/
Dijkstra.js
216 lines (142 loc) · 4.36 KB
/
Dijkstra.js
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
import { PriorityQueue } from '../extra/PriorityQueue.js';
/**
* Implementation of Dijkstra's algorithm.
*
* @author {@link https://github.com/Mugen87|Mugen87}
*/
class Dijkstra {
/**
* Constructs a Dijkstra algorithm object.
*
* @param {Graph} graph - The graph.
* @param {Number} source - The node index of the source node.
* @param {Number} target - The node index of the target node.
*/
constructor( graph = null, source = - 1, target = - 1 ) {
/**
* The graph.
* @type {?Graph}
* @default null
*/
this.graph = graph;
/**
* The node index of the source node.
* @type {Number}
* @default - 1
*/
this.source = source;
/**
* The node index of the target node.
* @type {Number}
* @default - 1
*/
this.target = target;
/**
* Whether the search was successful or not.
* @type {Boolean}
* @default false
*/
this.found = false;
this._cost = new Map(); // total cost of the bast path so far for a given node
this._shortestPathTree = new Map();
this._searchFrontier = new Map();
}
/**
* Executes the graph search. If the search was successful, {@link Dijkstra#found}
* is set to true.
*
* @return {Dijkstra} A reference to this Dijkstra object.
*/
search() {
const outgoingEdges = new Array();
const pQueue = new PriorityQueue( compare );
pQueue.push( {
cost: 0,
index: this.source
} );
// while the queue is not empty
while ( pQueue.length > 0 ) {
const nextNode = pQueue.pop();
const nextNodeIndex = nextNode.index;
// if the shortest path tree has the given node, we already found the shortest
// path to this particular one
if ( this._shortestPathTree.has( nextNodeIndex ) ) continue;
// move this edge from the frontier to the shortest path tree
if ( this._searchFrontier.has( nextNodeIndex ) === true ) {
this._shortestPathTree.set( nextNodeIndex, this._searchFrontier.get( nextNodeIndex ) );
}
// if the target has been found exit
if ( nextNodeIndex === this.target ) {
this.found = true;
return this;
}
// now relax the edges
this.graph.getEdgesOfNode( nextNodeIndex, outgoingEdges );
for ( let i = 0, l = outgoingEdges.length; i < l; i ++ ) {
const edge = outgoingEdges[ i ];
// the total cost to the node this edge points to is the cost to the
// current node plus the cost of the edge connecting them.
const newCost = ( this._cost.get( nextNodeIndex ) || 0 ) + edge.cost;
// We enhance our search frontier in two cases:
// 1. If the node was never on the search frontier
// 2. If the cost to this node is better than before
if ( ( this._searchFrontier.has( edge.to ) === false ) || newCost < ( this._cost.get( edge.to ) ) ) {
this._cost.set( edge.to, newCost );
this._searchFrontier.set( edge.to, edge );
pQueue.push( {
cost: newCost,
index: edge.to
} );
}
}
}
this.found = false;
return this;
}
/**
* Returns the shortest path from the source to the target node as an array of node indices.
*
* @return {Array<Number>} The shortest path.
*/
getPath() {
// array of node indices that comprise the shortest path from the source to the target
const path = new Array();
// just return an empty path if no path to target found or if no target has been specified
if ( this.found === false || this.target === - 1 ) return path;
// start with the target of the path
let currentNode = this.target;
path.push( currentNode );
// while the current node is not the source node keep processing
while ( currentNode !== this.source ) {
// determine the parent of the current node
currentNode = this._shortestPathTree.get( currentNode ).from;
// push the new current node at the beginning of the array
path.unshift( currentNode );
}
return path;
}
/**
* Returns the search tree of the algorithm as an array of edges.
*
* @return {Array<Edge>} The search tree.
*/
getSearchTree() {
return [ ...this._shortestPathTree.values() ];
}
/**
* Clears the internal state of the object. A new search is now possible.
*
* @return {Dijkstra} A reference to this Dijkstra object.
*/
clear() {
this.found = false;
this._cost.clear();
this._shortestPathTree.clear();
this._searchFrontier.clear();
return this;
}
}
function compare( a, b ) {
return ( a.cost < b.cost ) ? - 1 : ( a.cost > b.cost ) ? 1 : 0;
}
export { Dijkstra };