renames:
after the rename of "grid" to "cell", the name cell should not be used for the coordinates of the cell centers. In agreement with the names x_p/u_p for point positions/displacements, now the "point" is used to refer to the materialpoints (i.e. cell centers) Additionally, "_node"/"_point" are now suffixes to "coordinates"/"displacements". Finally, "coords" is renamed to "coordinates"
This commit is contained in:
parent
ac0a20696c
commit
0fdefa5e78
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@ -33,12 +33,12 @@ for filename in options.filenames:
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results = damask.Result(filename)
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if not results.structured: continue
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coords = damask.grid_filters.cell_coord0(results.grid,results.size,results.origin).reshape(-1,3,order='F')
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coords = damask.grid_filters.coordinates0_point(results.cells,results.size,results.origin).reshape(-1,3,order='F')
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N_digits = int(np.floor(np.log10(int(results.increments[-1][3:]))))+1
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N_digits = 5 # hack to keep test intact
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for inc in damask.util.show_progress(results.iterate('increments'),len(results.increments)):
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table = damask.Table(np.ones(np.product(results.grid),dtype=int)*int(inc[3:]),{'inc':(1,)})\
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table = damask.Table(np.ones(np.product(results.cells),dtype=int)*int(inc[3:]),{'inc':(1,)})\
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.add('pos',coords.reshape(-1,3))
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results.pick('homogenizations',False)
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@ -46,14 +46,14 @@ for filename in options.filenames:
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for label in options.con:
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x = results.get_dataset_location(label)
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if len(x) != 0:
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table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.grid.prod(),-1))
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table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.cells.prod(),-1))
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results.pick('phases',False)
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results.pick('homogenizations',True)
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for label in options.mat:
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x = results.get_dataset_location(label)
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if len(x) != 0:
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table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.grid.prod(),-1))
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table = table.add(label,results.read_dataset(x,0,plain=True).reshape(results.cells.prod(),-1))
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dirname = os.path.abspath(os.path.join(os.path.dirname(filename),options.dir))
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if not os.path.isdir(dirname):
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@ -71,13 +71,13 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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F = table.get(options.defgrad).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
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nodes = damask.grid_filters.node_coord(size,F)
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nodes = damask.grid_filters.coordinates_node(size,F)
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if options.shape:
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centers = damask.grid_filters.cell_coord(size,F)
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centers = damask.grid_filters.coordinates_point(size,F)
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shapeMismatch = shapeMismatch(size,F,nodes,centers)
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table = table.add('shapeMismatch(({}))'.format(options.defgrad),
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shapeMismatch.reshape(-1,1,order='F'),
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@ -44,7 +44,7 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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for label in options.labels:
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field = table.get(label)
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@ -48,24 +48,24 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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F = table.get(options.f).reshape(tuple(grid)+(-1,),order='F').reshape(tuple(grid)+(3,3))
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if options.nodal:
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damask.Table(damask.grid_filters.node_coord0(grid,size).reshape(-1,3,order='F'),
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damask.Table(damask.grid_filters.coordinates0_node(grid,size).reshape(-1,3,order='F'),
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{'pos':(3,)})\
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.add('avg({}).{}'.format(options.f,options.pos),
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damask.grid_filters.node_displacement_avg(size,F).reshape(-1,3,order='F'),
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damask.grid_filters.displacement_avg_node(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))\
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.add('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.node_displacement_fluct(size,F).reshape(-1,3,order='F'),
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damask.grid_filters.displacement_fluct_node(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))\
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.save((sys.stdout if name is None else os.path.splitext(name)[0]+'_nodal.txt'))
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else:
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table.add('avg({}).{}'.format(options.f,options.pos),
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damask.grid_filters.cell_displacement_avg(size,F).reshape(-1,3,order='F'),
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damask.grid_filters.displacement_avg_point(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))\
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.add('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.cell_displacement_fluct(size,F).reshape(-1,3,order='F'),
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damask.grid_filters.displacement_fluct_point(size,F).reshape(-1,3,order='F'),
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scriptID+' '+' '.join(sys.argv[1:]))\
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.save((sys.stdout if name is None else name))
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@ -44,7 +44,7 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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for label in options.labels:
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field = table.get(label)
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@ -143,7 +143,7 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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neighborhood = neighborhoods[options.neighborhood]
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diffToNeighbor = np.empty(list(grid+2)+[len(neighborhood)],'i')
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@ -44,7 +44,7 @@ for name in filenames:
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damask.util.report(scriptName,name)
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table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size,origin = damask.grid_filters.cell_coord0_gridSizeOrigin(table.get(options.pos))
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grid,size,origin = damask.grid_filters.cellSizeOrigin_coordinates0_point(table.get(options.pos))
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for label in options.labels:
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field = table.get(label)
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@ -302,7 +302,7 @@ class Geom:
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Each unique combintation of values results in one material ID.
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"""
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cells,size,origin = grid_filters.cell_coord0_gridSizeOrigin(table.get(coordinates))
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cells,size,origin = grid_filters.cellSizeOrigin_coordinates0_point(table.get(coordinates))
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labels_ = [labels] if isinstance(labels,str) else labels
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unique,unique_inverse = np.unique(np.hstack([table.get(l) for l in labels_]),return_inverse=True,axis=0)
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@ -344,11 +344,11 @@ class Geom:
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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(cells*3,size*3,-size).reshape(-1,3)
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coords = grid_filters.coordinates0_point(cells*3,size*3,-size).reshape(-1,3)
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else:
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weights_p = weights
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seeds_p = seeds
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coords = grid_filters.cell_coord0(cells,size).reshape(-1,3)
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coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3)
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pool = mp.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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@ -388,7 +388,7 @@ class Geom:
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Perform a periodic tessellation. Defaults to True.
