Metadata-Version: 2.1
Name: FAT-Forensics
Version: 0.1.2
Summary: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Home-page: https://fat-forensics.org/
Maintainer: Kacper Sokol
Maintainer-email: k.sokol@bristol.ac.uk
License: new BSD
Download-URL: https://pypi.org/project/FAT-Forensics/#files
Description: .. -*- mode: rst -*-
        
        =============  ================================================================
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        =============  ================================================================
        
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        ============================================================================
        FAT Forensics: Algorithmic Fairness, Accountability and Transparency Toolbox
        ============================================================================
        
        FAT Forensics (``fatf``) is a Python toolbox for evaluating fairness,
        accountability and transparency of predictive systems. It is built on top of
        SciPy_ and NumPy_, and is distributed under the 3-Clause BSD license (new BSD).
        
        FAT Forensics implements the state of the art *fairness*, *accountability* and
        *transparency* (FAT) algorithms for the three main components of any data
        modelling pipeline: *data* (raw data and features), predictive *models* and
        model *predictions*. We envisage two main use cases for the package, each
        supported by distinct features implemented to support it: an interactive
        *research mode* aimed at researchers who may want to use it for an exploratory
        analysis and a *deployment mode* aimed at practitioners who may want to use it
        for monitoring FAT aspects of a predictive system.
        
        Please visit the project's web site `https://fat-forensics.org`_ for more
        details.
        
        Installation
        ============
        
        Dependencies
        ------------
        
        FAT Forensics requires **Python 3.5** or higher and the following dependencies:
        
        +------------+------------+
        | Package    | Version    |
        +============+============+
        | NumPy_     | >=1.10.0   |
        +------------+------------+
        | SciPy_     | >=0.13.3   |
        +------------+------------+
        
        In addition, some of the modules require *optional* dependencies:
        
        +--------------------------------------------------------------+------------------+------------+
        | ``fatf`` module                                              | Package          | Version    |
        +==============================================================+==================+============+
        | ``fatf.transparency.predictions.surrogate_explainers``       |                  |            |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.transparency.predictions.surrogate_image_explainers`` |                  |            |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.transparency.sklearn``                                | `scikit-learn`_  | >=0.19.2   |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.utils.data.feature_selection.sklearn``                |                  |            |
        +--------------------------------------------------------------+------------------+------------+
        | ``fatf.transparency.predictions.surrogate_image_explainers`` |                  |            |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.utils.data.occlusion``                                | `scikit-image`_  | >=0.17.0   |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.utils.data.segmentation``                             |                  |            |
        +--------------------------------------------------------------+------------------+------------+
        | ``fatf.transparency.predictions.surrogate_image_explainers`` |                  |            |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.utils.data.occlusion``                                | `Pillow`_        | >=8.4.0    |
        +--------------------------------------------------------------+                  |            |
        | ``fatf.utils.data.segmentation``                             |                  |            |
        +--------------------------------------------------------------+------------------+------------+
        | ``fatf.vis``                                                 | matplotlib_      | >=3.0.0    |
        +--------------------------------------------------------------+------------------+------------+
        
        User Installation
        -----------------
        
        The easies way to install FAT Forensics is via ``pip``::
        
           pip install fat-forensics
        
        which will only installed the required dependencies. If you want to install the
        package together with all the auxiliary dependencies please consider using the
        ``[all]`` option::
        
           pip install fat-forensics[all]
        
        The documentation provides more detailed `installation instructions <inst_>`_.
        
        Changelog
        =========
        
        See the changelog_ for a development history and project milestones.
        
        Development
        ===========
        
        We welcome new contributors of all experience levels. The
        `Development Guide <dev_guide_>`_ has detailed information about contributing
        code, documentation, tests and more. Some basic development instructions are
        included below.
        
        Important Links
        ---------------
        
        * Project's web site and documentation: `https://fat-forensics.org`_.
        * Official source code repository:
          `https://github.com/fat-forensics/fat-forensics`_.
        * FAT Forensics releases: `https://pypi.org/project/fat-forensics`_.
        * Issue tracker: `https://github.com/fat-forensics/fat-forensics/issues`_.
        
