Added a delaunay triangulating grid that uses scipy.spatial faculties

This commit is contained in:
Stephen M. McQuay 2011-09-17 19:23:21 -06:00
parent 2f6c87dd4f
commit fcb2bf2931
2 changed files with 30 additions and 314 deletions

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@ -1,184 +1,27 @@
from collections import defaultdict
import pickle
from xml.dom.minidom import Document
import numpy as np
from scipy.spatial import KDTree
from interp.baker import interpolate
from interp.baker import get_phis
import interp
import logging
log = logging.getLogger("interp")
MAX_SEARCH_COUNT = 256
TOL = 1e-8
__version__ = interp.__version__
class grid(object):
def __init__(self, verts=None, q=None):
def __init__(self):
"""
verts = array of arrays (if passed in, will convert to numpy.array)
[
[x0,y0 <, z0>],
[x1,y1 <, z1>],
...
]
q = array (1D) of physical values
Child classes should populate at a minimum the points and values
arrays, and a method for getting a simplex and extra points.
"""
pass
if verts != None:
self.verts = np.array(verts)
self.tree = KDTree(self.verts)
if q != None:
self.q = np.array(q)
self.cells = {}
self.cells_for_vert = defaultdict(list)
def get_containing_simplex(self, X):
if not self.cells:
raise Exception("cell connectivity is not set up")
# get closest point
(dist, indicies) = self.tree.query(X, 2)
closest_point = indicies[0]
log.debug('X: %s' % X)
log.debug('point index: %d' % closest_point)
log.debug('actual point %s' % self.verts[closest_point])
log.debug('distance = %0.4f' % dist[0])
simplex = None
checked_cells = []
cells_to_check = list(self.cells_for_vert[closest_point])
attempts = 0
while not simplex and cells_to_check:
attempts += 1
if attempts > MAX_SEARCH_COUNT:
raise Exception("Is the search becoming exhaustive?'\
'(%d attempts)" % attempts)
cur_cell = cells_to_check.pop(0)
checked_cells.append(cur_cell)
if cur_cell.contains(X, self):
simplex = cur_cell
continue
for neighbor in cur_cell.neighbors:
if (neighbor not in checked_cells) \
and (neighbor not in cells_to_check):
cells_to_check.append(neighbor)
if not simplex:
raise Exception('no containing simplex found')
log.debug("simplex vert indicies: %s" % simplex.verts)
R = self.create_mesh(simplex.verts)
log.debug("R:\n%s", R)
log.debug('total attempts before finding simplex: %d' % attempts)
return R
def create_mesh(self, indicies):
"""
this function takes a list of indicies, and then creates and
returns a grid object (collection of verts and q).
note: the input is indicies, the grid contains verts
"""
return grid(self.verts[indicies], self.q[indicies])
def get_simplex_and_nearest_points(self, X, extra_points=3):
"""
this returns two grid objects: R and S.
R is a grid object that is a containing simplex around point X
S : some verts from all points that are not the simplex
"""
simplex_size = self.dim + 1
log.debug("extra verts: %d" % extra_points)
log.debug("simplex size: %d" % simplex_size)
r_mesh = self.get_containing_simplex(X)
# and some UNIQUE extra verts
(dist, indicies) = self.tree.query(X, simplex_size + extra_points)
log.debug("extra indicies: %s" % indicies)
unique_indicies = []
for index in indicies:
close_point_in_R = False
for rvert in r_mesh.verts:
if all(rvert == self.verts[index]):
close_point_in_R = True
break
if not close_point_in_R:
unique_indicies.append(index)
else:
log.debug('throwing out %s: %s' % (index, self.verts[index]))
log.debug("indicies: %s" % indicies)
log.debug("unique indicies: %s" % unique_indicies)
s_mesh = self.create_mesh(unique_indicies)
return (r_mesh, s_mesh)
def get_simplex_extra_points(self, X, extra_points=8):
pass
def interpolate(self, X, order=2, extra_points=3):
(R, S) = self.get_simplex_and_nearest_points(X, extra_points)
answer = interpolate(X, R, S, order)
return answer
def for_qhull_generator(self):
"""
this returns a generator that should be fed into qdelaunay
"""
yield str(len(self.verts[0]))
yield '%d' % len(self.verts)
for p in self.verts:
yield "%f %f %f" % tuple(p)
def for_qhull(self):
"""
this returns a single string that should be fed into qdelaunay
"""
r = '%d\n' % len(self.verts[0])
r += '%d\n' % len(self.verts)
for p in self.verts:
# r += "%f %f %f\n" % tuple(p)
r += "%s\n" % " ".join("%f" % i for i in p)
return r
def __str__(self):
r = ''
assert(len(self.verts) == len(self.q))
for c, i in enumerate(zip(self.verts, self.q)):
r += "%d vert(%s): q(%0.4f)" % (c, i[0], i[1])
cell_str = ", ".join([str(f.name) for f in self.cells_for_vert[c]])
r += " cells: [%s]" % cell_str
r += "\n"
if self.cells:
for v in self.cells.itervalues():
r += "%s\n" % v
return r
def normalize_q(self, new_max=0.1):
largest_number = np.max(np.abs(self.q))
self.q *= new_max / largest_number
r, s = self.get_simplex_extra_points(X, extra_points=extra_points)
return interpolate(X, self.points[r], self.values[r],
self.points[s], self.values[s], order=order)
def dump_to_blender_files(self,
pfile='/tmp/points.p', cfile='/tmp/cells.p'):
@ -192,81 +35,13 @@ class grid(object):
pickle.dump([f.verts for f in self.cells.itervalues()],
open(cfile, 'w'))
def get_xml(self):
doc = Document()
ps = doc.createElement("points")
doc.appendChild(ps)
for i in zip(self.verts, self.q):
p = doc.createElement("point")
p.setAttribute("x", str(i[0][0]))
p.setAttribute('y', str(i[0][1]))
p.setAttribute('z', str(i[0][2]))
p.setAttribute('q', str(i[1]))
ps.appendChild(p)
return doc
def toxml(self):
return self.get_xml().toxml()
def toprettyxml(self):
return self.get_xml().toprettyxml()
class cell(object):
def __init__(self, name):
self.name = name
self.verts = []
self.neighbors = []
def add_vert(self, v):
"""
v should be an index into grid.verts
"""
self.verts.append(v)
def add_neighbor(self, n):
"""
reference to another cell object
"""
self.neighbors.append(n)
def contains(self, X, G):
"""
X = point of interest
G = corrensponding grid object (G.verts)
because of the way i'm storing things, a cell simply stores
indicies, and so one must pass in a reference to the grid object
containing real verts.
this simply calls grid.simplex.contains
"""
return contains(X, [G.verts[i] for i in self.verts])
def __str__(self):
# neighbors = [str(i.name) for i in self.neighbors]
return '<cell %s: verts: %s neighbor count: %s>' %\
(
self.name,
self.verts,
len(self.neighbors),
# ", ".join(neighbors)
)
__repr__ = __str__
def contains(X, R):
"""
tests if X (point) is in R
R is a simplex, represented by a list of n-degree coordinates
R is a simplex, represented by a list of N-degree coordinates
"""
phis = get_phis(X, R)
r = True
if [i for i in phis if i < 0.0 - TOL]:
r = False
return r
any_negatives = any(map(lambda x: x < 0, phis))
return not any_negatives

