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Merge branch 'restructure-Orientation-2' into 'development' 

restructured Orientation

See merge request damask/DAMASK!412
This commit is contained in:
Philip Eisenlohr 2021-08-09 12:55:27 +00:00
parent be8e0dc86a 5292f9b414
commit 37ffd91f72
12 changed files with 1396 additions and 1461 deletions
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117
processing/legacy/addSchmidfactors.py vendored
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@ -1,117 +0,0 @@
#!/usr/bin/env python3
import os
import sys
from io import StringIO
from optparse import OptionParser
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
slipSystems = {
'fcc': damask.lattice.kinematics['cF']['slip'][:12],
'bcc': damask.lattice.kinematics['cI']['slip'],
'hex': damask.lattice.kinematics['hP']['slip'],
}
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(usage='%prog options [ASCIItable(s)]', description = """
Add columns listing Schmid factors (and optional trace vector of selected system) for given Euler angles.
""", version = scriptID)
lattice_choices = list(slipSystems.keys())
parser.add_option('-l',
'--lattice',
dest = 'lattice', type = 'choice', choices = lattice_choices, metavar='string',
help = 'type of lattice structure [%default] {}'.format(lattice_choices))
parser.add_option('--covera',
dest = 'CoverA', type = 'float', metavar = 'float',
help = 'C over A ratio for hexagonal systems [%default]')
parser.add_option('-f',
'--force',
dest = 'force',
type = 'float', nargs = 3, metavar = 'float float float',
help = 'force direction in lab frame [%default]')
parser.add_option('-n',
'--normal',
dest = 'normal',
type = 'float', nargs = 3, metavar = 'float float float',
help = 'stress plane normal in lab frame, per default perpendicular to the force')
parser.add_option('-o',
'--orientation',
dest = 'quaternion',
metavar = 'string',
help = 'label of crystal orientation given as unit quaternion [%default]')
parser.set_defaults(force = (0.0,0.0,1.0),
quaternion='orientation',
normal = None,
lattice = lattice_choices[0],
CoverA = np.sqrt(8./3.),
)
(options, filenames) = parser.parse_args()
if filenames == []: filenames = [None]
force = np.array(options.force)/np.linalg.norm(options.force)
if options.normal is not None:
normal = np.array(options.normal)/np.linalg.norm(options.ormal)
if abs(np.dot(force,normal)) > 1e-3:
parser.error('stress plane normal not orthogonal to force direction')
else:
normal = force
if options.lattice in ['bcc','fcc']:
slip_direction = slipSystems[options.lattice][:,:3]
slip_normal = slipSystems[options.lattice][:,3:]
elif options.lattice == 'hex':
slip_direction = np.zeros((len(slipSystems['hex']),3),'d')
slip_normal = np.zeros_like(slip_direction)
# convert 4 Miller index notation of hex to orthogonal 3 Miller index notation
for i in range(len(slip_direction)):
slip_direction[i] = np.array([slipSystems['hex'][i,0]*1.5,
(slipSystems['hex'][i,0] + 2.*slipSystems['hex'][i,1])*0.5*np.sqrt(3),
slipSystems['hex'][i,3]*options.CoverA,
])
slip_normal[i] = np.array([slipSystems['hex'][i,4],
(slipSystems['hex'][i,4] + 2.*slipSystems['hex'][i,5])/np.sqrt(3),
slipSystems['hex'][i,7]/options.CoverA,
])
slip_direction /= np.linalg.norm(slip_direction,axis=1,keepdims=True)
slip_normal /= np.linalg.norm(slip_normal, axis=1,keepdims=True)
labels = ['S[{direction[0]:.1g}_{direction[1]:.1g}_{direction[2]:.1g}]'
'({normal[0]:.1g}_{normal[1]:.1g}_{normal[2]:.1g})'\
.format(normal = theNormal, direction = theDirection,
) for theNormal,theDirection in zip(slip_normal,slip_direction)]
for name in filenames:
damask.util.report(scriptName,name)
table = damask.Table.load(StringIO(''.join(sys.stdin.read())) if name is None else name)
o = damask.Rotation.from_quaternion(table.get(options.quaternion))
force = np.broadcast_to(force, o.shape+(3,))
normal = np.broadcast_to(normal,o.shape+(3,))
slip_direction = np.broadcast_to(slip_direction,o.shape+slip_direction.shape)
slip_normal = np.broadcast_to(slip_normal, o.shape+slip_normal.shape)
S = np.abs(np.einsum('ijk,ik->ij',slip_direction,(o@force))*
np.einsum('ijk,ik->ij',slip_normal, (o@normal)))
for i,label in enumerate(labels):
table = table.add(label,S[:,i],scriptID+' '+' '.join(sys.argv[1:]))
table.save((sys.stdout if name is None else name))

2
python/damask/__init__.py
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@ -14,10 +14,10 @@ from . import tensor # noqa
from . import mechanics # noqa
from . import solver # noqa
from . import grid_filters # noqa
from . import lattice # noqa
#Modules that contain only one class (of the same name), are prefixed by a '_'.
#For example, '_colormap' containsa class called 'Colormap' which is imported as 'damask.Colormap'.
from ._rotation import Rotation # noqa
from ._crystal import Crystal # noqa
from ._orientation import Orientation # noqa
from ._table import Table # noqa
from ._vtk import VTK # noqa

