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DAMASK_EICMD
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compatible with older scipy versions

This commit is contained in:
Martin Diehl 2021-04-29 08:56:40 +02:00
parent 3c41cd609f
commit b061b4911d
2 changed files with 7 additions and 3 deletions
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8
python/damask/_grid.py
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@ -436,8 +436,12 @@ class Grid:
""" """
coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3) coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3)
KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds) tree = spatial.cKDTree(seeds,boxsize=size) if periodic else \
devNull,material_ = KDTree.query(coords, workers = int(os.environ.get('OMP_NUM_THREADS',4))) spatial.cKDTree(seeds)
try:
material_ = tree.query(coords, workers = int(os.environ.get('OMP_NUM_THREADS',4)))[1]
except TypeError:
material_ = tree.query(coords, n_jobs = int(os.environ.get('OMP_NUM_THREADS',4)))[1] # scipy <1.6
return Grid(material = (material_ if material is None else material[material_]).reshape(cells), return Grid(material = (material_ if material is None else material[material_]).reshape(cells),
size = size, size = size,

2
python/damask/seeds.py
View File

@ -78,7 +78,7 @@ def from_Poisson_disc(size,N_seeds,N_candidates,distance,periodic=True,rng_seed=
candidates = rng.random((N_candidates,3))*_np.broadcast_to(size,(N_candidates,3)) candidates = rng.random((N_candidates,3))*_np.broadcast_to(size,(N_candidates,3))
tree = _spatial.cKDTree(coords[:s],boxsize=size) if periodic else \ tree = _spatial.cKDTree(coords[:s],boxsize=size) if periodic else \
_spatial.cKDTree(coords[:s]) _spatial.cKDTree(coords[:s])
distances, dev_null = tree.query(candidates) distances = tree.query(candidates)[0]
best = distances.argmax() best = distances.argmax()
if distances[best] > distance: # require minimum separation if distances[best] > distance: # require minimum separation
coords[s] = candidates[best] # maximum separation to existing point cloud coords[s] = candidates[best] # maximum separation to existing point cloud