Main module#
For more details regarding the main classes, see:
NNGT#
Package aimed at facilitating the analysis of Neural Networks Growth and Topology.
The library mainly provides algorithms for
- generating networks
- analyzing their activity
- studying the graph theoretical properties of those networks
Available modules#
- analysis
- Tools to study graph topology and neuronal activity.
- core
- Where the main classes are coded; however, most useful classes and methods for users are loaded at the main level (nngt) when the library is imported, so nngt.core should generally not be used.
- generation
- Functions to generate specific networks.
- geometry
- Tools to work on metric graphs (see PyNCulture).
- io
- Tools for input/output operations.
- lib
- Basic functions used by several most other modules.
- simulation
- Tools to provide complex network generation with NEST and help analyze the influence of the network structure on neuronal activity.
- plot
- plot data or graphs using matplotlib and graph_tool.
Units#
Functions related to spatial embedding of networks are using micrometers (um) as default unit; other units from the metric system can also be provided:
- mm for milimeters
- cm centimeters
- dm for decimeters
- m for meters
Main classes and functions#
nngt.Graph([nodes, name, weighted, …]) |
The basic graph class, which inherits from a library class such as gt.Graph, networkx.DiGraph, or igraph.Graph. |
nngt.GroupProperty(size[, constraints, …]) |
Class defining the properties needed to create groups of neurons from an existing GraphClass or one of its subclasses. |
nngt.Network([name, weighted, directed, …]) |
The detailed class that inherits from Graph and implements additional properties to describe various biological functions and interact with the NEST simulator. |
nngt.NeuralGroup([nodes, ntype, …]) |
Class defining groups of neurons. |
nngt.NeuralPop([size, parent, with_models]) |
The basic class that contains groups of neurons and their properties. |
nngt.SpatialGraph([nodes, name, weighted, …]) |
The detailed class that inherits from Graph and implements additional properties to describe spatial graphs (i.e. |
nngt.SpatialNetwork(population[, name, …]) |
Class that inherits from Network and SpatialGraph to provide a detailed description of a real neural network in space, i.e. |
nngt.generate(di_instructions, **kwargs) |
Generate a Graph or one of its subclasses from a dict containing all the relevant informations. |
nngt.get_config([key, detailed]) |
Get the NNGT configuration as a dictionary. |
nngt.load_from_file(filename[, fmt, …]) |
Load a Graph from a file. |
nngt.num_mpi_processes() |
Returns the number of MPI processes (1 if MPI is not used) |
nngt.on_master_process() |
Check whether the current code is executing on the master process (rank 0) if MPI is used. |
nngt.save_to_file(graph, filename[, fmt, …]) |
Save a graph to file. |
nngt.seed([msd, seeds]) |
Seed the random generator used by NNGT (i.e. |
nngt.set_config(config[, value, silent]) |
Set NNGT’s configuration. |
nngt.use_backend(backend[, reloading, silent]) |
Allows the user to switch to a specific graph library as backend. |