3D-printing/OrcaSlicer
1
0
Fork 0
mirror of https://github.com/SoftFever/OrcaSlicer.git synced 2025-10-25 01:31:14 -06:00
Code Issues Projects Releases Packages Wiki Activity Actions 5

Merged branch 'dev_native' into lm_sla_supports_auto

Browse source 
Added igl library files
This commit is contained in:
Lukas Matena 2018-10-26 15:45:52 +02:00
commit 7681d00ee5
2865 changed files with 142806 additions and 22325 deletions
Download patch file Download diff file Expand all files Collapse all files

85
src/igl/sparse_cached.h Normal file
View file

@ -0,0 +1,85 @@
// This file is part of libigl, a simple c++ geometry processing library.
//
// Copyright (C) 2017 Daniele Panozzo <daniele.panozzo@gmail.com>
//
// 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/.
#ifndef IGL_SPARSE_CACHED_H
#define IGL_SPARSE_CACHED_H
#include "igl_inline.h"
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#include <Eigen/Dense>
#include <Eigen/Sparse>
namespace igl
{
// Build a sparse matrix from list of indices and values (I,J,V), similarly to
// the sparse function in matlab. Divides the construction in two phases, one
// for fixing the sparsity pattern, and one to populate it with values. Compared to
// igl::sparse, this version is slower for the first time (since it requires a
// precomputation), but faster to the subsequent evaluations.
//
// Templates:
// IndexVector list of indices, value should be non-negative and should
// expect to be cast to an index. Must implement operator(i) to retrieve
// ith element
// ValueVector list of values, value should be expect to be cast to type
// T. Must implement operator(i) to retrieve ith element
// T should be a eigen sparse matrix primitive type like int or double
// Input:
// I nnz vector of row indices of non zeros entries in X
// J nnz vector of column indices of non zeros entries in X
// V nnz vector of non-zeros entries in X
// Optional:
// m number of rows
// n number of cols
// Outputs:
// X m by n matrix of type T whose entries are to be found
//
// Example:
// Eigen::SparseMatrix<double> A;
// std::vector<Eigen::Triplet<double> > IJV;
// buildA(IJV);
// if (A.rows() == 0)
// {
// A = Eigen::SparseMatrix<double>(rows,cols);
// igl::sparse_cached_precompute(IJV,A,A_data);
// }
// else
// igl::sparse_cached(IJV,s.A,s.A_data);
template <typename DerivedI, typename Scalar>
IGL_INLINE void sparse_cached_precompute(
const Eigen::MatrixBase<DerivedI> & I,
const Eigen::MatrixBase<DerivedI> & J,
Eigen::VectorXi& data,
Eigen::SparseMatrix<Scalar>& X
);
template <typename Scalar>
IGL_INLINE void sparse_cached_precompute(
const std::vector<Eigen::Triplet<Scalar> >& triplets,
Eigen::VectorXi& data,
Eigen::SparseMatrix<Scalar>& X
);
template <typename Scalar>
IGL_INLINE void sparse_cached(
const std::vector<Eigen::Triplet<Scalar> >& triplets,
const Eigen::VectorXi& data,
Eigen::SparseMatrix<Scalar>& X);
template <typename DerivedV, typename Scalar>
IGL_INLINE void sparse_cached(
const Eigen::MatrixBase<DerivedV>& V,
const Eigen::VectorXi& data,
Eigen::SparseMatrix<Scalar>& X
);
}
#ifndef IGL_STATIC_LIBRARY
# include "sparse_cached.cpp"
#endif
#endif