## Some tools for manipulating nearest-neighbors graphs defined on regular grids C++ routines. Parallelization with OpenMP. Mex interfaces for GNU Octave or Matlab. Extension module for Python. A grid graph in dimension _D_ is defined by the following parameters: - `D` - the number of dimensions - `shape` - array of length `D`, giving the grid size in each dimension - `connectivity` - defines the neighboring relationship; corresponds to the square of the maximum Euclidean distance between two neighbors; if less than 4, it defines the number of coordinates allowed to simultaneously vary (+1 or -1) to define a neighbor; (in that case, each level ℓ of connectivity in dimension _D_ adds C_D_ ⨯ 2 neighbors). Corresponding number of neighbors for `D` = 2 and 3: |connectivity |   1|   2|   3| |-------------|---:|---:|---:| | 2D | 4| 8| (8)| | 3D | 6| 18| 26| Note that a connectivity of 4 or more includes neighbors whose coordinates might differ by 2 or more from the coordinates of the considered vertex. In that sense, in dimension 4 or more, including all immediately surrounding vertices (that is, all vertices for which each coordinate differ by 1 or less) would then also include vertices from a more distant surround: the neighbor _v_ + (2, 0, 0, 0) is at the same distance as the neighbor _v_ + (1, 1, 1, 1). A graph with _V_ vertices and _E_ edges is represented either as edge list (array of _E_ edges given as ordered pair of vertices), or as forward-star, where edges are numeroted (from 0 to _E_ − 1) so that all edges originating from a same vertex are consecutive, and represented by the following parameters: - `first_edge` - array of length _V_ + 1, indicating for each vertex, the first edge starting from the vertex (or, if there are none, starting from the next vertex); the last value is always the total number of edges - `adj_vertices` - array of length _E_, indicating for each edge, its ending vertex Vertices of the grid are indexed in _column-major_ order, that is indices increase first along the first dimension specified in the 'shape' array (in the usual convention in 2D, this corresponds to columns), and then along the second dimension, and so on up to the last dimension. Indexing in _row-major_ order (indices increase first along the last dimension and so on up to the first) can be obtained by simply reverting the order of the grid dimensions in the shape array (in 2D, this amounts to transposition). Work possibly in parallel with OpenMP API ### Directory tree . ├── include/ C++ headers, with some doc ├── octave/ GNU Octave or Matlab code │ ├── doc/ some documentation │ └── mex/ MEX C++ interfaces ├── python/ Python code │ └── cpython/ C Python interface └── src/ C++ sources ### C++ documentation Requires `C++11`. Be sure to have OpenMP enabled with your compiler to enjoy parallelization. Note that, as of 2020, MSVC still does not support OpenMP 3.0 (published in 2008); consider switching to a decent compiler. The C++ classes are documented within the corresponding headers in `include/`. ### Python extension module Requires `numpy` package. See the script `setup.py` for compiling the module with `distutils`; on UNIX systems, it can be directly interpreted as `python setup.py build_ext`. Compatible with Python 2 and Python 3. Once compiled, see the documentation with the `help()` python utility. ### GNU Octave or Matlab See the script `compile_grid_graph_mex.m` for typical compilation commands; it can be run directly from the GNU Octave interpreter, but Matlab users must set compilation flags directly on the command line `CXXFLAGS = ...` and `LDFLAGS = ...`. Extensive documention of the MEX interfaces can be found within dedicated `.m` files in `octave/doc/`. ### References and license This software is under the GPLv3 license. Hugo Raguet 2019, 2020