pymnet.MultiplexNetwork

class pymnet.MultiplexNetwork(couplings=None, directed=False, noEdge=0, fullyInterconnected=True)

Multiplex network as a special case of multilayer network.

Parameters:

couplingslist, str, tuple, None, MultilayerNetwork

Parameter determining how the layers are coupled, i.e., what inter-layer edges are present. If string, the parameter must be on of the policy types: ‘ordinal’, ‘categorical’, or ‘none’. None is same as ‘none’. Tuple can be used to give parameters to the coupling types, e.g. (‘categorical’,1.0) is categorical coupling with inter-edge weights equal to 1.0. If coupling is a network, it must be a monoplex one with the nodes corresponding to layer names. If a list is given, then the multiplex network will have aspects equal to the length of that list with each element corresponding to a coupling given as described above.

noEdgeobject

Any object signifying that there is no edge.

directedbool

True if the network is directed, otherwise it’s undirected.

fullyInterconnectedbool

Determines if the network is fully interconnected, i.e. all nodes are shared between all layers.

See also

MultilayerNetwork

A class for more general type of multilayer networks

Notes

The default implementation for this type of networks is ‘sequence of graphs’. That is, each intra-layer network is stored separately and accessing and modifying the intra-layer networks is independent of the other intra-layer networks. The couplings edges are not stored explicitly but they are only generated when needed.

Attributes:

edges

Methods

add_layer(layer[, aspect])	Adds node or a layer to given aspect in the network.
add_node(node[, layer])	Adds an empty node to the network.
get_layers([aspect])	Return the set of (elementary) layers (in a given aspect).
get_supra_adjacency_matrix([includeCouplings])	Return the supra-adjacency matrix and a list of node-layer pairs.
iter_layers([aspect])	Iterate over all layers.
iter_node_layers()	Iterate over all node-layer pairs.
iter_nodes([layer])	Iterate over nodes in the network.

__init__(couplings=None, directed=False, noEdge=0, fullyInterconnected=True)

Methods

__init__([couplings, directed, noEdge, ...])
add_layer(layer[, aspect])	Adds node or a layer to given aspect in the network.
add_node(node[, layer])	Adds an empty node to the network.
get_layers([aspect])	Return the set of (elementary) layers (in a given aspect).
get_supra_adjacency_matrix([includeCouplings])	Return the supra-adjacency matrix and a list of node-layer pairs.
iter_layers([aspect])	Iterate over all layers.
iter_node_layers()	Iterate over all node-layer pairs.
iter_nodes([layer])	Iterate over nodes in the network.

Attributes

edges