2.asDiagonal()*refM2);
+ VERIFY_IS_APPROX(m3=v1.asDiagonal()*m2.transpose(), refM3=v1.asDiagonal()*refM2.transpose());
+
+ VERIFY_IS_APPROX(m3=v2.asDiagonal()*m2*v1.asDiagonal(), refM3=v2.asDiagonal()*refM2*v1.asDiagonal());
+
+ // evaluate to a dense matrix to check the .row() and .col() iterator functions
+ VERIFY_IS_APPROX(d3=m2*d1, refM3=refM2*d1);
+ VERIFY_IS_APPROX(d3=m2.transpose()*d2, refM3=refM2.transpose()*d2);
+ VERIFY_IS_APPROX(d3=d2*m2, refM3=d2*refM2);
+ VERIFY_IS_APPROX(d3=d1*m2.transpose(), refM3=d1*refM2.transpose());
+ }
+
+ // test self adjoint products
+ {
+ DenseMatrix b = DenseMatrix::Random(rows, rows);
+ DenseMatrix x = DenseMatrix::Random(rows, rows);
+ DenseMatrix refX = DenseMatrix::Random(rows, rows);
+ DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
+ DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
+ DenseMatrix refS = DenseMatrix::Zero(rows, rows);
+ SparseMatrixType mUp(rows, rows);
+ SparseMatrixType mLo(rows, rows);
+ SparseMatrixType mS(rows, rows);
+ do {
+ initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
+ } while (refUp.isZero());
+ refLo = refUp.adjoint();
+ mLo = mUp.adjoint();
+ refS = refUp + refLo;
+ refS.diagonal() *= 0.5;
+ mS = mUp + mLo;
+ // TODO be able to address the diagonal....
+ for (int k=0; k<mS.outerSize(); ++k)
+ for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
+ if (it.index() == k)
+ it.valueRef() *= 0.5;
+
+ VERIFY_IS_APPROX(refS.adjoint(), refS);
+ VERIFY_IS_APPROX(mS.adjoint(), mS);
+ VERIFY_IS_APPROX(mS, refS);
+ VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
+
+ VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
+ VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
+ VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
+
+ // sparse selfadjointView * sparse
+ SparseMatrixType mSres(rows,rows);
+ VERIFY_IS_APPROX(mSres = mLo.template selfadjointView<Lower>()*mS,
+ refX = refLo.template selfadjointView<Lower>()*refS);
+ // sparse * sparse selfadjointview
+ VERIFY_IS_APPROX(mSres = mS * mLo.template selfadjointView<Lower>(),
+ refX = refS * refLo.template selfadjointView<Lower>());
+ }
+
+}
+
+// New test for Bug in SparseTimeDenseProduct
+template<typename SparseMatrixType, typename DenseMatrixType> void sparse_product_regression_test()
+{
+ // This code does not compile with afflicted versions of the bug
+ SparseMatrixType sm1(3,2);
+ DenseMatrixType m2(2,2);
+ sm1.setZero();
+ m2.setZero();
+
+ DenseMatrixType m3 = sm1*m2;
+
+
+ // This code produces a segfault with afflicted versions of another SparseTimeDenseProduct
+ // bug
+
+ SparseMatrixType sm2(20000,2);
+ sm2.setZero();
+ DenseMatrixType m4(sm2*m2);
+
+ VERIFY_IS_APPROX( m4(0,0), 0.0 );
+}
+
+void test_sparse_product()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,ColMajor> >()) );
+ CALL_SUBTEST_1( (sparse_product<SparseMatrix<double,RowMajor> >()) );
+ CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, ColMajor > >()) );
+ CALL_SUBTEST_2( (sparse_product<SparseMatrix<std::complex<double>, RowMajor > >()) );
+ CALL_SUBTEST_3( (sparse_product<SparseMatrix<float,ColMajor,long int> >()) );
+ CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) );
+ }
+}