cdlib.viz.plot_scoring

cdlib.viz.plot_scoring(graphs: list, ref_partitions: object, graph_names: list, methods: list, scoring: ~typing.Callable[[object, object], object] = <function adjusted_mutual_information>, nbRuns: int = 5) → object

绘制一系列方法在一系列图表上获得的分数。

Parameters:

• graphs – 用于计算的图列表

• ref_partitions – 与图对应的参考聚类列表

• graph_names – 要显示的图表名称列表

• methods – 以图作为输入并返回聚类作为输出的函数列表

• scoring – 使用的评分函数，默认为anmi

• nbRuns – 每个方法在每个图上运行的次数

Returns:

一个 seaborn 线图

示例：

>>> from cdlib import algorithms, viz, evaluation
>>> import networkx as nx
>>> g1 = nx.algorithms.community.LFR_benchmark_graph(1000, 3, 1.5, 0.5, min_community=20, average_degree=5)
>>> g2 = nx.algorithms.community.LFR_benchmark_graph(1000, 3, 1.5, 0.7, min_community=20, average_degree=5)
>>> names = ["g1", "g2"]
>>> graphs = [g1, g2]
>>> for g in graphs:
>>>     references.append(NodeClustering(communities={frozenset(g.nodes[v]['community']) for v in g}, graph=g, method_name="reference"))
>>> algos = [algorithms.crisp_partition.louvain, algorithms.crisp_partition.label_propagation]
>>> viz.plot_scoring(graphs, references, names, algos, nbRuns=2)