DAMASK_EICMD/python/damask/orientation.py

1478 lines
55 KiB
Python

# -*- coding: UTF-8 no BOM -*-
import math
import numpy as np
from . import Lambert
from .quaternion import Quaternion
from .quaternion import P
####################################################################################################
class Rotation:
u"""
Orientation stored as unit quaternion.
Following: D Rowenhorst et al. Consistent representations of and conversions between 3D rotations
10.1088/0965-0393/23/8/083501
Convention 1: coordinate frames are right-handed
Convention 2: a rotation angle ω is taken to be positive for a counterclockwise rotation
when viewing from the end point of the rotation axis towards the origin
Convention 3: rotations will be interpreted in the passive sense
Convention 4: Euler angle triplets are implemented using the Bunge convention,
with the angular ranges as [0, 2π],[0, π],[0, 2π]
Convention 5: the rotation angle ω is limited to the interval [0, π]
Convention 6: P = -1 (as default)
q is the real part, p = (x, y, z) are the imaginary parts.
Vector "a" (defined in coordinate system "A") is passively rotated
resulting in new coordinates "b" when expressed in system "B".
b = Q * a
b = np.dot(Q.asMatrix(),a)
"""
__slots__ = ['quaternion']
def __init__(self,quaternion = np.array([1.0,0.0,0.0,0.0])):
"""
Initializes to identity unless specified
If a quaternion is given, it needs to comply with the convection. Use .fromQuaternion
to check the input.
"""
if isinstance(quaternion,Quaternion):
self.quaternion = quaternion.copy()
else:
self.quaternion = Quaternion(q=quaternion[0],p=quaternion[1:4])
def __copy__(self):
"""Copy"""
return self.__class__(self.quaternion)
copy = __copy__
def __repr__(self):
"""Value in selected representation"""
return '\n'.join([
'{}'.format(self.quaternion),
'Matrix:\n{}'.format( '\n'.join(['\t'.join(list(map(str,self.asMatrix()[i,:]))) for i in range(3)]) ),
'Bunge Eulers / deg: {}'.format('\t'.join(list(map(str,self.asEulers(degrees=True)))) ),
])
def __mul__(self, other):
"""
Multiplication
Rotation: Details needed (active/passive), rotation of (3,3,3,3)-matrix should be considered
"""
if isinstance(other, Rotation): # rotate a rotation
return self.__class__(self.quaternion * other.quaternion).standardize()
elif isinstance(other, np.ndarray):
if other.shape == (3,): # rotate a single (3)-vector
( x, y, z) = self.quaternion.p
(Vx,Vy,Vz) = other[0:3]
A = self.quaternion.q*self.quaternion.q - np.dot(self.quaternion.p,self.quaternion.p)
B = 2.0 * (x*Vx + y*Vy + z*Vz)
C = 2.0 * P*self.quaternion.q
return np.array([
A*Vx + B*x + C*(y*Vz - z*Vy),
A*Vy + B*y + C*(z*Vx - x*Vz),
A*Vz + B*z + C*(x*Vy - y*Vx),
])
elif other.shape == (3,3,): # rotate a single (3x3)-matrix
return np.dot(self.asMatrix(),np.dot(other,self.asMatrix().T))
elif other.shape == (3,3,3,3,):
raise NotImplementedError
else:
return NotImplemented
elif isinstance(other, tuple): # used to rotate a meshgrid-tuple
( x, y, z) = self.quaternion.p
(Vx,Vy,Vz) = other[0:3]
A = self.quaternion.q*self.quaternion.q - np.dot(self.quaternion.p,self.quaternion.p)
B = 2.0 * (x*Vx + y*Vy + z*Vz)
C = 2.0 * P*self.quaternion.q
return np.array([
A*Vx + B*x + C*(y*Vz - z*Vy),
A*Vy + B*y + C*(z*Vx - x*Vz),
A*Vz + B*z + C*(x*Vy - y*Vx),
])
else:
return NotImplemented
def inverse(self):
"""In-place inverse rotation/backward rotation"""
self.quaternion.conjugate()
return self
def inversed(self):
"""Inverse rotation/backward rotation"""
return self.copy().inverse()
def standardize(self):
"""In-place quaternion representation with positive q"""
if self.quaternion.q < 0.0: self.quaternion.homomorph()
return self
def standardized(self):
"""Quaternion representation with positive q"""
return self.copy().standardize()
def misorientation(self,other):
"""Misorientation"""
return other*self.inversed()
def average(self,other):
"""Calculate the average rotation"""
return Rotation.fromAverage([self,other])
################################################################################################
# convert to different orientation representations (numpy arrays)
def asQuaternion(self):
"""Unit quaternion: (q, [p_1, p_2, p_3])"""
return self.quaternion.asArray()
def asEulers(self,
degrees = False):
"""Bunge-Euler angles: (φ_1, ϕ, φ_2)"""
eu = qu2eu(self.quaternion.asArray())
if degrees: eu = np.degrees(eu)
return eu
def asAxisAngle(self,
degrees = False):
"""Axis-angle pair: ([n_1, n_2, n_3], ω)"""
ax = qu2ax(self.quaternion.asArray())
if degrees: ax[3] = np.degrees(ax[3])
return ax
def asMatrix(self):
"""Rotation matrix"""
return qu2om(self.quaternion.asArray())
def asRodrigues(self,vector=False):
"""Rodrigues-Frank vector: ([n_1, n_2, n_3], tan(ω/2))"""
ro = qu2ro(self.quaternion.asArray())
return ro[:3]*ro[3] if vector else ro
def asHomochoric(self):
"""Homochoric vector: (h_1, h_2, h_3)"""
return qu2ho(self.quaternion.asArray())
def asCubochoric(self):
return qu2cu(self.quaternion.asArray())
def asM(self):
"""Intermediate representation supporting quaternion averaging (see F. Landis Markley et al.)"""
