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:
- pats
numpy.ndarray
EBSD pattern(s), of shape
(n detector rows, n detector columns)
, or(n patterns, n detector rows, n detector columns)
.- indexer
pyebsdindex.ebsd_index.EBSDIndexer
EBSD indexer instance storing all relevant parameters for band detection.
- PC0
list
,optional
Initial guess of PC. If not given,
indexer.PC
is used. Ifindexer.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. IfTrue
, then an optimization is run for each individual pattern, and an array of PC values is returned.
- pats
- 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.