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https://github.com/OrcaSlicer/OrcaSlicer.git
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* Update eigen from v3.3.7 to v5.0.1. This updates eigen from v3.3.7 released on December 11, 2018-12-11 to v5.0.1 released on 2025-11-11. There have be a large number of bug-fixes, optimizations, and improvements between these releases. See the details at; https://gitlab.com/libeigen/eigen/-/releases It retains the previous custom minimal `CMakeLists.txt`, and adds a README-OrcaSlicer.md that explains what version and parts of the upstream eigen release have been included, and where the full release can be found. * Update libigl from v2.0.0 (or older) to v2.6.0. This updates libigl from what was probably v2.0.0 released on 2018-10-16 to v2.6.0 released on 2025-05-15. It's possible the old version was even older than that but there is no version indicators in the code and I ran out of patience identifying missing changes and only went back as far as v2.0.0. There have been a large number of bug-fixes, optimizations, and improvements between these versions. See the following for details; https://github.com/libigl/libigl/releases I retained the minimal custom `CMakeLists.txt`, added `README.md` from the libigl distribution which identifies the version, and added a README-OrcaSlicer.md that details the version and parts that have been included. * Update libslic3r for libigl v2.6.0 changes. This updates libslic3r for all changes moving to eigen v5.0.1 and libigl v2.6.0. Despite the large number of updates to both dependencies, no changes were required for the eigen update, and only one change was required for the libigl update. For libigl, `igl::Hit` was changed to a template taking the Scalar type to use. Previously it was hard-coded to `float`, so to minimize possible impact I've updated all places it is used from `igl::Hit` to `igl::Hit<float>`. * Add compiler option `-DNOMINMAX` for libigl with MSVC. MSVC by default defines `min(()` and `max()` macros that break `std::numeric_limits<>::max()`. The upstream cmake that we don't include adds `-DNOMINMAX` for the libigl module when compiling with MSVC, so we need to add the same thing here. * Fix src/libslic3r/TriangleMeshDeal.cpp for the unmodified upstream libigl. This fixes `TriangleMeshDeal.cpp` to work with the unmodified upstream libigl v2.6.0. loop.{h,cpp} implementation. This file and feature was added in PR "BBS Port: Mesh Subdivision" (#12150) which included changes to `loop.{h,cpp}` in the old version of libigl. This PR avoids modifying the included dependencies, and uses the updated upstream versions of those files without any modifications, which requires fixing TriangleMeshDeal.cpp to work with them. In particular, the modifications made to `loop.{h,cpp}` included changing the return type from void to bool, adding additional validation checking of the input meshes, and returning false if they failed validation. These added checks looked unnecessary and would only have caught problems if the input mesh was very corrupt. To make `TriangleMeshDeal.cpp` work without this built-in checking functionality, I removed checking/handling of any `false` return value. There was also a hell of a lot of redundant copying and casting back and forth between float and double, so I cleaned that up. The input and output meshs use floats for the vertexes, and there would be no accuracy benefits from casting to and from doubles for the simple weighted average operations done by igl::loop(). So this just uses `Eigen:Map` to use the original input mesh vertex data directly without requiring any copy or casting. * Move eigen from included `deps_src` to externaly fetched `deps`. This copys what PrusaSlicer did and moved it from an included dependency under `deps_src` to an externaly fetched dependency under `deps`. This requires updating some `CMakeList.txt` configs and removing the old and obsolete `cmake/modules/FindEigen3.cmake`. The details of when this was done in PrusaSlicer and the followup fixes are at; *21116995d7* https://github.com/prusa3d/PrusaSlicer/issues/13608 * https://github.com/prusa3d/PrusaSlicer/pull/13609 *e3c277b9eeFor some reason I don't fully understand this also required fixing `src/slic3r/GUI/GUI_App.cpp` by adding `#include <boost/nowide/cstdio.hpp>` to fix an `error: ‘remove’ is not a member of ‘boost::nowide'`. The main thing I don't understand is how it worked before. Note that this include is in the PrusaSlicer version of this file, but it also significantly deviates from what is currently in OrcaSlicer in many other ways. * Whups... I missed adding the deps/Eigen/Eigen.cmake file... * Tidy some whitespace indenting in CMakeLists.txt. * Ugh... tabs indenting needing fixes. * Change the include order of deps/Eigen. It turns out that although Boost includes some references to Eigen, Eigen also includes some references to Boost for supporting some of it's additional numeric types. I don't think it matters much since we are not using these features, but I think technically its more correct to say Eigen depends on Boost than the other way around, so I've re-ordered them. * Add source for Eigen 5.0.1 download to flatpak yml config. * Add explicit `DEPENDS dep_Boost to deps/Eigen. I missed this before. This ensures we don't rely on include orders to make sure Boost is installed before we configure Eigen. * Add `DEPENDS dep_Boost dep_GMP dep_MPFR` to deps/Eigen. It turns out Eigen can also use GMP and MPFR for multi-precision and multi-precision-rounded numeric types if they are available. Again, I don't think we are using these so it doesn't really matter, but it is technically correct and ensures they are there if we ever do need them. * Fix deps DEPENDENCY ordering for GMP, MPFR, Eigen, and CGAL. I think this is finally correct. Apparently CGAL also optionally depends on Eigen, so the correct dependency order from lowest to highest is GMP, MPFR, Eigen, and CGAL. --------- Co-authored-by: Donovan Baarda <dbaarda@google.com> Co-authored-by: Noisyfox <timemanager.rick@gmail.com>
582 lines
16 KiB
C++
582 lines
16 KiB
C++
// This file is part of libigl, a simple c++ geometry processing library.
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//
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// Copyright (C) 2013 Alec Jacobson <alecjacobson@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_MATLAB_MATLAB_WORKSPACE_H
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#define IGL_MATLAB_MATLAB_WORKSPACE_H
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#include <Eigen/Dense>
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#include <Eigen/Sparse>
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#include <mat.h>
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#include <string>
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#include <vector>
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namespace igl
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{
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namespace matlab
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{
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/// Class which contains data of a matlab workspace which can be written to a
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/// .mat file and loaded from matlab
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///
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/// This depends on matlab at compile time (though it shouldn't necessarily
