psf

Point Spread Function calculations for fluorescence microscopy

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

The psf library is no longer actively developed.

:Author: Christoph Gohlke <https://www.cgohlke.com>_ :License: BSD-3-Clause :Version: 2026.1.18

Quickstart

Install the psf package and all dependencies from the Python Package Index <https://pypi.org/project/psf/>_::

python -m pip install -U "psf[all]"

See Examples_ for using the programming interface.

Source code and support are available on GitHub <https://github.com/cgohlke/psf>_.

Requirements

This revision was tested with the following requirements and dependencies (other versions may work):

• CPython <https://www.python.org>_ 3.11.9, 3.12.10, 3.13.11, 3.14.2 64-bit
• NumPy <https://pypi.org/project/numpy/>_ 2.4.1
• Matplotlib <https://pypi.org/project/matplotlib/>_ 3.10.8 (optional for plotting)

Revisions

2026.1.18

• Use multi-phase initialization.
• Improve code quality.

2025.8.1

• Drop support for Python 3.10, support Python 3.14.

2025.1.1

• Improve type hints.
• Drop support for Python 3.9, support Python 3.13.

2024.5.24

• Fix docstring examples not correctly rendered on GitHub.

2024.4.24

• Support NumPy 2.

2024.1.6

• …

Refer to the CHANGES file for older revisions.

References

• 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.
• Focal volume optics and experimental artifacts in confocal fluorescence correlation spectroscopy. S T Hess, W W Webb. Biophys J (83) 2300-17, 2002.
• Electromagnetic description of image formation in confocal fluorescence microscopy. T D Viser, S H Wiersma. J Opt Soc Am A (11) 599-608, 1994.
• 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.
• Gaussian approximations of fluorescence microscope point-spread function models. B Zhang, J Zerubia, J C Olivo-Marin. Appl. Optics (46) 1819-29, 2007.
• The SVI-wiki on 3D microscopy, deconvolution, visualization and analysis. https://svi.nl/NyquistRate

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) obsvol.sigma.ou (2.588..., 1.370...) obsvol = psf.PSF(psf.ISOTROPIC | psf.CONFOCAL, **args) print(obsvol, end='') PSF ISOTROPIC|CONFOCAL shape: (32, 32) pixel dimensions: (4.00, 4.00) um, (55.64, 61.80) ou, (8.06, 8.06) au excitation wavelength: 488.0 nm emission wavelength: 520.0 nm numeric aperture: 1.20 refractive index: 1.33 half cone angle: 64.19 deg magnification: 1.00 underfilling: 1.00 pinhole radius: 0.550 um, 8.498 ou, 1.1086 au, 4.40 px computing time: ... ms obsvol[0, :3] array([1. , 0.51071, 0.04397])

write the image plane to file

obsvol.slice(0).tofile('_test_slice.bin')

write a full 3D PSF volume to file

obsvol.volume().tofile('_test_volume.bin')

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