return self.quaternion.asM()
################################################################################################
# static constructors. The input data needs to follow the convention, options allow to
# relax these convections
@classmethod
def fromQuaternion(cls,
quaternion,
acceptHomomorph = False,
P = -1):
qu = quaternion if isinstance(quaternion, np.ndarray) else np.array(quaternion)
if P > 0: qu[1:4] *= -1 # convert from P=1 to P=-1
if qu[0] < 0.0:
if acceptHomomorph:
qu *= -1.
else:
raise ValueError('Quaternion has negative first component.\n{}'.format(qu[0]))
if not np.isclose(np.linalg.norm(qu), 1.0):
raise ValueError('Quaternion is not of unit length.\n{} {} {} {}'.format(*qu))
return cls(qu)
@classmethod
def fromEulers(cls,
eulers,
degrees = False):
eu = eulers if isinstance(eulers, np.ndarray) else np.array(eulers)
eu = np.radians(eu) if degrees else eu
if np.any(eu < 0.0) or np.any(eu > 2.0*np.pi) or eu[1] > np.pi:
raise ValueError('Euler angles outside of [0..2π],[0..π],[0..2π].\n{} {} {}.'.format(*eu))
return cls(eu2qu(eu))
@classmethod
def fromAxisAngle(cls,
angleAxis,
degrees = False,
normalise = False,
P = -1):
ax = angleAxis if isinstance(angleAxis, np.ndarray) else np.array(angleAxis)
if P > 0: ax[0:3] *= -1 # convert from P=1 to P=-1
if degrees: ax[3] = np.radians(ax[3])
if normalise: ax[0:3] /=np.linalg.norm(ax[0:3])
if ax[3] < 0.0 or ax[3] > np.pi:
raise ValueError('Axis angle rotation angle outside of [0..π].\n'.format(ax[3]))
if not np.isclose(np.linalg.norm(ax[0:3]), 1.0):
raise ValueError('Axis angle rotation axis is not of unit length.\n{} {} {}'.format(*ax[0:3]))
return cls(ax2qu(ax))
@classmethod
def fromMatrix(cls,
matrix,
containsStretch = False): #ToDo: better name?
om = matrix if isinstance(matrix, np.ndarray) else np.array(matrix).reshape((3,3)) # ToDo: Reshape here or require explicit?
if containsStretch:
(U,S,Vh) = np.linalg.svd(om) # singular value decomposition
om = np.dot(U,Vh)
if not np.isclose(np.linalg.det(om),1.0):
raise ValueError('matrix is not a proper rotation.\n{}'.format(om))
if not np.isclose(np.dot(om[0],om[1]), 0.0) \
or not np.isclose(np.dot(om[1],om[2]), 0.0) \
or not np.isclose(np.dot(om[2],om[0]), 0.0):
raise ValueError('matrix is not orthogonal.\n{}'.format(om))
return cls(om2qu(om))
@classmethod
def fromRodrigues(cls,
rodrigues,
normalise = False,
P = -1):
ro = rodrigues if isinstance(rodrigues, np.ndarray) else np.array(rodrigues)
if P > 0: ro[0:3] *= -1 # convert from P=1 to P=-1
if normalise: ro[0:3] /=np.linalg.norm(ro[0:3])
if not np.isclose(np.linalg.norm(ro[0:3]), 1.0):
raise ValueError('Rodrigues rotation axis is not of unit length.\n{} {} {}'.format(*ro[0:3]))
if ro[3] < 0.0:
raise ValueError('Rodriques rotation angle not positive.\n'.format(ro[3]))
return cls(ro2qu(ro))
@classmethod
def fromHomochoric(cls,
homochoric,
P = -1):
ho = homochoric if isinstance(homochoric, np.ndarray) else np.array(homochoric)
if P > 0: ho *= -1 # convert from P=1 to P=-1
return cls(ho2qu(ho))
@classmethod
def fromCubochoric(cls,
cubochoric,
P = -1):
cu = cubochoric if isinstance(cubochoric, np.ndarray) else np.array(cubochoric)
ho = cu2ho(cu)
if P > 0: ho *= -1 # convert from P=1 to P=-1
return cls(ho2qu(ho))
@classmethod
def fromAverage(cls,
rotations,
weights = []):
"""
Average rotation
ref: F. Landis Markley, Yang Cheng, John Lucas Crassidis, and Yaakov Oshman.
Averaging Quaternions,
Journal of Guidance, Control, and Dynamics, Vol. 30, No. 4 (2007), pp. 1193-1197.
doi: 10.2514/1.28949
usage: input a list of rotations and optional weights
"""
if not all(isinstance(item, Rotation) for item in rotations):
raise TypeError("Only instances of Rotation can be averaged.")
