12.4.5. networkx.drawing.layout.spring_layout¶

networkx.drawing.layout.spring_layout(G, k=None, pos=None, fixed=None, iterations=50, weight='weight', scale=1.0, center=None, dim=2)¶

Position nodes using Fruchterman-Reingold force-directed algorithm.

Parameters:

G : NetworkX graph or list of nodes k : float (default=None) Optimal distance between nodes. If None the distance is set to 1/sqrt(n) where n is the number of nodes. Increase this value to move nodes farther apart. pos : dict or None optional (default=None) Initial positions for nodes as a dictionary with node as keys and values as a coordinate list or tuple. If None, then use random initial positions. fixed : list or None optional (default=None) Nodes to keep fixed at initial position. iterations : int optional (default=50) Number of iterations of spring-force relaxation weight : string or None optional (default=’weight’) The edge attribute that holds the numerical value used for the edge weight. If None, then all edge weights are 1. scale : float (default=1.0) Scale factor for positions. The nodes are positioned in a box of size [0, scale] x [0, scale]. center : array-like or None Coordinate pair around which to center the layout. dim : int Dimension of layout

Returns:

pos : dict A dictionary of positions keyed by node

Examples

>>> G = nx.path_graph(4)
>>> pos = nx.spring_layout(G)

# The same using longer but equivalent function name >>> pos = nx.fruchterman_reingold_layout(G)