1 | # -*- coding: utf-8 -*- |
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2 | ''' |
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3 | *GSASIIlattice: Unit cells* |
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4 | --------------------------- |
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5 | |
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6 | Perform lattice-related computations |
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7 | |
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8 | Note that *g* is the reciprocal lattice tensor, and *G* is its inverse, |
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9 | :math:`G = g^{-1}`, where |
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10 | |
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11 | .. math:: |
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12 | |
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13 | G = \\left( \\begin{matrix} |
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14 | a^2 & a b\\cos\gamma & a c\\cos\\beta \\\\ |
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15 | a b\\cos\\gamma & b^2 & b c \cos\\alpha \\\\ |
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16 | a c\\cos\\beta & b c \\cos\\alpha & c^2 |
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17 | \\end{matrix}\\right) |
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18 | |
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19 | The "*A* tensor" terms are defined as |
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20 | :math:`A = (\\begin{matrix} G_{11} & G_{22} & G_{33} & 2G_{12} & 2G_{13} & 2G_{23}\\end{matrix})` and *A* can be used in this fashion: |
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21 | :math:`d^* = \sqrt {A_1 h^2 + A_2 k^2 + A_3 l^2 + A_4 hk + A_5 hl + A_6 kl}`, where |
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22 | *d* is the d-spacing, and :math:`d^*` is the reciprocal lattice spacing, |
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23 | :math:`Q = 2 \\pi d^* = 2 \\pi / d` |
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24 | ''' |
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25 | ########### SVN repository information ################### |
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26 | # $Date: 2016-07-09 15:45:12 +0000 (Sat, 09 Jul 2016) $ |
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27 | # $Author: vondreele $ |
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28 | # $Revision: 2367 $ |
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29 | # $URL: trunk/GSASIIlattice.py $ |
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30 | # $Id: GSASIIlattice.py 2367 2016-07-09 15:45:12Z vondreele $ |
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31 | ########### SVN repository information ################### |
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32 | import math |
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33 | import copy |
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34 | import sys |
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35 | import random as ran |
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36 | import numpy as np |
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37 | import numpy.linalg as nl |
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38 | import GSASIIpath |
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39 | import GSASIImath as G2mth |
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40 | import GSASIIspc as G2spc |
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41 | GSASIIpath.SetVersionNumber("$Revision: 2367 $") |
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42 | # trig functions in degrees |
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43 | sind = lambda x: np.sin(x*np.pi/180.) |
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44 | asind = lambda x: 180.*np.arcsin(x)/np.pi |
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45 | tand = lambda x: np.tan(x*np.pi/180.) |
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46 | atand = lambda x: 180.*np.arctan(x)/np.pi |
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47 | atan2d = lambda y,x: 180.*np.arctan2(y,x)/np.pi |
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48 | cosd = lambda x: np.cos(x*np.pi/180.) |
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49 | acosd = lambda x: 180.*np.arccos(x)/np.pi |
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50 | rdsq2d = lambda x,p: round(1.0/np.sqrt(x),p) |
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51 | rpd = np.pi/180. |
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52 | RSQ2PI = 1./np.sqrt(2.*np.pi) |
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53 | SQ2 = np.sqrt(2.) |
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54 | RSQPI = 1./np.sqrt(np.pi) |
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55 | R2pisq = 1./(2.*np.pi**2) |
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56 | nxs = np.newaxis |
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57 | |
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58 | def sec2HMS(sec): |
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59 | """Convert time in sec to H:M:S string |
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60 | |
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61 | :param sec: time in seconds |
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62 | :return: H:M:S string (to nearest 100th second) |
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63 | |
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64 | """ |
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65 | H = int(sec/3600) |
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66 | M = int(sec/60-H*60) |
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67 | S = sec-3600*H-60*M |
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68 | return '%d:%2d:%.2f'%(H,M,S) |
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69 | |
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70 | def rotdMat(angle,axis=0): |
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71 | """Prepare rotation matrix for angle in degrees about axis(=0,1,2) |
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72 | |
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73 | :param angle: angle in degrees |
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74 | :param axis: axis (0,1,2 = x,y,z) about which for the rotation |
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75 | :return: rotation matrix - 3x3 numpy array |
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76 | |
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77 | """ |
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78 | if axis == 2: |
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79 | return np.array([[cosd(angle),-sind(angle),0],[sind(angle),cosd(angle),0],[0,0,1]]) |
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80 | elif axis == 1: |
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81 | return np.array([[cosd(angle),0,-sind(angle)],[0,1,0],[sind(angle),0,cosd(angle)]]) |
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82 | else: |
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83 | return np.array([[1,0,0],[0,cosd(angle),-sind(angle)],[0,sind(angle),cosd(angle)]]) |
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84 | |
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85 | def rotdMat4(angle,axis=0): |
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86 | """Prepare rotation matrix for angle in degrees about axis(=0,1,2) with scaling for OpenGL |
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87 | |
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88 | :param angle: angle in degrees |
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89 | :param axis: axis (0,1,2 = x,y,z) about which for the rotation |
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90 | :return: rotation matrix - 4x4 numpy array (last row/column for openGL scaling) |
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91 | |
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92 | """ |
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93 | Mat = rotdMat(angle,axis) |
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94 | return np.concatenate((np.concatenate((Mat,[[0],[0],[0]]),axis=1),[[0,0,0,1],]),axis=0) |
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95 | |
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96 | def fillgmat(cell): |
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97 | """Compute lattice metric tensor from unit cell constants |
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98 | |
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99 | :param cell: tuple with a,b,c,alpha, beta, gamma (degrees) |
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100 | :return: 3x3 numpy array |
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101 | |
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102 | """ |
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103 | a,b,c,alp,bet,gam = cell |
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104 | g = np.array([ |
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105 | [a*a, a*b*cosd(gam), a*c*cosd(bet)], |
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106 | [a*b*cosd(gam), b*b, b*c*cosd(alp)], |
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107 | [a*c*cosd(bet) ,b*c*cosd(alp), c*c]]) |
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108 | return g |
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109 | |
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110 | def cell2Gmat(cell): |
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111 | """Compute real and reciprocal lattice metric tensor from unit cell constants |
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112 | |
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113 | :param cell: tuple with a,b,c,alpha, beta, gamma (degrees) |
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114 | :return: reciprocal (G) & real (g) metric tensors (list of two numpy 3x3 arrays) |
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115 | |
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116 | """ |
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117 | g = fillgmat(cell) |
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118 | G = nl.inv(g) |
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119 | return G,g |
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120 | |
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121 | def A2Gmat(A,inverse=True): |
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122 | """Fill real & reciprocal metric tensor (G) from A. |
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123 | |
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124 | :param A: reciprocal metric tensor elements as [G11,G22,G33,2*G12,2*G13,2*G23] |
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125 | :param bool inverse: if True return both G and g; else just G |
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126 | :return: reciprocal (G) & real (g) metric tensors (list of two numpy 3x3 arrays) |
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127 | |
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128 | """ |
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129 | G = np.zeros(shape=(3,3)) |
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130 | G = [ |
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131 | [A[0], A[3]/2., A[4]/2.], |
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132 | [A[3]/2.,A[1], A[5]/2.], |
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133 | [A[4]/2.,A[5]/2., A[2]]] |
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134 | if inverse: |
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135 | g = nl.inv(G) |
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136 | return G,g |
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137 | else: |
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138 | return G |
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139 | |
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140 | def Gmat2A(G): |
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141 | """Extract A from reciprocal metric tensor (G) |
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142 | |
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143 | :param G: reciprocal maetric tensor (3x3 numpy array |
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144 | :return: A = [G11,G22,G33,2*G12,2*G13,2*G23] |
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145 | |
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146 | """ |
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147 | return [G[0][0],G[1][1],G[2][2],2.*G[0][1],2.*G[0][2],2.*G[1][2]] |
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148 | |
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149 | def cell2A(cell): |
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150 | """Obtain A = [G11,G22,G33,2*G12,2*G13,2*G23] from lattice parameters |
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151 | |
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152 | :param cell: [a,b,c,alpha,beta,gamma] (degrees) |
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153 | :return: G reciprocal metric tensor as 3x3 numpy array |
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154 | |
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155 | """ |
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156 | G,g = cell2Gmat(cell) |
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157 | return Gmat2A(G) |
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158 | |
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159 | def A2cell(A): |
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160 | """Compute unit cell constants from A |
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161 | |
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162 | :param A: [G11,G22,G33,2*G12,2*G13,2*G23] G - reciprocal metric tensor |
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163 | :return: a,b,c,alpha, beta, gamma (degrees) - lattice parameters |
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164 | |
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165 | """ |
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166 | G,g = A2Gmat(A) |
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167 | return Gmat2cell(g) |
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168 | |
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169 | def Gmat2cell(g): |
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170 | """Compute real/reciprocal lattice parameters from real/reciprocal metric tensor (g/G) |
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171 | The math works the same either way. |
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172 | |
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173 | :param g (or G): real (or reciprocal) metric tensor 3x3 array |
