# -*- coding: UTF-8 no BOM -*- ################################################### # NOTE: everything here needs to be a np array # ################################################### import math,os import numpy as np # ****************************************************************************************** class Rodrigues: def __init__(self, vector = np.zeros(3)): self.vector = vector def asQuaternion(self): norm = np.linalg.norm(self.vector) halfAngle = np.arctan(norm) return Quaternion(np.cos(halfAngle),np.sin(halfAngle)*self.vector/norm) def asAngleAxis(self): norm = np.linalg.norm(self.vector) halfAngle = np.arctan(norm) return (2.0*halfAngle,self.vector/norm) # ****************************************************************************************** class Quaternion: u""" Orientation represented as unit quaternion. All methods and naming conventions based on Rowenhorst_etal2015 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] w is the real part, (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) """ def __init__(self, quat = None, q = 1.0, p = np.zeros(3,dtype=float)): """Initializes to identity unless specified""" self.q = quat[0] if quat is not None else q self.p = np.array(quat[1:4]) if quat is not None else p self.homomorph() def __iter__(self): """Components""" return iter(self.asList()) def __copy__(self): """Copy""" return self.__class__(q=self.q,p=self.p.copy()) copy = __copy__ def __repr__(self): """Readable string""" return 'Quaternion(real={q:+.6f}, imag=<{p[0]:+.6f}, {p[1]:+.6f}, {p[2]:+.6f}>)'.format(q=self.q,p=self.p) def __pow__(self, exponent): """Power""" omega = math.acos(self.q) return self.__class__(q= math.cos(exponent*omega), p=self.p * math.sin(exponent*omega)/math.sin(omega)) def __ipow__(self, exponent): """In-place power""" omega = math.acos(self.q) self.q = math.cos(exponent*omega) self.p *= math.sin(exponent*omega)/math.sin(omega) return self def __mul__(self, other): """Multiplication""" # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 try: # quaternion return self.__class__(q=self.q*other.q - np.dot(self.p,other.p), p=self.q*other.p + other.q*self.p + P * np.cross(self.p,other.p)) except: pass try: # vector (perform passive rotation) ( x, y, z) = self.p (Vx,Vy,Vz) = other[0:3] A = self.q*self.q - np.dot(self.p,self.p) B = 2.0 * (x*Vx + y*Vy + z*Vz) C = 2.0 * P*self.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), ]) except: pass try: # scalar return self.__class__(q=self.q*other, p=self.p*other) except: return self.copy() def __imul__(self, other): """In-place multiplication""" # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 try: # Quaternion self.q = self.q*other.q - np.dot(self.p,other.p) self.p = self.q*other.p + other.q*self.p + P * np.cross(self.p,other.p) except: pass return self def __div__(self, other): """Division""" if isinstance(other, (int,float)): return self.__class__(q=self.q / other, p=self.p / other) else: return NotImplemented def __idiv__(self, other): """In-place division""" if isinstance(other, (int,float)): self.q /= other self.p /= other return self def __add__(self, other): """Addition""" if isinstance(other, Quaternion): return self.__class__(q=self.q + other.q, p=self.p + other.p) else: return NotImplemented def __iadd__(self, other): """In-place addition""" if isinstance(other, Quaternion): self.q += other.q self.p += other.p return self def __sub__(self, other): """Subtraction""" if isinstance(other, Quaternion): return self.