849
python/damask/_crystal.py Normal file
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@ -0,0 +1,849 @@
import numpy as np
from . import util
from . import Rotation
lattice_symmetries = {
'aP': 'triclinic',
'mP': 'monoclinic',
'mS': 'monoclinic',
'oP': 'orthorhombic',
'oS': 'orthorhombic',
'oI': 'orthorhombic',
'oF': 'orthorhombic',
'tP': 'tetragonal',
'tI': 'tetragonal',
'hP': 'hexagonal',
'cP': 'cubic',
'cI': 'cubic',
'cF': 'cubic',
}
class Crystal():
"""Crystal lattice."""
def __init__(self,*,
family = None,
lattice = None,
a = None,b = None,c = None,
alpha = None,beta = None,gamma = None,
degrees = False):
"""
Representation of crystal in terms of crystal family or Bravais lattice.
Parameters
----------
family : {'triclinic', 'monoclinic', 'orthorhombic', 'tetragonal', 'hexagonal', 'cubic'}, optional.
Name of the crystal family.
Will be inferred if 'lattice' is given.
lattice : {'aP', 'mP', 'mS', 'oP', 'oS', 'oI', 'oF', 'tP', 'tI', 'hP', 'cP', 'cI', 'cF'}, optional.
Name of the Bravais lattice in Pearson notation.
a : float, optional
Length of lattice parameter 'a'.
b : float, optional
Length of lattice parameter 'b'.
c : float, optional
Length of lattice parameter 'c'.
alpha : float, optional
Angle between b and c lattice basis.
beta : float, optional
Angle between c and a lattice basis.
gamma : float, optional
Angle between a and b lattice basis.
degrees : bool, optional
Angles are given in degrees. Defaults to False.
"""
if family not in [None] + list(lattice_symmetries.values()):
raise KeyError(f'invalid crystal family "{family}"')
if lattice is not None and family is not None and family != lattice_symmetries[lattice]:
raise KeyError(f'incompatible family "{family}" for lattice "{lattice}"')
self.family = lattice_symmetries[lattice] if family is None else family
self.lattice = lattice
if self.lattice is not None:
self.a = 1 if a is None else a
self.b = b
self.c = c
self.a = float(self.a) if self.a is not None else \
(self.b / self.ratio['b'] if self.b is not None and self.ratio['b'] is not None else
self.c / self.ratio['c'] if self.c is not None and self.ratio['c'] is not None else None)
self.b = float(self.b) if self.b is not None else \
(self.a * self.ratio['b'] if self.a is not None and self.ratio['b'] is not None else
self.c / self.ratio['c'] * self.ratio['b']
if self.c is not None and self.ratio['b'] is not None and self.ratio['c'] is not None else None)
self.c = float(self.c) if self.c is not None else \
(self.a * self.ratio['c'] if self.a is not None and self.ratio['c'] is not None else
self.b / self.ratio['b'] * self.ratio['c']
if self.c is not None and self.ratio['b'] is not None and self.ratio['c'] is not None else None)
self.alpha = np.radians(alpha) if degrees and alpha is not None else alpha
self.beta = np.radians(beta) if degrees and beta is not None else beta
self.gamma = np.radians(gamma) if degrees and gamma is not None else gamma
if self.alpha is None and 'alpha' in self.immutable: self.alpha = self.immutable['alpha']
if self.beta is None and 'beta' in self.immutable: self.beta = self.immutable['beta']
if self.gamma is None and 'gamma' in self.immutable: self.gamma = self.immutable['gamma']
if \
(self.a is None) \
or (self.b is None or ('b' in self.immutable and self.b != self.immutable['b'] * self.a)) \
or (self.c is None or ('c' in self.immutable and self.c != self.immutable['c'] * self.b)) \
or (self.alpha is None or ('alpha' in self.immutable and self.alpha != self.immutable['alpha'])) \
or (self.beta is None or ('beta' in self.immutable and self.beta != self.immutable['beta'])) \
or (self.gamma is None or ('gamma' in self.immutable and self.gamma != self.immutable['gamma'])):
raise ValueError (f'Incompatible parameters {self.parameters} for crystal family {self.family}')
if np.any(np.array([self.alpha,self.beta,self.gamma]) <= 0):
raise ValueError ('Lattice angles must be positive')
if np.any([np.roll([self.alpha,self.beta,self.gamma],r)[0]
> np.sum(np.roll([self.alpha,self.beta,self.gamma],r)[1:]) for r in range(3)]):
raise ValueError ('Each lattice angle must be less than sum of others')
else:
self.a = self.b = self.c = None
self.alpha = self.beta = self.gamma = None
def __repr__(self):
"""Represent."""
return '\n'.join([f'Crystal family {self.family}']
+ ([] if self.lattice is None else [f'Bravais lattice {self.lattice}']+
list(map(lambda x:f'{x[0]}:{x[1]:.5g}',
zip(['a','b','c','alpha','beta','gamma',],
self.parameters))))
)
def __eq__(self,other):
"""
Equal to other.
Parameters
----------
other : Crystal
Crystal to check for equality.
"""
return self.lattice == other.lattice and \
self.parameters == other.parameters and \
self.family == other.family
@property
def parameters(self):
"""Return lattice parameters a, b, c, alpha, beta, gamma."""
return (self.a,self.b,self.c,self.alpha,self.beta,self.gamma)
@property
def immutable(self):
"""Return immutable lattice parameters."""
_immutable = {
'cubic': {
'b': 1.0,
'c': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
},
'hexagonal': {
'b': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': 2.*np.pi/3.,
},
'tetragonal': {
'b': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
},
'orthorhombic': {
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
},
'monoclinic': {
'alpha': np.pi/2.,
'gamma': np.pi/2.,
},
'triclinic': {}
}
return _immutable[self.family]
@property
def standard_triangle(self):
"""
Corners of the standard triangle.
Notes
-----
Not yet defined for monoclinic.
References
----------
Bases are computed from
>>> basis = {
... 'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,1.]/np.sqrt(2.), # green
... [1.,1.,1.]/np.sqrt(3.)]).T), # blue
... 'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # blue
... 'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [1.,1.,0.]/np.sqrt(2.)]).T), # blue
... 'orthorhombic': np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [0.,1.,0.]]).T), # blue
... }
"""
_basis = {
'cubic': {'improper':np.array([ [-1. , 0. , 1. ],
[ np.sqrt(2.) , -np.sqrt(2.) , 0. ],
[ 0. , np.sqrt(3.) , 0. ] ]),
'proper':np.array([ [ 0. , -1. , 1. ],
[-np.sqrt(2.) , np.sqrt(2.) , 0. ],
[ np.sqrt(3.) , 0. , 0. ] ]),
},
'hexagonal':
{'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -np.sqrt(3.) , 0. ],
[ 0. , 2. , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , np.sqrt(3.) , 0. ],
[ np.sqrt(3.) , -1. , 0. ] ]),
},
'tetragonal':
{'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -1. , 0. ],
[ 0. , np.sqrt(2.) , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , 1. , 0. ],
[ np.sqrt(2.) , 0. , 0. ] ]),
},
'orthorhombic':
{'improper':np.array([ [ 0., 0., 1.],
[ 1., 0., 0.],
[ 0., 1., 0.] ]),
'proper':np.array([ [ 0., 0., 1.],
[-1., 0., 0.],
[ 0., 1., 0.] ]),
}}
return _basis.get(self.family,None)
@property
def ratio(self):
"""Return axes ratios of own lattice."""
_ratio = { 'hexagonal': {'c': np.sqrt(8./3.)}}
return dict(b = self.immutable['b']
if 'b' in self.immutable else
_ratio[self.family]['b'] if self.family in _ratio and 'b' in _ratio[self.family] else None,
c = self.immutable['c']
if 'c' in self.immutable else
_ratio[self.family]['c'] if self.family in _ratio and 'c' in _ratio[self.family] else None,
)
@property
def basis_real(self):
"""
Return orthogonal real space crystal basis.
References
----------
C.T. Young and J.L. Lytton, Journal of Applied Physics 43:1408–1417, 1972
https://doi.org/10.1063/1.1661333
"""
if None in self.parameters:
raise KeyError('missing crystal lattice parameters')
return np.array([
[1,0,0],
[np.cos(self.gamma),np.sin(self.gamma),0],
[np.cos(self.beta),
(np.cos(self.alpha)-np.cos(self.beta)*np.cos(self.gamma)) /np.sin(self.gamma),
np.sqrt(1 - np.cos(self.alpha)**2 - np.cos(self.beta)**2 - np.cos(self.gamma)**2
+ 2 * np.cos(self.alpha) * np.cos(self.beta) * np.cos(self.gamma))/np.sin(self.gamma)],
],dtype=float).T \
* np.array([self.a,self.b,self.c])
@property
def basis_reciprocal(self):
"""Return reciprocal (dual) crystal basis."""
return np.linalg.inv(self.basis_real.T)
def to_lattice(self,*,direction=None,plane=None):
"""
Calculate lattice vector corresponding to crystal frame direction or plane normal.
Parameters
----------
direction|plane : numpy.ndarray of shape (...,3)
Vector along direction or plane normal.
Returns
-------
Miller : numpy.ndarray of shape (...,3)
Lattice vector of direction or plane.
Use util.scale_to_coprime to convert to (integer) Miller indices.
"""
if (direction is not None) ^ (plane is None):
raise KeyError('Specify either "direction" or "plane"')
axis,basis = (np.array(direction),self.basis_reciprocal.T) \
if plane is None else \
(np.array(plane),self.basis_real.T)
return np.einsum('il,...l',basis,axis)
def to_frame(self,*,uvw=None,hkl=None):
"""
Calculate crystal frame vector along lattice direction [uvw] or plane normal (hkl).
Parameters
----------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of crystallographic direction or plane normal.
Returns
-------
vector : numpy.ndarray of shape (...,3) or (N,...,3)
Crystal frame vector (or vectors if with_symmetry) along [uvw] direction or (hkl) plane normal.
"""
if (uvw is not None) ^ (hkl is None):
raise KeyError('Specify either "uvw" or "hkl"')
axis,basis = (np.array(uvw),self.basis_real) \
if hkl is None else \
(np.array(hkl),self.basis_reciprocal)
return np.einsum('il,...l',basis,axis)
def kinematics(self,mode):
"""
Return crystal kinematics systems.
Parameters
----------
mode : {'slip','twin'}
Deformation mode.
Returns
-------
direction_plane : dictionary
Directions and planes of deformation mode families.
"""
_kinematics = {
'cF': {
'slip' :[np.array([
[+0,+1,-1, +1,+1,+1],
[-1,+0,+1, +1,+1,+1],
[+1,-1,+0, +1,+1,+1],
[+0,-1,-1, -1,-1,+1],
[+1,+0,+1, -1,-1,+1],
[-1,+1,+0, -1,-1,+1],
[+0,-1,+1, +1,-1,-1],
[-1,+0,-1, +1,-1,-1],
[+1,+1,+0, +1,-1,-1],
[+0,+1,+1, -1,+1,-1],
[+1,+0,-1, -1,+1,-1],
[-1,-1,+0, -1,+1,-1]]),
np.array([
[+1,+1,+0, +1,-1,+0],
[+1,-1,+0, +1,+1,+0],
[+1,+0,+1, +1,+0,-1],
[+1,+0,-1, +1,+0,+1],
[+0,+1,+1, +0,+1,-1],
[+0,+1,-1, +0,+1,+1]])],
'twin' :[np.array([
[-2, 1, 1, 1, 1, 1],
[ 1,-2, 1, 1, 1, 1],
[ 1, 1,-2, 1, 1, 1],
[ 2,-1, 1, -1,-1, 1],
[-1, 2, 1, -1,-1, 1],
[-1,-1,-2, -1,-1, 1],
[-2,-1,-1, 1,-1,-1],
[ 1, 2,-1, 1,-1,-1],
[ 1,-1, 2, 1,-1,-1],
[ 2, 1,-1, -1, 1,-1],
[-1,-2,-1, -1, 1,-1],
[-1, 1, 2, -1, 1,-1]])]
},
'cI': {
'slip' :[np.array([
[+1,-1,+1, +0,+1,+1],
[-1,-1,+1, +0,+1,+1],
[+1,+1,+1, +0,-1,+1],
[-1,+1,+1, +0,-1,+1],
[-1,+1,+1, +1,+0,+1],
[-1,-1,+1, +1,+0,+1],
[+1,+1,+1, -1,+0,+1],
[+1,-1,+1, -1,+0,+1],
[-1,+1,+1, +1,+1,+0],
[-1,+1,-1, +1,+1,+0],
[+1,+1,+1, -1,+1,+0],
[+1,+1,-1, -1,+1,+0]]),
np.array([
[-1,+1,+1, +2,+1,+1],
[+1,+1,+1, -2,+1,+1],
[+1,+1,-1, +2,-1,+1],
[+1,-1,+1, +2,+1,-1],
[+1,-1,+1, +1,+2,+1],
[+1,+1,-1, -1,+2,+1],
[+1,+1,+1, +1,-2,+1],
[-1,+1,+1, +1,+2,-1],
[+1,+1,-1, +1,+1,+2],
[+1,-1,+1, -1,+1,+2],
[-1,+1,+1, +1,-1,+2],
[+1,+1,+1, +1,+1,-2]]),
np.array([
[+1,+1,-1, +1,+2,+3],
[+1,-1,+1, -1,+2,+3],
[-1,+1,+1, +1,-2,+3],
[+1,+1,+1, +1,+2,-3],
[+1,-1,+1, +1,+3,+2],
[+1,+1,-1, -1,+3,+2],
[+1,+1,+1, +1,-3,+2],
[-1,+1,+1, +1,+3,-2],
[+1,+1,-1, +2,+1,+3],
[+1,-1,+1, -2,+1,+3],
[-1,+1,+1, +2,-1,+3],
[+1,+1,+1, +2,+1,-3],
[+1,-1,+1, +2,+3,+1],
[+1,+1,-1, -2,+3,+1],
[+1,+1,+1, +2,-3,+1],
[-1,+1,+1, +2,+3,-1],
[-1,+1,+1, +3,+1,+2],
[+1,+1,+1, -3,+1,+2],
[+1,+1,-1, +3,-1,+2],
[+1,-1,+1, +3,+1,-2],
[-1,+1,+1, +3,+2,+1],
[+1,+1,+1, -3,+2,+1],
[+1,+1,-1, +3,-2,+1],
[+1,-1,+1, +3,+2,-1]])],
'twin' :[np.array([
[-1, 1, 1, 2, 1, 1],
[ 1, 1, 1, -2, 1, 1],
[ 1, 1,-1, 2,-1, 1],
[ 1,-1, 1, 2, 1,-1],
[ 1,-1, 1, 1, 2, 1],
[ 1, 1,-1, -1, 2, 1],
[ 1, 1, 1, 1,-2, 1],
[-1, 1, 1, 1, 2,-1],
[ 1, 1,-1, 1, 1, 2],
[ 1,-1, 1, -1, 1, 2],
[-1, 1, 1, 1,-1, 2],
[ 1, 1, 1, 1, 1,-2]])]
},
'hP': {
'slip' :[np.array([
[+2,-1,-1,+0, +0,+0,+0,+1],
[-1,+2,-1,+0, +0,+0,+0,+1],
[-1,-1,+2,+0, +0,+0,+0,+1]]),
np.array([
[+2,-1,-1,+0, +0,+1,-1,+0],
[-1,+2,-1,+0, -1,+0,+1,+0],
[-1,-1,+2,+0, +1,-1,+0,+0]]),
np.array([
[-1,+1,+0,+0, +1,+1,-2,+0],
[+0,-1,+1,+0, -2,+1,+1,+0],
[+1,+0,-1,+0, +1,-2,+1,+0]]),
np.array([
[-1,+2,-1,+0, +1,+0,-1,+1],
[-2,+1,+1,+0, +0,+1,-1,+1],
[-1,-1,+2,+0, -1,+1,+0,+1],
[+1,-2,+1,+0, -1,+0,+1,+1],
[+2,-1,-1,+0, +0,-1,+1,+1],
[+1,+1,-2,+0, +1,-1,+0,+1]]),
np.array([
[-2,+1,+1,+3, +1,+0,-1,+1],
[-1,-1,+2,+3, +1,+0,-1,+1],
[-1,-1,+2,+3, +0,+1,-1,+1],
[+1,-2,+1,+3, +0,+1,-1,+1],
[+1,-2,+1,+3, -1,+1,+0,+1],
[+2,-1,-1,+3, -1,+1,+0,+1],
[+2,-1,-1,+3, -1,+0,+1,+1],
[+1,+1,-2,+3, -1,+0,+1,+1],
[+1,+1,-2,+3, +0,-1,+1,+1],
[-1,+2,-1,+3, +0,-1,+1,+1],
[-1,+2,-1,+3, +1,-1,+0,+1],
[-2,+1,+1,+3, +1,-1,+0,+1]]),
np.array([
[-1,-1,+2,+3, +1,+1,-2,+2],
[+1,-2,+1,+3, -1,+2,-1,+2],
[+2,-1,-1,+3, -2,+1,+1,+2],
[+1,+1,-2,+3, -1,-1,+2,+2],
[-1,+2,-1,+3, +1,-2,+1,+2],
[-2,+1,+1,+3, +2,-1,-1,+2]])],
'twin' :[np.array([
[-1, 0, 1, 1, 1, 0,-1, 2], # shear = (3-(c/a)^2)/(sqrt(3) c/a) <-10.1>{10.2}
[ 0,-1, 1, 1, 0, 1,-1, 2],
[ 1,-1, 0, 1, -1, 1, 0, 2],
[ 1, 0,-1, 1, -1, 0, 1, 2],
[ 0, 1,-1, 1, 0,-1, 1, 2],
[-1, 1, 0, 1, 1,-1, 0, 2]]),
np.array([
[-1,-1, 2, 6, 1, 1,-2, 1], # shear = 1/(c/a) <11.6>{-1-1.1}
[ 1,-2, 1, 6, -1, 2,-1, 1],
[ 2,-1,-1, 6, -2, 1, 1, 1],
[ 1, 1,-2, 6, -1,-1, 2, 1],
[-1, 2,-1, 6, 1,-2, 1, 1],
[-2, 1, 1, 6, 2,-1,-1, 1]]),
np.array([
[ 1, 0,-1,-2, 1, 0,-1, 1], # shear = (4(c/a)^2-9)/(4 sqrt(3) c/a) <10.-2>{10.1}
[ 0, 1,-1,-2, 0, 1,-1, 1],
[-1, 1, 0,-2, -1, 1, 0, 1],
[-1, 0, 1,-2, -1, 0, 1, 1],
[ 0,-1, 1,-2, 0,-1, 1, 1],
[ 1,-1, 0,-2, 1,-1, 0, 1]]),
np.array([
[ 1, 1,-2,-3, 1, 1,-2, 2], # shear = 2((c/a)^2-2)/(3 c/a) <11.-3>{11.2}
[-1, 2,-1,-3, -1, 2,-1, 2],
[-2, 1, 1,-3, -2, 1, 1, 2],
[-1,-1, 2,-3, -1,-1, 2, 2],
[ 1,-2, 1,-3, 1,-2, 1, 2],
[ 2,-1,-1,-3, 2,-1,-1, 2]])]
},
}
master = _kinematics[self.lattice][mode]
if self.lattice == 'hP':
return {'direction':[util.Bravais_to_Miller(uvtw=m[:,0:4]) for m in master],
'plane': [util.Bravais_to_Miller(hkil=m[:,4:8]) for m in master]}
else:
return {'direction':[m[:,0:3] for m in master],
'plane': [m[:,3:6] for m in master]}
def relation_operations(self,model):
"""
Crystallographic orientation relationships for phase transformations.
Parameters
----------
model : str
Name of orientation relationship.
Returns
-------
operations : (string, damask.Rotation)
Resulting lattice and rotations characterizing the orientation relationship.
References
----------
S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
https://doi.org/10.1016/j.jallcom.2012.02.004
K. Kitahara et al., Acta Materialia 54(5):1279-1288, 2006
https://doi.org/10.1016/j.actamat.2005.11.001
Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
https://doi.org/10.1107/S0021889805038276
H. Kitahara et al., Materials Characterization 54(4-5):378-386, 2005
https://doi.org/10.1016/j.matchar.2004.12.015
Y. He et al., Acta Materialia 53(4):1179-1190, 2005
https://doi.org/10.1016/j.actamat.2004.11.021
"""
_orientation_relationships = {
'KS': {
'cF' : np.array([
[[-1, 0, 1],[ 1, 1, 1]],
[[-1, 0, 1],[ 1, 1, 1]],
[[ 0, 1,-1],[ 1, 1, 1]],
[[ 0, 1,-1],[ 1, 1, 1]],
[[ 1,-1, 0],[ 1, 1, 1]],
[[ 1,-1, 0],[ 1, 1, 1]],
[[ 1, 0,-1],[ 1,-1, 1]],
[[ 1, 0,-1],[ 1,-1, 1]],
[[-1,-1, 0],[ 1,-1, 1]],
[[-1,-1, 0],[ 1,-1, 1]],
[[ 0, 1, 1],[ 1,-1, 1]],
[[ 0, 1, 1],[ 1,-1, 1]],
[[ 0,-1, 1],[-1, 1, 1]],
[[ 0,-1, 1],[-1, 1, 1]],
[[-1, 0,-1],[-1, 1, 1]],
[[-1, 0,-1],[-1, 1, 1]],
[[ 1, 1, 0],[-1, 1, 1]],
[[ 1, 1, 0],[-1, 1, 1]],
[[-1, 1, 0],[ 1, 1,-1]],
[[-1, 1, 0],[ 1, 1,-1]],
[[ 0,-1,-1],[ 1, 1,-1]],
[[ 0,-1,-1],[ 1, 1,-1]],
[[ 1, 0, 1],[ 1, 1,-1]],
[[ 1, 0, 1],[ 1, 1,-1]],
],dtype=float),
'cI' : np.array([
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
[[-1,-1, 1],[ 0, 1, 1]],
[[-1, 1,-1],[ 0, 1, 1]],
],dtype=float),
},
'GT': {
'cF' : np.array([
[[ -5,-12, 17],[ 1, 1, 1]],
[[ 17, -5,-12],[ 1, 1, 1]],
[[-12, 17, -5],[ 1, 1, 1]],
[[ 5, 12, 17],[ -1, -1, 1]],
[[-17, 5,-12],[ -1, -1, 1]],
[[ 12,-17, -5],[ -1, -1, 1]],
[[ -5, 12,-17],[ -1, 1, 1]],
[[ 17, 5, 12],[ -1, 1, 1]],
[[-12,-17, 5],[ -1, 1, 1]],
[[ 5,-12,-17],[ 1, -1, 1]],
[[-17, -5, 12],[ 1, -1, 1]],
[[ 12, 17, 5],[ 1, -1, 1]],
[[ -5, 17,-12],[ 1, 1, 1]],
[[-12, -5, 17],[ 1, 1, 1]],
[[ 17,-12, -5],[ 1, 1, 1]],
[[ 5,-17,-12],[ -1, -1, 1]],
[[ 12, 5, 17],[ -1, -1, 1]],
[[-17, 12, -5],[ -1, -1, 1]],
[[ -5,-17, 12],[ -1, 1, 1]],
[[-12, 5,-17],[ -1, 1, 1]],
[[ 17, 12, 5],[ -1, 1, 1]],
[[ 5, 17, 12],[ 1, -1, 1]],
[[ 12, -5,-17],[ 1, -1, 1]],
[[-17,-12, 5],[ 1, -1, 1]],
],dtype=float),
'cI' : np.array([
[[-17, -7, 17],[ 1, 0, 1]],
[[ 17,-17, -7],[ 1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[-17, 17, -7],[ -1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[ 17, 17, 7],[ -1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[-17,-17, 7],[ 1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 17, -7],[ 1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[ 17,-17, -7],[ -1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[-17,-17, 7],[ -1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[ 17, 17, 7],[ 1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, -7, 17],[ 1, 0, 1]],
],dtype=float),
},
'GT_prime': {
'cF' : np.array([
[[ 0, 1, -1],[ 7, 17, 17]],
[[ -1, 0, 1],[ 17, 7, 17]],
[[ 1, -1, 0],[ 17, 17, 7]],
[[ 0, -1, -1],[ -7,-17, 17]],
[[ 1, 0, 1],[-17, -7, 17]],
[[ 1, -1, 0],[-17,-17, 7]],
[[ 0, 1, -1],[ 7,-17,-17]],
[[ 1, 0, 1],[ 17, -7,-17]],
[[ -1, -1, 0],[ 17,-17, -7]],
[[ 0, -1, -1],[ -7, 17,-17]],
[[ -1, 0, 1],[-17, 7,-17]],
[[ -1, -1, 0],[-17, 17, -7]],
[[ 0, -1, 1],[ 7, 17, 17]],
[[ 1, 0, -1],[ 17, 7, 17]],
[[ -1, 1, 0],[ 17, 17, 7]],
[[ 0, 1, 1],[ -7,-17, 17]],
[[ -1, 0, -1],[-17, -7, 17]],
[[ -1, 1, 0],[-17,-17, 7]],
[[ 0, -1, 1],[ 7,-17,-17]],
[[ -1, 0, -1],[ 17, -7,-17]],
[[ 1, 1, 0],[ 17,-17, -7]],
[[ 0, 1, 1],[ -7, 17,-17]],
[[ 1, 0, -1],[-17, 7,-17]],
[[ 1, 1, 0],[-17, 17, -7]],
],dtype=float),
'cI' : np.array([
[[ 1, 1, -1],[ 12, 5, 17]],
[[ -1, 1, 1],[ 17, 12, 5]],
[[ 1, -1, 1],[ 5, 17, 12]],
[[ -1, -1, -1],[-12, -5, 17]],
[[ 1, -1, 1],[-17,-12, 5]],
[[ 1, -1, -1],[ -5,-17, 12]],
[[ -1, 1, -1],[ 12, -5,-17]],
[[ 1, 1, 1],[ 17,-12, -5]],
[[ -1, -1, 1],[ 5,-17,-12]],
[[ 1, -1, -1],[-12, 5,-17]],
[[ -1, -1, 1],[-17, 12, -5]],
[[ -1, -1, -1],[ -5, 17,-12]],
[[ 1, -1, 1],[ 12, 17, 5]],
[[ 1, 1, -1],[ 5, 12, 17]],
[[ -1, 1, 1],[ 17, 5, 12]],
[[ -1, 1, 1],[-12,-17, 5]],
[[ -1, -1, -1],[ -5,-12, 17]],
[[ -1, 1, -1],[-17, -5, 12]],
[[ -1, -1, 1],[ 12,-17, -5]],
[[ -1, 1, -1],[ 5,-12,-17]],
[[ 1, 1, 1],[ 17, -5,-12]],
[[ 1, 1, 1],[-12, 17, -5]],
[[ 1, -1, -1],[ -5, 12,-17]],
[[ 1, 1, -1],[-17, 5,-12]],
],dtype=float),
},
'NW': {
'cF' : np.array([
[[ 2, -1, -1],[ 1, 1, 1]],
[[ -1, 2, -1],[ 1, 1, 1]],
[[ -1, -1, 2],[ 1, 1, 1]],
[[ -2, -1, -1],[ -1, 1, 1]],
[[ 1, 2, -1],[ -1, 1, 1]],
[[ 1, -1, 2],[ -1, 1, 1]],
[[ 2, 1, -1],[ 1, -1, 1]],
[[ -1, -2, -1],[ 1, -1, 1]],
[[ -1, 1, 2],[ 1, -1, 1]],
[[ 2, -1, 1],[ -1, -1, 1]],
[[ -1, 2, 1],[ -1, -1, 1]],
[[ -1, -1, -2],[ -1, -1, 1]],
],dtype=float),
'cI' : np.array([
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
],dtype=float),
},
'Pitsch': {
'cF' : np.array([
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 0, 1, -1],[ 1, 0, 0]],
[[ -1, 0, 1],[ 0, 1, 0]],
[[ 1, -1, 0],[ 0, 0, 1]],
[[ 1, 0, -1],[ 0, 1, 0]],
[[ -1, 1, 0],[ 0, 0, 1]],
[[ 0, -1, 1],[ 1, 0, 0]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : np.array([
[[ 1, -1, 1],[ -1, 0, 1]],
[[ 1, 1, -1],[ 1, -1, 0]],
[[ -1, 1, 1],[ 0, 1, -1]],
[[ -1, 1, -1],[ 0, -1, -1]],
[[ -1, -1, 1],[ -1, 0, -1]],
[[ 1, -1, -1],[ -1, -1, 0]],
[[ 1, -1, -1],[ -1, 0, -1]],
[[ -1, 1, -1],[ -1, -1, 0]],
[[ -1, -1, 1],[ 0, -1, -1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, -1, 1],[ 1, 0, -1]],
[[ 1, 1, -1],[ -1, 1, 0]],
],dtype=float),
},
'Bain': {
'cF' : np.array([
[[ 0, 1, 0],[ 1, 0, 0]],
[[ 0, 0, 1],[ 0, 1, 0]],
[[ 1, 0, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : np.array([
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
},
'Burgers' : {
'cI' : np.array([
[[ -1, 1, 1],[ 1, 1, 0]],
[[ -1, 1, -1],[ 1, 1, 0]],
[[ 1, 1, 1],[ 1, -1, 0]],
[[ 1, 1, -1],[ 1, -1, 0]],
[[ 1, 1, -1],[ 1, 0, 1]],
[[ -1, 1, 1],[ 1, 0, 1]],
[[ 1, 1, 1],[ -1, 0, 1]],
[[ 1, -1, 1],[ -1, 0, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ 1, 1, -1],[ 0, 1, 1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, 1, 1],[ 0, -1, 1]],
],dtype=float),
'hP' : np.array([
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
],dtype=float),
},
}
orientation_relationships = {k:v for k,v in _orientation_relationships.items() if self.lattice in v}
if model not in orientation_relationships:
raise KeyError(f'unknown orientation relationship "{model}"')
r = orientation_relationships[model]
sl = self.lattice
ol = (set(r)-{sl}).pop()
m = r[sl]
o = r[ol]
p_,_p = np.zeros(m.shape[:-1]+(3,)),np.zeros(o.shape[:-1]+(3,))
p_[...,0,:] = m[...,0,:] if m.shape[-1] == 3 else util.Bravais_to_Miller(uvtw=m[...,0,0:4])
p_[...,1,:] = m[...,1,:] if m.shape[-1] == 3 else util.Bravais_to_Miller(hkil=m[...,1,0:4])
_p[...,0,:] = o[...,0,:] if o.shape[-1] == 3 else util.Bravais_to_Miller(uvtw=o[...,0,0:4])
_p[...,1,:] = o[...,1,:] if o.shape[-1] == 3 else util.Bravais_to_Miller(hkil=o[...,1,0:4])
return (ol,Rotation.from_parallel(p_,_p))