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"""
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coords = grid_filters.cell_coord0(cells,size).reshape(-1,3)
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coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3)
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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devNull,material_ = KDTree.query(coords)
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@ -592,7 +592,7 @@ class Geom:
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c = (np.array(center) + .5)*self.size/self.cells if np.array(center).dtype in np.sctypes['int'] else \
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(np.array(center) - self.origin)
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coords = grid_filters.cell_coord0(self.cells,self.size,
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coords = grid_filters.coordinates0_point(self.cells,self.size,
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-(0.5*(self.size + (self.size/self.cells
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if np.array(center).dtype in np.sctypes['int'] else
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0)) if periodic else c))
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base_nodes = np.argwhere(mask.flatten(order='F')).reshape(-1,1)
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connectivity.append(np.block([base_nodes + o[i][k] for k in range(4)]))
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coords = grid_filters.node_coord0(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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coords = grid_filters.coordinates0_node(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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return VTK.from_unstructured_grid(coords,np.vstack(connectivity),'QUAD')
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return dataset
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@property
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def cell_coordinates(self):
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def coordinates0_point(self):
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"""Return initial coordinates of the cell centers."""
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if self.structured:
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return grid_filters.cell_coord0(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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return grid_filters.coordinates0_point(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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else:
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with h5py.File(self.fname,'r') as f:
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return f['geometry/x_c'][()]
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@property
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def node_coordinates(self):
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def coordinates0_node(self):
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"""Return initial coordinates of the cell centers."""
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if self.structured:
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return grid_filters.node_coord0(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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return grid_filters.coordinates0_node(self.cells,self.size,self.origin).reshape(-1,3,order='F')
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else:
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with h5py.File(self.fname,'r') as f:
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return f['geometry/x_n'][()]
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f['/geometry/T_c'].attrs['VTK_TYPE'] if h5py3 else \
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f['/geometry/T_c'].attrs['VTK_TYPE'].decode())
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elif mode.lower()=='point':
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v = VTK.from_poly_data(self.cell_coordinates)
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v = VTK.from_poly_data(self.coordinates0_point)
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N_digits = int(np.floor(np.log10(max(1,int(self.increments[-1][3:])))))+1
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@ -763,7 +763,7 @@ class Rotation:
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def _dg(eu,deg):
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"""Return infinitesimal Euler space volume of bin(s)."""
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phi_sorted = eu[np.lexsort((eu[:,0],eu[:,1],eu[:,2]))]
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steps,size,_ = grid_filters.cell_coord0_gridSizeOrigin(phi_sorted)
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steps,size,_ = grid_filters.cellSizeOrigin_coordinates0_point(phi_sorted)
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delta = np.radians(size/steps) if deg else size/steps
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return delta[0]*2.0*np.sin(delta[1]/2.0)*delta[2] / 8.0 / np.pi**2 * np.sin(np.radians(eu[:,1]) if deg else eu[:,1])
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@ -22,11 +22,11 @@ def _ks(size,cells,first_order=False):
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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cells : numpy.ndarray of shape (3)
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number of cells.
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Number of cells.
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first_order : bool, optional
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correction for first order derivatives, defaults to False.
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Correction for first order derivatives, defaults to False.
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"""
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k_sk = _np.where(_np.arange(cells[0])>cells[0]//2,_np.arange(cells[0])-cells[0],_np.arange(cells[0]))/size[0]
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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field : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
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periodic field of which the curl is calculated.
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Periodic field of which the curl is calculated.
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"""
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n = _np.prod(field.shape[3:])
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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field : numpy.ndarray of shape (:,:,:,3) or (:,:,:,3,3)
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periodic field of which the divergence is calculated.
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Periodic field of which the divergence is calculated.
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"""
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n = _np.prod(field.shape[3:])
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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field : numpy.ndarray of shape (:,:,:,1) or (:,:,:,3)
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periodic field of which the gradient is calculated.
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Periodic field of which the gradient is calculated.
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"""
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n = _np.prod(field.shape[3:])
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return _np.fft.irfftn(grad_,axes=(0,1,2),s=field.shape[:3])
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def cell_coord0(cells,size,origin=_np.zeros(3)):
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def coordinates0_point(cells,size,origin=_np.zeros(3)):
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"""
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Cell center positions (undeformed).
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Parameters
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----------
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cells : numpy.ndarray of shape (3)
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number of cells.
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Number of cells.
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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origin : numpy.ndarray, optional
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physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
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Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
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"""
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start = origin + size/cells*.5
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axis = -1)
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def cell_displacement_fluct(size,F):
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def displacement_fluct_point(size,F):
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"""
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Cell center displacement field from fluctuation part of the deformation gradient field.
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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F : numpy.ndarray
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deformation gradient field.
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Deformation gradient field.
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"""
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integrator = 0.5j*size/_np.pi
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return _np.fft.irfftn(displacement,axes=(0,1,2),s=F.shape[:3])
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def cell_displacement_avg(size,F):
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def displacement_avg_point(size,F):
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"""
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Cell center displacement field from average part of the deformation gradient field.
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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F : numpy.ndarray
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deformation gradient field.
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Deformation gradient field.
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"""
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F_avg = _np.average(F,axis=(0,1,2))
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return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),cell_coord0(F.shape[:3],size))
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return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_point(F.shape[:3],size))
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def cell_displacement(size,F):
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def displacement_point(size,F):
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"""
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Cell center displacement field from deformation gradient field.
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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F : numpy.ndarray
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deformation gradient field.
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Deformation gradient field.
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"""
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return cell_displacement_avg(size,F) + cell_displacement_fluct(size,F)
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return displacement_avg_point(size,F) + displacement_fluct_point(size,F)
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def cell_coord(size,F,origin=_np.zeros(3)):
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def coordinates_point(size,F,origin=_np.zeros(3)):
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"""
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Cell center positions.
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Parameters
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----------
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size : numpy.ndarray of shape (3)
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physical size of the periodic field.
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Physical size of the periodic field.
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F : numpy.ndarray
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deformation gradient field.
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Deformation gradient field.
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origin : numpy.ndarray of shape (3), optional
|
||||
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
|
||||
"""
|
||||
return cell_coord0(F.shape[:3],size,origin) + cell_displacement(size,F)
|
||||
return coordinates0_point(F.shape[:3],size,origin) + displacement_point(size,F)
|
||||
|
||||
|
||||
def cell_coord0_gridSizeOrigin(coord0,ordered=True):
|
||||
def cellSizeOrigin_coordinates0_point(coordinates0,ordered=True):
|
||||
"""
|
||||
Return grid 'DNA', i.e. cells, size, and origin from 1D array of cell positions.
|
||||
Return grid 'DNA', i.e. cells, size, and origin from 1D array of point positions.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
coord0 : numpy.ndarray of shape (:,3)
|
||||
undeformed cell coordinates.
|
||||
coordinates0 : numpy.ndarray of shape (:,3)
|
||||
Undeformed cell coordinates.
|
||||
ordered : bool, optional
|
||||
expect coord0 data to be ordered (x fast, z slow).
|
||||
Expect coordinates0 data to be ordered (x fast, z slow).
|
||||
|
||||
"""
|
||||
coords = [_np.unique(coord0[:,i]) for i in range(3)]
|
||||
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
||||
mincorner = _np.array(list(map(min,coords)))
|
||||
maxcorner = _np.array(list(map(max,coords)))
|
||||
cells = _np.array(list(map(len,coords)),'i')
|
||||
|
@ -232,8 +232,8 @@ def cell_coord0_gridSizeOrigin(coord0,ordered=True):
|
|||
size [_np.where(cells==1)] = origin[_np.where(cells==1)]*2.
|
||||
origin[_np.where(cells==1)] = 0.0
|
||||
|
||||
if cells.prod() != len(coord0):
|
||||
raise ValueError('Data count {len(coord0)} does not match cells {cells}.')
|
||||
if cells.prod() != len(coordinates0):
|
||||
raise ValueError('Data count {len(coordinates0)} does not match cells {cells}.')
|
||||
|
||||
start = origin + delta*.5
|
||||
end = origin - delta*.5 + size
|
||||
|
@ -244,37 +244,38 @@ def cell_coord0_gridSizeOrigin(coord0,ordered=True):
|
|||
_np.allclose(coords[2],_np.linspace(start[2],end[2],cells[2]),atol=atol)):
|
||||
raise ValueError('Regular cells spacing violated.')
|
||||
|
||||
if ordered and not _np.allclose(coord0.reshape(tuple(cells)+(3,),order='F'),cell_coord0(cells,size,origin),atol=atol):
|
||||
if ordered and not _np.allclose(coordinates0.reshape(tuple(cells)+(3,),order='F'),
|
||||
coordinates0_point(cells,size,origin),atol=atol):
|
||||
raise ValueError('Input data is not ordered (x fast, z slow).')
|
||||
|
||||
return (cells,size,origin)
|
||||
|
||||
|
||||
def coord0_check(coord0):
|
||||
def coordinates0_check(coordinates0):
|
||||
"""
|
||||
Check whether coordinates lie on a regular grid.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
coord0 : numpy.ndarray
|
||||
array of undeformed cell coordinates.
|
||||
coordinates0 : numpy.ndarray
|
||||
Array of undeformed cell coordinates.
|
||||
|
||||
"""
|
||||
cell_coord0_gridSizeOrigin(coord0,ordered=True)
|
||||
cellSizeOrigin_coordinates0_point(coordinates0,ordered=True)
|
||||
|
||||
|
||||
def node_coord0(cells,size,origin=_np.zeros(3)):
|
||||
def coordinates0_node(cells,size,origin=_np.zeros(3)):
|
||||
"""
|
||||
Nodal positions (undeformed).
|
||||
|
||||
Parameters
|
||||
----------
|
||||
cells : numpy.ndarray of shape (3)
|
||||
number of cells.
|
||||
Number of cells.
|
||||
size : numpy.ndarray of shape (3)
|
||||
physical size of the periodic field.
|
||||
Physical size of the periodic field.
