# # / /
# # c -3- d -8- e
# #
-# var graph = new Graph[Node,WeigthedLink[Node]]
+# var graph = new Graph[Node,WeightedLink]
#
# var na = new Node(graph)
# var nb = new Node(graph)
# ~~~
module a_star
-redef class Object
- protected fun debug_a_star: Bool do return false
- private fun debug(msg: String) do if debug_a_star then
- stderr.write "a_star debug: {msg}\n"
- end
-end
-
# General graph node
class Node
+ # Type of the others nodes in the `graph`
type N: Node
# parent graph
var graph: Graph[N, Link]
- init(graph: Graph[N, Link])
+ init
do
- self.graph = graph
graph.add_node(self)
end
private var open: Bool = false
# Main functionnality, returns path from `self` to `dest`
- fun path_to(dest: N, max_cost: Int, context: PathContext): nullable Path[N]
+ fun path_to(dest: N, max_cost: Int, context: PathContext): nullable AStarPath[N]
+ do
+ return path_to_alts(dest, max_cost, context, null)
+ end
+
+ # Find a path to a possible `destination` or a node accepted by `alt_targets`
+ fun path_to_alts(destination: nullable N, max_cost: Int, context: PathContext,
+ alt_targets: nullable TargetCondition[N]): nullable AStarPath[N]
do
var cost = 0
loop
var frontier_node: nullable N = null
- var bucket_searched: Int = 0
+ var bucket_searched = 0
# find next valid node in frontier/buckets
loop
var current_bucket = buckets[cost % nbr_buckets]
if current_bucket.is_empty then # move to next bucket
- debug "b {cost} {cost % nbr_buckets} {buckets[cost % nbr_buckets].hash}"
cost += 1
if cost > max_cost then return null
bucket_searched += 1
if bucket_searched > nbr_buckets then break
else # found a node
- debug "c {cost}"
frontier_node = current_bucket.pop
if frontier_node.open then break
return null
# at destination
- else if frontier_node == dest then
- debug "picked {frontier_node}, is destination"
+ else if frontier_node == destination or
+ (alt_targets != null and alt_targets.accept(frontier_node)) then
- var path = new Path[N](cost)
+ var path = new AStarPath[N](cost)
while frontier_node != self do
path.nodes.unshift(frontier_node)
- frontier_node = frontier_node.best_source.as(not null)
+ frontier_node = frontier_node.best_source
+ assert frontier_node != null
end
return path
else
frontier_node.open = false
- debug "w exploring adjacents of {frontier_node}"
-
for link in frontier_node.links do
var peek_node = link.to
- debug "v {context.is_blocked(link)} {peek_node.last_pathfinding_evocation != graph.pathfinding_current_evocation} {peek_node.best_cost_up_to > frontier_node.best_cost_up_to + context.cost(link)}, {peek_node.best_cost_up_to} > {frontier_node.best_cost_up_to} + {context.cost(link)}"
if not context.is_blocked(link) and
(peek_node.last_pathfinding_evocation != graph.pathfinding_current_evocation or
(peek_node.open and
peek_node.best_cost_up_to > cost + context.cost(link)))
then
-
peek_node.open = true
peek_node.last_pathfinding_evocation = graph.pathfinding_current_evocation
peek_node.best_cost_up_to = cost + context.cost(link)
peek_node.best_source = frontier_node
- var est_cost = peek_node.best_cost_up_to+context.heuristic_cost(link.from, peek_node)
+ var est_cost
+ if destination != null then
+ est_cost = peek_node.best_cost_up_to + context.heuristic_cost(peek_node, destination)
+ else if alt_targets != null then
+ est_cost = peek_node.best_cost_up_to + alt_targets.heuristic_cost(peek_node, link)
+ else est_cost = 0
+
var at_bucket = buckets[est_cost % nbr_buckets]
at_bucket.add(peek_node)
-
- debug "u putting {peek_node} at {est_cost} -> {est_cost % nbr_buckets} {at_bucket.hash}, {cost}+{context.cost(link)}"
end
end
end
# Link between two nodes and associated to a graph
class Link
+ # Type of the nodes in `graph`
type N: Node
+
+ # Type of the other links in `graph`
type L: Link
+ # The graph to which belongs `self`
var graph: Graph[N, L]
+ # Origin of this link
var from: N
+
+ # Endpoint of this link
var to: N
- init(graph: Graph[N, L], from, to: N)
+ init
do
- self.graph = graph
- self.from = from
- self.to = to
-
graph.add_link(self)
end
end
# General graph
class Graph[N: Node, L: Link]
+ # Nodes in this graph
var nodes: Set[N] = new HashSet[N]
+
+ # Links in this graph
var links: Set[L] = new HashSet[L]
+ # Add a `node` to this graph
fun add_node(node: N): N
do
nodes.add(node)
return node
end
+ # Add a `link` to this graph
fun add_link(link: L): L
do
links.add(link)
return link
end
- # used to check if nodes have been searched in one pathfinding
- var pathfinding_current_evocation: Int = 0
+ # Used to check if nodes have been searched in one pathfinding
+ private var pathfinding_current_evocation: Int = 0
end
-# Result from pathfinding, a walkable path
-class Path[N]
+# Result from path finding and a walkable path
+class AStarPath[N]
+ # The total cost of this path
var total_cost: Int
+ # The list of nodes composing this path
var nodes = new List[N]
- init (cost: Int) do total_cost = cost
+ private var at: Int = 0
- var at: Int = 0
+ # Step on the path and get the next node to travel
fun step: N
do
- assert nodes.length >= at else print "a_star::Path::step failed, is at_end_of_path"
+ assert nodes.length >= at else print "a_star::AStarPath::step failed, is at_end_of_path"
var s = nodes[at]
at += 1
return s
end
+ # Peek at the next step of the path
fun peek_step: N do return nodes[at]
+ # Are we at the end of this path?
fun at_end_of_path: Bool do return at >= nodes.length
end
# Context related to an evocation of pathfinding
class PathContext
+ # Type of the nodes in `graph`
type N: Node
+
+ # Type of the links in `graph`
type L: Link
+ # Graph to which is associated `self`
var graph: Graph[N, L]
# Worst cost of all the link's costs
# Heuristic
fun heuristic_cost(a, b: N): Int is abstract
+ # The worst cost suggested by the heuristic
fun worst_heuristic_cost: Int is abstract
end
redef fun worst_heuristic_cost do return 0
end
+# A `PathContext` for graphs with `WeightedLink`
class WeightedPathContext
super PathContext
redef type L: WeightedLink
- init(graph: Graph[N, L])
+ init
do
super
self.worst_cost = worst_cost
end
- redef var worst_cost: Int
+ redef var worst_cost: Int is noinit
redef fun cost(l) do
return l.weight
redef fun worst_heuristic_cost do return 0
end
+# A `Link` with a `weight`
class WeightedLink
super Link
+ # The `weight`, or cost, of this link
var weight: Int
+end
- init(graph: Graph[N, L], from, to: N, weight: Int)
- do
- super
+# Advanced path conditions with customizable accept states
+class TargetCondition[N: Node]
+ # Should the pathfinding accept `node` as a goal?
+ fun accept(node: N): Bool is abstract
- self.weight = weight
- end
+ # Approximate cost from `node` to an accept state
+ fun heuristic_cost(node: N, link: Link): Int is abstract
end