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/// have to) but it does not depend on running the matlab engine at run-time.
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///
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/// \bug Treats all matrices as doubles (this may actually be desired
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/// for some "index" matrices since matlab's sparse command takes doubles
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/// rather than int class matrices). It is of course not desired when dealing
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/// with logicals or uint's for images.
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///
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class MatlabWorkspace
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{
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private:
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/// List of names
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/// \bug Why not use a map? Any reason to allow duplicate names?
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std::vector<std::string> names;
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/// List of data pointers
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std::vector<mxArray*> data;
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public:
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MatlabWorkspace();
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~MatlabWorkspace();
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/// Clear names and data of variables in workspace
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inline void clear();
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/// Save current list of variables
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///
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/// @param[in] path path to .mat file
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/// @return true on success, false on failure
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inline bool write(const std::string & path) const;
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/// Load list of variables from .mat file
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///
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/// @param[in] path path to .mat file
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/// @return true on success, false on failure
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inline bool read(const std::string & path);
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/// Assign data to a variable name in the workspace
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///
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/// @tparam DerivedM eigen matrix (e.g. MatrixXd)
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/// @param[in] M data (usually a matrix)
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/// @param[in] name variable name to save into work space
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/// @return true on success, false on failure
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///
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/// \bug Assumes DerivedM is using column major ordering
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template <typename DerivedM>
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inline MatlabWorkspace& save(
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const Eigen::MatrixBase<DerivedM>& M,
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const std::string & name);
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/// \overload
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/// @tparam MT sparse matrix type (e.g. double)
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template <typename MT>
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inline MatlabWorkspace& save(
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const Eigen::SparseMatrix<MT>& M,
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const std::string & name);
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/// \overload
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/// @tparam ScalarM scalar type, e.g. double
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template <typename ScalarM>
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inline MatlabWorkspace& save(
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const std::vector<std::vector<ScalarM> > & vM,
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const std::string & name);
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/// \overload
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/// @tparam ScalarV scalar type, e.g. double
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template <typename ScalarV>
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inline MatlabWorkspace& save(
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const std::vector<ScalarV> & vV,
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const std::string & name);
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/// @tparam Q quaternion type
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///
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/// NOTE: Eigen stores quaternions coefficients as (i,j,k,1), but most of
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/// our matlab code stores them as (1,i,j,k) This takes a quaternion and
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/// saves it as a (1,i,j,k) row vector
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template <typename Q>
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inline MatlabWorkspace& save(
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const Eigen::Quaternion<Q> & q,
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const std::string & name);
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/// \overload
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inline MatlabWorkspace& save(
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const double d,
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const std::string & name);
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/// Same as save() but adds 1 to each element, useful for saving "index"
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/// matrices like lists of faces or elements
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/// @tparam DerivedM eigen matrix (e.g. MatrixXd)
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template <typename DerivedM>
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inline MatlabWorkspace& save_index(
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const Eigen::DenseBase<DerivedM>& M,
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const std::string & name);
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/// \overload
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/// @tparam MT sparse matrix type (e.g. double)
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template <typename ScalarM>
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inline MatlabWorkspace& save_index(
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const std::vector<std::vector<ScalarM> > & vM,
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const std::string & name);
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/// \overload
