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Scikit-Network is an open-source python package created at LINCS.

You are very welcome to participate and add your own graph algorithms.

We just ask you to follow some guidelines:

Getting Started

A toy package by François Durand

Allowed external dependencies

• NumPy
• SciPy
• Numba

Coding style

• Object oriented programming with Scikit-learn style: an algorithm is a class with a fit method.
• PEP8 coding style (it is recommended to use Pycharm Community as an IDE)
• Explicit variable names: graph, node, edge, adjacency_matrix or adj_matrix, source, target, edge_weights...
• NumPy docstring

node_weights: np.ndarray(dtype=float)
vector of node weights

Function or class description should begin with a imperative form or a noun.

Cluster nodes of the graph.

• Reference style: APA

Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment.