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python - 使用 Python 库生成有向图 任何 python 库

转载 作者:太空宇宙 更新时间:2023-11-04 02:15:47 24 4
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我正在用 Python 实现来自 GeeksForGeeks 的 Bellman ford 算法。我想使用一些库(如 pyplot 或 networkx 或类似的东西)生成图表(图表形式而不是字典类型 - 这很容易)。我希望图形 UI 包含节点、边和相应的成本。

from collections import defaultdict 

#Class to represent a graph
class Graph:

def __init__(self,vertices):
self.V= vertices #No. of vertices
self.graph = [] # default dictionary to store graph

# function to add an edge to graph
def addEdge(self,u,v,w):
self.graph.append([u, v, w])

# utility function used to print the solution
def printArr(self, dist):
print("Vertex Distance from Source")
for i in range(self.V):
print("%d \t\t %d" % (i, dist[i]))

# The main function that finds shortest distances from src to
# all other vertices using Bellman-Ford algorithm. The function
# also detects negative weight cycle
def BellmanFord(self, src):

# Step 1: Initialize distances from src to all other vertices
# as INFINITE
dist = [float("Inf")] * self.V
dist[src] = 0


# Step 2: Relax all edges |V| - 1 times. A simple shortest
# path from src to any other vertex can have at-most |V| - 1
# edges
for i in range(self.V - 1):
# Update dist value and parent index of the adjacent vertices of
# the picked vertex. Consider only those vertices which are still in
# queue
for u, v, w in self.graph:
if dist[u] != float("Inf") and dist[u] + w < dist[v]:
dist[v] = dist[u] + w

# Step 3: check for negative-weight cycles. The above step
# guarantees shortest distances if graph doesn't contain
# negative weight cycle. If we get a shorter path, then there
# is a cycle.

for u, v, w in self.graph:
if dist[u] != float("Inf") and dist[u] + w < dist[v]:
print "Graph contains negative weight cycle"
return

# print all distance
self.printArr(dist)

g = Graph(5)
g.addEdge(0, 1, -1)
g.addEdge(0, 2, 4)
g.addEdge(1, 2, 3)
g.addEdge(1, 3, 2)
g.addEdge(1, 4, 2)
g.addEdge(3, 2, 5)
g.addEdge(3, 1, 1)
g.addEdge(4, 3, -3)

我想要在终端或单独文件中的图形是(基于上面的代码):

enter image description here

最佳答案

ekiim 的文档链接非常有用。这是我为绘制图形所做的代码:

import networkx as nx  
import matplotlib.pyplot as plt
G=nx.DiGraph()
G.add_node(0),G.add_node(1),G.add_node(2),G.add_node(3),G.add_node(4)
G.add_edge(0, 1),G.add_edge(1, 2),G.add_edge(0, 2),G.add_edge(1, 4),G.add_edge(1, 3),G.add_edge(3, 2),G.add_edge(3,1),G.add_edge(4,3)
nx.draw(G, with_labels=True, font_weight='bold')
plt.show()

此代码免费打印有向图。我尝试按成本打印,但输出结果因成本困惑而严重失真。一些成本写在空白处,而边缘只有一两个。因此,如果有人知道实现它,那将非常有用。

关于python - 使用 Python 库生成有向图 任何 python 库,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/52706635/

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