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DAMASK_EICMD
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simplified

This commit is contained in:
Martin Diehl 2020-03-29 19:11:36 +02:00
parent 540428aab7
commit f1b4d81fb4
1 changed files with 19 additions and 15 deletions
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34
processing/pre/geom_fromVoronoiTessellation.py
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@ -21,36 +21,42 @@ def findClosestSeed(seeds, weights, point):
return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
def Laguerre_tessellation(grid, seeds, grains, size, periodic, weights, cpus):
def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), periodic = True, cpus = 2):
if periodic:
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_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3,order='F')
else:
weights_p = weights.flatten()
seeds_p = seeds
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
if cpus > 1:
default_args = partial(findClosestSeed,seeds_p,weights_p)
pool = multiprocessing.Pool(processes = cpus) # initialize workers
result = pool.map_async(default_args, [point for point in grid]) # evaluate function in parallel
pool = multiprocessing.Pool(processes = cpus)
result = pool.map_async(partial(findClosestSeed,seeds_p,weights_p), [coord for coord in coords])
pool.close()
pool.join()
closestSeeds = np.array(result.get()).flatten()
closest_seed = np.array(result.get())
else:
closestSeeds= np.array([findClosestSeed(seeds_p,weights_p,point) for point in grid])
closest_seed= np.array([findClosestSeed(seeds_p,weights_p,coord) for coord in coords])
return grains[closestSeeds%seeds.shape[0]]
if periodic:
closest_seed = closest_seed.reshape(grid[2]*3,grid[1]*3,grid[0]*3)
return closest_seed[grid[2]:grid[2]*2,grid[1]:grid[1]*2,grid[0]:grid[0]*2]%seeds.shape[0]
else:
return closest_seed
def Voronoi_tessellation(grid, seeds, grains, size, periodic = True):
def Voronoi_tessellation(grid, size, seeds, origin = np.zeros(3), periodic = True):
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
devNull,closestSeeds = KDTree.query(grid)
devNull,closest_seed = KDTree.query(coords)
return grains[closestSeeds]
return closest_seed
# --------------------------------------------------------------------
@ -191,13 +197,11 @@ for name in filenames:
if options.eulers in table.labels:
eulers = table.get(options.eulers)
coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
if options.laguerre:
indices = Laguerre_tessellation(coords,seeds,grains,size,options.periodic,
table.get(options.weight),options.cpus)
indices = grains[Laguerre_tessellation(grid,size,seeds,table.get(options.weight),origin,
options.periodic,options.cpus)]
else:
indices = Voronoi_tessellation (coords,seeds,grains,size,options.periodic)
indices = grains[Voronoi_tessellation (grid,size,seeds,origin,options.periodic)]
config_header = []
if options.config: