最佳的方式來可視化地表示這種算法？

Question

只是想知道什麼是可視化表示這個算法程序的最佳方式？如果可能的話，我們希望直觀地表示最短路徑和通過路由器的數據包？有任何想法嗎？看着烏龜，我們似乎可以達到我們想要的。任何指針歡迎。謝謝。

嘗試在視覺上表示此：顯示加權（數值）節點組之間的最短路徑。

from heapq import heappush, heappop # for priority queue 
pq = [] 

class node: 
    label = '' 
    # adjacency list of the node 
    neighbors = [] # list of nodes 
    distances = [] # distances to neighbors 
    # for Dijkstra 
    prevNode = None 
    totalDistance = float('Inf') 
    visited = False 
    # constructor 
    def __init__(self, label): 
     self.label = label 
     self.neighbors = [] 
     self.distances = [] 
     self.prevNode = None 
     self.totalDistance = float('Inf') 
     self.visited = False 


# find the shortest paths to all nodes recursively 
def dijkstra(node): 
    # visit all neighbors and update them if necessary 
    for i in range(len(node.neighbors)): 
     n = node.neighbors[i] 
     d = node.distances[i] 
     if n.totalDistance > d + node.totalDistance: 
      n.prevNode = node 
      n.totalDistance = d + node.totalDistance 
      heappush(pq, (n.totalDistance, n)) 
    node.visited = True 

    (d, ne) = heappop(pq) 
    if not ne.visited: 
     dijkstra(ne) 

# get the shortest path to the given node 
def route(endNode): 
    node = endNode 
    labels = [endNode.label] 
    # distances = [] 
    while node.label != node.prevNode.label: 
     # distances.append(node.totalDistance - node.prevNode.totalDistance) 
     node = node.prevNode 
     labels.append(node.label) 
    labels.reverse() 
    return labels 
    # distances.reverse() 
    # return (labels, distances) 

# create a graph 
a = node('a') 
b = node('b') 
c = node('c') 
d = node('d') 
e = node('e') 
f = node('f') 
g = node('g') 
graph = (a, b, c, d, e, f, g) 

# create bidirectional edges of the graph 
edges = [] 
edges.append((b, c, 3)) 
edges.append((d, e, 1)) 
edges.append((b, d, 2)) 
edges.append((c, e, 1)) 
edges.append((a, b, 1)) 
edges.append((a, d, 1)) 
edges.append((c, f, 1)) 
edges.append((e, f, 3)) 
edges.append((e, g, 1)) 

# create adjaceny list of neighbors for each node 
for edge in edges: 
    edge[0].neighbors.append(edge[1]) 
    edge[0].distances.append(edge[2]) 
    edge[1].neighbors.append(edge[0]) 
    edge[1].distances.append(edge[2]) 

# print the graph 
print 'The graph:' 
print 
for n in graph: 
    print 'Node: ', n.label 
    print 'Neighbors:' 
    for i in range(len(n.neighbors)): 
     print n.neighbors[i].label, n.distances[i] 
    print 

# find the shortest paths to all neighbors starting w/ the given node 
startNode = a 
print 'Route start node:', startNode.label 
startNode.prevNode = startNode 
startNode.totalDistance = 0 
dijkstra(startNode) 

##print 
##print 'The graph after Dijkstra:' 
##print 
##for n in graph: 
## print 'Node:', n.label 
## print 'totalDistance:', n.totalDistance 
## print 'prevNode:', n.prevNode.label 
## print 

# print the shortest path to the given node 
endNode = f 
print 'Route end node:', endNode.label 
print 'Route:', route(endNode) 
print 'Total distance:', endNode.totalDistance 

Answer 1

使用pydot，並選擇不同的樣式選擇邊緣。

Answer 2

顯示所有節點之間的距離與它們之間的路徑權重成比例的距離。然後用有向線連接每一對是最短路徑的一部分。

您可以使用networkx和graphvis在Python中創建這樣的圖表。