N = len(rotations)
if weights == [] or not weights:
weights = np.ones(N,dtype='i')
for i,(r,n) in enumerate(zip(rotations,weights)):
M = r.asM() * n if i == 0 \
else M + r.asM() * n # noqa add (multiples) of this rotation to average noqa
eig, vec = np.linalg.eig(M/N)
return cls.fromQuaternion(np.real(vec.T[eig.argmax()]),acceptHomomorph = True)
@classmethod
def fromRandom(cls):
r = np.random.random(3)
A = np.sqrt(r[2])
B = np.sqrt(1.0-r[2])
w = np.cos(2.0*np.pi*r[0])*A
x = np.sin(2.0*np.pi*r[1])*B
y = np.cos(2.0*np.pi*r[1])*B
z = np.sin(2.0*np.pi*r[0])*A
return cls.fromQuaternion([w,x,y,z],acceptHomomorph=True)
# ******************************************************************************************
class Symmetry:
"""
Symmetry operations for lattice systems
https://en.wikipedia.org/wiki/Crystal_system
"""
lattices = [None,'orthorhombic','tetragonal','hexagonal','cubic',]
def __init__(self, symmetry = None):
if isinstance(symmetry, str) and symmetry.lower() in Symmetry.lattices:
self.lattice = symmetry.lower()
else:
self.lattice = None
def __copy__(self):
"""Copy"""
return self.__class__(self.lattice)
copy = __copy__
def __repr__(self):
"""Readable string"""
return '{}'.format(self.lattice)
def __eq__(self, other):
"""Equal to other"""
return self.lattice == other.lattice
def __neq__(self, other):
"""Not equal to other"""
return not self.__eq__(other)
def __cmp__(self,other):
"""Linear ordering"""
myOrder = Symmetry.lattices.index(self.lattice)
otherOrder = Symmetry.lattices.index(other.lattice)
return (myOrder > otherOrder) - (myOrder < otherOrder)
def symmetryOperations(self,members=[]):
"""List (or single element) of symmetry operations as rotations."""
if self.lattice == 'cubic':
symQuats = [
[ 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.lattice == 'hexagonal':
symQuats = [
[ 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.lattice == 'tetragonal':
symQuats = [
[ 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.lattice == 'orthorhombic':
symQuats = [
[ 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 ],
]
else:
symQuats = [
[ 1.0,0.0,0.0,0.0 ],
]
symOps = list(map(Rotation,
np.array(symQuats)[np.atleast_1d(members) if members != [] else range(len(symQuats))]))
try:
iter(members) # asking for (even empty) list of members?
except TypeError:
return symOps[0] # no, return rotation object
else:
return symOps # yes, return list of rotations
def inFZ(self,rodrigues):
"""
Check whether given Rodrigues vector falls into fundamental zone of own symmetry.
Fundamental zone in Rodrigues space is point symmetric around origin.
"""
if (len(rodrigues) != 3):
raise ValueError('Input is not a Rodriques-Frank vector.\n')
if np.any(rodrigues == np.inf): return False
Rabs = abs(rodrigues)
if self.lattice == 'cubic':
return math.sqrt(2.0)-1.0 >= Rabs[0] \
and math.sqrt(2.0)-1.0 >= Rabs[1] \
and math.sqrt(2.0)-1.0 >= Rabs[2] \
and 1.0 >= Rabs[0] + Rabs[1] + Rabs[2]
elif self.lattice == 'hexagonal':
return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] and 1.0 >= Rabs[2] \
and 2.0 >= math.sqrt(3)*Rabs[0] + Rabs[1] \
and 2.0 >= math.sqrt(3)*Rabs[1] + Rabs[0] \
and 2.0 >= math.sqrt(3) + Rabs[2]
elif self.lattice == 'tetragonal':
return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] \
and math.sqrt(2.0) >= Rabs[0] + Rabs[1] \
and math.sqrt(2.0) >= Rabs[2] + 1.0
elif self.lattice == 'orthorhombic':
return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] and 1.0 >= Rabs[2]
else:
return True
def inDisorientationSST(self,rodrigues):
"""
Check whether given Rodrigues vector (of misorientation) falls into standard stereographic triangle of own symmetry.
Determination of disorientations follow the work of A. Heinz and P. Neumann:
Representation of Orientation and Disorientation Data for Cubic, Hexagonal, Tetragonal and Orthorhombic Crystals
Acta Cryst. (1991). A47, 780-789
"""
if (len(rodrigues) != 3):
raise ValueError('Input is not a Rodriques-Frank vector.\n')
R = rodrigues
epsilon = 0.0
if self.lattice == 'cubic':
return R[0] >= R[1]+epsilon and R[1] >= R[2]+epsilon and R[2] >= epsilon
elif self.lattice == 'hexagonal':
return R[0] >= math.sqrt(3)*(R[1]-epsilon) and R[1] >= epsilon and R[2] >= epsilon
elif self.lattice == 'tetragonal':
return R[0] >= R[1]-epsilon and R[1] >= epsilon and R[2] >= epsilon
elif self.lattice == 'orthorhombic':
return R[0] >= epsilon and R[1] >= epsilon and R[2] >= epsilon
else:
return True
def inSST(self,
vector,
proper = False,
color = False):
"""
Check whether given vector falls into standard stereographic triangle of own symmetry.
proper considers only vectors with z >= 0, hence uses two neighboring SSTs.
Return inverse pole figure color if requested.
Bases are computed from
basis = {'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
[1.,0.,1.]/np.sqrt(2.), # direction of green
[1.,1.,1.]/np.sqrt(3.)]).T), # direction of blue
'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
[1.,0.,0.], # direction of green
[np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # direction of blue
'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
[1.,0.,0.], # direction of green
[1.,1.,0.]/np.sqrt(2.)]).T), # direction of blue
'orthorhombic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
[1.,0.,0.], # direction of green
[0.,1.,0.]]).T), # direction of blue
}
"""
if self.lattice == '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.lattice == '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.lattice == '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.lattice == '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
if color:
return (True,np.zeros(3,'d'))
else:
return True
v = np.array(vector,dtype=float)
if proper: # check both improper ...
theComponents = np.dot(basis['improper'],v)
inSST = np.all(theComponents >= 0.0)
if not inSST: # ... and proper SST
theComponents = np.dot(basis['proper'],v)
inSST = np.all(theComponents >= 0.0)
else:
v[2] = abs(v[2]) # z component projects identical
theComponents = np.dot(basis['improper'],v) # for positive and negative values
inSST = np.all(theComponents >= 0.0)
if color: # have to return color array
if inSST:
rgb = np.power(theComponents/np.linalg.norm(theComponents),0.5) # smoothen color ramps
rgb = np.minimum(np.ones(3,dtype=float),rgb) # limit to maximum intensity
rgb /= max(rgb) # normalize to (HS)V = 1
else:
rgb = np.zeros(3,dtype=float)
return (inSST,rgb)
else:
return inSST
# code derived from https://github.com/ezag/pyeuclid
# suggested reading: http://web.mit.edu/2.998/www/QuaternionReport1.pdf
# ******************************************************************************************
class Lattice:
"""
Lattice system
Currently, this contains only a mapping from Bravais lattice to symmetry
and orientation relationships. It could include twin and slip systems.