824
python/damask/_orientation.py
View File

@ -1,11 +1,12 @@
import inspect
import copy
import numpy as np
from . import Rotation
from . import Crystal
from . import util
from . import tensor
from . import lattice as lattice_
lattice_symmetries = {
@ -30,10 +31,12 @@ lattice_symmetries = {
}
_parameter_doc = \
"""lattice : str
Either a crystal family out of {triclinic, monoclinic, orthorhombic, tetragonal, hexagonal, cubic}
or a Bravais lattice out of {aP, mP, mS, oP, oS, oI, oF, tP, tI, hP, cP, cI, cF}.
When specifying a Bravais lattice, additional lattice parameters might be required.
"""
family : {'triclinic', 'monoclinic', 'orthorhombic', 'tetragonal', 'hexagonal', 'cubic'}, optional.
Name of the crystal family.
Will be infered if 'lattice' is given.
lattice : {'aP', 'mP', 'mS', 'oP', 'oS', 'oI', 'oF', 'tP', 'tI', 'hP', 'cP', 'cI', 'cF'}, optional.
Name of the Bravais lattice in Pearson notation.
a : float, optional
Length of lattice parameter 'a'.
b : float, optional
@ -52,7 +55,7 @@ _parameter_doc = \
"""
class Orientation(Rotation):
class Orientation(Rotation,Crystal):
"""
Representation of crystallographic orientation as combination of rotation and either crystal family or Bravais lattice.
@ -73,7 +76,7 @@ class Orientation(Rotation):
- triclinic
- aP : primitive
- monoclininic
- monoclinic
- mP : primitive
- mS : base-centered
@ -104,13 +107,15 @@ class Orientation(Rotation):
--------
An array of 3 x 5 random orientations reduced to the fundamental zone of tetragonal symmetry:
>>> damask.Orientation.from_random(shape=(3,5),lattice='tetragonal').reduced
>>> import damask
>>> o=damask.Orientation.from_random(shape=(3,5),family='tetragonal').reduced
"""
@util.extend_docstring(_parameter_doc)
def __init__(self,
rotation = None,
rotation = np.array([1.0,0.0,0.0,0.0]), *,
family = None,
lattice = None,
a = None,b = None,c = None,
alpha = None,beta = None,gamma = None,
@ -126,79 +131,23 @@ class Orientation(Rotation):
Defaults to no rotation.
"""
Rotation.__init__(self) if rotation is None else Rotation.__init__(self,rotation=rotation)
if lattice in lattice_symmetries:
self.family = lattice_symmetries[lattice]
self.lattice = lattice
self.a = 1 if a is None else a
self.b = b
self.c = c
self.a = float(self.a) if self.a is not None else \
(self.b / self.ratio['b'] if self.b is not None and self.ratio['b'] is not None else
self.c / self.ratio['c'] if self.c is not None and self.ratio['c'] is not None else None)
self.b = float(self.b) if self.b is not None else \
(self.a * self.ratio['b'] if self.a is not None and self.ratio['b'] is not None else
self.c / self.ratio['c'] * self.ratio['b']
if self.c is not None and self.ratio['b'] is not None and self.ratio['c'] is not None else None)
self.c = float(self.c) if self.c is not None else \
(self.a * self.ratio['c'] if self.a is not None and self.ratio['c'] is not None else
self.b / self.ratio['b'] * self.ratio['c']
if self.c is not None and self.ratio['b'] is not None and self.ratio['c'] is not None else None)
self.alpha = np.radians(alpha) if degrees and alpha is not None else alpha
self.beta = np.radians(beta) if degrees and beta is not None else beta
self.gamma = np.radians(gamma) if degrees and gamma is not None else gamma
if self.alpha is None and 'alpha' in self.immutable: self.alpha = self.immutable['alpha']
if self.beta is None and 'beta' in self.immutable: self.beta = self.immutable['beta']
if self.gamma is None and 'gamma' in self.immutable: self.gamma = self.immutable['gamma']
if \
(self.a is None) \
or (self.b is None or ('b' in self.immutable and self.b != self.immutable['b'] * self.a)) \
or (self.c is None or ('c' in self.immutable and self.c != self.immutable['c'] * self.b)) \
or (self.alpha is None or ('alpha' in self.immutable and self.alpha != self.immutable['alpha'])) \
or (self.beta is None or ( 'beta' in self.immutable and self.beta != self.immutable['beta'])) \
or (self.gamma is None or ('gamma' in self.immutable and self.gamma != self.immutable['gamma'])):
raise ValueError (f'Incompatible parameters {self.parameters} for crystal family {self.family}')
if np.any(np.array([self.alpha,self.beta,self.gamma]) <= 0):
raise ValueError ('Lattice angles must be positive')
if np.any([np.roll([self.alpha,self.beta,self.gamma],r)[0]
> np.sum(np.roll([self.alpha,self.beta,self.gamma],r)[1:]) for r in range(3)]):
raise ValueError ('Each lattice angle must be less than sum of others')
elif lattice in set(lattice_symmetries.values()):
self.family = lattice
self.lattice = None
self.a = self.b = self.c = None
self.alpha = self.beta = self.gamma = None
else:
raise KeyError(f'Lattice "{lattice}" is unknown')
Rotation.__init__(self,rotation)
Crystal.__init__(self,family=family, lattice=lattice,
a=a,b=b,c=c, alpha=alpha,beta=beta,gamma=gamma, degrees=degrees)
def __repr__(self):
"""Represent."""
return '\n'.join(([] if self.lattice is None else [f'Bravais lattice {self.lattice}'])
+ ([f'Crystal family {self.family}'])
+ [super().__repr__()])
return '\n'.join([Crystal.__repr__(self),
Rotation.__repr__(self)])
def __copy__(self,**kwargs):
def __copy__(self,rotation=None):
"""Create deep copy."""
return self.__class__(rotation=kwargs['rotation'] if 'rotation' in kwargs else self.quaternion,
lattice =kwargs['lattice'] if 'lattice' in kwargs else self.lattice
if self.lattice is not None else self.family,
a =kwargs['a'] if 'a' in kwargs else self.a,
b =kwargs['b'] if 'b' in kwargs else self.b,
c =kwargs['c'] if 'c' in kwargs else self.c,
alpha =kwargs['alpha'] if 'alpha' in kwargs else self.alpha,
beta =kwargs['beta'] if 'beta' in kwargs else self.beta,
gamma =kwargs['gamma'] if 'gamma' in kwargs else self.gamma,
degrees =kwargs['degrees'] if 'degrees' in kwargs else None,
)
dup = copy.deepcopy(self)
if rotation is not None:
dup.quaternion = Orientation(rotation,family='cubic').quaternion
return dup
copy = __copy__
@ -213,8 +162,9 @@ class Orientation(Rotation):
Orientation to check for equality.
"""
matching_type = all([hasattr(other,attr) and getattr(self,attr) == getattr(other,attr)
for attr in ['family','lattice','parameters']])
matching_type = self.family == other.family and \
self.lattice == other.lattice and \
self.parameters == other.parameters
return np.logical_and(matching_type,super(self.__class__,self.reduced).__eq__(other.reduced))
def __ne__(self,other):
@ -251,8 +201,9 @@ class Orientation(Rotation):
Mask indicating where corresponding orientations are close.
"""
matching_type = all([hasattr(other,attr) and getattr(self,attr) == getattr(other,attr)
for attr in ['family','lattice','parameters']])
matching_type = self.family == other.family and \
self.lattice == other.lattice and \
self.parameters == other.parameters
return np.logical_and(matching_type,super(self.__class__,self.reduced).isclose(other.reduced))
@ -431,84 +382,6 @@ class Orientation(Rotation):
return o.copy(rotation=Rotation.from_matrix(tensor.transpose(om/np.linalg.norm(om,axis=-1,keepdims=True))))
@property
def symmetry_operations(self):
"""Symmetry operations as Rotations."""
if self.family == 'cubic':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2) ],
[ 0.0, 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, -0.5 ],
[-0.5, 0.5, -0.5, 0.5 ],
[-0.5, -0.5, 0.5, 0.5 ],
[-0.5, -0.5, 0.5, -0.5 ],
[-0.5, -0.5, -0.5, 0.5 ],
[-0.5, 0.5, -0.5, -0.5 ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0, 0.0 ],
[-0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0, 0.0 ],
]
elif self.family == 'hexagonal':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[-0.5*np.sqrt(3), 0.0, 0.0, -0.5 ],
[ 0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[ 0.0, 0.0, 0.0, 1.0 ],
[-0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[-0.5*np.sqrt(3), 0.0, 0.0, 0.5 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, -0.5*np.sqrt(3), 0.5, 0.0 ],
[ 0.0, 0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, -0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.5*np.sqrt(3), 0.5, 0.0 ],
]
elif self.family == 'tetragonal':
sym_quats = [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
]
elif self.family == 'orthorhombic':
sym_quats = [
[ 1.0,0.0,0.0,0.0 ],
[ 0.0,1.0,0.0,0.0 ],
[ 0.0,0.0,1.0,0.0 ],
[ 0.0,0.0,0.0,1.0 ],
]
elif self.family == 'monoclinic':
sym_quats = [
[ 1.0,0.0,0.0,0.0 ],
[ 0.0,0.0,1.0,0.0 ],
]
elif self.family == 'triclinic':
sym_quats = [
[ 1.0,0.0,0.0,0.0 ],
]
else:
raise KeyError(f'unknown crystal family "{self.family}"')
return Rotation.from_quaternion(sym_quats,accept_homomorph=True)
@property
def equivalent(self):
"""
@ -518,7 +391,8 @@ class Orientation(Rotation):
is added to the left of the Rotation array.
"""
o = self.symmetry_operations.broadcast_to(self.symmetry_operations.shape+self.shape,mode='right')
sym_ops = self.symmetry_operations
o = sym_ops.broadcast_to(sym_ops.shape+self.shape,mode='right')
return self.copy(rotation=o*Rotation(self.quaternion).broadcast_to(o.shape,mode='left'))
@ -619,381 +493,6 @@ class Orientation(Rotation):
return np.ones_like(rho[...,0],dtype=bool)
def relation_operations(self,model,return_lattice=False):
"""
Crystallographic orientation relationships for phase transformations.
Parameters
----------
model : str
Name of orientation relationship.
return_lattice : bool, optional
Return the target lattice in addition.
Returns
-------
operations : Rotations
Rotations characterizing the orientation relationship.
References
----------
S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
https://doi.org/10.1016/j.jallcom.2012.02.004
K. Kitahara et al., Acta Materialia 54(5):1279-1288, 2006
https://doi.org/10.1016/j.actamat.2005.11.001
Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
https://doi.org/10.1107/S0021889805038276
H. Kitahara et al., Materials Characterization 54(4-5):378-386, 2005
https://doi.org/10.1016/j.matchar.2004.12.015
Y. He et al., Acta Materialia 53(4):1179-1190, 2005
https://doi.org/10.1016/j.actamat.2004.11.021
"""
if model not in lattice_.relations:
raise KeyError(f'unknown orientation relationship "{model}"')
r = lattice_.relations[model]
if self.lattice not in r:
raise KeyError(f'relationship "{model}" not supported for lattice "{self.lattice}"')
sl = self.lattice
ol = (set(r)-{sl}).pop()
m = r[sl]
o = r[ol]
p_,_p = np.zeros(m.shape[:-1]+(3,)),np.zeros(o.shape[:-1]+(3,))
p_[...,0,:] = m[...,0,:] if m.shape[-1] == 3 else lattice_.Bravais_to_Miller(uvtw=m[...,0,0:4])
p_[...,1,:] = m[...,1,:] if m.shape[-1] == 3 else lattice_.Bravais_to_Miller(hkil=m[...,1,0:4])
_p[...,0,:] = o[...,0,:] if o.shape[-1] == 3 else lattice_.Bravais_to_Miller(uvtw=o[...,0,0:4])
_p[...,1,:] = o[...,1,:] if o.shape[-1] == 3 else lattice_.Bravais_to_Miller(hkil=o[...,1,0:4])
return (Rotation.from_parallel(p_,_p),ol) \
if return_lattice else \
Rotation.from_parallel(p_,_p)
def related(self,model):
"""
Orientations derived from the given relationship.
One dimension (length according to number of related orientations)
is added to the left of the Rotation array.
"""
o,lattice = self.relation_operations(model,return_lattice=True)
target = Orientation(lattice=lattice)
o = o.broadcast_to(o.shape+self.shape,mode='right')
return self.copy(rotation=o*Rotation(self.quaternion).broadcast_to(o.shape,mode='left'),
lattice=lattice,
b = self.b if target.ratio['b'] is None else self.a*target.ratio['b'],
c = self.c if target.ratio['c'] is None else self.a*target.ratio['c'],
alpha = None if 'alpha' in target.immutable else self.alpha,
beta = None if 'beta' in target.immutable else self.beta,
gamma = None if 'gamma' in target.immutable else self.gamma,
)
@property
def parameters(self):
"""Return lattice parameters a, b, c, alpha, beta, gamma."""
return (self.a,self.b,self.c,self.alpha,self.beta,self.gamma)
@property
def immutable(self):
"""Return immutable parameters of own lattice."""
if self.family == 'triclinic':
return {}
if self.family == 'monoclinic':
return {
'alpha': np.pi/2.,
'gamma': np.pi/2.,
}
if self.family == 'orthorhombic':
return {
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
}
if self.family == 'tetragonal':
return {
'b': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
}
if self.family == 'hexagonal':
return {
'b': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': 2.*np.pi/3.,
}
if self.family == 'cubic':
return {
'b': 1.0,
'c': 1.0,
'alpha': np.pi/2.,
'beta': np.pi/2.,
'gamma': np.pi/2.,
}
@property
def ratio(self):
"""Return axes ratios of own lattice."""
_ratio = { 'hexagonal': {'c': np.sqrt(8./3.)}}
return dict(b = self.immutable['b']
if 'b' in self.immutable else
_ratio[self.family]['b'] if self.family in _ratio and 'b' in _ratio[self.family] else None,
c = self.immutable['c']
if 'c' in self.immutable else
_ratio[self.family]['c'] if self.family in _ratio and 'c' in _ratio[self.family] else None,
)
@property
def basis_real(self):
"""
Calculate orthogonal real space crystal basis.
References
----------
C.T. Young and J.L. Lytton, Journal of Applied Physics 43:1408–1417, 1972
https://doi.org/10.1063/1.1661333
"""
if None in self.parameters:
raise KeyError('missing crystal lattice parameters')
return np.array([
[1,0,0],
[np.cos(self.gamma),np.sin(self.gamma),0],
[np.cos(self.beta),
(np.cos(self.alpha)-np.cos(self.beta)*np.cos(self.gamma)) /np.sin(self.gamma),
np.sqrt(1 - np.cos(self.alpha)**2 - np.cos(self.beta)**2 - np.cos(self.gamma)**2
+ 2 * np.cos(self.alpha) * np.cos(self.beta) * np.cos(self.gamma))/np.sin(self.gamma)],
],dtype=float).T \
* np.array([self.a,self.b,self.c])
@property
def basis_reciprocal(self):
"""Calculate reciprocal (dual) crystal basis."""
return np.linalg.inv(self.basis_real.T)
def in_SST(self,vector,proper=False):
"""
Check whether given crystal frame vector falls into standard stereographic triangle of own symmetry.
Parameters
----------
vector : numpy.ndarray of shape (...,3)
Vector to check.
proper : bool, optional
Consider only vectors with z >= 0, hence combine two neighboring SSTs.
Defaults to False.
Returns
-------
in : numpy.ndarray of shape (...)
Boolean array indicating whether vector falls into SST.
References
----------
Bases are computed from
>>> basis = {
... 'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,1.]/np.sqrt(2.), # green
... [1.,1.,1.]/np.sqrt(3.)]).T), # blue
... 'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # blue
... 'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [1.,1.,0.]/np.sqrt(2.)]).T), # blue
... 'orthorhombic': np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [0.,1.,0.]]).T), # blue
... }
"""
if not isinstance(vector,np.ndarray) or vector.shape[-1] != 3:
raise ValueError('input is not a field of three-dimensional vectors')
if self.family == 'cubic':
basis = {'improper':np.array([ [-1. , 0. , 1. ],
[ np.sqrt(2.) , -np.sqrt(2.) , 0. ],
[ 0. , np.sqrt(3.) , 0. ] ]),
'proper':np.array([ [ 0. , -1. , 1. ],
[-np.sqrt(2.) , np.sqrt(2.) , 0. ],
[ np.sqrt(3.) , 0. , 0. ] ]),
}
elif self.family == 'hexagonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -np.sqrt(3.) , 0. ],
[ 0. , 2. , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , np.sqrt(3.) , 0. ],
[ np.sqrt(3.) , -1. , 0. ] ]),
}
elif self.family == 'tetragonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -1. , 0. ],
[ 0. , np.sqrt(2.) , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , 1. , 0. ],
[ np.sqrt(2.) , 0. , 0. ] ]),
