2010-03-08 13:30:22 -08:00
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#!/usr/bin/python
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import sys
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import re
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from collections import defaultdict
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import numpy as np
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import scipy.spatial
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2010-03-18 22:18:59 -07:00
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from baker import run_baker
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2010-03-08 13:30:22 -08:00
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from baker.tools import exact_func, smberror
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2010-03-18 22:18:59 -07:00
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from simplex import face
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2010-03-08 13:30:22 -08:00
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from smcqdelaunay import *
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class grid(object):
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facet_re = re.compile(r'''
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-\s+(?P<facet>f\d+).*?
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vertices:\s(?P<verts>.*?)\n.*?
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neighboring\s facets:\s+(?P<neigh>[\sf\d]*)
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''', re.S|re.X)
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point_re = re.compile(r'''
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-\s+(?P<point>p\d+).*?
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neighbors:\s+(?P<neigh>[\sf\d]*)
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''', re.S|re.X)
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vert_re = re.compile(r'''
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(p\d+)
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''', re.S|re.X)
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def __init__(self, points, q):
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"""
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this thing eats two pre-constructed arrays of stuff:
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points = array of arrays (i will convert to numpy.array)
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[[x0,y0], [x1,y1], ...]
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q = array (1D) of important values
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"""
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self.points = np.array(points)
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self.q = np.array(q)
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self.tree = scipy.spatial.KDTree(self.points)
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self.faces = {}
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self.facets_for_point = defaultdict(list)
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def create_mesh(self, indicies):
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p = [self.points[i] for i in indicies]
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q = [self.q[i] for i in indicies]
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return grid(p, q)
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def get_simplex_and_nearest_points(self, X, extra_points = 3, simplex_size = 3):
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"""
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this returns two grid objects: R and S.
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R is a grid object that is the (a) containing simplex around point X
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S is S_j from baker's paper : some points from all point that are not the simplex
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"""
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2010-03-18 22:18:59 -07:00
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(dist, indicies) = self.tree.query(X, simplex_size + extra_points)
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2010-03-08 13:30:22 -08:00
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# get the containing simplex
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r_mesh = self.create_mesh(indicies[:simplex_size])
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# and some extra points
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s_mesh = self.create_mesh(indicies[simplex_size:])
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return (r_mesh, s_mesh)
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def get_points_conn(self, X):
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"""
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this returns two grid objects: R and S.
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this function differes from the get_simplex_and_nearest_points
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function in that it builds up the extra points based on
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connectivity information, not just nearest-neighbor.
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in theory, this will work much better for situations like
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points near a short edge in a boundary layer cell where the
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nearest points would all be colinear
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R is a grid object that is the (a) containing simplex around point X
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S is a connectivity-based nearest-neighbor lookup, limited to 3 extra points
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"""
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if not self.faces:
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self.construct_connectivity()
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# get closest point
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(dist, indicies) = self.tree.query(X, 2)
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simplex = None
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for i in self.facets_for_point[indicies[0]]:
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if i.contains(X, self):
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simplex = i
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break
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if not simplex:
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raise AssertionError('no containing simplex found')
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R = self.create_mesh(simplex.verts)
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s = []
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for c,i in enumerate(simplex.neighbors):
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s.extend([guy for guy in i.verts if not guy in simplex.verts])
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S = self.create_mesh(s)
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return R, S
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def run_baker(self, X):
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answer = None
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try:
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(R, S) = self.get_simplex_and_nearest_points(X)
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answer = run_baker(X, R, S)
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except smberror, e:
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2010-03-08 13:30:22 -08:00
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print "caught error: %s, trying with connectivity-based mesh" % e
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(R, S) = self.get_points_conn(X)
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answer = run_baker(X, R, S)
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return answer
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def construct_connectivity(self):
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"""
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a call to this method prepares the internal connectivity structure.
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this is part of the __init__ for a simple_rect_grid, but can be called from any grid object
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"""
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qdelaunay_string = get_qdelaunay_dump_str(self)
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facet_to_facets = []
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for matcher in grid.facet_re.finditer(qdelaunay_string):
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d = matcher.groupdict()
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facet_name = d['facet']
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verticies = d['verts']
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neighboring_facets = d['neigh']
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cur_face = face(facet_name)
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self.faces[facet_name] = cur_face
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for v in grid.vert_re.findall(verticies):
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vertex_index = int(v[1:])
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cur_face.add_vert(vertex_index)
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self.facets_for_point[vertex_index].append(cur_face)
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nghbrs = [(facet_name, i) for i in neighboring_facets.split()]
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facet_to_facets.extend(nghbrs)
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for rel in facet_to_facets:
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if rel[1] in self.faces:
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self.faces[rel[0]].add_neighbor(self.faces[rel[1]])
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# for matcher in grid.point_re.finditer(qdelaunay_string):
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# d = matcher.groupdict()
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# point = d['point']
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# neighboring_facets = d['neigh']
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# self.facets_for_point[int(point[1:])] = [i for i in neighboring_facets.split() if i in self.faces]
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def __str__(self):
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r = ''
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assert( len(self.points) == len(self.q) )
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for c, i in enumerate(zip(self.points, self.q)):
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r += "%d %r: %0.4f" % (c,i[0], i[1])
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facet_str = ", ".join([f.name for f in self.facets_for_point[c]])
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r += " faces: [%s]" % facet_str
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r += "\n"
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if self.faces:
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for v in self.faces.itervalues():
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r += "%s\n" % v
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return r
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if __name__ == '__main__':
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try:
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resolution = int(sys.argv[1])
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except:
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resolution = 10
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g = simple_rect_grid(resolution, resolution)
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print g.for_qhull()
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