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/// @tparam ScalarV scalar type, e.g. double
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template <typename ScalarV>
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inline MatlabWorkspace& save_index(
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const std::vector<ScalarV> & vV,
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const std::string & name);
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/// Find a certain matrix by name.
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///
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/// \bug Outputs the first found (not necessarily unique lists).
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///
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/// @tparam DerivedM eigen matrix (e.g. MatrixXd)
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/// @param[in] name exact name of matrix as string
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/// @param[out] M matrix
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/// @return true only if found.
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template <typename DerivedM>
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inline bool find(
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const std::string & name,
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Eigen::PlainObjectBase<DerivedM>& M);
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/// \overload
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/// @tparam MT sparse matrix type (e.g. double)
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template <typename MT>
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inline bool find(
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const std::string & name,
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Eigen::SparseMatrix<MT>& M);
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/// \overload
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inline bool find(
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const std::string & name,
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double & d);
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/// \overload
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inline bool find(
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const std::string & name,
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int & v);
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/// Subtracts 1 from all entries
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/// @tparam DerivedM eigen matrix (e.g. MatrixXd)
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/// @param[in] name exact name of matrix as string
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/// @param[out] M matrix
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template <typename DerivedM>
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inline bool find_index(
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const std::string & name,
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Eigen::PlainObjectBase<DerivedM>& M);
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};
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}
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}
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// Implementation
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// Be sure that this is not compiled into libigl.a
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// http://stackoverflow.com/a/3318993/148668
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// IGL
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#include "igl/list_to_matrix.h"
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// MATLAB
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#include "mat.h"
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// STL
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#include <iostream>
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#include <algorithm>
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#include <vector>
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inline igl::matlab::MatlabWorkspace::MatlabWorkspace():
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names(),
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data()
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{
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}
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inline igl::matlab::MatlabWorkspace::~MatlabWorkspace()
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{
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// clean up data
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clear();
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}
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inline void igl::matlab::MatlabWorkspace::clear()
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{
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for_each(data.begin(),data.end(),&mxDestroyArray);
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data.clear();
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names.clear();
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}
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inline bool igl::matlab::MatlabWorkspace::write(const std::string & path) const
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{
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using namespace std;
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MATFile * mat_file = matOpen(path.c_str(), "w");
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if(mat_file == NULL)
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{
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fprintf(stderr,"Error opening file %s\n",path.c_str());
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return false;
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}
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assert(names.size() == data.size());
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// loop over names and data
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for(int i = 0;i < (int)names.size(); i++)
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{
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// Put variable as LOCAL variable
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int status = matPutVariable(mat_file,names[i].c_str(), data[i]);
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if(status != 0)
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{
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cerr<<"^MatlabWorkspace::save Error: matPutVariable ("<<names[i]<<
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") failed"<<endl;
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return false;
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}
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}
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if(matClose(mat_file) != 0)
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{
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fprintf(stderr,"Error closing file %s\n",path.c_str());
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return false;
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}
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return true;
