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Fixing README and setup.py
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bhargavchippada committed Jan 23, 2019
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103 changes: 52 additions & 51 deletions README.md
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## 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.
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="./examples/geometric_graph.png">
<img width="460" height="300" src="https://raw.githubusercontent.com/bhargavchippada/forceatlas2/master/examples/geometric_graph.png" alt="Geometric Graph">
</p>

## Installation
Expand All @@ -35,73 +35,74 @@ To build and install run from source:
<b>Spatialize a 2D Grid</b>
</p>
<p align="center">
<img width="460" height="300" src="./examples/grid_graph.png">
<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:

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
<br/>

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

```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.

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()

```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, n² complexity to n.ln(n)
- **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”
- **edgeWeightInfluence**: How much influence you give to the edges weight. 0 is "no influence" and 1 is "normal"

## Documentation

Expand All @@ -116,7 +117,7 @@ Contributions are highly welcome. Please submit your pull requests and become a
Copyright (C) 2017 Bhargav Chippada [email protected].
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:
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 <[email protected]>
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6 changes: 3 additions & 3 deletions setup.py
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here = path.abspath(path.dirname(__file__))

# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
with open(path.join(here, 'README.md'), 'r') as f:
long_description = f.read()

print(">>>> Cython is installed?")
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setup(
name='fa2',
version='0.3.1',
version='0.3.4',
description='The fastest ForceAtlas2 algorithm for Python (and NetworkX)',
long_description_content_type='text/markdown',
long_description=long_description,
author='Bhargav Chippada',
author_email='[email protected]',
url='https://github.com/bhargavchippada/forceatlas2',
download_url='https://github.com/bhargavchippada/forceatlas2/archive/v0.3.1.tar.gz',
download_url='https://github.com/bhargavchippada/forceatlas2/archive/v0.3.4.tar.gz',
keywords=['forceatlas2', 'networkx', 'force-directed-graph', 'force-layout', 'graph'],
packages=['fa2'],
classifiers=[
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