Core module

Core classes and functions. Most of them are not visible in the module as they are directly loaded at nngt level.

Content

nngt.core.GraphObject

alias of GtGraph

class nngt.core.IGraph(nodes=0, g=None, directed=True, parent=None)

Bases: abc.Mock

Subclass of igraph.Graph.

__abstractmethods__ = frozenset([])

__init__(nodes=0, g=None, directed=True, parent=None)

betweenness_list(use_weights=True, as_prop=False, norm=True)

clear_all_edges()

Remove all connections in the graph.

degree_list(node_list=None, deg_type='total', use_weights=True)

edge_nb()

new_edge(source, target, weight=1.0)

Adding a connection to the graph, with optional properties.

Parameters:

• source (int/node) – Source node.
• target (int/node) – Target node.
• weight (double, optional (default: 1.)) – Weight of the connection (synaptic strength with NEST).

Returns:

The new connection.

new_edges(edge_list, eprops=None)

Adds a list of connections to the graph

new_node(n=1, ntype=1)

Adding a node to the graph, with optional properties.

Parameters:

• n (int, optional (default: 1)) – Number of nodes to add.
• ntype (int, optional (default: 1)) – Type of neuron (1 for excitatory, -1 for inhibitory)

Returns:

The node or an iterator over the nodes created.

node_nb()

remove_edge(edge)

remove_vertex(node, fast=False)

class nngt.core.GtGraph(nodes=0, g=None, directed=True, prune=False, vorder=None)

Bases: abc.Mock

Subclass of graph_tool.Graph that (with SnapGraph) unifies the methods to work with either graph_tool or SNAP.

__abstractmethods__ = frozenset([])

__init__(nodes=0, g=None, directed=True, prune=False, vorder=None)

@todo: document that see graph_tool.Graph‘s constructor

betweenness_list(use_weights=True, as_prop=False, norm=True)

clear_all_edges()

degree_list(node_list=None, deg_type='total', use_weights=True)

edge_nb()

new_edge(source, target, weight=1.0)

Adding an edge to the graph, with optional properties.

Parameters:

• source (int/node) – Source node.
• target (int/node) – Target node.
• weight (double, optional (default: 1.)) – Weight of the connection (synaptic strength with NEST).

Returns:

The new edge.

new_edges(edge_list, eprops=None)

Adds a list of edges to the graph @todo: see how the eprops work

new_node(n=1, ntype=1)

Adding a node to the graph, with optional properties.

Parameters:

• n (int, optional (default: 1)) – Number of nodes to add.
• ntype (int, optional (default: 1)) – Type of neuron (1 for excitatory, -1 for inhibitory)

Returns:

The node or an iterator over the nodes created.

node_nb()

class nngt.core.NxGraph(nodes=0, g=None, directed=True)

Bases: abc.Mock

Subclass of networkx Graph

__abstractmethods__ = frozenset([])

__init__(nodes=0, g=None, directed=True)

betweenness_list(use_weights=True, as_prop=False)

clear_all_edges()

Remove all connections in the graph

degree_list(node_list=None, deg_type='total', use_weights=True)

di_value = {'int': 0, 'double': 0.0, 'string': ''}

edge_nb()

new_edge(source, target, weight=1.0)

Adding a connection to the graph, with optional properties.

Parameters:

• source (int/node) – Source node.
• target (int/node) – Target node.
• add_missing (bool, optional (default: None)) – Add the nodes if they do not exist.
• weight (double, optional (default: 1.)) – Weight of the connection (synaptic strength with NEST).

Returns:

The new connection.

new_edge_attribute(name, value_type, values=None, val=None)

new_edges(edge_list, eprops=None)

Adds a list of connections to the graph

new_node(n=1, ntype=1)

Adding a node to the graph, with optional properties.

Parameters:

• n (int, optional (default: 1)) – Number of nodes to add.
• ntype (int, optional (default: 1)) – Type of neuron (1 for excitatory, -1 for inhibitory)

Returns:

The node or an iterator over the nodes created.

new_node_attribute(name, value_type, values=None, val=None)

node_nb()

set_node_property()