}
elif self.family == 'orthorhombic':
basis = {'improper':np.array([ [ 0., 0., 1.],
[ 1., 0., 0.],
[ 0., 1., 0.] ]),
'proper':np.array([ [ 0., 0., 1.],
[-1., 0., 0.],
[ 0., 1., 0.] ]),
}
else: # direct exit for unspecified symmetry
return np.ones_like(vector[...,0],bool)
if proper:
components_proper = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['proper'], vector.shape+(3,)),
vector), 12)
components_improper = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['improper'], vector.shape+(3,)),
vector), 12)
return np.all(components_proper >= 0.0,axis=-1) \
| np.all(components_improper >= 0.0,axis=-1)
else:
components = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['improper'], vector.shape+(3,)),
np.block([vector[...,:2],np.abs(vector[...,2:3])])), 12)
return np.all(components >= 0.0,axis=-1)
def IPF_color(self,vector,in_SST=True,proper=False):
"""
Map vector to RGB color within standard stereographic triangle of own symmetry.
Parameters
----------
vector : numpy.ndarray of shape (...,3)
Vector to colorize.
in_SST : bool, optional
Consider symmetrically equivalent orientations such that poles are located in SST.
Defaults to True.
proper : bool, optional
Consider only vectors with z >= 0, hence combine two neighboring SSTs (with mirrored colors).
Defaults to False.
Returns
-------
rgb : numpy.ndarray of shape (...,3)
RGB array of IPF colors.
Examples
--------
Inverse pole figure color of the e_3 direction for a crystal in "Cube" orientation with cubic symmetry:
>>> o = damask.Orientation(lattice='cubic')
>>> o.IPF_color([0,0,1])
array([1., 0., 0.])
References
----------
Bases are computed from
>>> basis = {
... 'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,1.]/np.sqrt(2.), # green
... [1.,1.,1.]/np.sqrt(3.)]).T), # blue
... 'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # blue
... 'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [1.,1.,0.]/np.sqrt(2.)]).T), # blue
... 'orthorhombic': np.linalg.inv(np.array([[0.,0.,1.], # direction of red
... [1.,0.,0.], # green
... [0.,1.,0.]]).T), # blue
... }
"""
if np.array(vector).shape[-1] != 3:
raise ValueError('input is not a field of three-dimensional vectors')
vector_ = self.to_SST(vector,proper) if in_SST else \
self @ np.broadcast_to(vector,self.shape+(3,))
if self.family == 'cubic':
basis = {'improper':np.array([ [-1. , 0. , 1. ],
[ np.sqrt(2.) , -np.sqrt(2.) , 0. ],
[ 0. , np.sqrt(3.) , 0. ] ]),
'proper':np.array([ [ 0. , -1. , 1. ],
[-np.sqrt(2.) , np.sqrt(2.) , 0. ],
[ np.sqrt(3.) , 0. , 0. ] ]),
}
elif self.family == 'hexagonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -np.sqrt(3.) , 0. ],
[ 0. , 2. , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , np.sqrt(3.) , 0. ],
[ np.sqrt(3.) , -1. , 0. ] ]),
}
elif self.family == 'tetragonal':
basis = {'improper':np.array([ [ 0. , 0. , 1. ],
[ 1. , -1. , 0. ],
[ 0. , np.sqrt(2.) , 0. ] ]),
'proper':np.array([ [ 0. , 0. , 1. ],
[-1. , 1. , 0. ],
[ np.sqrt(2.) , 0. , 0. ] ]),
}
elif self.family == 'orthorhombic':
basis = {'improper':np.array([ [ 0., 0., 1.],
[ 1., 0., 0.],
[ 0., 1., 0.] ]),
'proper':np.array([ [ 0., 0., 1.],
[-1., 0., 0.],
[ 0., 1., 0.] ]),
}
else: # direct exit for unspecified symmetry
return np.zeros_like(vector_)
if proper:
components_proper = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['proper'], vector_.shape+(3,)),
vector_), 12)
components_improper = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['improper'], vector_.shape+(3,)),
vector_), 12)
in_SST = np.all(components_proper >= 0.0,axis=-1) \
| np.all(components_improper >= 0.0,axis=-1)
components = np.where((in_SST & np.all(components_proper >= 0.0,axis=-1))[...,np.newaxis],
components_proper,components_improper)
else:
components = np.around(np.einsum('...ji,...i',
np.broadcast_to(basis['improper'], vector_.shape+(3,)),
np.block([vector_[...,:2],np.abs(vector_[...,2:3])])), 12)
in_SST = np.all(components >= 0.0,axis=-1)
with np.errstate(invalid='ignore',divide='ignore'):
rgb = (components/np.linalg.norm(components,axis=-1,keepdims=True))**0.5 # smoothen color ramps
rgb = np.clip(rgb,0.,1.) # clip intensity
rgb /= np.max(rgb,axis=-1,keepdims=True) # normalize to (HS)V = 1
rgb[np.broadcast_to(~in_SST[...,np.newaxis],rgb.shape)] = 0.0
return rgb
def disorientation(self,other,return_operators=False):
"""
Calculate disorientation between myself and given other orientation.
@ -1148,57 +647,185 @@ class Orientation(Rotation):
)
def to_lattice(self,*,direction=None,plane=None):
def in_SST(self,vector,proper=False):
"""
Calculate lattice vector corresponding to crystal frame direction or plane normal.
Check whether given crystal frame vector falls into standard stereographic triangle of own symmetry.
Parameters
----------
direction|normal : numpy.ndarray of shape (...,3)
Vector along direction or plane normal.
vector : numpy.ndarray of shape (...,3)
Vector to check.
proper : bool, optional
Consider only vectors with z >= 0, hence combine two neighboring SSTs.
Defaults to False.
Returns
-------
Miller : numpy.ndarray of shape (...,3)
lattice vector of direction or plane.
Use util.scale_to_coprime to convert to (integer) Miller indices.
in : numpy.ndarray of shape (...)
Boolean array indicating whether vector falls into SST.
"""
if (direction is not None) ^ (plane is None):
raise KeyError('specify either "direction" or "plane"')
axis,basis = (np.array(direction),self.basis_reciprocal.T) \
if plane is None else \
(np.array(plane),self.basis_real.T)
return np.einsum('il,...l',basis,axis)
if not isinstance(vector,np.ndarray) or vector.shape[-1] != 3:
raise ValueError('input is not a field of three-dimensional vectors')
if self.standard_triangle is None: # direct exit for no symmetry
return np.ones_like(vector[...,0],bool)
if proper:
components_proper = np.around(np.einsum('...ji,...i',
np.broadcast_to(self.standard_triangle['proper'], vector.shape+(3,)),
vector), 12)
components_improper = np.around(np.einsum('...ji,...i',
np.broadcast_to(self.standard_triangle['improper'], vector.shape+(3,)),
vector), 12)
return np.all(components_proper >= 0.0,axis=-1) \
| np.all(components_improper >= 0.0,axis=-1)
else:
components = np.around(np.einsum('...ji,...i',
np.broadcast_to(self.standard_triangle['improper'], vector.shape+(3,)),
np.block([vector[...,:2],np.abs(vector[...,2:3])])), 12)
return np.all(components >= 0.0,axis=-1)
def to_frame(self,*,uvw=None,hkl=None,with_symmetry=False):
def IPF_color(self,vector,in_SST=True,proper=False):
"""
Calculate crystal frame vector along lattice direction [uvw] or plane normal (hkl).
Map vector to RGB color within standard stereographic triangle of own symmetry.
Parameters
----------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of crystallographic direction or plane normal.
with_symmetry : bool, optional
Calculate all N symmetrically equivalent vectors.
vector : numpy.ndarray of shape (...,3)
Vector to colorize.
in_SST : bool, optional
Consider symmetrically equivalent orientations such that poles are located in SST.
Defaults to True.
proper : bool, optional
Consider only vectors with z >= 0, hence combine two neighboring SSTs (with mirrored colors).
Defaults to False.
Returns
-------
vector : numpy.ndarray of shape (...,3) or (N,...,3)
Crystal frame vector (or vectors if with_symmetry) along [uvw] direction or (hkl) plane normal.
rgb : numpy.ndarray of shape (...,3)
RGB array of IPF colors.
Examples
--------
Inverse pole figure color of the e_3 direction for a crystal in "Cube" orientation with cubic symmetry:
>>> import damask
>>> o = damask.Orientation(lattice='cubic')
>>> o.IPF_color([0,0,1])
array([1., 0., 0.])
"""
if (uvw is not None) ^ (hkl is None):
raise KeyError('specify either "uvw" or "hkl"')
axis,basis = (np.array(uvw),self.basis_real) \
if hkl is None else \
(np.array(hkl),self.basis_reciprocal)
return (self.symmetry_operations.broadcast_to(self.symmetry_operations.shape+axis.shape[:-1],mode='right')
@ np.broadcast_to(np.einsum('il,...l',basis,axis),self.symmetry_operations.shape+axis.shape)
if with_symmetry else
np.einsum('il,...l',basis,axis))
if np.array(vector).shape[-1] != 3:
raise ValueError('input is not a field of three-dimensional vectors')
vector_ = self.to_SST(vector,proper) if in_SST else \
self @ np.broadcast_to(vector,self.shape+(3,))
if self.standard_triangle is None: # direct exit for no symmetry
return np.zeros_like(vector_)
if proper:
components_proper = np.around(np.einsum('...ji,...i',
np.broadcast_to(self.standard_triangle['proper'], vector_.shape+(3,)),
vector_), 12)
components_improper = np.around(np.einsum('...ji,...i',
np.broadcast_to(self.standard_triangle['improper'], vector_.shape+(3,)),
vector_), 12)
in_SST = np.all(components_proper >= 0.0,axis=-1) \
| np.all(components_improper >= 0.0,axis=-1)
components = np.where((in_SST & np.all(components_proper >= 0.0,axis=-1))[...,np.newaxis],
components_proper,components_improper)
else:
components = np.around(np.einsum('...ji,...i',
np.broadcast_to(self .standard_triangle['improper'], vector_.shape+(3,)),
np.block([vector_[...,:2],np.abs(vector_[...,2:3])])), 12)
in_SST = np.all(components >= 0.0,axis=-1)
with np.errstate(invalid='ignore',divide='ignore'):
rgb = (components/np.linalg.norm(components,axis=-1,keepdims=True))**0.5 # smoothen color ramps
rgb = np.clip(rgb,0.,1.) # clip intensity
rgb /= np.max(rgb,axis=-1,keepdims=True) # normalize to (HS)V = 1
rgb[np.broadcast_to(~in_SST[...,np.newaxis],rgb.shape)] = 0.0
return rgb
@property
def symmetry_operations(self):
"""Symmetry operations as Rotations."""
_symmetry_operations = {
'cubic': [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2) ],
[ 0.0, 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2) ],
[ 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
[ 0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, 0.5 ],
[-0.5, 0.5, 0.5, -0.5 ],
[-0.5, 0.5, -0.5, 0.5 ],
[-0.5, -0.5, 0.5, 0.5 ],
[-0.5, -0.5, 0.5, -0.5 ],
[-0.5, -0.5, -0.5, 0.5 ],
[-0.5, 0.5, -0.5, -0.5 ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2), 0.0 ],
[-0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0, 0.0 ],
[-0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0, 0.0 ],
],
'hexagonal': [
[ 1.0, 0.0, 0.0, 0.0 ],
[-0.5*np.sqrt(3), 0.0, 0.0, -0.5 ],
[ 0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[ 0.0, 0.0, 0.0, 1.0 ],
[-0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
[-0.5*np.sqrt(3), 0.0, 0.0, 0.5 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, -0.5*np.sqrt(3), 0.5, 0.0 ],
[ 0.0, 0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, -0.5, -0.5*np.sqrt(3), 0.0 ],
[ 0.0, 0.5*np.sqrt(3), 0.5, 0.0 ],
],
'tetragonal': [
[ 1.0, 0.0, 0.0, 0.0 ],
[ 0.0, 1.0, 0.0, 0.0 ],
[ 0.0, 0.0, 1.0, 0.0 ],
[ 0.0, 0.0, 0.0, 1.0 ],
[ 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.0, -0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
],
'orthorhombic': [
[ 1.0,0.0,0.0,0.0 ],
[ 0.0,1.0,0.0,0.0 ],
[ 0.0,0.0,1.0,0.0 ],
[ 0.0,0.0,0.0,1.0 ],
],
'monoclinic': [
[ 1.0,0.0,0.0,0.0 ],
[ 0.0,0.0,1.0,0.0 ],
],
'triclinic': [
[ 1.0,0.0,0.0,0.0 ],
]}
return Rotation.from_quaternion(_symmetry_operations[self.family],accept_homomorph=True)
####################################################################################################
# functions that require lattice, not just family
def to_pole(self,*,uvw=None,hkl=None,with_symmetry=False):
"""
@ -1217,51 +844,78 @@ class Orientation(Rotation):
Lab frame vector (or vectors if with_symmetry) along [uvw] direction or (hkl) plane normal.
"""
v = self.to_frame(uvw=uvw,hkl=hkl,with_symmetry=with_symmetry)
v = self.to_frame(uvw=uvw,hkl=hkl)
if with_symmetry:
sym_ops = self.symmetry_operations
v = sym_ops.broadcast_to(sym_ops.shape+v.shape[:-1],mode='right') \
@ np.broadcast_to(v,sym_ops.shape+v.shape)
return ~(self if self.shape+v.shape[:-1] == () else self.broadcast_to(self.shape+v.shape[:-1],mode='right')) \
@ np.broadcast_to(v,self.shape+v.shape)
def Schmid(self,mode):
def Schmid(self,*,N_slip=None,N_twin=None):
u"""
Calculate Schmid matrix P = d ⨂ n in the lab frame for given lattice shear kinematics.
Calculate Schmid matrix P = d ⨂ n in the lab frame for selected deformation systems.
Parameters
----------
mode : {'slip', 'twin'}
Type of kinematics.
N_slip|N_twin : iterable of int
Number of deformation systems per family of the deformation system.
Use '*' to select all.
Returns
-------
P : numpy.ndarray of shape (...,N,3,3)
P : numpy.ndarray of shape (N,...,3,3)
Schmid matrix for each of the N deformation systems.
Examples
--------
Schmid matrix (in lab frame) of slip systems of a face-centered
Schmid matrix (in lab frame) of first octahedral slip system of a face-centered
cubic crystal in "Goss" orientation.
>>> import damask
>>> import numpy as np
>>> np.set_printoptions(3,suppress=True,floatmode='fixed')
>>> damask.Orientation.from_Eulers(phi=[0,45,0],degrees=True,lattice='cF').Schmid('slip')[0]
>>> O = damask.Orientation.from_Euler_angles(phi=[0,45,0],degrees=True,lattice='cF')
>>> O.Schmid(N_slip=[1])
array([[ 0.000, 0.000, 0.000],
[ 0.577, -0.000, 0.816],
[ 0.000, 0.000, 0.000]])
"""
try:
master = lattice_.kinematics[self.lattice][mode]
kinematics = {'direction':master[:,0:3],'plane':master[:,3:6]} \
if master.shape[-1] == 6 else \
{'direction':lattice_.Bravais_to_Miller(uvtw=master[:,0:4]),
'plane': lattice_.Bravais_to_Miller(hkil=master[:,4:8])}
except KeyError:
raise (f'"{mode}" not defined for lattice "{self.lattice}"')
d = self.to_frame(uvw=kinematics['direction'],with_symmetry=False)
p = self.to_frame(hkl=kinematics['plane'] ,with_symmetry=False)
P = np.einsum('...i,...j',d/np.linalg.norm(d,axis=-1,keepdims=True),
p/np.linalg.norm(p,axis=-1,keepdims=True))
if (N_slip is not None) ^ (N_twin is None):
raise KeyError('Specify either "N_slip" or "N_twin"')
return ~self.broadcast_to( self.shape+P.shape[:-2],mode='right') \
@ np.broadcast_to(P,self.shape+P.shape)
kinematics,active = (self.kinematics('slip'),N_slip) if N_twin is None else \
(self.kinematics('twin'),N_twin)
if active == '*': active = [len(a) for a in kinematics['direction']]
d = self.to_frame(uvw=np.vstack([kinematics['direction'][i][:n] for i,n in enumerate(active)]))
p = self.to_frame(hkl=np.vstack([kinematics['plane'][i][:n] for i,n in enumerate(active)]))
P = np.einsum('...i,...j',d/np.linalg.norm(d,axis=1,keepdims=True),
p/np.linalg.norm(p,axis=1,keepdims=True))
shape = P.shape[0:1]+self.shape+(3,3)
return ~self.broadcast_to(shape[:-2]) \
@ np.broadcast_to(P.reshape(util.shapeshifter(P.shape,shape)),shape)
def related(self,model):
"""
Orientations derived from the given relationship.
One dimension (length according to number of related orientations)
is added to the left of the Rotation array.
"""
lattice,o = self.relation_operations(model)
target = Crystal(lattice=lattice)
o = o.broadcast_to(o.shape+self.shape,mode='right')
return Orientation(rotation=o*Rotation(self.quaternion).broadcast_to(o.shape,mode='left'),
lattice=lattice,
b = self.b if target.ratio['b'] is None else self.a*target.ratio['b'],
c = self.c if target.ratio['c'] is None else self.a*target.ratio['c'],
alpha = None if 'alpha' in target.immutable else self.alpha,
beta = None if 'beta' in target.immutable else self.beta,
gamma = None if 'gamma' in target.immutable else self.gamma,
)

