Chebyfit is a Python library that implements the algorithms described in:

Analytic solutions to modelling exponential and harmonic functions using Chebyshev polynomials: fitting frequency-domain lifetime images with photobleaching. G C Malachowski, R M Clegg, and G I Redford. J Microsc. 2007; 228(3): 282-295. doi: 10.1111/j.1365-2818.2007.01846.x

Author:

Christoph Gohlke

License:

BSD 3-Clause

Version:

2026.8.8

Quickstart

Install the chebyfit package and all dependencies from the Python Package Index:

python -m pip install -U chebyfit

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 3.12.10, 3.13.15, 3.14.7, 3.15.0rc 64-bit

  • Numpy 2.5.2

Revisions

2026.8.8

  • Fix code review issues.

  • Improve docstrings.

  • Make C extension ABI3 and free-threading compatible.

  • Drop support for Python 3.11 and numpy 2.0 (SPEC0).

  • Support Python 3.15.

2026.1.18

  • Rename chebyshev_invers to chebyshev_inverse (breaking).

  • 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

  • …

Refer to the CHANGES file for older revisions.

Examples

Fit two-exponential decay function:

>>> deltat = 0.5
>>> t = numpy.arange(0, 128, deltat)
>>> data = 1.1 + 2.2 * numpy.exp(-t / 33.3) + 4.4 * numpy.exp(-t / 55.5)
>>> params, fitted = fit_exponentials(data, numexps=2, deltat=deltat)
>>> numpy.allclose(data, fitted)
True
>>> params['offset']
array([1.1])
>>> params['amplitude']
array([[4.4, 2.2]])
>>> params['rate']
array([[55.5, 33.3]])

Fit harmonic function with exponential decay:

>>> tt = t * (2 * math.pi / (t[-1] + deltat))
>>> data = 1.1 + numpy.exp(-t / 22.2) * (
...     3.3 - 4.4 * numpy.sin(tt) + 5.5 * numpy.cos(tt)
... )
>>> params, fitted = fit_harmonic_decay(data, deltat=0.5)
>>> numpy.allclose(data, fitted)
True
>>> params['offset']
array([1.1])
>>> params['rate']
array([22.2])
>>> params['amplitude']
array([[3.3, 4.4, 5.5]])

Fit experimental time-domain image:

>>> data = numpy.fromfile('test.b&h', dtype='float32').reshape((256, 256, 256))
>>> data = data[64 : 64 + 64]
>>> params, fitted = fit_exponentials(data, numexps=1, numcoef=16, axis=0)
>>> numpy.allclose(data.sum(axis=0), fitted.sum(axis=0))
True

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for cgohlke from gravatar.com cgohlke

Credits

Author: Christoph Gohlke

License

BSD-3-Clause

Requires

Python >=3.12

Provides Extra

all

Classifiers

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Release history Release notifications | RSS feed

This release

2026.8.8 This release

25 files

2026.1.18

36 files

2025.8.1

31 files

2025.1.1

24 files

2024.5.24

26 files

2024.4.24

23 files

2024.1.6

23 files

2023.4.22

18 files

2022.9.29

11 files

2022.8.26

10 files

2021.6.6

11 files

2020.1.1

8 files

2019.10.14

11 files

2019.4.22

9 files

2019.2.20

9 files

2019.1.28

11 files

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