756 lines
30 KiB
Python
756 lines
30 KiB
Python
import copy
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import multiprocessing as mp
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from functools import partial
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import numpy as np
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from scipy import ndimage,spatial
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from . import environment
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from . import Rotation
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from . import VTK
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from . import util
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from . import grid_filters
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class Geom:
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"""Geometry definition for grid solvers."""
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def __init__(self,material,size,origin=[0.0,0.0,0.0],comments=[]):
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"""
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New geometry definition from array of material, size, and origin.
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Parameters
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----------
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material : numpy.ndarray
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Material index array (3D).
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size : list or numpy.ndarray
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Physical size of the geometry in meter.
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origin : list or numpy.ndarray, optional
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Physical origin of the geometry in meter.
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comments : list of str, optional
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Comment lines.
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"""
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if len(material.shape) != 3:
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raise ValueError(f'Invalid material shape {material.shape}.')
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elif material.dtype not in np.sctypes['float'] + np.sctypes['int']:
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raise TypeError(f'Invalid material data type {material.dtype}.')
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else:
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self.material = np.copy(material)
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if self.material.dtype in np.sctypes['float'] and \
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np.all(self.material == self.material.astype(int).astype(float)):
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self.material = self.material.astype(int)
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if len(size) != 3 or any(np.array(size) <= 0):
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raise ValueError(f'Invalid size {size}.')
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else:
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self.size = np.array(size)
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if len(origin) != 3:
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raise ValueError(f'Invalid origin {origin}.')
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else:
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self.origin = np.array(origin)
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self.comments = [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
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def __repr__(self):
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"""Basic information on geometry definition."""
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return util.srepr([
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f'grid a b c: {util.srepr(self.grid, " x ")}',
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f'size x y z: {util.srepr(self.size, " x ")}',
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f'origin x y z: {util.srepr(self.origin," ")}',
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f'# materials: {self.N_materials}',
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f'max material: {np.nanmax(self.material)}',
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])
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def __copy__(self):
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"""Copy geometry."""
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return copy.deepcopy(self)
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def copy(self):
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"""Copy geometry."""
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return self.__copy__()
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def diff(self,other):
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"""
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Report property differences of self relative to other.
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Parameters
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----------
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other : Geom
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Geometry to compare self against.
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"""
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message = []
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if np.any(other.grid != self.grid):
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message.append(util.delete(f'grid a b c: {util.srepr(other.grid," x ")}'))
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message.append(util.emph( f'grid a b c: {util.srepr( self.grid," x ")}'))
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if not np.allclose(other.size,self.size):
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message.append(util.delete(f'size x y z: {util.srepr(other.size," x ")}'))
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message.append(util.emph( f'size x y z: {util.srepr( self.size," x ")}'))
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if not np.allclose(other.origin,self.origin):
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message.append(util.delete(f'origin x y z: {util.srepr(other.origin," ")}'))
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message.append(util.emph( f'origin x y z: {util.srepr( self.origin," ")}'))
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if other.N_materials != self.N_materials:
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message.append(util.delete(f'# materials: {other.N_materials}'))
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message.append(util.emph( f'# materials: { self.N_materials}'))
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if np.nanmax(other.material) != np.nanmax(self.material):
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message.append(util.delete(f'max material: {np.nanmax(other.material)}'))
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message.append(util.emph( f'max material: {np.nanmax( self.material)}'))
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return util.return_message(message)
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@property
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def grid(self):
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return np.asarray(self.material.shape)
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@property
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def N_materials(self):
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return np.unique(self.material).size
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@staticmethod
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def load_ASCII(fname):
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"""
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Read a geom file.
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Parameters
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----------
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fname : str or file handle
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Geometry file to read.
