641 lines
28 KiB
Python
641 lines
28 KiB
Python
import numpy as np
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from . import Rotation
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class Symmetry:
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"""
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Symmetry operations for lattice systems.
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References
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----------
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https://en.wikipedia.org/wiki/Crystal_system
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"""
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lattices = [None,'orthorhombic','tetragonal','hexagonal','cubic',]
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def __init__(self, symmetry = None):
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"""
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Symmetry Definition.
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Parameters
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----------
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symmetry : str, optional
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label of the crystal system
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"""
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if symmetry is not None and symmetry.lower() not in Symmetry.lattices:
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raise KeyError(f'Symmetry/crystal system "{symmetry}" is unknown')
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self.lattice = symmetry.lower() if isinstance(symmetry,str) else symmetry
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def __copy__(self):
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"""Copy."""
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return self.__class__(self.lattice)
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copy = __copy__
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def __repr__(self):
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"""Readable string."""
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return f'{self.lattice}'
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def __eq__(self, other):
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"""
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Equal to other.
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Parameters
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----------
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other : Symmetry
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Symmetry to check for equality.
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"""
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return self.lattice == other.lattice
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def __neq__(self, other):
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"""
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Not Equal to other.
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Parameters
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----------
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other : Symmetry
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Symmetry to check for inequality.
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"""
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return not self.__eq__(other)
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def __cmp__(self,other):
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"""
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Linear ordering.
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Parameters
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----------
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other : Symmetry
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Symmetry to check for for order.
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"""
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myOrder = Symmetry.lattices.index(self.lattice)
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otherOrder = Symmetry.lattices.index(other.lattice)
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return (myOrder > otherOrder) - (myOrder < otherOrder)
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def symmetryOperations(self,members=[]):
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"""List (or single element) of symmetry operations as rotations."""
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if self.lattice == 'cubic':
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symQuats = [
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[ 1.0, 0.0, 0.0, 0.0 ],
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[ 0.0, 1.0, 0.0, 0.0 ],
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[ 0.0, 0.0, 1.0, 0.0 ],
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[ 0.0, 0.0, 0.0, 1.0 ],
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[ 0.0, 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2) ],
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[ 0.0, 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2) ],
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[ 0.0, 0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2) ],
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[ 0.0, 0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2) ],
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[ 0.0, 0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
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[ 0.0, -0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0 ],
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[ 0.5, 0.5, 0.5, 0.5 ],
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[-0.5, 0.5, 0.5, 0.5 ],
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[-0.5, 0.5, 0.5, -0.5 ],
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[-0.5, 0.5, -0.5, 0.5 ],
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[-0.5, -0.5, 0.5, 0.5 ],
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[-0.5, -0.5, 0.5, -0.5 ],
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[-0.5, -0.5, -0.5, 0.5 ],
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[-0.5, 0.5, -0.5, -0.5 ],
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[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
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[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
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[-0.5*np.sqrt(2), 0.0, 0.5*np.sqrt(2), 0.0 ],
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[-0.5*np.sqrt(2), 0.0, -0.5*np.sqrt(2), 0.0 ],
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[-0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0, 0.0 ],
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[-0.5*np.sqrt(2),-0.5*np.sqrt(2), 0.0, 0.0 ],
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]
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elif self.lattice == 'hexagonal':
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symQuats = [
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[ 1.0, 0.0, 0.0, 0.0 ],
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[-0.5*np.sqrt(3), 0.0, 0.0, -0.5 ],
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[ 0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
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[ 0.0, 0.0, 0.0, 1.0 ],
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[-0.5, 0.0, 0.0, 0.5*np.sqrt(3) ],
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[-0.5*np.sqrt(3), 0.0, 0.0, 0.5 ],
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[ 0.0, 1.0, 0.0, 0.0 ],
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[ 0.0, -0.5*np.sqrt(3), 0.5, 0.0 ],
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[ 0.0, 0.5, -0.5*np.sqrt(3), 0.0 ],
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[ 0.0, 0.0, 1.0, 0.0 ],
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[ 0.0, -0.5, -0.5*np.sqrt(3), 0.0 ],
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[ 0.0, 0.5*np.sqrt(3), 0.5, 0.0 ],
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]
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elif self.lattice == 'tetragonal':
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symQuats = [
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[ 1.0, 0.0, 0.0, 0.0 ],
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[ 0.0, 1.0, 0.0, 0.0 ],
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[ 0.0, 0.0, 1.0, 0.0 ],
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[ 0.0, 0.0, 0.0, 1.0 ],
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[ 0.0, 0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
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[ 0.0, -0.5*np.sqrt(2), 0.5*np.sqrt(2), 0.0 ],
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[ 0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
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[-0.5*np.sqrt(2), 0.0, 0.0, 0.5*np.sqrt(2) ],
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]
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elif self.lattice == 'orthorhombic':
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symQuats = [
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[ 1.0,0.0,0.0,0.0 ],
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[ 0.0,1.0,0.0,0.0 ],
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[ 0.0,0.0,1.0,0.0 ],
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[ 0.0,0.0,0.0,1.0 ],
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]
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else:
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symQuats = [
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[ 1.0,0.0,0.0,0.0 ],
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]
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symOps = list(map(Rotation,
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np.array(symQuats)[np.atleast_1d(members) if members != [] else range(len(symQuats))]))
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try:
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iter(members) # asking for (even empty) list of members?
