import sys
import copy
import multiprocessing
from io import StringIO
from functools import partial
import numpy as np
from scipy import ndimage,spatial
from . import environment
from . import Rotation
from . import VTK
from . import util
from . import grid_filters
class Geom:
"""Geometry definition for grid solvers."""
def __init__(self,microstructure,size,origin=[0.0,0.0,0.0],homogenization=1,comments=[]):
"""
New geometry definition from array of microstructures and size.
Parameters
----------
microstructure : numpy.ndarray
Microstructure array (3D)
size : list or numpy.ndarray
Physical size of the microstructure in meter.
origin : list or numpy.ndarray, optional
Physical origin of the microstructure in meter.
homogenization : int, optional
Homogenization index.
comments : list of str, optional
Comment lines.
"""
self.set_microstructure(microstructure)
self.set_size(size)
self.set_origin(origin)
self.set_homogenization(homogenization)
self.set_comments(comments)
def __repr__(self):
"""Basic information on geometry definition."""
return util.srepr([
f'grid a b c: {util.srepr(self.get_grid ()," x ")}',
f'size x y z: {util.srepr(self.get_size ()," x ")}',
f'origin x y z: {util.srepr(self.get_origin()," ")}',
f'# materialpoints: {self.N_microstructure}',
f'max materialpoint: {np.nanmax(self.microstructure)}',
])
def __copy__(self):
"""Copy geometry."""
return copy.deepcopy(self)
def copy(self):
"""Copy geometry."""
return self.__copy__()
def duplicate(self,microstructure=None,size=None,origin=None,comments=None,autosize=False):
"""
Create a duplicate having updated microstructure, size, and origin.
Parameters
----------
microstructure : numpy.ndarray, optional
Microstructure array (3D).
size : list or numpy.ndarray, optional
Physical size of the microstructure in meter.
origin : list or numpy.ndarray, optional
Physical origin of the microstructure in meter.
comments : list of str, optional
Comment lines.
autosize : bool, optional
Ignore size parameter and rescale according to change of grid points.
"""
if size is not None and autosize:
raise ValueError('Auto-sizing conflicts with explicit size parameter.')
grid_old = self.get_grid()
dup = self.copy()
dup.set_microstructure(microstructure)
dup.set_origin(origin)
if comments is not None:
dup.set_comments(comments)
if size is not None:
dup.set_size(size)
elif autosize:
dup.set_size(dup.get_grid()/grid_old*self.get_size())
return dup
def diff(self,other):
"""
Report property differences of self relative to other.
Parameters
----------
other : Geom
Geometry to compare self against.
"""
message = []
if np.any(other.get_grid() != self.get_grid()):
message.append(util.delete(f'grid a b c: {util.srepr(other.get_grid()," x ")}'))
message.append(util.emph( f'grid a b c: {util.srepr( self.get_grid()," x ")}'))
if np.any(other.get_size() != self.get_size()):
message.append(util.delete(f'size x y z: {util.srepr(other.get_size()," x ")}'))
message.append(util.emph( f'size x y z: {util.srepr( self.get_size()," x ")}'))
if np.any(other.get_origin() != self.get_origin()):
message.append(util.delete(f'origin x y z: {util.srepr(other.get_origin()," ")}'))
message.append(util.emph( f'origin x y z: {util.srepr( self.get_origin()," ")}'))
if other.N_microstructure != self.N_microstructure:
message.append(util.delete(f'# materialpoints: {other.N_microstructure}'))
message.append(util.emph( f'# materialpoints: { self.N_microstructure}'))
if np.nanmax(other.microstructure) != np.nanmax(self.microstructure):
message.append(util.delete(f'max materialpoint: {np.nanmax(other.microstructure)}'))
message.append(util.emph( f'max materialpoint: {np.nanmax( self.microstructure)}'))
return util.return_message(message)
def set_comments(self,comments):
"""
Replace all existing comments.
Parameters
----------
comments : list of str
All comments.
