metrics

class PathLengthsMethods(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: str, Enum

BellmanFord = ‘bellman-ford’

Dijkstra = ‘dijkstra’

FloydWarshall = ‘floyd-warshall’

FloydWarshallNumpy = ‘floyd-warshall-numpy’

betweennesscentrality(graph, weight=None)

betweennesscentrality: GRAPH WEIGHT

Will return a dictionary of the betweenness centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the betweenness centrality for all nodes.

closenesscentrality(graph, weight=None)

closenesscentrality: GRAPH WEIGHT

Will return a dictionary of the closeness centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the closeness centrality for all nodes.

closenessvitality(graph, nodes, weight=None)

closenessvitality: GRAPH NODE WEIGHT

Will return a dictionary of the closeness vitality for a single node.

Parameters

graph : Networkx graph object.

nodes : Node to compute the closeness vitality for.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the closeness vitality for a single node.

clustering(graph, weight=None)

clustering: GRAPH WEIGHT

Will return a dictionary of the clustering coefficient for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the clustering coefficient for all nodes.

constraint(graph, nodes, weight=None)

constraint: GRAPH NODES WEIGHT

Will return a dictionary of the constraint for all specified nodes.

Parameters

graph : Networkx graph object.

nodes : Nodes to compute the constraint for.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the constraint for all specified nodes.

currentflowbc(graph, weight=None)

currentflowbc: GRAPH WEIGHT

Will return a dictionary of the current flow betweenness centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the current flow betweenness centrality for all nodes.

degree(graph, weight=None)

degree: GRAPH WEIGHT

Will return the degree of the specified node.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the degree for all nodes.

eccentricity(graph, weight=None)

eccentricity: GRAPH WEIGHT

Will return a dictionary of the eccentricity for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the eccentricity for all nodes.

effectivesize(graph, nodes, weight=None)

effectivesize: GRAPH NODES WEIGHT

Will return a dictionary of the effective size for all specified nodes.

Parameters

graph : Networkx graph object.

nodes : Nodes to compute the effective size for.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the effective size for all specified nodes.

eigencentrality(graph, weight=None)

eigencentrality: GRAPH WEIGHT

Will return a dictionary of the eigenvector centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the eigenvector centrality for all nodes.

get_metrics_ops()

Get a dictionary of all functions related to graph network metrics.

Returns

dict : Dictionary of functions.

harmoniccentrality(graph, weight=None)

harmoniccentrality: GRAPH WEIGHT

Will return a dictionary of the harmonic centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the harmonic centrality for all nodes.

informationcentrality(graph, weight=None)

informationcentrality: GRAPH WEIGHT

Will return a dictionary of the information centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the information centrality for all nodes.

loadcentrality(graph, weight=None)

loadcentrality: GRAPH WEIGHT

Will return a dictionary of the load centrality for all nodes.

Parameters

graph : Networkx graph object.

weight : Edge attributes to use as weight. Defaults to None.

Returns

dict : Dictionary of the load centrality for all nodes.

weightedpath(graph, df, label_name, cohort=None, iterations=1000, weight=None, method=‘dijkstra’, distribution=None, processes=1, verbose=False)

Function to compute the average weighted shortest path length for a group of nodes. The function will also compute the p-value between the group of nodes and the randomly generated null distribution.

Parameters

graph : Networkx graph object.

df : Dataframe containing the nodes.

label_name : Name of the column containing the group label.

cohort : Name of the cohort. Defaults to None.

iterations : Number of iterations to run. Defaults to 1000.

weight : Edge attributes to use as weight. Defaults to None.

method : Method to use for path computation. Defaults to “dijkstra”.

distribution : Pre-computed distribution. Defaults to None.

processes : Number of processes to use. Defaults to 1.

verbose : Verbose flag. Defaults to False.

Returns

avg_path_length : Average path length.

dist : Null distribution.

pvalue : P-value.