Merge remote-tracking branch 'origin/development' into thermal-restart
This commit is contained in:
Sharan
commit
d72347fe25
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@ -1,178 +0,0 @@
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#!/usr/bin/env python3
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import os
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import sys
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from io import StringIO
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from optparse import OptionParser
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import numpy as np
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from scipy import ndimage
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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getInterfaceEnergy = lambda A,B: np.float32((A != B)*1.0) # 1.0 if A & B are distinct, 0.0 otherwise
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struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood
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#--------------------------------------------------------------------------------------------------
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# MAIN
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#--------------------------------------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog option(s) [geomfile(s)]', description = """
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Smoothen interface roughness by simulated curvature flow.
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This is achieved by the diffusion of each initially sharply bounded grain volume within the periodic domain
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up to a given distance 'd' voxels.
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The final geometry is assembled by selecting at each voxel that grain index for which the concentration remains largest.
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References 10.1073/pnas.1111557108 (10.1006/jcph.1994.1105)
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""", version = scriptID)
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parser.add_option('-d', '--distance',
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dest = 'd',
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type = 'float', metavar = 'float',
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help = 'diffusion distance in voxels [%default]')
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parser.add_option('-N', '--iterations',
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dest = 'N',
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type = 'int', metavar = 'int',
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help = 'curvature flow iterations [%default]')
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parser.add_option('-i', '--immutable',
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action = 'extend', dest = 'immutable', metavar = '<int LIST>',
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help = 'list of immutable material indices')
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parser.add_option('--ndimage',
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dest = 'ndimage', action='store_true',
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help = 'use ndimage.gaussian_filter in lieu of explicit FFT')
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parser.set_defaults(d = 1,
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N = 1,
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immutable = [],
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ndimage = False,
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)
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(options, filenames) = parser.parse_args()
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options.immutable = list(map(int,options.immutable))
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if filenames == []: filenames = [None]
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for name in filenames:
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damask.util.report(scriptName,name)
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geom = damask.Grid.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid_original = geom.cells
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damask.util.croak(geom)
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material = np.tile(geom.material,np.where(grid_original == 1, 2,1)) # make one copy along dimensions with grid == 1
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grid = np.array(material.shape)
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# --- initialize support data ---------------------------------------------------------------------
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# store a copy of the initial material indices to find locations of immutable indices
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material_original = np.copy(material)
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if not options.ndimage:
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X,Y,Z = np.mgrid[0:grid[0],0:grid[1],0:grid[2]]
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# Calculates gaussian weights for simulating 3d diffusion
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gauss = np.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d),dtype=np.float32) \
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/np.power(2.0*np.pi*options.d*options.d,(3.0 - np.count_nonzero(grid_original == 1))/2.,dtype=np.float32)
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gauss[:,:,:grid[2]//2:-1] = gauss[:,:,1:(grid[2]+1)//2] # trying to cope with uneven (odd) grid size
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gauss[:,:grid[1]//2:-1,:] = gauss[:,1:(grid[1]+1)//2,:]
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gauss[:grid[0]//2:-1,:,:] = gauss[1:(grid[0]+1)//2,:,:]
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gauss = np.fft.rfftn(gauss).astype(np.complex64)
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for smoothIter in range(options.N):
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interfaceEnergy = np.zeros(material.shape,dtype=np.float32)
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for i in (-1,0,1):
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for j in (-1,0,1):
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for k in (-1,0,1):
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# assign interfacial energy to all voxels that have a differing neighbor (in Moore neighborhood)
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interfaceEnergy = np.maximum(interfaceEnergy,
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getInterfaceEnergy(material,np.roll(np.roll(np.roll(
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material,i,axis=0), j,axis=1), k,axis=2)))
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# periodically extend interfacial energy array by half a grid size in positive and negative directions
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periodic_interfaceEnergy = np.tile(interfaceEnergy,(3,3,3))[grid[0]//2:-grid[0]//2,