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}
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inline bool igl::matlab::MatlabWorkspace::read(const std::string & path)
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{
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using namespace std;
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MATFile * mat_file;
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mat_file = matOpen(path.c_str(), "r");
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if (mat_file == NULL)
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{
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cerr<<"Error: failed to open "<<path<<endl;
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return false;
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}
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int ndir;
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const char ** dir = (const char **)matGetDir(mat_file, &ndir);
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if (dir == NULL) {
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cerr<<"Error reading directory of file "<< path<<endl;
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return false;
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}
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mxFree(dir);
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// Must close and reopen
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if(matClose(mat_file) != 0)
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{
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cerr<<"Error: failed to close file "<<path<<endl;
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return false;
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}
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mat_file = matOpen(path.c_str(), "r");
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if (mat_file == NULL)
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{
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cerr<<"Error: failed to open "<<path<<endl;
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return false;
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}
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/* Read in each array. */
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for (int i=0; i<ndir; i++)
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{
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const char * name;
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mxArray * mx_data = matGetNextVariable(mat_file, &name);
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if (mx_data == NULL)
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{
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cerr<<"Error: matGetNextVariable failed in "<<path<<endl;
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return false;
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}
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const int dims = mxGetNumberOfDimensions(mx_data);
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assert(dims == 2);
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if(dims != 2)
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{
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fprintf(stderr,"Variable '%s' has %d ≠ 2 dimensions. Skipping\n",
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name,dims);
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mxDestroyArray(mx_data);
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continue;
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}
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// don't destroy
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names.push_back(name);
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data.push_back(mx_data);
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}
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if(matClose(mat_file) != 0)
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{
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cerr<<"Error: failed to close file "<<path<<endl;
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return false;
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}
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return true;
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}
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// Treat everything as a double
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template <typename DerivedM>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const Eigen::MatrixBase<DerivedM>& M,
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const std::string & name)
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{
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using namespace std;
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const int m = M.rows();
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const int n = M.cols();
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mxArray * mx_data = mxCreateDoubleMatrix(m,n,mxREAL);
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data.push_back(mx_data);
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names.push_back(name);
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// Copy data immediately
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// Use Eigen's map and cast to copy
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Eigen::Map< Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> >
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map(mxGetPr(mx_data),m,n);
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map = M.template cast<double>();
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return *this;
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}
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// Treat everything as a double
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template <typename MT>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const Eigen::SparseMatrix<MT>& M,
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const std::string & name)
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{
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using namespace std;
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const int m = M.rows();
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const int n = M.cols();
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// THIS WILL NOT WORK FOR ROW-MAJOR
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assert(n==M.outerSize());
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const int nzmax = M.nonZeros();
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mxArray * mx_data = mxCreateSparse(m, n, nzmax, mxREAL);
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data.push_back(mx_data);
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names.push_back(name);
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// Copy data immediately
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double * pr = mxGetPr(mx_data);
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mwIndex * ir = mxGetIr(mx_data);
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mwIndex * jc = mxGetJc(mx_data);
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// Iterate over outside
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int k = 0;
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for(int j=0; j<M.outerSize();j++)
