simplified
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@ -24,22 +24,22 @@ def findClosestSeed(seeds, weights, point):
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def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), periodic = True, cpus = 2):
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if periodic:
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weights_p = np.tile(weights,27).flatten(order='F') # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
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weights_p = np.tile(weights.squeeze(),27) # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
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seeds_p = np.vstack((seeds -np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
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seeds_p = np.vstack((seeds_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
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seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
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coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3,order='F')
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coords = damask.grid_filters.cell_coord0(grid*3,size*3,-origin-size).reshape(-1,3)
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else:
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weights_p = weights.flatten()
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weights_p = weights.squeeze()
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seeds_p = seeds
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
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if cpus > 1:
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pool = multiprocessing.Pool(processes = cpus)
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result = pool.map_async(partial(findClosestSeed,seeds_p,weights_p), [coord for coord in coords])
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pool.close()
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pool.join()
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closest_seed = np.array(result.get())
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closest_seed = np.array(result.get()).reshape(-1,3)
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else:
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closest_seed= np.array([findClosestSeed(seeds_p,weights_p,coord) for coord in coords])
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@ -52,7 +52,7 @@ def Laguerre_tessellation(grid, size, seeds, weights, origin = np.zeros(3), peri
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def Voronoi_tessellation(grid, size, seeds, origin = np.zeros(3), periodic = True):
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3,order='F')
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coords = damask.grid_filters.cell_coord0(grid,size,-origin).reshape(-1,3)
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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devNull,closest_seed = KDTree.query(coords)
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@ -224,7 +224,7 @@ for name in filenames:
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header = [scriptID + ' ' + ' '.join(sys.argv[1:])]\
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+ config_header
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geom = damask.Geom(indices.reshape(grid,order='F'),size,origin,
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geom = damask.Geom(indices.reshape(grid),size,origin,
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homogenization=options.homogenization,comments=header)
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damask.util.croak(geom)
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