Reconstructing/recovering the microstructure back from 2PC stats.

[Nimal136]

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]

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

[owaisahmad18]

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]

@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.