68
python/damask/_result.py
View File

@ -981,47 +981,35 @@ class Result:
self._add_generic_pointwise(self._add_stress_second_Piola_Kirchhoff,{'P':P,'F':F})
# The add_pole functionality needs discussion.
# The new Crystal object can perform such a calculation but the outcome depends on the lattice parameters
# as well as on whether a direction or plane is concerned (see the DAMASK_examples/pole_figure notebook).
# Below code appears to be too simplistic.
# @staticmethod
# def _add_pole(q,p,polar):
# pole = np.array(p)
# unit_pole = pole/np.linalg.norm(pole)
# m = util.scale_to_coprime(pole)
# rot = Rotation(q['data'].view(np.double).reshape(-1,4))
#
# rotatedPole = rot @ np.broadcast_to(unit_pole,rot.shape+(3,)) # rotate pole according to crystal orientation
# xy = rotatedPole[:,0:2]/(1.+abs(unit_pole[2])) # stereographic projection
# coords = xy if not polar else \
# np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
# return {
# 'data': coords,
# 'label': 'p^{}_[{} {} {})'.format(u'rφ' if polar else 'xy',*m),
# 'meta' : {
# 'unit': '1',
# 'description': '{} coordinates of stereographic projection of pole (direction/plane) in crystal frame'\
# .format('Polar' if polar else 'Cartesian'),
# 'creator': 'add_pole'
# }
# }
# def add_pole(self,q,p,polar=False):
# """
# Add coordinates of stereographic projection of given pole in crystal frame.
#
# Parameters
# ----------
# q : str
# Name of the dataset containing the crystallographic orientation as quaternions.
# p : numpy.array of shape (3)
# Crystallographic direction or plane.
# polar : bool, optional
# Give pole in polar coordinates. Defaults to False.
#
# """
# self._add_generic_pointwise(self._add_pole,{'q':q},{'p':p,'polar':polar})
@staticmethod
def _add_pole(q,uvw,hkl):
c = q['meta']['c/a'] if 'c/a' in q['meta'] else 1
pole = Orientation(q['data'], lattice=q['meta']['lattice'], a=1, c=c).to_pole(uvw=uvw,hkl=hkl)
return {
'data': pole,
'label': 'p^[{} {} {}]'.format(*uvw) if uvw else 'p^({} {} {})'.format(*hkl),
'meta' : {
'unit': '1',
'description': f"lab frame vector along lattice {'direction' if uvw else 'plane'}",
'creator': 'add_pole'
}
}
def add_pole(self,q='O',*,uvw=None,hkl=None):
"""
Add lab frame vector along lattice direction [uvw] or plane normal (hkl).
Parameters
----------
q : str
Name of the dataset containing the crystallographic orientation as quaternions.
Defaults to 'O'.
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of crystallographic direction or plane normal.
"""
self._add_generic_pointwise(self._add_pole,{'q':q},{'uvw':uvw,'hkl':hkl})
@staticmethod

