导入csv矩阵以在networkx python中创建加权和定向网络[关闭](import csv matrix to create a weighted and directed network in networkx python [closed])

我是python和networkx的新手。 如何通过导入csv格式的权重邻接矩阵来创建定向和加权网络（参见下面的2 * 2示例）？

3.4, 1.2, 0.8, 1.3,

提前致谢。

I am new to python and networkx. How can I create a directed and weighted network by importing a weights adjacency matrix in csv format (see below for a 2*2 example)?

3.4, 1.2, 0.8, 1.3,

Thanks in advance.

最满意答案

至少有两个选项：您可以使用numpy.loadtxt这样的文件直接读入numpy数组。 也许这就是您所需要的全部，因为您可能希望使用矩阵对其执行线性代数运算。

如果您需要定向网络，则只需使用networkx.from_numpy_matrix从中初始化图形：

adj_mat = numpy.loadtxt(filename) net = networkx.from_numpy_matrix(adj_mat, create_using=networkx.DiGraph())

net.edges(data=True)

[(0, 0, {'weight': 3.4}), (0, 1, {'weight': 1.2}), (1, 0, {'weight': 0.8}), (1, 1, {'weight': 1.3})]

There are at least two options: You can read such a file directly into a numpy array using numpy.loadtxt. Maybe that is all you need since you might want to use the matrix to perform linear algebra operations on it.

If you need a directed network you can then simply initialize a graph from it with networkx.from_numpy_matrix:

adj_mat = numpy.loadtxt(filename) net = networkx.from_numpy_matrix(adj_mat, create_using=networkx.DiGraph())

net.edges(data=True)

[(0, 0, {'weight': 3.4}), (0, 1, {'weight': 1.2}), (1, 0, {'weight': 0.8}), (1, 1, {'weight': 1.3})]

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