Python Dijkstra Algorithm

问题

I am trying to write Dijkstra's Algorithm, however I am struggling on how to 'say' certain things in code. To visualize, here are the columns I want represented using arrays:

   max_nodes  
   A  B  C         Length       Predecessor       Visited/Unvisited
A 0  1   2             -1                                              U
B 1  0   1             -1                                              U
C 2  1   0             -1                                              U

So, there will be several arrays, as seen in my code below:

def dijkstra (graph, start, end)

network[max_nodes][max_nodes]
state  [max_nodes][length]
state2 [max_nodes][predecessor]
state3 [max_nodes][visited]
initialNode = 0

    for nodes in graph:
      D[max_nodes][length] = -1
      P[max_nodes][predecessor] = ""
      V[max_nodes][visited] = false

      for l in graph:

       length = lengthFromSource[node] + graph[node][l]
          if length < lengthFromSourceNode[w]:
             state[l][length] = x
             state2[l][predecessor] 
             state3[l][visited] = true
          x +=1

The part in bold is where I am stuck on - I am trying to implement this section of the algorithm:

3. For current node, consider all its unvisited neighbors and calculate their tentative distance. For example, if current node (A) has distance of 6, and an edge connecting it with another node (B) is 2, the distance to B through A will be 6+2=8. If this distance is less than the previously recorded distance, overwrite the distance
4. When we are done considering all neighbors of the current node, mark it as visited. A visited node will not be checked ever again; its distance recorded now is final and minimal

I think I am on the right track, i'm just stuck on how to say 'start at a node, get the length from source to a node, if length is smaller, overwrite previous value, then move to next node

回答1:

First, I assume this is a homework problem, as the best suggest is to not bother writing it yourself, but to find an existing implementation on the web. Here's one that looks pretty good, for example.

Assuming you do need to reinvent the wheel, the code referenced there uses dictionaries to store the node data. So you feed it something like:

{ 
  's': {'u' : 10, 'x' : 5}, 
  'u': {'v' : 1, 'x' : 2}, 
  'v': {'y' : 4}, 
  'x': {'u' : 3, 'v' : 9, 'y' : 2}, 
  'y': {'s' : 7, 'v' : 6}
}

This seems a more intuitive way of presenting your graph information. Visited nodes and distances can be kept in dictionaries as well.

回答2:

I also used a dictionary to store the network.

create a network dictionary (user provided)

net = {'0':{'1':100, '2':300},
       '1':{'3':500, '4':500, '5':100},
       '2':{'4':100, '5':100},
       '3':{'5':20},
       '4':{'5':20},
       '5':{}
       }

shortest path algorithm (user needs to specify start and terminal nodes)

def dijkstra(net, s, t):
    # sanity check
    if s == t:
        return "The start and terminal nodes are the same. Minimum distance is 0."
    if net.has_key(s)==False:
        return "There is no start node called " + str(s) + "."
    if net.has_key(t)==False:
        return "There is no terminal node called " + str(t) + "."
    # create a labels dictionary
    labels={}
    # record whether a label was updated
    order={}
    # populate an initial labels dictionary
    for i in net.keys():
        if i == s: labels[i] = 0 # shortest distance form s to s is 0
        else: labels[i] = float("inf") # initial labels are infinity
    from copy import copy
    drop1 = copy(labels) # used for looping
    ## begin algorithm
    while len(drop1) > 0:
        # find the key with the lowest label
        minNode = min(drop1, key = drop1.get) #minNode is the node with the smallest label
        # update labels for nodes that are connected to minNode
        for i in net[minNode]:
            if labels[i] > (labels[minNode] + net[minNode][i]):
                labels[i] = labels[minNode] + net[minNode][i]
                drop1[i] = labels[minNode] + net[minNode][i]
                order[i] = minNode
        del drop1[minNode] # once a node has been visited, it's excluded from drop1
    ## end algorithm
    # print shortest path
    temp = copy(t)
    rpath = []
    path = []
    while 1:
        rpath.append(temp)
        if order.has_key(temp): temp = order[temp]
        else: return "There is no path from " + str(s) + " to " + str(t) + "."
        if temp == s:
            rpath.append(temp)
            break
    for j in range(len(rpath)-1,-1,-1):
        path.append(rpath[j])
    return "The shortest path from " + s + " to " + t + " is " + str(path) + ". Minimum distance is " + str(labels[t]) + "."

# Given a large random network find the shortest path from '0' to '5'
print dijkstra(net=randNet(), s='0', t='5')

来源：https://stackoverflow.com/questions/4997851/python-dijkstra-algorithm