778 lines
29 KiB
Python
778 lines
29 KiB
Python
import sys
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from io import StringIO
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import multiprocessing
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from functools import partial
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import numpy as np
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from scipy import ndimage,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,microstructure,size,origin=[0.0,0.0,0.0],homogenization=1,comments=[]):
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"""
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New geometry definition from array of microstructures and size.
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Parameters
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----------
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microstructure : numpy.ndarray
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microstructure array (3D)
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size : list or numpy.ndarray
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physical size of the microstructure in meter.
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origin : list or numpy.ndarray, optional
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physical origin of the microstructure in meter.
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homogenization : int, optional
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homogenization index.
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comments : list of str, optional
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comments lines.
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"""
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self.set_microstructure(microstructure)
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self.set_size(size)
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self.set_origin(origin)
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self.set_homogenization(homogenization)
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self.set_comments(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.get_grid ()," x ")}',
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f'size x y z: {util.srepr(self.get_size ()," x ")}',
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f'origin x y z: {util.srepr(self.get_origin()," ")}',
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f'# microstructures: {self.N_microstructure}',
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f'max microstructure: {np.nanmax(self.microstructure)}',
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])
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def update(self,microstructure=None,size=None,origin=None,rescale=False):
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"""
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Update microstructure and size.
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Parameters
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----------
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microstructure : numpy.ndarray, optional
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microstructure array (3D).
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size : list or numpy.ndarray, optional
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physical size of the microstructure in meter.
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origin : list or numpy.ndarray, optional
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physical origin of the microstructure in meter.
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rescale : bool, optional
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ignore size parameter and rescale according to change of grid points.
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"""
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grid_old = self.get_grid()
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size_old = self.get_size()
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origin_old = self.get_origin()
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unique_old = self.N_microstructure
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max_old = np.nanmax(self.microstructure)
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if size is not None and rescale:
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raise ValueError('Either set size explicitly or rescale automatically')
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self.set_microstructure(microstructure)
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self.set_origin(origin)
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if size is not None:
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self.set_size(size)
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elif rescale:
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self.set_size(self.get_grid()/grid_old*self.size)
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message = [f'grid a b c: {util.srepr(grid_old," x ")}']
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if np.any(grid_old != self.get_grid()):
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message[-1] = util.delete(message[-1])
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message.append(util.emph(f'grid a b c: {util.srepr(self.get_grid()," x ")}'))
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message.append(f'size x y z: {util.srepr(size_old," x ")}')
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if np.any(size_old != self.get_size()):
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message[-1] = util.delete(message[-1])
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message.append(util.emph(f'size x y z: {util.srepr(self.get_size()," x ")}'))
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message.append(f'origin x y z: {util.srepr(origin_old," ")}')
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if np.any(origin_old != self.get_origin()):
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message[-1] = util.delete(message[-1])
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message.append(util.emph(f'origin x y z: {util.srepr(self.get_origin()," ")}'))
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message.append(f'# microstructures: {unique_old}')
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if unique_old != self.N_microstructure:
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message[-1] = util.delete(message[-1])
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message.append(util.emph(f'# microstructures: {self.N_microstructure}'))
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message.append(f'max microstructure: {max_old}')
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if max_old != np.nanmax(self.microstructure):
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message[-1] = util.delete(message[-1])
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message.append(util.emph(f'max microstructure: {np.nanmax(self.microstructure)}'))
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return util.return_message(message)
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def set_comments(self,comments):
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"""
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Replace all existing comments.
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Parameters
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----------
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comments : list of str
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new comments.
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"""
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self.comments = []
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self.add_comments(comments)
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def add_comments(self,comments):
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"""
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Append comments to existing comments.
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Parameters
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----------
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comments : list of str
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new comments.
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"""
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self.comments += [str(c) for c in comments] if isinstance(comments,list) else [str(comments)]
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def set_microstructure(self,microstructure):
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"""
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Replace the existing microstructure representation.
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The complete microstructure is replaced (indcluding grid definition),
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unless a masked array is provided in which case the grid dimensions
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need to match and masked entries are not replaced.
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Parameters
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----------
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microstructure : numpy.ndarray or numpy.ma.core.MaskedArray of shape (:,:,:)
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Microstructure indices.
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"""
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if microstructure is not None:
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if isinstance(microstructure,np.ma.core.MaskedArray):
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self.microstructure = np.where(microstructure.mask,
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self.microstructure,microstructure.data)
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else:
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self.microstructure = np.copy(microstructure)
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if len(self.microstructure.shape) != 3:
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raise ValueError(f'Invalid microstructure shape {microstructure.shape}')
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elif self.microstructure.dtype not in np.sctypes['float'] + np.sctypes['int']:
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raise TypeError(f'Invalid microstructue data type {microstructure.dtype}')
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def set_size(self,size):
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"""
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Replace the existing size information.
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Parameters
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----------
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size : list or numpy.ndarray
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physical size of the microstructure in meter.
