cdlib.viz.plot_event_radar

cdlib.viz.plot_event_radar(lc: LifeCycle, set_name: str, direction: str, min_branch_size: int = 1, rescale: bool = True, color: str = 'green', ax: object | None = None)

绘制给定事件集的事件权重雷达图。

Parameters:

• lc – 生命周期对象

• set_name – 事件集名称，例如“0_2”

• direction – 事件集的方向，可以是“+”或“-”

• min_branch_size – 被视为分支的最小大小，默认为1

• rescale – 将雷达重新缩放到最大值，默认为 True

• color – 雷达的颜色，默认为“green”

• ax – matplotlib轴，默认为None

Returns:

matplotlib 轴

Example:

>>> from cdlib import TemporalClustering, LifeCycle
>>> from cdlib import algorithms
>>> from cdlib.viz import plot_flow
>>> from networkx.generators.community import LFR_benchmark_graph
>>> tc = TemporalClustering()
>>> for t in range(0, 10):
>>>     g = LFR_benchmark_graph(
>>>         n=250,
>>>         tau1=3,
>>>         tau2=1.5,
>>>         mu=0.1,
>>>         average_degree=5,
>>>         min_community=20,
>>>         seed=10,
>>>     )
>>>     coms = algorithms.louvain(g)  # here any CDlib algorithm can be applied
>>>     tc.add_clustering(coms, t)
>>> events = LifeCycle(tc)
>>> events.compute_events("facets")
>>> fig = plot_event_radar(events, "0_2", "+")
>>> fig.show()