-
Notifications
You must be signed in to change notification settings - Fork 196
/
BellmanFordSP.java
277 lines (252 loc) · 10.6 KB
/
BellmanFordSP.java
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
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
/*************************************************************************
* Compilation: javac BellmanFordSP.java
* Execution: java BellmanFordSP filename.txt s
* Dependencies: EdgeWeightedDigraph.java DirectedEdge.java Queue.java
* EdgeWeightedDirectedCycle.java
* Data files: http://algs4.cs.princeton.edu/44sp/tinyEWDn.txt
* http://algs4.cs.princeton.edu/44sp/mediumEWDnc.txt
*
* Bellman-Ford shortest path algorithm. Computes the shortest path tree in
* edge-weighted digraph G from vertex s, or finds a negative cost cycle
* reachable from s.
*
* % java BellmanFordSP tinyEWDn.txt 0
* 0 to 0 ( 0.00)
* 0 to 1 ( 0.93) 0->2 0.26 2->7 0.34 7->3 0.39 3->6 0.52 6->4 -1.25 4->5 0.35 5->1 0.32
* 0 to 2 ( 0.26) 0->2 0.26
* 0 to 3 ( 0.99) 0->2 0.26 2->7 0.34 7->3 0.39
* 0 to 4 ( 0.26) 0->2 0.26 2->7 0.34 7->3 0.39 3->6 0.52 6->4 -1.25
* 0 to 5 ( 0.61) 0->2 0.26 2->7 0.34 7->3 0.39 3->6 0.52 6->4 -1.25 4->5 0.35
* 0 to 6 ( 1.51) 0->2 0.26 2->7 0.34 7->3 0.39 3->6 0.52
* 0 to 7 ( 0.60) 0->2 0.26 2->7 0.34
*
* % java BellmanFordSP tinyEWDnc.txt 0
* 4->5 0.35
* 5->4 -0.66
*
*
*************************************************************************/
/**
* The <tt>BellmanFordSP</tt> class represents a data type for solving the
* single-source shortest paths problem in edge-weighted digraphs with
* no negative cycles.
* The edge weights can be positive, negative, or zero.
* This class finds either a shortest path from the source vertex <em>s</em>
* to every other vertex or a negative cycle reachable from the source vertex.
* <p>
* This implementation uses the Bellman-Ford-Moore algorithm.
* The constructor takes time proportional to <em>V</em> (<em>V</em> + <em>E</em>)
* in the worst case, where <em>V</em> is the number of vertices and <em>E</em>
* is the number of edges.
* Afterwards, the <tt>distTo()</tt>, <tt>hasPathTo()</tt>, and <tt>hasNegativeCycle()</tt>
* methods take constant time; the <tt>pathTo()</tt> and <tt>negativeCycle()</tt>
* method takes time proportional to the number of edges returned.
* <p>
* For additional documentation, see <a href="/algs4/44sp">Section 4.4</a> of
* <i>Algorithms, 4th Edition</i> by Robert Sedgewick and Kevin Wayne.
*
* @author Robert Sedgewick
* @author Kevin Wayne
*/
public class BellmanFordSP {
private double[] distTo; // distTo[v] = distance of shortest s->v path
private DirectedEdge[] edgeTo; // edgeTo[v] = last edge on shortest s->v path
private boolean[] onQueue; // onQueue[v] = is v currently on the queue?
private Queue<Integer> queue; // queue of vertices to relax
private int cost; // number of calls to relax()
private Iterable<DirectedEdge> cycle; // negative cycle (or null if no such cycle)
/**
* Computes a shortest paths tree from <tt>s</tt> to every other vertex in
* the edge-weighted digraph <tt>G</tt>.
* @param G the acyclic digraph
* @param s the source vertex
* @throws IllegalArgumentException unless 0 ≤ <tt>s</tt> ≤ <tt>V</tt> - 1
*/
public BellmanFordSP(EdgeWeightedDigraph G, int s) {
distTo = new double[G.V()];
edgeTo = new DirectedEdge[G.V()];
onQueue = new boolean[G.V()];
for (int v = 0; v < G.V(); v++)
distTo[v] = Double.POSITIVE_INFINITY;
distTo[s] = 0.0;
// Bellman-Ford algorithm
queue = new Queue<Integer>();
queue.enqueue(s);
onQueue[s] = true;
while (!queue.isEmpty() && !hasNegativeCycle()) {
int v = queue.dequeue();
onQueue[v] = false;
relax(G, v);
}
assert check(G, s);
}
// relax vertex v and put other endpoints on queue if changed
private void relax(EdgeWeightedDigraph G, int v) {
for (DirectedEdge e : G.adj(v)) {
int w = e.to();
if (distTo[w] > distTo[v] + e.weight()) {
distTo[w] = distTo[v] + e.weight();
edgeTo[w] = e;
if (!onQueue[w]) {
queue.enqueue(w);
onQueue[w] = true;
}
}
if (cost++ % G.V() == 0)
findNegativeCycle();
}
}
/**
* Is there a negative cycle reachable from the source vertex <tt>s</tt>?
* @return <tt>true</tt> if there is a negative cycle reachable from the
* source vertex <tt>s</tt>, and <tt>false</tt> otherwise
*/
public boolean hasNegativeCycle() {
return cycle != null;
}
/**
* Returns a negative cycle reachable from the source vertex <tt>s</tt>, or <tt>null</tt>
* if there is no such cycle.