"""
self.comments = []
self.add_comments(comments)
def add_comments(self,comments):
"""
Append comments to existing comments.
Parameters
----------
comments : list of str
New comments.
"""
self.comments += [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
def set_microstructure(self,microstructure):
"""
Replace the existing microstructure representation.
The complete microstructure is replaced (indcluding grid definition),
unless a masked array is provided in which case the grid dimensions
need to match and masked entries are not replaced.
Parameters
----------
microstructure : numpy.ndarray or numpy.ma.core.MaskedArray of shape (:,:,:)
Microstructure indices.
"""
if microstructure is not None:
if isinstance(microstructure,np.ma.core.MaskedArray):
self.microstructure = np.where(microstructure.mask,
self.microstructure,microstructure.data)
else:
self.microstructure = np.copy(microstructure)
if self.microstructure.dtype in np.sctypes['float'] and \
np.all(self.microstructure == self.microstructure.astype(int).astype(float)):
self.microstructure = self.microstructure.astype(int)
if len(self.microstructure.shape) != 3:
raise ValueError(f'Invalid microstructure shape {microstructure.shape}')
elif self.microstructure.dtype not in np.sctypes['float'] + np.sctypes['int']:
raise TypeError(f'Invalid microstructure data type {microstructure.dtype}')
def set_size(self,size):
"""
Replace the existing size information.
Parameters
----------
size : list or numpy.ndarray
Physical size of the microstructure in meter.
"""
if size is not None:
if len(size) != 3 or any(np.array(size) <= 0):
raise ValueError(f'Invalid size {size}')
else:
self.size = np.array(size)
def set_origin(self,origin):
"""
Replace the existing origin information.
Parameters
----------
origin : list or numpy.ndarray
Physical origin of the microstructure in meter.
"""
if origin is not None:
if len(origin) != 3:
raise ValueError(f'Invalid origin {origin}')
else:
self.origin = np.array(origin)
def set_homogenization(self,homogenization):
"""
Replace the existing homogenization index.
Parameters
----------
homogenization : int
Homogenization index.
"""
if homogenization is not None:
if not isinstance(homogenization,int) or homogenization < 1:
raise TypeError(f'Invalid homogenization {homogenization}.')
else:
self.homogenization = homogenization
@property
def grid(self):
return self.get_grid()
@property
def N_microstructure(self):
return np.unique(self.microstructure).size
def get_microstructure(self):
"""Return the microstructure representation."""
return np.copy(self.microstructure)
def get_size(self):
"""Return the physical size in meter."""
return np.copy(self.size)
def get_origin(self):
"""Return the origin in meter."""
return np.copy(self.origin)
def get_grid(self):
"""Return the grid discretization."""
return np.asarray(self.microstructure.shape)
def get_homogenization(self):
"""Return the homogenization index."""
return self.homogenization
def get_comments(self):
"""Return the comments."""
return self.comments[:]
@staticmethod
def from_file(fname):
"""
Read a geom file.
Parameters
----------
fname : str or file handle
Geometry file to read.
