psf

Point Spread Function calculations for fluorescence microscopy.

https://github.com/cgohlke/psf

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Point Spread Function calculations for fluorescence microscopy.

README.rst

..
  This file is generated by setup.py

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 `_
:License: BSD-3-Clause
:Version: 2025.8.1

Quickstart
----------

Install the psf package and all dependencies from the
`Python Package Index `_::

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

See `Examples`_ for using the programming interface.

Source code and support are available on
`GitHub `_.

Requirements
------------

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

- `CPython `_ 3.11.9, 3.12.10, 3.13.5, 3.14.0rc 64-bit
- `NumPy `_ 2.3.2
- `Matplotlib `_  3.10.5
  (optional for plotting)

Revisions
---------

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

- Change PSF.TYPES from dict to set (breaking).

2023.4.26

- Use enums.
- Derive Dimensions from UserDict.
- Add type hints.
- Convert to Google style docstrings.
- Drop support for Python 3.8 and numpy < 1.21 (NEP29).

2022.9.26

- Fix setup.py.

2022.9.12

- Drop support for Python 3.7 (NEP 29).
- Update metadata.

2021.6.6

- Drop support for Python 3.6 (NEP 29).

2020.1.1

- Drop support for Python 2.7 and 3.5.
- Update copyright.

2019.10.14

- Support Python 3.8.

2019.4.22

- Fix setup requirements.
- Fix compiler warning.

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

Examples
--------

.. code-block:: python

    >>> 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.

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