psf 2019.2.20

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:

2019.2.20

Requirements

• CPython 2.7 or 3.5+

• Numpy 1.14

• Matplotlib 2.2 (optional for plotting)

• A Python distutils compatible C compiler (build)

Revisions

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.