From 869b4443ac4a55c09a0632e2dbf621587749e164 Mon Sep 17 00:00:00 2001 From: Gael Guennebaud Date: Mon, 25 Jan 2016 11:55:39 +0100 Subject: [PATCH] Add SparseVector::conservativeResize() method. --- Eigen/src/SparseCore/SparseVector.h | 18 ++++++++++ test/sparse_vector.cpp | 54 ++++++++++++++++++++++++----- 2 files changed, 64 insertions(+), 8 deletions(-) diff --git a/Eigen/src/SparseCore/SparseVector.h b/Eigen/src/SparseCore/SparseVector.h index 7ec73a365..4db3003d2 100644 --- a/Eigen/src/SparseCore/SparseVector.h +++ b/Eigen/src/SparseCore/SparseVector.h @@ -222,6 +222,24 @@ class SparseVector m_data.clear(); } + /** Resizes the sparse vector to \a newSize, while leaving old values untouched. + * + * If the size of the vector is decreased, then the storage of the out-of bounds coefficients is kept and reserved. + * Call .data().squeeze() to free extra memory. + * + * \sa reserve(), setZero() + */ + void conservativeResize(Index newSize) + { + if (newSize < m_size) + { + Index i = 0; + while (i void sparse_vector(int rows, int cols) +template void sparse_vector(int rows, int cols) { double densityMat = (std::max)(8./(rows*cols), 0.01); double densityVec = (std::max)(8./float(rows), 0.1); typedef Matrix DenseMatrix; typedef Matrix DenseVector; - typedef SparseVector SparseVectorType; - typedef SparseMatrix SparseMatrixType; + typedef SparseVector SparseVectorType; + typedef SparseMatrix SparseMatrixType; Scalar eps = 1e-6; SparseMatrixType m1(rows,rows); @@ -87,8 +87,10 @@ template void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(m1*v2, refM1*refV2); VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2)); - int i = internal::random(0,rows-1); - VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i))); + { + int i = internal::random(0,rows-1); + VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i))); + } VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm()); @@ -111,15 +113,51 @@ template void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); + // test conservative resize + { + std::vector inc; + if(rows > 3) + inc.push_back(-3); + inc.push_back(0); + inc.push_back(3); + inc.push_back(1); + inc.push_back(10); + + for(std::size_t i = 0; i< inc.size(); i++) { + StorageIndex incRows = inc[i]; + SparseVectorType vec1(rows); + DenseVector refVec1 = DenseVector::Zero(rows); + initSparse(densityVec, refVec1, vec1); + + vec1.conservativeResize(rows+incRows); + refVec1.conservativeResize(rows+incRows); + if (incRows > 0) refVec1.tail(incRows).setZero(); + + VERIFY_IS_APPROX(vec1, refVec1); + + // Insert new values + if (incRows > 0) + vec1.insert(vec1.rows()-1) = refVec1(refVec1.rows()-1) = 1; + + VERIFY_IS_APPROX(vec1, refVec1); + } + } + } void test_sparse_vector() { for(int i = 0; i < g_repeat; i++) { + int r = Eigen::internal::random(1,500), c = Eigen::internal::random(1,500); + if(Eigen::internal::random(0,4) == 0) { + r = c; // check square matrices in 25% of tries + } + EIGEN_UNUSED_VARIABLE(r+c); + CALL_SUBTEST_1(( sparse_vector(8, 8) )); - CALL_SUBTEST_2(( sparse_vector, int>(16, 16) )); - CALL_SUBTEST_1(( sparse_vector(299, 535) )); - CALL_SUBTEST_1(( sparse_vector(299, 535) )); + CALL_SUBTEST_2(( sparse_vector, int>(r, c) )); + CALL_SUBTEST_1(( sparse_vector(r, c) )); + CALL_SUBTEST_1(( sparse_vector(r, c) )); } }