def compute(self):
"""ABC API"""
Delaunay.__init__(self,
self._points,
self._furthest_site,
self._incremental,
self._qhull_options)
def compute(self):
"""ABC API"""
self.id = "D({},{})".format(self._furthest_site, self._qhull_options)
Delaunay.__init__(self,
self._points,
self._furthest_site,
self._incremental,
self._qhull_options)
def compute(self):
"""ABC API"""
self.id = "D({},{})".format(self._furthest_site, self._qhull_options)
Delaunay.__init__(self,
self._points,
self._furthest_site,
self._incremental,
self._qhull_options)
def __init__(self, points):
"""
:param points: coordinates of the points to triangulate
:type points: (npoints, ndim) numpy float array
"""
# most of the hard work is done here:
Delaunay.__init__(self, points)
# obtain the number of dimensions
ndim = self.points.shape[1]
# obtain the number of facets in the convex hull:
nfacets = self.convex_hull.shape[0]
# obtain the number of simplices:
try:
nsimplices = self.simplices.shape[0]
except AttributeError:
# this is necessary for outdated versions of scipy which
# use the incorrect term "vertices" instead of "simplices"
self.simplices = self.vertices
nsimplices = self.simplices.shape[0]
# create array representation of each facet in the convex hull:
self.convex_hull_array = np.empty((nfacets, ndim, ndim),
dtype=self.points.dtype)
"""Array representation of the facets which make up the convex hull"""
for i in xrange(nfacets):
for j in xrange(ndim):
self.convex_hull_array[i,
j, :] = self.points[self.convex_hull[i,
j]]
# create lookup array for facets:
self.facet_to_simplex = np.empty((nfacets), dtype=self.simplices.dtype)
"""
Lookup array which gives the index of the simplex corresponding to each facet
from the convex hull
"""
for i in xrange(nfacets):
for j in xrange(nsimplices):
if (set.issubset(set(self.convex_hull[i]),
set(self.simplices[j]))):
self.facet_to_simplex[i] = j
break
def compute(self):
"""ABC API"""
Delaunay.__init__(self, self._points, self._furthest_site,
self._incremental, self._qhull_options)