501
python/damask/lattice.py
View File

@ -1,501 +0,0 @@
import numpy as _np
def Bravais_to_Miller(*,uvtw=None,hkil=None):
"""
Transform 4 Miller–Bravais indices to 3 Miller indices of crystal direction [uvw] or plane normal (hkl).
Parameters
----------
uvtw|hkil : numpy.ndarray of shape (...,4)
Miller–Bravais indices of crystallographic direction [uvtw] or plane normal (hkil).
Returns
-------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of [uvw] direction or (hkl) plane normal.
"""
if (uvtw is not None) ^ (hkil is None):
raise KeyError('Specify either "uvtw" or "hkil"')
axis,basis = (_np.array(uvtw),_np.array([[1,0,-1,0],
[0,1,-1,0],
[0,0, 0,1]])) \
if hkil is None else \
(_np.array(hkil),_np.array([[1,0,0,0],
[0,1,0,0],
[0,0,0,1]]))
return _np.einsum('il,...l',basis,axis)
def Miller_to_Bravais(*,uvw=None,hkl=None):
"""
Transform 3 Miller indices to 4 Miller–Bravais indices of crystal direction [uvtw] or plane normal (hkil).
Parameters
----------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of crystallographic direction [uvw] or plane normal (hkl).
Returns
-------
uvtw|hkil : numpy.ndarray of shape (...,4)
Miller–Bravais indices of [uvtw] direction or (hkil) plane normal.
"""
if (uvw is not None) ^ (hkl is None):
raise KeyError('Specify either "uvw" or "hkl"')
axis,basis = (_np.array(uvw),_np.array([[ 2,-1, 0],
[-1, 2, 0],
[-1,-1, 0],
[ 0, 0, 3]])/3) \
if hkl is None else \
(_np.array(hkl),_np.array([[ 1, 0, 0],
[ 0, 1, 0],
[-1,-1, 0],
[ 0, 0, 1]]))
return _np.einsum('il,...l',basis,axis)
kinematics = {
'cF': {
'slip' : _np.array([
[+0,+1,-1 , +1,+1,+1],
[-1,+0,+1 , +1,+1,+1],
[+1,-1,+0 , +1,+1,+1],
[+0,-1,-1 , -1,-1,+1],
[+1,+0,+1 , -1,-1,+1],
[-1,+1,+0 , -1,-1,+1],
[+0,-1,+1 , +1,-1,-1],
[-1,+0,-1 , +1,-1,-1],
[+1,+1,+0 , +1,-1,-1],
[+0,+1,+1 , -1,+1,-1],
[+1,+0,-1 , -1,+1,-1],
[-1,-1,+0 , -1,+1,-1],
[+1,+1,+0 , +1,-1,+0],
[+1,-1,+0 , +1,+1,+0],
[+1,+0,+1 , +1,+0,-1],
[+1,+0,-1 , +1,+0,+1],
[+0,+1,+1 , +0,+1,-1],
[+0,+1,-1 , +0,+1,+1],
],'d'),
'twin' : _np.array([
[-2, 1, 1, 1, 1, 1],
[ 1,-2, 1, 1, 1, 1],
[ 1, 1,-2, 1, 1, 1],
[ 2,-1, 1, -1,-1, 1],
[-1, 2, 1, -1,-1, 1],
[-1,-1,-2, -1,-1, 1],
[-2,-1,-1, 1,-1,-1],
[ 1, 2,-1, 1,-1,-1],
[ 1,-1, 2, 1,-1,-1],
[ 2, 1,-1, -1, 1,-1],
[-1,-2,-1, -1, 1,-1],
[-1, 1, 2, -1, 1,-1],
],dtype=float),
},
'cI': {
'slip' : _np.array([
[+1,-1,+1 , +0,+1,+1],
[-1,-1,+1 , +0,+1,+1],
[+1,+1,+1 , +0,-1,+1],
[-1,+1,+1 , +0,-1,+1],
[-1,+1,+1 , +1,+0,+1],
[-1,-1,+1 , +1,+0,+1],
[+1,+1,+1 , -1,+0,+1],
[+1,-1,+1 , -1,+0,+1],
[-1,+1,+1 , +1,+1,+0],
[-1,+1,-1 , +1,+1,+0],
[+1,+1,+1 , -1,+1,+0],
[+1,+1,-1 , -1,+1,+0],
[-1,+1,+1 , +2,+1,+1],
[+1,+1,+1 , -2,+1,+1],
[+1,+1,-1 , +2,-1,+1],
[+1,-1,+1 , +2,+1,-1],
[+1,-1,+1 , +1,+2,+1],
[+1,+1,-1 , -1,+2,+1],
[+1,+1,+1 , +1,-2,+1],
[-1,+1,+1 , +1,+2,-1],
[+1,+1,-1 , +1,+1,+2],
[+1,-1,+1 , -1,+1,+2],
[-1,+1,+1 , +1,-1,+2],
[+1,+1,+1 , +1,+1,-2],
[+1,+1,-1 , +1,+2,+3],
[+1,-1,+1 , -1,+2,+3],
[-1,+1,+1 , +1,-2,+3],
[+1,+1,+1 , +1,+2,-3],
[+1,-1,+1 , +1,+3,+2],
[+1,+1,-1 , -1,+3,+2],
[+1,+1,+1 , +1,-3,+2],
[-1,+1,+1 , +1,+3,-2],
[+1,+1,-1 , +2,+1,+3],
[+1,-1,+1 , -2,+1,+3],
[-1,+1,+1 , +2,-1,+3],
[+1,+1,+1 , +2,+1,-3],
[+1,-1,+1 , +2,+3,+1],
[+1,+1,-1 , -2,+3,+1],
[+1,+1,+1 , +2,-3,+1],
[-1,+1,+1 , +2,+3,-1],
[-1,+1,+1 , +3,+1,+2],
[+1,+1,+1 , -3,+1,+2],
[+1,+1,-1 , +3,-1,+2],
[+1,-1,+1 , +3,+1,-2],
[-1,+1,+1 , +3,+2,+1],
[+1,+1,+1 , -3,+2,+1],
[+1,+1,-1 , +3,-2,+1],
[+1,-1,+1 , +3,+2,-1],
],'d'),
'twin' : _np.array([
[-1, 1, 1, 2, 1, 1],
[ 1, 1, 1, -2, 1, 1],
[ 1, 1,-1, 2,-1, 1],
[ 1,-1, 1, 2, 1,-1],
[ 1,-1, 1, 1, 2, 1],
[ 1, 1,-1, -1, 2, 1],
[ 1, 1, 1, 1,-2, 1],
[-1, 1, 1, 1, 2,-1],
[ 1, 1,-1, 1, 1, 2],
[ 1,-1, 1, -1, 1, 2],
[-1, 1, 1, 1,-1, 2],
[ 1, 1, 1, 1, 1,-2],
],dtype=float),
},
'hP': {
'slip' : _np.array([
[+2,-1,-1,+0 , +0,+0,+0,+1],
[-1,+2,-1,+0 , +0,+0,+0,+1],
[-1,-1,+2,+0 , +0,+0,+0,+1],
[+2,-1,-1,+0 , +0,+1,-1,+0],
[-1,+2,-1,+0 , -1,+0,+1,+0],
[-1,-1,+2,+0 , +1,-1,+0,+0],
[-1,+1,+0,+0 , +1,+1,-2,+0],
[+0,-1,+1,+0 , -2,+1,+1,+0],
[+1,+0,-1,+0 , +1,-2,+1,+0],
[-1,+2,-1,+0 , +1,+0,-1,+1],
[-2,+1,+1,+0 , +0,+1,-1,+1],
[-1,-1,+2,+0 , -1,+1,+0,+1],
[+1,-2,+1,+0 , -1,+0,+1,+1],
[+2,-1,-1,+0 , +0,-1,+1,+1],
[+1,+1,-2,+0 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +1,+0,-1,+1],
[-1,-1,+2,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , +0,+1,-1,+1],
[+1,-2,+1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+1,+0,+1],
[+2,-1,-1,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , -1,+0,+1,+1],
[+1,+1,-2,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +0,-1,+1,+1],
[-1,+2,-1,+3 , +1,-1,+0,+1],
[-2,+1,+1,+3 , +1,-1,+0,+1],
[-1,-1,+2,+3 , +1,+1,-2,+2],
[+1,-2,+1,+3 , -1,+2,-1,+2],
[+2,-1,-1,+3 , -2,+1,+1,+2],
[+1,+1,-2,+3 , -1,-1,+2,+2],
[-1,+2,-1,+3 , +1,-2,+1,+2],
[-2,+1,+1,+3 , +2,-1,-1,+2],
],'d'),
'twin' : _np.array([
[-1, 0, 1, 1, 1, 0, -1, 2], # shear = (3-(c/a)^2)/(sqrt(3) c/a) <-10.1>{10.2}
[ 0, -1, 1, 1, 0, 1, -1, 2],
[ 1, -1, 0, 1, -1, 1, 0, 2],
[ 1, 0, -1, 1, -1, 0, 1, 2],
[ 0, 1, -1, 1, 0, -1, 1, 2],
[-1, 1, 0, 1, 1, -1, 0, 2],
[-1, -1, 2, 6, 1, 1, -2, 1], # shear = 1/(c/a) <11.6>{-1-1.1}
[ 1, -2, 1, 6, -1, 2, -1, 1],
[ 2, -1, -1, 6, -2, 1, 1, 1],
[ 1, 1, -2, 6, -1, -1, 2, 1],
[-1, 2, -1, 6, 1, -2, 1, 1],
[-2, 1, 1, 6, 2, -1, -1, 1],
[ 1, 0, -1, -2, 1, 0, -1, 1], # shear = (4(c/a)^2-9)/(4 sqrt(3) c/a) <10.-2>{10.1}
[ 0, 1, -1, -2, 0, 1, -1, 1],
[-1, 1, 0, -2, -1, 1, 0, 1],
[-1, 0, 1, -2, -1, 0, 1, 1],
[ 0, -1, 1, -2, 0, -1, 1, 1],
[ 1, -1, 0, -2, 1, -1, 0, 1],
[ 1, 1, -2, -3, 1, 1, -2, 2], # shear = 2((c/a)^2-2)/(3 c/a) <11.-3>{11.2}
[-1, 2, -1, -3, -1, 2, -1, 2],
[-2, 1, 1, -3, -2, 1, 1, 2],
[-1, -1, 2, -3, -1, -1, 2, 2],
[ 1, -2, 1, -3, 1, -2, 1, 2],
[ 2, -1, -1, -3, 2, -1, -1, 2],
],dtype=float),
},
}
# Kurdjomov--Sachs orientation relationship for fcc <-> bcc transformation
# from S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
# also see K. Kitahara et al., Acta Materialia 54:1279-1288, 2006
relations = {
'KS': {
'cF' : _np.array([
[[ -1, 0, 1],[ 1, 1, 1]],
[[ -1, 0, 1],[ 1, 1, 1]],
[[ 0, 1, -1],[ 1, 1, 1]],
[[ 0, 1, -1],[ 1, 1, 1]],
[[ 1, -1, 0],[ 1, 1, 1]],
[[ 1, -1, 0],[ 1, 1, 1]],
[[ 1, 0, -1],[ 1, -1, 1]],
[[ 1, 0, -1],[ 1, -1, 1]],
[[ -1, -1, 0],[ 1, -1, 1]],
[[ -1, -1, 0],[ 1, -1, 1]],
[[ 0, 1, 1],[ 1, -1, 1]],
[[ 0, 1, 1],[ 1, -1, 1]],
[[ 0, -1, 1],[ -1, 1, 1]],
[[ 0, -1, 1],[ -1, 1, 1]],
[[ -1, 0, -1],[ -1, 1, 1]],
[[ -1, 0, -1],[ -1, 1, 1]],
[[ 1, 1, 0],[ -1, 1, 1]],
[[ 1, 1, 0],[ -1, 1, 1]],
[[ -1, 1, 0],[ 1, 1, -1]],
[[ -1, 1, 0],[ 1, 1, -1]],
[[ 0, -1, -1],[ 1, 1, -1]],
[[ 0, -1, -1],[ 1, 1, -1]],
[[ 1, 0, 1],[ 1, 1, -1]],
[[ 1, 0, 1],[ 1, 1, -1]],
],dtype=float),
'cI' : _np.array([
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ -1, -1, 1],[ 0, 1, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
],dtype=float),
},
'GT': {
'cF' : _np.array([
[[ -5,-12, 17],[ 1, 1, 1]],
[[ 17, -5,-12],[ 1, 1, 1]],
[[-12, 17, -5],[ 1, 1, 1]],
[[ 5, 12, 17],[ -1, -1, 1]],
[[-17, 5,-12],[ -1, -1, 1]],
[[ 12,-17, -5],[ -1, -1, 1]],
[[ -5, 12,-17],[ -1, 1, 1]],
[[ 17, 5, 12],[ -1, 1, 1]],
[[-12,-17, 5],[ -1, 1, 1]],
[[ 5,-12,-17],[ 1, -1, 1]],
[[-17, -5, 12],[ 1, -1, 1]],
[[ 12, 17, 5],[ 1, -1, 1]],
[[ -5, 17,-12],[ 1, 1, 1]],
[[-12, -5, 17],[ 1, 1, 1]],
[[ 17,-12, -5],[ 1, 1, 1]],
[[ 5,-17,-12],[ -1, -1, 1]],
[[ 12, 5, 17],[ -1, -1, 1]],
[[-17, 12, -5],[ -1, -1, 1]],
[[ -5,-17, 12],[ -1, 1, 1]],
[[-12, 5,-17],[ -1, 1, 1]],
[[ 17, 12, 5],[ -1, 1, 1]],
[[ 5, 17, 12],[ 1, -1, 1]],
[[ 12, -5,-17],[ 1, -1, 1]],
[[-17,-12, 5],[ 1, -1, 1]],
],dtype=float),
'cI' : _np.array([
[[-17, -7, 17],[ 1, 0, 1]],
[[ 17,-17, -7],[ 1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[-17, 17, -7],[ -1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[ 17, 17, 7],[ -1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[-17,-17, 7],[ 1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 17, -7],[ 1, 1, 0]],
[[ -7,-17, 17],[ 0, 1, 1]],
[[ 17, -7,-17],[ 1, 0, 1]],
[[ 17,-17, -7],[ -1, -1, 0]],
[[ 7, 17, 17],[ 0, -1, 1]],
[[-17, 7,-17],[ -1, 0, 1]],
[[-17,-17, 7],[ -1, 1, 0]],
[[ -7, 17,-17],[ 0, 1, 1]],
[[ 17, 7, 17],[ -1, 0, 1]],
[[ 17, 17, 7],[ 1, -1, 0]],
[[ 7,-17,-17],[ 0, -1, 1]],
[[-17, -7, 17],[ 1, 0, 1]],
],dtype=float),
},
'GT_prime': {
'cF' : _np.array([
[[ 0, 1, -1],[ 7, 17, 17]],
[[ -1, 0, 1],[ 17, 7, 17]],
[[ 1, -1, 0],[ 17, 17, 7]],
[[ 0, -1, -1],[ -7,-17, 17]],
[[ 1, 0, 1],[-17, -7, 17]],
[[ 1, -1, 0],[-17,-17, 7]],
[[ 0, 1, -1],[ 7,-17,-17]],
[[ 1, 0, 1],[ 17, -7,-17]],
[[ -1, -1, 0],[ 17,-17, -7]],
[[ 0, -1, -1],[ -7, 17,-17]],
[[ -1, 0, 1],[-17, 7,-17]],
[[ -1, -1, 0],[-17, 17, -7]],
[[ 0, -1, 1],[ 7, 17, 17]],
[[ 1, 0, -1],[ 17, 7, 17]],
[[ -1, 1, 0],[ 17, 17, 7]],
[[ 0, 1, 1],[ -7,-17, 17]],
[[ -1, 0, -1],[-17, -7, 17]],
[[ -1, 1, 0],[-17,-17, 7]],
[[ 0, -1, 1],[ 7,-17,-17]],
[[ -1, 0, -1],[ 17, -7,-17]],
[[ 1, 1, 0],[ 17,-17, -7]],
[[ 0, 1, 1],[ -7, 17,-17]],
[[ 1, 0, -1],[-17, 7,-17]],
[[ 1, 1, 0],[-17, 17, -7]],
],dtype=float),
'cI' : _np.array([
[[ 1, 1, -1],[ 12, 5, 17]],
[[ -1, 1, 1],[ 17, 12, 5]],
[[ 1, -1, 1],[ 5, 17, 12]],
[[ -1, -1, -1],[-12, -5, 17]],
[[ 1, -1, 1],[-17,-12, 5]],
[[ 1, -1, -1],[ -5,-17, 12]],
[[ -1, 1, -1],[ 12, -5,-17]],
[[ 1, 1, 1],[ 17,-12, -5]],
[[ -1, -1, 1],[ 5,-17,-12]],
[[ 1, -1, -1],[-12, 5,-17]],
[[ -1, -1, 1],[-17, 12, -5]],
[[ -1, -1, -1],[ -5, 17,-12]],
[[ 1, -1, 1],[ 12, 17, 5]],
[[ 1, 1, -1],[ 5, 12, 17]],
[[ -1, 1, 1],[ 17, 5, 12]],
[[ -1, 1, 1],[-12,-17, 5]],
[[ -1, -1, -1],[ -5,-12, 17]],
[[ -1, 1, -1],[-17, -5, 12]],
[[ -1, -1, 1],[ 12,-17, -5]],
[[ -1, 1, -1],[ 5,-12,-17]],
[[ 1, 1, 1],[ 17, -5,-12]],
[[ 1, 1, 1],[-12, 17, -5]],
[[ 1, -1, -1],[ -5, 12,-17]],
[[ 1, 1, -1],[-17, 5,-12]],
],dtype=float),
},
'NW': {
'cF' : _np.array([
[[ 2, -1, -1],[ 1, 1, 1]],
[[ -1, 2, -1],[ 1, 1, 1]],
[[ -1, -1, 2],[ 1, 1, 1]],
[[ -2, -1, -1],[ -1, 1, 1]],
[[ 1, 2, -1],[ -1, 1, 1]],
[[ 1, -1, 2],[ -1, 1, 1]],
[[ 2, 1, -1],[ 1, -1, 1]],
[[ -1, -2, -1],[ 1, -1, 1]],
[[ -1, 1, 2],[ 1, -1, 1]],
[[ 2, -1, 1],[ -1, -1, 1]],
[[ -1, 2, 1],[ -1, -1, 1]],
[[ -1, -1, -2],[ -1, -1, 1]],
],dtype=float),
'cI' : _np.array([
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
[[ 0, -1, 1],[ 0, 1, 1]],
],dtype=float),
},
'Pitsch': {
'cF' : _np.array([
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 0, 1, -1],[ 1, 0, 0]],
[[ -1, 0, 1],[ 0, 1, 0]],
[[ 1, -1, 0],[ 0, 0, 1]],
[[ 1, 0, -1],[ 0, 1, 0]],
[[ -1, 1, 0],[ 0, 0, 1]],
[[ 0, -1, 1],[ 1, 0, 0]],
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : _np.array([
[[ 1, -1, 1],[ -1, 0, 1]],
[[ 1, 1, -1],[ 1, -1, 0]],
[[ -1, 1, 1],[ 0, 1, -1]],
[[ -1, 1, -1],[ 0, -1, -1]],
[[ -1, -1, 1],[ -1, 0, -1]],
[[ 1, -1, -1],[ -1, -1, 0]],
[[ 1, -1, -1],[ -1, 0, -1]],
[[ -1, 1, -1],[ -1, -1, 0]],
[[ -1, -1, 1],[ 0, -1, -1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, -1, 1],[ 1, 0, -1]],
[[ 1, 1, -1],[ -1, 1, 0]],
],dtype=float),
},
'Bain': {
'cF' : _np.array([
[[ 0, 1, 0],[ 1, 0, 0]],
[[ 0, 0, 1],[ 0, 1, 0]],
[[ 1, 0, 0],[ 0, 0, 1]],
],dtype=float),
'cI' : _np.array([
[[ 0, 1, 1],[ 1, 0, 0]],
[[ 1, 0, 1],[ 0, 1, 0]],
[[ 1, 1, 0],[ 0, 0, 1]],
],dtype=float),
},
'Burgers' : {
'cI' : _np.array([
[[ -1, 1, 1],[ 1, 1, 0]],
[[ -1, 1, -1],[ 1, 1, 0]],
[[ 1, 1, 1],[ 1, -1, 0]],
[[ 1, 1, -1],[ 1, -1, 0]],
[[ 1, 1, -1],[ 1, 0, 1]],
[[ -1, 1, 1],[ 1, 0, 1]],
[[ 1, 1, 1],[ -1, 0, 1]],
[[ 1, -1, 1],[ -1, 0, 1]],
[[ -1, 1, -1],[ 0, 1, 1]],
[[ 1, 1, -1],[ 0, 1, 1]],
[[ -1, 1, 1],[ 0, -1, 1]],
[[ 1, 1, 1],[ 0, -1, 1]],
],dtype=float),
'hP' : _np.array([
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
[[ -1, 2, -1, 0],[ 0, 0, 0, 1]],
[[ -1, -1, 2, 0],[ 0, 0, 0, 1]],
],dtype=float),
},
}

77
python/damask/util.py
View File

@ -27,6 +27,7 @@ __all__=[
'execution_stamp',
'shapeshifter', 'shapeblender',
'extend_docstring', 'extended_docstring',
'Bravais_to_Miller', 'Miller_to_Bravais',
'DREAM3D_base_group', 'DREAM3D_cell_data_group',
'dict_prune', 'dict_flatten'
]
@ -286,6 +287,8 @@ def project_stereographic(vector,direction='z',normalize=True,keepdims=False):
Examples
--------
>>> import damask
>>> import numpy as np
>>> project_stereographic(np.ones(3))
[0.3660254, 0.3660254]
>>> project_stereographic(np.ones(3),direction='x',normalize=False,keepdims=True)
@ -338,7 +341,7 @@ def hybrid_IA(dist,N,rng_seed=None):
def shapeshifter(fro,to,mode='left',keep_ones=False):
"""
Return a tuple that reshapes 'fro' to become broadcastable to 'to'.
Return dimensions that reshape 'fro' to become broadcastable to 'to'.
Parameters
----------
@ -355,6 +358,22 @@ def shapeshifter(fro,to,mode='left',keep_ones=False):
Treat '1' in fro as literal value instead of dimensional placeholder.
Defaults to False.
Returns
-------
new_dims : tuple
Dimensions for reshape.
Example
-------
>>> import numpy as np
>>> from damask import util
>>> a = np.ones((3,4,2))
>>> b = np.ones(4)
>>> b_extended = b.reshape(util.shapeshifter(b.shape,a.shape))
>>> (a * np.broadcast_to(b_extended,a.shape)).shape
(3,4,2)
"""
beg = dict(left ='(^.*\\b)',
right='(^.*?\\b)')
@ -499,6 +518,62 @@ def DREAM3D_cell_data_group(fname):
return cell_data_group
def Bravais_to_Miller(*,uvtw=None,hkil=None):
"""
Transform 4 Miller–Bravais indices to 3 Miller indices of crystal direction [uvw] or plane normal (hkl).
Parameters
----------
uvtw|hkil : numpy.ndarray of shape (...,4)
Miller–Bravais indices of crystallographic direction [uvtw] or plane normal (hkil).
Returns
-------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of [uvw] direction or (hkl) plane normal.
"""
if (uvtw is not None) ^ (hkil is None):
raise KeyError('Specify either "uvtw" or "hkil"')
axis,basis = (np.array(uvtw),np.array([[1,0,-1,0],
[0,1,-1,0],
[0,0, 0,1]])) \
if hkil is None else \
(np.array(hkil),np.array([[1,0,0,0],
[0,1,0,0],
[0,0,0,1]]))
return np.einsum('il,...l',basis,axis)
def Miller_to_Bravais(*,uvw=None,hkl=None):
"""
Transform 3 Miller indices to 4 Miller–Bravais indices of crystal direction [uvtw] or plane normal (hkil).
Parameters
----------
uvw|hkl : numpy.ndarray of shape (...,3)
Miller indices of crystallographic direction [uvw] or plane normal (hkl).
Returns
-------
uvtw|hkil : numpy.ndarray of shape (...,4)
Miller–Bravais indices of [uvtw] direction or (hkil) plane normal.
"""
if (uvw is not None) ^ (hkl is None):
raise KeyError('Specify either "uvw" or "hkl"')
axis,basis = (np.array(uvw),np.array([[ 2,-1, 0],
[-1, 2, 0],
[-1,-1, 0],
[ 0, 0, 3]])/3) \
if hkl is None else \
(np.array(hkl),np.array([[ 1, 0, 0],
[ 0, 1, 0],
[-1,-1, 0],
[ 0, 0, 1]]))
return np.einsum('il,...l',basis,axis)
def dict_prune(d):
"""
Recursively remove empty dictionaries.

