From e26434979adc33bd949566ba7bf02dff64e80a3e Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 gi/pf/tied_resampler.h | 122 -------------------------------------------------
 1 file changed, 122 deletions(-)
 delete mode 100644 gi/pf/tied_resampler.h

(limited to 'gi/pf/tied_resampler.h')

diff --git a/gi/pf/tied_resampler.h b/gi/pf/tied_resampler.h
deleted file mode 100644
index a4f4af36..00000000
--- a/gi/pf/tied_resampler.h
+++ /dev/null
@@ -1,122 +0,0 @@
-#ifndef _TIED_RESAMPLER_H_
-#define _TIED_RESAMPLER_H_
-
-#include <set>
-#include <vector>
-#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);
-  }
-
-  size_t size() const {
-    return crps.size();
-  }
-
-  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;
-  }
-
-  double LogLikelihood() const {
-    return LogLikelihood(discount, strength);
-  }
-
-  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) {
-    if (size() == 0) { std::cerr << "EMPTY - not resampling\n"; return; }
-    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_hyperparameters(discount, strength);
-  }
- private:
-  std::set<CRP*> crps;
-  const double d_alpha, d_beta, s_shape, s_rate;
-  double discount, strength;
-};
-
-// split according to some criterion
-template <class CRP>
-struct BinTiedResampler {
-  explicit BinTiedResampler(unsigned nbins) :
-      resamplers(nbins, TiedResampler<CRP>(1,1,1,1)) {}
-
-  void Add(unsigned bin, CRP* crp) {
-    resamplers[bin].Add(crp);
-  }
-
-  void Remove(unsigned bin, CRP* crp) {
-    resamplers[bin].Remove(crp);
-  }
-
-  void ResampleHyperparameters(MT19937* rng) {
-    for (unsigned i = 0; i < resamplers.size(); ++i) {
-      std::cerr << "BIN " << i << " (" << resamplers[i].size() << " CRPs): " << std::flush;
-      resamplers[i].ResampleHyperparameters(rng);
-    }
-  }
-
-  double LogLikelihood() const {
-    double llh = 0;
-    for (unsigned i = 0; i < resamplers.size(); ++i)
-      llh += resamplers[i].LogLikelihood();
-    return llh;
-  }
-
- private:
-  std::vector<TiedResampler<CRP> > resamplers;
-};
-
-#endif
-- 
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