从 CSV 文件中的邻接矩阵绘制 NetworkX 图

Question

我一直在与这个问题作斗争，我知道这很简单——但我对 Python 或 NetworkX 的经验很少。我的问题很简单，我正在尝试绘制一个看起来像这样的矩阵的大型数据集（大约 200 行/列）。第一行和第一列是相同的。

  A,B,C,D,E,F,G,H,I,J,K
A,0,1,1,0,1,1,1,1,0,1,0
B,1,0,0,0,1,1,1,1,0,1,0
C,1,0,0,0,1,1,1,1,0,1,0

它只是一个显示人们如何联系的矩阵，我只想导入并绘制这个 csv 文件，它在 NetworkX 中有相应的标签。

我有这个文件 (people.csv)，并查看以前的答案 here，似乎最好的方法是将数据放入带有 numpy 的数组中。

这似乎有问题：

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
from numpy import genfromtxt
import numpy as np

mydata = genfromtxt('mouse.csv', delimiter=',')

我得到以下输出：

File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/npyio.py", line 1272, in genfromtxt
  fhd = iter(np.lib._datasource.open(fname, 'rbU'))
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/_datasource.py", line 145, in open
  return ds.open(path, mode)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/_datasource.py", line 472, in open
  found = self._findfile(path)
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/_datasource.py", line 323, in _findfile
  if self.exists(name):
File "/System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/lib/_datasource.py", line 417, in exists
  from urllib2 import urlopen
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/urllib2.py", line 94, in <module>
  import httplib
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/httplib.py", line 69, in <module>
  from array import array
      File "/Users/Plosslab/Documents/PythonStuff/array.py", line 4, in <module>
      NameError: name 'array' is not defined

Answer 1

我制作了一个名为 mycsv.csv 的小型 csv，其中包含以下内容：

,a,b,c,d
a,0,1,0,1
b,1,0,1,0
c,0,1,0,1
d,1,0,1,0

您没有“，”作为第一行的第一个字符，而是有一个空格，所以如果这是我的错误，请告诉我。总体思路将是相同的。像这样读入csv：

from numpy import genfromtxt
import numpy as np
mydata = genfromtxt('mycsv.csv', delimiter=',')
print(mydata)
print(type(mydata))

打印出来：

[[ nan  nan  nan  nan  nan]
 [ nan   0.   1.   0.   1.]
 [ nan   1.   0.   1.   0.]
 [ nan   0.   1.   0.   1.]
 [ nan   1.   0.   1.   0.]]
<type 'numpy.ndarray'>

现在我们已经将 csv 作为 numpy 数组读入，我们只需要提取邻接矩阵：

adjacency = mydata[1:,1:]
print(adjacency)

打印出来：

[[ 0.  1.  0.  1.]
 [ 1.  0.  1.  0.]
 [ 0.  1.  0.  1.]
 [ 1.  0.  1.  0.]]

如果我的小示例与您的不完全一样，您可以根据需要对 numpy 数组进行切片。

要绘制图形，您需要导入 matplotlib 和 networkx：

import matplotlib.pyplot as plt
import networkx as nx

def show_graph_with_labels(adjacency_matrix, mylabels):
    rows, cols = np.where(adjacency_matrix == 1)
    edges = zip(rows.tolist(), cols.tolist())
    gr = nx.Graph()
    gr.add_edges_from(edges)
    nx.draw(gr, node_size=500, labels=mylabels, with_labels=True)
    plt.show()

show_graph_with_labels(adjacency, make_label_dict(get_labels('mycsv.csv')))

这里有一个简短的tutorial 用 python 绘制图表。

Answer 2

这可以通过使用pandas 和networkx 轻松完成。

例如，我创建了一个名为test.csv 的小csv 文件

A,B,C,D,E,F,G,H,I,J,K
A,0,1,1,0,1,1,1,1,0,1,0
B,1,0,0,0,1,1,1,1,0,1,0
C,1,0,0,0,1,1,1,1,0,1,0
D,0,0,0,0,1,0,1,1,0,1,0
E,1,0,0,0,1,1,1,1,0,1,0
F,0,0,1,0,1,0,0,0,0,1,0
G,1,0,0,0,0,0,0,1,0,0,0
H,1,0,0,0,1,1,1,0,0,1,0
I,0,0,0,1,0,0,0,0,0,0,0
J,1,0,0,0,1,1,1,1,0,1,0
K,1,0,0,0,1,0,1,0,0,1,0

您可以读取此 csv 文件并按如下方式创建图表

import pandas as pd
import networkx as nx
input_data = pd.read_csv('test.csv', index_col=0)
G = nx.DiGraph(input_data.values)

要绘制此图，请使用

nx.draw(G)

你会得到一个类似的情节。

Answer 3

这与Scott's excellent answer 相同，但可以正确处理没有边的节点。

import matplotlib.pyplot as plt
import networkx as nx

def show_graph_with_labels(adjacency_matrix, mylabels):
    rows, cols = np.where(adjacency_matrix == 1)
    edges = zip(rows.tolist(), cols.tolist())
    gr = nx.Graph()
    all_rows = range(0, adjacency_matrix.shape[0])
    for n in all_rows:
        gr.add_node(n)
    gr.add_edges_from(edges)
    nx.draw(gr, node_size=900, labels=mylabels, with_labels=True)
    plt.show()