584 lines
21 KiB
Python
584 lines
21 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 VTK
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from . import util
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from . import Environment
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from . import grid_filters
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class Geom:
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"""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 : integer, 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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'grid a b c: {}'.format(' x '.join(map(str,self.get_grid ()))),
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'size x y z: {}'.format(' x '.join(map(str,self.get_size ()))),
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'origin x y z: {}'.format(' '.join(map(str,self.get_origin()))),
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'homogenization: {}'.format(self.get_homogenization()),
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'# microstructures: {}'.format(len(np.unique(self.microstructure))),
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'max microstructure: {}'.format(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 = len(np.unique(self.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 = ['grid a b c: {}'.format(' x '.join(map(str,grid_old)))]
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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('grid a b c: {}'.format(' x '.join(map(str,self.get_grid())))))
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message.append('size x y z: {}'.format(' x '.join(map(str,size_old))))
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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('size x y z: {}'.format(' x '.join(map(str,self.get_size())))))
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message.append('origin x y z: {}'.format(' '.join(map(str,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('origin x y z: {}'.format(' '.join(map(str,self.get_origin())))))
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message.append('homogenization: {}'.format(self.get_homogenization()))
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message.append('# microstructures: {}'.format(unique_old))
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if unique_old != len(np.unique(self.microstructure)):
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message[-1] = util.delete(message[-1])
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message.append(util.emph('# microstructures: {}'.format(len(np.unique(self.microstructure)))))
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message.append('max microstructure: {}'.format(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('max microstructure: {}'.format(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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Parameters
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----------
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microstructure : numpy.ndarray
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microstructure array (3D).
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"""
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if microstructure is not None:
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if len(microstructure.shape) != 3:
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raise ValueError('Invalid microstructure shape {}'.format(microstructure.shape))
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elif microstructure.dtype not in np.sctypes['float'] + np.sctypes['int']:
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raise TypeError('Invalid data type {} for microstructure'.format(microstructure.dtype))
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else:
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self.microstructure = np.copy(microstructure)
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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('Invalid size {}'.format(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('Invalid origin {}'.format(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 : integer
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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('Invalid homogenization {}'.format(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 len(np.unique(self.microstructure))
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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.array(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 = ['{} header'.format(len(self.comments)+4)] + 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('homogenization {}'.format(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('Invalid file: expected {} entries, found {}'.format(grid.prod(),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 : 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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#comments = 'geom.py:from_Laguerre_tessellation v{}'.format(version)
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return Geom(microstructure+1,size,homogenization=1)
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@staticmethod
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def from_Voronoi_tessellation(grid,size,seeds,periodic=True):
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"""
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Generate geometry from Voronoi tessellation.
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Parameters
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----------
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grid : numpy.ndarray of shape (3)
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number of grid points in x,y,z direction.
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size : list or numpy.ndarray of shape (3)
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physical size of the microstructure in meter.
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seeds : numpy.ndarray of shape (:,3)
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position of the seed points in meter. All points need to lay within the box.
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periodic : Boolean, optional
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perform a periodic tessellation. Defaults to True.
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"""
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coords = grid_filters.cell_coord0(grid,size).reshape(-1,3)
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KDTree = spatial.cKDTree(seeds,boxsize=size) if periodic else spatial.cKDTree(seeds)
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devNull,microstructure = KDTree.query(coords)
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#comments = 'geom.py:from_Voronoi_tessellation v{}'.format(version)
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return Geom(microstructure.reshape(grid)+1,size,homogenization=1)
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def to_file(self,fname,pack=None):
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"""
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Writes a geom file.
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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()/np.unique(self.microstructure).size < 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('{}\n'.format(former))
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elif compressType == 'to':
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f.write('{} to {}\n'.format(start,former))
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elif compressType == 'of':
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f.write('{} of {}\n'.format(reps,former))
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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('{}\n'.format(former))
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elif compressType == 'to':
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f.write('{} to {}\n'.format(start,former))
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elif compressType == 'of':
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f.write('{} of {}\n'.format(reps,former))
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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 mirror(self,directions,reflect=False):
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"""
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Mirror microstructure along given directions.
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Parameters
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----------
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directions : iterable containing str
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direction(s) along which the microstructure is mirrored. Valid entries are 'x', 'y', 'z'.
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reflect : bool, optional
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reflect (include) outermost layers.
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"""
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valid = {'x','y','z'}
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if not all(isinstance(d, str) for d in directions):
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raise TypeError('Directions are not of type str.')
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elif not set(directions).issubset(valid):
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raise ValueError('Invalid direction specified {}'.format(set(directions).difference(valid)))
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limits = [None,None] if reflect else [-2,0]
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ms = self.get_microstructure()
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if 'z' in directions:
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ms = np.concatenate([ms,ms[:,:,limits[0]:limits[1]:-1]],2)
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if 'y' in directions:
|
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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)
|
|
|
|
#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 : iterable of int
|
|
new grid dimension
|
|
|
|
"""
|
|
#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))]
|
|
|
|
#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)
|
|
|
|
#self.add_comments('geom.py:renumber v{}'.format(version)
|
|
return self.update(renumbered)
|