Changeset 4413
 Timestamp:
 Apr 24, 2020 9:52:46 PM (17 months ago)
 Location:
 trunk
 Files:

 2 edited
Legend:
 Unmodified
 Added
 Removed

trunk/GSASIIobj.py
r4399 r4413 1000 1000 letter or string flag value (such as I or A for iso/anisotropic). 1001 1001 1002 Texture implementation 1003  1004 1005 There are two different places where texture can be treated in GSASII. 1006 One is for mitigating the effects of texture in a structural refinement. 1007 The other is for texture characterization. 1008 1009 For reducing the effect of texture in a structural refinement 1010 there are entries labeled preferred orientation in each phase's 1011 data tab. Two different 1012 approaches can be used for this, the MarchDollase model and 1013 spherical harmonics. 1014 For the MarchDollase model, one axis in reciprocal space is designated as 1015 unique (defaulting to the 001 axis) and reflections are corrected 1016 according to the angle they make with this axis depending on 1017 the MarchDollase ratio. (If unity, no correction is made). 1018 The ratio can be greater than one or less than one depending on if 1019 crystallites oriented along the designated axis are 1020 overrepresented or underrepresented. For most crystal systems there is an 1021 obvious choice for the direction of the unique axis and then only a single 1022 term needs to be refined. If the number is close to 1, then the correction 1023 is not needed. 1024 1025 The second method for reducing the effect of texture in a structural 1026 refinement is to create a probability surface as an expansion in 1027 terms spherical harmonic functions. Only functions consistent with 1028 cylindrical diffraction suymmetry and having texture symmetry 1029 consistent with the Laue class of phase are used and are allowed, 1030 so the higher the symmetry 1031 the fewer terms that are available for a given spherical harmonics order. 1032 For use of this correction, select the lowest order that provides 1033 refinable terms and perform a refinement. If the texture index remains close to 1034 one, then the correction is not needed. If a significant improvement is 1035 noted in the profile Rwp, one may wish to see if a higher order expansion 1036 gives an even larger improvement. 1037 1038 To characterize texture in a material, one needs data collected with the 1039 sample at multiple orientations or, for TOF, with detectors at multiple 1040 locations around the sample. In this case the detector orientation is given in 1041 each histogram's Sample Parameters and the sample's orientation is described 1042 with the Euler angles specifed on the phase's Texture tab, which is also 1043 where the texture type (cylindrical, rolling,...) and the sherical 1044 harmonic order is selected. This should not be used with a single dataset and 1045 should not be used if the preferred orientations corrections are used. 1046 1047 The coordinate system used for texture characterization is defined where 1048 the sample coordinates (Psi, gamma) are defined with an instrument coordinate 1049 system (I, J, K) such that I is normal to the diffraction plane and J is coincident with the 1050 direction of the incident radiation beam pointing away from the source. We further define 1051 a standard set of righthanded goniometer eulerian angles (Omega, Chi, Phi) so that Omega and Phi are 1052 rotations about I and Chi is a rotation about J when Omega, Chi, Phi = 0. Finally, as the sample 1053 may be mounted so that the sample coordinate system (Is, Js, Ks) does not coincide with 1054 the instrument coordinate system (I, J, K), we define three eulerian sample rotation angles 1055 (Omegas, Chis, Phis) that describe the rotation from (I, J, K) to (Is, Js, Ks). The sample rotation 1056 angles are defined so that with the goniometer angles at zero Omegas and Phis are rotations 1057 about I and Chis is a rotation about J. 1058 1002 1059 ISODISTORT implementation 1003 1060  
trunk/NIST_profile/atan_windowed_FP_profile.py
r4403 r4413 138 138 139 139 140 #cu_ka_spectdata=numpy.array(( #each cluster is wavelength/m, intensity, fwhm/m, from Cu kalpha paper 141 # (0.15405925, 3.91, 0.0436e3), #ka11 142 # (0.15410769, 0.474, 0.0558e3), #ka12 143 # (0.15443873, 1.53, 0.0487e3), #ka21 144 # (0.15446782, 0.754, 0.0630e3), #ka22 145 # ))*(1e9,1,1e9) 146 # replaced due to Sphinx problem with scaled values: 140 147 cu_ka_spectdata=numpy.array(( #each cluster is wavelength/m, intensity, fwhm/m, from Cu kalpha paper 141 (0.15405925 , 3.91, 0.0436e3), #ka11142 (0.15410769 , 0.474, 0.0558e3), #ka12143 (0.15443873 , 1.53, 0.0487e3), #ka21144 (0.15446782 , 0.754, 0.0630e3), #ka22145 )) *(1e9,1,1e9)148 (0.15405925e9, 3.91, 0.0436e12), #ka11 149 (0.15410769e9, 0.474, 0.0558e12), #ka12 150 (0.15443873e9, 1.53, 0.0487e12), #ka21 151 (0.15446782e9, 0.754, 0.0630e12), #ka22 152 )) 146 153 147 154 if __name__ == "__main__":
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