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85 lines
2.9 KiB
C++
85 lines
2.9 KiB
C++
// This file is part of libigl, a simple c++ geometry processing library.
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//
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// Copyright (C) 2017 Daniele Panozzo <daniele.panozzo@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla Public License
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// v. 2.0. If a copy of the MPL was not distributed with this file, You can
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// obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef IGL_SPARSE_CACHED_H
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#define IGL_SPARSE_CACHED_H
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#include "igl_inline.h"
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#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
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#include <Eigen/Dense>
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#include <Eigen/Sparse>
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namespace igl
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{
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// Build a sparse matrix from list of indices and values (I,J,V), similarly to
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// the sparse function in matlab. Divides the construction in two phases, one
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// for fixing the sparsity pattern, and one to populate it with values. Compared to
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// igl::sparse, this version is slower for the first time (since it requires a
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// precomputation), but faster to the subsequent evaluations.
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//
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// Templates:
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// IndexVector list of indices, value should be non-negative and should
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// expect to be cast to an index. Must implement operator(i) to retrieve
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// ith element
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// ValueVector list of values, value should be expect to be cast to type
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// T. Must implement operator(i) to retrieve ith element
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// T should be a eigen sparse matrix primitive type like int or double
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// Input:
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// I nnz vector of row indices of non zeros entries in X
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// J nnz vector of column indices of non zeros entries in X
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// V nnz vector of non-zeros entries in X
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// Optional:
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// m number of rows
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// n number of cols
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// Outputs:
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// X m by n matrix of type T whose entries are to be found
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//
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// Example:
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// Eigen::SparseMatrix<double> A;
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// std::vector<Eigen::Triplet<double> > IJV;
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// buildA(IJV);
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// if (A.rows() == 0)
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// {
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// A = Eigen::SparseMatrix<double>(rows,cols);
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// igl::sparse_cached_precompute(IJV,A,A_data);
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// }
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// else
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// igl::sparse_cached(IJV,s.A,s.A_data);
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template <typename DerivedI, typename Scalar>
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IGL_INLINE void sparse_cached_precompute(
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const Eigen::MatrixBase<DerivedI> & I,
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const Eigen::MatrixBase<DerivedI> & J,
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Eigen::VectorXi& data,
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Eigen::SparseMatrix<Scalar>& X
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);
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template <typename Scalar>
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IGL_INLINE void sparse_cached_precompute(
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const std::vector<Eigen::Triplet<Scalar> >& triplets,
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Eigen::VectorXi& data,
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Eigen::SparseMatrix<Scalar>& X
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);
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template <typename Scalar>
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IGL_INLINE void sparse_cached(
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const std::vector<Eigen::Triplet<Scalar> >& triplets,
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const Eigen::VectorXi& data,
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Eigen::SparseMatrix<Scalar>& X);
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template <typename DerivedV, typename Scalar>
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IGL_INLINE void sparse_cached(
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const Eigen::MatrixBase<DerivedV>& V,
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const Eigen::VectorXi& data,
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Eigen::SparseMatrix<Scalar>& X
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);
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}
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#ifndef IGL_STATIC_LIBRARY
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# include "sparse_cached.cpp"
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#endif
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#endif
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