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"""
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try:
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f = open(fname)
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except TypeError:
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f = fname
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f.seek(0)
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try:
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header_length,keyword = f.readline().split()[:2]
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header_length = int(header_length)
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except ValueError:
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header_length,keyword = (-1, 'invalid')
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if not keyword.startswith('head') or header_length < 3:
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raise TypeError('Header length information missing or invalid')
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content = f.readlines()
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comments = []
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for i,line in enumerate(content[:header_length]):
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items = line.split('#')[0].lower().strip().split()
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key = items[0] if items else ''
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if key == 'grid':
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grid = np.array([ int(dict(zip(items[1::2],items[2::2]))[i]) for i in ['a','b','c']])
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elif key == 'size':
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size = np.array([float(dict(zip(items[1::2],items[2::2]))[i]) for i in ['x','y','z']])
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elif key == 'origin':
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origin = np.array([float(dict(zip(items[1::2],items[2::2]))[i]) for i in ['x','y','z']])
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else:
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comments.append(line.strip())
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material = np.empty(grid.prod()) # initialize as flat array
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i = 0
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for line in content[header_length:]:
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items = line.split('#')[0].split()
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if len(items) == 3:
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if items[1].lower() == 'of':
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items = np.ones(int(items[0]))*float(items[2])
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elif items[1].lower() == 'to':
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items = np.linspace(int(items[0]),int(items[2]),
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abs(int(items[2])-int(items[0]))+1,dtype=float)
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else: items = list(map(float,items))
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else: items = list(map(float,items))
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material[i:i+len(items)] = items
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i += len(items)
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if i != grid.prod():
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raise TypeError(f'Invalid file: expected {grid.prod()} entries, found {i}')
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if not np.any(np.mod(material,1) != 0.0): # no float present
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material = material.astype('int')
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return Geom(material.reshape(grid,order='F'),size,origin,comments)
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@staticmethod
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def load(fname):
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"""
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Read a VTK rectilinear grid.
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Parameters
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----------
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fname : str or or pathlib.Path
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Geometry file to read.
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Valid extension is .vtr, it will be appended if not given.
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"""
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v = VTK.load(fname if str(fname).endswith('.vtr') else str(fname)+'.vtr')
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comments = v.get_comments()
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grid = np.array(v.vtk_data.GetDimensions())-1
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bbox = np.array(v.vtk_data.GetBounds()).reshape(3,2).T
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return Geom(material = v.get('material').reshape(grid,order='F'),
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size = bbox[1] - bbox[0],
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origin = bbox[0],
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comments=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,material=None,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 : int 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 geometry 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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material : numpy.ndarray of shape (seeds.shape[0]), optional
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Material ID of the seeds. Defaults to None, in which case materials are
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consecutively numbered.
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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) # 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)
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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(grid,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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pool.close()
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pool.join()
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material_ = np.array(result.get())
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if periodic:
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material_ = material_.reshape(grid*3)
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material_ = material_[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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material_ = material_.reshape(grid)
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return Geom(material = material_+1 if material is None else material[material_],
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size = size,
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comments = util.execution_stamp('Geom','from_Laguerre_tessellation'),
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)
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@staticmethod
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def from_Voronoi_tessellation(grid,size,seeds,material=None,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 : int 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 geometry 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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material : numpy.ndarray of shape (seeds.shape[0]), optional
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Material ID of the seeds. Defaults to None, in which case materials are
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consecutively numbered.
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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)
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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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return Geom(material = (material_+1 if material is None else material[material_]).reshape(grid),
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size = size,
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comments = util.execution_stamp('Geom','from_Voronoi_tessellation'),
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)
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@staticmethod
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def from_minimal_surface(grid,size,surface,threshold=0.0,periods=1,materials=(1,2)):
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"""
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Generate geometry from definition of minimal surface.
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Parameters
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----------
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grid : int 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 geometry in meter.
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surface : {'primitive', 'gyroid', 'diamond'}
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Type of the minimal surface.
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threshold : float, optional.
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Threshold of the minimal surface. Defaults to 0.0.
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periods : integer, optional.
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Number of periods per unit cell. Defaults to 1.
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materials : (int, int), optional
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Material IDs. Defaults to (1,2).