https://en.wikipedia.org/wiki/Bravais_lattice
"""
lattices = {
'triclinic':{'symmetry':None},
'bct':{'symmetry':'tetragonal'},
'hex':{'symmetry':'hexagonal'},
'fcc':{'symmetry':'cubic','c/a':1.0},
'bcc':{'symmetry':'cubic','c/a':1.0},
}
def __init__(self, lattice):
self.lattice = lattice
self.symmetry = Symmetry(self.lattices[lattice]['symmetry'])
def __repr__(self):
"""Report basic lattice information"""
return 'Bravais lattice {} ({} symmetry)'.format(self.lattice,self.symmetry)
# Kurdjomov--Sachs orientation relationship for fcc <-> bcc transformation
# from S. Morito et al. Journal of Alloys and Compounds 577 (2013) 587-S592
# also see K. Kitahara et al. Acta Materialia 54 (2006) 1279-1288
KS = {'mapping':{'fcc':0,'bcc':1},
'planes': 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'),
'directions': 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')}
# Greninger--Troiano orientation relationship for fcc <-> bcc transformation
# from Y. He et al. Journal of Applied Crystallography 39 (2006) 72-81
GT = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 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],[ 0, -1, 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],[ 0, -1, 1]],
[[ 1, -1, 1],[ 1, 0, 1]]],dtype='float'),
'directions': np.array([
[[ -5,-12, 17],[-17, -7, 17]],
[[ 17, -5,-12],[ 17,-17, -7]],
[[-12, 17, -5],[ -7, 17,-17]],
[[ 5, 12, 17],[ 17, 7, 17]],
[[-17, 5,-12],[-17, 17, -7]],
[[ 12,-17, -5],[ 7,-17,-17]],
[[ -5, 12,-17],[-17, 7,-17]],
[[ 17, 5, 12],[ 17, 17, 7]],
[[-12,-17, 5],[ -7,-17, 17]],
[[ 5,-12,-17],[ 17, -7,-17]],
[[-17, -5, 12],[-17,-17, 7]],
[[ 12, 17, 5],[ 7, 17, 17]],
[[ -5, 17,-12],[-17, 17, -7]],
[[-12, -5, 17],[ -7,-17, 17]],
[[ 17,-12, -5],[ 17, -7,-17]],
[[ 5,-17,-12],[ 17,-17, -7]],
[[ 12, 5, 17],[ 7, 17, 17]],
[[-17, 12, -5],[-17, 7,-17]],
[[ -5,-17, 12],[-17,-17, 7]],
[[-12, 5,-17],[ -7, 17,-17]],
[[ 17, 12, 5],[ 17, 7, 17]],
[[ 5, 17, 12],[ 17, 17, 7]],
[[ 12, -5,-17],[ 7,-17,-17]],
[[-17,-12, 5],[-17, 7, 17]]],dtype='float')}
# Greninger--Troiano' orientation relationship for fcc <-> bcc transformation
# from Y. He et al. Journal of Applied Crystallography 39 (2006) 72-81
GTprime = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 7, 17, 17],[ 12, 5, 17]],
[[ 17, 7, 17],[ 17, 12, 5]],
[[ 17, 17, 7],[ 5, 17, 12]],
[[ -7,-17, 17],[-12, -5, 17]],
[[-17, -7, 17],[-17,-12, 5]],
[[-17,-17, 7],[ -5,-17, 12]],
[[ 7,-17,-17],[ 12, -5,-17]],
[[ 17, -7,-17],[ 17,-12, -5]],
[[ 17,-17, -7],[ 5,-17,-12]],
[[ -7, 17,-17],[-12, 5,-17]],
[[-17, 7,-17],[-17, 12, -5]],
[[-17, 17, -7],[ -5, 17,-12]],
[[ 7, 17, 17],[ 12, 17, 5]],
[[ 17, 7, 17],[ 5, 12, 17]],
[[ 17, 17, 7],[ 17, 5, 12]],
[[ -7,-17, 17],[-12,-17, 5]],
[[-17, -7, 17],[ -5,-12, 17]],
[[-17,-17, 7],[-17, -5, 12]],
[[ 7,-17,-17],[ 12,-17, -5]],
[[ 17, -7,-17],[ 5, -12,-17]],
[[ 17,-17, 7],[ 17, -5,-12]],
[[ -7, 17,-17],[-12, 17, -5]],
[[-17, 7,-17],[ -5, 12,-17]],
[[-17, 17, -7],[-17, 5,-12]]],dtype='float'),
'directions': 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]],
[[ 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]]],dtype='float')}
# Nishiyama--Wassermann orientation relationship for fcc <-> bcc transformation
# from H. Kitahara et al. Materials Characterization 54 (2005) 378-386
NW = {'mapping':{'fcc':0,'bcc':1},
'planes': 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]]],dtype='float'),
'directions': np.array([
[[ 2, -1, -1],[ 0, -1, 1]],
[[ -1, 2, -1],[ 0, -1, 1]],
[[ -1, -1, 2],[ 0, -1, 1]],
[[ -2, -1, -1],[ 0, -1, 1]],
[[ 1, 2, -1],[ 0, -1, 1]],
[[ 1, -1, 2],[ 0, -1, 1]],
[[ 2, 1, -1],[ 0, -1, 1]],
[[ -1, -2, -1],[ 0, -1, 1]],
[[ -1, 1, 2],[ 0, -1, 1]],
[[ -1, 2, 1],[ 0, -1, 1]],
[[ -1, 2, 1],[ 0, -1, 1]],
[[ -1, -1, -2],[ 0, -1, 1]]],dtype='float')}