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{
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jc[j] = k;
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// Iterate over inside
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for(typename Eigen::SparseMatrix<MT>::InnerIterator it (M,j); it; ++it)
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{
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pr[k] = it.value();
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ir[k] = it.row();
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k++;
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}
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}
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jc[M.outerSize()] = k;
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return *this;
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}
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template <typename ScalarM>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const std::vector<std::vector<ScalarM> > & vM,
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const std::string & name)
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{
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Eigen::MatrixXd M;
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list_to_matrix(vM,M);
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return this->save(M,name);
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}
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template <typename ScalarV>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const std::vector<ScalarV> & vV,
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const std::string & name)
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{
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Eigen::MatrixXd V;
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list_to_matrix(vV,V);
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return this->save(V,name);
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}
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template <typename Q>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const Eigen::Quaternion<Q> & q,
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const std::string & name)
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{
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Eigen::Matrix<Q,1,4> qm;
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qm(0,0) = q.w();
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qm(0,1) = q.x();
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qm(0,2) = q.y();
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qm(0,3) = q.z();
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return save(qm,name);
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}
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save(
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const double d,
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const std::string & name)
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{
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Eigen::VectorXd v(1);
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v(0) = d;
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return save(v,name);
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}
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template <typename DerivedM>
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inline igl::matlab::MatlabWorkspace&
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igl::matlab::MatlabWorkspace::save_index(
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const Eigen::DenseBase<DerivedM>& M,
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const std::string & name)
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{
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DerivedM Mp1 = M;
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Mp1.array() += 1;
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return this->save(Mp1,name);
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}
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template <typename ScalarM>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save_index(
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const std::vector<std::vector<ScalarM> > & vM,
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const std::string & name)
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{
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Eigen::MatrixXd M;
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list_to_matrix(vM,M);
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return this->save_index(M,name);
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}
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template <typename ScalarV>
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inline igl::matlab::MatlabWorkspace& igl::matlab::MatlabWorkspace::save_index(
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const std::vector<ScalarV> & vV,
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const std::string & name)
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{
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Eigen::MatrixXd V;
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list_to_matrix(vV,V);
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return this->save_index(V,name);
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}
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template <typename DerivedM>
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inline bool igl::matlab::MatlabWorkspace::find(
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const std::string & name,
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Eigen::PlainObjectBase<DerivedM>& M)
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{
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using namespace std;
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const int i = std::find(names.begin(), names.end(), name)-names.begin();
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if(i>=(int)names.size())
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{
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return false;
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}
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assert(i<=(int)data.size());
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mxArray * mx_data = data[i];
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assert(!mxIsSparse(mx_data));
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assert(mxGetNumberOfDimensions(mx_data) == 2);
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//cout<<name<<": "<<mxGetM(mx_data)<<" "<<mxGetN(mx_data)<<endl;
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const int m = mxGetM(mx_data);
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const int n = mxGetN(mx_data);
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// Handle vectors: in the sense that anything found becomes a column vector,
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// whether it was column vector, row vector or matrix
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if(DerivedM::IsVectorAtCompileTime)
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{
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assert(m==1 || n==1 || (m==0 && n==0));