|
||||
origin : numpy.ndarray of shape (3), optional
|
||||
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
|
||||
"""
|
||||
return _np.stack(_np.meshgrid(_np.linspace(origin[0],size[0]+origin[0],cells[0]+1),
|
||||
|
@ -283,71 +284,71 @@ def node_coord0(cells,size,origin=_np.zeros(3)):
|
|||
axis = -1)
|
||||
|
||||
|
||||
def node_displacement_fluct(size,F):
|
||||
def displacement_fluct_node(size,F):
|
||||
"""
|
||||
Nodal displacement field from fluctuation part of the deformation gradient field.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
size : numpy.ndarray of shape (3)
|
||||
physical size of the periodic field.
|
||||
Physical size of the periodic field.
|
||||
F : numpy.ndarray
|
||||
deformation gradient field.
|
||||
Deformation gradient field.
|
||||
|
||||
"""
|
||||
return cell_2_node(cell_displacement_fluct(size,F))
|
||||
return point_2_node(displacement_fluct_point(size,F))
|
||||
|
||||
|
||||
def node_displacement_avg(size,F):
|
||||
def displacement_avg_node(size,F):
|
||||
"""
|
||||
Nodal displacement field from average part of the deformation gradient field.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
size : numpy.ndarray of shape (3)
|
||||
physical size of the periodic field.
|
||||
Physical size of the periodic field.
|
||||
F : numpy.ndarray
|
||||
deformation gradient field.
|
||||
Deformation gradient field.
|
||||
|
||||
"""
|
||||
F_avg = _np.average(F,axis=(0,1,2))
|
||||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),node_coord0(F.shape[:3],size))
|
||||
return _np.einsum('ml,ijkl->ijkm',F_avg - _np.eye(3),coordinates0_node(F.shape[:3],size))
|
||||
|
||||
|
||||
def node_displacement(size,F):
|
||||
def displacement_node(size,F):
|
||||
"""
|
||||
Nodal displacement field from deformation gradient field.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
size : numpy.ndarray of shape (3)
|
||||
physical size of the periodic field.
|
||||
Physical size of the periodic field.
|
||||
F : numpy.ndarray
|
||||
deformation gradient field.
|
||||
Deformation gradient field.
|
||||
|
||||
"""
|
||||
return node_displacement_avg(size,F) + node_displacement_fluct(size,F)
|
||||
return displacement_avg_node(size,F) + displacement_fluct_node(size,F)
|
||||
|
||||
|
||||
def node_coord(size,F,origin=_np.zeros(3)):
|
||||
def coordinates_node(size,F,origin=_np.zeros(3)):
|
||||
"""
|
||||
Nodal positions.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
size : numpy.ndarray of shape (3)
|
||||
physical size of the periodic field.
|
||||
Physical size of the periodic field.
|
||||
F : numpy.ndarray
|
||||
deformation gradient field.
|
||||
Deformation gradient field.
|
||||
origin : numpy.ndarray of shape (3), optional
|
||||
physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
Physical origin of the periodic field. Defaults to [0.0,0.0,0.0].
|
||||
|
||||
"""
|
||||
return node_coord0(F.shape[:3],size,origin) + node_displacement(size,F)
|
||||
return coordinates0_node(F.shape[:3],size,origin) + displacement_node(size,F)
|
||||
|
||||
|
||||
def cell_2_node(cell_data):
|
||||
"""Interpolate periodic cell data to nodal data."""
|
||||
def point_2_node(cell_data):
|
||||
"""Interpolate periodic point data to nodal data."""
|
||||
n = ( cell_data + _np.roll(cell_data,1,(0,1,2))
|
||||
+ _np.roll(cell_data,1,(0,)) + _np.roll(cell_data,1,(1,)) + _np.roll(cell_data,1,(2,))
|
||||
+ _np.roll(cell_data,1,(0,1)) + _np.roll(cell_data,1,(1,2)) + _np.roll(cell_data,1,(2,0)))*0.125
|
||||
|
@ -355,8 +356,8 @@ def cell_2_node(cell_data):
|
|||
return _np.pad(n,((0,1),(0,1),(0,1))+((0,0),)*len(cell_data.shape[3:]),mode='wrap')
|
||||
|
||||
|
||||
def node_2_cell(node_data):
|
||||
"""Interpolate periodic nodal data to cell data."""
|
||||
def node_2_point(node_data):
|
||||
"""Interpolate periodic nodal data to point data."""
|
||||
c = ( node_data + _np.roll(node_data,1,(0,1,2))
|
||||
+ _np.roll(node_data,1,(0,)) + _np.roll(node_data,1,(1,)) + _np.roll(node_data,1,(2,))
|
||||
+ _np.roll(node_data,1,(0,1)) + _np.roll(node_data,1,(1,2)) + _np.roll(node_data,1,(2,0)))*0.125
|
||||
|
@ -364,27 +365,27 @@ def node_2_cell(node_data):
|
|||
return c[1:,1:,1:]
|
||||
|
||||
|
||||
def node_coord0_gridSizeOrigin(coord0,ordered=True):
|
||||
def cellSizeOrigin_coordinates0_node(coordinates0,ordered=True):
|
||||
"""
|
||||
Return grid 'DNA', i.e. cells, size, and origin from 1D array of nodal positions.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
coord0 : numpy.ndarray of shape (:,3)
|
||||
undeformed nodal coordinates.
|
||||
coordinates0 : numpy.ndarray of shape (:,3)
|
||||
Undeformed nodal coordinates.
|
||||
ordered : bool, optional
|
||||
expect coord0 data to be ordered (x fast, z slow).
|
||||
Expect coordinates0 data to be ordered (x fast, z slow).