# Pitsch orientation relationship for fcc <-> bcc transformation
# from Y. He et al. Acta Materialia 53 (2005) 1179-1190
Pitsch = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 0, 1, 0],[ -1, 0, 1]],
[[ 0, 0, 1],[ 1, -1, 0]],
[[ 1, 0, 0],[ 0, 1, -1]],
[[ 1, 0, 0],[ 0, -1, -1]],
[[ 0, 1, 0],[ -1, 0, -1]],
[[ 0, 0, 1],[ -1, -1, 0]],
[[ 0, 1, 0],[ -1, 0, -1]],
[[ 0, 0, 1],[ -1, -1, 0]],
[[ 1, 0, 0],[ 0, -1, -1]],
[[ 1, 0, 0],[ 0, -1, 1]],
[[ 0, 1, 0],[ 1, 0, -1]],
[[ 0, 0, 1],[ -1, 1, 0]]],dtype='float'),
'directions': np.array([
[[ 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],[ 1, 1, -1]]],dtype='float')}
# Bain orientation relationship for fcc <-> bcc transformation
# from Y. He et al./Journal of Applied Crystallography (2006). 39, 72-81
Bain = {'mapping':{'fcc':0,'bcc':1},
'planes': np.array([
[[ 1, 0, 0],[ 1, 0, 0]],
[[ 0, 1, 0],[ 0, 1, 0]],
[[ 0, 0, 1],[ 0, 0, 1]]],dtype='float'),
'directions': np.array([
[[ 0, 1, 0],[ 0, 1, 1]],
[[ 0, 0, 1],[ 1, 0, 1]],
[[ 1, 0, 0],[ 1, 1, 0]]],dtype='float')}
def relationOperations(self,model):
models={'KS':self.KS, 'GT':self.GT, "GT'":self.GTprime,
'NW':self.NW, 'Pitsch': self.Pitsch, 'Bain':self.Bain}
try:
relationship = models[model]
except:
raise KeyError('Orientation relationship "{}" is unknown'.format(model))
if self.lattice not in relationship['mapping']:
raise ValueError('Relationship "{}" not supported for lattice "{}"'.format(model,self.lattice))
r = {'lattice':Lattice((set(relationship['mapping'])-{self.lattice}).pop()), # target lattice
'rotations':[] }
myPlane_id = relationship['mapping'][self.lattice]
otherPlane_id = (myPlane_id+1)%2
myDir_id = myPlane_id +2
otherDir_id = otherPlane_id +2
for miller in np.hstack((relationship['planes'],relationship['directions'])):
myPlane = miller[myPlane_id]/ np.linalg.norm(miller[myPlane_id])
myDir = miller[myDir_id]/ np.linalg.norm(miller[myDir_id])
myMatrix = np.array([myDir,np.cross(myPlane,myDir),myPlane]).T
otherPlane = miller[otherPlane_id]/ np.linalg.norm(miller[otherPlane_id])
otherDir = miller[otherDir_id]/ np.linalg.norm(miller[otherDir_id])
otherMatrix = np.array([otherDir,np.cross(otherPlane,otherDir),otherPlane]).T
r['rotations'].append(Rotation.fromMatrix(np.dot(otherMatrix,myMatrix.T)))
return r
class Orientation:
"""
Crystallographic orientation
A crystallographic orientation contains a rotation and a lattice
"""
__slots__ = ['rotation','lattice']
def __repr__(self):
"""Report lattice type and orientation"""
return self.lattice.__repr__()+'\n'+self.rotation.__repr__()
def __init__(self, rotation, lattice):
if isinstance(lattice, Lattice):
self.lattice = lattice
else:
self.lattice = Lattice(lattice) # assume string
if isinstance(rotation, Rotation):
self.rotation = rotation
else:
self.rotation = Rotation(rotation) # assume quaternion
def disorientation(self,
other,
SST = True,
symmetries = False):
"""
Disorientation between myself and given other orientation.
Rotation axis falls into SST if SST == True.
(Currently requires same symmetry for both orientations.
Look into A. Heinz and P. Neumann 1991 for cases with differing sym.)
"""
if self.lattice.symmetry != other.lattice.symmetry:
raise NotImplementedError('disorientation between different symmetry classes not supported yet.')
mySymEqs = self.equivalentOrientations() if SST else self.equivalentOrientations([0]) # take all or only first sym operation
otherSymEqs = other.equivalentOrientations()
for i,sA in enumerate(mySymEqs):
aInv = sA.rotation.inversed()
for j,sB in enumerate(otherSymEqs):
b = sB.rotation
r = b*aInv
for k in range(2):
r.inverse()
breaker = self.lattice.symmetry.inFZ(r.asRodrigues(vector=True)) \
and (not SST or other.lattice.symmetry.inDisorientationSST(r.asRodrigues(vector=True)))
if breaker: break
if breaker: break
if breaker: break
return (Orientation(r,self.lattice), i,j, k == 1) if symmetries else r # disorientation ...