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174 | :return: a,b,c,alpha, beta, gamma (degrees) (or a*,b*,c*,alpha*,beta*,gamma* degrees) |
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175 | |
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176 | """ |
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177 | oldset = np.seterr('raise') |
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178 | a = np.sqrt(max(0,g[0][0])) |
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179 | b = np.sqrt(max(0,g[1][1])) |
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180 | c = np.sqrt(max(0,g[2][2])) |
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181 | alp = acosd(g[2][1]/(b*c)) |
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182 | bet = acosd(g[2][0]/(a*c)) |
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183 | gam = acosd(g[0][1]/(a*b)) |
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184 | np.seterr(**oldset) |
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185 | return a,b,c,alp,bet,gam |
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186 | |
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187 | def invcell2Gmat(invcell): |
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188 | """Compute real and reciprocal lattice metric tensor from reciprocal |
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189 | unit cell constants |
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190 | |
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191 | :param invcell: [a*,b*,c*,alpha*, beta*, gamma*] (degrees) |
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192 | :return: reciprocal (G) & real (g) metric tensors (list of two 3x3 arrays) |
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193 | |
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194 | """ |
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195 | G = fillgmat(invcell) |
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196 | g = nl.inv(G) |
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197 | return G,g |
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198 | |
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199 | def prodMGMT(G,Mat): |
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200 | '''Transform metric tensor by matrix |
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201 | |
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202 | :param G: array metric tensor |
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203 | :param Mat: array transformation matrix |
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204 | :return: array new metric tensor |
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205 | |
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206 | ''' |
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207 | return np.inner(Mat,np.inner(G,Mat).T) |
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208 | |
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209 | def TransformCell(cell,Trans): |
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210 | '''Transform lattice parameters by matrix |
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211 | |
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212 | :param cell: list a,b,c,alpha,beta,gamma,(volume) |
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213 | :param Trans: array transformation matrix |
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214 | :return: array transformed a,b,c,alpha,beta,gamma,volume |
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215 | |
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216 | ''' |
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217 | newCell = np.zeros(7) |
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218 | g = cell2Gmat(cell)[1] |
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219 | newg = prodMGMT(g,Trans) |
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220 | newCell[:6] = Gmat2cell(newg) |
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221 | newCell[6] = calc_V(cell2A(newCell[:6])) |
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222 | return newCell |
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223 | |
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224 | def TransformXYZ(XYZ,Trans,Vec): |
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225 | return np.inner(XYZ,Trans)+Vec |
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226 | |
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227 | def TransformU6(U6,Trans): |
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228 | Uij = np.inner(Trans,np.inner(U6toUij(U6),Trans)) |
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229 | return UijtoU6(Uij) |
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230 | |
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231 | def TransformPhase(oldPhase,newPhase,Trans,Vec): |
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232 | '''Transform atoms from oldPhase to newPhase by Trans & Vec |
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233 | |
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234 | :param oldPhase: dict G2 phase info for old phase |
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235 | :param newPhase: dict G2 phase info for new phase; with new cell & space group |
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236 | atoms are from oldPhase & will be transformed |
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237 | :param Trans: array transformation matrix |
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238 | :param Vec: array transformation vector |
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239 | ''' |
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240 | |
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241 | cx,ct,cs,cia = oldPhase['General']['AtomPtrs'] |
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242 | SGData = newPhase['General']['SGData'] |
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243 | invTrans = nl.inv(Trans) |
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244 | newAtoms = FillUnitCell(oldPhase) |
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245 | Unit =[abs(int(max(unit))-1) for unit in Trans] |
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246 | for i,unit in enumerate(Unit): |
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247 | if unit > 0: |
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248 | for j in range(unit): |
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249 | moreAtoms = copy.deepcopy(newAtoms) |
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250 | for atom in moreAtoms: |
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251 | atom[cx+i] += 1. |
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252 | newAtoms += moreAtoms |
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253 | for atom in newAtoms: |
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254 | atom[cx:cx+3] = TransformXYZ(atom[cx:cx+3],invTrans.T,Vec)%1. |
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255 | if atom[cia] == 'A': |
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256 | atom[cia+2:cia+8] = TransformU6(atom[cia+2:cia+8],invTrans) |
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257 | atom[cs:cs+2] = G2spc.SytSym(atom[cx:cx+3],SGData) |
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258 | atom[cia+8] = ran.randint(0,sys.maxint) |
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259 | newPhase['Atoms'] = newAtoms |
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260 | newPhase['Atoms'] = GetUnique(newPhase) |
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261 | newPhase['Drawing']['Atoms'] = [] |
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262 | return newPhase |
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263 | |
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264 | def FillUnitCell(Phase): |
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265 | Atoms = Phase['Atoms'] |
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266 | atomData = [] |
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267 | SGData = Phase['General']['SGData'] |
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268 | cx,ct,cs,cia = Phase['General']['AtomPtrs'] |
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269 | unit = np.zeros(3) |
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270 | for atom in Atoms: |
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271 | XYZ = np.array(atom[cx:cx+3]) |
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272 | xyz = XYZ%1. |
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273 | unit = XYZ-xyz |
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274 | if atom[cia] == 'A': |
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275 | Uij = atom[cia+2:cia+8] |
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276 | result = G2spc.GenAtom(xyz,SGData,False,Uij,True) |
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277 | for item in result: |
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278 | if item[0][2] >= .95: item[0][2] -= 1. |
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279 | atom[cx:cx+3] = item[0] |
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280 | atom[cia+2:cia+8] = item[1] |
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281 | atomData.append(atom[:cia+9]) #not SS stuff |
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282 | else: |
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283 | result = G2spc.GenAtom(xyz,SGData,False,Move=True) |
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284 | for item in result: |
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285 | if item[0][2] >= .95: item[0][2] -= 1. |
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286 | atom[cx:cx+3] = item[0] |
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287 | atomData.append(atom[:cia+9]) #not SS stuff |
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288 | return atomData |
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289 | |
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290 | def GetUnique(Phase): |
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291 | |
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292 | def noDuplicate(xyzA,XYZ,Amat): |
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293 | if True in [np.allclose(np.inner(Amat,xyzA),np.inner(Amat,xyzB),atol=0.05) for xyzB in XYZ]: |
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294 | return False |
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295 | return True |
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296 | |
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297 | cx,ct,cs,cia = Phase['General']['AtomPtrs'] |
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298 | cell = Phase['General']['Cell'][1:7] |
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299 | Amat,Bmat = cell2AB(cell) |
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300 | SGData = Phase['General']['SGData'] |
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301 | Atoms = Phase['Atoms'] |
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302 | Ind = len(Atoms) |
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303 | newAtoms = [] |
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304 | Indx = {} |
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305 | XYZ = {} |
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306 | for ind in range(Ind): |
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307 | XYZ[ind] = np.array(Atoms[ind][cx:cx+3])%1. |
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308 | Indx[ind] = True |
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309 | for ind in range(Ind): |
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310 | if Indx[ind]: |
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311 | xyz = XYZ[ind] |
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312 | for jnd in range(Ind): |
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313 | if ind != jnd and Indx[jnd]: |
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314 | Equiv = G2spc.GenAtom(XYZ[jnd],SGData,Move=True) |
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315 | xyzs = np.array([equiv[0] for equiv in Equiv]) |
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316 | Indx[jnd] = noDuplicate(xyz,xyzs,Amat) |
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317 | Ind = [] |
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318 | for ind in Indx: |
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319 | if Indx[ind]: |
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320 | newAtoms.append(Atoms[ind]) |
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321 | return newAtoms |
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322 | |
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323 | def calc_rVsq(A): |
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324 | """Compute the square of the reciprocal lattice volume (1/V**2) from A' |
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325 | |
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326 | """ |
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327 | G,g = A2Gmat(A) |
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328 | rVsq = nl.det(G) |
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329 | if rVsq < 0: |
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330 | return 1 |
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331 | return rVsq |
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332 | |
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333 | def calc_rV(A): |
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334 | """Compute the reciprocal lattice volume (V*) from A |
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335 | """ |
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336 | return np.sqrt(calc_rVsq(A)) |
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337 | |
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338 | def calc_V(A): |
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339 | """Compute the real lattice volume (V) from A |
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340 | """ |
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341 | return 1./calc_rV(A) |
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342 | |
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343 | def A2invcell(A): |
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344 | """Compute reciprocal unit cell constants from A |
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345 | returns tuple with a*,b*,c*,alpha*, beta*, gamma* (degrees) |
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346 | """ |
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347 | G,g = A2Gmat(A) |
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348 | return Gmat2cell(G) |
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349 | |
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350 | def Gmat2AB(G): |
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351 | """Computes orthogonalization matrix from reciprocal metric tensor G |
