Python library with tools for classifier calibration.
Project description
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://classifier-calibration.github.io/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. 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 and Scikit-learn, it is possible to check for pep8 and other code conventions with
make code-analysis
Documentation
The documentation can be found at https://www.classifier-calibration.com/PyCalib/, and it is automatically updated after every push to the master branch.
All documentation is done ussing the Sphinx documentation
generator. The documentation is written in
reStructuredText (*.rst) files in the docs/source
folder. We try to
follow the conventions from Numpy and Scikit-learn.
The examples with images in folder docs/source/examples
are generated
automatically with Sphinx-gallery from the python code in folder
examples/ starting with xmpl_{example_name}.py
.
The docuemnation can be build with the command
make doc
(Keep in mind that the documentation has its own Makefile inside folder 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.
After building, the docs/build/html
folder is pushed to the branch
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
Project details
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