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grid[1]//2:-grid[1]//2,
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grid[2]//2:-grid[2]//2]
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# transform bulk volume (i.e. where interfacial energy remained zero), store index of closest boundary voxel
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index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0.,
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return_distances = False,
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return_indices = True)
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# want array index of nearest voxel on periodically extended boundary
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periodic_bulkEnergy = periodic_interfaceEnergy[index[0],
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index[1],
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index[2]].reshape(2*grid) # fill bulk with energy of nearest interface
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if options.ndimage:
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periodic_diffusedEnergy = ndimage.gaussian_filter(
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np.where(ndimage.morphology.binary_dilation(periodic_interfaceEnergy > 0.,
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structure = struc,
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iterations = int(round(options.d*2.))-1, # fat boundary
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),
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periodic_bulkEnergy, # ...and zero everywhere else
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0.),
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sigma = options.d)
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else:
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diffusedEnergy = np.fft.irfftn(np.fft.rfftn(
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np.where(
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ndimage.morphology.binary_dilation(interfaceEnergy > 0.,
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structure = struc,
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iterations = int(round(options.d*2.))-1),# fat boundary
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periodic_bulkEnergy[grid[0]//2:-grid[0]//2, # retain filled energy on fat boundary...
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grid[1]//2:-grid[1]//2,
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grid[2]//2:-grid[2]//2], # ...and zero everywhere else
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0.)).astype(np.complex64) *
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gauss).astype(np.float32)
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periodic_diffusedEnergy = np.tile(diffusedEnergy,(3,3,3))[grid[0]//2:-grid[0]//2,
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grid[1]//2:-grid[1]//2,
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grid[2]//2:-grid[2]//2] # periodically extend the smoothed bulk energy
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# transform voxels close to interface region
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index = ndimage.morphology.distance_transform_edt(periodic_diffusedEnergy >= 0.95*np.amax(periodic_diffusedEnergy),
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return_distances = False,
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return_indices = True) # want index of closest bulk grain
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periodic_material = np.tile(material,(3,3,3))[grid[0]//2:-grid[0]//2,
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grid[1]//2:-grid[1]//2,
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grid[2]//2:-grid[2]//2] # periodically extend the geometry
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material = periodic_material[index[0],
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index[1],
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index[2]].reshape(2*grid)[grid[0]//2:-grid[0]//2,
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grid[1]//2:-grid[1]//2,
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grid[2]//2:-grid[2]//2] # extent grains into interface region
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# replace immutable materials with closest mutable ones
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index = ndimage.morphology.distance_transform_edt(np.in1d(material,options.immutable).reshape(grid),
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return_distances = False,
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return_indices = True)
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material = material[index[0],
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index[1],
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index[2]]
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immutable = np.zeros(material.shape, dtype=np.bool)
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# find locations where immutable materials have been in original structure
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for micro in options.immutable:
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immutable += material_original == micro
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# undo any changes involving immutable materials
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material = np.where(immutable, material_original,material)
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damask.Grid(material = material[0:grid_original[0],0:grid_original[1],0:grid_original[2]],
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size = geom.size,
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origin = geom.origin,
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comments = geom.comments + [scriptID + ' ' + ' '.join(sys.argv[1:])],
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)\
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.save(sys.stdout if name is None else name)
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@ -1 +1 @@
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v3.0.0-alpha5-545-gad74f5dbe
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v3.0.0-alpha5-552-ga6e78c5b6
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|
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@ -9,3 +9,4 @@ import numpy as np
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FloatSequence = Union[np.ndarray,Sequence[float]]
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IntSequence = Union[np.ndarray,Sequence[int]]
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FileHandle = Union[TextIO, str, Path]
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NumpyRngSeed = Union[int, IntSequence, np.random.SeedSequence, np.random.BitGenerator, np.random.Generator]
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|
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@ -1,3 +1,4 @@
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"""Functionality for generation of seed points for Voronoi or Laguerre tessellation."""