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352 | |
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353 | :returns: tuple of two 3x3 numpy arrays (A,B) |
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354 | |
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355 | * A for crystal to Cartesian transformations A*x = np.inner(A,x) = X |
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356 | * B (= inverse of A) for Cartesian to crystal transformation B*X = np.inner(B,X) = x |
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357 | |
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358 | """ |
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359 | cellstar = Gmat2cell(G) |
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360 | g = nl.inv(G) |
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361 | cell = Gmat2cell(g) |
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362 | A = np.zeros(shape=(3,3)) |
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363 | # from Giacovazzo (Fundamentals 2nd Ed.) p.75 |
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364 | A[0][0] = cell[0] # a |
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365 | A[0][1] = cell[1]*cosd(cell[5]) # b cos(gamma) |
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366 | A[0][2] = cell[2]*cosd(cell[4]) # c cos(beta) |
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367 | A[1][1] = cell[1]*sind(cell[5]) # b sin(gamma) |
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368 | A[1][2] = -cell[2]*cosd(cellstar[3])*sind(cell[4]) # - c cos(alpha*) sin(beta) |
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369 | A[2][2] = 1/cellstar[2] # 1/c* |
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370 | B = nl.inv(A) |
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371 | return A,B |
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372 | |
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373 | def cell2AB(cell): |
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374 | """Computes orthogonalization matrix from unit cell constants |
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375 | |
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376 | :param tuple cell: a,b,c, alpha, beta, gamma (degrees) |
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377 | :returns: tuple of two 3x3 numpy arrays (A,B) |
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378 | A for crystal to Cartesian transformations A*x = np.inner(A,x) = X |
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379 | B (= inverse of A) for Cartesian to crystal transformation B*X = np.inner(B,X) = x |
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380 | """ |
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381 | G,g = cell2Gmat(cell) |
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382 | cellstar = Gmat2cell(G) |
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383 | A = np.zeros(shape=(3,3)) |
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384 | # from Giacovazzo (Fundamentals 2nd Ed.) p.75 |
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385 | A[0][0] = cell[0] # a |
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386 | A[0][1] = cell[1]*cosd(cell[5]) # b cos(gamma) |
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387 | A[0][2] = cell[2]*cosd(cell[4]) # c cos(beta) |
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388 | A[1][1] = cell[1]*sind(cell[5]) # b sin(gamma) |
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389 | A[1][2] = -cell[2]*cosd(cellstar[3])*sind(cell[4]) # - c cos(alpha*) sin(beta) |
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390 | A[2][2] = 1/cellstar[2] # 1/c* |
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391 | B = nl.inv(A) |
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392 | return A,B |
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393 | |
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394 | def HKL2SpAng(H,cell,SGData): |
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395 | """Computes spherical coords for hkls; view along 001 |
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396 | |
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397 | :param array H: arrays of hkl |
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398 | :param tuple cell: a,b,c, alpha, beta, gamma (degrees) |
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399 | :param dict SGData: space group dictionary |
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400 | :returns: arrays of r,phi,psi (radius,inclination,azimuth) about 001 |
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401 | """ |
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402 | A,B = cell2AB(cell) |
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403 | xH = np.inner(B,H) |
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404 | r = np.sqrt(np.sum(xH**2,axis=0)) |
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405 | phi = acosd(xH[2]/r) |
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406 | psi = atan2d(xH[1],xH[0]) |
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407 | phi = np.where(phi>90.,180.-phi,phi) |
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408 | # GSASIIpath.IPyBreak() |
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409 | return r,phi,psi |
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410 | |
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411 | def U6toUij(U6): |
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412 | """Fill matrix (Uij) from U6 = [U11,U22,U33,U12,U13,U23] |
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413 | NB: there is a non numpy version in GSASIIspc: U2Uij |
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414 | |
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415 | :param list U6: 6 terms of u11,u22,... |
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416 | :returns: |
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417 | Uij - numpy [3][3] array of uij |
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418 | """ |
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419 | U = np.array([ |
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420 | [U6[0], U6[3], U6[4]], |
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421 | [U6[3], U6[1], U6[5]], |
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422 | [U6[4], U6[5], U6[2]]]) |
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423 | return U |
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424 | |
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425 | def UijtoU6(U): |
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426 | """Fill vector [U11,U22,U33,U12,U13,U23] from Uij |
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427 | NB: there is a non numpy version in GSASIIspc: Uij2U |
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428 | """ |
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429 | U6 = np.array([U[0][0],U[1][1],U[2][2],U[0][1],U[0][2],U[1][2]]) |
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430 | return U6 |
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431 | |
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432 | def betaij2Uij(betaij,G): |
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433 | """ |
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434 | Convert beta-ij to Uij tensors |
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435 | |
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436 | :param beta-ij - numpy array [beta-ij] |
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437 | :param G: reciprocal metric tensor |
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438 | :returns: Uij: numpy array [Uij] |
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439 | """ |
---|
440 | ast = np.sqrt(np.diag(G)) #a*, b*, c* |
---|
441 | Mast = np.multiply.outer(ast,ast) |
---|
442 | return R2pisq*UijtoU6(U6toUij(betaij)/Mast) |
---|
443 | |
---|
444 | def Uij2betaij(Uij,G): |
---|
445 | """ |
---|
446 | Convert Uij to beta-ij tensors -- stub for eventual completion |
---|
447 | |
---|
448 | :param Uij: numpy array [Uij] |
---|
449 | :param G: reciprocal metric tensor |
---|
450 | :returns: beta-ij - numpy array [beta-ij] |
---|
451 | """ |
---|
452 | pass |
---|
453 | |
---|
454 | def cell2GS(cell): |
---|
455 | ''' returns Uij to betaij conversion matrix''' |
---|
456 | G,g = cell2Gmat(cell) |
---|
457 | GS = G |
---|
458 | GS[0][1] = GS[1][0] = math.sqrt(GS[0][0]*GS[1][1]) |
---|
459 | GS[0][2] = GS[2][0] = math.sqrt(GS[0][0]*GS[2][2]) |
---|
460 | GS[1][2] = GS[2][1] = math.sqrt(GS[1][1]*GS[2][2]) |
---|
461 | return GS |
---|
462 | |
---|
463 | def Uij2Ueqv(Uij,GS,Amat): |
---|
464 | ''' returns 1/3 trace of diagonalized U matrix''' |
---|
465 | U = np.multiply(U6toUij(Uij),GS) |
---|
466 | U = np.inner(Amat,np.inner(U,Amat).T) |
---|
467 | E,R = nl.eigh(U) |
---|
468 | return np.sum(E)/3. |
---|
469 | |
---|
470 | def CosAngle(U,V,G): |
---|
471 | """ calculate cos of angle between U & V in generalized coordinates |
---|
472 | defined by metric tensor G |
---|
473 | |
---|
474 | :param U: 3-vectors assume numpy arrays, can be multiple reflections as (N,3) array |
---|
475 | :param V: 3-vectors assume numpy arrays, only as (3) vector |
---|
476 | :param G: metric tensor for U & V defined space assume numpy array |
---|
477 | :returns: |
---|
478 | cos(phi) |
---|
479 | """ |
---|
480 | u = (U.T/np.sqrt(np.sum(np.inner(U,G)*U,axis=1))).T |
---|
481 | v = V/np.sqrt(np.inner(V,np.inner(G,V))) |
---|
482 | cosP = np.inner(u,np.inner(G,v)) |
---|
483 | return cosP |
---|
484 | |
---|
485 | def CosSinAngle(U,V,G): |
---|
486 | """ calculate sin & cos of angle between U & V in generalized coordinates |
---|
487 | defined by metric tensor G |
---|
488 | |
---|
489 | :param U: 3-vectors assume numpy arrays |
---|
490 | :param V: 3-vectors assume numpy arrays |
---|
491 | :param G: metric tensor for U & V defined space assume numpy array |
---|
492 | :returns: |
---|
493 | cos(phi) & sin(phi) |
---|
494 | """ |
---|
495 | u = U/np.sqrt(np.inner(U,np.inner(G,U))) |
---|
496 | v = V/np.sqrt(np.inner(V,np.inner(G,V))) |
---|
497 | cosP = np.inner(u,np.inner(G,v)) |
---|
498 | sinP = np.sqrt(max(0.0,1.0-cosP**2)) |
---|
499 | return cosP,sinP |
---|
500 | |
---|
501 | def criticalEllipse(prob): |
---|
502 | """ |
---|
503 | Calculate critical values for probability ellipsoids from probability |
---|
504 | """ |
---|
505 | if not ( 0.01 <= prob < 1.0): |
---|
506 | return 1.54 |
---|
507 | coeff = np.array([6.44988E-09,4.16479E-07,1.11172E-05,1.58767E-04,0.00130554, |
---|
508 | 0.00604091,0.0114921,-0.040301,-0.6337203,1.311582]) |
---|
509 | llpr = math.log(-math.log(prob)) |
---|
510 | return np.polyval(coeff,llpr) |
---|
511 | |
---|
512 | def CellBlock(nCells): |
---|
513 | """ |
---|
514 | Generate block of unit cells n*n*n on a side; [0,0,0] centered, n = 2*nCells+1 |
---|
515 | currently only works for nCells = 0 or 1 (not >1) |
---|
516 | """ |
---|
517 | if nCells: |
---|
518 | N = 2*nCells+1 |
---|
519 | N2 = N*N |
---|
520 | N3 = N*N*N |
---|
521 | cellArray = [] |
---|
522 | A = np.array(range(N3)) |
---|
523 | cellGen = np.array([A/N2-1,A/N%N-1,A%N-1]).T |
---|
524 | for cell in cellGen: |
---|
525 | cellArray.append(cell) |
---|
526 | return cellArray |
---|
527 | else: |
---|
528 | return [0,0,0] |
---|
529 | |
---|
530 | def CellAbsorption(ElList,Volume): |
---|
531 | '''Compute unit cell absorption |
---|
532 | |
---|
533 | :param dict ElList: dictionary of element contents including mu and |
---|
534 | number of atoms be cell |
---|
535 | :param float Volume: unit cell volume |
---|
536 | :returns: mu-total/Volume |
---|
537 | ''' |
---|
538 | muT = 0 |
---|
539 | for El in ElList: |
---|
540 | muT += ElList[El]['mu']*ElList[El]['FormulaNo'] |
---|
541 | return muT/Volume |
---|
542 | |
---|
543 | #Permutations and Combinations |
---|
544 | # Four routines: combinations,uniqueCombinations, selections & permutations |
---|
545 | #These taken from Python Cookbook, 2nd Edition. 19.15 p724-726 |
---|
546 | # |
---|
547 | def _combinators(_handle, items, n): |
---|
548 | """ factored-out common structure of all following combinators """ |
---|
549 | if n==0: |
---|
550 | yield [ ] |
---|
551 | return |
---|
552 | for i, item in enumerate(items): |
---|
553 | this_one = [ item ] |
---|
554 | for cc in _combinators(_handle, _handle(items, i), n-1): |
---|
555 | yield this_one + cc |
---|
556 | def combinations(items, n): |
---|
557 | """ take n distinct items, order matters """ |
---|
558 | def skipIthItem(items, i): |
---|
559 | return items[:i] + items[i+1:] |
---|
560 | return _combinators(skipIthItem, items, n) |
---|
561 | def uniqueCombinations(items, n): |
---|
562 | """ take n distinct items, order is irrelevant """ |
---|
563 | def afterIthItem(items, i): |
---|
564 | return items[i+1:] |
---|
565 | return _combinators(afterIthItem, items, n) |
---|
566 | def selections(items, n): |
---|
567 | """ take n (not necessarily distinct) items, order matters """ |
---|
568 | def keepAllItems(items, i): |
---|
569 | return items |
---|
570 | return _combinators(keepAllItems, items, n) |
---|
571 | def permutations(items): |
---|
572 | """ take all items, order matters """ |
---|
573 | return combinations(items, len(items)) |
---|
574 | |
---|
575 | #reflection generation routines |
---|
576 | #for these: H = [h,k,l]; A is as used in calc_rDsq; G - inv metric tensor, g - metric tensor; |
---|
577 | # cell - a,b,c,alp,bet,gam in A & deg |
---|
578 | |
---|
579 | def Pos2dsp(Inst,pos): |
---|
580 | ''' convert powder pattern position (2-theta or TOF, musec) to d-spacing |
---|
581 | ''' |
---|
582 | if 'C' in Inst['Type'][0] or 'PKS' in Inst['Type'][0]: |
---|
583 | wave = G2mth.getWave(Inst) |
---|
584 | return wave/(2.0*sind((pos-Inst.get('Zero',[0,0])[1])/2.0)) |
---|
585 | else: #'T'OF - ignore difB |
---|
586 | return TOF2dsp(Inst,pos) |
---|
587 | |
---|
588 | def TOF2dsp(Inst,Pos): |
---|
589 | ''' convert powder pattern TOF, musec to d-spacing by successive approximation |
---|
590 | Pos can be numpy array |
---|
591 | ''' |
---|
592 | def func(d,pos,Inst): |
---|
593 | return (pos-Inst['difA'][1]*d**2-Inst['Zero'][1]-Inst['difB'][1]/d)/Inst['difC'][1] |
---|
594 | dsp0 = np.ones_like(Pos) |
---|
595 | N = 0 |
---|
596 | while True: #successive approximations |
---|
597 | dsp = func(dsp0,Pos,Inst) |
---|
598 | if np.allclose(dsp,dsp0,atol=0.000001): |
---|
599 | return dsp |
---|
600 | dsp0 = dsp |
---|
601 | N += 1 |
---|
602 | if N > 10: |
---|
603 | return dsp |
---|
604 | |
---|
605 | def Dsp2pos(Inst,dsp): |
---|
606 | ''' convert d-spacing to powder pattern position (2-theta or TOF, musec) |
---|
607 | ''' |
---|
608 | if 'C' in Inst['Type'][0] or 'PKS' in Inst['Type'][0]: |
---|
609 | wave = G2mth.getWave(Inst) |
---|
610 | pos = 2.0*asind(wave/(2.*dsp))+Inst.get('Zero',[0,0])[1] |
---|
611 | else: #'T'OF |
---|
612 | pos = Inst['difC'][1]*dsp+Inst['Zero'][1]+Inst['difA'][1]*dsp**2+Inst.get('difB',[0,0,False])[1]/dsp |
---|
613 | return pos |
---|
614 | |
---|
615 | def getPeakPos(dataType,parmdict,dsp): |
---|
616 | ''' convert d-spacing to powder pattern position (2-theta or TOF, musec) |
---|
617 | ''' |
---|
