PYME.localization.FitFactories.PRInterpFitQR module

PYME.localization.FitFactories.PRInterpFitQR.FitFactory

alias of PSFFitFactory

PYME.localization.FitFactories.PRInterpFitQR.FitResult(fitResults, metadata, slicesUsed=None, resultCode=-1, fitErr=None, startParams=None, nchi2=-1)

class PYME.localization.FitFactories.PRInterpFitQR.PSFFitFactory(data, metadata, fitfcn=<function f_Interp3d>, background=None, noiseSigma=None, **kwargs)

Bases: PSFFitFactory

Create a fit factory which will operate on image data (data), potentially using voxel sizes etc contained in metadata.

FromPoint(x, y, z=None, roiHalfSize=5, axialHalfSize=15)

This should be overridden in derived classes to actually do the fitting. The function which gets implemented should return a numpy record array, of the dtype defined in the module level FitResultsDType variable (the calling function uses FitResultsDType to pre-allocate an array for the results)

classmethod evalModel(params, md, x=0, y=0, roiHalfSize=5, model=<function f_Interp3d>)

PYME.localization.FitFactories.PRInterpFitQR.PSFFitResultR(fitResults, metadata, slicesUsed=None, resultCode=-1, fitErr=None, startParams=None, nchi2=-1)

PYME.localization.FitFactories.PRInterpFitQR.f_Interp3d(p, interpolator, X, Y, Z, safeRegion, splitaxis, *args)

3D PSF model function with constant background - parameter vector [A, x0, y0, z0, background]

PYME.localization.FitFactories.PRInterpFitQR.genFitImage(fitResults, md, fitfcn=<function f_Interp3d>)

PYME.localization.FitFactories.PRInterpFitQR.getDataErrors(im, metadata)