paramnet 0.1

NetworkX graphs with required node/edge parameters

paramgraph provides a convenience mixin, Parametrized, for creating subclasses of NetworkX’s Graph (DiGraph) that have expected parameters associated with each node and/or edge (e.g., in a network dynamical system). It enforces the existence of specified named attributes for the (Di)Graph’s nodes/edges, and also maintains a well-defined order for the nodes. This allows the user to extract a given node (edge) parameters as a well-defined vector (matrix).

Examples

A parametrized network class can be created by subclassing from Graph or DiGraph using the Parametrized mixin and specifying the names of the node/edge parameters in the class definition:

class MyGraph(Parametrized, Graph):
    _node_params = ['x']
    _edge_params = ['weight']

G = MyGraph()

As with all mixins, Parametrized should be inherited from first as above. Any instance of this class will require all corresponding attributes to be defined for each new node or edge, meaning the following will raise exceptions:

G.add_node(0)

G.add_edge(0, 1)

Because Parametrize maintains the order of nodes, one can get a numpy ndarray corresponding to the value of a given parameter for all nodes (edges)

G.add_node("a", x=1)
G.add_node("b", x=2)

G.add_edge("a", "b", weight=10)

# returns [1, 2]
G.node_param_vector('x')

# returns [[0, 10],
#          [10, 0]]
G.edge_param_matrix('weight')

For convenience, the weighted adjacency matrix can also be accessed through the property .A

# equivalent to G.edge_param_matrix('weight')
G.A

Dependencies

• NetworkX (>= 2.0)

• indexed.py

• scipy

License

paramnet is released under the MIT license. See LICENSE for details.