__class__(q=self.q - other.q, p=self.p - other.p) else: return NotImplemented def __isub__(self, other): """In-place subtraction""" if isinstance(other, Quaternion): self.q -= other.q self.p -= other.p return self def __neg__(self): """Additive inverse""" self.q = -self.q self.p = -self.p return self def __abs__(self): """Norm""" return math.sqrt(self.q ** 2 + np.dot(self.p,self.p)) magnitude = __abs__ def __eq__(self,other): """Equal at e-8 precision""" return (self-other).magnitude() < 1e-8 or (-self-other).magnitude() < 1e-8 def __ne__(self,other): """Not equal at e-8 precision""" return not self.__eq__(self,other) def __cmp__(self,other): """Linear ordering""" return (1 if np.linalg.norm(self.asRodrigues()) > np.linalg.norm(other.asRodrigues()) else 0) \ - (1 if np.linalg.norm(self.asRodrigues()) < np.linalg.norm(other.asRodrigues()) else 0) def magnitude_squared(self): return self.q ** 2 + np.dot(self.p,self.p) def identity(self): self.q = 1. self.p = np.zeros(3,dtype=float) return self def normalize(self): d = self.magnitude() if d > 0.0: self.q /= d self.p /= d return self def conjugate(self): self.p = -self.p return self def inverse(self): d = self.magnitude() if d > 0.0: self.conjugate() self /= d return self def homomorph(self): if self.q < 0.0: self.q = -self.q self.p = -self.p return self def normalized(self): return self.copy().normalize() def conjugated(self): return self.copy().conjugate() def inversed(self): return self.copy().inverse() def homomorphed(self): return self.copy().homomorph() def asList(self): return [self.q]+list(self.p) def asM(self): # to find Averaging Quaternions (see F. Landis Markley et al.) return np.outer(self.asList(),self.asList()) def asMatrix(self): # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 qbarhalf = 0.5*(self.q**2 - np.dot(self.p,self.p)) return 2.0*np.array( [[ qbarhalf + self.p[0]**2 , self.p[0]*self.p[1] -P* self.q*self.p[2], self.p[0]*self.p[2] +P* self.q*self.p[1] ], [ self.p[0]*self.p[1] +P* self.q*self.p[2], qbarhalf + self.p[1]**2 , self.p[1]*self.p[2] -P* self.q*self.p[0] ], [ self.p[0]*self.p[2] -P* self.q*self.p[1], self.p[1]*self.p[2] +P* self.q*self.p[0], qbarhalf + self.p[2]**2 ], ]) def asAngleAxis(self, degrees = False, flat = False): if self.q > 1.: self.normalize() s = math.sqrt(1. - self.q**2) x = 2*self.q**2 - 1. y = 2*self.q * s angle = math.atan2(y,x) if angle < 0.0: angle *= -1. s *= -1. if flat: return np.hstack((np.degrees(angle) if degrees else angle, np.array([1.0, 0.0, 0.0] if np.abs(angle) < 1e-6 else self.p / s))) else: return (np.degrees(angle) if degrees else angle, np.array([1.0, 0.0, 0.0] if np.abs(angle) < 1e-6 else self.p / s)) def asRodrigues(self): return np.inf*np.ones(3) if self.q == 0.0 else self.p/self.q def asEulers(self, degrees = False): """Orientation as Bunge-Euler angles.""" # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 q03 = self.q**2 + self.p[2]**2 q12 = self.p[0]**2 + self.p[1]**2 chi = np.sqrt(q03*q12) if abs(chi) < 1e-10 and abs(q12) < 1e-10: eulers = np.array([math.atan2(-2*P*self.q*self.p[2],self.q**2-self.p[2]**2),0,0]) elif abs(chi) < 1e-10 and abs(q03) < 1e-10: eulers = np.array([math.atan2( 2 *self.p[0]*self.p[1],self.p[0]**2-self.p[1]**2),np.pi,0]) else: eulers = np.array([math.atan2((self.p[0]*self.p[2]-P*self.q*self.p[1])/chi,(-P*self.q*self.p[0]-self.p[1]*self.p[2])/chi), math.atan2(2*chi,q03-q12), math.atan2((P*self.q*self.p[1]+self.p[0]*self.p[2])/chi,( self.p[1]*self.p[2]-P*self.q*self.p[0])/chi), ]) return np.degrees(eulers) if degrees else eulers # # Static constructors @classmethod def fromIdentity(cls): return cls() @classmethod def fromRandom(cls,randomSeed = None): import binascii if randomSeed is None: randomSeed = int(binascii.hexlify(os.urandom(4)),16) np.random.seed(randomSeed) r = np.random.random(3) A = math.sqrt(max(0.0,r[2])) B = math.sqrt(max(0.0,1.0-r[2])) w = math.cos(2.0*math.pi*r[0])*A x = math.sin(2.0*math.pi*r[1])*B y = math.cos(2.0*math.pi*r[1])*B z = math.sin(2.0*math.pi*r[0])*A return cls(quat=[w,x,y,z]) @classmethod def fromRodrigues(cls, rodrigues): if not isinstance(rodrigues, np.ndarray): rodrigues = np.array(rodrigues) norm = np.linalg.norm(rodrigues) halfangle = math.atan(norm) s = math.sin(halfangle) c = math.cos(halfangle) return cls(q=c,p=s*rodrigues/norm) @classmethod def fromAngleAxis(cls, angle, axis, degrees = False): if not isinstance(axis, np.ndarray): axis = np.array(axis,dtype=float) axis = axis.astype(float)/np.linalg.norm(axis) angle = np.radians(angle) if degrees else angle s = math.sin(0.5 * angle) c = math.cos(0.5 * angle) return cls(q=c,p=axis*s) @classmethod def fromEulers(cls, eulers, degrees = False): if not isinstance(eulers, np.ndarray): eulers = np.array(eulers,dtype=float) eulers = np.radians(eulers) if degrees else eulers sigma = 0.5*(eulers[0]+eulers[2]) delta = 0.5*(eulers[0]-eulers[2]) c = np.cos(0.5*eulers[1]) s = np.sin(0.5*eulers[1]) # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 w = c * np.cos(sigma) x = -P * s * np.cos(delta) y = -P * s * np.sin(delta) z = -P * c * np.sin(sigma) return cls(quat=[w,x,y,z]) # Modified Method to calculate Quaternion from Orientation Matrix, # Source: http://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToQuaternion/ @classmethod def fromMatrix(cls, m): if m.shape != (3,3) and np.prod(m.shape) == 9: m = m.reshape(3,3) # Rowenhorst_etal2015 MSMSE: value of P is selected as -1 P = -1.0 w = 0.5*math.sqrt(max(0.0,1.0+m[0,0]+m[1,1]+m[2,2])) x = P*0.5*math.sqrt(max(0.0,1.0+m[0,0]-m[1,1]-m[2,2])) y = P*0.5*math.sqrt(max(0.0,1.0-m[0,0]+m[1,1]-m[2,2])) z = P*0.5*math.sqrt(max(0.0,1.0-m[0,0]-m[1,1]+m[2,2])) x *= -1 if m[2,1] < m[1,2] else 1 y *= -1 if m[0,2] < m[2,0] else 1 z *= -1 if m[1,0] < m[0,1] else 1 return cls(quat=np.array([w,x,y,z])/math.sqrt(w**2 + x**2 + y**2 + z**2)) @classmethod def new_interpolate(cls, q1, q2, t): """ Interpolation See http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20070017872_2007014421.pdf for (another?) way to interpolate quaternions. """ assert isinstance(q1, Quaternion) and isinstance(q2, Quaternion) Q = cls() costheta = q1.q*q2.q + np.dot(q1.p,q2.p) if costheta < 0.: costheta = -costheta q1 = q1.conjugated() elif costheta > 1.: costheta = 1. theta = math.acos(costheta) if abs(theta) < 0.01: Q.q = q2.q Q.p = q2.p return Q sintheta = math.sqrt(1.0 - costheta * costheta) if abs(sintheta) < 0.01: Q.q = (q1.q + q2.q) * 0.5 Q.p = (q1.p + q2.p) * 0.5 return Q ratio1 = math.sin((1.0 - t) * theta) / sintheta ratio2 = math.sin( t * theta) / sintheta Q.q = q1.q * ratio1 + q2.q * ratio2 Q.p = q1.p * ratio1 + q2.p * ratio2 return Q # ****************************************************************************************** class Symmetry: lattices = [None,'orthorhombic','tetragonal','hexagonal','cubic',] def __init__(self, symmetry = None): """Lattice with given symmetry, defaults to 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): """Readbable string""" return '{}'.format(self.lattice) def __eq__(self, other): """Equal""" return self.lattice == other.lattice def __neq__(self, other): """Not equal""" 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 symmetryQuats(self,who = []): """List of symmetry operations as quaternions.""" 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*math.sqrt(2), 0.5*math.sqrt(2) ], [ 0.0, 0.0, 0.5*math.sqrt(2),-0.5*math.sqrt(2) ], [ 0.0, 0.5*math.sqrt(2), 0.0, 0.5*math.sqrt(2) ], [ 0.0, 0.5*math.sqrt(2), 0.0, -0.5*math.sqrt(2) ], [ 0.0, 0.5*math.sqrt(2),-0.5*math.sqrt(2), 0.0 ], [ 0.0, -0.5*math.sqrt(2),-0.5*math.