__init__(self, incoming_graph_data=None, multigraph_input=None, **attr)
Data to initialize graph. If incoming_graph_data=None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python packages are installed the data can also be a 2D NumPy array, a SciPy sparse matrix, or a PyGraphviz graph.
Note: Only used when :None:None:`incoming_graph_data` is a dict. If True, :None:None:`incoming_graph_data` is assumed to be a dict-of-dict-of-dict-of-dict structure keyed by node to neighbor to edge keys to edge data for multi-edges. A NetworkXError is raised if this is not the case. If False, to_networkx_graph
is used to try to determine the dict's graph data structure as either a dict-of-dict-of-dict keyed by node to neighbor to edge data, or a dict-of-iterable keyed by node to neighbors. If None, the treatment for True is tried, but if it fails, the treatment for False is tried.
Attributes to add to graph as key=value pairs.
Initialize a graph with edges, name, or graph attributes.
>>> G = nx.Graph() # or DiGraph, MultiGraph, MultiDiGraph, etc
... G = nx.Graph(name="my graph")
... e = [(1, 2), (2, 3), (3, 4)] # list of edges
... G = nx.Graph(e)
Arbitrary graph attribute pairs (key=value) may be assigned
>>> G = nx.Graph(e, day="Friday")See :
... G.graph {'day': 'Friday'}
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them