Metadata-Version: 2.1
Name: pycalib
Version: 0.0.9.dev4
Summary: Python library with tools for classifier calibration.
Home-page: https://www.perellonieto.com/PyCalib/index.html
Author: Miquel Perello Nieto, Hao Song, Telmo de Menezes e Silva Filho
Author-email: perello.nieto@gmail.com
License: UNKNOWN
Download-URL: https://github.com/perellonieto/pycalib/archive/0.0.9.dev4.tar.gz
Description: [![CI][ci:b]][ci]
        [![Documentation][documentation:b]][documentation]
        [![License BSD3][license:b]][license]
        ![Python3.8][python:b]
        [![pypi][pypi:b]][pypi]
        [![codecov][codecov:b]][codecov]
        
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        [license]: https://github.com/perellonieto/PyCalib/blob/master/LICENSE.txt
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        PyCalib
        =======
        Python library for classifier calibration
        
        User installation
        -----------------
        
        The PyCalib package can be installed from Pypi with the command
        
        ```
        pip install pycalib
        ```
        
        Documentation
        -------------
        
        The documentation can be found at https://www.perellonieto.com/PyCalib/
        
        Development
        ===========
        
        There is a make file to automate some of the common tasks during development.
        After downloading the repository create the virtual environment with the
        command
        
        ```
        make venv
        ```
        
        This will create a `venv` folder in your current folder. The environment needs
        to be loaded out of the makefile with
        
        ```
        source venv/bin/activate
        ```
        
        After the environment is loaded, all dependencies can be installed with
        
        ```
        make requirements-dev
        ```
        
        Unittest
        --------
        
        Unittests are specified as doctest examples in simple functions (see example ),
        and more complex tests in their own python files starting with `test_` (see
        example ).
        
        Run the unittest with the command
        
        ```
        make test
        ```
        
        The test will show a unittest result including the coverage of the code.
        Ideally we want to increase the coverage to cover most of the library.
        
        Contiunous Integration
        ----------------------
        
        Every time a commit is pushed to the master branch a unittest is run following
        the workflow [.github/workflows/ci.yml](.github/workflows/ci.yml). The CI badge
        in the README file will show if the test has passed or not.
        
        Analyse code
        ------------
        
        We are trying to follow the same code standards as in [Numpy][numpy:c] and 
        [Scikit-learn][sklearn:c], it is possible to check for pep8 and other code
        conventions with
        
        [numpy:c]: https://numpy.org/devdocs/dev/index.html
        [sklearn:c]: https://scikit-learn.org/stable/developers/index.html
        
        ```
        make code-analysis
        ```
        
        Documentation
        -------------
        
        The documentation can be found at
        [https://www.perellonieto.com/PyCalib/](https://www.perellonieto.com/PyCalib/),
        and it is automatically updated after every push to the master branch.
        
        All documentation is done ussing the [Sphinx documentation
        generator][sphinx:l].  The documentation is written in
        [reStructuredText][rst:l] (\*.rst) files in the `docs/source` folder. We try to
        follow the conventions from [Numpy][numpy:d] and [Scikit-learn][sklearn:d].
        
        [numpy:d]: https://numpydoc.readthedocs.io/en/latest/format.html
        [sklearn:d]: https://scikit-learn.org/stable/developers/contributing.html#documentation
        
        The examples with images in folder `docs/source/examples` are generated
        automatically with [Sphinx-gallery][sphinx:g] from the python code in folder
        [examples/](examples/) starting with `xmpl_{example_name}.py`.
        
        [rst:l]: https://docutils.sourceforge.io/rst.html
        [sphinx:l]: https://www.sphinx-doc.org/en/master/
        [sphinx:g]: https://sphinx-gallery.github.io/stable/index.html
        
        The docuemnation can be build with the command
        
        ```
        make doc
        ```
        
        (Keep in mind that the documentation has its own Makefile inside folder [docs](docs)).
        
        After building the documentation, a new folder should appear in `docs/build/`
        with an `index.html` that can be opened locally for further exploration.
        
        The documentation is always build and deployed every time a new commit is
        pushed to the master branch with the workflow
        [.github/workflows/documentation.yml](.github/workflows/documentation.yml).
        
        After building, the `docs/build/html` folder is pushed to the branch
        [gh-pages][gh:l].
        
        [gh:l]: https://github.com/perellonieto/PyCalib/tree/gh-pages
        
        Check Readme
        ------------
        
        It is possible to check that the README file passes some tests for Pypi by
        running
        
        ```
        make check-readme
        ```
        
        Upload to PyPi
        --------------
        
        After testing that the code passes all unittests and upgrading the version in
        the file `pycalib/__init__.py` the code can be published in Pypi with the
        following command:
        
        ```
        make pypi
        ```
        
        It may require user and password if these are not set in your home directory a
        file  __.pypirc__
        
        ```
        [pypi]
        username = __token__
        password = pypi-yourtoken
        ```
        
        Contributors
        ------------
        
        This code has been adapted by Miquel from several previous codes. The following
        is a list of people that has been involved in some parts of the code.
        
        - Miquel Perello Nieto
        - Hao Song
        - Telmo Silva Filho
        - Markus Kängsepp
        
Keywords: classifier calibration,calibration,classification
Platform: UNKNOWN
Description-Content-Type: text/markdown