# ... own sym, other sym,
# self-->other: True, self<--other: False
def inFZ(self):
return self.lattice.symmetry.inFZ(self.rotation.asRodrigues(vector=True))
def equivalentOrientations(self,members=[]):
"""List of orientations which are symmetrically equivalent"""
try:
iter(members) # asking for (even empty) list of members?
except TypeError:
return self.__class__(self.lattice.symmetry.symmetryOperations(members)*self.rotation,self.lattice) # no, return rotation object
else:
return [self.__class__(q*self.rotation,self.lattice) \
for q in self.lattice.symmetry.symmetryOperations(members)] # yes, return list of rotations
def relatedOrientations(self,model):
"""List of orientations related by the given orientation relationship"""
r = self.lattice.relationOperations(model)
return [self.__class__(self.rotation*o,r['lattice']) for o in r['rotations']]
def reduced(self):
"""Transform orientation to fall into fundamental zone according to symmetry"""
for me in self.equivalentOrientations():
if self.lattice.symmetry.inFZ(me.rotation.asRodrigues(vector=True)): break
return self.__class__(me.rotation,self.lattice)
def inversePole(self,
axis,
proper = False,
SST = True):
"""Axis rotated according to orientation (using crystal symmetry to ensure location falls into SST)"""
if SST: # pole requested to be within SST
for i,o in enumerate(self.equivalentOrientations()): # test all symmetric equivalent quaternions
pole = o.rotation*axis # align crystal direction to axis
if self.lattice.symmetry.inSST(pole,proper): break # found SST version
else:
pole = self.rotation*axis # align crystal direction to axis
return (pole,i if SST else 0)
def IPFcolor(self,axis):
"""TSL color of inverse pole figure for given axis"""
color = np.zeros(3,'d')
for o in self.equivalentOrientations():
pole = o.rotation*axis # align crystal direction to axis
inSST,color = self.lattice.symmetry.inSST(pole,color=True)
if inSST: break
return color
@classmethod
def fromAverage(cls,
orientations,
weights = []):
"""Create orientation from average of list of orientations"""
if not all(isinstance(item, Orientation) for item in orientations):
raise TypeError("Only instances of Orientation can be averaged.")
closest = []
ref = orientations[0]
for o in orientations:
closest.append(o.equivalentOrientations(
ref.disorientation(o,
SST = False, # select (o[ther]'s) sym orientation
symmetries = True)[2]).rotation) # with lowest misorientation
return Orientation(Rotation.fromAverage(closest,weights),ref.lattice)
def average(self,other):
"""Calculate the average rotation"""
return Orientation.fromAverage([self,other])
####################################################################################################
# Code below available according to the following conditions on https://github.com/MarDiehl/3Drotations
####################################################################################################
# Copyright (c) 2017-2019, Martin Diehl/Max-Planck-Institut für Eisenforschung GmbH
# Copyright (c) 2013-2014, Marc De Graef/Carnegie Mellon University
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are
# permitted provided that the following conditions are met:
#
# - Redistributions of source code must retain the above copyright notice, this list
# of conditions and the following disclaimer.
# - Redistributions in binary form must reproduce the above copyright notice, this
# list of conditions and the following disclaimer in the documentation and/or
# other materials provided with the distribution.
# - Neither the names of Marc De Graef, Carnegie Mellon University nor the names
# of its contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
# USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
####################################################################################################
def isone(a):
return np.isclose(a,1.0,atol=1.0e-7,rtol=0.0)
def iszero(a):
return np.isclose(a,0.0,atol=1.0e-12,rtol=0.0)
#---------- quaternion ----------
def qu2om(qu):
"""Quaternion to orientation matrix"""
qq = qu[0]**2-(qu[1]**2 + qu[2]**2 + qu[3]**2)
om = np.diag(qq + 2.0*np.array([qu[1],qu[2],qu[3]])**2)
om[1,0] = 2.0*(qu[2]*qu[1]+qu[0]*qu[3])
om[0,1] = 2.0*(qu[1]*qu[2]-qu[0]*qu[3])
om[2,1] = 2.0*(qu[3]*qu[2]+qu[0]*qu[1])
om[1,2] = 2.0*(qu[2]*qu[3]-qu[0]*qu[1])
om[0,2] = 2.0*(qu[1]*qu[3]+qu[0]*qu[2])
om[2,0] = 2.0*(qu[3]*qu[1]-qu[0]*qu[2])
return om if P > 0.0 else om.T
def qu2eu(qu):
"""Quaternion to Euler angles"""
q03 = qu[0]**2+qu[3]**2
q12 = qu[1]**2+qu[2]**2
chi = np.sqrt(q03*q12)
if iszero(chi):
eu = np.array([np.arctan2(-P*2.0*qu[0]*qu[3],qu[0]**2-qu[3]**2), 0.0, 0.0]) if iszero(q12) else \
np.array([np.arctan2(2.0*qu[1]*qu[2],qu[1]**2-qu[2]**2), np.pi, 0.0])
else:
eu = np.array([np.arctan2((-P*qu[0]*qu[2]+qu[1]*qu[3])*chi, (-P*qu[0]*qu[1]-qu[2]*qu[3])*chi ),
np.arctan2( 2.0*chi, q03-q12 ),
np.arctan2(( P*qu[0]*qu[2]+qu[1]*qu[3])*chi, (-P*qu[0]*qu[1]+qu[2]*qu[3])*chi )])
# reduce Euler angles to definition range, i.e a lower limit of 0.0
eu = np.where(eu<0, (eu+2.0*np.pi)%np.array([2.0*np.pi,np.pi,2.0*np.pi]),eu)
return eu
def qu2ax(qu):
"""
Quaternion to axis angle
Modified version of the original formulation, should be numerically more stable
"""
if iszero(qu[1]**2+qu[2]**2+qu[3]**2): # set axis to [001] if the angle is 0/360
ax = [ 0.0, 0.0, 1.0, 0.0 ]
elif not iszero(qu[0]):
s = np.sign(qu[0])/np.sqrt(qu[1]**2+qu[2]**2+qu[3]**2)
omega = 2.0 * np.arccos(np.clip(qu[0],-1.0,1.0))
ax = [ qu[1]*s, qu[2]*s, qu[3]*s, omega ]
else:
ax = [ qu[1], qu[2], qu[3], np.pi]
return np.array(ax)
def qu2ro(qu):
"""Quaternion to Rodrigues vector"""
if iszero(qu[0]):
ro = [qu[1], qu[2], qu[3], np.inf]
else:
s = np.linalg.norm([qu[1],qu[2],qu[3]])
ro = [0.0,0.0,P,0.0] if iszero(s) else \
[ qu[1]/s, qu[2]/s, qu[3]/s, np.tan(np.arccos(np.clip(qu[0],-1.0,1.0)))] # avoid numerical difficulties
return np.array(ro)
def qu2ho(qu):
"""Quaternion to homochoric"""
omega = 2.0 * np.arccos(np.clip(qu[0],-1.0,1.0)) # avoid numerical difficulties
if iszero(omega):
ho = np.array([ 0.0, 0.0, 0.0 ])
else:
ho = np.array([qu[1], qu[2], qu[3]])
f = 0.75 * ( omega - np.sin(omega) )
ho = ho/np.linalg.norm(ho) * f**(1./3.)