618 | if 'C' in dataType: |
---|
619 | pos = 2.0*asind(parmdict['Lam']/(2.*dsp))+parmdict['Zero'] |
---|
620 | else: #'T'OF |
---|
621 | pos = parmdict['difC']*dsp+parmdict['difA']*dsp**2+parmdict['difB']/dsp+parmdict['Zero'] |
---|
622 | return pos |
---|
623 | |
---|
624 | def calc_rDsq(H,A): |
---|
625 | 'needs doc string' |
---|
626 | rdsq = H[0]*H[0]*A[0]+H[1]*H[1]*A[1]+H[2]*H[2]*A[2]+H[0]*H[1]*A[3]+H[0]*H[2]*A[4]+H[1]*H[2]*A[5] |
---|
627 | return rdsq |
---|
628 | |
---|
629 | def calc_rDsq2(H,G): |
---|
630 | 'needs doc string' |
---|
631 | return np.inner(H,np.inner(G,H)) |
---|
632 | |
---|
633 | def calc_rDsqSS(H,A,vec): |
---|
634 | 'needs doc string' |
---|
635 | rdsq = calc_rDsq(H[:3]+(H[3]*vec).T,A) |
---|
636 | return rdsq |
---|
637 | |
---|
638 | def calc_rDsqZ(H,A,Z,tth,lam): |
---|
639 | 'needs doc string' |
---|
640 | rdsq = calc_rDsq(H,A)+Z*sind(tth)*2.0*rpd/lam**2 |
---|
641 | return rdsq |
---|
642 | |
---|
643 | def calc_rDsqZSS(H,A,vec,Z,tth,lam): |
---|
644 | 'needs doc string' |
---|
645 | rdsq = calc_rDsq(H[:3]+(H[3][:,np.newaxis]*vec).T,A)+Z*sind(tth)*2.0*rpd/lam**2 |
---|
646 | return rdsq |
---|
647 | |
---|
648 | def calc_rDsqT(H,A,Z,tof,difC): |
---|
649 | 'needs doc string' |
---|
650 | rdsq = calc_rDsq(H,A)+Z/difC |
---|
651 | return rdsq |
---|
652 | |
---|
653 | def calc_rDsqTSS(H,A,vec,Z,tof,difC): |
---|
654 | 'needs doc string' |
---|
655 | rdsq = calc_rDsq(H[:3]+(H[3][:,np.newaxis]*vec).T,A)+Z/difC |
---|
656 | return rdsq |
---|
657 | |
---|
658 | def MaxIndex(dmin,A): |
---|
659 | 'needs doc string' |
---|
660 | Hmax = [0,0,0] |
---|
661 | try: |
---|
662 | cell = A2cell(A) |
---|
663 | except: |
---|
664 | cell = [1,1,1,90,90,90] |
---|
665 | for i in range(3): |
---|
666 | Hmax[i] = int(round(cell[i]/dmin)) |
---|
667 | return Hmax |
---|
668 | |
---|
669 | def transposeHKLF(transMat,Super,refList): |
---|
670 | ''' Apply transformation matrix to hkl(m) |
---|
671 | param: transmat: 3x3 or 4x4 array |
---|
672 | param: Super: 0 or 1 for extra index |
---|
673 | param: refList list of h,k,l,.... |
---|
674 | return: newRefs transformed list of h',k',l',,, |
---|
675 | return: badRefs list of noninteger h',k',l'... |
---|
676 | ''' |
---|
677 | newRefs = np.copy(refList) |
---|
678 | badRefs = [] |
---|
679 | for H in newRefs: |
---|
680 | newH = np.inner(transMat,H[:3+Super]) |
---|
681 | H[:3+Super] = np.rint(newH) |
---|
682 | if not np.allclose(newH,H[:3+Super],atol=0.01): |
---|
683 | badRefs.append(newH) |
---|
684 | return newRefs,badRefs |
---|
685 | |
---|
686 | def sortHKLd(HKLd,ifreverse,ifdup,ifSS=False): |
---|
687 | '''sort reflection list on d-spacing; can sort in either order |
---|
688 | |
---|
689 | :param HKLd: a list of [h,k,l,d,...]; |
---|
690 | :param ifreverse: True for largest d first |
---|
691 | :param ifdup: True if duplicate d-spacings allowed |
---|
692 | :return sorted reflection list |
---|
693 | ''' |
---|
694 | T = [] |
---|
695 | N = 3 |
---|
696 | if ifSS: |
---|
697 | N = 4 |
---|
698 | for i,H in enumerate(HKLd): |
---|
699 | if ifdup: |
---|
700 | T.append((H[N],i)) |
---|
701 | else: |
---|
702 | T.append(H[N]) |
---|
703 | D = dict(zip(T,HKLd)) |
---|
704 | T.sort() |
---|
705 | if ifreverse: |
---|
706 | T.reverse() |
---|
707 | X = [] |
---|
708 | okey = '' |
---|
709 | for key in T: |
---|
710 | if key != okey: X.append(D[key]) #remove duplicate d-spacings |
---|
711 | okey = key |
---|
712 | return X |
---|
713 | |
---|
714 | def SwapIndx(Axis,H): |
---|
715 | 'needs doc string' |
---|
716 | if Axis in [1,-1]: |
---|
717 | return H |
---|
718 | elif Axis in [2,-3]: |
---|
719 | return [H[1],H[2],H[0]] |
---|
720 | else: |
---|
721 | return [H[2],H[0],H[1]] |
---|
722 | |
---|
723 | def Rh2Hx(Rh): |
---|
724 | 'needs doc string' |
---|
725 | Hx = [0,0,0] |
---|
726 | Hx[0] = Rh[0]-Rh[1] |
---|
727 | Hx[1] = Rh[1]-Rh[2] |
---|
728 | Hx[2] = np.sum(Rh) |
---|
729 | return Hx |
---|
730 | |
---|
731 | def Hx2Rh(Hx): |
---|
732 | 'needs doc string' |
---|
733 | Rh = [0,0,0] |
---|
734 | itk = -Hx[0]+Hx[1]+Hx[2] |
---|
735 | if itk%3 != 0: |
---|
736 | return 0 #error - not rhombohedral reflection |
---|
737 | else: |
---|
738 | Rh[1] = itk/3 |
---|
739 | Rh[0] = Rh[1]+Hx[0] |
---|
740 | Rh[2] = Rh[1]-Hx[1] |
---|
741 | if Rh[0] < 0: |
---|
742 | for i in range(3): |
---|
743 | Rh[i] = -Rh[i] |
---|
744 | return Rh |
---|
745 | |
---|
746 | def CentCheck(Cent,H): |
---|
747 | 'needs doc string' |
---|
748 | h,k,l = H |
---|
749 | if Cent == 'A' and (k+l)%2: |
---|
750 | return False |
---|
751 | elif Cent == 'B' and (h+l)%2: |
---|
752 | return False |
---|
753 | elif Cent == 'C' and (h+k)%2: |
---|
754 | return False |
---|
755 | elif Cent == 'I' and (h+k+l)%2: |
---|
756 | return False |
---|
757 | elif Cent == 'F' and ((h+k)%2 or (h+l)%2 or (k+l)%2): |
---|
758 | return False |
---|
759 | elif Cent == 'R' and (-h+k+l)%3: |
---|
760 | return False |
---|
761 | else: |
---|
762 | return True |
---|
763 | |
---|
764 | def GetBraviasNum(center,system): |
---|
765 | """Determine the Bravais lattice number, as used in GenHBravais |
---|
766 | |
---|
767 | :param center: one of: 'P', 'C', 'I', 'F', 'R' (see SGLatt from GSASIIspc.SpcGroup) |
---|
768 | :param system: one of 'cubic', 'hexagonal', 'tetragonal', 'orthorhombic', 'trigonal' (for R) |
---|
769 | 'monoclinic', 'triclinic' (see SGSys from GSASIIspc.SpcGroup) |
---|
770 | :return: a number between 0 and 13 |
---|
771 | or throws a ValueError exception if the combination of center, system is not found (i.e. non-standard) |
---|
772 | |
---|
773 | """ |
---|
774 | if center.upper() == 'F' and system.lower() == 'cubic': |
---|
775 | return 0 |
---|
776 | elif center.upper() == 'I' and system.lower() == 'cubic': |
---|
777 | return 1 |
---|
778 | elif center.upper() == 'P' and system.lower() == 'cubic': |
---|
779 | return 2 |
---|
780 | elif center.upper() == 'R' and system.lower() == 'trigonal': |
---|
781 | return 3 |
---|
782 | elif center.upper() == 'P' and system.lower() == 'hexagonal': |
---|
783 | return 4 |
---|
784 | elif center.upper() == 'I' and system.lower() == 'tetragonal': |
---|
785 | return 5 |
---|
786 | elif center.upper() == 'P' and system.lower() == 'tetragonal': |
---|
787 | return 6 |
---|
788 | elif center.upper() == 'F' and system.lower() == 'orthorhombic': |
---|
789 | return 7 |
---|
790 | elif center.upper() == 'I' and system.lower() == 'orthorhombic': |
---|
791 | return 8 |
---|
792 | elif center.upper() == 'C' and system.lower() == 'orthorhombic': |
---|
793 | return 9 |
---|
794 | elif center.upper() == 'P' and system.lower() == 'orthorhombic': |
---|
795 | return 10 |
---|
796 | elif center.upper() == 'C' and system.lower() == 'monoclinic': |
---|
797 | return 11 |
---|
798 | elif center.upper() == 'P' and system.lower() == 'monoclinic': |
---|
799 | return 12 |
---|
800 | elif center.upper() == 'P' and system.lower() == 'triclinic': |
---|
801 | return 13 |
---|
802 | raise ValueError,'non-standard Bravais lattice center=%s, cell=%s' % (center,system) |
---|
803 | |
---|
804 | def GenHBravais(dmin,Bravais,A): |
---|
805 | """Generate the positionally unique powder diffraction reflections |
---|
806 | |
---|
807 | :param dmin: minimum d-spacing in A |
---|
808 | :param Bravais: lattice type (see GetBraviasNum). Bravais is one of:: |
---|
809 | 0 F cubic |
---|
810 | 1 I cubic |
---|
811 | 2 P cubic |
---|
812 | 3 R hexagonal (trigonal not rhombohedral) |
---|
813 | 4 P hexagonal |
---|
814 | 5 I tetragonal |
---|
815 | 6 P tetragonal |
---|
816 | 7 F orthorhombic |
---|
817 | 8 I orthorhombic |
---|
818 | 9 C orthorhombic |
---|
819 | 10 P orthorhombic |
---|
820 | 11 C monoclinic |
---|
821 | 12 P monoclinic |
---|
822 | 13 P triclinic |
---|
823 | |
---|
824 | :param A: reciprocal metric tensor elements as [G11,G22,G33,2*G12,2*G13,2*G23] |
---|
825 | :return: HKL unique d list of [h,k,l,d,-1] sorted with largest d first |
---|
826 | |
---|
827 | """ |
---|
828 | import math |
---|
829 | if Bravais in [9,11]: |
---|
830 | Cent = 'C' |
---|
831 | elif Bravais in [1,5,8]: |
---|
832 | Cent = 'I' |
---|
833 | elif Bravais in [0,7]: |
---|
834 | Cent = 'F' |
---|
835 | elif Bravais in [3]: |
---|
836 | Cent = 'R' |
---|
837 | else: |
---|
838 | Cent = 'P' |
---|
839 | Hmax = MaxIndex(dmin,A) |
---|
840 | dminsq = 1./(dmin**2) |
---|
841 | HKL = [] |
---|
842 | if Bravais == 13: #triclinic |
---|
843 | for l in range(-Hmax[2],Hmax[2]+1): |
---|
844 | for k in range(-Hmax[1],Hmax[1]+1): |
---|
845 | hmin = 0 |
---|
846 | if (k < 0): hmin = 1 |
---|
847 | if (k ==0 and l < 0): hmin = 1 |
---|
848 | for h in range(hmin,Hmax[0]+1): |
---|
849 | H=[h,k,l] |
---|
850 | rdsq = calc_rDsq(H,A) |
---|
851 | if 0 < rdsq <= dminsq: |
---|
852 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
853 | elif Bravais in [11,12]: #monoclinic - b unique |
---|
854 | Hmax = SwapIndx(2,Hmax) |
---|
855 | for h in range(Hmax[0]+1): |
---|
856 | for k in range(-Hmax[1],Hmax[1]+1): |
---|
857 | lmin = 0 |
---|
858 | if k < 0:lmin = 1 |
---|
859 | for l in range(lmin,Hmax[2]+1): |
---|
860 | [h,k,l] = SwapIndx(-2,[h,k,l]) |
---|
861 | H = [] |
---|
862 | if CentCheck(Cent,[h,k,l]): H=[h,k,l] |
---|
863 | if H: |
---|
864 | rdsq = calc_rDsq(H,A) |
---|
865 | if 0 < rdsq <= dminsq: |
---|
866 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
867 | [h,k,l] = SwapIndx(2,[h,k,l]) |
---|
868 | elif Bravais in [7,8,9,10]: #orthorhombic |
---|
869 | for h in range(Hmax[0]+1): |
---|
870 | for k in range(Hmax[1]+1): |
---|
871 | for l in range(Hmax[2]+1): |
---|
872 | H = [] |
---|
873 | if CentCheck(Cent,[h,k,l]): H=[h,k,l] |
---|
874 | if H: |
---|
875 | rdsq = calc_rDsq(H,A) |
---|
876 | if 0 < rdsq <= dminsq: |
---|
877 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
878 | elif Bravais in [5,6]: #tetragonal |
---|
879 | for l in range(Hmax[2]+1): |
---|
880 | for k in range(Hmax[1]+1): |
---|
881 | for h in range(k,Hmax[0]+1): |
---|
882 | H = [] |
---|
883 | if CentCheck(Cent,[h,k,l]): H=[h,k,l] |
---|
884 | if H: |
---|
885 | rdsq = calc_rDsq(H,A) |
---|
886 | if 0 < rdsq <= dminsq: |
---|
887 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
888 | elif Bravais in [3,4]: |
---|
889 | lmin = 0 |
---|
890 | if Bravais == 3: lmin = -Hmax[2] #hexagonal/trigonal |
---|
891 | for l in range(lmin,Hmax[2]+1): |
---|
892 | for k in range(Hmax[1]+1): |
---|
893 | hmin = k |
---|
894 | if l < 0: hmin += 1 |
---|
895 | for h in range(hmin,Hmax[0]+1): |
---|
896 | H = [] |
---|
897 | if CentCheck(Cent,[h,k,l]): H=[h,k,l] |
---|
898 | if H: |
---|
899 | rdsq = calc_rDsq(H,A) |
---|
900 | if 0 < rdsq <= dminsq: |
---|
901 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
902 | |
---|
903 | else: #cubic |
---|
904 | for l in range(Hmax[2]+1): |
---|
905 | for k in range(l,Hmax[1]+1): |
---|
906 | for h in range(k,Hmax[0]+1): |
---|
907 | H = [] |
---|
908 | if CentCheck(Cent,[h,k,l]): H=[h,k,l] |
---|
909 | if H: |
---|
910 | rdsq = calc_rDsq(H,A) |
---|
911 | if 0 < rdsq <= dminsq: |
---|
912 | HKL.append([h,k,l,rdsq2d(rdsq,6),-1]) |
---|
913 | return sortHKLd(HKL,True,False) |
---|
914 | |
---|
915 | def getHKLmax(dmin,SGData,A): |
---|
916 | 'finds maximum allowed hkl for given A within dmin' |
---|
917 | SGLaue = SGData['SGLaue'] |
---|
918 | if SGLaue in ['3R','3mR']: #Rhombohedral axes |
---|
919 | Hmax = [0,0,0] |
---|
920 | cell = A2cell(A) |
---|
921 | aHx = cell[0]*math.sqrt(2.0*(1.0-cosd(cell[3]))) |
---|
922 | cHx = cell[0]*math.sqrt(3.0*(1.0+2.0*cosd(cell[3]))) |
---|
923 | Hmax[0] = Hmax[1] = int(round(aHx/dmin)) |
---|
924 | Hmax[2] = int(round(cHx/dmin)) |
---|
925 | #print Hmax,aHx,cHx |
---|
926 | else: # all others |
---|
927 | Hmax = MaxIndex(dmin,A) |
---|
928 | return Hmax |
---|
929 | |
---|
930 | def GenHLaue(dmin,SGData,A): |
---|
931 | """Generate the crystallographically unique powder diffraction reflections |
---|
932 | for a lattice and Bravais type |
---|
933 | |
---|
934 | :param dmin: minimum d-spacing |
---|
935 | :param SGData: space group dictionary with at least |
---|
936 | |
---|
937 | * 'SGLaue': Laue group symbol: one of '-1','2/m','mmm','4/m','6/m','4/mmm','6/mmm', '3m1', '31m', '3', '3R', '3mR', 'm3', 'm3m' |
---|
938 | * 'SGLatt': lattice centering: one of 'P','A','B','C','I','F' |
---|
939 | * 'SGUniq': code for unique monoclinic axis one of 'a','b','c' (only if 'SGLaue' is '2/m') otherwise an empty string |
---|
940 | |
---|
941 | :param A: reciprocal metric tensor elements as [G11,G22,G33,2*G12,2*G13,2*G23] |
---|
942 | :return: HKL = list of [h,k,l,d] sorted with largest d first and is unique |
---|
943 | part of reciprocal space ignoring anomalous dispersion |
---|
944 | |
---|
945 | """ |
---|
946 | import math |
---|
947 | SGLaue = SGData['SGLaue'] |
---|
948 | SGLatt = SGData['SGLatt'] |
---|
949 | SGUniq = SGData['SGUniq'] |
---|
950 | #finds maximum allowed hkl for given A within dmin |
---|
951 | Hmax = getHKLmax(dmin,SGData,A) |
---|
952 | |
---|
953 | dminsq = 1./(dmin**2) |
---|
954 | HKL = [] |
---|
955 | if SGLaue == '-1': #triclinic |
---|
956 | for l in range(-Hmax[2],Hmax[2]+1): |
---|
957 | for k in range(-Hmax[1],Hmax[1]+1): |
---|
958 | hmin = 0 |
---|
959 | if (k < 0) or (k ==0 and l < 0): hmin = 1 |
---|
960 | for h in range(hmin,Hmax[0]+1): |
---|
961 | H = [] |
---|
962 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
963 | if H: |
---|
964 | rdsq = calc_rDsq(H,A) |
---|
965 | if 0 < rdsq <= dminsq: |
---|
966 | HKL.append([h,k,l,1/math.sqrt(rdsq)]) |
---|
967 | elif SGLaue == '2/m': #monoclinic |
---|
968 | axisnum = 1 + ['a','b','c'].index(SGUniq) |
---|
969 | Hmax = SwapIndx(axisnum,Hmax) |
---|
970 | for h in range(Hmax[0]+1): |
---|
971 | for k in range(-Hmax[1],Hmax[1]+1): |
---|
972 | lmin = 0 |
---|
973 | if k < 0:lmin = 1 |
---|
974 | for l in range(lmin,Hmax[2]+1): |
---|
975 | [h,k,l] = SwapIndx(-axisnum,[h,k,l]) |
---|
976 | H = [] |
---|
977 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
978 | if H: |
---|
979 | rdsq = calc_rDsq(H,A) |
---|
980 | if 0 < rdsq <= dminsq: |
---|
981 | HKL.append([h,k,l,1/math.sqrt(rdsq)]) |
---|
982 | [h,k,l] = SwapIndx(axisnum,[h,k,l]) |
---|
983 | elif SGLaue in ['mmm','4/m','6/m']: #orthorhombic |
---|
984 | for l in range(Hmax[2]+1): |
---|
985 | for h in range(Hmax[0]+1): |
---|
986 | kmin = 1 |
---|
987 | if SGLaue == 'mmm' or h ==0: kmin = 0 |
---|
988 | for k in range(kmin,Hmax[1]+1): |
---|
989 | H = [] |
---|
990 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
991 | if H: |
---|
992 | rdsq = calc_rDsq(H,A) |
---|
993 | if 0 < rdsq <= dminsq: |
---|
994 | HKL.append([h,k,l,1/math.sqrt(rdsq)]) |
---|
995 | elif SGLaue in ['4/mmm','6/mmm']: #tetragonal & hexagonal |
---|
996 | for l in range(Hmax[2]+1): |
---|
997 | for h in range(Hmax[0]+1): |
---|
998 | for k in range(h+1): |
---|
999 | H = [] |
---|
1000 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
1001 | if H: |
---|
1002 | rdsq = calc_rDsq(H,A) |
---|
1003 | if 0 < rdsq <= dminsq: |
---|
1004 | HKL.append([h,k,l,1/math.sqrt(rdsq)]) |
---|
1005 | elif SGLaue in ['3m1','31m','3','3R','3mR']: #trigonals |
---|
1006 | for l in range(-Hmax[2],Hmax[2]+1): |
---|
1007 | hmin = 0 |
---|
1008 | if l < 0: hmin = 1 |
---|
1009 | for h in range(hmin,Hmax[0]+1): |
---|
1010 | if SGLaue in ['3R','3']: |
---|
1011 | kmax = h |
---|
1012 | kmin = -int((h-1.)/2.) |
---|