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"""
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s = {'primitive': lambda x,y,z: np.cos(x)+np.cos(y)+np.cos(z),
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'gyroid': lambda x,y,z: np.sin(x)*np.cos(y)+np.sin(y)*np.cos(z)+np.cos(x)*np.sin(z),
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'diamond': lambda x,y,z: np.cos(x-y)*np.cos(z)+np.sin(x+y)*np.sin(z),
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}
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x,y,z = np.meshgrid(periods*2.0*np.pi*(np.arange(grid[0])+0.5)/grid[0],
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periods*2.0*np.pi*(np.arange(grid[1])+0.5)/grid[1],
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periods*2.0*np.pi*(np.arange(grid[2])+0.5)/grid[2],
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indexing='ij',sparse=True)
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return Geom(material = np.where(threshold < s[surface](x,y,z),materials[1],materials[0]),
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size = size,
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comments = util.execution_stamp('Geom','from_minimal_surface'),
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)
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def save_ASCII(self,fname,compress=None):
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"""
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Writes a geom file.
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Parameters
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----------
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fname : str or file handle
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Geometry file to write with extension '.geom'.
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compress : bool, optional
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Compress geometry with 'x of y' and 'a to b'.
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"""
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header = [f'{len(self.comments)+4} header'] + self.comments \
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+ ['grid a {} b {} c {}'.format(*self.grid),
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'size x {} y {} z {}'.format(*self.size),
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'origin x {} y {} z {}'.format(*self.origin),
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'homogenization 1',
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]
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grid = self.grid
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if compress is None:
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plain = grid.prod()/self.N_materials < 250
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else:
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plain = not compress
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if plain:
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format_string = '%g' if self.material.dtype in np.sctypes['float'] else \
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'%{}i'.format(1+int(np.floor(np.log10(np.nanmax(self.material)))))
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np.savetxt(fname,
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self.material.reshape([grid[0],np.prod(grid[1:])],order='F').T,
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header='\n'.join(header), fmt=format_string, comments='')
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else:
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try:
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f = open(fname,'w')
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except TypeError:
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f = fname
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compressType = None
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former = start = -1
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reps = 0
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for current in self.material.flatten('F'):
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if abs(current - former) == 1 and (start - current) == reps*(former - current):
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compressType = 'to'
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reps += 1
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elif current == former and start == former:
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compressType = 'of'
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reps += 1
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else:
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if compressType is None:
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f.write('\n'.join(header)+'\n')
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elif compressType == '.':
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f.write(f'{former}\n')
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elif compressType == 'to':
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f.write(f'{start} to {former}\n')
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elif compressType == 'of':
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f.write(f'{reps} of {former}\n')
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compressType = '.'
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start = current
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reps = 1
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former = current
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if compressType == '.':
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f.write(f'{former}\n')
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elif compressType == 'to':
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f.write(f'{start} to {former}\n')
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elif compressType == 'of':
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f.write(f'{reps} of {former}\n')
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def save(self,fname,compress=True):
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"""
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Generates vtk rectilinear grid.
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Parameters
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----------
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fname : str, optional
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Filename to write. If no file is given, a string is returned.
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Valid extension is .vtr, it will be appended if not given.
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compress : bool, optional
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Compress with zlib algorithm. Defaults to True.
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"""
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v = VTK.from_rectilinearGrid(self.grid,self.size,self.origin)
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v.add(self.material.flatten(order='F'),'material')
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v.add_comments(self.comments)
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v.save(fname if str(fname).endswith('.vtr') else str(fname)+'.vtr',parallel=False,compress=compress)
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def show(self):
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"""Show on screen."""
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v = VTK.from_rectilinearGrid(self.grid,self.size,self.origin)
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v.show()
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def add_primitive(self,dimension,center,exponent,
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fill=None,R=Rotation(),inverse=False,periodic=True):
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"""
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Inserts a primitive geometric object at a given position.
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Parameters
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----------
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dimension : int or float numpy.ndarray of shape(3)
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Dimension (diameter/side length) of the primitive. If given as
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integers, grid point locations (cell centers) are addressed.
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If given as floats, coordinates are addressed.
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center : int or float numpy.ndarray of shape(3)
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Center of the primitive. If given as integers, grid point
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locations (cell centers) are addressed.
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If given as floats, coordinates are addressed.
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exponent : numpy.ndarray of shape(3) or float
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Exponents for the three axes.