return ho
def qu2cu(qu):
"""Quaternion to cubochoric"""
return ho2cu(qu2ho(qu))
#---------- orientation matrix ----------
def om2qu(om):
"""
Orientation matrix to quaternion
The original formulation (direct conversion) had (numerical?) issues
"""
return eu2qu(om2eu(om))
def om2eu(om):
"""Orientation matrix to Euler angles"""
if abs(om[2,2]) < 1.0:
zeta = 1.0/np.sqrt(1.0-om[2,2]**2)
eu = np.array([np.arctan2(om[2,0]*zeta,-om[2,1]*zeta),
np.arccos(om[2,2]),
np.arctan2(om[0,2]*zeta, om[1,2]*zeta)])
else:
eu = np.array([np.arctan2( om[0,1],om[0,0]), np.pi*0.5*(1-om[2,2]),0.0]) # following the paper, not the reference implementation
# reduce Euler angles to definition range, i.e a lower limit of 0.0
eu = np.where(eu<0, (eu+2.0*np.pi)%np.array([2.0*np.pi,np.pi,2.0*np.pi]),eu)
return eu
def om2ax(om):
"""Orientation matrix to axis angle"""
ax=np.empty(4)
# first get the rotation angle
t = 0.5*(om.trace() -1.0)
ax[3] = np.arccos(np.clip(t,-1.0,1.0))
if iszero(ax[3]):
ax = [ 0.0, 0.0, 1.0, 0.0]
else:
w,vr = np.linalg.eig(om)
# next, find the eigenvalue (1,0j)
i = np.where(np.isclose(w,1.0+0.0j))[0][0]
ax[0:3] = np.real(vr[0:3,i])
diagDelta = np.array([om[1,2]-om[2,1],om[2,0]-om[0,2],om[0,1]-om[1,0]])
ax[0:3] = np.where(iszero(diagDelta), ax[0:3],np.abs(ax[0:3])*np.sign(-P*diagDelta))
return np.array(ax)
def om2ro(om):
"""Orientation matrix to Rodriques vector"""
return eu2ro(om2eu(om))
def om2ho(om):
"""Orientation matrix to homochoric"""
return ax2ho(om2ax(om))
def om2cu(om):
"""Orientation matrix to cubochoric"""
return ho2cu(om2ho(om))
#---------- Euler angles ----------
def eu2qu(eu):
"""Euler angles to quaternion"""
ee = 0.5*eu
cPhi = np.cos(ee[1])
sPhi = np.sin(ee[1])
qu = np.array([ cPhi*np.cos(ee[0]+ee[2]),
-P*sPhi*np.cos(ee[0]-ee[2]),
-P*sPhi*np.sin(ee[0]-ee[2]),
-P*cPhi*np.sin(ee[0]+ee[2]) ])
if qu[0] < 0.0: qu*=-1
return qu
def eu2om(eu):
"""Euler angles to orientation matrix"""
c = np.cos(eu)
s = np.sin(eu)
om = np.array([[+c[0]*c[2]-s[0]*s[2]*c[1], +s[0]*c[2]+c[0]*s[2]*c[1], +s[2]*s[1]],
[-c[0]*s[2]-s[0]*c[2]*c[1], -s[0]*s[2]+c[0]*c[2]*c[1], +c[2]*s[1]],
[+s[0]*s[1], -c[0]*s[1], +c[1] ]])
om[np.where(iszero(om))] = 0.0
return om
def eu2ax(eu):
"""Euler angles to axis angle"""
t = np.tan(eu[1]*0.5)
sigma = 0.5*(eu[0]+eu[2])
delta = 0.5*(eu[0]-eu[2])
tau = np.linalg.norm([t,np.sin(sigma)])
alpha = np.pi if iszero(np.cos(sigma)) else \
2.0*np.arctan(tau/np.cos(sigma))
if iszero(alpha):
ax = np.array([ 0.0, 0.0, 1.0, 0.0 ])
else:
ax = -P/tau * np.array([ t*np.cos(delta), t*np.sin(delta), np.sin(sigma) ]) # passive axis-angle pair so a minus sign in front
ax = np.append(ax,alpha)
if alpha < 0.0: ax *= -1.0 # ensure alpha is positive
return ax
def eu2ro(eu):
"""Euler angles to Rodrigues vector"""
ro = eu2ax(eu) # convert to axis angle representation
if ro[3] >= np.pi: # Differs from original implementation. check convention 5
ro[3] = np.inf
elif iszero(ro[3]):
ro = np.array([ 0.0, 0.0, P, 0.0 ])
else:
ro[3] = np.tan(ro[3]*0.5)
return ro
def eu2ho(eu):
"""Euler angles to homochoric"""
return ax2ho(eu2ax(eu))
def eu2cu(eu):
"""Euler angles to cubochoric"""
return ho2cu(eu2ho(eu))
#---------- axis angle ----------
def ax2qu(ax):
"""Axis angle to quaternion"""
if iszero(ax[3]):
qu = np.array([ 1.0, 0.0, 0.0, 0.0 ])
else:
c = np.cos(ax[3]*0.5)
s = np.sin(ax[3]*0.5)
qu = np.array([ c, ax[0]*s, ax[1]*s, ax[2]*s ])
return qu
def ax2om(ax):
"""Axis angle to orientation matrix"""