1013 | else: |
---|
1014 | kmin = 0 |
---|
1015 | kmax = h |
---|
1016 | if SGLaue in ['3m1','3mR'] and l < 0: kmax = h-1 |
---|
1017 | if SGLaue == '31m' and l < 0: kmin = 1 |
---|
1018 | for k in range(kmin,kmax+1): |
---|
1019 | H = [] |
---|
1020 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
1021 | if SGLaue in ['3R','3mR']: |
---|
1022 | H = Hx2Rh(H) |
---|
1023 | if H: |
---|
1024 | rdsq = calc_rDsq(H,A) |
---|
1025 | if 0 < rdsq <= dminsq: |
---|
1026 | HKL.append([H[0],H[1],H[2],1/math.sqrt(rdsq)]) |
---|
1027 | else: #cubic |
---|
1028 | for h in range(Hmax[0]+1): |
---|
1029 | for k in range(h+1): |
---|
1030 | lmin = 0 |
---|
1031 | lmax = k |
---|
1032 | if SGLaue =='m3': |
---|
1033 | lmax = h-1 |
---|
1034 | if h == k: lmax += 1 |
---|
1035 | for l in range(lmin,lmax+1): |
---|
1036 | H = [] |
---|
1037 | if CentCheck(SGLatt,[h,k,l]): H=[h,k,l] |
---|
1038 | if H: |
---|
1039 | rdsq = calc_rDsq(H,A) |
---|
1040 | if 0 < rdsq <= dminsq: |
---|
1041 | HKL.append([h,k,l,1/math.sqrt(rdsq)]) |
---|
1042 | return sortHKLd(HKL,True,True) |
---|
1043 | |
---|
1044 | def GenPfHKLs(nMax,SGData,A): |
---|
1045 | """Generate the unique pole figure reflections for a lattice and Bravais type. |
---|
1046 | Min d-spacing=1.0A & no more than nMax returned |
---|
1047 | |
---|
1048 | :param nMax: maximum number of hkls returned |
---|
1049 | :param SGData: space group dictionary with at least |
---|
1050 | |
---|
1051 | * 'SGLaue': Laue group symbol: one of '-1','2/m','mmm','4/m','6/m','4/mmm','6/mmm', '3m1', '31m', '3', '3R', '3mR', 'm3', 'm3m' |
---|
1052 | * 'SGLatt': lattice centering: one of 'P','A','B','C','I','F' |
---|
1053 | * 'SGUniq': code for unique monoclinic axis one of 'a','b','c' (only if 'SGLaue' is '2/m') otherwise an empty string |
---|
1054 | |
---|
1055 | :param A: reciprocal metric tensor elements as [G11,G22,G33,2*G12,2*G13,2*G23] |
---|
1056 | :return: HKL = list of 'h k l' strings sorted with largest d first; no duplicate zones |
---|
1057 | |
---|
1058 | """ |
---|
1059 | HKL = np.array(GenHLaue(1.0,SGData,A)).T[:3].T #strip d-spacings |
---|
1060 | N = min(nMax,len(HKL)) |
---|
1061 | return ['%d %d %d'%(h[0],h[1],h[2]) for h in HKL[:N]] |
---|
1062 | |
---|
1063 | def GenSSHLaue(dmin,SGData,SSGData,Vec,maxH,A): |
---|
1064 | 'needs a doc string' |
---|
1065 | HKLs = [] |
---|
1066 | vec = np.array(Vec) |
---|
1067 | vstar = np.sqrt(calc_rDsq(vec,A)) #find extra needed for -n SS reflections |
---|
1068 | dvec = 1./(maxH*vstar+1./dmin) |
---|
1069 | HKL = GenHLaue(dvec,SGData,A) |
---|
1070 | SSdH = [vec*h for h in range(-maxH,maxH+1)] |
---|
1071 | SSdH = dict(zip(range(-maxH,maxH+1),SSdH)) |
---|
1072 | for h,k,l,d in HKL: |
---|
1073 | ext = G2spc.GenHKLf([h,k,l],SGData)[0] #h,k,l must be integral values here |
---|
1074 | if not ext and d >= dmin: |
---|
1075 | HKLs.append([h,k,l,0,d]) |
---|
1076 | for dH in SSdH: |
---|
1077 | if dH: |
---|
1078 | DH = SSdH[dH] |
---|
1079 | H = [h+DH[0],k+DH[1],l+DH[2]] |
---|
1080 | d = 1/np.sqrt(calc_rDsq(H,A)) |
---|
1081 | if d >= dmin: |
---|
1082 | HKLM = np.array([h,k,l,dH]) |
---|
1083 | if G2spc.checkSSLaue([h,k,l,dH],SGData,SSGData) and G2spc.checkSSextc(HKLM,SSGData): |
---|
1084 | HKLs.append([h,k,l,dH,d]) |
---|
1085 | return HKLs |
---|
1086 | |
---|
1087 | def LaueUnique2(SGData,refList): |
---|
1088 | ''' Impose Laue symmetry on hkl |
---|
1089 | :param SGData: space group data from 'P '+Laue |
---|
1090 | :param HKLF: np.array([[h,k,l,...]]) reflection set to be converted |
---|
1091 | |
---|
1092 | :return: HKLF new reflection array with imposed Laue symmetry |
---|
1093 | ''' |
---|
1094 | for ref in refList: |
---|
1095 | H = ref[:3] |
---|
1096 | Uniq = G2spc.GenHKLf(H,SGData)[2] |
---|
1097 | Uniq = G2mth.sortArray(G2mth.sortArray(G2mth.sortArray(Uniq,2),1),0) |
---|
1098 | ref[:3] = Uniq[-1] |
---|
1099 | return refList |
---|
1100 | |
---|
1101 | def LaueUnique(Laue,HKLF): |
---|
1102 | ''' Impose Laue symmetry on hkl |
---|
1103 | :param Laue: str Laue symbol |
---|
1104 | centrosymmetric Laue groups |
---|
1105 | ['-1','2/m','112/m','2/m11','mmm','-42m','-4m2','4/mmm','-3','-31m','-3m1', |
---|
1106 | '6/m','6/mmm','m3','m3m'] |
---|
1107 | noncentrosymmetric Laue groups |
---|
1108 | ['1','2','211','112','m','m11','11m','222','mm2','m2m','2mm', |
---|
1109 | '4','-4','422','4mm','3','312','321','31m','3m1', |
---|
1110 | '6','-6','622','6mm','-62m','-6m2','23','432','-43m'] |
---|
1111 | :param HKLF: np.array([[h,k,l,...]]) reflection set to be converted |
---|
1112 | |
---|
1113 | :return: HKLF new reflection array with imposed Laue symmetry |
---|
1114 | ''' |
---|
1115 | |
---|
1116 | HKLFT = HKLF.T |
---|
1117 | mat41 = np.array([[0,1,0],[-1,0,0],[0,0,1]]) #hkl -> k,-h,l |
---|
1118 | mat43 = np.array([[0,-1,0],[1,0,0],[0,0,1]]) #hkl -> -k,h,l |
---|
1119 | mat4bar = np.array([[0,-1,0],[1,0,0],[0,0,-1]]) #hkl -> k,-h,-l |
---|
1120 | mat31 = np.array([[-1,-1,0],[1,0,0],[0,0,1]]) #hkl -> ihl = -h-k,h,l |
---|
1121 | mat32 = np.array([[0,1,0],[-1,-1,0],[0,0,1]]) #hkl -> kil = k,-h-k,l |
---|
1122 | matd3 = np.array([[0,1,0],[0,0,1],[1,0,0]]) #hkl -> k,l,h |
---|
1123 | matd3q = np.array([[0,0,-1],[-1,0,0],[0,1,0]]) #hkl -> -l,-h,k |
---|
1124 | matd3t = np.array([[0,0,-1],[1,0,0],[0,-1,0]]) #hkl -> -l,h,-k |
---|
1125 | matd3p = np.array([[0,1,0],[0,0,-1],[-1,0,0]]) #hkl -> k,-l,-h |
---|
1126 | mat6 = np.array([[1,1,0],[-1,0,0],[0,0,1]]) #hkl -> h+k,-h,l really 65 |
---|
1127 | matdm = np.array([[0,1,0],[1,0,0],[0,0,1]]) #hkl -> k,h,l |
---|
1128 | matdmt = np.array([[0,-1,0],[-1,0,0],[0,0,1]]) #hkl -> -k,-h,l |
---|
1129 | matdmp = np.array([[-1,-1,0],[0,1,0],[0,0,1]]) #hkl -> -h-k,k,l |
---|
1130 | matdmq = np.array([[-1,0,0],[1,1,0],[0,0,1]]) #hkl -> -h,h+k,l |
---|
1131 | matkm = np.array([[-1,0,0],[1,1,0],[0,0,1]]) #hkl -> -h,h+k,l |
---|
1132 | matkmp = np.array([[1,0,0],[-1,-1,0],[0,0,1]]) #hkl -> h,-h-k,l |
---|
1133 | matd2 = np.array([[0,1,0],[1,0,0],[0,0,-1]]) #hkl -> k,h,-l |
---|
1134 | matd2p = np.array([[-1,-1,0],[0,1,0],[0,0,-1]]) #hkl -> -h-k,k,-l |
---|
1135 | matdm3 = np.array([[1,0,0],[0,0,1],[0,1,0]]) #hkl -> h,l,k |
---|
1136 | mat2d43 = np.array([[0,1,0],[1,0,0],[0,0,1]]) #hkl -> k,-h,l |
---|
1137 | math2 = np.array([[0,-1,0],[-1,0,0],[0,0,-1]]) #hkl -> -k,-h,-l |
---|
1138 | matk2 = np.array([[-1,0,0],[1,1,0],[0,0,-1]]) #hkl -> -h,-i,-l |
---|
1139 | #triclinic |
---|
1140 | if Laue == '1': #ok |
---|
1141 | pass |
---|
1142 | elif Laue == '-1': #ok |
---|
1143 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1144 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]<0),HKLFT[:3]*np.array([-1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1145 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([-1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1146 | #monoclinic |
---|
1147 | #noncentrosymmetric - all ok |
---|
1148 | elif Laue == '2': |
---|
1149 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1150 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([-1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1151 | elif Laue == '1 1 2': |
---|
1152 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1153 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]<0),HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1154 | elif Laue == '2 1 1': |
---|
1155 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1156 | HKLFT[:3] = np.where((HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1157 | elif Laue == 'm': |
---|
1158 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1159 | elif Laue == 'm 1 1': |
---|
1160 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1161 | elif Laue == '1 1 m': |
---|
1162 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1163 | #centrosymmetric - all ok |
---|
1164 | elif Laue == '2/m 1 1': |
---|
1165 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1166 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1167 | HKLFT[:3] = np.where((HKLFT[2]*HKLFT[0]==0)&(HKLFT[1]<0),HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1168 | elif Laue == '2/m': |
---|
1169 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1170 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1171 | HKLFT[:3] = np.where((HKLFT[0]*HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1172 | elif Laue == '1 1 2/m': |
---|
1173 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1174 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1175 | HKLFT[:3] = np.where((HKLFT[1]*HKLFT[2]==0)&(HKLFT[0]<0),HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1176 | #orthorhombic |
---|
1177 | #noncentrosymmetric - all OK |
---|
1178 | elif Laue == '2 2 2': |
---|
1179 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1180 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1181 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1182 | HKLFT[:3] = np.where((HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1183 | elif Laue == 'm m 2': |
---|
1184 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1185 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1186 | elif Laue == '2 m m': |
---|
1187 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1188 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1189 | elif Laue == 'm 2 m': |
---|
1190 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1191 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1192 | #centrosymmetric - all ok |
---|
1193 | elif Laue == 'm m m': |
---|
1194 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1195 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1196 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1197 | #tetragonal |
---|
1198 | #noncentrosymmetric - all ok |
---|
1199 | elif Laue == '4': |
---|
1200 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1201 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1202 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]>0),np.squeeze(np.inner(HKLF[:,:3],mat41[nxs,:,:])).T,HKLFT[:3]) |
---|
1203 | elif Laue == '-4': |
---|
1204 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1205 | HKLFT[:3] = np.where(HKLFT[0]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1206 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1207 | HKLFT[:3] = np.where(HKLFT[1]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1208 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1209 | elif Laue == '4 2 2': |
---|
1210 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1211 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1212 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1213 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[1]<HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1214 | HKLFT[:3] = np.where(HKLFT[0]==0,np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) #in lieu od 2-fold |
---|
1215 | elif Laue == '4 m m': |
---|
1216 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1217 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1218 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1219 | HKLFT[:3] = np.where(HKLFT[0]<HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1220 | elif Laue == '-4 2 m': |
---|
1221 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1222 | HKLFT[:3] = np.where(HKLFT[0]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1223 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1224 | HKLFT[:3] = np.where(HKLFT[1]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1225 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1226 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1227 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1228 | elif Laue == '-4 m 2': |
---|
1229 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1230 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1231 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[1]<=0),np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1232 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]<0),HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1233 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[1]==0),np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1234 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1235 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[0]>HKLFT[1]),np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1236 | #centrosymmetric - all ok |
---|
1237 | elif Laue == '4/m': |
---|
1238 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1239 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1240 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1241 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]>0),np.squeeze(np.inner(HKLF[:,:3],mat41[nxs,:,:])).T,HKLFT[:3]) |
---|
1242 | elif Laue == '4/m m m': |
---|
1243 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1244 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1245 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1246 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],mat41[nxs,:,:])).T,HKLFT[:3]) |
---|
1247 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1248 | #trigonal - all hex cell |
---|
1249 | #noncentrosymmetric - all ok |
---|
1250 | elif Laue == '3': |
---|
1251 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1252 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1253 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1254 | elif Laue == '3 1 2': |
---|
1255 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matk2[nxs,:,:])).T,HKLFT[:3]) |
---|
1256 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1257 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1258 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1259 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],matk2[nxs,:,:])).T,HKLFT[:3]) |
---|
1260 | elif Laue == '3 2 1': |
---|
1261 | HKLFT[:3] = np.where(HKLFT[0]<=-2*HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1262 | HKLFT[:3] = np.where(HKLFT[1]<-2*HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1263 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1264 | HKLFT[:3] = np.where((HKLFT[2]>0)&(HKLFT[1]==HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1265 | HKLFT[:3] = np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T |
---|
1266 | HKLFT[:3] = np.where((HKLFT[0]!=0)&(HKLFT[2]>0)&(HKLFT[0]==-2*HKLFT[1]),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1267 | elif Laue == '3 1 m': |
---|
1268 | HKLFT[:3] = np.where(HKLFT[0]>=HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1269 | HKLFT[:3] = np.where(2*HKLFT[1]<-HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1270 | HKLFT[:3] = np.where(HKLFT[1]>-2*HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matdmp[nxs,:,:])).T,HKLFT[:3]) |
---|
1271 | HKLFT[:3] = np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T |
---|
1272 | elif Laue == '3 m 1': |
---|
1273 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1274 | HKLFT[:3] = np.where((HKLFT[1]+HKLFT[0])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1275 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],matkm[nxs,:,:])).T,HKLFT[:3]) |
---|
1276 | #centrosymmetric |
---|
1277 | elif Laue == '-3': #ok |
---|
