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Reconstructing/recovering the microstructure back from 2PC stats. #567

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Nimal136 opened this issue Aug 15, 2021 · 3 comments
Open

Reconstructing/recovering the microstructure back from 2PC stats. #567

Nimal136 opened this issue Aug 15, 2021 · 3 comments
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@Nimal136
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Hi Team,
I have a relative loading map of 2PCs after PCA and thought of reconstructing it back to the raw microstructure to look at how the reduced-order representation of the set of microstructures looks like. I remember reading this paper (doi.org/10.1016/j.actamat.2007.10.044) on recovering the microstructure from the computed 2PC stats using a phase recovery algorithm. Has this been implemented in the package or is there any plan to do it in future versions? Such functionality would be helpful to visualise what are the interesting features in the ensemble of microstructures.
Cheers

@wd15
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wd15 commented Aug 17, 2021

This is not implemented in PyMKS currently. No plans as yet either. If you do have a go at implementing it then I would certainly be interested in integrating that into PyMKS.

Edit: if you have a prototype implementation then we can work that into PyMKS

@wd15 wd15 added this to the 0.5 milestone Aug 17, 2021
@owaisahmad18
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data_correlation = TwoPointCorrelation(
periodic_boundary=True,
cutoff=25,
correlations=[(0,0),(0,1)]
).transform(data)

how can i use the output from TwoPointCorrelation command in pymks package and feed it to MCRpy or any other package to reconstruct microstructure. please help.

@wd15
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wd15 commented Dec 15, 2022

@owaisahmad18 the output from PyMKS is just a Numpy array which you can save in a variety of formats. I suspect that MCRpy would also be using Numpy arrays so you could use the two tools in a single Python session.

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