concepts icon indicating copy to clipboard operation
concepts copied to clipboard

Published 20 hours ago • verified publisher icon xflr6
→

Metadata

Formal Concept Analysis with Python

Concepts

|PyPI version| |License| |Supported Python| |Wheel|

|Build| |Codecov| |Readthedocs-stable| |Readthedocs-latest|

Concepts is a simple Python implementation of Formal Concept Analysis (FCA_).

|Logo|

FCA provides a mathematical model for describing a set of objects (e.g. King Arthur, Sir Robin, and the holy grail) with a set of properties (e.g. human, knight, king, and mysterious) which each of the objects either has or not. A table called formal context defines which objects have a given property and vice versa which properties a given object has.

Links

  • GitHub: https://github.com/xflr6/concepts
  • PyPI: https://pypi.org/project/concepts/
  • Documentation: https://concepts.readthedocs.io
  • Changelog: https://concepts.readthedocs.io/en/latest/changelog.html
  • Issue Tracker: https://github.com/xflr6/concepts/issues
  • Download: https://pypi.org/project/concepts/#files

Installation

This package runs under Python 3.8+, use pip_ to install:

.. code:: bash

$ pip install concepts

This will also install the bitsets_ and graphviz_ packages from PyPI as required dependencies.

Rendering lattice graphs depends on the Graphviz software_. Make sure its dot executable is on your systems' path.

Quickstart

Create a formal context defining which object has which property, e.g. from a simple ASCII-art style cross-table with object rows and property columns (alternatively load a CXT or CSV file):

.. code:: python

>>> import concepts
>>> context = concepts.Context.fromstring('''
...            |human|knight|king |mysterious|
... King Arthur|  X  |  X   |  X  |          |
... Sir Robin  |  X  |  X   |     |          |
... holy grail |     |      |     |     X    |
... ''')
>>> context  # doctest: +ELLIPSIS
<Context object mapping 3 objects to 4 properties [dae7402a] at 0x...>

Query common properties of objects or common objects of properties (derivation):

.. code:: python

>>> context.intension(['King Arthur', 'Sir Robin'])
('human', 'knight')

>>> context.extension(['knight', 'mysterious'])
()

Get the closest matching objects-properties pair of objects or properties (formal concepts):

.. code:: python

>>> context['Sir Robin', 'holy grail']
(('King Arthur', 'Sir Robin', 'holy grail'), ())

>>> context['king',]
(('King Arthur',), ('human', 'knight', 'king'))

Iterate over the concept lattice of all objects-properties pairs:

.. code:: python

>>> for extent, intent in context.lattice:
...     print(extent, intent)
() ('human', 'knight', 'king', 'mysterious')
('King Arthur',) ('human', 'knight', 'king')
('holy grail',) ('mysterious',)
('King Arthur', 'Sir Robin') ('human', 'knight')
('King Arthur', 'Sir Robin', 'holy grail') ()

Make a Graphviz visualization of the lattice (use .graphviz(view=True) to directly render it and display the resulting PDF):

.. code:: python

>>> context.lattice.graphviz()  # doctest: +ELLIPSIS
<graphviz.graphs.Digraph object at 0x...>

.. image:: https://raw.github.com/xflr6/concepts/master/docs/holy-grail.png :align: center

Further reading

  • https://en.wikipedia.org/wiki/Formal_concept_analysis
  • http://www.upriss.org.uk/fca/

The generation of the concept lattice is based on the algorithm from C. Lindig. Fast Concept Analysis_. In Gerhard Stumme, editors, Working with Conceptual Structures - Contributions to ICCS 2000, Shaker Verlag, Aachen, Germany, 2000.

Most of the included example CXT files are taken from Uta Priss' FCA homepage_.

The mushroom dataset is converted from the UCI Mashine Learning repsitory_.

See also

The implementation is based on these Python packages:

  • bitsets_ |--| Ordered subsets over a predefined domain
  • graphviz_ |--| Simple Python interface for Graphviz

The following package is build on top of concepts:

  • features_ |--| Feature set algebra for linguistics

If you want to apply FCA to bigger data sets, you might want to consider other implementations_ based on more sophisticated algorithms_ like In-Close_ or Fcbo_.

License

Concepts is distributed under the MIT license_.

.. _FCA: https://en.wikipedia.org/wiki/Formal_concept_analysis .. _Fast Concept Analysis: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.948 .. _FCA homepage: http://www.upriss.org.uk/fca/examples.html .. _UCI Mashine Learning repsitory: https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/

.. _pip: https://pip.readthedocs.io .. _Graphviz software: http://www.graphviz.org

.. _bitsets: https://pypi.org/project/bitsets/ .. _graphviz: https://pypi.org/project/graphviz/ .. _features: https://pypi.org/project/features/

.. _other implementations: http://www.upriss.org.uk/fca/fcasoftware.html .. _more sophisticated algorithms: https://upriss.github.io/fca/fcaalgorithms.html .. _In-Close: https://sourceforge.net/projects/inclose/ .. _Fcbo: http://fcalgs.sourceforge.net

.. _MIT license: https://opensource.org/licenses/MIT

.. |--| unicode:: U+2013

.. |PyPI version| image:: https://img.shields.io/pypi/v/concepts.svg :target: https://pypi.org/project/concepts/ :alt: Latest PyPI Version .. |License| image:: https://img.shields.io/pypi/l/concepts.svg :target: https://github.com/xflr6/concepts/blob/master/LICENSE.txt :alt: License .. |Supported Python| image:: https://img.shields.io/pypi/pyversions/concepts.svg :target: https://pypi.org/project/concepts/ :alt: Supported Python Versions .. |Wheel| image:: https://img.shields.io/pypi/wheel/concepts.svg :target: https://pypi.org/project/concepts/#files :alt: Wheel format

.. |Build| image:: https://github.com/xflr6/concepts/actions/workflows/build.yaml/badge.svg?branch=master :target: https://github.com/xflr6/concepts/actions/workflows/build.yaml?query=branch%3Amaster :alt: Build .. |Codecov| image:: https://codecov.io/gh/xflr6/concepts/branch/master/graph/badge.svg :target: https://codecov.io/gh/xflr6/concepts :alt: Codecov .. |Readthedocs-stable| image:: https://readthedocs.org/projects/concepts/badge/?version=stable :target: https://concepts.readthedocs.io/en/stable/?badge=stable :alt: Readthedocs stable .. |Readthedocs-latest| image:: https://readthedocs.org/projects/concepts/badge/?version=latest :target: https://concepts.readthedocs.io/en/latest/?badge=latest :alt: Readthedocs latest

.. |Logo| image:: https://raw.github.com/xflr6/concepts/master/docs/logo_full.png :alt: Logo

← Metadata

101
Stars
21
Forks
Watchers

Owner

verified publisher icon xflr6

Metadata

Formal Concept Analysis with Python

Back