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M.resize(m*n,1);
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}else
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{
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M.resize(m,n);
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}
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assert(mxGetNumberOfElements(mx_data) == M.size());
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// Use Eigen's map and cast to copy
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M = Eigen::Map< Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> >
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(mxGetPr(mx_data),M.rows(),M.cols()).cast<typename DerivedM::Scalar>();
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return true;
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}
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template <typename MT>
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inline bool igl::matlab::MatlabWorkspace::find(
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const std::string & name,
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Eigen::SparseMatrix<MT>& M)
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{
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using namespace std;
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using namespace Eigen;
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const int i = std::find(names.begin(), names.end(), name)-names.begin();
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if(i>=(int)names.size())
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{
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return false;
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}
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assert(i<=(int)data.size());
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mxArray * mx_data = data[i];
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// Handle boring case where matrix is actually an empty dense matrix
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if(mxGetNumberOfElements(mx_data) == 0)
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{
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M.resize(0,0);
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return true;
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}
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assert(mxIsSparse(mx_data));
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assert(mxGetNumberOfDimensions(mx_data) == 2);
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//cout<<name<<": "<<mxGetM(mx_data)<<" "<<mxGetN(mx_data)<<endl;
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const int m = mxGetM(mx_data);
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const int n = mxGetN(mx_data);
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// TODO: It should be possible to directly load the data into the sparse
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// matrix without going through the triplets
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// Copy data immediately
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double * pr = mxGetPr(mx_data);
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mwIndex * ir = mxGetIr(mx_data);
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mwIndex * jc = mxGetJc(mx_data);
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vector<Triplet<MT> > MIJV;
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const int nnz = mxGetNzmax(mx_data);
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MIJV.reserve(nnz);
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// Iterate over outside
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int k = 0;
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for(int j=0; j<n;j++)
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{
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// Iterate over inside
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while(k<(int)jc[j+1])
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{
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//cout<<ir[k]<<" "<<j<<" "<<pr[k]<<endl;
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assert((int)ir[k]<m);
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assert((int)j<n);
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MIJV.push_back(Triplet<MT >(ir[k],j,pr[k]));
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k++;
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}
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}
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M.resize(m,n);
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M.setFromTriplets(MIJV.begin(),MIJV.end());
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|
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return true;
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}
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|
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inline bool igl::matlab::MatlabWorkspace::find(
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|
const std::string & name,
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|
int & v)
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|
{
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|
using namespace std;
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|
const int i = std::find(names.begin(), names.end(), name)-names.begin();
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|
if(i>=(int)names.size())
|
|
{
|
|
return false;
|
|
}
|
|
assert(i<=(int)data.size());
|
|
mxArray * mx_data = data[i];
|
|
assert(!mxIsSparse(mx_data));
|
|
assert(mxGetNumberOfDimensions(mx_data) == 2);
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|
//cout<<name<<": "<<mxGetM(mx_data)<<" "<<mxGetN(mx_data)<<endl;
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assert(mxGetNumberOfElements(mx_data) == 1);
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copy(
|
|
mxGetPr(mx_data),
|
|
mxGetPr(mx_data)+mxGetNumberOfElements(mx_data),
|
|
&v);
|
|
return true;
|
|
}
|
|
|
|
inline bool igl::matlab::MatlabWorkspace::find(
|
|
const std::string & name,
|
|
double & d)
|
|
{
|
|
using namespace std;
|
|
const int i = std::find(names.begin(), names.end(), name)-names.begin();
|
|
if(i>=(int)names.size())
|
|
{
|
|
return false;
|
|
}
|
|
assert(i<=(int)data.size());
|
|
mxArray * mx_data = data[i];
|
|
assert(!mxIsSparse(mx_data));
|
|
assert(mxGetNumberOfDimensions(mx_data) == 2);
|
|
//cout<<name<<": "<<mxGetM(mx_data)<<" "<<mxGetN(mx_data)<<endl;
|
|
assert(mxGetNumberOfElements(mx_data) == 1);
|
|
copy(
|
|
mxGetPr(mx_data),
|
|
mxGetPr(mx_data)+mxGetNumberOfElements(mx_data),
|
|
&d);
|
|
return true;
|
|
}
|
|
|
|
template <typename DerivedM>
|
|
inline bool igl::matlab::MatlabWorkspace::find_index(
|
|
const std::string & name,
|
|
Eigen::PlainObjectBase<DerivedM>& M)
|
|
{
|
|
if(!find(name,M))
|
|
{
|
|
return false;
|
|
}
|
|
M.array() -= 1;
|
|
return true;
|
|
}
|
|
|
|
|
|
//template <typename Data>
|
|
//bool igl::matlab::MatlabWorkspace::save(const Data & M, const std::string & name)
|
|
//{
|
|
// using namespace std;
|
|
// // If I don't know the type then I can't save it
|
|
// cerr<<"^MatlabWorkspace::save Error: Unknown data type. "<<
|
|
// name<<" not saved."<<endl;
|
|
// return false;
|
|
//}
|
|
|
|
#endif
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|