57
python/tests/test_Crystal.py Normal file
View File

@ -0,0 +1,57 @@
import pytest
import numpy as np
from damask import Crystal
class TestCrystal:
def test_double_to_lattice(self):
c = Crystal(lattice='cF')
with pytest.raises(KeyError):
c.to_lattice(direction=np.ones(3),plane=np.ones(3))
def test_double_to_frame(self):
c = Crystal(lattice='cF')
with pytest.raises(KeyError):
c.to_frame(uvw=np.ones(3),hkl=np.ones(3))
@pytest.mark.parametrize('lattice,a,b,c,alpha,beta,gamma',
[
('aP',0.5,2.0,3.0,0.8,0.5,1.2),
('mP',1.0,2.0,3.0,np.pi/2,0.5,np.pi/2),
('oI',0.5,1.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('tP',0.5,0.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('hP',1.0,None,1.6,np.pi/2,np.pi/2,2*np.pi/3),
('cF',1.0,1.0,None,np.pi/2,np.pi/2,np.pi/2),
])
def test_bases_contraction(self,lattice,a,b,c,alpha,beta,gamma):
c = Crystal(lattice=lattice,
a=a,b=b,c=c,
alpha=alpha,beta=beta,gamma=gamma)
assert np.allclose(np.eye(3),np.einsum('ik,jk',c.basis_real,c.basis_reciprocal))
@pytest.mark.parametrize('keyFrame,keyLattice',[('uvw','direction'),('hkl','plane'),])
@pytest.mark.parametrize('vector',np.array([
[1.,1.,1.],
[-2.,3.,0.5],
[0.,0.,1.],
[1.,1.,1.],
[2.,2.,2.],
[0.,1.,1.],
]))
@pytest.mark.parametrize('lattice,a,b,c,alpha,beta,gamma',
[
('aP',0.5,2.0,3.0,0.8,0.5,1.2),
('mP',1.0,2.0,3.0,np.pi/2,0.5,np.pi/2),
('oI',0.5,1.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('tP',0.5,0.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('hP',1.0,1.0,1.6,np.pi/2,np.pi/2,2*np.pi/3),
('cF',1.0,1.0,1.0,np.pi/2,np.pi/2,np.pi/2),
])
def test_to_frame_to_lattice(self,lattice,a,b,c,alpha,beta,gamma,vector,keyFrame,keyLattice):
c = Crystal(lattice=lattice,
a=a,b=b,c=c,
alpha=alpha,beta=beta,gamma=gamma)
assert np.allclose(vector,
c.to_frame(**{keyFrame:c.to_lattice(**{keyLattice:vector})}))

