Metadata-Version: 2.1
Name: bicm
Version: 0.9
Summary: Package for bipartite configuration model
Home-page: https://github.com/mat701/BiCM
Author: Matteo Bruno
Author-email: matteo.bruno@imtlucca.it
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=2.7
Description-Content-Type: text/markdown

BiCM package.

This is a Python package for the computation of the maximum entropy bipartite configuration model (BiCM) and the projection of bipartite networks on one layer. It was developed with Python 3.5.

You can install this package via pip: 

    pip install bicm

Documentation is available at https://bipartite-configuration-model.readthedocs.io/en/latest/.

For more solvers of maximum entropy configuration models visit https://meh.imtlucca.it/

## How to cite

If you use the `bicm` module, please cite its location on Github
[https://github.com/mat701/BiCM](https://github.com/mat701/BiCM) and the
original articles \[Saracco2015\] and \[Saracco2017\].

### References

\[Saracco2015\] [F. Saracco, R. Di Clemente, A. Gabrielli, T. Squartini, Randomizing bipartite networks: the case of the World Trade Web, Scientific Reports 5, 10595 (2015)](http://www.nature.com/articles/srep10595).

\[Saracco2017\] [F. Saracco, M. J. Straka, R. Di Clemente, A. Gabrielli, G. Caldarelli, and T. Squartini, Inferring monopartite projections of bipartite networks: an entropy-based approach, New J. Phys. 19, 053022 (2017)](http://stacks.iop.org/1367-2630/19/i=5/a=053022)

\[Squartini2011\] [T. Squartini, D. Garlaschelli, Analytical maximum-likelihood method to detect patterns in real networks, New Journal of Physics 13, (2011)](http://iopscience.iop.org/article/10.1088/1367-2630/13/8/083001)