        Source Code
        -----------
        
        You can check out the latest FAT Forensics source code via git with the
        command::
        
           git clone https://github.com/fat-forensics/fat-forensics.git
        
        Contributing
        ------------
        
        To learn more about contributing to FAT Forensics, please see our
        `Contributing Guide <contrib_guide_>`_.
        
        Testing
        -------
        
        You can launch the test suite from the root directory of this repository with::
        
           make test-with-code-coverage
        
        To run the tests you will need to have version 3.9.1 of ``pytest`` installed.
        This package, together with other development dependencies, can be also
        installed with::
        
           pip install -r requirements-dev.txt
        
        or with::
        
           pip install fat-forensics[dev]
        
        See the *Testing* section of the `Development Guide <dev_testing_>`_ page for
        more information.
        
            Please note that the ``make test-with-code-coverage`` command will test the
            version of the package in the local ``fatf`` directory and not the one
            installed since the pytest command is preceded by ``PYTHONPATH=./``. If
            you want to test the installed version, consider using the command from the
            ``Makefile`` without the ``PYTHONPATH`` variable.
        
            To control the randomness during the tests the ``Makefile`` sets the random
            seed to ``42`` by preceding each test command with ``FATF_SEED=42``, which
            sets the environment variable responsible for that. More information about
            the setup of the *Testing Environment* is available on the
            `development <dev_testing_env_>`_ web page in the documentation.
        
        Submitting a Pull Request
        -------------------------
        
        Before opening a Pull Request, please have a look at the
        `Contributing <contrib_guide_>`_ page to make sure that your code complies with
        our guidelines.
        
        Help and Support
        ================
        
        For help please have a look at our
        `documentation web page <https://fat-forensics.org>`_, especially the
        `Getting Started <getting_started_>`_ page.
        
        Communication
        -------------
        
        You can reach out to us at:
        
        * our gitter_ channel for code-related development discussion; and
        * our `mailing list`_ for discussion about the project's future and the
          direction of the development.
        
        More information about the communication can be found in our documentation
        on the `main page <https://fat-forensics.org/index.html#communication>`_ and
        on the
        `develop page <https://fat-forensics.org/development.html#communication>`_.
        
        Citation
        --------
        
        If you use FAT Forensics in a scientific publication, we would appreciate
        citations! Information on how to cite use is available on the
        `citation <https://fat-forensics.org/getting_started/cite.html>`_ web page in
        our documentation.
        
        Acknowledgements
        ================
        This project is the result of a collaborative research agreement between Thales
        and the University of Bristol with the initial funding provided by Thales.
        
        .. _SciPy: https://scipy.org/
        .. _NumPy: https://www.numpy.org/
        .. _scikit-learn: https://scikit-learn.org/stable/
        .. _matplotlib: https://matplotlib.org/
        .. _scikit-image: https://scikit-image.org/
        .. _Pillow: https://pillow.readthedocs.io/
        .. _`https://fat-forensics.org`: https://fat-forensics.org
        .. _inst: https://fat-forensics.org/getting_started/install_deps_os.html#installation-instructions
        .. _changelog: https://fat-forensics.org/changelog.html
        .. _dev_guide: https://fat-forensics.org/development.html
        .. _`https://github.com/fat-forensics/fat-forensics`: https://github.com/fat-forensics/fat-forensics
        .. _`https://pypi.org/project/fat-forensics`: https://pypi.org/project/fat-forensics
        .. _`https://github.com/fat-forensics/fat-forensics/issues`: https://github.com/fat-forensics/fat-forensics/issues
        .. _contrib_guide: https://fat-forensics.org/development.html#contributing-code
        .. _dev_testing: https://fat-forensics.org/development.html#testing
        .. _dev_testing_env: https://fat-forensics.org/development.html#testing-environment
        .. _getting_started: https://fat-forensics.org/getting_started/index.html
        .. _gitter: https://gitter.im/fat-forensics
        .. _`mailing list`: https://groups.google.com/forum/#!forum/fat-forensics
        
Platform: UNKNOWN
Requires-Python: ~=3.5
Provides-Extra: all
Provides-Extra: dev
Provides-Extra: ml
Provides-Extra: vis