|
||||
|
||||
"""
|
||||
coords = [_np.unique(coord0[:,i]) for i in range(3)]
|
||||
coords = [_np.unique(coordinates0[:,i]) for i in range(3)]
|
||||
mincorner = _np.array(list(map(min,coords)))
|
||||
maxcorner = _np.array(list(map(max,coords)))
|
||||
cells = _np.array(list(map(len,coords)),'i') - 1
|
||||
size = maxcorner-mincorner
|
||||
origin = mincorner
|
||||
|
||||
if (cells+1).prod() != len(coord0):
|
||||
raise ValueError('Data count {len(coord0)} does not match cells {cells}.')
|
||||
if (cells+1).prod() != len(coordinates0):
|
||||
raise ValueError('Data count {len(coordinates0)} does not match cells {cells}.')
|
||||
|
||||
atol = _np.max(size)*5e-2
|
||||
if not (_np.allclose(coords[0],_np.linspace(mincorner[0],maxcorner[0],cells[0]+1),atol=atol) and \
|
||||
|
@ -392,7 +393,8 @@ def node_coord0_gridSizeOrigin(coord0,ordered=True):
|
|||
_np.allclose(coords[2],_np.linspace(mincorner[2],maxcorner[2],cells[2]+1),atol=atol)):
|
||||
raise ValueError('Regular cells spacing violated.')
|
||||
|
||||
if ordered and not _np.allclose(coord0.reshape(tuple(cells+1)+(3,),order='F'),node_coord0(cells,size,origin),atol=atol):
|
||||
if ordered and not _np.allclose(coordinates0.reshape(tuple(cells+1)+(3,),order='F'),
|
||||
coordinates0_node(cells,size,origin),atol=atol):
|
||||
raise ValueError('Input data is not ordered (x fast, z slow).')
|
||||
|
||||
return (cells,size,origin)
|
||||
|
@ -412,9 +414,9 @@ def regrid(size,F,cells_new):
|
|||
New cells for undeformed coordinates.
|
||||
|
||||
"""
|
||||
c = cell_coord0(F.shape[:3],size) \
|
||||
+ cell_displacement_avg(size,F) \
|
||||
+ cell_displacement_fluct(size,F)
|
||||
c = coordinates0_point(F.shape[:3],size) \
|
||||
+ displacement_avg_point(size,F) \
|
||||
+ displacement_fluct_point(size,F)
|
||||
|
||||
outer = _np.dot(_np.average(F,axis=(0,1,2)),size)
|
||||
for d in range(3):
|
||||
|
@ -422,4 +424,4 @@ def regrid(size,F,cells_new):
|
|||
c[_np.where(c[:,:,:,d]>outer[d])] -= outer[d]
|
||||
|
||||
tree = _spatial.cKDTree(c.reshape(-1,3),boxsize=outer)
|
||||
return tree.query(cell_coord0(cells_new,outer))[1].flatten()
|
||||
return tree.query(coordinates0_point(cells_new,outer))[1].flatten()
|
||||
|
|
|
@ -29,7 +29,7 @@ def from_random(size,N_seeds,cells=None,rng_seed=None):
|
|||
if cells is None:
|
||||
coords = rng.random((N_seeds,3)) * size
|
||||
else:
|
||||
grid_coords = grid_filters.cell_coord0(cells,size).reshape(-1,3,order='F')
|
||||
grid_coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
|
||||
coords = grid_coords[rng.choice(_np.prod(cells),N_seeds, replace=False)] \
|
||||
+ _np.broadcast_to(size/cells,(N_seeds,3))*(rng.random((N_seeds,3))*.5-.25) # wobble without leaving cells
|
||||
|
||||
|
@ -98,7 +98,7 @@ def from_geom(geom,selection=None,invert=False,average=False,periodic=True):
|
|||
material = geom.material.reshape((-1,1),order='F')
|
||||
mask = _np.full(geom.cells.prod(),True,dtype=bool) if selection is None else \
|
||||
_np.isin(material,selection,invert=invert).flatten()
|
||||
coords = grid_filters.cell_coord0(geom.cells,geom.size).reshape(-1,3,order='F')
|
||||
coords = grid_filters.coordinates0_point(geom.cells,geom.size).reshape(-1,3,order='F')
|
||||
|
||||
if not average:
|
||||
return (coords[mask],material[mask])
|
||||
|
|
|
@ -394,7 +394,7 @@ class TestGeom:
|
|||
def test_from_table(self):
|
||||
cells = np.random.randint(60,100,3)
|
||||
size = np.ones(3)+np.random.rand(3)
|
||||
coords = grid_filters.cell_coord0(cells,size).reshape(-1,3,order='F')
|
||||
coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
|
||||
z=np.ones(cells.prod())
|
||||
z[cells[:2].prod()*int(cells[2]/2):]=0
|
||||
t = Table(np.column_stack((coords,z)),{'coords':3,'z':1})
|
||||
|
@ -407,7 +407,7 @@ class TestGeom:
|
|||
size = np.ones(3)+np.random.rand(3)
|
||||
s = seeds.from_random(size,np.random.randint(60,100))
|
||||
geom = Geom.from_Voronoi_tessellation(cells,size,s)
|
||||
coords = grid_filters.cell_coord0(cells,size)
|
||||
coords = grid_filters.coordinates0_point(cells,size)
|
||||
t = Table(np.column_stack((coords.reshape(-1,3,order='F'),geom.material.flatten(order='F'))),{'c':3,'m':1})
