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\u003chttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098679\u003e`_.\n\n**Warning:** Some features (especially *Prevent Overlapping*) are not completely implemented. I'm waiting for your pull-requests.\n\nExample of social graph rendered with force atlas 2 layout:\n\n.. image:: https://raw.githubusercontent.com/bosiakov/fa2l/master/_static/result.jpg\n\nInstalling\n----------\n\nSupports Python 3.3+\n\nInstall from pip:\n\n.. code-block:: bash\n\n     pip install fa2l\n\n\nTo build and install run from source:\n\n.. code-block:: bash\n\n     python setup.py install\n\nUsage\n-----\n\n.. code-block:: python\n\n    import networkx as nx\n    from fa2l import force_atlas2_layout\n    import matplotlib.pyplot as plt\n\n    G = nx.erdos_renyi_graph(100, 0.15, directed=False)\n\n    positions = force_atlas2_layout(G,\n                                    iterations=1000,\n                                    pos_list=None,\n                                    node_masses=None,\n                                    outbound_attraction_distribution=False,\n                                    lin_log_mode=False,\n                                    prevent_overlapping=False,\n                                    edge_weight_influence=1.0,\n\n                                    jitter_tolerance=1.0,\n                                    barnes_hut_optimize=True,\n                                    barnes_hut_theta=0.5,\n\n                                    scaling_ratio=2.0,\n                                    strong_gravity_mode=False,\n                                    multithread=False,\n                                    gravity=1.0)\n\n    nx.draw_networkx(G, positions, cmap=plt.get_cmap('jet'), node_size=50, with_labels=False)\n    plt.show()\n\n\nFeatures\n--------\n\nForce Atlas 2 features these settings:\n\n- *Approximate Repulsion*: Barnes Hut optimization: n² complexity to n.ln(n).\n- *Gravity*: Attracts nodes to the center. Prevents islands from drifting away.\n- *Dissuade Hubs*: Distributes attraction along outbound edges. Hubs attract less and thus are pushed to the borders.\n- *LinLog mode*: Switch ForceAtlas model from lin-lin to lin-log. Makes clusters more tight.\n- *Prevent Overlap*. WARNING! Does not work very well.\n- *Tolerance*: How much swinging you allow. Above 1 discouraged. Lower gives less speed and more precision.\n- *Edge Weight Influence*: How much influence you give to the edges weight. 0 is \"no influence\" and 1 is \"normal\".\n\nDocumentation\n-------------\n\nYou will find all the documentation in the source code\n\nCopyright\n---------\n\nCopyright Eugene Bosiakov. Licensed under the GNU GPLv3.\n\nThis files are based on the java files included in Gephi (Copyright 2011 Gephi Consortium).\n\nAlso thanks to Max Shinn.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbosiakov%2Ffa2l","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbosiakov%2Ffa2l","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbosiakov%2Ffa2l/lists"}