| Name | psf JSON |
| Version |
2025.1.1
JSON |
| download |
| home_page | https://www.cgohlke.com |
| Summary | Point Spread Function calculations for fluorescence microscopy |
| upload_time | 2025-01-02 19:30:56 |
| maintainer | None |
| docs_url | None |
| author | Christoph Gohlke |
| requires_python | >=3.10 |
| license | BSD |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
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: 2025.1.1
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>`_ 3.10.11, 3.11.9, 3.12.8, 3.13.1 64-bit
- `NumPy <https://pypi.org/project/numpy/>`_ 2.1.3
- `Matplotlib <https://pypi.org/project/matplotlib/>`_ 3.10.0
(optional for plotting)
Revisions
---------
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
--------
>>> 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.
Raw data
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