retworkx.spring_layout¶
- spring_layout(graph, pos=None, fixed=None, k=None, repulsive_exponent=2, adaptive_cooling=True, num_iter=50, tol=1e-06, weight_fn=None, default_weight=1, scale=1, center=None, seed=None)[source]¶
- spring_layout(graph: retworkx.PyDiGraph, pos=None, fixed=None, k=None, repulsive_exponent=2, adaptive_cooling=True, num_iter=50, tol=1e-06, weight_fn=None, default_weight=1, scale=1, center=None, seed=None)
- spring_layout(graph: retworkx.PyGraph, pos=None, fixed=None, k=None, repulsive_exponent=2, adaptive_cooling=True, num_iter=50, tol=1e-06, weight_fn=None, default_weight=1, scale=1, center=None, seed=None)
Position nodes using Fruchterman-Reingold force-directed algorithm.
The algorithm simulates a force-directed representation of the network treating edges as springs holding nodes close, while treating nodes as repelling objects, sometimes called an anti-gravity force. Simulation continues until the positions are close to an equilibrium.
- Parameters
graph – Graph to be used. Can either be a
PyGraph
orPyDiGraph
.pos (dict) – Initial node positions as a dictionary with node ids as keys and values as a coordinate list. If
None
, then use random initial positions. (default=None
)fixed (set) – Nodes to keep fixed at initial position. Error raised if fixed specified and
pos
is not. (default=None
)k (float) – Optimal distance between nodes. If
None
the distance is set to \(\frac{1}{\sqrt{n}}\) where \(n\) is the number of nodes. Increase this value to move nodes farther apart. (default=None
)repulsive_exponent (int) – Repulsive force exponent. (
default=2
)adaptive_cooling (bool) – Use an adaptive cooling scheme. If set to
False
, a linear cooling scheme is used. (default=True
)num_iter (int) – Maximum number of iterations. (
default=50
)tol (float) – Threshold for relative error in node position changes. The iteration stops if the error is below this threshold. (
default = 1e-6
)weight_fn – An optional weight function for an edge. It will accept a single argument, the edge’s weight object and will return a float which will be used to represent the weight of the edge.
default_weight (float (default=1)) – If
weight_fn
isn’t specified this optional float value will be used for the weight/cost of each edgescale (float|None) – Scale factor for positions. Not used unless fixed is None. If scale is
None
, no re-scaling is performed. (default=1.0
)center (list) – Coordinate pair around which to center the layout. Not used unless fixed is
None
. (default=None
)seed (int) – An optional seed to use for the random number generator
- Returns
A dictionary of positions keyed by node id.
- Return type
dict