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0 gives octahedron (ǀxǀ^(2^0) + ǀyǀ^(2^0) + ǀzǀ^(2^0) < 1)
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1 gives sphere (ǀxǀ^(2^1) + ǀyǀ^(2^1) + ǀzǀ^(2^1) < 1)
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fill : int, optional
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Fill value for primitive. Defaults to material.max() + 1.
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R : damask.Rotation, optional
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Rotation of primitive. Defaults to no rotation.
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inverse : Boolean, optional
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Retain original materials within primitive and fill outside.
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Defaults to False.
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periodic : Boolean, optional
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Repeat primitive over boundaries. Defaults to True.
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"""
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# normalized 'radius' and center
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r = np.array(dimension)/self.grid/2.0 if np.array(dimension).dtype in np.sctypes['int'] else \
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np.array(dimension)/self.size/2.0
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c = (np.array(center) + .5)/self.grid if np.array(center).dtype in np.sctypes['int'] else \
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(np.array(center) - self.origin)/self.size
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coords = grid_filters.cell_coord0(self.grid,np.ones(3)) \
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- ((np.ones(3)-(1./self.grid if np.array(center).dtype in np.sctypes['int'] else 0))*0.5 if periodic else c) # periodic center is always at CoG
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coords_rot = R.broadcast_to(tuple(self.grid))@coords
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with np.errstate(all='ignore'):
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mask = np.where(np.sum(np.power(coords_rot/r,2.0**exponent),axis=-1) > 1.0,True,False)
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if periodic: # translate back to center
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mask = np.roll(mask,((c-np.ones(3)*.5)*self.grid).astype(int),(0,1,2))
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fill_ = np.full_like(self.material,np.nanmax(self.material)+1 if fill is None else fill)
|
||
|
||
return Geom(material = np.where(np.logical_not(mask) if inverse else mask, self.material,fill_),
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','add_primitive')],
|
||
)
|
||
|
||
|
||
def mirror(self,directions,reflect=False):
|
||
"""
|
||
Mirror geometry along given directions.
|
||
|
||
Parameters
|
||
----------
|
||
directions : iterable containing str
|
||
Direction(s) along which the geometry is mirrored.
|
||
Valid entries are 'x', 'y', 'z'.
|
||
reflect : bool, optional
|
||
Reflect (include) outermost layers. Defaults to False.
|
||
|
||
"""
|
||
valid = ['x','y','z']
|
||
if not set(directions).issubset(valid):
|
||
raise ValueError(f'Invalid direction {set(directions).difference(valid)} specified.')
|
||
|
||
limits = [None,None] if reflect else [-2,0]
|
||
mat = self.material.copy()
|
||
|
||
if 'x' in directions:
|
||
mat = np.concatenate([mat,mat[limits[0]:limits[1]:-1,:,:]],0)
|
||
if 'y' in directions:
|
||
mat = np.concatenate([mat,mat[:,limits[0]:limits[1]:-1,:]],1)
|
||
if 'z' in directions:
|
||
mat = np.concatenate([mat,mat[:,:,limits[0]:limits[1]:-1]],2)
|
||
|
||
return Geom(material = mat,
|
||
size = self.size/self.grid*np.asarray(mat.shape),
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','mirror')],
|
||
)
|
||
|
||
|
||
def flip(self,directions):
|
||
"""
|
||
Flip geometry along given directions.
|
||
|
||
Parameters
|
||
----------
|
||
directions : iterable containing str
|
||
Direction(s) along which the geometry is flipped.
|
||
Valid entries are 'x', 'y', 'z'.
|
||
|
||
"""
|
||
valid = ['x','y','z']
|
||
if not set(directions).issubset(valid):
|
||
raise ValueError(f'Invalid direction {set(directions).difference(valid)} specified.')
|
||
|
||
mat = np.flip(self.material, (valid.index(d) for d in directions if d in valid))
|
||
|
||
return Geom(material = mat,
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','flip')],
|
||
)
|
||
|
||
|
||
def scale(self,grid,periodic=True):
|
||
"""
|
||
Scale geometry to new grid.
|
||
|
||
Parameters
|
||
----------
|
||
grid : numpy.ndarray of shape (3)
|
||
Number of grid points in x,y,z direction.