1278 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([-1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1279 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1280 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1281 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1282 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[0]<0),-np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1283 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],-mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1284 | elif Laue == '-3 m 1': #ok |
---|
1285 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1286 | HKLFT[:3] = np.where((HKLFT[1]+HKLFT[0])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1287 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],matkm[nxs,:,:])).T,HKLFT[:3]) |
---|
1288 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1289 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[1]<HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1290 | elif Laue == '-3 1 m': #ok |
---|
1291 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([-1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1292 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1293 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1294 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1295 | HKLFT[:3] = np.where(HKLFT[0]<=0,np.squeeze(np.inner(HKLF[:,:3],-mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1296 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1297 | #hexagonal |
---|
1298 | #noncentrosymmetric |
---|
1299 | elif Laue == '6': #ok |
---|
1300 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1301 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1302 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1303 | HKLFT[:3] = np.where(HKLFT[0]==0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1304 | elif Laue == '-6': #ok |
---|
1305 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1306 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1307 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1308 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1309 | elif Laue == '6 2 2': #ok |
---|
1310 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1311 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1312 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1313 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1314 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1315 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[0]>HKLFT[1]),np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1316 | elif Laue == '6 m m': #ok |
---|
1317 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1318 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1319 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1320 | HKLFT[:3] = np.where(HKLFT[0]==0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1321 | HKLFT[:3] = np.where(HKLFT[0]>HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1322 | elif Laue == '-6 m 2': #ok |
---|
1323 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matk2[nxs,:,:])).T,HKLFT[:3]) |
---|
1324 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1325 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1326 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat31[nxs,:,:])).T,HKLFT[:3]) |
---|
1327 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],matk2[nxs,:,:])).T,HKLFT[:3]) |
---|
1328 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1329 | elif Laue == '-6 2 m': #ok |
---|
1330 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1331 | HKLFT[:3] = np.where(HKLFT[0]<=-2*HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1332 | HKLFT[:3] = np.where(HKLFT[1]<-2*HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1333 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1334 | HKLFT[:3] = np.where((HKLFT[2]>0)&(HKLFT[1]==HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1335 | HKLFT[:3] = np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T |
---|
1336 | HKLFT[:3] = np.where(HKLFT[2]<0,np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1337 | HKLFT[:3] = np.where(HKLFT[0]>HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1338 | #centrosymmetric |
---|
1339 | elif Laue == '6/m': #ok |
---|
1340 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1341 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1342 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1343 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1344 | HKLFT[:3] = np.where(HKLFT[0]==0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1345 | elif Laue == '6/m m m': #ok |
---|
1346 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1347 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1348 | HKLFT[:3] = np.where((HKLFT[0]+HKLFT[1])<0,np.squeeze(np.inner(HKLF[:,:3],mat32[nxs,:,:])).T,HKLFT[:3]) |
---|
1349 | HKLFT[:3] = np.where(HKLFT[0]<0,np.squeeze(np.inner(HKLF[:,:3],mat6[nxs,:,:])).T,HKLFT[:3]) |
---|
1350 | HKLFT[:3] = np.where(HKLFT[0]>HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],matdm.T[nxs,:,:])).T,HKLFT[:3]) |
---|
1351 | #cubic - all ok |
---|
1352 | #noncentrosymmetric - |
---|
1353 | elif Laue == '2 3': |
---|
1354 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1355 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1356 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1357 | HKLFT[:3] = np.where((HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1358 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1359 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1360 | HKLFT[:3] = np.where((HKLFT[2]<0)&((HKLFT[0]>-HKLFT[2])|(HKLFT[1]>-HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3t[nxs,:,:])).T,HKLFT[:3]) |
---|
1361 | HKLFT[:3] = np.where((HKLFT[2]<0)&((HKLFT[0]>-HKLFT[2])|(HKLFT[1]>=-HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3t[nxs,:,:])).T,HKLFT[:3]) |
---|
1362 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([-1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1363 | elif Laue == '4 3 2': |
---|
1364 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,-1,-1])[:,nxs],HKLFT[:3]) |
---|
1365 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1366 | HKLFT[:3] = np.where(HKLFT[1]<0,np.squeeze(np.inner(HKLF[:,:3],mat43[nxs,:,:])).T,HKLFT[:3]) |
---|
1367 | HKLFT[:3] = np.where((HKLFT[2]==0)&(HKLFT[1]<HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matd2[nxs,:,:])).T,HKLFT[:3]) |
---|
1368 | HKLFT[:3] = np.where(HKLFT[0]==0,np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) #in lieu od 2-fold |
---|
1369 | HKLFT[:3] = np.where((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2]),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1370 | HKLFT[:3] = np.where((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2]),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1371 | HKLFT[:3] = np.where(HKLFT[1]==0,np.squeeze(np.inner(HKLF[:,:3],mat2d43[nxs,:,:])).T,HKLFT[:3]) |
---|
1372 | elif Laue == '-4 3 m': |
---|
1373 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1374 | HKLFT[:3] = np.where(HKLFT[0]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1375 | HKLFT[:3] = np.where(HKLFT[0]<=0,HKLFT[:3]*np.array([-1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1376 | HKLFT[:3] = np.where(HKLFT[1]<=0,np.squeeze(np.inner(HKLF[:,:3],mat4bar[nxs,:,:])).T,HKLFT[:3]) |
---|
1377 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[1]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1378 | HKLFT[:3] = np.where(HKLFT[1]<HKLFT[0],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1379 | HKLFT[:3] = np.where((HKLFT[0]==0)&(HKLFT[2]<0),HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1380 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1381 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1382 | HKLFT[:3] = np.where((HKLFT[2]>=0)&(HKLFT[1]<HKLFT[0]),np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1383 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([-1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1384 | HKLFT[:3] = np.where((HKLFT[0]<0)&(HKLFT[2]<-HKLFT[0])&(HKLFT[1]>HKLFT[2]),np.squeeze(np.inner(HKLF[:,:3],matd3q[nxs,:,:])).T,HKLFT[:3]) |
---|
1385 | HKLFT[:3] = np.where((HKLFT[0]<0)&(HKLFT[2]>=-HKLFT[0])&(HKLFT[1]>HKLFT[2]),np.squeeze(np.inner(HKLF[:,:3],matdm3[nxs,:,:])).T,HKLFT[:3]) |
---|
1386 | #centrosymmetric |
---|
1387 | elif Laue == 'm 3': |
---|
1388 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1389 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1390 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1391 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1392 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1393 | elif Laue == 'm 3 m': |
---|
1394 | HKLFT[:3] = np.where(HKLFT[0]<0,HKLFT[:3]*np.array([-1,1,1])[:,nxs],HKLFT[:3]) |
---|
1395 | HKLFT[:3] = np.where(HKLFT[1]<0,HKLFT[:3]*np.array([1,-1,1])[:,nxs],HKLFT[:3]) |
---|
1396 | HKLFT[:3] = np.where(HKLFT[2]<0,HKLFT[:3]*np.array([1,1,-1])[:,nxs],HKLFT[:3]) |
---|
1397 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1398 | HKLFT[:3] = np.where((HKLFT[2]>=0)&((HKLFT[0]>=HKLFT[2])|(HKLFT[1]>HKLFT[2])),np.squeeze(np.inner(HKLF[:,:3],matd3[nxs,:,:])).T,HKLFT[:3]) |
---|
1399 | HKLFT[:3] = np.where(HKLFT[0]>HKLFT[1],np.squeeze(np.inner(HKLF[:,:3],matdm[nxs,:,:])).T,HKLFT[:3]) |
---|
1400 | return HKLFT.T |
---|
1401 | |
---|
1402 | |
---|
1403 | #Spherical harmonics routines |
---|
1404 | def OdfChk(SGLaue,L,M): |
---|
1405 | 'needs doc string' |
---|
1406 | if not L%2 and abs(M) <= L: |
---|
1407 | if SGLaue == '0': #cylindrical symmetry |
---|
1408 | if M == 0: return True |
---|
1409 | elif SGLaue == '-1': |
---|
1410 | return True |
---|
1411 | elif SGLaue == '2/m': |
---|
1412 | if not abs(M)%2: return True |
---|
1413 | elif SGLaue == 'mmm': |
---|
1414 | if not abs(M)%2 and M >= 0: return True |
---|
1415 | elif SGLaue == '4/m': |
---|
1416 | if not abs(M)%4: return True |
---|
1417 | elif SGLaue == '4/mmm': |
---|
1418 | if not abs(M)%4 and M >= 0: return True |
---|
1419 | elif SGLaue in ['3R','3']: |
---|
1420 | if not abs(M)%3: return True |
---|
1421 | elif SGLaue in ['3mR','3m1','31m']: |
---|
1422 | if not abs(M)%3 and M >= 0: return True |
---|
1423 | elif SGLaue == '6/m': |
---|
1424 | if not abs(M)%6: return True |
---|
1425 | elif SGLaue == '6/mmm': |
---|
1426 | if not abs(M)%6 and M >= 0: return True |
---|
1427 | elif SGLaue == 'm3': |
---|
1428 | if M > 0: |
---|
1429 | if L%12 == 2: |
---|
1430 | if M <= L/12: return True |
---|
1431 | else: |
---|
1432 | if M <= L/12+1: return True |
---|
1433 | elif SGLaue == 'm3m': |
---|
1434 | if M > 0: |
---|
1435 | if L%12 == 2: |
---|
1436 | if M <= L/12: return True |
---|
1437 | else: |
---|
1438 | if M <= L/12+1: return True |
---|
1439 | return False |
---|
1440 | |
---|
1441 | def GenSHCoeff(SGLaue,SamSym,L,IfLMN=True): |
---|
1442 | 'needs doc string' |
---|
1443 | coeffNames = [] |
---|
1444 | for iord in [2*i+2 for i in range(L/2)]: |
---|
1445 | for m in [i-iord for i in range(2*iord+1)]: |
---|
1446 | if OdfChk(SamSym,iord,m): |
---|
1447 | for n in [i-iord for i in range(2*iord+1)]: |
---|
1448 | if OdfChk(SGLaue,iord,n): |
---|
1449 | if IfLMN: |
---|
1450 | coeffNames.append('C(%d,%d,%d)'%(iord,m,n)) |
---|
1451 | else: |
---|
1452 | coeffNames.append('C(%d,%d)'%(iord,n)) |
---|
1453 | return coeffNames |
---|
1454 | |
---|
1455 | def CrsAng(H,cell,SGData): |
---|
1456 | 'needs doc string' |
---|
1457 | a,b,c,al,be,ga = cell |
---|
1458 | SQ3 = 1.732050807569 |
---|
1459 | H1 = np.array([1,0,0]) |
---|
1460 | H2 = np.array([0,1,0]) |
---|
1461 | H3 = np.array([0,0,1]) |
---|
1462 | H4 = np.array([1,1,1]) |
---|
1463 | G,g = cell2Gmat(cell) |
---|
1464 | Laue = SGData['SGLaue'] |
---|
1465 | Naxis = SGData['SGUniq'] |
---|
1466 | if len(H.shape) == 1: |
---|
1467 | DH = np.inner(H,np.inner(G,H)) |
---|
1468 | else: |
---|
1469 | DH = np.array([np.inner(h,np.inner(G,h)) for h in H]) |
---|
1470 | if Laue == '2/m': |
---|
1471 | if Naxis == 'a': |
---|
1472 | DR = np.inner(H1,np.inner(G,H1)) |
---|
1473 | DHR = np.inner(H,np.inner(G,H1)) |
---|
1474 | elif Naxis == 'b': |
---|
1475 | DR = np.inner(H2,np.inner(G,H2)) |
---|
1476 | DHR = np.inner(H,np.inner(G,H2)) |
---|
1477 | else: |
---|
1478 | DR = np.inner(H3,np.inner(G,H3)) |
---|
1479 | DHR = np.inner(H,np.inner(G,H3)) |
---|
1480 | elif Laue in ['R3','R3m']: |
---|
1481 | DR = np.inner(H4,np.inner(G,H4)) |
---|
1482 | DHR = np.inner(H,np.inner(G,H4)) |
---|
1483 | else: |
---|
1484 | DR = np.inner(H3,np.inner(G,H3)) |
---|
1485 | DHR = np.inner(H,np.inner(G,H3)) |
---|
1486 | DHR /= np.sqrt(DR*DH) |
---|
1487 | phi = np.where(DHR <= 1.0,acosd(DHR),0.0) |
---|
1488 | if Laue == '-1': |
---|
1489 | BA = H.T[1]*a/(b-H.T[0]*cosd(ga)) |
---|
1490 | BB = H.T[0]*sind(ga)**2 |
---|
1491 | elif Laue == '2/m': |
---|
1492 | if Naxis == 'a': |
---|
1493 | BA = H.T[2]*b/(c-H.T[1]*cosd(al)) |
---|
1494 | BB = H.T[1]*sind(al)**2 |
---|
1495 | elif Naxis == 'b': |
---|
1496 | BA = H.T[0]*c/(a-H.T[2]*cosd(be)) |
---|
1497 | BB = H.T[2]*sind(be)**2 |
---|
1498 | else: |
---|
1499 | BA = H.T[1]*a/(b-H.T[0]*cosd(ga)) |
---|
1500 | BB = H.T[0]*sind(ga)**2 |
---|
1501 | elif Laue in ['mmm','4/m','4/mmm']: |
---|
1502 | BA = H.T[1]*a |
---|
1503 | BB = H.T[0]*b |
---|
1504 | elif Laue in ['3R','3mR']: |
---|
1505 | BA = H.T[0]+H.T[1]-2.0*H.T[2] |
---|
1506 | BB = SQ3*(H.T[0]-H.T[1]) |
---|
1507 | elif Laue in ['m3','m3m']: |
---|
1508 | BA = H.T[1] |
---|
1509 | BB = H.T[0] |
---|
1510 | else: |
---|
1511 | BA = H.T[0]+2.0*H.T[1] |
---|
1512 | BB = SQ3*H.T[0] |
---|
1513 | beta = atan2d(BA,BB) |
---|
1514 | return phi,beta |
---|
1515 | |
---|
1516 | def SamAng(Tth,Gangls,Sangl,IFCoup): |
---|
1517 | """Compute sample orientation angles vs laboratory coord. system |
---|
1518 | |
---|
1519 | :param Tth: Signed theta |
---|
1520 | :param Gangls: Sample goniometer angles phi,chi,omega,azmuth |
---|
1521 | :param Sangl: Sample angle zeros om-0, chi-0, phi-0 |
---|
1522 | :param IFCoup: True if omega & 2-theta coupled in CW scan |
---|
1523 | :returns: |
---|
1524 | psi,gam: Sample odf angles |
---|
1525 | dPSdA,dGMdA: Angle zero derivatives |
---|
1526 | """ |
---|
1527 | |
---|
1528 | if IFCoup: |
---|
1529 | GSomeg = sind(Gangls[2]+Tth) |
---|
1530 | GComeg = cosd(Gangls[2]+Tth) |
---|
1531 | else: |
---|
1532 | GSomeg = sind(Gangls[2]) |
---|
1533 | GComeg = cosd(Gangls[2]) |
---|
1534 | GSTth = sind(Tth) |
---|
1535 | GCTth = cosd(Tth) |
---|
1536 | GSazm = sind(Gangls[3]) |
---|
1537 | GCazm = cosd(Gangls[3]) |
---|
1538 | GSchi = sind(Gangls[1]) |
---|
1539 | GCchi = cosd(Gangls[1]) |
---|
1540 | GSphi = sind(Gangls[0]+Sangl[2]) |
---|
1541 | GCphi = cosd(Gangls[0]+Sangl[2]) |
---|
1542 | SSomeg = sind(Sangl[0]) |
---|
1543 | SComeg = cosd(Sangl[0]) |
---|
1544 | SSchi = sind(Sangl[1]) |
---|
1545 | SCchi = cosd(Sangl[1]) |
---|
1546 | AT = -GSTth*GComeg+GCTth*GCazm*GSomeg |
---|
1547 | BT = GSTth*GSomeg+GCTth*GCazm*GComeg |
---|
1548 | CT = -GCTth*GSazm*GSchi |
---|
1549 | DT = -GCTth*GSazm*GCchi |
---|
1550 | |
---|
1551 | BC1 = -AT*GSphi+(CT+BT*GCchi)*GCphi |
---|
1552 | BC2 = DT-BT*GSchi |
---|
1553 | BC3 = AT*GCphi+(CT+BT*GCchi)*GSphi |
---|
1554 | |
---|
1555 | BC = BC1*SComeg*SCchi+BC2*SComeg*SSchi-BC3*SSomeg |
---|
1556 | psi = acosd(BC) |
---|
1557 | |
---|
1558 | BD = 1.0-BC**2 |
---|
1559 | C = np.where(BD>1.e-6,rpd/np.sqrt(BD),0.) |
---|
1560 | dPSdA = [-C*(-BC1*SSomeg*SCchi-BC2*SSomeg*SSchi-BC3*SComeg), |
---|
1561 | -C*(-BC1*SComeg*SSchi+BC2*SComeg*SCchi), |
---|
1562 | -C*(-BC1*SSomeg-BC3*SComeg*SCchi)] |
