Metadata-Version: 2.1
Name: fa2
Version: 0.3.4
Summary: The fastest ForceAtlas2 algorithm for Python (and NetworkX)
Home-page: https://github.com/bhargavchippada/forceatlas2
Author: Bhargav Chippada
Author-email: bhargavchippada19@gmail.com
License: UNKNOWN
Download-URL: https://github.com/bhargavchippada/forceatlas2/archive/v0.3.4.tar.gz
Description: ## ForceAtlas2 for Python and NetworkX
        
        A port of Gephi's Force Atlas 2 layout algorithm to Python 2 and Python 3 (with a wrapper for NetworkX). This is the fastest python implementation available with most of the features complete. It also supports Barnes Hut approximation for maximum speedup.
        
        ForceAtlas2 is a very fast layout algorithm for force directed graphs. The implementation is based on this [paper](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098679) and the corresponding [gephi-java-code](https://github.com/gephi/gephi/blob/master/modules/LayoutPlugin/src/main/java/org/gephi/layout/plugin/forceAtlas2/ForceAtlas2.java). Its really quick compared to the fruchterman reingold algorithm (spring layout) of networkx and scales well to high number of nodes (>10000).
        
        <p align="center" text-align="center">
            <b>Spatialize a random Geometric Graph</b>
        </p>
        <p align="center">
          <img width="460" height="300" src="https://raw.githubusercontent.com/bhargavchippada/forceatlas2/master/examples/geometric_graph.png" alt="Geometric Graph">
        </p>
        
        ## Installation
        
        Install from pip:
        
            pip install fa2
        
        To build and install run from source:
        
            python setup.py install
        
        **Cython is highly recommended if you are buidling from source as it will speed up by a factor of 10-100x depending on the graph**
        
        ### Dependencies
        
        -   numpy (adjacency matrix as complete matrix)
        -   scipy (adjacency matrix as sparse matrix)
        -   tqdm (progressbar)
        -   Cython (10-100x speedup)
        -   networkx (To use the NetworkX wrapper function, you obviously need NetworkX)
        
        <p align="center" text-align="center">
            <b>Spatialize a 2D Grid</b>
        </p>
        <p align="center">
          <img width="460" height="300" src="https://raw.githubusercontent.com/bhargavchippada/forceatlas2/master/examples/grid_graph.png" alt="Grid Graph">
        </p>
        
        ## Usage
        
        from fa2 import ForceAtlas2
        
        Create a ForceAtlas2 object with the appropriate settings. ForceAtlas2 class contains two important methods:
        ```python
        forceatlas2 (G, pos, iterations)
        # G is a graph in 2D numpy ndarray format (or) scipy sparse matrix format
        # pos is a numpy array (Nx2) of initial positions of nodes
        # iterations is num of iterations to run the algorithm
        ```
        ```python
        forceatlas2_networkx_layout(G, pos, iterations)
        # G is networkx graph
        # pos is a dictionary, as in networkx
        # iterations is num of iterations to run the algorithm
        ```
        Below is an example usage. You can also see the feature settings of ForceAtlas2 class.
        
        ```python
        import networkx as nx
        from fa2 import ForceAtlas2
        import matplotlib.pyplot as plt
        
        G = nx.random_geometric_graph(400, 0.2)
        
        forceatlas2 = ForceAtlas2(
                                # Behavior alternatives
                                outboundAttractionDistribution=True,  # Dissuade hubs
                                linLogMode=False,  # NOT IMPLEMENTED
                                adjustSizes=False,  # Prevent overlap (NOT IMPLEMENTED)
                                edgeWeightInfluence=1.0,
        
                                # Performance
                                jitterTolerance=1.0,  # Tolerance
                                barnesHutOptimize=True,
                                barnesHutTheta=1.2,
                                multiThreaded=False,  # NOT IMPLEMENTED
        
                                # Tuning
                                scalingRatio=2.0,
                                strongGravityMode=False,
                                gravity=1.0,
        
                                # Log
                                verbose=True)
        
        positions = forceatlas2.forceatlas2_networkx_layout(G, pos=None, iterations=2000)
        nx.draw_networkx_nodes(G, positions, node_size=20, with_labels=False, node_color="blue", alpha=0.4)
        nx.draw_networkx_edges(G, positions, edge_color="green", alpha=0.05)
        plt.axis('off')
        plt.show()
        ```
        You can also take a look at forceatlas2.py file for understanding the ForceAtlas2 class and its functions better.
        
        ## Features Completed
        
        -   **barnesHutOptimize**: Barnes Hut optimization, n<sup>2</sup> complexity to n.ln(n)
        -   **gravity**: Attracts nodes to the center. Prevents islands from drifting away
        -   **Dissuade Hubs**: Distributes attraction along outbound edges. Hubs attract less and thus are pushed to the borders
        -   **scalingRatio**: How much repulsion you want. More makes a more sparse graph
        -   **strongGravityMode**: A stronger gravity view
        -   **jitterTolerance**: How much swinging you allow. Above 1 discouraged. Lower gives less speed and more precision
        -   **verbose**: Shows a progressbar of iterations completed. Also, shows time taken for different force computations
        -   **edgeWeightInfluence**: How much influence you give to the edges weight. 0 is "no influence" and 1 is "normal"
        
        ## Documentation
        
        You will find all the documentation in the source code
        
        ## Contributors
        
        Contributions are highly welcome. Please submit your pull requests and become a collaborator.
        
        ## Copyright
        
            Copyright (C) 2017 Bhargav Chippada bhargavchippada19@gmail.com.
            Licensed under the GNU GPLv3.
        
        The files are heavily based on the java files included in Gephi, git revision 2b9a7c8 and Max Shinn's port to python of the algorithm. Here I include the copyright information from those files:
        
            Copyright 2008-2011 Gephi
            Authors : Mathieu Jacomy <mathieu.jacomy@gmail.com>
            Website : http://www.gephi.org
            Copyright 2011 Gephi Consortium. All rights reserved.
            Portions Copyrighted 2011 Gephi Consortium.
            The contents of this file are subject to the terms of either the
            GNU General Public License Version 3 only ("GPL") or the Common
            Development and Distribution License("CDDL") (collectively, the
            "License"). You may not use this file except in compliance with
            the License.
        
            <https://github.com/mwshinn/forceatlas2-python>
            Copyright 2016 Max Shinn <mws41@cam.ac.uk>
            Available under the GPLv3
        
            Also, thanks to Eugene Bosiakov <https://github.com/bosiakov/fa2l>
        
Keywords: forceatlas2,networkx,force-directed-graph,force-layout,graph
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
Provides-Extra: networkx