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*math.sqrt(2), 0.0, 0.0, 0.5*math.sqrt(2) ], [ 0.5*math.sqrt(2), 0.0, 0.0, 0.5*math.sqrt(2) ], [-0.5*math.sqrt(2), 0.0, 0.5*math.sqrt(2), 0.0 ], [-0.5*math.sqrt(2), 0.0, -0.5*math.sqrt(2), 0.0 ], [-0.5*math.sqrt(2), 0.5*math.sqrt(2), 0.0, 0.0 ], [-0.5*math.sqrt(2),-0.5*math.sqrt(2), 0.0, 0.0 ], ] elif self.lattice == 'hexagonal': symQuats = [ [ 1.0,0.0,0.0,0.0 ], [-0.5*math.sqrt(3), 0.0, 0.0,-0.5 ], [ 0.5, 0.0, 0.0, 0.5*math.sqrt(3) ], [ 0.0,0.0,0.0,1.0 ], [-0.5, 0.0, 0.0, 0.5*math.sqrt(3) ], [-0.5*math.sqrt(3), 0.0, 0.0, 0.5 ], [ 0.0,1.0,0.0,0.0 ], [ 0.0,-0.5*math.sqrt(3), 0.5, 0.0 ], [ 0.0, 0.5,-0.5*math.sqrt(3), 0.0 ], [ 0.0,0.0,1.0,0.0 ], [ 0.0,-0.5,-0.5*math.sqrt(3), 0.0 ], [ 0.0, 0.5*math.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*math.sqrt(2), 0.5*math.sqrt(2), 0.0 ], [ 0.0,-0.5*math.sqrt(2), 0.5*math.sqrt(2), 0.0 ], [ 0.5*math.sqrt(2), 0.0, 0.0, 0.5*math.sqrt(2) ], [-0.5*math.sqrt(2), 0.0, 0.0, 0.5*math.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 ], ] return list(map(Quaternion, np.array(symQuats)[np.atleast_1d(np.array(who)) if who != [] else range(len(symQuats))])) def equivalentQuaternions(self, quaternion, who = []): """List of symmetrically equivalent quaternions based on own symmetry.""" return [q*quaternion for q in self.symmetryQuats(who)] def inFZ(self,R): """Check whether given Rodrigues vector falls into fundamental zone of own symmetry.""" if isinstance(R, Quaternion): R = R.asRodrigues() # translate accidentially passed quaternion # fundamental zone in Rodrigues space is point symmetric around origin R = abs(R) if self.lattice == 'cubic': return math.sqrt(2.0)-1.0 >= R[0] \ and math.sqrt(2.0)-1.0 >= R[1] \ and math.sqrt(2.0)-1.0 >= R[2] \ and 1.0 >= R[0] + R[1] + R[2] elif self.lattice == 'hexagonal': return 1.0 >= R[0] and 1.0 >= R[1] and 1.0 >= R[2] \ and 2.0 >= math.sqrt(3)*R[0] + R[1] \ and 2.0 >= math.sqrt(3)*R[1] + R[0] \ and 2.0 >= math.sqrt(3) + R[2] elif self.lattice == 'tetragonal': return 1.0 >= R[0] and 1.0 >= R[1] \ and math.sqrt(2.0) >= R[0] + R[1] \ and math.sqrt(2.0) >= R[2] + 1.0 elif self.lattice == 'orthorhombic': return 1.0 >= R[0] and 1.0 >= R[1] and 1.0 >= R[2] else: return True def inDisorientationSST(self,R): """ 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 isinstance(R, Quaternion): R = R.asRodrigues() # translate accidentially passed quaternion 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. """ # 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.)]).transpose()), # 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.)]).transpose()), # 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.)]).transpose()), # direction of blue # 'orthorhombic' : np.linalg.inv(np.array([[0.,0.,1.], # direction of red # [1.,0.,0.], # direction of green # [0.,1.,0.]]).transpose()), # 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 Orientation: __slots__ = ['quaternion','symmetry'] def __init__(self, quaternion = Quaternion.fromIdentity(), Rodrigues = None, angleAxis = None, matrix = None, Eulers = None, random = False, # integer to have a fixed seed or True for real random symmetry = None, degrees = False, ): if random: # produce random orientation if isinstance(random, bool ): self.quaternion = Quaternion.fromRandom() else: self.quaternion = Quaternion.fromRandom(randomSeed=random) elif isinstance(Eulers, np.ndarray) and Eulers.shape == (3,): # based on given Euler angles self.quaternion = Quaternion.fromEulers(Eulers,degrees=degrees) elif isinstance(matrix, np.ndarray) : # based on given rotation matrix self.quaternion = Quaternion.fromMatrix(matrix) elif isinstance(angleAxis, np.ndarray) and