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improved performance for non-weighted Voronoi Tessellation

This commit is contained in:
Martin Diehl 2015-10-06 18:03:06 +00:00
parent 6e05082133
commit f014cef043
1 changed files with 20 additions and 16 deletions
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36
processing/pre/geom_fromVoronoiTessellation.py
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@ -5,6 +5,7 @@ import os,sys,math,string
import numpy as np
import multiprocessing
from optparse import OptionParser
from scipy import spatial
import damask
scriptID = string.replace('$Id$','\n','\\n')
@ -75,25 +76,30 @@ def laguerreTessellation(undeformed, coords, weights, grains, nonperiodic = Fals
]).astype(float)
squaredweights = np.power(np.tile(weights,len(copies)),2) # Laguerre weights (squared, size N*n)
for i,vec in enumerate(copies): # periodic copies of seed points (size N*n)
try: seeds = np.append(seeds, coords+vec, axis=0)
except NameError: seeds = coords+vec
except NameError: seeds = coords+vec
arguments = [[arg] + [seeds,squaredweights] for arg in list(undeformed)]
if cpus > 1: # use multithreading
pool = multiprocessing.Pool(processes = cpus) # initialize workers
result = pool.map_async(findClosestSeed, arguments) # evaluate function in parallel
pool.close()
pool.join()
closestSeeds = np.array(result.get()).flatten()
if all(squaredweights == 0.0): # standard Voronoi (no weights, KD tree)
myKDTree = spatial.cKDTree(seeds)
devNull,closestSeeds = myKDTree.query(undeformed)
else:
closestSeeds = np.zeros(len(arguments),dtype='i')
for i,arg in enumerate(arguments):
closestSeeds[i] = findClosestSeed(arg)
damask.util.croak('...using {} cpu{}'.format(options.cpus, 's' if options.cpus > 1 else ''))
arguments = [[arg] + [seeds,squaredweights] for arg in list(undeformed)]
return grains[closestSeeds%coords.shape[0]] # closestSeed is modulo number of original seed points (i.e. excluding periodic copies)
if cpus > 1: # use multithreading
pool = multiprocessing.Pool(processes = cpus) # initialize workers
result = pool.map_async(findClosestSeed, arguments) # evaluate function in parallel
pool.close()
pool.join()
closestSeeds = np.array(result.get()).flatten()
else:
closestSeeds = np.zeros(len(arguments),dtype='i')
for i,arg in enumerate(arguments):
closestSeeds[i] = findClosestSeed(arg)
return grains[closestSeeds%coords.shape[0]] # closestSeed is modulo number of original seed points (i.e. excluding periodic copies)
# --------------------------------------------------------------------
# MAIN
@ -267,8 +273,6 @@ for name in filenames:
damask.util.croak('tessellating...')
damask.util.croak('...using {} cpu{}'.format(options.cpus, 's' if options.cpus > 1 else ''))
grid = np.vstack(meshgrid2(x, y, z)).reshape(3,-1).T
indices = laguerreTessellation(grid, coords, weights, grains, options.nonperiodic, options.cpus)