* @return a negative cycle reachable from the soruce vertex <tt>s</tt>
* as an iterable of edges, and <tt>null</tt> if there is no such cycle
*/
public Iterable<DirectedEdge> negativeCycle() {
return cycle;
}
// by finding a cycle in predecessor graph
private void findNegativeCycle() {
int V = edgeTo.length;
EdgeWeightedDigraph spt = new EdgeWeightedDigraph(V);
for (int v = 0; v < V; v++)
if (edgeTo[v] != null)
spt.addEdge(edgeTo[v]);
EdgeWeightedDirectedCycle finder = new EdgeWeightedDirectedCycle(spt);
cycle = finder.cycle();
}
/**
* Returns the length of a shortest path from the source vertex <tt>s</tt> to vertex <tt>v</tt>.
* @param v the destination vertex
* @return the length of a shortest path from the source vertex <tt>s</tt> to vertex <tt>v</tt>;
* <tt>Double.POSITIVE_INFINITY</tt> if no such path
* @throws UnsupportedOperationException if there is a negative cost cycle reachable
* from the source vertex <tt>s</tt>
*/
public double distTo(int v) {
if (hasNegativeCycle())
throw new UnsupportedOperationException("Negative cost cycle exists");
return distTo[v];
}
/**
* Is there a path from the source <tt>s</tt> to vertex <tt>v</tt>?
* @param v the destination vertex
* @return <tt>true</tt> if there is a path from the source vertex
* <tt>s</tt> to vertex <tt>v</tt>, and <tt>false</tt> otherwise
*/
public boolean hasPathTo(int v) {
return distTo[v] < Double.POSITIVE_INFINITY;
}
/**
* Returns a shortest path from the source <tt>s</tt> to vertex <tt>v</tt>.
* @param v the destination vertex
* @return a shortest path from the source <tt>s</tt> to vertex <tt>v</tt>
* as an iterable of edges, and <tt>null</tt> if no such path
* @throws UnsupportedOperationException if there is a negative cost cycle reachable
* from the source vertex <tt>s</tt>
*/
public Iterable<DirectedEdge> pathTo(int v) {
if (hasNegativeCycle())
throw new UnsupportedOperationException("Negative cost cycle exists");
if (!hasPathTo(v)) return null;
Stack<DirectedEdge> path = new Stack<DirectedEdge>();
for (DirectedEdge e = edgeTo[v]; e != null; e = edgeTo[e.from()]) {
path.push(e);
}
return path;
}
// check optimality conditions: either
// (i) there exists a negative cycle reacheable from s
// or
// (ii) for all edges e = v->w: distTo[w] <= distTo[v] + e.weight()
// (ii') for all edges e = v->w on the SPT: distTo[w] == distTo[v] + e.weight()
private boolean check(EdgeWeightedDigraph G, int s) {
// has a negative cycle
if (hasNegativeCycle()) {
double weight = 0.0;
for (DirectedEdge e : negativeCycle()) {
weight += e.weight();
}
if (weight >= 0.0) {
System.err.println("error: weight of negative cycle = " + weight);
return false;
}
}
// no negative cycle reachable from source
else {
// check that distTo[v] and edgeTo[v] are consistent
if (distTo[s] != 0.0 || edgeTo[s] != null) {
System.err.println("distanceTo[s] and edgeTo[s] inconsistent");
return false;
}
for (int v = 0; v < G.V(); v++) {
if (v == s) continue;
if (edgeTo[v] == null && distTo[v] != Double.POSITIVE_INFINITY) {
System.err.println("distTo[] and edgeTo[] inconsistent");
return false;
}
}
// check that all edges e = v->w satisfy distTo[w] <= distTo[v] + e.weight()
for (int v = 0; v < G.V(); v++) {
for (DirectedEdge e : G.adj(v)) {
int w = e.to();
if (distTo[v] + e.weight() < distTo[w]) {
System.err.println("edge " + e + " not relaxed");
return false;
}
}
}
// check that all edges e = v->w on SPT satisfy distTo[w] == distTo[v] + e.weight()
for (int w = 0; w < G.V(); w++) {
if (edgeTo[w] == null) continue;
DirectedEdge e = edgeTo[w];
int v = e.from();
if (w != e.to()) return false;
if (distTo[v] + e.weight() != distTo[w]) {
System.err.println("edge " + e + " on shortest path not tight");
return false;
}
}
}
StdOut.println("Satisfies optimality conditions");
StdOut.println();
return true;
}
/**
* Unit tests the <tt>BellmanFordSP</tt> data type.
*/
public static void main(String[] args) {
In in = new In(args[0]);
int s = Integer.parseInt(args[1]);
EdgeWeightedDigraph G = new EdgeWeightedDigraph(in);
BellmanFordSP sp = new BellmanFordSP(G, s);
// print negative cycle
if (sp.hasNegativeCycle()) {
for (DirectedEdge e : sp.negativeCycle())
StdOut.println(e);
}
// print shortest paths
else {
for (int v = 0; v < G.V(); v++) {
if (sp.hasPathTo(v)) {
StdOut.printf("%d to %d (%5.2f) ", s, v, sp.distTo(v));
for (DirectedEdge e : sp.pathTo(v)) {
StdOut.print(e + " ");
}
StdOut.println();
}
else {
StdOut.printf("%d to %d no path\n", s, v);
}
}
}
}
}