This is a fibonacci-heap priority-queue implementation. That means
insert: O(1)
decrease_priority: Amortized O(1)
delete_min: Amortized O(log n)
This project is different from K. Kodamas PQueue in that it allows a decrease key operation. That makes PriorityQueue usable for algorithms like dijkstras shortest path algorithm, while PQueue is more suitable for Heapsort and the like.
(c) 2005 Brian Schröder
Please submit bugreports to [email protected]
This extension is under the same license as ruby.
Do not hold me reliable for anything that happens to you, your programs or anything else because of this extension. It worked for me, but there is no guarantee it will work for you.
- Ruby 1.8
- c Compiler
De-compress archive and enter its top directory. Then type:
($ su) # ruby setup.rb
These simple step installs this program under the default location of Ruby libraries. You can also install files into your favorite directory by supplying setup.rb some options. Try "ruby setup.rb --help".
($ su) # gem install PriorityQueue
In this priority queue implementation the queue behaves similarly to a hash that maps objects onto priorities.
require 'priority_queue'
q = PriorityQueue.new
q["node1"] = 0
q["node2"] = 1
q.min #=> "node1"
q[q.min] #=> 0
q.min_value #=> 0
q["node2"] = -1
q.delete_min #=> "node2", 1
q["node2"] #= nil
q["node3"] = 1
q.delete("node3") #=> "node3", 1
q.delete("node2") #=> nil
require 'priority_queue'
q = PriorityQueue.new
q.push "node1", 0
q.push "node2", 1
q.min #=> "node1"
q.decrease_priority("node2", -1)
q.pop_min #=> "node2"
q.min #=> "node1"
for more exmples look into the documentation, the unit tests and the benchmark suite.
def dijkstra(start_node)
# Nodes that may have neighbours wich can be relaxed further
active = PriorityQueue.new
# Best distances found so far
distances = Hash.new { 1.0 / 0.0 }
# Parent pointers describing shortest paths for all nodes
parents = Hash.new
# Initialize with start node
active[start_node] = 0
until active.empty?
u, distance = active.delete_min
distances[u] = distance
d = distance + 1
u.neighbours.each do | v |
next unless d < distances[v] # we can't relax this one
active[v] = distances[v] = d
parents[v] = u
end
end
parents
end
The benchmark directory contains an example where a random graph is created and the shortests paths from a random node in this graph to all other nodes are calculated with dijkstras shortests path algorithm. The algorithm is used to compare the three different priority queue implementations in this package.
- PoorPriorityQueue: A minimal priority queue implementation wich has delete_min in O(n).
- RubyPriorityQueue: An efficent implementation in pure ruby.
- CPriorityQueue: The same efficent implementation as a c extension.
The results are shown here
- Only write documentation once