psf 2019.10.14

Point Spread Function calculations for fluorescence microscopy

Psf is a Python library to calculate Point Spread Functions (PSF) for fluorescence microscopy.

This library is no longer actively developed.

Authors:	Christoph Gohlke, Oliver Holub
Organization:	Laboratory for Fluorescence Dynamics. University of California, Irvine
License:	3-clause BSD
Version:	2019.10.14

Requirements

• CPython 2.7 or 3.5+
• Numpy 1.11
• Matplotlib 2.2 (optional for plotting)
• A Python distutils compatible C compiler (build)

Revisions

2019.10.14

Support Python 3.8.

2019.4.22

Fix setup requirements. Fix compiler warning.

2019.1.1

Update copyright year.

References

1. Electromagnetic diffraction in optical systems. II. Structure of the image field in an aplanatic system. B Richards and E Wolf. Proc R Soc Lond A, 253 (1274), 358-379, 1959.
2. Focal volume optics and experimental artifacts in confocal fluorescence correlation spectroscopy. S T Hess, W W Webb. Biophys J (83) 2300-17, 2002.
3. Electromagnetic description of image formation in confocal fluorescence microscopy. T D Viser, S H Wiersma. J Opt Soc Am A (11) 599-608, 1994.
4. Photon counting histogram: one-photon excitation. B Huang, T D Perroud, R N Zare. Chem Phys Chem (5), 1523-31, 2004. Supporting information: Calculation of the observation volume profile.
5. Gaussian approximations of fluorescence microscope point-spread function models. B Zhang, J Zerubia, J C Olivo-Marin. Appl. Optics (46) 1819-29, 2007.
6. The SVI-wiki on 3D microscopy, deconvolution, visualization and analysis. https://svi.nl/NyquistRate
7. Theory of Confocal Microscopy: Resolution and Contrast in Confocal Microscopy. http://www.olympusfluoview.com/theory/resolutionintro.html

Examples

>>> import psf
>>> args = dict(shape=(32, 32), dims=(4, 4), ex_wavelen=488, em_wavelen=520,
...             num_aperture=1.2, refr_index=1.333,
...             pinhole_radius=0.55, pinhole_shape='round')
>>> obsvol = psf.PSF(psf.GAUSSIAN | psf.CONFOCAL, **args)
>>> print('%.5f, %.5f' % obsvol.sigma.ou)
2.58832, 1.37059
>>> obsvol = psf.PSF(psf.ISOTROPIC | psf.CONFOCAL, **args)
>>> obsvol[0, :3]
array([ 1.     ,  0.51071,  0.04397])
>>> # save the image plane to file
>>> obsvol.slice(0).tofile('_test_slice.bin')
>>> # save a full 3D PSF volume to file
>>> obsvol.volume().tofile('_test_volume.bin')

Refer to the psf_example.py file in the source distribution for more.