avoid detour via shell
This commit is contained in:
Martin Diehl
parent
f1b4d81fb4
commit
e61c1a027b
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@ -1,11 +1,15 @@
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import sys
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from io import StringIO
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import multiprocessing
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from functools import partial
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import numpy as np
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from scipy import ndimage
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from scipy import ndimage,spatial
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from . import VTK
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from . import util
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from . import Environment
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from . import grid_filters
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class Geom:
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@ -50,7 +54,7 @@ class Geom:
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def update(self,microstructure=None,size=None,origin=None,rescale=False):
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"""
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Updates microstructure and size.
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Update microstructure and size.
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Parameters
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----------
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@ -113,7 +117,7 @@ class Geom:
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def set_comments(self,comments):
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"""
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Replaces all existing comments.
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Replace all existing comments.
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Parameters
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----------
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@ -127,7 +131,7 @@ class Geom:
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def add_comments(self,comments):
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"""
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Appends comments to existing comments.
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Append comments to existing comments.
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Parameters
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----------
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@ -140,7 +144,7 @@ class Geom:
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def set_microstructure(self,microstructure):
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"""
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Replaces the existing microstructure representation.
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Replace the existing microstructure representation.
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Parameters
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----------
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@ -159,7 +163,7 @@ class Geom:
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def set_size(self,size):
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"""
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Replaces the existing size information.
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Replace the existing size information.
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Parameters
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----------
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@ -179,7 +183,7 @@ class Geom:
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def set_origin(self,origin):
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"""
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Replaces the existing origin information.
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Replace the existing origin information.
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Parameters
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----------
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@ -196,7 +200,7 @@ class Geom:
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def set_homogenization(self,homogenization):
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"""
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Replaces the existing homogenization index.
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Replace the existing homogenization index.
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Parameters
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----------
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@ -264,7 +268,7 @@ class Geom:
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@staticmethod
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def from_file(fname):
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"""
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Reads a geom file.
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Read a geom file.
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Parameters
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----------
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@ -325,6 +329,81 @@ class Geom:
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return Geom(microstructure.reshape(grid),size,origin,homogenization,comments)
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@staticmethod
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def _find_closest_seed(seeds, weights, point):
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return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
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@staticmethod
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def from_Laguerre_tessellation(grid,size,seeds,weights,periodic=True):
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"""
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Generate geometry from Laguerre tessellation.
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Parameters
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----------
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grid : numpy.ndarray of shape (3)
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number of grid points in x,y,z direction.
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size : list or numpy.ndarray of shape (3)
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physical size of the microstructure in meter.
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seeds : numpy.ndarray of shape (:,3)
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position of the seed points in meter. All points need to lay within the box.
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weights : numpy.ndarray of shape (seeds.shape[0])
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weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation.
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periodic : Boolean, optional
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perform a periodic tessellation. Defaults to True.
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"""
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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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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 = grid_filters.cell_coord0(grid*3,size*3,-size).reshape(-1,3,order='F')
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else:
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weights_p = weights.flatten()
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seeds_p = seeds
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coords = grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
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pool = multiprocessing.Pool(processes = int(Environment().options['DAMASK_NUM_THREADS']))
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result = pool.map_async(partial(Geom._find_closest_seed,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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microstructure = np.array(result.get())
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if periodic:
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microstructure = microstructure.reshape(grid[0]*3,grid[1]*3,grid[2]*3)
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microstructure = microstructure[grid[0]:grid[0]*2,grid[1]:grid[1]*2,grid[2]:grid[2]*2]%seeds.shape[0]
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else:
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microstructure = microstructure.reshape(grid)
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#comments = 'geom.py:from_Laguerre_tessellation v{}'.format(version)
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return Geom(microstructure+1,size,homogenization=1)
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@staticmethod
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def from_Voronoi_tessellation(grid,size,seeds,periodic=True):
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"""
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Generate geometry from Voronoi tessellation.
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Parameters
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----------
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grid : numpy.ndarray of shape (3)
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number of grid points in x,y,z direction.
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size : list or numpy.ndarray of shape (3)
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physical size of the microstructure in meter.
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seeds : numpy.ndarray of shape (:,3)
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position of the seed points in meter. All points need to lay within the box.
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periodic : Boolean, optional
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perform a periodic tessellation. Defaults to True.
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"""
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coords = grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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devNull,microstructure = KDTree.query(coords)
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#comments = 'geom.py:from_Voronoi_tessellation v{}'.format(version)
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return Geom(microstructure.reshape(grid)+1,size,homogenization=1)
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def to_file(self,fname,pack=None):
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"""
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Writes a geom file.
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@ -97,3 +97,24 @@ class TestGeom:
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reference = os.path.join(reference_dir,'scale_{}.geom'.format(tag))
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if update: modified.to_file(reference)
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assert geom_equal(modified,Geom.from_file(reference))
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@pytest.mark.parametrize('periodic',[(True),(False)])
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def test_tessellation(self,periodic):
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grid = np.random.randint(10,20,3)
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size = np.random.random(3) + 1.0
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N_seeds= np.random.randint(10,30)
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seeds = np.random.rand(N_seeds,3) * np.broadcast_to(size,(N_seeds,3))
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Voronoi = Geom.from_Voronoi_tessellation( grid,size,seeds, periodic)
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Laguerre = Geom.from_Laguerre_tessellation(grid,size,seeds,np.ones(N_seeds),periodic)
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assert geom_equal(Laguerre,Voronoi)
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def test_Laguerre(self):
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grid = np.random.randint(10,20,3)
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size = np.random.random(3) + 1.0
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N_seeds= np.random.randint(10,30)
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seeds = np.random.rand(N_seeds,3) * np.broadcast_to(size,(N_seeds,3))
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weights= np.full((N_seeds),-np.inf)
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ms = np.random.randint(1, N_seeds+1)
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weights[ms-1] = np.random.random()
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Laguerre = Geom.from_Laguerre_tessellation(grid,size,seeds,weights,np.random.random()>0.5)
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assert np.all(Laguerre.microstructure == ms)
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