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"""
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if size is None:
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grid = np.asarray(self.microstructure.shape)
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self.size = grid/np.max(grid)
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else:
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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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def set_origin(self,origin):
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"""
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Replace the existing origin information.
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Parameters
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----------
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origin : list or numpy.ndarray
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physical origin of the microstructure in meter
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"""
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if origin is not None:
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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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def set_homogenization(self,homogenization):
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"""
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Replace the existing homogenization index.
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Parameters
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----------
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homogenization : int
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homogenization index
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"""
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if homogenization is not None:
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if not isinstance(homogenization,int) or homogenization < 1:
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raise TypeError(f'Invalid homogenization {homogenization}')
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else:
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self.homogenization = homogenization
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@property
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def grid(self):
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return self.get_grid()
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@property
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def N_microstructure(self):
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return np.unique(self.microstructure).size
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def get_microstructure(self):
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"""Return the microstructure representation."""
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return np.copy(self.microstructure)
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def get_size(self):
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"""Return the physical size in meter."""
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return np.copy(self.size)
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def get_origin(self):
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"""Return the origin in meter."""
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return np.copy(self.origin)
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def get_grid(self):
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"""Return the grid discretization."""
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return np.asarray(self.microstructure.shape)
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def get_homogenization(self):
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"""Return the homogenization index."""
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return self.homogenization
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def get_comments(self):
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"""Return the comments."""
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return self.comments[:]
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def get_header(self):
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"""Return the full header (grid, size, origin, homogenization, comments)."""
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header = [f'{len(self.comments)+4} header'] + self.comments
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header.append('grid a {} b {} c {}'.format(*self.get_grid()))
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header.append('size x {} y {} z {}'.format(*self.get_size()))
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header.append('origin x {} y {} z {}'.format(*self.get_origin()))
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header.append(f'homogenization {self.get_homogenization()}')
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return header
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@staticmethod
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def from_file(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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header_length,keyword = f.readline().split()[:2]
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header_length = int(header_length)
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content = f.readlines()
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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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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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elif key == 'homogenization':
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homogenization = int(items[1])
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else:
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comments.append(line.strip())
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microstructure = 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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microstructure[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(microstructure,1) != 0.0): # no float present
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microstructure = microstructure.astype('int')
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return Geom(microstructure.reshape(grid,order='F'),size,origin,homogenization,comments)
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@staticmethod
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def _find_closest_seed(seeds, weights, point):
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return np.argmin(np.sum((np.broadcast_to(point,(len(seeds),3))-seeds)**2,axis=1) - weights)
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@staticmethod
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def from_Laguerre_tessellation(grid,size,seeds,weights,periodic=True):
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"""
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Generate geometry from Laguerre tessellation.
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Parameters
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----------
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grid : 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 microstructure in meter.
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seeds : numpy.ndarray of shape (:,3)
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Position of the seed points in meter. All points need to lay within the box.
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weights : numpy.ndarray of shape (seeds.shape[0])
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Weights of the seeds. Setting all weights to 1.0 gives a standard Voronoi tessellation.
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periodic : Boolean, optional
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Perform a periodic tessellation. Defaults to True.
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"""
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if periodic:
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weights_p = np.tile(weights,27) # 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 = multiprocessing.Pool(processes = int(environment.options['DAMASK_NUM_THREADS']))
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result = pool.map_async(partial(Geom._find_closest_seed,seeds_p,weights_p), [coord for coord in coords])
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pool.close()
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pool.join()
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microstructure = np.array(result.get())
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if periodic:
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microstructure = microstructure.reshape(grid*3)
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microstructure = microstructure[grid[0]:grid[0]*2,grid[1]:grid[1]*2,grid[2]:grid[2]*2]%seeds.shape[0]
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else:
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microstructure = microstructure.reshape(grid)
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#ToDo: comments = 'geom.py:from_Laguerre_tessellation v{}'.format(version)
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return Geom(microstructure+1,size,homogenization=1)
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@staticmethod
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def from_Voronoi_tessellation(grid,size,seeds,periodic=True):
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"""
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Generate geometry from Voronoi tessellation.
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Parameters
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----------
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grid : 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 microstructure in meter.
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seeds : numpy.ndarray of shape (:,3)
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Position of the seed points in meter. All points need to lay within the box.
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periodic : Boolean, optional
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Perform a periodic tessellation. Defaults to True.
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"""
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coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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devNull,microstructure = KDTree.query(coords)
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#ToDo: comments = 'geom.py:from_Voronoi_tessellation v{}'.format(version)
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return Geom(microstructure.reshape(grid)+1,size,homogenization=1)
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def to_file(self,fname,pack=None):
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"""
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Writes a geom file.
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Parameters
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----------
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fname : str or file handle
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Geometry file to write.
