merge with upstream

1 files changed, 161 insertions, 0 deletions

diff --git a/gi/pf/nuisance_test.cc b/gi/pf/nuisance_test.cc
new file mode 100644
index 00000000..fc0af9cb
--- /dev/null
+++ b/gi/pf/nuisance_test.cc
@@ -0,0 +1,161 @@
+#include "ccrp.h"
+
+#include <vector>
+#include <iostream>
+
+#include "tdict.h"
+#include "transliterations.h"
+
+using namespace std;
+
+MT19937 rng;
+
+ostream& operator<<(ostream&os, const vector<int>& v) {
+  os << '[' << v[0];
+  if (v.size() == 2) os << ' ' << v[1];
+  return os << ']';
+}
+
+struct Base {
+  Base() : llh(), v(2), v1(1), v2(1), crp(0.25, 0.5) {}
+  inline double p0(const vector<int>& x) const {
+    double p = 0.75;
+    if (x.size() == 2) p = 0.25;
+    p *= 1.0 / 3.0;
+    if (x.size() == 2) p *= 1.0 / 3.0;
+    return p;
+  }
+  double est_deriv_prob(int a, int b, int seg) const {
+    assert(a > 0 && a < 4);  // a \in {1,2,3}
+    assert(b > 0 && b < 4);  // b \in {1,2,3}
+    assert(seg == 0 || seg == 1);   // seg \in {0,1}
+    if (seg == 0) {
+      v[0] = a;
+      v[1] = b;
+      return crp.prob(v, p0(v));
+    } else {
+      v1[0] = a;
+      v2[0] = b;
+      return crp.prob(v1, p0(v1)) * crp.prob(v2, p0(v2));
+    }
+  }
+  double est_marginal_prob(int a, int b) const {
+    return est_deriv_prob(a,b,0) + est_deriv_prob(a,b,1);
+  }
+  int increment(int a, int b, double* pw = NULL) {
+    double p1 = est_deriv_prob(a, b, 0);
+    double p2 = est_deriv_prob(a, b, 1);
+    //p1 = 0.5; p2 = 0.5;
+    int seg = rng.SelectSample(p1,p2);
+    double tmp = 0;
+    if (!pw) pw = &tmp;
+    double& w = *pw;
+    if (seg == 0) {
+      v[0] = a;
+      v[1] = b;
+      w = crp.prob(v, p0(v)) / p1;
+      if (crp.increment(v, p0(v), &rng)) {
+        llh += log(p0(v));
+      }
+    } else {
+      v1[0] = a;
+      w = crp.prob(v1, p0(v1)) / p2;
+      if (crp.increment(v1, p0(v1), &rng)) {
+        llh += log(p0(v1));
+      }
+      v2[0] = b;
+      w *= crp.prob(v2, p0(v2));
+      if (crp.increment(v2, p0(v2), &rng)) {
+        llh += log(p0(v2));
+      }
+    }
+    return seg;
+  }
+  void increment(int a, int b, int seg) {
+    if (seg == 0) {
+      v[0] = a;
+      v[1] = b;
+      if (crp.increment(v, p0(v), &rng)) {
+        llh += log(p0(v));
+      }
+    } else {
+      v1[0] = a;
+      if (crp.increment(v1, p0(v1), &rng)) {
+        llh += log(p0(v1));
+      }
+      v2[0] = b;
+      if (crp.increment(v2, p0(v2), &rng)) {
+        llh += log(p0(v2));
+      }
+    }
+  }
+  void decrement(int a, int b, int seg) {
+    if (seg == 0) {
+      v[0] = a;
+      v[1] = b;
+      if (crp.decrement(v, &rng)) {
+        llh -= log(p0(v));
+      }
+    } else {
+      v1[0] = a;
+      if (crp.decrement(v1, &rng)) {
+        llh -= log(p0(v1));
+      }
+      v2[0] = b;
+      if (crp.decrement(v2, &rng)) {
+        llh -= log(p0(v2));
+      }
+    }
+  }
+  double log_likelihood() const {
+    return llh + crp.log_crp_prob();
+  }
+  double llh;
+  mutable vector<int> v, v1, v2;
+  CCRP<vector<int> > crp;
+};
+
+int main(int argc, char** argv) {
+  double tl = 0;
+  const int ITERS = 1000;
+  const int PARTICLES = 20;
+  const int DATAPOINTS = 50;
+  WordID x = TD::Convert("souvenons");
+  WordID y = TD::Convert("remember");
+  vector<WordID> src; TD::ConvertSentence("s o u v e n o n s", &src);
+  vector<WordID> trg; TD::ConvertSentence("r e m e m b e r", &trg);
+//  Transliterations xx;
+//  xx.Initialize(x, src, y, trg);
+//  return 1;
+
+ for (int j = 0; j < ITERS; ++j) {
+  Base b;
+  vector<int> segs(DATAPOINTS);
+  SampleSet<double> ss;
+  vector<int> sss;
+  for (int i = 0; i < DATAPOINTS; i++) {
+    ss.clear();
+    sss.clear();
+    int x = ((i / 10) % 3) + 1;
+    int y = (i % 3) + 1;
+    //double ep = b.est_marginal_prob(x,y);
+    //cerr << "est p(" << x << "," << y << ") = " << ep << endl;
+    for (int n = 0; n < PARTICLES; ++n) {
+      double w;
+      int seg = b.increment(x,y,&w);
+      //cerr << seg << " w=" << w << endl;
+      ss.add(w);
+      sss.push_back(seg);
+      b.decrement(x,y,seg);
+    }
+    int seg = sss[rng.SelectSample(ss)];
+    b.increment(x, y, seg);
+    //cerr << "Selected: " << seg << endl;
+    //return 1;
+    segs[i] = seg;
+  }
+  tl += b.log_likelihood();
+ }
+  cerr << "LLH=" << tl / ITERS << endl;
+}
+