|
||
periodic : Boolean, optional
|
||
Assume geometry to be periodic. Defaults to True.
|
||
|
||
"""
|
||
return Geom(material = ndimage.interpolation.zoom(
|
||
self.material,
|
||
grid/self.grid,
|
||
output=self.material.dtype,
|
||
order=0,
|
||
mode=('wrap' if periodic else 'nearest'),
|
||
prefilter=False
|
||
),
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','scale')],
|
||
)
|
||
|
||
|
||
def clean(self,stencil=3,selection=None,periodic=True):
|
||
"""
|
||
Smooth geometry by selecting most frequent material index within given stencil at each location.
|
||
|
||
Parameters
|
||
----------
|
||
stencil : int, optional
|
||
Size of smoothing stencil.
|
||
selection : list, optional
|
||
Field values that can be altered. Defaults to all.
|
||
periodic : Boolean, optional
|
||
Assume geometry to be periodic. Defaults to True.
|
||
|
||
"""
|
||
def mostFrequent(arr,selection=None):
|
||
me = arr[arr.size//2]
|
||
if selection is None or me in selection:
|
||
unique, inverse = np.unique(arr, return_inverse=True)
|
||
return unique[np.argmax(np.bincount(inverse))]
|
||
else:
|
||
return me
|
||
|
||
return Geom(material = ndimage.filters.generic_filter(
|
||
self.material,
|
||
mostFrequent,
|
||
size=(stencil if selection is None else stencil//2*2+1,)*3,
|
||
mode=('wrap' if periodic else 'nearest'),
|
||
extra_keywords=dict(selection=selection),
|
||
).astype(self.material.dtype),
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','clean')],
|
||
)
|
||
|
||
|
||
def renumber(self):
|
||
"""Renumber sorted material indices to 1,...,N."""
|
||
renumbered = np.empty(self.grid,dtype=self.material.dtype)
|
||
for i, oldID in enumerate(np.unique(self.material)):
|
||
renumbered = np.where(self.material == oldID, i+1, renumbered)
|
||
|
||
return Geom(material = renumbered,
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','renumber')],
|
||
)
|
||
|
||
|
||
def rotate(self,R,fill=None):
|
||
"""
|
||
Rotate geometry (pad if required).
|
||
|
||
Parameters
|
||
----------
|
||
R : damask.Rotation
|
||
Rotation to apply to the geometry.
|
||
fill : int or float, optional
|
||
Material index to fill the corners. Defaults to material.max() + 1.
|
||
|
||
"""
|
||
if fill is None: fill = np.nanmax(self.material) + 1
|
||
dtype = float if np.isnan(fill) or int(fill) != fill or self.material.dtype==np.float else int
|
||
|
||
Eulers = R.as_Eulers(degrees=True)
|
||
material_in = self.material.copy()
|
||
|
||
# These rotations are always applied in the reference coordinate system, i.e. (z,x,z) not (z,x',z'')
|
||
# see https://www.cs.utexas.edu/~theshark/courses/cs354/lectures/cs354-14.pdf
|
||
for angle,axes in zip(Eulers[::-1], [(0,1),(1,2),(0,1)]):
|
||
material_out = ndimage.rotate(material_in,angle,axes,order=0,
|
||
prefilter=False,output=dtype,cval=fill)
|
||
if np.prod(material_in.shape) == np.prod(material_out.shape):
|
||
# avoid scipy interpolation errors for rotations close to multiples of 90°
|
||
material_in = np.rot90(material_in,k=np.rint(angle/90.).astype(int),axes=axes)
|
||
else:
|
||
material_in = material_out
|
||
|
||
origin = self.origin-(np.asarray(material_in.shape)-self.grid)*.5 * self.size/self.grid
|
||
|
||
return Geom(material = material_in,
|
||
size = self.size/self.grid*np.asarray(material_in.shape),
|
||
origin = origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','rotate')],
|
||
)
|
||
|
||
|
||
def canvas(self,grid=None,offset=None,fill=None):
|
||
"""
|
||
Crop or enlarge/pad geometry.
|
||
|
||
Parameters
|
||
----------
|
||
grid : numpy.ndarray of shape (3)
|
||
Number of grid points in x,y,z direction.