c = np.cos(ax[3])
s = np.sin(ax[3])
omc = 1.0-c
om=np.diag(ax[0:3]**2*omc + c)
for idx in [[0,1,2],[1,2,0],[2,0,1]]:
q = omc*ax[idx[0]] * ax[idx[1]]
om[idx[0],idx[1]] = q + s*ax[idx[2]]
om[idx[1],idx[0]] = q - s*ax[idx[2]]
return om if P < 0.0 else om.T
def ax2eu(ax):
"""Orientation matrix to Euler angles"""
return om2eu(ax2om(ax))
def ax2ro(ax):
"""Axis angle to Rodrigues vector"""
if iszero(ax[3]):
ro = [ 0.0, 0.0, P, 0.0 ]
else:
ro = [ax[0], ax[1], ax[2]]
# 180 degree case
ro += [np.inf] if np.isclose(ax[3],np.pi,atol=1.0e-15,rtol=0.0) else \
[np.tan(ax[3]*0.5)]
return np.array(ro)
def ax2ho(ax):
"""Axis angle to homochoric"""
f = (0.75 * ( ax[3] - np.sin(ax[3]) ))**(1.0/3.0)
ho = ax[0:3] * f
return ho
def ax2cu(ax):
"""Axis angle to cubochoric"""
return ho2cu(ax2ho(ax))
#---------- Rodrigues--Frank ----------
def ro2qu(ro):
"""Rodrigues vector to quaternion"""
return ax2qu(ro2ax(ro))
def ro2om(ro):
"""Rodgrigues vector to orientation matrix"""
return ax2om(ro2ax(ro))
def ro2eu(ro):
"""Rodrigues vector to orientation matrix"""
return om2eu(ro2om(ro))
def ro2ax(ro):
"""Rodrigues vector to axis angle"""
ta = ro[3]
if iszero(ta):
ax = [ 0.0, 0.0, 1.0, 0.0 ]
elif not np.isfinite(ta):
ax = [ ro[0], ro[1], ro[2], np.pi ]
else:
angle = 2.0*np.arctan(ta)
ta = 1.0/np.linalg.norm(ro[0:3])
ax = [ ro[0]/ta, ro[1]/ta, ro[2]/ta, angle ]
return np.array(ax)
def ro2ho(ro):
"""Rodrigues vector to homochoric"""
if iszero(np.sum(ro[0:3]**2.0)):
ho = [ 0.0, 0.0, 0.0 ]
else:
f = 2.0*np.arctan(ro[3]) -np.sin(2.0*np.arctan(ro[3])) if np.isfinite(ro[3]) else np.pi
ho = ro[0:3] * (0.75*f)**(1.0/3.0)
return np.array(ho)
def ro2cu(ro):
"""Rodrigues vector to cubochoric"""
return ho2cu(ro2ho(ro))
#---------- homochoric ----------
def ho2qu(ho):
"""Homochoric to quaternion"""
return ax2qu(ho2ax(ho))
def ho2om(ho):
"""Homochoric to orientation matrix"""
return ax2om(ho2ax(ho))
def ho2eu(ho):
"""Homochoric to Euler angles"""
return ax2eu(ho2ax(ho))
def ho2ax(ho):
"""Homochoric to axis angle"""
tfit = np.array([+1.0000000000018852, -0.5000000002194847,
-0.024999992127593126, -0.003928701544781374,
-0.0008152701535450438, -0.0002009500426119712,
-0.00002397986776071756, -0.00008202868926605841,
+0.00012448715042090092, -0.0001749114214822577,
+0.0001703481934140054, -0.00012062065004116828,
+0.000059719705868660826, -0.00001980756723965647,
+0.000003953714684212874, -0.00000036555001439719544])
# normalize h and store the magnitude
hmag_squared = np.sum(ho**2.)
if iszero(hmag_squared):
ax = np.array([ 0.0, 0.0, 1.0, 0.0 ])
else:
hm = hmag_squared
# convert the magnitude to the rotation angle
s = tfit[0] + tfit[1] * hmag_squared
for i in range(2,16):
hm *= hmag_squared
s += tfit[i] * hm
ax = np.append(ho/np.sqrt(hmag_squared),2.0*np.arccos(np.clip(s,-1.0,1.0)))
return ax
def ho2ro(ho):
"""Axis angle to Rodriques vector"""
return ax2ro(ho2ax(ho))
def ho2cu(ho):
"""Homochoric to cubochoric"""
return Lambert.BallToCube(ho)
#---------- cubochoric ----------
def cu2qu(cu):
"""Cubochoric to quaternion"""
return ho2qu(cu2ho(cu))
def cu2om(cu):
"""Cubochoric to orientation matrix"""
return ho2om(cu2ho(cu))
def cu2eu(cu):
"""Cubochoric to Euler angles"""
return ho2eu(cu2ho(cu))
def cu2ax(cu):
"""Cubochoric to axis angle"""
return ho2ax(cu2ho(cu))
def cu2ro(cu):
"""Cubochoric to Rodrigues vector"""
return ho2ro(cu2ho(cu))
def cu2ho(cu):
"""Cubochoric to homochoric"""
return Lambert.CubeToBall(cu)