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from typing import Tuple as _Tuple
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@ -5,7 +6,7 @@ from typing import Tuple as _Tuple
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from scipy import spatial as _spatial
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import numpy as _np
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from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence
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from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence, NumpyRngSeed as _NumpyRngSeed
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from . import util as _util
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from . import grid_filters as _grid_filters
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@ -13,7 +14,7 @@ from . import grid_filters as _grid_filters
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def from_random(size: _FloatSequence,
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N_seeds: int,
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cells: _IntSequence = None,
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rng_seed=None) -> _np.ndarray:
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rng_seed: _NumpyRngSeed = None) -> _np.ndarray:
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"""
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Place seeds randomly in space.
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@ -53,7 +54,7 @@ def from_Poisson_disc(size: _FloatSequence,
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N_candidates: int,
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distance: float,
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periodic: bool = True,
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rng_seed=None) -> _np.ndarray:
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rng_seed: _NumpyRngSeed = None) -> _np.ndarray:
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"""
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Place seeds according to a Poisson disc distribution.
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|
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@ -16,7 +16,7 @@ import numpy as np
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import h5py
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from . import version
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from ._typehints import IntSequence, FloatSequence
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from ._typehints import FloatSequence, NumpyRngSeed
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# limit visibility
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__all__=[
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@ -396,7 +396,7 @@ def execution_stamp(class_name: str,
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def hybrid_IA(dist: np.ndarray,
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N: int,
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rng_seed: Union[int, IntSequence] = None) -> np.ndarray:
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rng_seed: NumpyRngSeed = None) -> np.ndarray:
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"""
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Hybrid integer approximation.
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|
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@ -287,7 +287,7 @@ class TestOrientation:
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@pytest.mark.parametrize('family',crystal_families)
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@pytest.mark.parametrize('proper',[True,False])
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def test_in_SST(self,family,proper):
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assert Orientation(family=family).in_SST(np.zeros(3),proper) # noqa
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assert Orientation(family=family).in_SST(np.zeros(3),proper)
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@pytest.mark.parametrize('function',['in_SST','IPF_color'])
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def test_invalid_argument(self,function):
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|
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@ -367,13 +367,13 @@ class TestResult:
