Comments (3)
Hi,
It seems there is no The_Lambda_parameters.ipynb notebook in the package. I tried the following codes, but it failed. Could you help check it? Thank you.
each_Lambda3, each_Lambda2, average_Lambda3, average_Lambda2 = opt.compute_lambda(return_type='both')
print(F"each_Lambda3:{each_Lambda3}")
print(F"each_Lambda2:{each_Lambda2}")
print(F"average_Lambda3:{average_Lambda3}")
print(F"average_Lambda2:{average_Lambda2}")
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Ah great point, thanks for letting me know it's not up here! I should be able to get it uploaded by the weekend.
In the meanwhile just in case you need it quickly, the overall idea is this:
Lambda3 describes diagonal B-cation displacements along all 3 directions of the octahedra.
Lambda2 describes the largest diagonal B-cation displacements along one of the three planes of the octahedra.
Then in terms of usage, if you use compute_lambda(..., return_type = 'octahedra_lambda')
the returned signature will be:
octahedra_lambda3, octahedra_lambda2
where each of these is a np.ndarray containing the Lambda3, Lambda2 values for each individual octahedra.
compute_lambda(..., return_type = 'lambda')
will do the same as above, but instead of np.ndarrays, it will simply return the average Lambda3, Lambda2 across all octahedra in the system.
And finally compute_lambda(..., return_type = 'both')
returns both of the above with the return signature of:
each_Lambda3, each_Lambda2, average_Lambda3, average_Lambda2
.
In terms of the parameters themselves for a more detailed description check out:
https://doi.org/10.1063/5.0159407
Hope this helps in the meantime, and thanks for bringing up that the notebook is currently missing!
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Hi, sorry for the delay but the notebook is up now!
Yes what you have there is correct, so if you have some Perovskite
object perov
, then you can do this:
oct_lambda_3_both, oct_lambda_2_both, lambda_3_both, lambda_2_both = perov.compute_lambda(return_type = 'both')
Then the first two would be the individual values by octahedra, and the final two would be the averaged ones.
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