Metadata-Version: 2.1
Name: b-fade
Version: 0.0.0
Summary: B-FADE: Bayesian FAtigue moDel Estimator
Home-page: https://github.com/aletgn/b-fade
Author: Alessandro Tognan
Author-email: tognan.alessandro@spes.uniud.it
Project-URL: Bug Tracker, https://github.com/aletgn/b-fade/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: odfpy
Requires-Dist: openpyxl
Requires-Dist: scikit-learn
Requires-Dist: numdifftools
Requires-Dist: PyYAML
Provides-Extra: dev
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: twine ; extra == 'dev'
Requires-Dist: setuptools ; extra == 'dev'
Requires-Dist: build ; extra == 'dev'
Provides-Extra: test
Requires-Dist: notebook ; extra == 'test'

# B-FADE: Bayesian FAtigue moDel Estimator

The package implements Maximum a Posteriori Estimation (MAP) to accomplish the estimation of fatigue models' parameters. Currently the package is designed to identify the El Haddad (EH) curve given a fatigue & defectivity characterisation dataset. Other curves are foreseen in future developments.

## Features

- Maximum a Posteriori Estimation and computation of the predictive posterior.
- Monte Carlo Estimation of the prediction interval for the considered curve.
- Data pre-processing & visualisation.

## Quick Setup

B-FADE is available at [PyPI](https://pypi.org/project/b-fade/), so it can be installed using common package managers, such as `pip` or `conda`:

```
pip install --user b-fade
```

```
conda install b-fade
```

For further instructions, please take a look at the documentation.

## Documentation

Please refer to [ReadTheDocs](https://b-fade.readthedocs.io/en/latest/) for detailed instructions about installing, utilising B-FADE and working examples.
