optimize#

pyebsdindex.pcopt.optimize(pats, indexer, PC0=None, batch=False)[source]#

Optimize pattern center (PC) (PCx, PCy, PCz) in the convention of the indexer.vendor with Nelder-Mead.

Parameters:

patsnumpy.ndarray: EBSD pattern(s), of shape (n detector rows, n detector columns), or (n patterns, n detector rows, n detector columns).
indexerpyebsdindex.ebsd_index.EBSDIndexer: EBSD indexer instance storing all relevant parameters for band detection.
PC0list, optional: Initial guess of PC. If not given, indexer.PC is used. If indexer.vendor is "EMSOFT", the PC must be four numbers, the final number being the pixel size.
batchbool, optional: Default is False which indicates the fit for a set of patterns should be optimized using the cumulative fit for all the patterns, and one PC will be returned. If True, then an optimization is run for each individual pattern, and an array of PC values is returned.

Returns:

numpy.ndarray: Optimized PC.

Notes

SciPy’s Nelder-Mead minimization function is used with a tolerance fatol=0.00001 between each iteration, ending the optimization when the improvement is below this value.