当我尝试betweenness_centrality()
使用 julia 的 LightGraphs 包计算我的 SimpleWeightedGraph 时,它会无限期地运行。它不断增加它的 RAM 使用量,直到在某个时候它崩溃而没有错误消息。我的图表有问题吗?或者找到此问题原因的最佳方法是什么?
我的图表不是由 LightGraphs 生成的,而是由另一个库 FlashWeave 生成的。我不知道这是否重要...
未加权的 SimpleGraph 或我在 LightGraphs 中创建的加权图不会出现此问题...
using BenchmarkTools
using FlashWeave
using ParserCombinator
using GraphIO.GML
using LightGraphs
using SimpleWeightedGraphs
data_path = /path/to/my/data
netw_results = FlashWeave.learn_network(data_path,
sensitive = true,
heterogeneous = false)
dummy_weighted_graph = SimpleWeightedGraph(smallgraph(:house))
# {5, 6} undirected simple Int64 graph with Float64 weights
my_weighted_graph = graph(netw_results_no_meta)
# {6558, 8484} undirected simple Int64 graph with Float64 weights
# load_graph() only loads unweighted graphs
save_network(gml_no_meta_path, netw_results_no_meta)
my_unweighted_graph = loadgraph(gml_no_meta_path, GMLFormat())
# {6558, 8484} undirected simple Int64 graph
@time betweenness_centrality(my_unweighted_graph)
# 12.467820 seconds (45.30 M allocations: 7.531 GiB, 2.73% gc time)
@time betweenness_centrality(dummy_weighted_graph)
# 0.271050 seconds (282.41 k allocations: 13.838 MiB)
@time betweenness_centrality(my_weighted_graph)
# steadily increasing RAM usage until RAM is full and julia crashes.