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cdlib/algorithms/biparitte_clustering.py

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from BiMLPA import BiMLPA_SqrtDeg, relabeling, output_community
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from cdlib import BiNodeClustering
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import networkx as nx
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.. note:: Reference implementation: https://github.com/hbkt/BiMLPA
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"""
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from BiMLPA import BiMLPA_SqrtDeg, relabeling, output_community
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g = convert_graph_formats(g, nx.Graph)
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bimlpa = BiMLPA_SqrtDeg(g, theta, lambd)

cdlib/algorithms/overlapping_partition.py

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@@ -113,7 +113,7 @@ def angel(g, threshold, min_community_size=3):
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:References:
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1. Rossetti G. **Angel: efficient, and effective, node-centric community discovery in static and dynamic networks.**
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1. Rossetti, Giulio. "Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery." International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.
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.. note:: Reference implementation: https://github.com/GiulioRossetti/ANGEL
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"""

cdlib/evaluation/fitness.py

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:References:
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1. ######
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1. Citraro, Salvatore, and Giulio Rossetti. "Eva: Attribute-Aware Network Segmentation." International Conference on Complex Networks and Their Applications. Springer, Cham, 2019.
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"""
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pur = Eva.purity(communities.coms_labels)
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return FitnessResult(score=pur)

docs/bibliography.rst

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@@ -74,8 +74,7 @@ Reference evaluation:
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- Erdos_renyi_modularity: Erdos, P., & Renyi, A. (1959). `On random graphs I. <https://gnunet.org/sites/default/files/Erd%C5%91s%20%26%20R%C3%A9nyi%20-%20On%20Random%20Graphs.pdf/>`_ Publ. Math. Debrecen, 6, 290-297.
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- Modularity_density: Li, Z., Zhang, S., Wang, R. S., Zhang, X. S., & Chen, L. (2008). `Quantitative function for algorithms detection. <https://www.sciencedirect.com/science/article/pii/S0020025516305059/>`_ Physical review E, 77(3), 036109.
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- Z_modularity: Miyauchi, Atsushi, and Yasushi Kawase. `Z-score-based modularity for algorithms detection in networks. <https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147805/>`_ PloS one 11.1 (2016): e0147805.
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- Surprise: Traag, V. A., Aldecoa, R., & Delvenne, J. C. (2015). `Detecting communities using asymptotical surprise. <https://link.aps.org/doi/10.1103/PhysRevE.92.022816/>`_ Physical Review E, 92(2), 022816.
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- Significance: Traag, V. A., Aldecoa, R., & Delvenne, J. C. (2015). `Detecting communities using asymptotical surprise. <https://link.aps.org/doi/10.1103/PhysRevE.92.022816/>`_ Physical Review E, 92(2), 022816.
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- Surprise & Significance: Traag, V. A., Aldecoa, R., & Delvenne, J. C. (2015). `Detecting communities using asymptotical surprise .. <https://link.aps.org/doi/10.1103/PhysRevE.92.022816/>`_ Physical Review E, 92(2), 022816.
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- average_internal_degree: Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004). `Defining and identifying communities in networks. <https://www.pnas.org/content/101/9/2658.short/>`_ Proceedings of the National Academy of Sciences, 101(9), 2658-2663.
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- conductance: Shi, J., Malik, J.: `Normalized cuts and image segmentation. <https://repository.upenn.edu/cgi/viewcontent.cgi?article=1101&context=cis_papers/>`_ Departmental Papers (CIS), 107 (2000)
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- cut_ratio: Fortunato, S.: `Community detection in graphs. <https://www.sciencedirect.com/science/article/pii/S0370157309002841/>`_ Physics reports 486(3-5), 75–174 (2010)

docs/conf.py

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return MagicMock()
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MOCK_MODULES = ['ipaddress', 'graph-tool', 'leidenalg', 'numpy', 'scipy', 'networkx', 'sklearn', 'pquality', 'functools', 'nf1',
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MOCK_MODULES = ['ipaddress', 'graph-tool', 'leidenalg', 'numpy', 'scipy', 'networkx', 'karateclub', 'bimlpa', 'sklearn', 'pquality', 'functools', 'nf1',
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'ipython', 'pygtk', 'gtk', 'gobject', 'argparse', 'matplotlib', 'matplotlib.pyplot', 'scikit-learn',
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'python-igraph', 'wurlitzer', 'pulp','seaborn','pandas', 'infomap', 'angel-cd', 'omega_index_py3', 'karateclub',
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'bimlpa']
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'python-igraph', 'wurlitzer', 'pulp', 'seaborn', 'pandas', 'infomap', 'angel-cd', 'omega_index_py3'] #, 'karateclub', 'bimlpa']
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sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES)
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html_theme = "sphinx_rtd_theme"
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# (source start file, target name, title,
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# author, documentclass [howto, manual, or own class]).
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latex_documents = [
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(master_doc, 'CDlib.tex', u'CDlib Documentation',
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u'Giulio Rossetti', 'manual'),
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(master_doc, 'CDlib.tex', u'CDlib Documentation', u'Giulio Rossetti', 'manual'),
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]
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# The name of an image file (relative to this directory) to place at the top of

docs/reference/classes/node_clustering.rst

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.. autosummary::
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NodeClustering.normalized_mutual_information
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NodeClustering.overlapping_normalized_mutual_information
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NodeClustering.overlapping_normalized_mutual_information_MGH
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NodeClustering.overlapping_normalized_mutual_information_LFK
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NodeClustering.omega
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NodeClustering.f1
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NodeClustering.nf1

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