"""
try:
f = open(fname)
except TypeError:
f = fname
f.seek(0)
try:
header_length,keyword = f.readline().split()[:2]
header_length = int(header_length)
except ValueError:
header_length,keyword = (-1, 'invalid')
if not keyword.startswith('head') or header_length < 3:
raise TypeError('Header length information missing or invalid')
content = f.readlines()
comments = []
for i,line in enumerate(content[:header_length]):
items = line.split('#')[0].lower().strip().split()
key = items[0] if items else ''
if key == 'grid':
grid = np.array([ int(dict(zip(items[1::2],items[2::2]))[i]) for i in ['a','b','c']])
elif key == 'size':
size = np.array([float(dict(zip(items[1::2],items[2::2]))[i]) for i in ['x','y','z']])
elif key == 'origin':
origin = np.array([float(dict(zip(items[1::2],items[2::2]))[i]) for i in ['x','y','z']])
elif key == 'homogenization':
homogenization = int(items[1])
else:
comments.append(line.strip())
microstructure = np.empty(grid.prod()) # initialize as flat array
i = 0
for line in content[header_length:]:
items = line.split('#')[0].split()
if len(items) == 3:
if items[1].lower() == 'of':
items = np.ones(int(items[0]))*float(items[2])
elif items[1].lower() == 'to':
items = np.linspace(int(items[0]),int(items[2]),
abs(int(items[2])-int(items[0]))+1,dtype=float)
else: items = list(map(float,items))
else: items = list(map(float,items))
microstructure[i:i+len(items)] = items
i += len(items)
if i != grid.prod():
raise TypeError(f'Invalid file: expected {grid.prod()} entries, found {i}')
if not np.any(np.mod(microstructure,1) != 0.0): # no float present
microstructure = microstructure.astype('int')
return Geom(microstructure.reshape(grid,order='F'),size,origin,homogenization,comments)
@staticmethod
def from_vtr(fname):
"""
Read a VTK rectilinear grid.
Parameters
----------
fname : str or or pathlib.Path
Geometry file to read.
Valid extension is .vtr, it will be appended if not given.
"""
v = VTK.from_file(fname if str(fname).endswith('.vtr') else str(fname)+'.vtr')
comments = v.get_comments()
grid = np.array(v.vtk_data.GetDimensions())-1
bbox = np.array(v.vtk_data.GetBounds()).reshape(3,2).T
size = bbox[1] - bbox[0]
return Geom(v.get('materialpoint').reshape(grid,order='F'),size,bbox[0],comments=comments)
@staticmethod
def _find_closest_seed(seeds, weights, point):
return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
@staticmethod
def from_Laguerre_tessellation(grid,size,seeds,weights,periodic=True):
"""
Generate geometry from Laguerre tessellation.
Parameters
----------
grid : int numpy.ndarray of shape (3)
Number of grid points in x,y,z direction.
size : list or numpy.ndarray of shape (3)
Physical size of the microstructure in meter.
seeds : numpy.ndarray of shape (:,3)
Position of the seed points in meter. All points need to lay within the box.
weights : numpy.ndarray of shape (seeds.shape[0])
Weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation.
periodic : Boolean, optional
Perform a periodic tessellation. Defaults to True.
"""
if periodic:
weights_p = np.tile(weights,27) # Laguerre weights (1,2,3,1,2,3,...,1,2,3)
seeds_p = np.vstack((seeds -np.array([size[0],0.,0.]),seeds, seeds +np.array([size[0],0.,0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,size[1],0.]),seeds_p,seeds_p+np.array([0.,size[1],0.])))
seeds_p = np.vstack((seeds_p-np.array([0.,0.,size[2]]),seeds_p,seeds_p+np.array([0.,0.,size[2]])))
coords = grid_filters.cell_coord0(grid*3,size*3,-size).reshape(-1,3)
else:
weights_p = weights
seeds_p = seeds
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
pool = multiprocessing.Pool(processes = int(environment.options['DAMASK_NUM_THREADS']))
result = pool.map_async(partial(Geom._find_closest_seed,seeds_p,weights_p), [coord for coord in coords])
pool.close()
pool.join()
microstructure = np.array(result.get())
if periodic:
microstructure = microstructure.reshape(grid*3)
microstructure = microstructure[grid[0]:grid[0]*2,grid[1]:grid[1]*2,grid[2]:grid[2]*2]%seeds.shape[0]
else:
microstructure = microstructure.reshape(grid)
return Geom(microstructure+1,size,homogenization=1,
comments=util.execution_stamp('Geom','from_Laguerre_tessellation'),
)
@staticmethod
def from_Voronoi_tessellation(grid,size,seeds,periodic=True):
"""
Generate geometry from Voronoi tessellation.
Parameters
----------
grid : int numpy.ndarray of shape (3)
Number of grid points in x,y,z direction.
size : list or numpy.ndarray of shape (3)
Physical size of the microstructure in meter.
seeds : numpy.ndarray of shape (:,3)
Position of the seed points in meter. All points need to lay within the box.
periodic : Boolean, optional
Perform a periodic tessellation. Defaults to True.
"""
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
devNull,microstructure = KDTree.query(coords)
return Geom(microstructure.reshape(grid)+1,size,homogenization=1,
comments=util.execution_stamp('Geom','from_Voronoi_tessellation'),
)
def to_file(self,fname,format='vtr',pack=None):
"""
Writes a geom file.
Parameters
----------
fname : str or file handle
Geometry file to write.
format : {'vtr', 'ASCII'}, optional
File format, defaults to 'vtr'. Available formats are:
- vtr: VTK rectilinear grid file, extension '.vtr'.
- ASCII: Plain text file, extension '.geom'.
pack : bool, optional
Compress ASCII geometry with 'x of y' and 'a to b'.
"""
def _to_ASCII(geom,fname,pack=None):
"""
Writes a geom file.
Parameters
----------
geom : Geom object
Geometry to write.
fname : str or file handle
Geometry file to write.
pack : bool, optional
Compress geometry with 'x of y' and 'a to b'.
"""
header = [f'{len(geom.comments)+4} header'] + geom.comments
header.append('grid a {} b {} c {}'.format(*geom.get_grid()))
header.append('size x {} y {} z {}'.format(*geom.get_size()))
header.append('origin x {} y {} z {}'.format(*geom.get_origin()))
header.append(f'homogenization {geom.get_homogenization()}')
grid = geom.get_grid()
if pack is None:
plain = grid.prod()/geom.N_microstructure < 250
else:
plain = not pack
if plain:
format_string = '%g' if geom.microstructure.dtype in np.sctypes['float'] else \
'%{}i'.format(1+int(np.floor(np.log10(np.nanmax(geom.microstructure)))))
np.savetxt(fname,
geom.microstructure.reshape([grid[0],np.prod(grid[1:])],order='F').T,
header='\n'.join(header), fmt=format_string, comments='')
else:
try:
f = open(fname,'w')
except TypeError:
f = fname
compressType = None
former = start = -1
reps = 0
for current in geom.microstructure.flatten('F'):
if abs(current - former) == 1 and (start - current) == reps*(former - current):
compressType = 'to'
reps += 1
elif current == former and start == former:
compressType = 'of'
reps += 1
else:
if compressType is None:
f.write('\n'.join(header)+'\n')
elif compressType == '.':
f.write(f'{former}\n')
elif compressType == 'to':
f.write(f'{start} to {former}\n')
elif compressType == 'of':
f.write(f'{reps} of {former}\n')
compressType = '.'
start = current
reps = 1
former = current
if compressType == '.':
f.write(f'{former}\n')
elif compressType == 'to':
f.write(f'{start} to {former}\n')
elif compressType == 'of':
f.write(f'{reps} of {former}\n')
def _to_vtr(geom,fname=None):
"""
Generates vtk rectilinear grid.
Parameters
----------
geom : Geom object
Geometry to write.
fname : str, optional
Filename to write. If no file is given, a string is returned.
Valid extension is .vtr, it will be appended if not given.
"""
v = VTK.from_rectilinearGrid(geom.grid,geom.size,geom.origin)
v.add(geom.microstructure.flatten(order='F'),'materialpoint')
v.add_comments(geom.comments)
if fname:
v.to_file(fname if str(fname).endswith('.vtr') else str(fname)+'.vtr')
else:
sys.stdout.write(v.__repr__())
if format.lower() == 'ascii':
return _to_ASCII(self,fname,pack)
elif format.lower() == 'vtr':
return _to_vtr(self,fname)
else:
raise TypeError(f'Unknown format {format}.')
def as_ASCII(self,pack=False):
"""Format geometry as human-readable ASCII."""
f = StringIO()
self.to_file(f,'ASCII',pack)
f.seek(0)
return ''.join(f.readlines())
def add_primitive(self,dimension,center,exponent,
fill=None,R=Rotation(),inverse=False,periodic=True):
"""
Inserts a primitive geometric object at a given position.
Parameters
----------
dimension : int or float numpy.ndarray of shape(3)
Dimension (diameter/side length) of the primitive. If given as
integers, grid point locations (cell centers) are addressed.
If given as floats, coordinates are addressed.
center : int or float numpy.ndarray of shape(3)
Center of the primitive. If given as integers, grid point
locations (cell centers) are addressed.
If given as floats, coordinates are addressed.
exponent : numpy.ndarray of shape(3) or float
Exponents for the three axis.
0 gives octahedron (|x|^(2^0) + |y|^(2^0) + |z|^(2^0) < 1)
1 gives a sphere (|x|^(2^1) + |y|^(2^1) + |z|^(2^1) < 1)
fill : int, optional
Fill value for primitive. Defaults to microstructure.max() + 1.
R : damask.Rotation, optional
Rotation of primitive. Defaults to no rotation.
inverse : Boolean, optional
Retain original microstructure within primitive and fill outside.
Defaults to False.
periodic : Boolean, optional
Repeat primitive over boundaries. Defaults to True.
"""
# normalized 'radius' and center
r = np.array(dimension)/self.grid/2.0 if np.array(dimension).dtype in np.sctypes['int'] else \
np.array(dimension)/self.size/2.0
c = (np.array(center) + .5)/self.grid if np.array(center).dtype in np.sctypes['int'] else \
(np.array(center) - self.origin)/self.size
coords = grid_filters.cell_coord0(self.grid,np.ones(3)) \
- ((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
coords_rot = R.broadcast_to(tuple(self.grid))@coords
with np.errstate(all='ignore'):
mask = np.where(np.sum(np.power(coords_rot/r,2.0**exponent),axis=-1) > 1.0,True,False)
if periodic: # translate back to center
mask = np.roll(mask,((c-np.ones(3)*.5)*self.grid).astype(int),(0,1,2))
fill_ = np.full_like(self.microstructure,np.nanmax(self.microstructure)+1 if fill is None else fill)
ms = np.ma.MaskedArray(fill_,np.logical_not(mask) if inverse else mask)
return self.duplicate(ms,
comments=self.get_comments()+[util.execution_stamp('Geom','add_primitive')],
)
def mirror(self,directions,reflect=False):
"""
Mirror microstructure along given directions.
Parameters
----------
directions : iterable containing str
Direction(s) along which the microstructure 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]
ms = self.get_microstructure()
if 'z' in directions:
ms = np.concatenate([ms,ms[:,:,limits[0]:limits[1]:-1]],2)
if 'y' in directions:
ms = np.concatenate([ms,ms[:,limits[0]:limits[1]:-1,:]],1)
if 'x' in directions:
ms = np.concatenate([ms,ms[limits[0]:limits[1]:-1,:,:]],0)
return self.duplicate(ms,
comments=self.get_comments()+[util.execution_stamp('Geom','mirror')],
autosize=True)
def flip(self,directions):
"""
Flip microstructure along given directions.
Parameters
----------
directions : iterable containing str
Direction(s) along which the microstructure 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.')
ms = np.flip(self.microstructure, (valid.index(d) for d in directions if d in valid))
return self.duplicate(ms,
comments=self.get_comments()+[util.execution_stamp('Geom','flip')],
)
def scale(self,grid,periodic=True):
"""
Scale microstructure 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 self.duplicate(ndimage.interpolation.zoom(
self.microstructure,
grid/self.get_grid(),
output=self.microstructure.dtype,
order=0,
mode=('wrap' if periodic else 'nearest'),
prefilter=False
),
comments=self.get_comments()+[util.execution_stamp('Geom','scale')],
)
def clean(self,stencil=3,selection=None,periodic=True):
"""
Smooth microstructure by selecting most frequent 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 self.duplicate(ndimage.filters.generic_filter(
self.microstructure,
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.microstructure.dtype),
comments=self.get_comments()+[util.execution_stamp('Geom','clean')],
)
def renumber(self):
"""Renumber sorted microstructure indices to 1,...,N."""