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except TypeError:
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return symOps[0] # no, return rotation object
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else:
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return symOps # yes, return list of rotations
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def inFZ(self,rodrigues):
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"""
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Check whether given Rodrigues-Frank vector falls into fundamental zone of own symmetry.
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Fundamental zone in Rodrigues space is point symmetric around origin.
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"""
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if (len(rodrigues) != 3):
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raise ValueError('Input is not a Rodrigues-Frank vector.\n')
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if np.any(rodrigues == np.inf): return False
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Rabs = abs(rodrigues)
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if self.lattice == 'cubic':
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return np.sqrt(2.0)-1.0 >= Rabs[0] \
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and np.sqrt(2.0)-1.0 >= Rabs[1] \
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and np.sqrt(2.0)-1.0 >= Rabs[2] \
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and 1.0 >= Rabs[0] + Rabs[1] + Rabs[2]
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elif self.lattice == 'hexagonal':
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return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] and 1.0 >= Rabs[2] \
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and 2.0 >= np.sqrt(3)*Rabs[0] + Rabs[1] \
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and 2.0 >= np.sqrt(3)*Rabs[1] + Rabs[0] \
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and 2.0 >= np.sqrt(3) + Rabs[2]
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elif self.lattice == 'tetragonal':
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return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] \
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and np.sqrt(2.0) >= Rabs[0] + Rabs[1] \
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and np.sqrt(2.0) >= Rabs[2] + 1.0
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elif self.lattice == 'orthorhombic':
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return 1.0 >= Rabs[0] and 1.0 >= Rabs[1] and 1.0 >= Rabs[2]
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else:
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return True
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def inDisorientationSST(self,rodrigues):
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"""
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Check whether given Rodrigues-Frank vector (of misorientation) falls into standard stereographic triangle of own symmetry.
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References
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----------
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A. Heinz and P. Neumann, Acta Crystallographica Section A 47:780-789, 1991
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https://doi.org/10.1107/S0108767391006864
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"""
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if (len(rodrigues) != 3):
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raise ValueError('Input is not a Rodrigues-Frank vector.\n')
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R = rodrigues
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epsilon = 0.0
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if self.lattice == 'cubic':
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return R[0] >= R[1]+epsilon and R[1] >= R[2]+epsilon and R[2] >= epsilon
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elif self.lattice == 'hexagonal':
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return R[0] >= np.sqrt(3)*(R[1]-epsilon) and R[1] >= epsilon and R[2] >= epsilon
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elif self.lattice == 'tetragonal':
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return R[0] >= R[1]-epsilon and R[1] >= epsilon and R[2] >= epsilon
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elif self.lattice == 'orthorhombic':
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return R[0] >= epsilon and R[1] >= epsilon and R[2] >= epsilon
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else:
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return True
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def inSST(self,
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vector,
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proper = False,
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color = False):
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"""
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Check whether given vector falls into standard stereographic triangle of own symmetry.
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proper considers only vectors with z >= 0, hence uses two neighboring SSTs.
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Return inverse pole figure color if requested.