|
||||
assert geom_equal(geom.sort().renumber(),Geom.from_table(t,'c',['m']))
|
||||
|
||||
|
|
|
@ -356,11 +356,11 @@ class TestResult:
|
|||
@pytest.mark.parametrize('mode',['cell','node'])
|
||||
def test_coordinates(self,default,mode):
|
||||
if mode == 'cell':
|
||||
a = grid_filters.cell_coord0(default.cells,default.size,default.origin)
|
||||
b = default.cell_coordinates.reshape(tuple(default.cells)+(3,),order='F')
|
||||
a = grid_filters.coordinates0_point(default.cells,default.size,default.origin)
|
||||
b = default.coordinates0_point.reshape(tuple(default.cells)+(3,),order='F')
|
||||
elif mode == 'node':
|
||||
a = grid_filters.node_coord0(default.cells,default.size,default.origin)
|
||||
b = default.node_coordinates.reshape(tuple(default.cells+1)+(3,),order='F')
|
||||
a = grid_filters.coordinates0_node(default.cells,default.size,default.origin)
|
||||
b = default.coordinates0_node.reshape(tuple(default.cells+1)+(3,),order='F')
|
||||
assert np.allclose(a,b)
|
||||
|
||||
@pytest.mark.parametrize('output',['F',[],['F','P']])
|
||||
|
|
|
@ -1022,7 +1022,7 @@ class TestRotation:
|
|||
rng = tuple(zip(np.zeros(3),limits))
|
||||
|
||||
weights = Table.load(ref_path/'ODF_experimental_cell.txt').get('intensity').flatten()
|
||||
Eulers = grid_filters.cell_coord0(steps,limits)
|
||||
Eulers = grid_filters.coordinates0_point(steps,limits)
|
||||
Eulers = np.radians(Eulers) if not degrees else Eulers
|
||||
|
||||
Eulers_r = Rotation.from_ODF(weights,Eulers.reshape(-1,3,order='F'),N,degrees,fractions).as_Euler_angles(True)
|
||||
|
@ -1040,7 +1040,7 @@ class TestRotation:
|
|||
weights = Table.load(ref_path/'ODF_experimental.txt').get('intensity')
|
||||
weights = weights.reshape(steps+1,order='F')[:-1,:-1,:-1].reshape(-1,order='F')
|
||||
|
||||
Eulers = grid_filters.node_coord0(steps,limits)[:-1,:-1,:-1]
|
||||
Eulers = grid_filters.coordinates0_node(steps,limits)[:-1,:-1,:-1]
|
||||
Eulers = np.radians(Eulers) if not degrees else Eulers
|
||||
|
||||
Eulers_r = Rotation.from_ODF(weights,Eulers.reshape(-1,3,order='F'),N,degrees).as_Euler_angles(True)
|
||||
|
|
|
@ -155,8 +155,8 @@ class TestVTK:
|
|||
cells = np.array([5,6,7],int)
|
||||
size = np.array([.6,1.,.5])
|
||||
rectilinearGrid = VTK.from_rectilinear_grid(cells,size)
|
||||
c = grid_filters.cell_coord0(cells,size).reshape(-1,3,order='F')
|
||||
n = grid_filters.node_coord0(cells,size).reshape(-1,3,order='F')
|
||||
c = grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
|
||||
n = grid_filters.coordinates0_node(cells,size).reshape(-1,3,order='F')
|
||||
rectilinearGrid.add(c,'cell')
|
||||
rectilinearGrid.add(n,'node')
|
||||
if update:
|
||||
|
|
|
@ -5,33 +5,33 @@ from damask import grid_filters
|
|||
|
||||
class TestGridFilters:
|
||||
|
||||
def test_cell_coord0(self):
|
||||
def test_coordinates0_point(self):
|
||||
size = np.random.random(3)
|
||||
cells = np.random.randint(8,32,(3))
|
||||
coord = grid_filters.cell_coord0(cells,size)
|
||||
coord = grid_filters.coordinates0_point(cells,size)
|
||||
assert np.allclose(coord[0,0,0],size/cells*.5) and coord.shape == tuple(cells) + (3,)
|
||||
|
||||
def test_node_coord0(self):
|
||||
def test_coordinates0_node(self):
|
||||
size = np.random.random(3)
|
||||
cells = np.random.randint(8,32,(3))
|
||||
coord = grid_filters.node_coord0(cells,size)
|
||||
coord = grid_filters.coordinates0_node(cells,size)
|
||||
assert np.allclose(coord[-1,-1,-1],size) and coord.shape == tuple(cells+1) + (3,)
|
||||
|
||||
def test_coord0(self):
|
||||
size = np.random.random(3)
|
||||
cells = np.random.randint(8,32,(3))
|
||||
c = grid_filters.cell_coord0(cells+1,size+size/cells)
|
||||
n = grid_filters.node_coord0(cells,size) + size/cells*.5
|
||||
c = grid_filters.coordinates0_point(cells+1,size+size/cells)
|
||||
n = grid_filters.coordinates0_node(cells,size) + size/cells*.5
|
||||
assert np.allclose(c,n)
|
||||
|
||||
@pytest.mark.parametrize('mode',['cell','node'])
|
||||
@pytest.mark.parametrize('mode',['point','node'])
|
||||
def test_grid_DNA(self,mode):
|
||||
"""Ensure that xx_coord0_gridSizeOrigin is the inverse of xx_coord0."""
