請幫助我更改可視化 Louvain 聚類算法的結果。我從網站 https://github.com/taynaud/python-louvain獲取代碼 我可以重寫代碼以便每個集群都有自己的形狀（圓形、三角形、正方形……）嗎？import community as community_louvainimport matplotlib.cm as cmimport matplotlib.pyplot as pltimport networkx as nx# load the karate club graphG = nx.karate_club_graph()# compute the best partitionpartition = community_louvain.best_partition(G)# draw the graphpos = nx.spring_layout(G)# color the nodes according to their partitioncmap = cm.get_cmap('viridis', max(partition.values()) + 1)nx.draw_networkx_nodes(G, pos, partition.keys(), node_size=40, cmap=cmap, node_color=list(partition.values()))nx.draw_networkx_edges(G, pos, alpha=0.5)plt.show()
1 回答
MM們
TA貢獻1886條經驗 獲得超2個贊
不幸的nx.draw_networkx_nodes是不接受可迭代的形狀，因此您必須遍歷節點并單獨繪制它們。此外，我們必須索引生成的cmap，否則，單值社區值將映射到相同的初始 cmap 顏色。對于可能的形狀，我只是復制文檔中提到的可用形狀的字符串，并根據分區號對其進行索引：
# load the karate club graph
G = nx.karate_club_graph()
# compute the best partition
partition = community_louvain.best_partition(G)
cmap = cm.get_cmap('viridis', max(partition.values()) + 1)
shapes = 'so^>v<dph8'
plt.figure(figsize=(12,8))
# draw the graph
pos = nx.spring_layout(G)
# color the nodes according to their partition
cmap = cm.get_cmap('viridis', max(partition.values()) + 1)
nx.draw_networkx_edges(G, pos, alpha=0.5)
for node, color in partition.items():
nx.draw_networkx_nodes(G, pos, [node], node_size=100,
node_color=[cmap.colors[color]],
node_shape=shapes[color])
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