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Bases are computed from
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>>> basis = {'cubic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
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... [1.,0.,1.]/np.sqrt(2.), # direction of green
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... [1.,1.,1.]/np.sqrt(3.)]).T), # direction of blue
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... 'hexagonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
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... [1.,0.,0.], # direction of green
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... [np.sqrt(3.),1.,0.]/np.sqrt(4.)]).T), # direction of blue
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... 'tetragonal' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red
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... [1.,0.,0.], # direction of green
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... [1.,1.,0.]/np.sqrt(2.)]).T), # direction of blue
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... 'orthorhombic': np.linalg.inv(np.array([[0.,0.,1.], # direction of red
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... [1.,0.,0.], # direction of green
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... [0.,1.,0.]]).T), # direction of blue
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... }
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"""
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if self.lattice == 'cubic':
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basis = {'improper':np.array([ [-1. , 0. , 1. ],
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[ np.sqrt(2.) , -np.sqrt(2.) , 0. ],
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[ 0. , np.sqrt(3.) , 0. ] ]),
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'proper':np.array([ [ 0. , -1. , 1. ],
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[-np.sqrt(2.) , np.sqrt(2.) , 0. ],
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[ np.sqrt(3.) , 0. , 0. ] ]),
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}
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elif self.lattice == 'hexagonal':
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basis = {'improper':np.array([ [ 0. , 0. , 1. ],
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[ 1. , -np.sqrt(3.) , 0. ],
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[ 0. , 2. , 0. ] ]),
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'proper':np.array([ [ 0. , 0. , 1. ],
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[-1. , np.sqrt(3.) , 0. ],
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[ np.sqrt(3.) , -1. , 0. ] ]),
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}
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elif self.lattice == 'tetragonal':
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basis = {'improper':np.array([ [ 0. , 0. , 1. ],
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[ 1. , -1. , 0. ],
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[ 0. , np.sqrt(2.) , 0. ] ]),
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'proper':np.array([ [ 0. , 0. , 1. ],
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[-1. , 1. , 0. ],
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[ np.sqrt(2.) , 0. , 0. ] ]),
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}
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elif self.lattice == 'orthorhombic':
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basis = {'improper':np.array([ [ 0., 0., 1.],
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[ 1., 0., 0.],
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[ 0., 1., 0.] ]),
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'proper':np.array([ [ 0., 0., 1.],
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[-1., 0., 0.],
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[ 0., 1., 0.] ]),
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}
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else: # direct exit for unspecified symmetry
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if color:
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return (True,np.zeros(3,'d'))
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else:
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return True
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v = np.array(vector,dtype=float)
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if proper: # check both improper ...
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theComponents = np.around(np.dot(basis['improper'],v),12)
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inSST = np.all(theComponents >= 0.0)
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if not inSST: # ... and proper SST
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theComponents = np.around(np.dot(basis['proper'],v),12)
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inSST = np.all(theComponents >= 0.0)
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else:
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v[2] = abs(v[2]) # z component projects identical
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theComponents = np.around(np.dot(basis['improper'],v),12) # for positive and negative values
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inSST = np.all(theComponents >= 0.0)
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if color: # have to return color array
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if inSST:
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rgb = np.power(theComponents/np.linalg.norm(theComponents),0.5) # smoothen color ramps
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rgb = np.minimum(np.ones(3,dtype=float),rgb) # limit to maximum intensity
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rgb /= max(rgb) # normalize to (HS)V = 1
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else:
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rgb = np.zeros(3,dtype=float)
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return (inSST,rgb)
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else:
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return inSST
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# code derived from https://github.com/ezag/pyeuclid
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# suggested reading: http://web.mit.edu/2.998/www/QuaternionReport1.pdf
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# ******************************************************************************************
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class Lattice:
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"""
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Lattice system.
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Currently, this contains only a mapping from Bravais lattice to symmetry
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and orientation relationships. It could include twin and slip systems.
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References
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----------
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https://en.wikipedia.org/wiki/Bravais_lattice
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"""
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lattices = {
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'triclinic':{'symmetry':None},
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'bct':{'symmetry':'tetragonal'},
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'hex':{'symmetry':'hexagonal'},
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'fcc':{'symmetry':'cubic','c/a':1.0},
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'bcc':{'symmetry':'cubic','c/a':1.0},
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}
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def __init__(self, lattice):
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"""
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New lattice of given type.
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Parameters
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----------
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lattice : str
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Bravais lattice.
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"""
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self.lattice = lattice
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self.symmetry = Symmetry(self.lattices[lattice]['symmetry'])
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def __repr__(self):
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"""Report basic lattice information."""