|
||
offset : numpy.ndarray of shape (3)
|
||
Offset (measured in grid points) from old to new geometry [0,0,0].
|
||
fill : int or float, optional
|
||
Material index to fill the background. Defaults to material.max() + 1.
|
||
|
||
"""
|
||
if offset is None: offset = 0
|
||
if fill is None: fill = np.nanmax(self.material) + 1
|
||
dtype = float if int(fill) != fill or self.material.dtype in np.sctypes['float'] else int
|
||
|
||
canvas = np.full(self.grid if grid is None else grid,fill,dtype)
|
||
|
||
LL = np.clip( offset, 0,np.minimum(self.grid, grid+offset))
|
||
UR = np.clip( offset+grid, 0,np.minimum(self.grid, grid+offset))
|
||
ll = np.clip(-offset, 0,np.minimum( grid,self.grid-offset))
|
||
ur = np.clip(-offset+self.grid,0,np.minimum( grid,self.grid-offset))
|
||
|
||
canvas[ll[0]:ur[0],ll[1]:ur[1],ll[2]:ur[2]] = self.material[LL[0]:UR[0],LL[1]:UR[1],LL[2]:UR[2]]
|
||
|
||
return Geom(material = canvas,
|
||
size = self.size/self.grid*np.asarray(canvas.shape),
|
||
origin = self.origin+offset*self.size/self.grid,
|
||
comments = self.comments+[util.execution_stamp('Geom','canvas')],
|
||
)
|
||
|
||
|
||
def substitute(self,from_material,to_material):
|
||
"""
|
||
Substitute material indices.
|
||
|
||
Parameters
|
||
----------
|
||
from_material : iterable of ints
|
||
Material indices to be substituted.
|
||
to_material : iterable of ints
|
||
New material indices.
|
||
|
||
"""
|
||
substituted = self.material.copy()
|
||
for from_ms,to_ms in zip(from_material,to_material):
|
||
substituted[self.material==from_ms] = to_ms
|
||
|
||
return Geom(material = substituted,
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','substitute')],
|
||
)
|
||
|
||
|
||
def vicinity_offset(self,vicinity=1,offset=None,trigger=[],periodic=True):
|
||
"""
|
||
Offset material index of points in the vicinity of xxx.
|
||
|
||
Different from themselves (or listed as triggers) within a given (cubic) vicinity,
|
||
i.e. within the region close to a grain/phase boundary.
|
||
ToDo: use include/exclude as in seeds.from_geom
|
||
|
||
Parameters
|
||
----------
|
||
vicinity : int, optional
|
||
Voxel distance checked for presence of other materials.
|
||
Defaults to 1.
|
||
offset : int, optional
|
||
Offset (positive or negative) to tag material indices,
|
||
defaults to material.max() + 1.
|
||
trigger : list of ints, optional
|
||
List of material indices that trigger a change.
|
||
Defaults to [], meaning that any different neighbor triggers a change.
|
||
periodic : Boolean, optional
|
||
Assume geometry to be periodic. Defaults to True.
|
||
|
||
"""
|
||
def tainted_neighborhood(stencil,trigger):
|
||
|
||
me = stencil[stencil.shape[0]//2]
|
||
if len(trigger) == 0:
|
||
return np.any(stencil != me)
|
||
if me in trigger:
|
||
trigger = set(trigger)
|
||
trigger.remove(me)
|
||
trigger = list(trigger)
|
||
return np.any(np.in1d(stencil,np.array(trigger)))
|
||
|
||
offset_ = np.nanmax(self.material) if offset is None else offset
|
||
mask = ndimage.filters.generic_filter(self.material,
|
||
tainted_neighborhood,
|
||
size=1+2*vicinity,
|
||
mode='wrap' if periodic else 'nearest',
|
||
extra_keywords={'trigger':trigger})
|
||
|
||
return Geom(material = np.where(mask, self.material + offset_,self.material),
|
||
size = self.size,
|
||
origin = self.origin,
|
||
comments = self.comments+[util.execution_stamp('Geom','vicinity_offset')],
|
||
)
|