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@pytest.mark.parametrize('mode',['cell','node'])
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def test_coordinates(self,default,mode):
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if mode == 'cell': # noqa
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a = grid_filters.coordinates0_point(default.cells,default.size,default.origin)
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b = default.coordinates0_point.reshape(tuple(default.cells)+(3,),order='F')
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elif mode == 'node':
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a = grid_filters.coordinates0_node(default.cells,default.size,default.origin)
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b = default.coordinates0_node.reshape(tuple(default.cells+1)+(3,),order='F')
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assert np.allclose(a,b)
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if mode == 'cell':
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a = grid_filters.coordinates0_point(default.cells,default.size,default.origin)
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b = default.coordinates0_point.reshape(tuple(default.cells)+(3,),order='F')
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elif mode == 'node':
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a = grid_filters.coordinates0_node(default.cells,default.size,default.origin)
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b = default.coordinates0_node.reshape(tuple(default.cells+1)+(3,),order='F')
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assert np.allclose(a,b)
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@pytest.mark.parametrize('output',['F','*',['P'],['P','F']],ids=range(4))
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@pytest.mark.parametrize('fname',['12grains6x7x8_tensionY.hdf5'],ids=range(1))
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@ -421,7 +421,7 @@ class TestResult:
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def test_XDMF_datatypes(self,tmp_path,single_phase,update,ref_path):
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for shape in [('scalar',()),('vector',(3,)),('tensor',(3,3)),('matrix',(12,))]:
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for dtype in ['f4','f8','i1','i2','i4','i8','u1','u2','u4','u8']:
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single_phase.add_calculation(f"np.ones(np.shape(#F#)[0:1]+{shape[1]},'{dtype}')",f'{shape[0]}_{dtype}') # noqa
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single_phase.add_calculation(f"np.ones(np.shape(#F#)[0:1]+{shape[1]},'{dtype}')",f'{shape[0]}_{dtype}')
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fname = os.path.splitext(os.path.basename(single_phase.fname))[0]+'.xdmf'
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os.chdir(tmp_path)
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single_phase.export_XDMF()
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|
|
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@ -1076,19 +1076,19 @@ class TestRotation:
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def test_from_fiber_component(self,N,sigma):
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p = []
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for run in range(5):
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alpha = np.random.random()*2*np.pi,np.arccos(np.random.random()) # noqa
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beta = np.random.random()*2*np.pi,np.arccos(np.random.random())
|
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alpha = np.random.random()*2*np.pi,np.arccos(np.random.random())
|
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beta = np.random.random()*2*np.pi,np.arccos(np.random.random())
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|
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f_in_C = np.array([np.sin(alpha[0])*np.cos(alpha[1]), np.sin(alpha[0])*np.sin(alpha[1]), np.cos(alpha[0])])
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f_in_S = np.array([np.sin(beta[0] )*np.cos(beta[1] ), np.sin(beta[0] )*np.sin(beta[1] ), np.cos(beta[0] )])
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ax = np.append(np.cross(f_in_C,f_in_S), - np.arccos(np.dot(f_in_C,f_in_S)))
