FindUBUsingIndexedPeaks v1¶

Summary¶

Calculate the UB matrix from a peaks workspace, containing indexed peaks.

Properties¶

Description¶

Given a set of peaks at least three of which have been assigned Miller indices, this algorithm will find the UB matrix, that best maps the integer (h,k,l) values to the corresponding Q vectors. The set of indexed peaks must include three linearly independent Q vectors. The (h,k,l) values from the peaks are first rounded to form integer (h,k,l) values. The algorithm then forms a possibly over-determined linear system of equations representing the mapping from (h,k,l) to Q for each indexed peak. The system of linear equations is then solved in the least squares sense, using QR factorization.

Usage¶

Example:

ws=LoadIsawPeaks("TOPAZ_3007.peaks")
print("After LoadIsawPeaks does the workspace have an orientedLattice: %s" % ws.sample().hasOrientedLattice())

FindUBUsingIndexedPeaks(ws)
print("After FindUBUsingIndexedPeaks does the workspace have an orientedLattice: %s" % ws.sample().hasOrientedLattice())

print(ws.sample().getOrientedLattice().getUB())

Output:

After LoadIsawPeaks does the workspace have an orientedLattice: False
After FindUBUsingIndexedPeaks does the workspace have an orientedLattice: True
[[-0.04542062  0.04061954 -0.01223576]
 [ 0.00140377 -0.00318446  0.11654506]
 [ 0.05749773  0.03223779  0.02737294]]

Categories: AlgorithmIndex | Crystal\UBMatrix

Source¶

C++ source: FindUBUsingIndexedPeaks.cpp (last modified: 2019-10-25)

C++ header: FindUBUsingIndexedPeaks.h (last modified: 2019-10-25)