|
||||
"""Ensure that cellSizeOrigin_coordinates0_xx is the inverse of coordinates0_xx."""
|
||||
cells = np.random.randint(8,32,(3))
|
||||
size = np.random.random(3)
|
||||
origin = np.random.random(3)
|
||||
coord0 = eval(f'grid_filters.{mode}_coord0(cells,size,origin)') # noqa
|
||||
_cells,_size,_origin = eval(f'grid_filters.{mode}_coord0_gridSizeOrigin(coord0.reshape(-1,3,order="F"))')
|
||||
coord0 = eval(f'grid_filters.coordinates0_{mode}(cells,size,origin)') # noqa
|
||||
_cells,_size,_origin = eval(f'grid_filters.cellSizeOrigin_coordinates0_{mode}(coord0.reshape(-1,3,order="F"))')
|
||||
assert np.allclose(cells,_cells) and np.allclose(size,_size) and np.allclose(origin,_origin)
|
||||
|
||||
def test_displacement_fluct_equivalence(self):
|
||||
|
@ -39,43 +39,43 @@ class TestGridFilters:
|
|||
size = np.random.random(3)
|
||||
cells = np.random.randint(8,32,(3))
|
||||
F = np.random.random(tuple(cells)+(3,3))
|
||||
assert np.allclose(grid_filters.node_displacement_fluct(size,F),
|
||||
grid_filters.cell_2_node(grid_filters.cell_displacement_fluct(size,F)))
|
||||
assert np.allclose(grid_filters.displacement_fluct_node(size,F),
|
||||
grid_filters.point_2_node(grid_filters.displacement_fluct_point(size,F)))
|
||||
|
||||
def test_interpolation_to_node(self):
|
||||
size = np.random.random(3)
|
||||
cells = np.random.randint(8,32,(3))
|
||||
F = np.random.random(tuple(cells)+(3,3))
|
||||
assert np.allclose(grid_filters.node_coord(size,F) [1:-1,1:-1,1:-1],
|
||||
grid_filters.cell_2_node(grid_filters.cell_coord(size,F))[1:-1,1:-1,1:-1])
|
||||
assert np.allclose(grid_filters.coordinates_node(size,F) [1:-1,1:-1,1:-1],
|
||||
grid_filters.point_2_node(grid_filters.coordinates_point(size,F))[1:-1,1:-1,1:-1])
|
||||
|
||||
def test_interpolation_to_cell(self):
|
||||
cells = np.random.randint(1,30,(3))
|
||||
|
||||
node_coord_x = np.linspace(0,np.pi*2,num=cells[0]+1)
|
||||
node_field_x = np.cos(node_coord_x)
|
||||
coordinates_node_x = np.linspace(0,np.pi*2,num=cells[0]+1)
|
||||
node_field_x = np.cos(coordinates_node_x)
|
||||
node_field = np.broadcast_to(node_field_x.reshape(-1,1,1),cells+1)
|
||||
|
||||
cell_coord_x = node_coord_x[:-1]+node_coord_x[1]*.5
|
||||
cell_field_x = np.interp(cell_coord_x,node_coord_x,node_field_x,period=np.pi*2.)
|
||||
coordinates0_point_x = coordinates_node_x[:-1]+coordinates_node_x[1]*.5
|
||||
cell_field_x = np.interp(coordinates0_point_x,coordinates_node_x,node_field_x,period=np.pi*2.)
|
||||
cell_field = np.broadcast_to(cell_field_x.reshape(-1,1,1),cells)
|
||||
|
||||
assert np.allclose(cell_field,grid_filters.node_2_cell(node_field))
|
||||
assert np.allclose(cell_field,grid_filters.node_2_point(node_field))
|
||||
|
||||
@pytest.mark.parametrize('mode',['cell','node'])
|
||||
def test_coord0_origin(self,mode):
|
||||
@pytest.mark.parametrize('mode',['point','node'])
|
||||
def test_coordinates0_origin(self,mode):
|
||||
origin= np.random.random(3)
|
||||
size = np.random.random(3) # noqa
|
||||
cells = np.random.randint(8,32,(3))
|
||||
shifted = eval(f'grid_filters.{mode}_coord0(cells,size,origin)')
|
||||
unshifted = eval(f'grid_filters.{mode}_coord0(cells,size)')
|
||||
shifted = eval(f'grid_filters.coordinates0_{mode}(cells,size,origin)')
|
||||
unshifted = eval(f'grid_filters.coordinates0_{mode}(cells,size)')
|
||||
if mode == 'cell':
|
||||
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(cells) +(3,)))
|
||||
elif mode == 'node':
|
||||
assert np.allclose(shifted,unshifted+np.broadcast_to(origin,tuple(cells+1)+(3,)))
|
||||
|
||||
@pytest.mark.parametrize('function',[grid_filters.cell_displacement_avg,
|
||||
grid_filters.node_displacement_avg])
|
||||
@pytest.mark.parametrize('function',[grid_filters.displacement_avg_point,
|
||||
grid_filters.displacement_avg_node])
|
||||
def test_displacement_avg_vanishes(self,function):
|
||||
"""Ensure that random fluctuations in F do not result in average displacement."""
