bigraph package
Subpackages
Submodules
bigraph.algorithms module
- class bigraph.algorithms.Algorithms
Bases:
object
- static adamic_adar(set_one: list, set_two: list, graph) float
Calculate Adamic Adar score for input lists
- Parameters
set_one – A list of graph nodes -> part one
set_two – A list of graph nodes -> part two
graph – NetworkX bipartite graph
- Returns
Adamic Adar score
- static common_neighbors(set_one: list, set_two: list) int
Calculate Common neighbors score for input lists
- Parameters
set_one – A list of graph nodes -> part one
set_two – A list of graph nodes -> part two
- Returns
Common neighbours score
- static jaccard(set_one: list, set_two: list) float
Calculate Jaccard score for input lists
- Parameters
set_one – A list of graph nodes -> part one
set_two – A list of graph nodes -> part two
- Returns
Jaccard score
- static katz_similarity(node_i: int, node_j: int, graph) float
Calculate Katz score for input nodes
- Parameters
node_i – Starting node
node_j – Destination node
graph – NetworkX bipartite graph
- Returns
Katz similarity score
- static preferential_attachment(set_one: list, set_two: list) int
Calculate Preferential attachment score for input lists
- Parameters
set_one – A list of graph nodes -> part one
set_two – A list of graph nodes -> part two
- Returns
Preferential attachment score
bigraph.bigraph module
- class bigraph.bigraph.BiGraph
Bases:
bigraph.algorithms.Algorithms
,bigraph.preprocessing.import_files.ImportFiles
,bigraph.preprocessing.make_graph.MakeGraph
,bigraph.preprocessing.get_adjacents.GetAdjacents
- aa_predict() dict
Compute the Jaccard-Needham dissimilarity between two 1-D arrays.
- Returns
A dictionary containing the Adamic-adar score for left_element and right_element.
- cn_predict() dict
Return the common neighbors of two nodes in a graph.
- Returns
A dictionary containing the Common neighbours score for left_element and right_element.
- jc_predict() dict
Compute the Jaccard-Needham dissimilarity between two 1-D arrays.
- Returns
A dictionary containing the Jaccard distance between vectors left_element and right_element.
- katz_predict(df_nodes: dict) dict
Compute the Katz similarity score of all node pairs.
- Parameters
df_nodes – Graph nodes
- Returns
A dictionary containing the Preferential attachment score for left_element and right_element.
- pa_predict() dict
Compute the preferential attachment score of all node pairs.
- Returns
A dictionary containing the Preferential attachment score for left_element and right_element.
Module contents
A package for link prediction in bipartite networks.
- class bigraph.BiGraph
Bases:
bigraph.algorithms.Algorithms
,bigraph.preprocessing.import_files.ImportFiles
,bigraph.preprocessing.make_graph.MakeGraph
,bigraph.preprocessing.get_adjacents.GetAdjacents
- aa_predict() dict
Compute the Jaccard-Needham dissimilarity between two 1-D arrays.
- Returns
A dictionary containing the Adamic-adar score for left_element and right_element.
- cn_predict() dict
Return the common neighbors of two nodes in a graph.
- Returns
A dictionary containing the Common neighbours score for left_element and right_element.
- jc_predict() dict
Compute the Jaccard-Needham dissimilarity between two 1-D arrays.
- Returns
A dictionary containing the Jaccard distance between vectors left_element and right_element.
- katz_predict(df_nodes: dict) dict
Compute the Katz similarity score of all node pairs.
- Parameters
df_nodes – Graph nodes
- Returns
A dictionary containing the Preferential attachment score for left_element and right_element.
- pa_predict() dict
Compute the preferential attachment score of all node pairs.
- Returns
A dictionary containing the Preferential attachment score for left_element and right_element.