angleAxis.shape == (4,): # based on given angle and rotation axis self.quaternion = Quaternion.fromAngleAxis(angleAxis[0],angleAxis[1:4],degrees=degrees) elif isinstance(Rodrigues, np.ndarray) and Rodrigues.shape == (3,): # based on given Rodrigues vector self.quaternion = Quaternion.fromRodrigues(Rodrigues) elif isinstance(quaternion, Quaternion): # based on given quaternion self.quaternion = quaternion.homomorphed() elif (isinstance(quaternion, np.ndarray) and quaternion.shape == (4,)) or \ (isinstance(quaternion, list) and len(quaternion) == 4 ): # based on given quaternion-like array self.quaternion = Quaternion(quat=quaternion).homomorphed() self.symmetry = Symmetry(symmetry) def __copy__(self): """Copy""" return self.__class__(quaternion=self.quaternion,symmetry=self.symmetry.lattice) copy = __copy__ def __repr__(self): """Value as all implemented representations""" return '\n'.join([ 'Symmetry: {}'.format(self.symmetry), 'Quaternion: {}'.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 asQuaternion(self): return self.quaternion.asList() def asEulers(self, degrees = False, ): return self.quaternion.asEulers(degrees) eulers = property(asEulers) def asRodrigues(self): return self.quaternion.asRodrigues() rodrigues = property(asRodrigues) def asAngleAxis(self, degrees = False, flat = False): return self.quaternion.asAngleAxis(degrees,flat) angleAxis = property(asAngleAxis) def asMatrix(self): return self.quaternion.asMatrix() matrix = property(asMatrix) def inFZ(self): return self.symmetry.inFZ(self.quaternion.asRodrigues()) infz = property(inFZ) def equivalentQuaternions(self, who = []): return self.symmetry.equivalentQuaternions(self.quaternion,who) def equivalentOrientations(self, who = []): return [Orientation(quaternion = q, symmetry = self.symmetry.lattice) for q in self.equivalentQuaternions(who)] def reduced(self): """Transform orientation to fall into fundamental zone according to symmetry""" for me in self.symmetry.equivalentQuaternions(self.quaternion): if self.symmetry.inFZ(me.asRodrigues()): break return Orientation(quaternion=me,symmetry=self.symmetry.lattice) def disorientation(self, other, SST = True): """ 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.symmetry != other.symmetry: raise TypeError('disorientation between different symmetry classes not supported yet.') misQ = other.quaternion*self.quaternion.conjugated() mySymQs = self.symmetry.symmetryQuats() if SST else self.symmetry.symmetryQuats()[:1] # take all or only first sym operation otherSymQs = other.symmetry.symmetryQuats() for i,sA in enumerate(mySymQs): for j,sB in enumerate(otherSymQs): theQ = sB*misQ*sA.conjugated() for k in range(2): theQ.conjugate() breaker = self.symmetry.inFZ(theQ) \ and (not SST or other.symmetry.inDisorientationSST(theQ)) if breaker: break if breaker: break if breaker: break # disorientation, own sym, other sym, self-->other: True, self<--other: False return (Orientation(quaternion = theQ,symmetry = self.symmetry.lattice), i,j, k == 1) 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,q in enumerate(self.symmetry.equivalentQuaternions(self.quaternion)): # test all symmetric equivalent quaternions pole = q*axis # align crystal direction to axis if self.symmetry.inSST(pole,proper): break # found SST version else: pole = self.quaternion*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 q in self.symmetry.equivalentQuaternions(self.quaternion): pole = q*axis # align crystal direction to axis inSST,color = self.symmetry.inSST(pole,color=True) if inSST: break return color @classmethod def average(cls, orientations, multiplicity = []): """ Average orientation 