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return f'Bravais lattice {self.lattice} ({self.symmetry} symmetry)'
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# Kurdjomov--Sachs orientation relationship for fcc <-> bcc transformation
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# from S. Morito et al., Journal of Alloys and Compounds 577:s587-s592, 2013
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# also see K. Kitahara et al., Acta Materialia 54:1279-1288, 2006
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KS = {'mapping':{'fcc':0,'bcc':1},
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'planes': np.array([
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]],
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[[ 1, 1, -1],[ 0, 1, 1]]],dtype='float'),
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'directions': np.array([
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[[ -1, 0, 1],[ -1, -1, 1]],
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[[ -1, 0, 1],[ -1, 1, -1]],
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[[ 0, 1, -1],[ -1, -1, 1]],
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[[ 0, 1, -1],[ -1, 1, -1]],
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[[ 1, -1, 0],[ -1, -1, 1]],
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[[ 1, -1, 0],[ -1, 1, -1]],
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[[ 1, 0, -1],[ -1, -1, 1]],
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[[ 1, 0, -1],[ -1, 1, -1]],
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[[ -1, -1, 0],[ -1, -1, 1]],
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[[ -1, -1, 0],[ -1, 1, -1]],
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[[ 0, 1, 1],[ -1, -1, 1]],
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[[ 0, 1, 1],[ -1, 1, -1]],
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[[ 0, -1, 1],[ -1, -1, 1]],
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[[ 0, -1, 1],[ -1, 1, -1]],
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[[ -1, 0, -1],[ -1, -1, 1]],
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[[ -1, 0, -1],[ -1, 1, -1]],
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[[ 1, 1, 0],[ -1, -1, 1]],
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[[ 1, 1, 0],[ -1, 1, -1]],
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[[ -1, 1, 0],[ -1, -1, 1]],
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[[ -1, 1, 0],[ -1, 1, -1]],
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[[ 0, -1, -1],[ -1, -1, 1]],
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[[ 0, -1, -1],[ -1, 1, -1]],
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[[ 1, 0, 1],[ -1, -1, 1]],
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[[ 1, 0, 1],[ -1, 1, -1]]],dtype='float')}
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# Greninger--Troiano orientation relationship for fcc <-> bcc transformation
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# from Y. He et al., Journal of Applied Crystallography 39:72-81, 2006
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GT = {'mapping':{'fcc':0,'bcc':1},
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'planes': np.array([
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[[ 1, 1, 1],[ 1, 0, 1]],
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[[ 1, 1, 1],[ 1, 1, 0]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ -1, -1, 1],[ -1, 0, 1]],
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[[ -1, -1, 1],[ -1, -1, 0]],
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[[ -1, -1, 1],[ 0, -1, 1]],
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[[ -1, 1, 1],[ -1, 0, 1]],
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[[ -1, 1, 1],[ -1, 1, 0]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ 1, -1, 1],[ 1, 0, 1]],
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[[ 1, -1, 1],[ 1, -1, 0]],
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[[ 1, -1, 1],[ 0, -1, 1]],
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[[ 1, 1, 1],[ 1, 1, 0]],
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[[ 1, 1, 1],[ 0, 1, 1]],
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[[ 1, 1, 1],[ 1, 0, 1]],
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[[ -1, -1, 1],[ -1, -1, 0]],
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[[ -1, -1, 1],[ 0, -1, 1]],
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[[ -1, -1, 1],[ -1, 0, 1]],
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[[ -1, 1, 1],[ -1, 1, 0]],
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[[ -1, 1, 1],[ 0, 1, 1]],
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[[ -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 39:72-81, 2006
|
|
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 54:378-386, 2005
|
|
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]],
|
|
[[ 2, -1, 1],[ 0, -1, 1]], #It is wrong in the paper, but matrix is correct
|
|
[[ -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 53:1179-1190, 2005
|
|
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 39:72-81, 2006
|
|
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):
|
|
"""
|
|
Crystallographic orientation relationships for phase transformations.
|
|
|
|
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
|
|
|
|
"""
|
|
models={'KS':self.KS, 'GT':self.GT, 'GT_prime':self.GTprime,
|
|
'NW':self.NW, 'Pitsch': self.Pitsch, 'Bain':self.Bain}
|
|
try:
|
|
relationship = models[model]
|
|
except KeyError :
|
|
raise KeyError(f'Orientation relationship "{model}" is unknown')
|
|
|
|
if self.lattice not in relationship['mapping']:
|
|
raise ValueError(f'Relationship "{model}" not supported for lattice "{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])
|
|
|
|
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])
|
|
|
|
r['rotations'].append(Rotation.from_matrix(np.dot(otherMatrix.T,myMatrix)))
|
|
|
|
return r
|