diff options
author | Gael Guennebaud <g.gael@free.fr> | 2011-03-22 11:58:22 +0100 |
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committer | Gael Guennebaud <g.gael@free.fr> | 2011-03-22 11:58:22 +0100 |
commit | 22c7609d72c3faaebe7931a4f6759e3c4546839a (patch) | |
tree | d91e10a7219d5352d6b118b0084a6eaf18f7f404 | |
parent | 5fda8cdfb36a56288c54bd2f87bf596cb06b506a (diff) |
extend sparse product unit tests
-rw-r--r-- | test/sparse.h | 51 | ||||
-rw-r--r-- | test/sparse_basic.cpp | 1 | ||||
-rw-r--r-- | test/sparse_product.cpp | 116 | ||||
-rw-r--r-- | test/sparse_vector.cpp | 2 |
4 files changed, 109 insertions, 61 deletions
diff --git a/test/sparse.h b/test/sparse.h index 949a597fc..530ae30bc 100644 --- a/test/sparse.h +++ b/test/sparse.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> +// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -58,30 +58,35 @@ enum { * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero, * and zero coefficients respectively. */ -template<typename Scalar> void +template<typename Scalar,int Opt1,int Opt2> void initSparse(double density, - Matrix<Scalar,Dynamic,Dynamic>& refMat, - SparseMatrix<Scalar>& sparseMat, + Matrix<Scalar,Dynamic,Dynamic,Opt1>& refMat, + SparseMatrix<Scalar,Opt2>& sparseMat, int flags = 0, std::vector<Vector2i>* zeroCoords = 0, std::vector<Vector2i>* nonzeroCoords = 0) { + enum { IsRowMajor = SparseMatrix<Scalar,Opt2>::IsRowMajor }; sparseMat.setZero(); sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); - for(int j=0; j<refMat.cols(); j++) + + for(int j=0; j<sparseMat.outerSize(); j++) { sparseMat.startVec(j); - for(int i=0; i<refMat.rows(); i++) + for(int i=0; i<sparseMat.innerSize(); i++) { + int ai(i), aj(j); + if(IsRowMajor) + std::swap(ai,aj); Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = internal::random<Scalar>()*Scalar(3.); v = v*v + Scalar(5.); } - if ((flags & MakeLowerTriangular) && j>i) + if ((flags & MakeLowerTriangular) && aj>ai) v = Scalar(0); - else if ((flags & MakeUpperTriangular) && j<i) + else if ((flags & MakeUpperTriangular) && aj<ai) v = Scalar(0); if ((flags&ForceRealDiag) && (i==j)) @@ -91,42 +96,46 @@ initSparse(double density, { sparseMat.insertBackByOuterInner(j,i) = v; if (nonzeroCoords) - nonzeroCoords->push_back(Vector2i(i,j)); + nonzeroCoords->push_back(Vector2i(ai,aj)); } else if (zeroCoords) { - zeroCoords->push_back(Vector2i(i,j)); + zeroCoords->push_back(Vector2i(ai,aj)); } - refMat(i,j) = v; + refMat(ai,aj) = v; } } sparseMat.finalize(); } -template<typename Scalar> void +template<typename Scalar,int Opt1,int Opt2> void initSparse(double density, - Matrix<Scalar,Dynamic,Dynamic>& refMat, - DynamicSparseMatrix<Scalar>& sparseMat, + Matrix<Scalar,Dynamic,Dynamic, Opt1>& refMat, + DynamicSparseMatrix<Scalar, Opt2>& sparseMat, int flags = 0, std::vector<Vector2i>* zeroCoords = 0, std::vector<Vector2i>* nonzeroCoords = 0) { + enum { IsRowMajor = DynamicSparseMatrix<Scalar,Opt2>::IsRowMajor }; sparseMat.setZero(); sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); - for(int j=0; j<refMat.cols(); j++) + for(int j=0; j<sparseMat.outerSize(); j++) { sparseMat.startVec(j); // not needed for DynamicSparseMatrix - for(int i=0; i<refMat.rows(); i++) + for(int i=0; i<sparseMat.innerSize(); i++) { + int ai(i), aj(j); + if(IsRowMajor) + std::swap(ai,aj); Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = internal::random<Scalar>()*Scalar(3.); v = v*v + Scalar(5.); } - if ((flags & MakeLowerTriangular) && j>i) + if ((flags & MakeLowerTriangular) && aj>ai) v = Scalar(0); - else if ((flags & MakeUpperTriangular) && j<i) + else if ((flags & MakeUpperTriangular) && aj<ai) v = Scalar(0); if ((flags&ForceRealDiag) && (i==j)) @@ -136,13 +145,13 @@ initSparse(double density, { sparseMat.insertBackByOuterInner(j,i) = v; if (nonzeroCoords) - nonzeroCoords->push_back(Vector2i(i,j)); + nonzeroCoords->push_back(Vector2i(ai,aj)); } else if (zeroCoords) { - zeroCoords->push_back(Vector2i(i,j)); + zeroCoords->push_back(Vector2i(ai,aj)); } - refMat(i,j) = v; + refMat(ai,aj) = v; } } sparseMat.finalize(); diff --git a/test/sparse_basic.cpp b/test/sparse_basic.cpp index 9d79ca740..7910bbf8f 100644 --- a/test/sparse_basic.cpp +++ b/test/sparse_basic.cpp @@ -1,6 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // +// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> // // Eigen is free software; you can redistribute it and/or diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp index 90ec3781e..1d2183bc3 100644 --- a/test/sparse_product.cpp +++ b/test/sparse_product.cpp @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> +// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -24,11 +24,37 @@ #include "sparse.h" -template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& ref) +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) { + int c = internal::random(0,m2.cols()-1); + int c1 = internal::random(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) { + int r = internal::random(0,m2.rows()-1); + int c1 = internal::random(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; - const Index rows = ref.rows(); - const Index cols = ref.cols(); + Index n = 100; + const Index rows = internal::random<int>(1,n); + const Index cols = internal::random<int>(1,n); + const Index depth = internal::random<int>(1,n); typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; @@ -41,25 +67,37 @@ template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& // test matrix-matrix product { - DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat5 = DenseMatrix::Random(rows, rows); + 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, rows); - SparseMatrixType m3(rows, rows); - SparseMatrixType m4(rows, rows); - initSparse<Scalar>(density, refMat2, m2); - initSparse<Scalar>(density, refMat3, m3); - initSparse<Scalar>(density, refMat4, m4); - - int c = internal::random<int>(0,rows-1); +// 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); VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3); - VERIFY_IS_APPROX(m4=m2.transpose()*m3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(m4=m2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); - VERIFY_IS_APPROX(m4=m2*m3.transpose(), refMat4=refMat2*refMat3.transpose()); + 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); @@ -67,24 +105,23 @@ template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& // sparse * dense VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3); - VERIFY_IS_APPROX(dm4=m2*refMat3.transpose(), refMat4=refMat2*refMat3.transpose()); - VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); + 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=m2.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2.transpose()*(refMat3+refMat5)*0.5); + 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*m3.transpose(), refMat4=refMat2*refMat3.transpose()); - VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); + 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 - VERIFY_IS_APPROX(m4=m2.col(c)*dv1.transpose(), refMat4=refMat2.col(c)*dv1.transpose()); - VERIFY_IS_APPROX(m4=dv1*m2.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose()); + test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4); - VERIFY_IS_APPROX(m3=m3*m3, refMat3=refMat3*refMat3); + VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6); } // test matrix - diagonal product @@ -116,18 +153,19 @@ template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& do { initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular); } while (refUp.isZero()); - refLo = refUp.transpose().conjugate(); - mLo = mUp.transpose().conjugate(); + 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.transpose().conjugate(), mS); + VERIFY_IS_APPROX(mS.adjoint(), mS); VERIFY_IS_APPROX(mS, refS); VERIFY_IS_APPROX(x=mS*b, refX=refS*b); @@ -162,12 +200,12 @@ template<typename SparseMatrixType, typename DenseMatrixType> void sparse_produc void test_sparse_product() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(8, 8)) ); - CALL_SUBTEST_2( sparse_product(SparseMatrix<std::complex<double> >(16, 16)) ); - CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(33, 33)) ); - - CALL_SUBTEST_3( sparse_product(DynamicSparseMatrix<double>(8, 8)) ); - + 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<DynamicSparseMatrix<float, ColMajor> >()) ); + CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, RowMajor> >()) ); CALL_SUBTEST_4( (sparse_product_regression_test<SparseMatrix<double,RowMajor>, Matrix<double, Dynamic, Dynamic, RowMajor> >()) ); } } diff --git a/test/sparse_vector.cpp b/test/sparse_vector.cpp index be85740c0..b3249915e 100644 --- a/test/sparse_vector.cpp +++ b/test/sparse_vector.cpp @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> +// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public |