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n = Rotation.from_axis_angle(ax if ax[3] > 0.0 else ax*-1.0 ,normalize=True) # rotation to align fiber axis in crystal and sample system
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f_in_C = np.array([np.sin(alpha[0])*np.cos(alpha[1]), np.sin(alpha[0])*np.sin(alpha[1]), np.cos(alpha[0])])
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f_in_S = np.array([np.sin(beta[0] )*np.cos(beta[1] ), np.sin(beta[0] )*np.sin(beta[1] ), np.cos(beta[0] )])
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ax = np.append(np.cross(f_in_C,f_in_S), - np.arccos(np.dot(f_in_C,f_in_S)))
|
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n = Rotation.from_axis_angle(ax if ax[3] > 0.0 else ax*-1.0 ,normalize=True) # rotation to align fiber axis in crystal and sample system
|
||||
|
||||
o = Rotation.from_fiber_component(alpha,beta,np.radians(sigma),N,False)
|
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angles = np.arccos(np.clip(np.dot(o@np.broadcast_to(f_in_S,(N,3)),n@f_in_S),-1,1))
|
||||
dist = np.array(angles) * (np.random.randint(0,2,N)*2-1)
|
||||
o = Rotation.from_fiber_component(alpha,beta,np.radians(sigma),N,False)
|
||||
angles = np.arccos(np.clip(np.dot(o@np.broadcast_to(f_in_S,(N,3)),n@f_in_S),-1,1))
|
||||
dist = np.array(angles) * (np.random.randint(0,2,N)*2-1)
|
||||
|
||||
p.append(stats.normaltest(dist)[1])
|
||||
p.append(stats.normaltest(dist)[1])
|
||||
|
||||
sigma_out = np.degrees(np.std(dist))
|
||||
p = np.average(p)
|
||||
|
|
|
|||
|
|
@ -173,11 +173,11 @@ class TestVTK:
|
|||
polyData = VTK.from_poly_data(points)
|
||||
polyData.add(points,'coordinates')
|
||||
if update:
|
||||
polyData.save(ref_path/'polyData') # noqa
|
||||
polyData.save(ref_path/'polyData')
|
||||
else:
|
||||
reference = VTK.load(ref_path/'polyData.vtp') # noqa
|
||||
assert polyData.__repr__() == reference.__repr__() and \
|
||||
np.allclose(polyData.get('coordinates'),points)
|
||||
reference = VTK.load(ref_path/'polyData.vtp')
|
||||
assert polyData.__repr__() == reference.__repr__() and \
|
||||
np.allclose(polyData.get('coordinates'),points)
|
||||
|
||||
@pytest.mark.xfail(int(vtk.vtkVersion.GetVTKVersion().split('.')[0])<8, reason='missing METADATA')
|
||||
def test_compare_reference_rectilinearGrid(self,update,ref_path,tmp_path):
|
||||
|
|
@ -189,8 +189,8 @@ class TestVTK:
|
|||
rectilinearGrid.add(np.ascontiguousarray(c),'cell')
|
||||
rectilinearGrid.add(np.ascontiguousarray(n),'node')
|
||||
if update:
|
||||
rectilinearGrid.save(ref_path/'rectilinearGrid') # noqa
|
||||
rectilinearGrid.save(ref_path/'rectilinearGrid')
|
||||
else:
|
||||
reference = VTK.load(ref_path/'rectilinearGrid.vtr') # noqa
|
||||
assert rectilinearGrid.__repr__() == reference.__repr__() and \
|
||||
np.allclose(rectilinearGrid.get('cell'),c)
|
||||
reference = VTK.load(ref_path/'rectilinearGrid.vtr')
|
||||
assert rectilinearGrid.__repr__() == reference.__repr__() and \
|
||||
np.allclose(rectilinearGrid.get('cell'),c)
|
||||
|
|
|
|||
|
|
@ -8,10 +8,9 @@ submodule(phase:eigen) thermalexpansion
|
|||
integer, dimension(:), allocatable :: kinematics_thermal_expansion_instance
|
||||
|
||||
type :: tParameters
|
||||
real(pReal) :: &
|
||||
T_ref
|
||||
real(pReal), dimension(3,3,3) :: &
|
||||
A = 0.0_pReal
|
||||
type(tPolynomial) :: &
|
||||
A_11, &
|
||||
A_33
|
||||
end type tParameters
|
||||
|
||||
type(tParameters), dimension(:), allocatable :: param
|
||||
|
|
@ -34,7 +33,7 @@ module function thermalexpansion_init(kinematics_length) result(myKinematics)
|
|||
phase, &
|
||||
mech, &
|
||||
kinematics, &
|
||||
kinematic_type
|
||||
myConfig
|
||||
|
||||
print'(/,1x,a)', '<<<+- phase:mechanical:eigen:thermalexpansion init -+>>>'
|
||||
|
||||
|
|
@ -56,21 +55,13 @@ module function thermalexpansion_init(kinematics_length) result(myKinematics)
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do k = 1, kinematics%length
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if (myKinematics(k,p)) then
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associate(prm => param(kinematics_thermal_expansion_instance(p)))
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kinematic_type => kinematics%get(k)
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prm%T_ref = kinematic_type%get_asFloat('T_ref', defaultVal=T_ROOM)
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myConfig => kinematics%get(k)