277
python/tests/test_Orientation.py
View File

@ -7,7 +7,6 @@ from damask import Orientation
from damask import Table
from damask import util
from damask import grid_filters
from damask import lattice
from damask import _orientation
crystal_families = set(_orientation.lattice_symmetries.values())
@ -25,38 +24,42 @@ def set_of_rodrigues(set_of_quaternions):
class TestOrientation:
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[None,5,(4,6)])
def test_equal(self,lattice,shape):
def test_equal(self,family,shape):
R = Rotation.from_random(shape)
assert Orientation(R,lattice) == Orientation(R,lattice) if shape is None else \
(Orientation(R,lattice) == Orientation(R,lattice)).all()
assert Orientation(R,family=family) == Orientation(R,family=family) if shape is None else \
(Orientation(R,family=family) == Orientation(R,family=family)).all()
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[None,5,(4,6)])
def test_unequal(self,lattice,shape):
def test_unequal(self,family,shape):
R = Rotation.from_random(shape)
assert not ( Orientation(R,lattice) != Orientation(R,lattice) if shape is None else \
(Orientation(R,lattice) != Orientation(R,lattice)).any())
assert not ( Orientation(R,family=family) != Orientation(R,family=family) if shape is None else \
(Orientation(R,family=family) != Orientation(R,family=family)).any())
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[None,5,(4,6)])
def test_close(self,lattice,shape):
R = Orientation.from_random(lattice=lattice,shape=shape)
def test_close(self,family,shape):
R = Orientation.from_random(family=family,shape=shape)
assert R.isclose(R.reduced).all() and R.allclose(R.reduced)
@pytest.mark.parametrize('a,b',[
(dict(rotation=[1,0,0,0],lattice='triclinic'),
dict(rotation=[0.5,0.5,0.5,0.5],lattice='triclinic')),
(dict(rotation=[1,0,0,0],family='triclinic'),
dict(rotation=[0.5,0.5,0.5,0.5],family='triclinic')),
(dict(rotation=[1,0,0,0],lattice='cubic'),
dict(rotation=[1,0,0,0],lattice='hexagonal')),
(dict(rotation=[1,0,0,0],family='cubic'),
dict(rotation=[1,0,0,0],family='hexagonal')),
])
def test_unequal_family(self,a,b):
assert Orientation(**a) != Orientation(**b)
@pytest.mark.parametrize('a,b',[
(dict(rotation=[1,0,0,0],lattice='cF',a=1),
dict(rotation=[1,0,0,0],lattice='cF',a=2)),
])
def test_nonequal(self,a,b):
def test_unequal_lattice(self,a,b):
assert Orientation(**a) != Orientation(**b)
@pytest.mark.parametrize('kwargs',[
@ -72,7 +75,7 @@ class TestOrientation:
])
def test_invalid_init(self,kwargs):
with pytest.raises(ValueError):
Orientation(**kwargs).parameters # noqa
Orientation(**kwargs)
@pytest.mark.parametrize('kwargs',[
dict(lattice='aP',a=1.0,b=1.1,c=1.2,alpha=np.pi/4,beta=np.pi/3,gamma=np.pi/2),
@ -100,47 +103,47 @@ class TestOrientation:
assert o != p
def test_from_quaternion(self):
assert np.all(Orientation.from_quaternion(q=np.array([1,0,0,0]),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_quaternion(q=np.array([1,0,0,0]),family='triclinic').as_matrix()
== np.eye(3))
def test_from_Euler_angles(self):
assert np.all(Orientation.from_Euler_angles(phi=np.zeros(3),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_Euler_angles(phi=np.zeros(3),family='triclinic').as_matrix()
== np.eye(3))
def test_from_axis_angle(self):
assert np.all(Orientation.from_axis_angle(axis_angle=[1,0,0,0],lattice='triclinic').as_matrix()
assert np.all(Orientation.from_axis_angle(axis_angle=[1,0,0,0],family='triclinic').as_matrix()
== np.eye(3))
def test_from_basis(self):
assert np.all(Orientation.from_basis(basis=np.eye(3),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_basis(basis=np.eye(3),family='triclinic').as_matrix()
== np.eye(3))
def test_from_matrix(self):
assert np.all(Orientation.from_matrix(R=np.eye(3),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_matrix(R=np.eye(3),family='triclinic').as_matrix()
== np.eye(3))
def test_from_Rodrigues_vector(self):
assert np.all(Orientation.from_Rodrigues_vector(rho=np.array([0,0,1,0]),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_Rodrigues_vector(rho=np.array([0,0,1,0]),family='triclinic').as_matrix()
== np.eye(3))
def test_from_homochoric(self):
assert np.all(Orientation.from_homochoric(h=np.zeros(3),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_homochoric(h=np.zeros(3),family='triclinic').as_matrix()
== np.eye(3))
def test_from_cubochoric(self):
assert np.all(Orientation.from_cubochoric(x=np.zeros(3),lattice='triclinic').as_matrix()
assert np.all(Orientation.from_cubochoric(x=np.zeros(3),family='triclinic').as_matrix()
== np.eye(3))
def test_from_spherical_component(self):
assert np.all(Orientation.from_spherical_component(center=Rotation(),
sigma=0.0,N=1,lattice='triclinic').as_matrix()
sigma=0.0,N=1,family='triclinic').as_matrix()
== np.eye(3))
def test_from_fiber_component(self):
r = Rotation.from_fiber_component(alpha=np.zeros(2),beta=np.zeros(2),
sigma=0.0,N=1,rng_seed=0)
assert np.all(Orientation.from_fiber_component(alpha=np.zeros(2),beta=np.zeros(2),
sigma=0.0,N=1,rng_seed=0,lattice='triclinic').quaternion
sigma=0.0,N=1,rng_seed=0,family='triclinic').quaternion
== r.quaternion)
@pytest.mark.parametrize('kwargs',[
@ -185,26 +188,26 @@ class TestOrientation:
with pytest.raises(ValueError):
Orientation(lattice='aP',a=1,b=2,c=3,alpha=45,beta=45,gamma=90.0001,degrees=True) # noqa
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('angle',[10,20,30,40])
def test_average(self,angle,lattice):
o = Orientation.from_axis_angle(lattice=lattice,axis_angle=[[0,0,1,10],[0,0,1,angle]],degrees=True)
def test_average(self,angle,family):
o = Orientation.from_axis_angle(family=family,axis_angle=[[0,0,1,10],[0,0,1,angle]],degrees=True)
avg_angle = o.average().as_axis_angle(degrees=True,pair=True)[1]
assert np.isclose(avg_angle,10+(angle-10)/2.)
@pytest.mark.parametrize('lattice',crystal_families)
def test_reduced_equivalent(self,lattice):
i = Orientation(lattice=lattice)
o = Orientation.from_random(lattice=lattice)
@pytest.mark.parametrize('family',crystal_families)
def test_reduced_equivalent(self,family):
i = Orientation(family=family)
o = Orientation.from_random(family=family)
eq = o.equivalent
FZ = np.argmin(abs(eq.misorientation(i.broadcast_to(len(eq))).as_axis_angle(pair=True)[1]))
assert o.reduced == eq[FZ]
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('N',[1,8,32])
def test_disorientation(self,lattice,N):
o = Orientation.from_random(lattice=lattice,shape=N)
p = Orientation.from_random(lattice=lattice,shape=N)
def test_disorientation(self,family,N):
o = Orientation.from_random(family=family,shape=N)
p = Orientation.from_random(family=family,shape=N)
d,ops = o.disorientation(p,return_operators=True)
@ -218,72 +221,72 @@ class TestOrientation:
.misorientation(p[n].equivalent[ops[n][1]])
.as_quaternion())
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('a,b',[
((2,3,2),(2,3,2)),
((2,2),(4,4)),
((3,1),(1,3)),
(None,None),
])
def test_disorientation_blending(self,lattice,a,b):
o = Orientation.from_random(lattice=lattice,shape=a)
p = Orientation.from_random(lattice=lattice,shape=b)
def test_disorientation_blending(self,family,a,b):
o = Orientation.from_random(family=family,shape=a)
p = Orientation.from_random(family=family,shape=b)
blend = util.shapeblender(o.shape,p.shape)
for loc in np.random.randint(0,blend,(10,len(blend))):
assert o[tuple(loc[:len(o.shape)])].disorientation(p[tuple(loc[-len(p.shape):])]) \
.isclose(o.disorientation(p)[tuple(loc)])
@pytest.mark.parametrize('lattice',crystal_families)
def test_disorientation360(self,lattice):
o_1 = Orientation(Rotation(),lattice)
o_2 = Orientation.from_Euler_angles(lattice=lattice,phi=[360,0,0],degrees=True)
@pytest.mark.parametrize('family',crystal_families)
def test_disorientation360(self,family):
o_1 = Orientation(Rotation(),family=family)
o_2 = Orientation.from_Euler_angles(family=family,phi=[360,0,0],degrees=True)
assert np.allclose((o_1.disorientation(o_2)).as_matrix(),np.eye(3))
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[(1),(2,3),(4,3,2)])
def test_reduced_vectorization(self,lattice,shape):
o = Orientation.from_random(lattice=lattice,shape=shape)
def test_reduced_vectorization(self,family,shape):
o = Orientation.from_random(family=family,shape=shape)
for r, theO in zip(o.reduced.flatten(),o.flatten()):
assert r == theO.reduced
@pytest.mark.parametrize('lattice',crystal_families)
def test_reduced_corner_cases(self,lattice):
@pytest.mark.parametrize('family',crystal_families)
def test_reduced_corner_cases(self,family):
# test whether there is always a sym-eq rotation that falls into the FZ
N = np.random.randint(10,40)
size = np.ones(3)*np.pi**(2./3.)
grid = grid_filters.coordinates0_node([N+1,N+1,N+1],size,-size*.5)
evenly_distributed = Orientation.from_cubochoric(x=grid[:-2,:-2,:-2],lattice=lattice)
evenly_distributed = Orientation.from_cubochoric(x=grid[:-2,:-2,:-2],family=family)
assert evenly_distributed.shape == evenly_distributed.reduced.shape
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[(1),(2,3),(4,3,2)])
@pytest.mark.parametrize('vector',np.array([[1,0,0],[1,2,3],[-1,1,-1]]))
@pytest.mark.parametrize('proper',[True,False])
def test_to_SST_vectorization(self,lattice,shape,vector,proper):
o = Orientation.from_random(lattice=lattice,shape=shape)
def test_to_SST_vectorization(self,family,shape,vector,proper):
o = Orientation.from_random(family=family,shape=shape)
for r, theO in zip(o.to_SST(vector=vector,proper=proper).reshape((-1,3)),o.flatten()):
assert np.allclose(r,theO.to_SST(vector=vector,proper=proper))
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('shape',[(1),(2,3),(4,3,2)])
@pytest.mark.parametrize('vector',np.array([[1,0,0],[1,2,3],[-1,1,-1]]))
@pytest.mark.parametrize('proper',[True,False])
@pytest.mark.parametrize('in_SST',[True,False])
def test_IPF_color_vectorization(self,lattice,shape,vector,proper,in_SST):
o = Orientation.from_random(lattice=lattice,shape=shape)
def test_IPF_color_vectorization(self,family,shape,vector,proper,in_SST):
o = Orientation.from_random(family=family,shape=shape)
for r, theO in zip(o.IPF_color(vector,in_SST=in_SST,proper=proper).reshape((-1,3)),o.flatten()):
assert np.allclose(r,theO.IPF_color(vector,in_SST=in_SST,proper=proper))
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('a,b',[
((2,3,2),(2,3,2)),
((2,2),(4,4)),
((3,1),(1,3)),
(None,(3,)),
])
def test_to_SST_blending(self,lattice,a,b):
o = Orientation.from_random(lattice=lattice,shape=a)
def test_to_SST_blending(self,family,a,b):
o = Orientation.from_random(family=family,shape=a)
v = np.random.random(b+(3,))
blend = util.shapeblender(o.shape,b)
for loc in np.random.randint(0,blend,(10,len(blend))):
@ -298,75 +301,45 @@ class TestOrientation:
{'label':'blue', 'RGB':[0,0,1],'direction':[1,1,1]}])
@pytest.mark.parametrize('proper',[True,False])
def test_IPF_cubic(self,color,proper):
cube = Orientation(lattice='cubic')
cube = Orientation(family='cubic')
for direction in set(permutations(np.array(color['direction']))):
assert np.allclose(np.array(color['RGB']),
cube.IPF_color(vector=np.array(direction),proper=proper))
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('proper',[True,False])
def test_IPF_equivalent(self,set_of_quaternions,lattice,proper):
def test_IPF_equivalent(self,set_of_quaternions,family,proper):
direction = np.random.random(3)*2.0-1.0
o = Orientation(rotation=set_of_quaternions,lattice=lattice).equivalent
o = Orientation(rotation=set_of_quaternions,family=family).equivalent
color = o.IPF_color(vector=direction,proper=proper)
assert np.allclose(np.broadcast_to(color[0,...],color.shape),color)
@pytest.mark.parametrize('lattice',crystal_families)
def test_in_FZ_vectorization(self,set_of_rodrigues,lattice):
result = Orientation.from_Rodrigues_vector(rho=set_of_rodrigues.reshape((-1,4,4)),lattice=lattice).in_FZ.reshape(-1)
@pytest.mark.parametrize('family',crystal_families)
def test_in_FZ_vectorization(self,set_of_rodrigues,family):
result = Orientation.from_Rodrigues_vector(rho=set_of_rodrigues.reshape((-1,4,4)),family=family).in_FZ.reshape(-1)
for r,rho in zip(result,set_of_rodrigues[:len(result)]):
assert r == Orientation.from_Rodrigues_vector(rho=rho,lattice=lattice).in_FZ
assert r == Orientation.from_Rodrigues_vector(rho=rho,family=family).in_FZ
@pytest.mark.parametrize('lattice',crystal_families)
def test_in_disorientation_FZ_vectorization(self,set_of_rodrigues,lattice):
@pytest.mark.parametrize('family',crystal_families)
def test_in_disorientation_FZ_vectorization(self,set_of_rodrigues,family):
result = Orientation.from_Rodrigues_vector(rho=set_of_rodrigues.reshape((-1,4,4)),
lattice=lattice).in_disorientation_FZ.reshape(-1)
family=family).in_disorientation_FZ.reshape(-1)
for r,rho in zip(result,set_of_rodrigues[:len(result)]):
assert r == Orientation.from_Rodrigues_vector(rho=rho,lattice=lattice).in_disorientation_FZ
assert r == Orientation.from_Rodrigues_vector(rho=rho,family=family).in_disorientation_FZ
@pytest.mark.parametrize('proper',[True,False])
@pytest.mark.parametrize('lattice',crystal_families)
def test_in_SST_vectorization(self,lattice,proper):
@pytest.mark.parametrize('family',crystal_families)
def test_in_SST_vectorization(self,family,proper):
vecs = np.random.rand(20,4,3)
result = Orientation(lattice=lattice).in_SST(vecs,proper).flatten()
result = Orientation(family=family).in_SST(vecs,proper).flatten()
for r,v in zip(result,vecs.reshape((-1,3))):
assert np.all(r == Orientation(lattice=lattice).in_SST(v,proper))
@pytest.mark.parametrize('invalid_lattice',['fcc','bcc','hello'])
def test_invalid_lattice_init(self,invalid_lattice):
with pytest.raises(KeyError):
Orientation(lattice=invalid_lattice) # noqa
assert np.all(r == Orientation(family=family).in_SST(v,proper))
@pytest.mark.parametrize('invalid_family',[None,'fcc','bcc','hello'])
def test_invalid_symmetry_family(self,invalid_family):
def test_invalid_lattice_init(self,invalid_family):
with pytest.raises(KeyError):
o = Orientation(lattice='cubic')
o.family = invalid_family
o.symmetry_operations # noqa
Orientation(family=invalid_family)
def test_invalid_rot(self):
with pytest.raises(TypeError):
Orientation.from_random(lattice='cubic') * np.ones(3)
def test_missing_symmetry_immutable(self):
with pytest.raises(KeyError):
Orientation(lattice=None).immutable # noqa
def test_missing_symmetry_basis_real(self):
with pytest.raises(KeyError):
Orientation(lattice=None).basis_real # noqa
def test_missing_symmetry_basis_reciprocal(self):
with pytest.raises(KeyError):
Orientation(lattice=None).basis_reciprocal # noqa
def test_double_to_lattice(self):
with pytest.raises(KeyError):
Orientation().to_lattice(direction=np.ones(3),plane=np.ones(3)) # noqa
def test_double_to_frame(self):
with pytest.raises(KeyError):
Orientation().to_frame(uvw=np.ones(3),hkl=np.ones(3)) # noqa
@pytest.mark.parametrize('relation',[None,'Peter','Paul'])
def test_unknown_relation(self,relation):
@ -388,28 +361,22 @@ class TestOrientation:
a=a,b=b,c=c,
alpha=alpha,beta=beta,gamma=gamma).related(relation) # noqa
@pytest.mark.parametrize('lattice',crystal_families)
@pytest.mark.parametrize('family',crystal_families)
@pytest.mark.parametrize('proper',[True,False])
def test_in_SST(self,lattice,proper):
assert Orientation(lattice=lattice).in_SST(np.zeros(3),proper)
def test_in_SST(self,family,proper):
assert Orientation(family=family).in_SST(np.zeros(3),proper)
@pytest.mark.parametrize('function',['in_SST','IPF_color'])
def test_invalid_argument(self,function):
o = Orientation(lattice='cubic') # noqa
o = Orientation(family='cubic') # noqa
with pytest.raises(ValueError):
eval(f'o.{function}(np.ones(4))')
@pytest.mark.parametrize('model',lattice.relations)
def test_relationship_definition(self,model):
m,o = list(lattice.relations[model])
assert lattice.relations[model][m].shape[:-1] == lattice.relations[model][o].shape[:-1]
@pytest.mark.parametrize('model',['Bain','KS','GT','GT_prime','NW','Pitsch'])
@pytest.mark.parametrize('lattice',['cF','cI'])
def test_relationship_vectorize(self,set_of_quaternions,lattice,model):
r = Orientation(rotation=set_of_quaternions[:200].reshape((50,4,4)),lattice=lattice).related(model)
for i in range(200):
assert (r.reshape((-1,200))[:,i] == Orientation(set_of_quaternions[i],lattice).related(model)).all()
assert (r.reshape((-1,200))[:,i] == Orientation(set_of_quaternions[i],lattice=lattice).related(model)).all()
@pytest.mark.parametrize('model',['Bain','KS','GT','GT_prime','NW','Pitsch'])
@pytest.mark.parametrize('lattice',['cF','cI'])
@ -444,45 +411,6 @@ class TestOrientation:
)
assert np.allclose(o.to_frame(uvw=np.eye(3)),basis), 'Lattice basis disagrees with initialization'
@pytest.mark.parametrize('lattice,a,b,c,alpha,beta,gamma',
[
('aP',0.5,2.0,3.0,0.8,0.5,1.2),
('mP',1.0,2.0,3.0,np.pi/2,0.5,np.pi/2),
('oI',0.5,1.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('tP',0.5,0.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('hP',1.0,None,1.6,np.pi/2,np.pi/2,2*np.pi/3),
('cF',1.0,1.0,None,np.pi/2,np.pi/2,np.pi/2),
])
def test_bases_contraction(self,lattice,a,b,c,alpha,beta,gamma):
L = Orientation(lattice=lattice,
a=a,b=b,c=c,
alpha=alpha,beta=beta,gamma=gamma)
assert np.allclose(np.eye(3),np.einsum('ik,jk',L.basis_real,L.basis_reciprocal))
@pytest.mark.parametrize('keyFrame,keyLattice',[('uvw','direction'),('hkl','plane'),])
@pytest.mark.parametrize('vector',np.array([
[1.,1.,1.],
[-2.,3.,0.5],
[0.,0.,1.],
[1.,1.,1.],
[2.,2.,2.],
[0.,1.,1.],
]))
@pytest.mark.parametrize('lattice,a,b,c,alpha,beta,gamma',
[
('aP',0.5,2.0,3.0,0.8,0.5,1.2),
('mP',1.0,2.0,3.0,np.pi/2,0.5,np.pi/2),
('oI',0.5,1.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('tP',0.5,0.5,3.0,np.pi/2,np.pi/2,np.pi/2),
('hP',1.0,1.0,1.6,np.pi/2,np.pi/2,2*np.pi/3),
('cF',1.0,1.0,1.0,np.pi/2,np.pi/2,np.pi/2),
])
def test_to_frame_to_lattice(self,lattice,a,b,c,alpha,beta,gamma,vector,keyFrame,keyLattice):
L = Orientation(lattice=lattice,
a=a,b=b,c=c,
alpha=alpha,beta=beta,gamma=gamma)
assert np.allclose(vector,
L.to_frame(**{keyFrame:L.to_lattice(**{keyLattice:vector})}))
@pytest.mark.parametrize('lattice,a,b,c,alpha,beta,gamma',
[
@ -510,13 +438,22 @@ class TestOrientation:
assert o.to_pole(**{kw:vector,'with_symmetry':with_symmetry}).shape \
== o.shape + (o.symmetry_operations.shape if with_symmetry else ()) + vector.shape
@pytest.mark.parametrize('lattice',['hP','cI','cF'])
@pytest.mark.parametrize('mode',['slip','twin'])
def test_Schmid(self,update,ref_path,lattice,mode):
L = Orientation(lattice=lattice)
reference = ref_path/f'{lattice}_{mode}.txt'
P = L.Schmid(mode)
if update:
table = Table(P.reshape(-1,9),{'Schmid':(3,3,)})
table.save(reference)
assert np.allclose(P,Table.load(reference).get('Schmid'))
@pytest.mark.parametrize('lattice',['hP','cI','cF']) #tI not included yet
def test_Schmid(self,update,ref_path,lattice):
O = Orientation(lattice=lattice) # noqa
for mode in ['slip','twin']:
reference = ref_path/f'{lattice}_{mode}.txt'
P = O.Schmid(N_slip='*') if mode == 'slip' else O.Schmid(N_twin='*')
if update:
table = Table(P.reshape(-1,9),{'Schmid':(3,3,)})
table.save(reference)
assert np.allclose(P,Table.load(reference).get('Schmid'))
@pytest.mark.parametrize('lattice',['hP','cI','cF']) # tI not included yet
def test_Schmid_vectorize(self,lattice):
O = Orientation.from_random(shape=4,lattice=lattice) # noqa
for mode in ['slip','twin']:
Ps = O.Schmid(N_slip='*') if mode == 'slip' else O.Schmid(N_twin='*')
for i in range(4):
P = O[i].Schmid(N_slip='*') if mode == 'slip' else O[i].Schmid(N_twin='*')
assert np.allclose(P,Ps[:,i])

21
python/tests/test_Result.py
View File

@ -12,7 +12,6 @@ import vtk
import numpy as np
from damask import Result
from damask import Rotation
from damask import Orientation
from damask import tensor
from damask import mechanics
@ -220,17 +219,15 @@ class TestResult:
in_file = default.place('S')
assert np.allclose(in_memory,in_file)
@pytest.mark.skip(reason='requires rework of lattice.f90')
@pytest.mark.parametrize('polar',[True,False])
def test_add_pole(self,default,polar):
pole = np.array([1.,0.,0.])
default.add_pole('O',pole,polar)
rot = Rotation(default.place('O'))
rotated_pole = rot * np.broadcast_to(pole,rot.shape+(3,))
xy = rotated_pole[:,0:2]/(1.+abs(pole[2]))
in_memory = xy if not polar else \
np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
in_file = default.place('p^{}_[1 0 0)'.format(u'rφ' if polar else 'xy'))
@pytest.mark.parametrize('options',[{'uvw':[1,0,0]},{'hkl':[0,1,1]}])
def test_add_pole(self,default,options):
default.add_pole(**options)
rot = default.place('O')
in_memory = Orientation(rot,lattice=rot.dtype.metadata['lattice']).to_pole(**options)
brackets = ['[[]','[]]'] if 'uvw' in options.keys() else ['(',')'] # escape fnmatch
label = '{}{} {} {}{}'.format(brackets[0],*(list(options.values())[0]),brackets[1])
in_file = default.place(f'p^{label}')
print(in_file - in_memory)
assert np.allclose(in_memory,in_file)
def test_add_rotation(self,default):

34
python/tests/test_lattice.py
View File

@ -1,34 +0,0 @@
import pytest
import numpy as np
from damask import lattice
class TestLattice:
def test_double_Bravais_to_Miller(self):
with pytest.raises(KeyError):
lattice.Bravais_to_Miller(uvtw=np.ones(4),hkil=np.ones(4)) # noqa
def test_double_Miller_to_Bravais(self):
with pytest.raises(KeyError):
lattice.Miller_to_Bravais(uvw=np.ones(4),hkl=np.ones(4)) # noqa
@pytest.mark.parametrize('vector',np.array([
[1,0,0],
[1,1,0],
[1,1,1],
[1,0,-2],
]))
@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
def test_Miller_Bravais_Miller(self,vector,kw_Miller,kw_Bravais):
assert np.all(vector == lattice.Bravais_to_Miller(**{kw_Bravais:lattice.Miller_to_Bravais(**{kw_Miller:vector})}))
@pytest.mark.parametrize('vector',np.array([
[1,0,-1,2],
[1,-1,0,3],
[1,1,-2,-3],
[0,0,0,1],
]))
@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
def test_Bravais_Miller_Bravais(self,vector,kw_Miller,kw_Bravais):
assert np.all(vector == lattice.Miller_to_Bravais(**{kw_Miller:lattice.Bravais_to_Miller(**{kw_Bravais:vector})}))

30
python/tests/test_util.py
View File

@ -158,3 +158,33 @@ class TestUtil:
({'A':{'B':{},'C':'D'}}, {'B':{},'C':'D'})])
def test_flatten(self,full,reduced):
assert util.dict_flatten(full) == reduced
def test_double_Bravais_to_Miller(self):
with pytest.raises(KeyError):
util.Bravais_to_Miller(uvtw=np.ones(4),hkil=np.ones(4))
def test_double_Miller_to_Bravais(self):
with pytest.raises(KeyError):
util.Miller_to_Bravais(uvw=np.ones(4),hkl=np.ones(4))
@pytest.mark.parametrize('vector',np.array([
[1,0,0],
[1,1,0],
[1,1,1],
[1,0,-2],
]))
@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
def test_Miller_Bravais_Miller(self,vector,kw_Miller,kw_Bravais):
assert np.all(vector == util.Bravais_to_Miller(**{kw_Bravais:util.Miller_to_Bravais(**{kw_Miller:vector})}))
@pytest.mark.parametrize('vector',np.array([
[1,0,-1,2],
[1,-1,0,3],
[1,1,-2,-3],
[0,0,0,1],
]))
@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
def test_Bravais_Miller_Bravais(self,vector,kw_Miller,kw_Bravais):
assert np.all(vector == util.Miller_to_Bravais(**{kw_Miller:util.Bravais_to_Miller(**{kw_Bravais:vector})}))