tie params

1 files changed, 82 insertions, 0 deletions

diff --git a/gi/pf/tied_resampler.h b/gi/pf/tied_resampler.h
new file mode 100644
index 00000000..208fb9c7
--- /dev/null
+++ b/gi/pf/tied_resampler.h
@@ -0,0 +1,82 @@
+#ifndef _TIED_RESAMPLER_H_
+#define _TIED_RESAMPLER_H_
+
+#include <set>
+#include "sampler.h"
+#include "slice_sampler.h"
+#include "m.h"
+
+template <class CRP>
+struct TiedResampler {
+  explicit TiedResampler(double da, double db, double ss, double sr, double d=0.5, double s=1.0) :
+      d_alpha(da),
+      d_beta(db),
+      s_shape(ss),
+      s_rate(sr),
+      discount(d),
+      strength(s) {}
+
+  void Add(CRP* crp) {
+    crps.insert(crp);
+    crp->set_discount(discount);
+    crp->set_strength(strength);
+    assert(!crp->has_discount_prior());
+    assert(!crp->has_strength_prior());
+  }
+
+  void Remove(CRP* crp) {
+    crps.erase(crp);
+  }
+
+  double LogLikelihood(double d, double s) const {
+    if (s <= -d) return -std::numeric_limits<double>::infinity();
+    double llh = Md::log_beta_density(d, d_alpha, d_beta) +
+                 Md::log_gamma_density(d + s, s_shape, s_rate);
+    for (typename std::set<CRP*>::iterator it = crps.begin(); it != crps.end(); ++it)
+      llh += (*it)->log_crp_prob(d, s);
+    return llh;
+  }
+
+  struct DiscountResampler {
+    DiscountResampler(const TiedResampler& m) : m_(m) {}
+    const TiedResampler& m_;
+    double operator()(const double& proposed_discount) const {
+      return m_.LogLikelihood(proposed_discount, m_.strength);
+    }
+  };
+
+  struct AlphaResampler {
+    AlphaResampler(const TiedResampler& m) : m_(m) {}
+    const TiedResampler& m_;
+    double operator()(const double& proposed_strength) const {
+      return m_.LogLikelihood(m_.discount, proposed_strength);
+    }
+  };
+
+  void ResampleHyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) {
+    const DiscountResampler dr(*this);
+    const AlphaResampler ar(*this);
+    for (int iter = 0; iter < nloop; ++iter) {
+      strength = slice_sampler1d(ar, strength, *rng, -discount + std::numeric_limits<double>::min(),
+                              std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
+      double min_discount = std::numeric_limits<double>::min();
+      if (strength < 0.0) min_discount -= strength;
+      discount = slice_sampler1d(dr, discount, *rng, min_discount,
+                          1.0, 0.0, niterations, 100*niterations);
+    }
+    strength = slice_sampler1d(ar, strength, *rng, -discount + std::numeric_limits<double>::min(),
+                            std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
+    std::cerr << "TiedCRPs(d=" << discount << ",s="
+              << strength << ") = " << LogLikelihood(discount, strength) << std::endl;
+    for (typename std::set<CRP*>::iterator it = crps.begin(); it != crps.end(); ++it) {
+      (*it)->set_discount(discount);
+      (*it)->set_strength(strength);
+    }
+  }
+ private:
+  std::set<CRP*> crps;
+  const double d_alpha, d_beta, s_shape, s_rate;
+  double discount, strength;
+};
+
+#endif