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prm%A_11 = polynomial(myConfig%asDict(),'A_11','T')
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if (any(phase_lattice(p) == ['hP','tI'])) &
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prm%A_33 = polynomial(myConfig%asDict(),'A_33','T')
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prm%A(1,1,1) = kinematic_type%get_asFloat('A_11')
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prm%A(1,1,2) = kinematic_type%get_asFloat('A_11,T', defaultVal=0.0_pReal)
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prm%A(1,1,3) = kinematic_type%get_asFloat('A_11,T^2',defaultVal=0.0_pReal)
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if (any(phase_lattice(p) == ['hP','tI'])) then
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prm%A(3,3,1) = kinematic_type%get_asFloat('A_33')
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prm%A(3,3,2) = kinematic_type%get_asFloat('A_33,T', defaultVal=0.0_pReal)
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prm%A(3,3,3) = kinematic_type%get_asFloat('A_33,T^2',defaultVal=0.0_pReal)
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end if
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do i=1, size(prm%A,3)
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prm%A(1:3,1:3,i) = lattice_symmetrize_33(prm%A(1:3,1:3,i),phase_lattice(p))
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end do
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end associate
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end if
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||||
end do
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@ -91,22 +82,20 @@ module subroutine thermalexpansion_LiAndItsTangent(Li, dLi_dTstar, ph,me)
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dLi_dTstar !< derivative of Li with respect to Tstar (4th-order tensor defined to be zero)
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||||
|
||||
real(pReal) :: T, dot_T
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||||
real(pReal), dimension(3,3) :: A
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||||
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||||
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||||
T = thermal_T(ph,me)
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||||
dot_T = thermal_dot_T(ph,me)
|
||||
|
||||
associate(prm => param(kinematics_thermal_expansion_instance(ph)))
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||||
Li = dot_T * ( &
|
||||
prm%A(1:3,1:3,1) & ! constant coefficient
|
||||
+ prm%A(1:3,1:3,2)*(T - prm%T_ref) & ! linear coefficient
|
||||
+ prm%A(1:3,1:3,3)*(T - prm%T_ref)**2 & ! quadratic coefficient
|
||||
) / &
|
||||
(1.0_pReal &
|
||||
+ prm%A(1:3,1:3,1)*(T - prm%T_ref) / 1.0_pReal &
|
||||
+ prm%A(1:3,1:3,2)*(T - prm%T_ref)**2 / 2.0_pReal &
|
||||
+ prm%A(1:3,1:3,3)*(T - prm%T_ref)**3 / 3.0_pReal &
|
||||
)
|
||||
|
||||
A = 0.0_pReal
|
||||
A(1,1) = prm%A_11%at(T)
|
||||
if (any(phase_lattice(ph) == ['hP','tI'])) A(3,3) = prm%A_33%at(T)
|
||||
A = lattice_symmetrize_33(A,phase_lattice(ph))
|
||||
Li = dot_T * A
|
||||
|
||||
end associate
|
||||
dLi_dTstar = 0.0_pReal
|
||||
|
||||
|
|
|
|||
|
|
@ -48,7 +48,7 @@ module subroutine elastic_init(phases)
|
|||
prm%C_11 = polynomial(elastic%asDict(),'C_11','T')
|
||||
prm%C_12 = polynomial(elastic%asDict(),'C_12','T')
|
||||
prm%C_44 = polynomial(elastic%asDict(),'C_44','T')
|
||||
|
||||
|
||||
if (any(phase_lattice(ph) == ['hP','tI'])) then
|
||||
prm%C_13 = polynomial(elastic%asDict(),'C_13','T')
|
||||
prm%C_33 = polynomial(elastic%asDict(),'C_33','T')
|
||||
|
|
@ -77,7 +77,7 @@ pure module function elastic_C66(ph,en) result(C66)
|
|||
|
||||
|
||||
associate(prm => param(ph))
|
||||
|
||||
|
||||
C66 = 0.0_pReal
|
||||
T = thermal_T(ph,en)
|
||||
|
||||
|
|
|
|||
|
|
@ -163,7 +163,7 @@ subroutine selfTest
|
|||
'T_ref: '//trim(adjustl(x_ref_s))//IO_EOL
|
||||
Dict => YAML_parse_str(trim(YAML_s))
|
||||
p2 = polynomial(dict%asDict(),'C','T')
|
||||
if (dNeq(p1%at(x),p2%at(x),1.0e-12_pReal)) error stop 'polynomials: init'
|
||||
if (dNeq(p1%at(x),p2%at(x),1.0e-10_pReal)) error stop 'polynomials: init'
|
||||
|
||||
p1 = polynomial(coef*[0.0_pReal,1.0_pReal,0.0_pReal],x_ref)
|
||||
if (dNeq(p1%at(x_ref+x),-p1%at(x_ref-x),1.0e-10_pReal)) error stop 'polynomials: eval(odd)'
|
||||
|
|
|
|||
Loading…
Reference in New Issue