这应该很简单,但我无法弄清楚。我只需要
我可以单独执行这些操作,但我不知道如何从导入的矩阵转到networkx模块中的图形对象。如果我能够转换为networkx图,那么我可以创建一个edgelist并写入文件。
要读入的矩阵示例(保存在.txt文件中)
1 0 1 0 1
1 0 1 0 0
1 0 1 0 1
0 0 1 0 0
1 1 1 1 0
1 1 1 0 1
1 0 1 0 0
答案 0 :(得分:4)
这使用numpy读取矩阵并将邻接数据转换为边缘列表。然后它创建一个networkx图,并绘制一个图。
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
# Load the adjacency matrix into a numpy array.
a = np.loadtxt('matrix.txt', dtype=int)
print "a:"
print a
num_nodes = a.shape[0] + a.shape[1]
# Get the row and column coordinates where the array is 1.
rows, cols = np.where(a == 1)
# We label the nodes corresponding to the rows with integers from 0 to
# a.shape[0]-1, and we label the nodes corresponding to the columns with
# integers from a.shape[0] to a.shape[0] + a.shape[1] - 1.
# Rearranges the list of rows and columns into a list of edge tuples.
edges = zip(rows.tolist(), (cols + a.shape[0]).tolist())
print "U nodes:", np.arange(a.shape[0])
print "V nodes:", np.arange(a.shape[1]) + a.shape[0]
print "edges"
print edges
# Create a Graph object (from the networkx library).
b = nx.Graph()
b.add_nodes_from(range(num_nodes)) # This line not strictly necessry.
b.add_edges_from(edges)
# Draw the graph. First create positions for each node. Put the U nodes
# on the left (x=1) and the V nodes on the right (x=2).
pos = dict([(k, (1, k - 0.5 * a.shape[0]))
for k in range(a.shape[0])])
pos.update(dict([(k + a.shape[0], (2, k - 0.5 * a.shape[1]))
for k in range(a.shape[1])]))
nx.draw_networkx(b, pos=pos, node_color=(['c'] * a.shape[0]) + (['y'] * a.shape[1]))
plt.axis('off')
plt.show()
输出:
a:
[[1 0 1 0 1]
[1 0 1 0 0]
[1 0 1 0 1]
[0 0 1 0 0]
[1 1 1 1 0]
[1 1 1 0 1]
[1 0 1 0 0]]
U nodes: [0 1 2 3 4 5 6]
V nodes: [ 7 8 9 10 11]
edges:
[(0, 7), (0, 9), (0, 11), (1, 7), (1, 9), (2, 7), (2, 9), (2, 11), (3, 9), (4, 7), (4, 8), (4, 9), (4, 10), (5, 7), (5, 8), (5, 9), (5, 11), (6, 7), (6, 9)]
情节:
答案 1 :(得分:3)
您不需要将NetworkX转换为简单的边缘列表:
adj = """1 0 1 0 1
1 0 1 0 0
1 0 1 0 1
0 0 1 0 0
1 1 1 1 0
1 1 1 0 1
1 0 1 0 0"""
for row,line in enumerate(adj.split('\n')):
for col,val in enumerate(line.split(' ')):
if val == '1':
print row,col
答案 2 :(得分:1)
import numpy as np
#read matrix without head.
a = np.loadtxt('admatrix.txt', delimiter=',', dtype=int) #set the delimiter as you need
print "a:"
print a
print 'shape:',a.shape[0] ,"*", a.shape[1]
num_nodes = a.shape[0] + a.shape[1]
num_edge = 0
edgeSet = set()
for row in range(a.shape[0]):
for column in range(a.shape[1]):
if a.item(row,column) == 1 and (column,row) not in edgeSet: #get rid of repeat edge
num_edge += 1
edgeSet.add((row,column))
print '\nnum_edge:', num_edge
print 'edge Set:', edgeSet
print ''
for edge in edgeSet:
print edge[0] , edge[1]
此代码将读取以逗号分隔的邻接矩阵文件,并输出带有打印的边列表。
例如,adj-matrix.txt是:
0, 1, 0, 1
1, 0, 1, 0
0, 1, 0, 0
1, 0, 0, 0
edgelist的输出将是:
0 1
0 3
1 2
答案 3 :(得分:0)
对于阅读文件,您需要python的fp = open('\path\to\filename.txt')
docs.python.org great information如何做到这一点,并且在您第一次学习时通常是搜索答案的好地方。
您可以查看边缘列表的networkx包。他们有examples如何做到这一点。如果您已安装setuptools,则可以使用easy_install networkx