|
||||
size = np.random.random(3)
|
||||
|
@ -84,8 +84,8 @@ class TestGridFilters:
|
|||
F += np.eye(3) - np.average(F,axis=(0,1,2))
|
||||
assert np.allclose(function(size,F),0.0)
|
||||
|
||||
@pytest.mark.parametrize('function',[grid_filters.cell_displacement_fluct,
|
||||
grid_filters.node_displacement_fluct])
|
||||
@pytest.mark.parametrize('function',[grid_filters.displacement_fluct_point,
|
||||
grid_filters.displacement_fluct_node])
|
||||
def test_displacement_fluct_vanishes(self,function):
|
||||
"""Ensure that constant F does not result in fluctuating displacement."""
|
||||
size = np.random.random(3)
|
||||
|
@ -93,16 +93,16 @@ class TestGridFilters:
|
|||
F = np.broadcast_to(np.random.random((3,3)), tuple(cells)+(3,3))
|
||||
assert np.allclose(function(size,F),0.0)
|
||||
|
||||
@pytest.mark.parametrize('function',[grid_filters.coord0_check,
|
||||
grid_filters.node_coord0_gridSizeOrigin,
|
||||
grid_filters.cell_coord0_gridSizeOrigin])
|
||||
@pytest.mark.parametrize('function',[grid_filters.coordinates0_check,
|
||||
grid_filters.cellSizeOrigin_coordinates0_node,
|
||||
grid_filters.cellSizeOrigin_coordinates0_point])
|
||||
def test_invalid_coordinates(self,function):
|
||||
invalid_coordinates = np.random.random((np.random.randint(12,52),3))
|
||||
with pytest.raises(ValueError):
|
||||
function(invalid_coordinates)
|
||||
|
||||
@pytest.mark.parametrize('function',[grid_filters.node_coord0_gridSizeOrigin,
|
||||
grid_filters.cell_coord0_gridSizeOrigin])
|
||||
@pytest.mark.parametrize('function',[grid_filters.cellSizeOrigin_coordinates0_node,
|
||||
grid_filters.cellSizeOrigin_coordinates0_point])
|
||||
def test_uneven_spaced_coordinates(self,function):
|
||||
start = np.random.random(3)
|
||||
end = np.random.random(3)*10. + start
|
||||
|
@ -116,13 +116,13 @@ class TestGridFilters:
|
|||
|
||||
|
||||
@pytest.mark.parametrize('mode',[True,False])
|
||||
@pytest.mark.parametrize('function',[grid_filters.node_coord0_gridSizeOrigin,
|
||||
grid_filters.cell_coord0_gridSizeOrigin])
|
||||
@pytest.mark.parametrize('function',[grid_filters.cellSizeOrigin_coordinates0_node,
|
||||
grid_filters.cellSizeOrigin_coordinates0_point])
|
||||
def test_unordered_coordinates(self,function,mode):
|
||||
origin = np.random.random(3)
|
||||
size = np.random.random(3)*10.+origin
|
||||
cells = np.random.randint(8,32,(3))
|
||||
unordered = grid_filters.node_coord0(cells,size,origin).reshape(-1,3)
|
||||
unordered = grid_filters.coordinates0_node(cells,size,origin).reshape(-1,3)
|
||||
if mode:
|
||||
with pytest.raises(ValueError):
|
||||
function(unordered,mode)
|
||||
|
@ -192,7 +192,7 @@ class TestGridFilters:
|
|||
size = np.random.random(3)+1.0
|
||||
cells = np.random.randint(8,32,(3))
|
||||
|
||||
nodes = grid_filters.cell_coord0(cells,size)
|
||||
nodes = grid_filters.coordinates0_point(cells,size)
|
||||
my_locals = locals() # needed for list comprehension
|
||||
|
||||
field = np.stack([np.broadcast_to(eval(f,globals(),my_locals),cells) for f in field_def],axis=-1)
|
||||
|
@ -252,7 +252,7 @@ class TestGridFilters:
|
|||
size = np.random.random(3)+1.0
|
||||
cells = np.random.randint(8,32,(3))
|
||||
|
||||
nodes = grid_filters.cell_coord0(cells,size)
|
||||
nodes = grid_filters.coordinates0_point(cells,size)
|
||||
my_locals = locals() # needed for list comprehension
|
||||
|
||||
field = np.stack([np.broadcast_to(eval(f,globals(),my_locals),cells) for f in field_def],axis=-1)
|
||||
|
@ -305,7 +305,7 @@ class TestGridFilters:
|
|||
size = np.random.random(3)+1.0
|
||||
cells = np.random.randint(8,32,(3))
|
||||
|
||||
nodes = grid_filters.cell_coord0(cells,size)
|
||||
nodes = grid_filters.coordinates0_point(cells,size)
|
||||
my_locals = locals() # needed for list comprehension
|
||||
|
||||
field = np.stack([np.broadcast_to(eval(f,globals(),my_locals),cells) for f in field_def],axis=-1)
|
||||
|
|
|
@ -41,7 +41,7 @@ class TestSeeds:
|
|||
def test_from_geom_grid(self,periodic,average):
|
||||
cells = np.random.randint(10,20,3)
|
||||
size = np.ones(3) + np.random.random(3)
|
||||
coords = grid_filters.cell_coord0(cells,size).reshape(-1,3)
|
||||
coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3)
|
||||
np.random.shuffle(coords)
|
||||
geom_1 = Geom.from_Voronoi_tessellation(cells,size,coords)
|
||||
coords,material = seeds.from_geom(geom_1,average=average,periodic=periodic)
|
||||
|
|
Loading…
Reference in New Issue