核心分解

此笔记本演示了图的 \(k\)-核心分解。

[1]:

from IPython.display import SVG

[2]:

import numpy as np

[3]:

from sknetwork.data import karate_club, painters
from sknetwork.topology import get_core_decomposition
from sknetwork.visualization import visualize_graph
from sknetwork.utils import directed2undirected

图

[4]:

graph = karate_club(metadata=True)
adjacency = graph.adjacency
position = graph.position

[5]:

values = get_core_decomposition(adjacency)

[6]:

image = visualize_graph(adjacency, position, scores=values)
SVG(image)

[6]:

../../_images/tutorials_topology_core_decomposition_8_0.svg

有向图

[7]:

graph = painters(metadata=True)
adjacency = graph.adjacency
names = graph.names
position = graph.position

[8]:

values = get_core_decomposition(directed2undirected(adjacency))

[9]:

image = visualize_graph(adjacency, position, names, scores=values)
SVG(image)

[9]:

../../_images/tutorials_topology_core_decomposition_12_0.svg