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@ -1,86 +1,27 @@
import re
import logging
import scipy.spatial
log = logging.getLogger("interp")
from interp.grid import grid as basegrid
from interp.grid import grid as basegrid, cell
from subprocess import Popen, PIPE
def get_simplex_extra_points(X, points, triangulation, kdtree, extra_points=8):
simplex_id = triangulation.find_simplex(X)
simplex_verts_ids = set(triangulation.vertices[simplex_id])
def get_qdelaunay_dump(g):
"""
pass in interp.grid g, and get back lines from a qhull triangulation:
distances, kdt_ids = kdtree.query(X, extra_points + len(simplex_verts_ids))
kdt_ids = set(kdt_ids)
qdelaunay Qt f
"""
cmd = 'qdelaunay Qt f'
p = Popen(cmd.split(), bufsize=1, stdin=PIPE, stdout=PIPE)
so, se = p.communicate(g.for_qhull())
for i in so.splitlines():
yield i
simplex_ids = list(simplex_verts_ids)
extra_points_ids = list(kdt_ids - simplex_verts_ids)
def get_qdelaunay_dump_str(g):
return "\n".join(get_qdelaunay_dump(g))
def get_index_only(g):
cmd = 'qdelaunay Qt i'
p = Popen(cmd.split(), bufsize=1, stdin=PIPE, stdout=PIPE)
so, se = p.communicate(g.for_qhull())
for i in so.splitlines():
yield i
def get_index_only_str(g):
return "\n".join(get_index_only(g))
return simplex_ids, extra_points_ids
class dgrid(basegrid):
cell_re = re.compile(r'''
-\s+(?P<cell>f\d+).*?
vertices:\s(?P<verts>.*?)\n.*?
neighboring\s facets:\s+(?P<neigh>[\sf\d]*)
''', re.S|re.X)
def __init__(self, points, values):
self.points = points
self.values = values
self.triangulation = scipy.spatial.Delaunay(points)
self.kdtree = scipy.spatial.KDTree(points)
vert_re = re.compile(r'''
(p\d+)
''', re.S|re.X)
def __init__(self, verts, q = None):
self.dim = len(verts[0])
basegrid.__init__(self, verts,q)
self.construct_connectivity()
def construct_connectivity(self):
"""
a call to this method prepares the internal connectivity structure.
"""
log.info('start')
qdelaunay_string = get_qdelaunay_dump_str(self)
with open('/tmp/qdel.out', 'w') as of:
of.write(qdelaunay_string)
cell_to_cells = []
for matcher in dgrid.cell_re.finditer(qdelaunay_string):
d = matcher.groupdict()
cell_name = d['cell']
verticies = d['verts']
neighboring_cells = d['neigh']
cur_cell = cell(cell_name)
self.cells[cell_name] = cur_cell
for v in dgrid.vert_re.findall(verticies):
vertex_index = int(v[1:])
cur_cell.add_vert(vertex_index)
self.cells_for_vert[vertex_index].append(cur_cell)
nghbrs = [(cell_name, i) for i in neighboring_cells.split()]
cell_to_cells.extend(nghbrs)
log.debug(cell_to_cells)
for rel in cell_to_cells:
if rel[1] in self.cells:
self.cells[rel[0]].add_neighbor(self.cells[rel[1]])
log.debug(self.cells)
log.info('end')
def get_simplex_extra_points(self, X, extra_points=8):
return get_simplex_extra_points(X, self.points, self.triangulation,
self.kdtree, extra_points=extra_points)