Dijkstra’s shortest path algorithm in Coffeescript

Jonathan Ricketson

I (thought) I had a need for a shortest path implementation across a graph. Turns out I don’t, but here it is in case it is useful to someone else.

It is adapted from a javascript implementation.

To use: new Dijkstra().find_path(source_node, dest_node)
source_node and dest_node should have methods called “adjacent_nodes” that knows about the nodes that they are attached to.
This implementation assumes equal weighting on all links.

class Dijkstra
  constructor: () ->
    @predecessors = {}
  single_source_shortest_paths: (s, d) ->
    costs = {}
    costs[s] = 0
    open = {'0': [s]}
    keys = (obj) ->
      keys = []
      for key of obj
    sorter = (a, b) ->
      parseFloat(a) - parseFloat(b);
    add_to_open = (cost, v) ->
      key = '' + cost;
      open[key] ?= [];
    while (open)
      # In the nodes remaining in graph,
      # find the node, u, that currently has the shortest path from s.
      key = keys(open).pop()
      break if ! key?
      bucket = open[key]
      u = bucket.shift()
      delete open[key] if (bucket.length == 0)
      # Current cost of path from s to u.
      w_of_s_to_u = parseFloat(key)
      # v is the node across the current edge from u.
      for v in u.adjacent_nodes()
        w_of_s_to_v = w_of_s_to_u + 1
        costs[v] ?= Infinity
        if costs[v] > w_of_s_to_v
          costs[v] = w_of_s_to_v
          add_to_open(w_of_s_to_v, v)
          @predecessors[v] = u
        # If a destination node was specified and we reached it, we're done.
        if v.hash == d.hash
          open = null
    costs[d] ? Infinity
  extract_shortest_path_from_predecessor_list: (d) ->
    nodes = [];
    u = d
    while (u)
      u = @predecessors[u]
  find_cost: (s, d) ->
    @single_source_shortest_paths(s, d)
  find_path: (s, d) ->
    cost = @single_source_shortest_paths(s, d)
    if cost < Infinity
      return @extract_shortest_path_from_predecessor_list(d)
    throw new Error("Could not find a path from #{s} to #{d}.")

This entry was posted on November 21st, 2010.