renumbered = np.empty(self.get_grid(),dtype=self.microstructure.dtype)
for i, oldID in enumerate(np.unique(self.microstructure)):
renumbered = np.where(self.microstructure == oldID, i+1, renumbered)
return self.duplicate(renumbered,
comments=self.get_comments()+[util.execution_stamp('Geom','renumber')],
)
def rotate(self,R,fill=None):
"""
Rotate microstructure (pad if required).
Parameters
----------
R : damask.Rotation
Rotation to apply to the microstructure.
fill : int or float, optional
Microstructure index to fill the corners. Defaults to microstructure.max() + 1.
"""
if fill is None: fill = np.nanmax(self.microstructure) + 1
dtype = float if np.isnan(fill) or int(fill) != fill or self.microstructure.dtype==np.float else int
Eulers = R.as_Eulers(degrees=True)
microstructure_in = self.get_microstructure()
# 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)]):
microstructure_out = ndimage.rotate(microstructure_in,angle,axes,order=0,
prefilter=False,output=dtype,cval=fill)
if np.prod(microstructure_in.shape) == np.prod(microstructure_out.shape):
# avoid scipy interpolation errors for rotations close to multiples of 90°
microstructure_in = np.rot90(microstructure_in,k=np.rint(angle/90.).astype(int),axes=axes)
else:
microstructure_in = microstructure_out
origin = self.origin-(np.asarray(microstructure_in.shape)-self.grid)*.5 * self.size/self.grid
return self.duplicate(microstructure_in,
origin=origin,
comments=self.get_comments()+[util.execution_stamp('Geom','rotate')],
autosize=True,
)
def canvas(self,grid=None,offset=None,fill=None):
"""
Crop or enlarge/pad microstructure.
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 microstructure[0,0,0].
fill : int or float, optional
Microstructure index to fill the background. Defaults to microstructure.max() + 1.
"""
if offset is None: offset = 0
if fill is None: fill = np.nanmax(self.microstructure) + 1
dtype = float if int(fill) != fill or self.microstructure.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.microstructure[LL[0]:UR[0],LL[1]:UR[1],LL[2]:UR[2]]
return self.duplicate(canvas,
origin=self.origin+offset*self.size/self.grid,
comments=self.get_comments()+[util.execution_stamp('Geom','canvas')],
autosize=True,
)
def substitute(self,from_microstructure,to_microstructure):
"""
Substitute microstructure indices.
Parameters
----------
from_microstructure : iterable of ints
Microstructure indices to be substituted.
to_microstructure : iterable of ints
New microstructure indices.
"""
substituted = self.get_microstructure()
for from_ms,to_ms in zip(from_microstructure,to_microstructure):
substituted[self.microstructure==from_ms] = to_ms
return self.duplicate(substituted,
comments=self.get_comments()+[util.execution_stamp('Geom','substitute')],
)
def vicinity_offset(self,vicinity=1,offset=None,trigger=[],periodic=True):
"""
Offset microstructure 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 microstructure.
Defaults to 1.
offset : int, optional
Offset (positive or negative) to tag microstructure indices,
defaults to microstructure.max() + 1.
trigger : list of ints, optional
List of microstructure indices triggering a change.
Defaults to [], meaning that different neigboors trigger 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.microstructure) if offset is None else offset
mask = ndimage.filters.generic_filter(self.microstructure,
tainted_neighborhood,
size=1+2*vicinity,
mode='wrap' if periodic else 'nearest',
extra_keywords={'trigger':trigger})
microstructure = np.ma.MaskedArray(self.microstructure + offset_, np.logical_not(mask))
return self.duplicate(microstructure,
comments=self.get_comments()+[util.execution_stamp('Geom','vicinity_offset')],
)