Skip to main content

Network Analysis Tool around Python-Igraph Library for graph-theoretic parameters evaluation offering a variety of functions useful for bioinformatics including community detection and interactive visualisation of graph offering menu-driven simple to use an approach ( Initial version of code : https://github.com/nitinp14920914/igraphtool)

Project description

pnat

Network Analysis Tool around Python-Igraph Library for graph-theoretic parameters evaluation offering a variety of functions useful for bioinformatics including community detection and interactive visualisation of graph offering menu-driven simple to use an approach ( Initial version of code : https://github.com/nitinp14920914/igraphtool)

Table of contents

Installation

Dependencies

python2.7/3.6
Matplotlib v3.1.1
python-igraph v0.7.1.post6
Networkx v2.3
pyvis v0.1.7.0

Matplotlib

Debian / Ubuntu :  sudo apt-get install python-matplotlib
Fedora / Redhat :  sudo yum install python-matplotlib

for pip
python -m pip install -U pip setuptools
python -m pip install matplotlib
python -m pip install pyvis

python-igraph

Debian / Ubuntu : sudo apt-get install python-igraph
Fedora / Redhat : sudo yum install python-igraph

using pip
pip install python-igraph

NetworkX

python -m pip install networkx

Pyvis

python -m pip install pyvis

List of Files

pnat.py
readme

Network Analysis Tool Usage

Usage

python pnat.py -format filename

For help

  python pnat.py -h or --help
  • Enter the function number you want

  • It Returns output for a selected function

  • Network output files are written in graphml format

  • A directory named temp is created on very first initialisation of script

  • There is also a ./temp directory associated with pnat.py where plots/figures/are exported and saved

List of Functions

usage -format [filename]

format: adjacencncy matrix -adj  edgelist -edgelist  graphml -graphml  lgl -lgl  random network -random

=========== Feature List v1.0 =====================
Parameter Evaluation........................###
	Degree Distribution Histogram...........(1)
	Centrality : 
		* Eigenvector centrality........(2)
		* Betweenness centrality........(3)
	Average path length.....................(4)
	Degree distribution.....................(5)
	Clustering coefficient..................(6)
		* Average Clustering coefficient[1]
		* Each-nodes Clustering coeff.  [2]
	Shortest path between two nodes.........(7)
	Shortest path between all nodes.........(8)
	Degree distribution power law...........(9)
	Functional motifs......................(10)
	Modularity.............................(13)
	Connectivity : 
		vertex * For given two vertex..(14)
	       	       *Overall................(15)
		Edge   * For given two vertex..(16)
	       	       *Overall................(17)
	No. of clusters........................(18)
	Diameter...............................(23)
	Average path length....................(24)
	Giant_component Extraction.............(25)
Know-your Graph.............................###
	Maximum degree nodes.... ........... . (30)
	Minimum degree nodes.... ...........  .(31)
	Neighbour vertex : 
		* For two specified vertes.....(11)
		* For all vertex of graph......(12)
	Node label from its node id(Every node)(20)
	Node label from its node id(Every node)(21)
Saving/Writing Graph........................###
	Adjacency matrix.......................(19)
	Edgelist...............................(22)
	Interactive Plot.......................(34)
Editing Graph Data .........................###
	Add vertex(single)..............  ..   (26)
	Add vertices(many)..................   (27)
	Delete vertex(single)................ .(28)
	Delete vertices(many).... ........... .(29)
	Deleting all nodes saving in file .....(32)
Community Detection/Structure..........    .###
	Community Detection/Structure..........(33)
	* Community_walktrap           [1]
	* Compare_communities          [2]
	* Community_edge_betweenness   [3]
	* Community_infomap            [4]
	* Community_label_propagation  [5]

Contact Information

For any trouble and query feel free we would love to respond

Project details


Release history Release notifications

This version

1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pnat, version 1.0
Filename, size File type Python version Upload date Hashes
Filename, size pnat-1.0-py3-none-any.whl (7.7 kB) File type Wheel Python version py3 Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page