---|
1563 | |
---|
1564 | BA = -BC1*SSchi+BC2*SCchi |
---|
1565 | BB = BC1*SSomeg*SCchi+BC2*SSomeg*SSchi+BC3*SComeg |
---|
1566 | gam = atan2d(BB,BA) |
---|
1567 | |
---|
1568 | BD = (BA**2+BB**2)/rpd |
---|
1569 | |
---|
1570 | dBAdO = 0 |
---|
1571 | dBAdC = -BC1*SCchi-BC2*SSchi |
---|
1572 | dBAdF = BC3*SSchi |
---|
1573 | |
---|
1574 | dBBdO = BC1*SComeg*SCchi+BC2*SComeg*SSchi-BC3*SSomeg |
---|
1575 | dBBdC = -BC1*SSomeg*SSchi+BC2*SSomeg*SCchi |
---|
1576 | dBBdF = BC1*SComeg-BC3*SSomeg*SCchi |
---|
1577 | |
---|
1578 | dGMdA = np.where(BD > 1.e-6,[(BA*dBBdO-BB*dBAdO)/BD,(BA*dBBdC-BB*dBAdC)/BD, \ |
---|
1579 | (BA*dBBdF-BB*dBAdF)/BD],[np.zeros_like(BD),np.zeros_like(BD),np.zeros_like(BD)]) |
---|
1580 | |
---|
1581 | return psi,gam,dPSdA,dGMdA |
---|
1582 | |
---|
1583 | BOH = { |
---|
1584 | 'L=2':[[],[],[]], |
---|
1585 | 'L=4':[[0.30469720,0.36418281],[],[]], |
---|
1586 | 'L=6':[[-0.14104740,0.52775103],[],[]], |
---|
1587 | 'L=8':[[0.28646862,0.21545346,0.32826995],[],[]], |
---|
1588 | 'L=10':[[-0.16413497,0.33078546,0.39371345],[],[]], |
---|
1589 | 'L=12':[[0.26141975,0.27266871,0.03277460,0.32589402], |
---|
1590 | [0.09298802,-0.23773812,0.49446631,0.0],[]], |
---|
1591 | 'L=14':[[-0.17557309,0.25821932,0.27709173,0.33645360],[],[]], |
---|
1592 | 'L=16':[[0.24370673,0.29873515,0.06447688,0.00377,0.32574495], |
---|
1593 | [0.12039646,-0.25330128,0.23950998,0.40962508,0.0],[]], |
---|
1594 | 'L=18':[[-0.16914245,0.17017340,0.34598142,0.07433932,0.32696037], |
---|
1595 | [-0.06901768,0.16006562,-0.24743528,0.47110273,0.0],[]], |
---|
1596 | 'L=20':[[0.23067026,0.31151832,0.09287682,0.01089683,0.00037564,0.32573563], |
---|
1597 | [0.13615420,-0.25048007,0.12882081,0.28642879,0.34620433,0.0],[]], |
---|
1598 | 'L=22':[[-0.16109560,0.10244188,0.36285175,0.13377513,0.01314399,0.32585583], |
---|
1599 | [-0.09620055,0.20244115,-0.22389483,0.17928946,0.42017231,0.0],[]], |
---|
1600 | 'L=24':[[0.22050742,0.31770654,0.11661736,0.02049853,0.00150861,0.00003426,0.32573505], |
---|
1601 | [0.13651722,-0.21386648,0.00522051,0.33939435,0.10837396,0.32914497,0.0], |
---|
1602 | [0.05378596,-0.11945819,0.16272298,-0.26449730,0.44923956,0.0,0.0]], |
---|
1603 | 'L=26':[[-0.15435003,0.05261630,0.35524646,0.18578869,0.03259103,0.00186197,0.32574594], |
---|
1604 | [-0.11306511,0.22072681,-0.18706142,0.05439948,0.28122966,0.35634355,0.0],[]], |
---|
1605 | 'L=28':[[0.21225019,0.32031716,0.13604702,0.03132468,0.00362703,0.00018294,0.00000294,0.32573501], |
---|
1606 | [0.13219496,-0.17206256,-0.08742608,0.32671661,0.17973107,0.02567515,0.32619598,0.0], |
---|
1607 | [0.07989184,-0.16735346,0.18839770,-0.20705337,0.12926808,0.42715602,0.0,0.0]], |
---|
1608 | 'L=30':[[-0.14878368,0.01524973,0.33628434,0.22632587,0.05790047,0.00609812,0.00022898,0.32573594], |
---|
1609 | [-0.11721726,0.20915005,-0.11723436,-0.07815329,0.31318947,0.13655742,0.33241385,0.0], |
---|
1610 | [-0.04297703,0.09317876,-0.11831248,0.17355132,-0.28164031,0.42719361,0.0,0.0]], |
---|
1611 | 'L=32':[[0.20533892,0.32087437,0.15187897,0.04249238,0.00670516,0.00054977,0.00002018,0.00000024,0.32573501], |
---|
1612 | [0.12775091,-0.13523423,-0.14935701,0.28227378,0.23670434,0.05661270,0.00469819,0.32578978,0.0], |
---|
1613 | [0.09703829,-0.19373733,0.18610682,-0.14407046,0.00220535,0.26897090,0.36633402,0.0,0.0]], |
---|
1614 | 'L=34':[[-0.14409234,-0.01343681,0.31248977,0.25557722,0.08571889,0.01351208,0.00095792,0.00002550,0.32573508], |
---|
1615 | [-0.11527834,0.18472133,-0.04403280,-0.16908618,0.27227021,0.21086614,0.04041752,0.32688152,0.0], |
---|
1616 | [-0.06773139,0.14120811,-0.15835721,0.18357456,-0.19364673,0.08377174,0.43116318,0.0,0.0]] |
---|
1617 | } |
---|
1618 | |
---|
1619 | Lnorm = lambda L: 4.*np.pi/(2.0*L+1.) |
---|
1620 | |
---|
1621 | def GetKcl(L,N,SGLaue,phi,beta): |
---|
1622 | 'needs doc string' |
---|
1623 | import pytexture as ptx |
---|
1624 | if SGLaue in ['m3','m3m']: |
---|
1625 | if 'array' in str(type(phi)) and np.any(phi.shape): |
---|
1626 | Kcl = np.zeros_like(phi) |
---|
1627 | else: |
---|
1628 | Kcl = 0. |
---|
1629 | for j in range(0,L+1,4): |
---|
1630 | im = j/4 |
---|
1631 | if 'array' in str(type(phi)) and np.any(phi.shape): |
---|
1632 | pcrs = ptx.pyplmpsi(L,j,len(phi),phi)[0] |
---|
1633 | else: |
---|
1634 | pcrs = ptx.pyplmpsi(L,j,1,phi)[0] |
---|
1635 | Kcl += BOH['L=%d'%(L)][N-1][im]*pcrs*cosd(j*beta) |
---|
1636 | else: |
---|
1637 | if 'array' in str(type(phi)) and np.any(phi.shape): |
---|
1638 | pcrs = ptx.pyplmpsi(L,N,len(phi),phi)[0] |
---|
1639 | else: |
---|
1640 | pcrs = ptx.pyplmpsi(L,N,1,phi)[0] |
---|
1641 | pcrs *= RSQ2PI |
---|
1642 | if N: |
---|
1643 | pcrs *= SQ2 |
---|
1644 | if SGLaue in ['mmm','4/mmm','6/mmm','R3mR','3m1','31m']: |
---|
1645 | if SGLaue in ['3mR','3m1','31m']: |
---|
1646 | if N%6 == 3: |
---|
1647 | Kcl = pcrs*sind(N*beta) |
---|
1648 | else: |
---|
1649 | Kcl = pcrs*cosd(N*beta) |
---|
1650 | else: |
---|
1651 | Kcl = pcrs*cosd(N*beta) |
---|
1652 | else: |
---|
1653 | Kcl = pcrs*(cosd(N*beta)+sind(N*beta)) |
---|
1654 | return Kcl |
---|
1655 | |
---|
1656 | def GetKsl(L,M,SamSym,psi,gam): |
---|
1657 | 'needs doc string' |
---|
1658 | import pytexture as ptx |
---|
1659 | if 'array' in str(type(psi)) and np.any(psi.shape): |
---|
1660 | psrs,dpdps = ptx.pyplmpsi(L,M,len(psi),psi) |
---|
1661 | else: |
---|
1662 | psrs,dpdps = ptx.pyplmpsi(L,M,1,psi) |
---|
1663 | psrs *= RSQ2PI |
---|
1664 | dpdps *= RSQ2PI |
---|
1665 | if M: |
---|
1666 | psrs *= SQ2 |
---|
1667 | dpdps *= SQ2 |
---|
1668 | if SamSym in ['mmm',]: |
---|
1669 | dum = cosd(M*gam) |
---|
1670 | Ksl = psrs*dum |
---|
1671 | dKsdp = dpdps*dum |
---|
1672 | dKsdg = -psrs*M*sind(M*gam) |
---|
1673 | else: |
---|
1674 | dum = cosd(M*gam)+sind(M*gam) |
---|
1675 | Ksl = psrs*dum |
---|
1676 | dKsdp = dpdps*dum |
---|
1677 | dKsdg = psrs*M*(-sind(M*gam)+cosd(M*gam)) |
---|
1678 | return Ksl,dKsdp,dKsdg |
---|
1679 | |
---|
1680 | def GetKclKsl(L,N,SGLaue,psi,phi,beta): |
---|
1681 | """ |
---|
1682 | This is used for spherical harmonics description of preferred orientation; |
---|
1683 | cylindrical symmetry only (M=0) and no sample angle derivatives returned |
---|
1684 | """ |
---|
1685 | import pytexture as ptx |
---|
1686 | Ksl,x = ptx.pyplmpsi(L,0,1,psi) |
---|
1687 | Ksl *= RSQ2PI |
---|
1688 | if SGLaue in ['m3','m3m']: |
---|
1689 | Kcl = 0.0 |
---|
1690 | for j in range(0,L+1,4): |
---|
1691 | im = j/4 |
---|
1692 | pcrs,dum = ptx.pyplmpsi(L,j,1,phi) |
---|
1693 | Kcl += BOH['L=%d'%(L)][N-1][im]*pcrs*cosd(j*beta) |
---|
1694 | else: |
---|
1695 | pcrs,dum = ptx.pyplmpsi(L,N,1,phi) |
---|
1696 | pcrs *= RSQ2PI |
---|
1697 | if N: |
---|
1698 | pcrs *= SQ2 |
---|
1699 | if SGLaue in ['mmm','4/mmm','6/mmm','R3mR','3m1','31m']: |
---|
1700 | if SGLaue in ['3mR','3m1','31m']: |
---|
1701 | if N%6 == 3: |
---|
1702 | Kcl = pcrs*sind(N*beta) |
---|
1703 | else: |
---|
1704 | Kcl = pcrs*cosd(N*beta) |
---|
1705 | else: |
---|
1706 | Kcl = pcrs*cosd(N*beta) |
---|
1707 | else: |
---|
1708 | Kcl = pcrs*(cosd(N*beta)+sind(N*beta)) |
---|
1709 | return Kcl*Ksl,Lnorm(L) |
---|
1710 | |
---|
1711 | def Glnh(Start,SHCoef,psi,gam,SamSym): |
---|
1712 | 'needs doc string' |
---|
1713 | import pytexture as ptx |
---|
1714 | |
---|
1715 | if Start: |
---|
1716 | ptx.pyqlmninit() |
---|
1717 | Start = False |
---|
1718 | Fln = np.zeros(len(SHCoef)) |
---|
1719 | for i,term in enumerate(SHCoef): |
---|
1720 | l,m,n = eval(term.strip('C')) |
---|
1721 | pcrs,dum = ptx.pyplmpsi(l,m,1,psi) |
---|
1722 | pcrs *= RSQPI |
---|
1723 | if m == 0: |
---|
1724 | pcrs /= SQ2 |
---|
1725 | if SamSym in ['mmm',]: |
---|
1726 | Ksl = pcrs*cosd(m*gam) |
---|
1727 | else: |
---|
1728 | Ksl = pcrs*(cosd(m*gam)+sind(m*gam)) |
---|
1729 | Fln[i] = SHCoef[term]*Ksl*Lnorm(l) |
---|
1730 | ODFln = dict(zip(SHCoef.keys(),list(zip(SHCoef.values(),Fln)))) |
---|
1731 | return ODFln |
---|
1732 | |
---|
1733 | def Flnh(Start,SHCoef,phi,beta,SGData): |
---|
1734 | 'needs doc string' |
---|
1735 | import pytexture as ptx |
---|
1736 | |
---|
1737 | if Start: |
---|
1738 | ptx.pyqlmninit() |
---|
1739 | Start = False |
---|
1740 | Fln = np.zeros(len(SHCoef)) |
---|
1741 | for i,term in enumerate(SHCoef): |
---|
1742 | l,m,n = eval(term.strip('C')) |
---|
1743 | if SGData['SGLaue'] in ['m3','m3m']: |
---|
1744 | Kcl = 0.0 |
---|
1745 | for j in range(0,l+1,4): |
---|
1746 | im = j/4 |
---|
1747 | pcrs,dum = ptx.pyplmpsi(l,j,1,phi) |
---|
1748 | Kcl += BOH['L='+str(l)][n-1][im]*pcrs*cosd(j*beta) |
---|
1749 | else: #all but cubic |
---|
1750 | pcrs,dum = ptx.pyplmpsi(l,n,1,phi) |
---|
1751 | pcrs *= RSQPI |
---|
1752 | if n == 0: |
---|
1753 | pcrs /= SQ2 |
---|
1754 | if SGData['SGLaue'] in ['mmm','4/mmm','6/mmm','R3mR','3m1','31m']: |
---|
1755 | if SGData['SGLaue'] in ['3mR','3m1','31m']: |
---|
1756 | if n%6 == 3: |
---|
1757 | Kcl = pcrs*sind(n*beta) |
---|
1758 | else: |
---|
1759 | Kcl = pcrs*cosd(n*beta) |
---|
1760 | else: |
---|
1761 | Kcl = pcrs*cosd(n*beta) |
---|
1762 | else: |
---|
1763 | Kcl = pcrs*(cosd(n*beta)+sind(n*beta)) |
---|
1764 | Fln[i] = SHCoef[term]*Kcl*Lnorm(l) |
---|
1765 | ODFln = dict(zip(SHCoef.keys(),list(zip(SHCoef.values(),Fln)))) |
---|
1766 | return ODFln |
---|
1767 | |
---|
1768 | def polfcal(ODFln,SamSym,psi,gam): |
---|
1769 | '''Perform a pole figure computation. |
---|
1770 | Note that the the number of gam values must either be 1 or must |
---|
1771 | match psi. Updated for numpy 1.8.0 |
---|
1772 | ''' |
---|
1773 | import pytexture as ptx |
---|
1774 | PolVal = np.ones_like(psi) |
---|
1775 | for term in ODFln: |
---|
1776 | if abs(ODFln[term][1]) > 1.e-3: |
---|
1777 | l,m,n = eval(term.strip('C')) |
---|
1778 | psrs,dum = ptx.pyplmpsi(l,m,len(psi),psi) |
---|
1779 | if SamSym in ['-1','2/m']: |
---|
1780 | if m: |
---|
1781 | Ksl = RSQPI*psrs*(cosd(m*gam)+sind(m*gam)) |
---|
1782 | else: |
---|
1783 | Ksl = RSQPI*psrs/SQ2 |
---|
1784 | else: |
---|
1785 | if m: |
---|
1786 | Ksl = RSQPI*psrs*cosd(m*gam) |
---|
1787 | else: |
---|
1788 | Ksl = RSQPI*psrs/SQ2 |
---|
1789 | PolVal += ODFln[term][1]*Ksl |
---|
1790 | return PolVal |
---|
1791 | |
---|
1792 | def invpolfcal(ODFln,SGData,phi,beta): |
---|
1793 | 'needs doc string' |
---|
1794 | import pytexture as ptx |
---|
1795 | |
---|
1796 | invPolVal = np.ones_like(beta) |
---|
1797 | for term in ODFln: |
---|
1798 | if abs(ODFln[term][1]) > 1.e-3: |
---|
1799 | l,m,n = eval(term.strip('C')) |
---|
1800 | if SGData['SGLaue'] in ['m3','m3m']: |
---|
1801 | Kcl = 0.0 |
---|
1802 | for j in range(0,l+1,4): |
---|
1803 | im = j/4 |
---|
1804 | pcrs,dum = ptx.pyplmpsi(l,j,len(beta),phi) |
---|
1805 | Kcl += BOH['L=%d'%(l)][n-1][im]*pcrs*cosd(j*beta) |
---|
1806 | else: #all but cubic |
---|
1807 | pcrs,dum = ptx.pyplmpsi(l,n,len(beta),phi) |
---|
1808 | pcrs *= RSQPI |
---|
1809 | if n == 0: |
---|
1810 | pcrs /= SQ2 |
---|
1811 | if SGData['SGLaue'] in ['mmm','4/mmm','6/mmm','R3mR','3m1','31m']: |
---|
1812 | if SGData['SGLaue'] in ['3mR','3m1','31m']: |
---|
1813 | if n%6 == 3: |
---|
1814 | Kcl = pcrs*sind(n*beta) |
---|
1815 | else: |
---|
1816 | Kcl = pcrs*cosd(n*beta) |
---|
1817 | else: |
---|
1818 | Kcl = pcrs*cosd(n*beta) |
---|
1819 | else: |
---|
1820 | Kcl = pcrs*(cosd(n*beta)+sind(n*beta)) |
---|
1821 | invPolVal += ODFln[term][1]*Kcl |
---|
1822 | return invPolVal |
---|
1823 | |
---|
1824 | |
---|
1825 | def textureIndex(SHCoef): |
---|
1826 | 'needs doc string' |
---|
1827 | Tindx = 1.0 |
---|
1828 | for term in SHCoef: |
---|
1829 | l = eval(term.strip('C'))[0] |
---|
1830 | Tindx += SHCoef[term]**2/(2.0*l+1.) |
---|
1831 | return Tindx |
---|
1832 | |
---|
1833 | # self-test materials follow. |
---|
1834 | selftestlist = [] |
---|
1835 | '''Defines a list of self-tests''' |
---|
1836 | selftestquiet = True |
---|
1837 | def _ReportTest(): |
---|
1838 | 'Report name and doc string of current routine when ``selftestquiet`` is False' |
---|
1839 | if not selftestquiet: |
---|
1840 | import inspect |
---|
1841 | caller = inspect.stack()[1][3] |
---|
1842 | doc = eval(caller).__doc__ |
---|
1843 | if doc is not None: |
---|
1844 | print('testing '+__file__+' with '+caller+' ('+doc+')') |
---|
1845 | else: |
---|
1846 | print('testing '+__file__()+" with "+caller) |
---|
1847 | NeedTestData = True |
---|
1848 | def TestData(): |
---|
1849 | array = np.array |
---|
1850 | global NeedTestData |
---|
1851 | NeedTestData = False |
---|
1852 | global CellTestData |
---|
1853 | # output from uctbx computed on platform darwin on 2010-05-28 |
---|
1854 | CellTestData = [ |
---|
1855 | # cell, g, G, cell*, V, V* |
---|
1856 | [(4, 4, 4, 90, 90, 90), |
---|
1857 | array([[ 1.60000000e+01, 9.79717439e-16, 9.79717439e-16], |
---|
1858 | [ 9.79717439e-16, 1.60000000e+01, 9.79717439e-16], |
---|
1859 | [ 9.79717439e-16, 9.79717439e-16, 1.60000000e+01]]), array([[ 6.25000000e-02, 3.82702125e-18, 3.82702125e-18], |
---|
1860 | [ 3.82702125e-18, 6.25000000e-02, 3.82702125e-18], |
---|
1861 | [ 3.82702125e-18, 3.82702125e-18, 6.25000000e-02]]), (0.25, 0.25, 0.25, 90.0, 90.0, 90.0), 64.0, 0.015625], |
---|
1862 | # cell, g, G, cell*, V, V* |
---|
1863 | [(4.0999999999999996, 5.2000000000000002, 6.2999999999999998, 100, 80, 130), |
---|
1864 | array([[ 16.81 , -13.70423184, 4.48533243], |
---|
1865 | [-13.70423184, 27.04 , -5.6887143 ], |
---|
1866 | [ 4.48533243, -5.6887143 , 39.69 ]]), array([[ 0.10206349, 0.05083339, -0.00424823], |
---|
1867 | [ 0.05083339, 0.06344997, 0.00334956], |
---|
1868 | [-0.00424823, 0.00334956, 0.02615544]]), (0.31947376387537696, 0.25189277536327803, 0.16172643497798223, 85.283666420376008, 94.716333579624006, 50.825714168082683), 100.98576357983838, 0.0099023858863968445], |
---|
1869 | # cell, g, G, cell*, V, V* |
---|
1870 | [(3.5, 3.5, 6, 90, 90, 120), |
---|
1871 | array([[ 1.22500000e+01, -6.12500000e+00, 1.28587914e-15], |
---|
1872 | [ -6.12500000e+00, 1.22500000e+01, 1.28587914e-15], |
---|
1873 | [ 1.28587914e-15, 1.28587914e-15, 3.60000000e+01]]), array([[ 1.08843537e-01, 5.44217687e-02, 3.36690552e-18], |
---|
1874 | [ 5.44217687e-02, 1.08843537e-01, 3.36690552e-18], |
---|
1875 | [ 3.36690552e-18, 3.36690552e-18, 2.77777778e-02]]), (0.32991443953692895, 0.32991443953692895, 0.16666666666666669, 90.0, 90.0, 60.000000000000021), 63.652867178156257, 0.015710211406520427], |
---|
1876 | ] |
---|
1877 | global CoordTestData |
---|
1878 | CoordTestData = [ |
---|
1879 | # cell, ((frac, ortho),...) |
---|
1880 | ((4,4,4,90,90,90,), [ |
---|
1881 | ((0.10000000000000001, 0.0, 0.0),(0.40000000000000002, 0.0, 0.0)), |
---|
1882 | ((0.0, 0.10000000000000001, 0.0),(2.4492935982947065e-17, 0.40000000000000002, 0.0)), |
---|
1883 | ((0.0, 0.0, 0.10000000000000001),(2.4492935982947065e-17, -2.4492935982947065e-17, 0.40000000000000002)), |
---|
1884 | ((0.10000000000000001, 0.20000000000000001, 0.29999999999999999),(0.40000000000000013, 0.79999999999999993, 1.2)), |
---|
1885 | ((0.20000000000000001, 0.29999999999999999, 0.10000000000000001),(0.80000000000000016, 1.2, 0.40000000000000002)), |
---|
1886 | ((0.29999999999999999, 0.20000000000000001, 0.10000000000000001),(1.2, 0.80000000000000004, 0.40000000000000002)), |
---|
1887 | ((0.5, 0.5, 0.5),(2.0, 1.9999999999999998, 2.0)), |
---|
1888 | ]), |
---|
1889 | # cell, ((frac, ortho),...) |
---|
1890 | ((4.1,5.2,6.3,100,80,130,), [ |
---|
1891 | ((0.10000000000000001, 0.0, 0.0),(0.40999999999999998, 0.0, 0.0)), |
---|
1892 | ((0.0, 0.10000000000000001, 0.0),(-0.33424955703700043, 0.39834311042186865, 0.0)), |
---|
1893 | ((0.0, 0.0, 0.10000000000000001),(0.10939835193016617, -0.051013289294572106, 0.6183281045774256)), |
---|
1894 | ((0.10000000000000001, 0.20000000000000001, 0.29999999999999999),(0.069695941716497567, 0.64364635296002093, 1.8549843137322766)), |
---|
1895 | ((0.20000000000000001, 0.29999999999999999, 0.10000000000000001),(-0.073350319180835066, 1.1440160419710339, 0.6183281045774256)), |
---|
1896 | ((0.29999999999999999, 0.20000000000000001, 0.10000000000000001),(0.67089923785616512, 0.74567293154916525, 0.6183281045774256)), |
---|
1897 | ((0.5, 0.5, 0.5),(0.92574397446582857, 1.7366491056364828, 3.0916405228871278)), |
---|
1898 | ]), |
---|
1899 | # cell, ((frac, ortho),...) |
---|
1900 | ((3.5,3.5,6,90,90,120,), [ |
---|
1901 | ((0.10000000000000001, 0.0, 0.0),(0.35000000000000003, 0.0, 0.0)), |
---|
1902 | ((0.0, 0.10000000000000001, 0.0),(-0.17499999999999993, 0.3031088913245536, 0.0)), |
---|
1903 | ((0.0, 0.0, 0.10000000000000001),(3.6739403974420595e-17, -3.6739403974420595e-17, 0.60000000000000009)), |
---|
1904 | ((0.10000000000000001, 0.20000000000000001, 0.29999999999999999),(2.7675166561703527e-16, 0.60621778264910708, 1.7999999999999998)), |
---|
1905 | ((0.20000000000000001, 0.29999999999999999, 0.10000000000000001),(0.17500000000000041, 0.90932667397366063, 0.60000000000000009)), |
---|
1906 | ((0.29999999999999999, 0.20000000000000001, 0.10000000000000001),(0.70000000000000018, 0.6062177826491072, 0.60000000000000009)), |
---|
1907 | ((0.5, 0.5, 0.5),(0.87500000000000067, 1.5155444566227676, 3.0)), |
---|
1908 | ]), |
---|
1909 | ] |
---|
1910 | global LaueTestData #generated by GSAS |
---|
1911 | LaueTestData = { |
---|
1912 | 'R 3 m':[(4.,4.,6.,90.,90.,120.),((1,0,1,6),(1,0,-2,6),(0,0,3,2),(1,1,0,6),(2,0,-1,6),(2,0,2,6), |
---|
1913 | (1,1,3,12),(1,0,4,6),(2,1,1,12),(2,1,-2,12),(3,0,0,6),(1,0,-5,6),(2,0,-4,6),(3,0,-3,6),(3,0,3,6), |
---|
1914 | (0,0,6,2),(2,2,0,6),(2,1,4,12),(2,0,5,6),(3,1,-1,12),(3,1,2,12),(1,1,6,12),(2,2,3,12),(2,1,-5,12))], |
---|
1915 | 'R 3':[(4.,4.,6.,90.,90.,120.),((1,0,1,6),(1,0,-2,6),(0,0,3,2),(1,1,0,6),(2,0,-1,6),(2,0,2,6),(1,1,3,6), |
---|
1916 | (1,1,-3,6),(1,0,4,6),(3,-1,1,6),(2,1,1,6),(3,-1,-2,6),(2,1,-2,6),(3,0,0,6),(1,0,-5,6),(2,0,-4,6), |
---|
1917 | (2,2,0,6),(3,0,3,6),(3,0,-3,6),(0,0,6,2),(3,-1,4,6),(2,0,5,6),(2,1,4,6),(4,-1,-1,6),(3,1,-1,6), |
---|
1918 | (3,1,2,6),(4,-1,2,6),(2,2,-3,6),(1,1,-6,6),(1,1,6,6),(2,2,3,6),(2,1,-5,6),(3,-1,-5,6))], |
---|
1919 | 'P 3':[(4.,4.,6.,90.,90.,120.),((0,0,1,2),(1,0,0,6),(1,0,1,6),(0,0,2,2),(1,0,-1,6),(1,0,2,6),(1,0,-2,6), |
---|
1920 | (1,1,0,6),(0,0,3,2),(1,1,1,6),(1,1,-1,6),(1,0,3,6),(1,0,-3,6),(2,0,0,6),(2,0,-1,6),(1,1,-2,6), |
---|
1921 | (1,1,2,6),(2,0,1,6),(2,0,-2,6),(2,0,2,6),(0,0,4,2),(1,1,-3,6),(1,1,3,6),(1,0,-4,6),(1,0,4,6), |
---|
1922 | (2,0,-3,6),(2,1,0,6),(2,0,3,6),(3,-1,0,6),(2,1,1,6),(3,-1,-1,6),(2,1,-1,6),(3,-1,1,6),(1,1,4,6), |
---|
1923 | (3,-1,2,6),(3,-1,-2,6),(1,1,-4,6),(0,0,5,2),(2,1,2,6),(2,1,-2,6),(3,0,0,6),(3,0,1,6),(2,0,4,6), |
---|
1924 | (2,0,-4,6),(3,0,-1,6),(1,0,-5,6),(1,0,5,6),(3,-1,-3,6),(2,1,-3,6),(2,1,3,6),(3,-1,3,6),(3,0,-2,6), |
---|
1925 | (3,0,2,6),(1,1,5,6),(1,1,-5,6),(2,2,0,6),(3,0,3,6),(3,0,-3,6),(0,0,6,2),(2,0,-5,6),(2,1,-4,6), |
---|
1926 | (2,2,-1,6),(3,-1,-4,6),(2,2,1,6),(3,-1,4,6),(2,1,4,6),(2,0,5,6),(1,0,-6,6),(1,0,6,6),(4,-1,0,6), |
---|
1927 | (3,1,0,6),(3,1,-1,6),(3,1,1,6),(4,-1,-1,6),(2,2,2,6),(4,-1,1,6),(2,2,-2,6),(3,1,2,6),(3,1,-2,6), |
---|
1928 | (3,0,4,6),(3,0,-4,6),(4,-1,-2,6),(4,-1,2,6),(2,2,-3,6),(1,1,6,6),(1,1,-6,6),(2,2,3,6),(3,-1,5,6), |
---|
1929 | (2,1,5,6),(2,1,-5,6),(3,-1,-5,6))], |
---|
1930 | 'P 3 m 1':[(4.,4.,6.,90.,90.,120.),((0,0,1,2),(1,0,0,6),(1,0,-1,6),(1,0,1,6),(0,0,2,2),(1,0,-2,6), |
---|
1931 | (1,0,2,6),(1,1,0,6),(0,0,3,2),(1,1,1,12),(1,0,-3,6),(1,0,3,6),(2,0,0,6),(1,1,2,12),(2,0,1,6), |
---|
1932 | (2,0,-1,6),(0,0,4,2),(2,0,-2,6),(2,0,2,6),(1,1,3,12),(1,0,-4,6),(1,0,4,6),(2,0,3,6),(2,1,0,12), |
---|
1933 | (2,0,-3,6),(2,1,1,12),(2,1,-1,12),(1,1,4,12),(2,1,2,12),(0,0,5,2),(2,1,-2,12),(3,0,0,6),(1,0,-5,6), |
---|
1934 | (3,0,1,6),(3,0,-1,6),(1,0,5,6),(2,0,4,6),(2,0,-4,6),(2,1,3,12),(2,1,-3,12),(3,0,-2,6),(3,0,2,6), |
---|
1935 | (1,1,5,12),(3,0,-3,6),(0,0,6,2),(2,2,0,6),(3,0,3,6),(2,1,4,12),(2,2,1,12),(2,0,5,6),(2,1,-4,12), |
---|
1936 | (2,0,-5,6),(1,0,-6,6),(1,0,6,6),(3,1,0,12),(3,1,-1,12),(3,1,1,12),(2,2,2,12),(3,1,2,12), |
---|
1937 | (3,0,4,6),(3,1,-2,12),(3,0,-4,6),(1,1,6,12),(2,2,3,12))], |
---|
1938 | 'P 3 1 m':[(4.,4.,6.,90.,90.,120.),((0,0,1,2),(1,0,0,6),(0,0,2,2),(1,0,1,12),(1,0,2,12),(1,1,0,6), |
---|
1939 | (0,0,3,2),(1,1,-1,6),(1,1,1,6),(1,0,3,12),(2,0,0,6),(2,0,1,12),(1,1,2,6),(1,1,-2,6),(2,0,2,12), |
---|
1940 | (0,0,4,2),(1,1,-3,6),(1,1,3,6),(1,0,4,12),(2,1,0,12),(2,0,3,12),(2,1,1,12),(2,1,-1,12),(1,1,-4,6), |
---|
1941 | (1,1,4,6),(0,0,5,2),(2,1,-2,12),(2,1,2,12),(3,0,0,6),(1,0,5,12),(2,0,4,12),(3,0,1,12),(2,1,-3,12), |
---|
1942 | (2,1,3,12),(3,0,2,12),(1,1,5,6),(1,1,-5,6),(3,0,3,12),(0,0,6,2),(2,2,0,6),(2,1,-4,12),(2,0,5,12), |
---|
1943 | (2,2,-1,6),(2,2,1,6),(2,1,4,12),(3,1,0,12),(1,0,6,12),(2,2,2,6),(3,1,-1,12),(2,2,-2,6),(3,1,1,12), |
---|
1944 | (3,1,-2,12),(3,0,4,12),(3,1,2,12),(1,1,-6,6),(2,2,3,6),(2,2,-3,6),(1,1,6,6))], |
---|
1945 | } |
---|
1946 | |
---|
1947 | global FLnhTestData |
---|
1948 | FLnhTestData = [{ |
---|
1949 | 'C(4,0,0)': (0.965, 0.42760447), |
---|
1950 | 'C(2,0,0)': (1.0122, -0.80233610), |
---|
1951 | 'C(2,0,2)': (0.0061, 8.37491546E-03), |
---|
1952 | 'C(6,0,4)': (-0.0898, 4.37985696E-02), |
---|
1953 | 'C(6,0,6)': (-0.1369, -9.04081762E-02), |
---|
1954 | 'C(6,0,0)': (0.5935, -0.18234928), |
---|
1955 | 'C(4,0,4)': (0.1872, 0.16358127), |
---|
1956 | 'C(6,0,2)': (0.6193, 0.27573633), |
---|
1957 | 'C(4,0,2)': (-0.1897, 0.12530720)},[1,0,0]] |
---|
1958 | def test0(): |
---|
1959 | if NeedTestData: TestData() |
---|
1960 | msg = 'test cell2Gmat, fillgmat, Gmat2cell' |
---|
1961 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
1962 | G, g = cell2Gmat(cell) |
---|
1963 | assert np.allclose(G,tG),msg |
---|
1964 | assert np.allclose(g,tg),msg |
---|
1965 | tcell = Gmat2cell(g) |
---|
1966 | assert np.allclose(cell,tcell),msg |
---|
1967 | tcell = Gmat2cell(G) |
---|
1968 | assert np.allclose(tcell,trcell),msg |
---|
1969 | selftestlist.append(test0) |
---|
1970 | |
---|
1971 | def test1(): |
---|
1972 | 'test cell2A and A2Gmat' |
---|
1973 | _ReportTest() |
---|
1974 | if NeedTestData: TestData() |
---|
1975 | msg = 'test cell2A and A2Gmat' |
---|
1976 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
1977 | G, g = A2Gmat(cell2A(cell)) |
---|
1978 | assert np.allclose(G,tG),msg |
---|
1979 | assert np.allclose(g,tg),msg |
---|
1980 | selftestlist.append(test1) |
---|
1981 | |
---|
1982 | def test2(): |
---|
1983 | 'test Gmat2A, A2cell, A2Gmat, Gmat2cell' |
---|
1984 | _ReportTest() |
---|
1985 | if NeedTestData: TestData() |
---|
1986 | msg = 'test Gmat2A, A2cell, A2Gmat, Gmat2cell' |
---|
1987 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
1988 | G, g = cell2Gmat(cell) |
---|
1989 | tcell = A2cell(Gmat2A(G)) |
---|
1990 | assert np.allclose(cell,tcell),msg |
---|
1991 | selftestlist.append(test2) |
---|
1992 | |
---|
1993 | def test3(): |
---|
1994 | 'test invcell2Gmat' |
---|
1995 | _ReportTest() |
---|
1996 | if NeedTestData: TestData() |
---|
1997 | msg = 'test invcell2Gmat' |
---|
1998 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
1999 | G, g = invcell2Gmat(trcell) |
---|
2000 | assert np.allclose(G,tG),msg |
---|
2001 | assert np.allclose(g,tg),msg |
---|
2002 | selftestlist.append(test3) |
---|
2003 | |
---|
2004 | def test4(): |
---|
2005 | 'test calc_rVsq, calc_rV, calc_V' |
---|
2006 | _ReportTest() |
---|
2007 | if NeedTestData: TestData() |
---|
2008 | msg = 'test calc_rVsq, calc_rV, calc_V' |
---|
2009 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
2010 | assert np.allclose(calc_rV(cell2A(cell)),trV), msg |
---|
2011 | assert np.allclose(calc_V(cell2A(cell)),tV), msg |
---|
2012 | selftestlist.append(test4) |
---|
2013 | |
---|
2014 | def test5(): |
---|
2015 | 'test A2invcell' |
---|
2016 | _ReportTest() |
---|
2017 | if NeedTestData: TestData() |
---|
2018 | msg = 'test A2invcell' |
---|
2019 | for (cell, tg, tG, trcell, tV, trV) in CellTestData: |
---|
2020 | rcell = A2invcell(cell2A(cell)) |
---|
2021 | assert np.allclose(rcell,trcell),msg |
---|
2022 | selftestlist.append(test5) |
---|
2023 | |
---|
2024 | def test6(): |
---|
2025 | 'test cell2AB' |
---|
2026 | _ReportTest() |
---|
2027 | if NeedTestData: TestData() |
---|
2028 | msg = 'test cell2AB' |
---|
2029 | for (cell,coordlist) in CoordTestData: |
---|
2030 | A,B = cell2AB(cell) |
---|
2031 | for (frac,ortho) in coordlist: |
---|
2032 | to = np.inner(A,frac) |
---|
2033 | tf = np.inner(B,to) |
---|
2034 | assert np.allclose(ortho,to), msg |
---|
2035 | assert np.allclose(frac,tf), msg |
---|
2036 | to = np.sum(A*frac,axis=1) |
---|
2037 | tf = np.sum(B*to,axis=1) |
---|
2038 | assert np.allclose(ortho,to), msg |
---|
2039 | assert np.allclose(frac,tf), msg |
---|
2040 | selftestlist.append(test6) |
---|
2041 | |
---|
2042 | def test7(): |
---|
2043 | 'test GetBraviasNum(...) and GenHBravais(...)' |
---|
2044 | _ReportTest() |
---|
2045 | import os.path |
---|
2046 | import sys |
---|
2047 | import GSASIIspc as spc |
---|
2048 | testdir = os.path.join(os.path.split(os.path.abspath( __file__ ))[0],'testinp') |
---|
2049 | if os.path.exists(testdir): |
---|
2050 | if testdir not in sys.path: sys.path.insert(0,testdir) |
---|
2051 | import sgtbxlattinp |
---|
2052 | derror = 1e-4 |
---|
2053 | def indexmatch(hklin, hkllist, system): |
---|
2054 | for hklref in hkllist: |
---|
2055 | hklref = list(hklref) |
---|
2056 | # these permutations are far from complete, but are sufficient to |
---|
2057 | # allow the test to complete |
---|
2058 | if system == 'cubic': |
---|
2059 | permlist = [(1,2,3),(1,3,2),(2,1,3),(2,3,1),(3,1,2),(3,2,1),] |
---|
2060 | elif system == 'monoclinic': |
---|
2061 | permlist = [(1,2,3),(-1,2,-3)] |
---|
2062 | else: |
---|
2063 | permlist = [(1,2,3)] |
---|
2064 | |
---|
2065 | for perm in permlist: |
---|
2066 | hkl = [abs(i) * hklin[abs(i)-1] / i for i in perm] |
---|
2067 | if hkl == hklref: return True |
---|
2068 | if [-i for i in hkl] == hklref: return True |
---|
2069 | else: |
---|
2070 | return False |
---|
2071 | |
---|
2072 | for key in sgtbxlattinp.sgtbx7: |
---|
2073 | spdict = spc.SpcGroup(key) |
---|
2074 | cell = sgtbxlattinp.sgtbx7[key][0] |
---|
2075 | system = spdict[1]['SGSys'] |
---|
2076 | center = spdict[1]['SGLatt'] |
---|
2077 | |
---|
2078 | bravcode = GetBraviasNum(center, system) |
---|
2079 | |
---|
2080 | g2list = GenHBravais(sgtbxlattinp.dmin, bravcode, cell2A(cell)) |
---|
2081 | |
---|
2082 | assert len(sgtbxlattinp.sgtbx7[key][1]) == len(g2list), 'Reflection lists differ for %s' % key |
---|
2083 | for h,k,l,d,num in g2list: |
---|
2084 | for hkllist,dref in sgtbxlattinp.sgtbx7[key][1]: |
---|
2085 | if abs(d-dref) < derror: |
---|
2086 | if indexmatch((h,k,l,), hkllist, system): |
---|
2087 | break |
---|
2088 | else: |
---|
2089 | assert 0,'No match for %s at %s (%s)' % ((h,k,l),d,key) |
---|
2090 | selftestlist.append(test7) |
---|
2091 | |
---|
2092 | def test8(): |
---|
2093 | 'test GenHLaue' |
---|
2094 | _ReportTest() |
---|
2095 | import GSASIIspc as spc |
---|
2096 | import sgtbxlattinp |
---|
2097 | derror = 1e-4 |
---|
2098 | dmin = sgtbxlattinp.dmin |
---|
2099 | |
---|
2100 | def indexmatch(hklin, hklref, system, axis): |
---|
2101 | # these permutations are far from complete, but are sufficient to |
---|
2102 | # allow the test to complete |
---|
2103 | if system == 'cubic': |
---|
2104 | permlist = [(1,2,3),(1,3,2),(2,1,3),(2,3,1),(3,1,2),(3,2,1),] |
---|
2105 | elif system == 'monoclinic' and axis=='b': |
---|
2106 | permlist = [(1,2,3),(-1,2,-3)] |
---|
2107 | elif system == 'monoclinic' and axis=='a': |
---|
2108 | permlist = [(1,2,3),(1,-2,-3)] |
---|
2109 | elif system == 'monoclinic' and axis=='c': |
---|
2110 | permlist = [(1,2,3),(-1,-2,3)] |
---|
2111 | elif system == 'trigonal': |
---|
2112 | permlist = [(1,2,3),(2,1,3),(-1,-2,3),(-2,-1,3)] |
---|
2113 | elif system == 'rhombohedral': |
---|
2114 | permlist = [(1,2,3),(2,3,1),(3,1,2)] |
---|
2115 | else: |
---|
2116 | permlist = [(1,2,3)] |
---|
2117 | |
---|
2118 | hklref = list(hklref) |
---|
2119 | for perm in permlist: |
---|
2120 | hkl = [abs(i) * hklin[abs(i)-1] / i for i in perm] |
---|
2121 | if hkl == hklref: return True |
---|
2122 | if [-i for i in hkl] == hklref: return True |
---|
2123 | return False |
---|
2124 | |
---|
2125 | for key in sgtbxlattinp.sgtbx8: |
---|
2126 | spdict = spc.SpcGroup(key)[1] |
---|
2127 | cell = sgtbxlattinp.sgtbx8[key][0] |
---|
2128 | center = spdict['SGLatt'] |
---|
2129 | Laue = spdict['SGLaue'] |
---|
2130 | Axis = spdict['SGUniq'] |
---|
2131 | system = spdict['SGSys'] |
---|
2132 | |
---|
2133 | g2list = GenHLaue(dmin,spdict,cell2A(cell)) |
---|
2134 | #if len(g2list) != len(sgtbxlattinp.sgtbx8[key][1]): |
---|
2135 | # print 'failed',key,':' ,len(g2list),'vs',len(sgtbxlattinp.sgtbx8[key][1]) |
---|
2136 | # print 'GSAS-II:' |
---|
2137 | # for h,k,l,d in g2list: print ' ',(h,k,l),d |
---|
2138 | # print 'SGTBX:' |
---|
2139 | # for hkllist,dref in sgtbxlattinp.sgtbx8[key][1]: print ' ',hkllist,dref |
---|
2140 | assert len(g2list) == len(sgtbxlattinp.sgtbx8[key][1]), ( |
---|
2141 | 'Reflection lists differ for %s' % key |
---|
2142 | ) |
---|
2143 | #match = True |
---|
2144 | for h,k,l,d in g2list: |
---|
2145 | for hkllist,dref in sgtbxlattinp.sgtbx8[key][1]: |
---|
2146 | if abs(d-dref) < derror: |
---|
2147 | if indexmatch((h,k,l,), hkllist, system, Axis): break |
---|
2148 | else: |
---|
2149 | assert 0,'No match for %s at %s (%s)' % ((h,k,l),d,key) |
---|
2150 | #match = False |
---|
2151 | #if not match: |
---|
2152 | #for hkllist,dref in sgtbxlattinp.sgtbx8[key][1]: print ' ',hkllist,dref |
---|
2153 | #print center, Laue, Axis, system |
---|
2154 | selftestlist.append(test8) |
---|
2155 | |
---|
2156 | def test9(): |
---|
2157 | 'test GenHLaue' |
---|
2158 | _ReportTest() |
---|
2159 | import GSASIIspc as G2spc |
---|
2160 | if NeedTestData: TestData() |
---|
2161 | for spc in LaueTestData: |
---|
2162 | data = LaueTestData[spc] |
---|
2163 | cell = data[0] |
---|
2164 | hklm = np.array(data[1]) |
---|
2165 | H = hklm[-1][:3] |
---|
2166 | hklO = hklm.T[:3].T |
---|
2167 | A = cell2A(cell) |
---|
2168 | dmin = 1./np.sqrt(calc_rDsq(H,A)) |
---|
2169 | SGData = G2spc.SpcGroup(spc)[1] |
---|
2170 | hkls = np.array(GenHLaue(dmin,SGData,A)) |
---|
2171 | hklN = hkls.T[:3].T |
---|
2172 | #print spc,hklO.shape,hklN.shape |
---|
2173 | err = True |
---|
2174 | for H in hklO: |
---|
2175 | if H not in hklN: |
---|
2176 | print H,' missing from hkl from GSASII' |
---|
2177 | err = False |
---|
2178 | assert(err) |
---|
2179 | selftestlist.append(test9) |
---|
2180 | |
---|
2181 | |
---|
2182 | |
---|
2183 | |
---|
2184 | if __name__ == '__main__': |
---|
2185 | # run self-tests |
---|
2186 | selftestquiet = False |
---|
2187 | for test in selftestlist: |
---|
2188 | test() |
---|
2189 | print "OK" |
---|