julia - 在Julia中生成加权有向网络形式邻接矩阵

Question

我想根据Julia(v0.7)中的邻接矩阵生成加权和定向网络。

到目前为止，我已经尝试过:

using LightGraphs
using SimpleWeightedGraphs

A = rand(100, 100)
G = Graph(A)

但我得到错误:

ERROR: ArgumentError: Adjacency / distance matrices must be symmetric
Stacktrace:
 [1] SimpleGraph{Int64}(::Array{Float64,2}) at /home/user/.julia/packages/LightGraphs/PPsyP/src/SimpleGraphs/simplegraph.jl:78
 [2] SimpleGraph(::Array{Float64,2}) at /home/user/.julia/packages/LightGraphs/PPsyP/src/SimpleGraphs/simplegraph.jl:72
 [3] top-level scope at none:0

到目前为止，我只在github( https://github.com/JuliaGraphs/SimpleWeightedGraphs.jl)页面上看到了该示例，该示例从and edgelist生成加权图。但是，如果我可以直接从邻接矩阵生成图，则更希望。

Answer 1

根据crstnbr的答案，Graph是无权的无向的，因此理想情况下，邻接矩阵与[0, 1]中的值对称。
将任何对称矩阵馈给Graph构造函数，会为每个非零元素创建边:

A = rand(3,3);
Graph(A+A');
println.(edges(G));
 Edge 1 => 1
 Edge 1 => 2
 Edge 1 => 3
 Edge 2 => 2
 Edge 2 => 3
 Edge 3 => 3

SimpleWeightedDiGraph具有多个构造函数，这些构造函数可以采用密集或 SparseMatrixCSC邻接矩阵:

SimpleWeightedDiGraph(rand(4,4))
 {4, 16} directed simple Int64 graph with Float64 weights

SimpleWeightedDiGraph(rand([0,1], 3, 3))
 {3, 5} directed simple Int64 graph with Int64 weights

using SparseArrays
SimpleWeightedDiGraph( sprand(3, 3, 0.5) )
 {3, 5} directed simple Int64 graph with Float64 weights