blob: bc91330b68a33f9e2845cf1029499384e23f9962 (
plain)
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
|
#include "rst.h"
using namespace std;
// David B. Wilson. Generating Random Spanning Trees More Quickly than the Cover Time.
// this is an awesome algorithm
TreeSampler::TreeSampler(const ArcFactoredForest& af) : forest(af), usucc(af.size() + 1) {
// edges are directed from modifiers to heads, and finally to the root
vector<double> p;
for (int m = 1; m <= forest.size(); ++m) {
#if USE_ALIAS_SAMPLER
p.clear();
#else
SampleSet<double>& ss = usucc[m];
#endif
double z = 0;
for (int h = 0; h <= forest.size(); ++h) {
double u = forest(h-1,m-1).edge_prob.as_float();
z += u;
#if USE_ALIAS_SAMPLER
p.push_back(u);
#else
ss.add(u);
#endif
}
#if USE_ALIAS_SAMPLER
for (int i = 0; i < p.size(); ++i) { p[i] /= z; }
usucc[m].Init(p);
#endif
}
}
void TreeSampler::SampleRandomSpanningTree(EdgeSubset* tree, MT19937* prng) {
MT19937& rng = *prng;
const int r = 0;
bool success = false;
while (!success) {
int roots = 0;
tree->h_m_pairs.clear();
tree->roots.clear();
vector<int> next(forest.size() + 1, -1);
vector<char> in_tree(forest.size() + 1, 0);
in_tree[r] = 1;
//cerr << "Forest size: " << forest.size() << endl;
for (int i = 0; i <= forest.size(); ++i) {
//cerr << "Sampling starting at u=" << i << endl;
int u = i;
if (in_tree[u]) continue;
while(!in_tree[u]) {
#if USE_ALIAS_SAMPLER
next[u] = usucc[u].Draw(rng);
#else
next[u] = rng.SelectSample(usucc[u]);
#endif
u = next[u];
}
u = i;
//cerr << (u-1);
int prev = u-1;
while(!in_tree[u]) {
in_tree[u] = true;
u = next[u];
//cerr << " > " << (u-1);
if (u == r) {
++roots;
tree->roots.push_back(prev);
} else {
tree->h_m_pairs.push_back(make_pair<short,short>(u-1,prev));
}
prev = u-1;
}
//cerr << endl;
}
assert(roots > 0);
if (roots > 1) {
//cerr << "FAILURE\n";
} else {
success = true;
}
}
};
|
