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DAMASK_EICMD
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local functions cannot be pickled (required for multiprocessing)

This commit is contained in:
Martin Diehl 2020-03-21 17:04:27 +01:00
parent c31c9be628
commit a2b92569d2
1 changed files with 7 additions and 7 deletions
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14
processing/pre/geom_fromVoronoiTessellation.py
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@ -11,6 +11,12 @@ from scipy import spatial
import damask import damask
def findClosestSeed(fargs):
seeds, myWeights, point = fargs
tmp = np.repeat(point.reshape(3,1), len(seeds), axis=1).T
dist = np.sum((tmp - seeds)**2,axis=1) -myWeights
return np.argmin(dist) # seed point closest to point
scriptName = os.path.splitext(os.path.basename(__file__))[0] scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version]) scriptID = ' '.join([scriptName,damask.version])
@ -18,12 +24,6 @@ scriptID = ' '.join([scriptName,damask.version])
def Laguerre_tessellation(grid, seeds, grains, size, periodic, weights, cpus): def Laguerre_tessellation(grid, seeds, grains, size, periodic, weights, cpus):
def findClosestSeed(fargs):
point, seeds, myWeights = fargs
tmp = np.repeat(point.reshape(3,1), len(seeds), axis=1).T
dist = np.sum((tmp - seeds)**2,axis=1) -myWeights
return np.argmin(dist) # seed point closest to point
if periodic: if periodic:
weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3) weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
seeds_p = np.vstack((seeds +np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.]))) seeds_p = np.vstack((seeds +np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
@ -33,7 +33,7 @@ def Laguerre_tessellation(grid, seeds, grains, size, periodic, weights, cpus):
weights_p = weights.flatten() weights_p = weights.flatten()
seeds_p = seeds seeds_p = seeds
arguments = [[arg,seeds_p,weights_p] for arg in list(grid)] arguments = [[seeds_p,weights_p,arg] for arg in list(grid)]
if cpus > 1: # use multithreading if cpus > 1: # use multithreading
pool = multiprocessing.Pool(processes = cpus) # initialize workers pool = multiprocessing.Pool(processes = cpus) # initialize workers