Spaces:
Runtime error
Runtime error
File size: 2,099 Bytes
c3d0293 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2020 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Code from Chumpy and OpenDR. Placed here to avoid chumpy dependency
# The original code can be found in https://github.com/MPI-IS/mesh
import numpy as np
import scipy.sparse as sp
def row(A):
return A.reshape((1, -1))
def col(A):
return A.reshape((-1, 1))
def get_vert_connectivity(mesh_v, mesh_f):
"""Returns a sparse matrix (of size #verts x #verts) where each nonzero
element indicates a neighborhood relation. For example, if there is a
nonzero element in position (15,12), that means vertex 15 is connected
by an edge to vertex 12."""
vpv = sp.csc_matrix((len(mesh_v), len(mesh_v)))
# for each column in the faces...
for i in range(3):
IS = mesh_f[:, i]
JS = mesh_f[:, (i + 1) % 3]
data = np.ones(len(IS))
ij = np.vstack((row(IS.flatten()), row(JS.flatten())))
mtx = sp.csc_matrix((data, ij), shape=vpv.shape)
vpv = vpv + mtx + mtx.T
return vpv
def get_vertices_per_edge(mesh_v, mesh_f):
"""Returns an Ex2 array of adjacencies between vertices, where
each element in the array is a vertex index. Each edge is included
only once. If output of get_faces_per_edge is provided, this is used to
avoid call to get_vert_connectivity()"""
vc = sp.coo_matrix(get_vert_connectivity(mesh_v, mesh_f))
result = np.hstack((col(vc.row), col(vc.col)))
result = result[result[:, 0] < result[:, 1]] # for uniqueness
return result
|