LikeFit
LikeFit is a library to fit data for science and engineering. It provides a user-friendly and comprehensive interface for linear and non-linear least squares, and likelihood fits.
Install
python -m pip install likefit
Features
- Linear and nonlinear least squares fit with a consistent interface
- Fit of histograms with a Poisson likelihood
- Calculation of estimators, errors, and correlations
- Evaluation of goodness-of-fit with chi-squared test
- Plot of error bands, confidence regions, and likelihood functions
How to use
These demos contain Jupyter notebooks that show how to use the LikeFit library.
Contributing
If you want to contribute, please fork the repository and use a feature branch. Pull requests are warmly welcome.
Links
- Repository: https://github.com/ravignad/likefit/
- Demos: https://github.com/ravignad/likefit_demos.git
Licensing
The code in this project is licensed under MIT license.
1 maintainer
Release files for likefit 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| likefit-0.2.4.tar.gz | 10.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| likefit-0.2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.4 kB
Release files / likefit-0.2.4.tar.gz
| Download URL | likefit-0.2.4.tar.gz |
|---|---|
| Size | 10.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
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Release files / likefit-0.2.4-py3-none-any.whl
| Download URL | likefit-0.2.4-py3-none-any.whl |
|---|---|
| Size | 9.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
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