reskit.features¶
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reskit.features.bag_of_edges(X, SPL=None, symmetric=True, return_df=False, offset=1)[source]¶ Bag of edges graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: bag_of_edges : numpy array
Bag of edges for the graph.
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reskit.features.closeness_centrality(X)[source]¶ Closeness centrality graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: cl_c : numpy array
Closeness centralities of nodes for the graph.
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reskit.features.betweenness_centrality(X)[source]¶ Betweenness centrality graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: btw : numpy array
Betweenness centralities of nodes for the graph.
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reskit.features.eigenvector_centrality(X)[source]¶ Eigenvector centrality graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: eigc : numpy array
Eigenvector centralities of nodes for the graph.
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reskit.features.pagerank(X)[source]¶ Pagerank graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: pgrnk : numpy array
Pagerank vector for the graph.
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reskit.features.degrees(X)[source]¶ Degree graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: degrees : numpy array
Degrees of nodes for the graph.
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reskit.features.clustering_coefficient(X)[source]¶ Clustering coefficient graph metric.
Parameters: X : numpy matrix
Adjacency matrix of a graph.
Returns: clst_geommean : numpy array
Clustering coefficients of nodes for the graph.