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NNGT 2.8.0
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NNGT 2.8.0



User Documentation

 * Installation
 * Intro & user manual
   Toggle navigation of Intro & user manual
   * Graph generation
   * Properties of graph components
   * Consistent tools for graph analysis
   * Parallelism
   * Groups, structures, and neuronal populations
   * Interacting with the NEST simulator
   * Activity analysis
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     * Simulation module
   * Graph generation
   * Main module (API)
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     * Graph classes
     * Main functions
     * Side classes
     * Analysis module
     * Generation module
     * Geometry module
     * Lib module
     * Plot module
     * Simulation module
 * Tutorial
 * Gallery
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   * Visualizing graph structures
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     * Geospatial networks
     * Chord diagram
     * Hive plot panel
     * Layouts for topological representations
   * Visualizing graph properties
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     * Plot the degree distributions of a graph
     * Plot the betweenness distributions of a graph
     * Plot various graph properties
   * Geospatial networks
   * Chord diagram
   * Hive plot panel
   * Layouts for topological representations
   * Plot the degree distributions of a graph
   * Plot the betweenness distributions of a graph
   * Plot various graph properties

Contributing

 * Contributing to NNGT
 * SourceHut
 * Codeberg
 * GitHub

Modules

 * Main module (API)
   Toggle navigation of Main module (API)
   * Graph classes
   * Main functions
   * Side classes
   * Analysis module
   * Generation module
   * Geometry module
   * Lib module
   * Plot module
   * Simulation module
 * Analysis module
 * Database module
 * Generation module
 * Geospatial module
 * Geometry module
 * Lib module
 * Plot module
 * Simulation module

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WELCOME TO NNGT’S DOCUMENTATION!#


OVERVIEW#

The Neural Networks and Graphs’ Topology (NNGT) module provides a unified
interface to access, generate, and analyze networks via any of the well-known
Python graph libraries: networkx, igraph, and graph-tool.

For people in neuroscience, the library also provides tools to grow and study
detailed biological networks by interfacing efficient graph libraries with
highly distributed activity simulators.

The library has two main targets:

 * people looking for a unifying interface for these three graph libraries,
   allowing to run and share a single code on different platforms

 * neuroscience people looking for an easy way to generate complex networks
   while keeping track of neuronal populations and their biological properties


MAIN CLASSES#

NNGT provides four main classes. The two first are aimed at the
graph-theoretical community, the third and fourth are more for the neuroscience
community. Additional details are provided on the Main module (API) page.

Graph

provides a simple implementation to access and analyse topological graphs by
wrapping any graph object from other graph libraries.

SpatialGraph

a Graph embedded in space (nodes have positions and connections are associated
to a distance).

Network

provides more detailed characteristics to emulate biological neural networks,
such as classes of inhibitory and excitatory neurons, synaptic properties…

SpatialNetwork

combines spatial embedding and biological properties.


GENERATION OF GRAPHS#

Structured graphs and connectivity:

connectivity between the nodes can be chosen from various well-known graph
models, specific groups and structures can be generated to simplify edge
generation

Populations:

populations of neurons can be used and be set to respect various constraints
(for instance a given fraction of inhibitory neurons), they simplify network
generation and make it highly efficient to interact with the NEST simulator

Synaptic properties:

synaptic weights and delays can be set from various distributions or correlated
to edge properties


INTERACTING WITH NEST#

The generated graphs can be used to easily create complex networks using the
NEST simulator, on which you can then simulate their activity.


THE DOCS#

User Documentation

 * Installation
   * Dependencies
   * Simple install
   * Local install
   * Configuration
   * Using NEST
 * Intro & user manual
   * Yet another graph library?
   * Description
 * Tutorial
   * NNGT properties and configuration
   * The Graph object
   * Generating and analyzing more complex networks
   * Using random numbers
   * Structuring nodes: Group and Structure
   * The same with neurons: NeuralGroup, NeuralPop
   * Real neuronal networks and NEST interaction: the Network
   * Underlying graph objects and libraries
 * Gallery
   * Visualizing graph structures
   * Visualizing graph properties
   * Visualizing graph structures
   * Visualizing graph properties

Contributing

 * Contributing to NNGT
   * Signaling issues and bugs
   * Preparing a contribution
   * Sending a patch to SourceHut
   * Making a PR on GitHub
 * SourceHut
 * Codeberg
 * GitHub

Modules

 * Main module (API)
 * Analysis module
 * Database module
 * Generation module
 * Geospatial module
 * Geometry module
 * Lib module
 * Plot module
 * Simulation module


INDICES AND TABLES#

 * Index

 * Module Index

 * Search Page

Next
Installation
Copyright © 2015, Tanguy Fardet
Made with Sphinx and @pradyunsg's Furo

On this page
 * Welcome to NNGT’s documentation!
   * Overview
     * Main classes
     * Generation of graphs
     * Interacting with NEST
   * The docs
   * Indices and tables

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