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View Code? Open in Web Editor NEWDetermine new space groups for analyzing pump-probe crystallography experiments
License: MIT License
Determine new space groups for analyzing pump-probe crystallography experiments
License: MIT License
If one specifies an hmax
parameter >1, it will be the case that several parallel Miller planes are available. Here is an example where both [0, -2, -2]
and [0, -1, -1]
can be seen in the output:
> regroup *.mccd.inp -sg 19 --hmax 2
Facet Angle spacegroup n_symops
mean std count
0 (0, -2, -1) 4.577838 0.493757 129 P 1 (No. 1) 1
1 (0, -2, -2) 7.435163 0.513735 129 P 1 (No. 1) 1
2 (0, -1, -1) 7.435163 0.513735 129 P 1 (No. 1) 1
3 (0, -2, 0) 17.367348 0.521376 129 P 1 21 1 (a,b,c-1/4) (No. 4) 2
4 (0, -1, 0) 17.367348 0.521376 129 P 1 21 1 (a,b,c-1/4) (No. 4) 2
.. ... ... ... ... ... ...
119 (0, 2, 0) 162.632652 0.521376 129 P 1 21 1 (a,b,c-1/4) (No. 4) 2
120 (0, 1, 0) 162.632652 0.521376 129 P 1 21 1 (a,b,c-1/4) (No. 4) 2
121 (0, 1, 1) 172.564837 0.513735 129 P 1 (No. 1) 1
122 (0, 2, 2) 172.564837 0.513735 129 P 1 (No. 1) 1
123 (0, 2, 1) 175.422162 0.493757 129 P 1 (No. 1) 1
[124 rows x 6 columns]
In these cases, I think it makes the most sense to prune the output to only specify the Miller plane for which the gcd
of the different spacings is 1.
To my knowledge, this can be implemented fairly simply by calling d = np.gcd.reduce([h, k, l])
and skipping/dropping entries for which d > 1
.
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