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github.com/danielnyga/pracmln @1.2.4

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README

pracmln -- Markov logic networks in Python

pracmln is a toolbox for statistical relational learning and reasoning and provides a pure python implementation of Markov logic networks. pracmln is a statistical relational learning and reasoning system that supports efficient learning and inference in relational domains. pracmln has started as a fork of the ProbCog toolbox and has been extended by latest developments in learning and reasoning by the Institute for Artificial Intelligence at the University of Bremen, Germany.

  • Project Page: http://www.pracmln.org
  • Lead developer: Daniel Nyga (nyga@cs.uni-bremen.de)

Installation

$ pip install pracmln

Documentation

pracmln comes with its own sphinx-based documentation. To build it, conduct the following actions:

$ cd path/to/pracmln/doc
$ make html

If you have installed Sphinx, the documentation should be build. Open it in your favorite web browser:

$ firefox _build/html/index.html

Sphinx can be installed with

$ sudo pip install sphinx sphinxcontrib-bibtex

Core symbols most depended-on inside this repo

get
called by 243
python3/pracmln/utils/undo.py
get
called by 243
python2/pracmln/utils/undo.py
append
called by 239
python2/pracmln/utils/undo.py
append
called by 231
python3/pracmln/utils/undo.py
write
called by 101
python2/pracmln/mln/base.py
iteritems
called by 64
python2/pracmln/utils/eval.py
set
called by 63
python3/pracmln/utils/undo.py
set
called by 63
python2/pracmln/utils/undo.py

Shape

Method 2,545
Class 390
Function 390

Languages

Python93%
TypeScript6%
C++1%
Java1%

Modules by API surface

python2/pracmln/logic/common.py287 symbols
python3/pracmln/logic/common.py286 symbols
python3/pracmln/utils/undo.py101 symbols
python2/pracmln/utils/undo.py101 symbols
doc/source/_static/js/d3.min.js99 symbols
python3/pracmln/utils/widgets.py82 symbols
python2/pracmln/utils/widgets.py82 symbols
python3/pracmln/mlnlearn.py64 symbols
python2/pracmln/mlnlearn.py64 symbols
doc/source/_static/js/d3.layout.min.js61 symbols
python3/pracmln/mlnquery.py59 symbols
python2/pracmln/mlnquery.py59 symbols

For agents

$ claude mcp add pracmln \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact

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