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。
请您参考如下方法:
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
