o X۷i@s2ddlmZddlZddlmZGdddZdS)) annotationsN)GDel2Dc@s6eZdZdZd ddZd ddZddd Zd d ZdS)Delaunaya Delaunay tessellation in 2 dimensions. Parameters ---------- points : ndarray of floats, shape (npoints, ndim) Coordinates of points to triangulate furthest_site : bool, optional Whether to compute a furthest-site Delaunay triangulation. This option will be ignored, since it is not supported by CuPy Default: False incremental : bool, optional Allow adding new points incrementally. This takes up some additional resources. This option will be ignored, since it is not supported by CuPy. Default: False Attributes ---------- points : ndarray of double, shape (npoints, ndim) Coordinates of input points. simplices : ndarray of ints, shape (nsimplex, ndim+1) Indices of the points forming the simplices in the triangulation. For 2-D, the points are oriented counterclockwise. neighbors : ndarray of ints, shape (nsimplex, ndim+1) Indices of neighbor simplices for each simplex. The kth neighbor is opposite to the kth vertex. For simplices at the boundary, -1 denotes no neighbor.0 vertex_neighbor_vertices : tuple of two ndarrays of int; (indptr, indices) Neighboring vertices of vertices. The indices of neighboring vertices of vertex `k` are ``indices[indptr[k]:indptr[k+1]]``. Notes ----- This implementation makes use of GDel2D to perform the triangulation in 2D. See [1]_ for more information. References ---------- .. [1] A GPU accelerated algorithm for 3D Delaunay triangulation (2014). Thanh-Tung Cao, Ashwin Nanjappa, Mingcen Gao, Tiow-Seng Tan. Proc. 18th ACM SIGGRAPH Symp. Interactive 3D Graphics and Games, 47-55. FcCsV|jddkr td|rtd|rtd||_t|j|_|j\|_|_dS)N/Delaunay only supports 2D inputs at the moment.z0furthest_site argument is not supported by CuPy.z.incremental argument is not supported by CuPy.)shape ValueErrorpointsr _triangulatorcompute simplices neighbors)selfr furthest_site incrementalrS/home/ubuntu/vllm_env/lib/python3.10/site-packages/cupyx/scipy/spatial/_delaunay.py__init__4s zDelaunay.__init__cCsttj|jdftjd}tjdtjd}|r(tj|jd|jddftjd}|j|||\}}|r8||fS|S)a, Find the simplices containing the given points. Parameters ---------- xi : ndarray of double, shape (..., ndim) Points to locate eps: float Tolerance allowed in the inside-triangle check. find_coords: bool, optional Whether to return the barycentric coordinates of `xi` with respect to the found simplices. Returns ------- i : ndarray of int, same shape as `xi` Indices of simplices containing each point. Points outside the triangulation get the value -1. c : ndarray of float64, same shape as `xi`, optional Barycentric coordinates of `xi` with respect to the enclosing simplices. Returned only when `find_coords` is True. r)dtyper)cupyemptyrint32float64r find_point_in_triangulation)rxieps find_coordsoutcrrr_find_simplex_coordinatesDs$z"Delaunay._find_simplex_coordinatesNcCsF|durdttjj}nt|}|jddkrtd|||S)ak Find the simplices containing the given points. Parameters ---------- xi : ndarray of double, shape (..., ndim) Points to locate bruteforce : bool, optional Whether to only perform a brute-force search. Not used by CuPy tol : float, optional Tolerance allowed in the inside-triangle check. Default is ``100*eps``. Returns ------- i : ndarray of int, same shape as `xi` Indices of simplices containing each point. Points outside the triangulation get the value -1. Ndrrr)rfinfodoublerfloatrr r!)rr bruteforcetolrrrr find_simplexgs  zDelaunay.find_simplexcCs |jS)z Neighboring vertices of vertices. Tuple of two ndarrays of int: (indptr, indices). The indices of neighboring vertices of vertex `k` are ``indices[indptr[k]:indptr[k+1]]``. )r vertex_neighbor_vertices)rrrrr)s z!Delaunay.vertex_neighbor_vertices)FF)F)FN)__name__ __module__ __qualname____doc__rr!r(r)rrrrrs  +  # r) __future__rr$cupyx.scipy.spatial.delaunay_2d._trirrrrrrs