linumpy.psf.psf_estimator#

Functions#

extract_psfParametersFromMosaic(vol[, f, nProfiles, ...])

Computes the confocal PSF from a slice.

get_3dPSF(zf, zr, res, volshape)

Generate a 3D PSF based on Gaussian beam parameters.

Module Contents#

linumpy.psf.psf_estimator.extract_psfParametersFromMosaic(vol, f=0.01, nProfiles=10, zr_0=610.0, res=6.5, nIterations=15)[source]#

Computes the confocal PSF from a slice.

Parameters:

  • vol (ndarray) – A stitched tissue slice with axes in order (x, y, z).

  • f (float) – Smoothing factor (in fraction of image size).

  • nProfiles (int) – Number of intensity profile to use.

  • zr_0 (float) – Initial Rayleigh length to use in micron (default=%(default)s for a 3X objective)

  • res (float) – Z resolution (in micron).

Returns:

Focal depth (zf) and Rayleigh length (zr) in micron

Return type:

(2,) tuple

linumpy.psf.psf_estimator.get_3dPSF(zf, zr, res, volshape)[source]#

Generate a 3D PSF based on Gaussian beam parameters.

Parameters:

  • zf (float) – Focal depth in microns

  • zr (float) – Rayleigh length in microns

  • res (float) – Axial resolution in micron / pixel

  • volshape ((3,) list of int) – Output volume shape in pixel

Returns:

3D PSF of shape ‘volshape’

Return type:

ndarray