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: a = Orientation(Eulers=np.radians([10, 10, 0]), symmetry='hexagonal') b = Orientation(Eulers=np.radians([20, 0, 0]), symmetry='hexagonal') avg = Orientation.average([a,b]) """ if not all(isinstance(item, Orientation) for item in orientations): raise TypeError("Only instances of Orientation can be averaged.") N = len(orientations) if multiplicity == [] or not multiplicity: multiplicity = np.ones(N,dtype='i') reference = orientations[0] # take first as reference for i,(o,n) in enumerate(zip(orientations,multiplicity)): closest = o.equivalentOrientations(reference.disorientation(o,SST = False)[2])[0] # select sym orientation with lowest misorientation M = closest.quaternion.asM() * n if i == 0 else M + closest.quaternion.asM() * n # noqa add (multiples) of this orientation to average noqa eig, vec = np.linalg.eig(M/N) return Orientation(quaternion = Quaternion(quat = np.real(vec.T[eig.argmax()])), symmetry = reference.symmetry.lattice) def related(self, relationModel, direction, targetSymmetry = 'cubic'): """ Orientation relationship positive number: fcc --> bcc negative number: bcc --> fcc """ if relationModel not in ['KS','GT','GTdash','NW','Pitsch','Bain']: return None if int(direction) == 0: return None # KS from S. Morito et al./Journal of Alloys and Compounds 5775 (2013) S587-S592 # for KS rotation matrices also check K. Kitahara et al./Acta Materialia 54 (2006) 1279-1288 # GT from Y. He et al./Journal of Applied Crystallography (2006). 39, 72-81 # GT' from Y. He et al./Journal of Applied Crystallography (2006). 39, 72-81 # NW from H. Kitahara et al./Materials Characterization 54 (2005) 378-386 # Pitsch from Y. He et al./Acta Materialia 53 (2005) 1179-1190 # Bain from Y. He et al./Journal of Applied Crystallography (2006). 39, 72-81 variant = int(abs(direction))-1 (me,other) = (0,1) if direction > 0 else (1,0) planes = {'KS': \ 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]]]), 'GT': \ 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]]]), 'GTdash': \ 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]]]), 'NW': \ 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]]]), 'Pitsch': \ 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]]]), 'Bain': \ np.array([[[ 1, 0, 0],[ 1, 0, 0]], [[ 0, 1, 0],[ 0, 1, 0]], [[ 0, 0, 1],[ 0, 0, 1]]]), } normals = {'KS': \ 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]]]), 'GT': \ 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]]]), 'GTdash': \ 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]]]), 'NW': \ 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]]]), 'Pitsch': \ 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]]]), 'Bain': \ np.array([[[ 0, 1, 0],[ 0, 1, 1]], [[ 0, 0, 1],[ 1, 0, 1]], [[ 1, 0, 0],[ 1, 1, 0]]]), } myPlane = [float(i) for i in planes[relationModel][variant,me]] # map(float, planes[...]) does not work in python 3 myPlane /= np.linalg.norm(myPlane) myNormal = [float(i) for i in normals[relationModel][variant,me]] # map(float, planes[...]) does not work in python 3 myNormal /= np.linalg.norm(myNormal) myMatrix = np.array([myNormal,np.cross(myPlane,myNormal),myPlane]).T otherPlane = [float(i) for i in planes[relationModel][variant,other]] # map(float, planes[...]) does not work in python 3 otherPlane /= np.linalg.norm(otherPlane) otherNormal = [float(i) for i in normals[relationModel][variant,other]] # map(float, planes[...]) does not work in python 3 otherNormal /= np.linalg.norm(otherNormal) otherMatrix = np.array([otherNormal,np.cross(otherPlane,otherNormal),otherPlane]).T rot=np.dot(otherMatrix,myMatrix.T) return Orientation(matrix=np.dot(rot,self.asMatrix()),symmetry=targetSymmetry)