function Dijkstra(G, w, s)for each vertex v in V[G]         # 初始化d[v] := infinity             # 將各點的已知最短距離先設成無窮大previous[v] := undefined     # 各点的已知最短路径上的前趋都未知d[s] := 0                         # 因为出发点到出发点间不需移动任何距离，所以可以直接将s到s的最小距离设为0S := empty setQ := set of all verticeswhile Q is not an empty set       # Dijkstra演算法主體u := Extract_Min(Q)S.append(u)for each edge outgoing from u as (u,v)if d[v] > d[u] + w(u,v)       # 拓展边（u,v）。w(u,v)为从u到v的路径长度。d[v] := d[u] + w(u,v)   # 更新路径长度到更小的那个和值。previous[v] := u        # 紀錄前趨頂點

import sys
class Graph():def __init__(self, vertices):self.V = verticesself.graph = [[0 for _ in range(self.V)] for _ in range(self.V)]# 打印距离def print_distance(self, dist, parent):for node in range(self.V):print('distance')print(node, dist[node])print('path')self.print_path(parent, node)print('---------')# 打印路径def print_path(self, parent, j):if parent[j] == -1:print(j)returnself.print_path(parent, parent[j])print(j)# 找出最小距离的结点def min_distance(self, dist, sptSet):min_val = sys.maxsizemin_index = 0for v in range(self.V):if dist[v] < min_val and not sptSet[v]:min_val = dist[v]min_index = vreturn min_index# 核心算法def dijkstra(self, src):dist = [sys.maxsize] * self.Vdist[src] = 0sptSet = [False] * self.Vparent = [-1] * self.Vfor count in range(self.V):# 找出前驱结点u = self.min_distance(dist, sptSet)sptSet[u] = True# 如果某个节点的路径大于经过前驱结点的路径，则更新结果成经过前驱结点的路径for v in range(self.V):if self.graph[u][v] > 0 and not sptSet[v] and dist[v] > dist[u] + self.graph[u][v]:dist[v] = dist[u] + self.graph[u][v]parent[v] = uself.print_distance(dist, parent)
g = Graph(8)
g.graph = [[0, 0, 7, 7, 2, 0, 0, 0],[0, 0, 3, 8, 0, 0, 8, 0],[7, 3, 0, 0, 0, 7, 0, 0],[7, 8, 0, 0, 0, 0, 0, 0],[2, 0, 0, 0, 0, 0, 0, 8],[0, 0, 7, 0, 0, 0, 8, 0],[0, 8, 0, 0, 0, 8, 0, 6],[0, 0, 0, 0, 8, 0, 6, 0]]
g.dijkstra(0)

import copy
INF = 1e9
class Graph():def __init__(self, graph):self.V = len(graph)self.graph = graph# 打印距离def print_distance(self, dist):for i in range(self.V):for j in range(self.V):print('%5s' % (dist[i][j] if dist[i][j] != INF else 'INF'), end='')print('')# 核心算法def floydwarshall(self):dist = copy.deepcopy(self.graph)for k in range(self.V):for i in range(self.V):for j in range(self.V):# 不考虑自己指向自己的情况if i == j:continuedist[i][j] = min(dist[i][j], dist[i][k] + dist[k][j])self.print_distance(dist)
g = Graph([[INF, INF, 1, INF, INF, INF, INF, INF],[INF, INF, 2, 8, INF, 5, INF, INF],[9, INF, INF, INF, 2, INF, INF, INF],[INF, INF, INF, INF, INF, 2, INF, INF],[INF, INF, INF, INF, INF, INF, INF, 9],[INF, INF, INF, INF, INF, INF, INF, INF],[INF, INF, INF, INF, 1, INF, INF, INF],[INF, INF, INF, INF, INF, 7, 7, INF]])
g.floydwarshall()