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pack : 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 = self.get_header()
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grid = self.get_grid()
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if pack is None:
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plain = grid.prod()/self.N_microstructure < 250
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else:
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plain = not pack
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if plain:
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format_string = '%g' if self.microstructure.dtype in np.sctypes['float'] else \
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'%{}i'.format(1+int(np.floor(np.log10(np.nanmax(self.microstructure)))))
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np.savetxt(fname,
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self.microstructure.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.microstructure.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(self.get_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 to_vtk(self,fname=None):
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"""
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Generates vtk file.
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Parameters
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----------
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fname : str, optional
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Vtk file to write. If no file is given, a string is returned.
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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.microstructure.flatten(order='F'),'microstructure')
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if fname:
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v.write(fname)
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else:
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sys.stdout.write(v.__repr__())
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def show(self):
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"""Show raw content (as in file)."""
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f=StringIO()
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self.to_file(f)
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f.seek(0)
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return ''.join(f.readlines())
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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 axis.
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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 False.
|
|
|
|
"""
|
|
# 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)*0.5 if periodic else c) # center if periodic
|
|
coords_rot = R.broadcast_to(tuple(self.grid))@coords
|
|
|
|
with np.errstate(over='ignore',under='ignore'):
|
|
mask = np.where(np.sum(np.abs(coords_rot/r)**(2.0**exponent),axis=-1) < 1,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.update(ms)
|
|
|
|
|
|
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.
|
|
|
|
"""
|
|
valid = {'x','y','z'}
|
|
if not all(isinstance(d, str) for d in directions):
|
|
raise TypeError('Directions are not of type str.')
|
|
elif 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)
|
|
|
|
#ToDo: self.add_comments('geom.py:mirror v{}'.format(version)
|
|
return self.update(ms,rescale=True)
|
|
|
|
|
|
def scale(self,grid):
|
|
"""
|
|
Scale microstructure to new grid.
|
|
|
|
Parameters
|
|
----------
|
|
grid : numpy.ndarray of shape (3)
|
|
Number of grid points in x,y,z direction.
|
|
|
|
"""
|
|
#ToDo: self.add_comments('geom.py:scale v{}'.format(version)
|
|
return self.update(
|
|
ndimage.interpolation.zoom(
|
|
self.microstructure,
|
|
grid/self.get_grid(),
|
|
output=self.microstructure.dtype,
|
|
order=0,
|
|
mode='nearest',
|
|
prefilter=False
|
|
)
|
|
)
|
|
|
|
|
|
def clean(self,stencil=3):
|
|
"""
|
|
Smooth microstructure by selecting most frequent index within given stencil at each location.
|
|
|
|
Parameters
|
|
----------
|
|
stencil : int, optional
|
|
Size of smoothing stencil.
|
|
|
|
"""
|
|
def mostFrequent(arr):
|
|
unique, inverse = np.unique(arr, return_inverse=True)
|
|
return unique[np.argmax(np.bincount(inverse))]
|
|
|
|
#ToDo: self.add_comments('geom.py:clean v{}'.format(version)
|
|
return self.update(ndimage.filters.generic_filter(
|
|
self.microstructure,
|
|
mostFrequent,
|
|
size=(stencil,)*3
|
|
).astype(self.microstructure.dtype)
|
|
)
|
|
|
|
|
|
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)
|
|
|
|
#ToDo: self.add_comments('geom.py:renumber v{}'.format(version)
|
|
return self.update(renumbered)
|
|
|
|
|
|
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
|
|
|
|
#ToDo: self.add_comments('geom.py:rotate v{}'.format(version)
|
|
return self.update(microstructure_in,origin=origin,rescale=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 corners. Defaults to microstructure.max() + 1.
|
|
|
|
"""
|
|
if fill is None: fill = np.nanmax(self.microstructure) + 1
|
|
if offset is None: offset = 0
|
|
dtype = float if int(fill) != fill or self.microstructure.dtype==np.float else int
|
|
|
|
canvas = np.full(self.grid if grid is None else grid,
|
|
fill if fill is not None else np.nanmax(self.microstructure)+1,dtype)
|
|
|
|
l = np.clip( offset, 0,np.minimum(self.grid +offset,grid)) # noqa
|
|
r = np.clip( offset+self.grid,0,np.minimum(self.grid*2+offset,grid))
|
|
L = np.clip(-offset, 0,np.minimum(grid -offset,self.grid))
|
|
R = np.clip(-offset+grid, 0,np.minimum(grid*2 -offset,self.grid))
|
|
|
|
canvas[l[0]:r[0],l[1]:r[1],l[2]:r[2]] = self.microstructure[L[0]:R[0],L[1]:R[1],L[2]:R[2]]
|
|
|
|
#ToDo: self.add_comments('geom.py:canvas v{}'.format(version)
|
|
return self.update(canvas,origin=self.origin+offset*self.size/self.grid,rescale=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
|
|
|
|
#ToDo: self.add_comments('geom.py:substitute v{}'.format(version)
|
|
return self.update(substituted)
|
|
|
|
|
|
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))
|
|
|
|
#ToDo: self.add_comments('geom.py:vicinity_offset v{}'.format(version)
|
|
return self.update(microstructure)
|
|
|