Fit exponential and harmonic functions using Chebyshev polynomials
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:
- 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):
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
1 maintainer
Metadata
1 maintainer
Release files for chebyfit 2026.8.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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No |
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twine/7.0.0 CPython/3.14.7
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Release files / chebyfit-2026.8.8-cp312-abi3-macosx_10_13_x86_64.whl
| Download URL | chebyfit-2026.8.8-cp312-abi3-macosx_10_13_x86_64.whl |
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| Tags | CPython 3.12 abi3 macOS 10.13+ x86-64 |
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No |
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Security for chebyfit 2026.8.8
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