cdec cleanup, remove bayesian stuff, parsing stuff

1 files changed, 0 insertions, 50 deletions

diff --git a/gi/pf/poisson_uniform_word_model.h b/gi/pf/poisson_uniform_word_model.h
deleted file mode 100644
index 76204a0e..00000000
--- a/gi/pf/poisson_uniform_word_model.h
+++ /dev/null
@@ -1,50 +0,0 @@
-#ifndef _POISSON_UNIFORM_WORD_MODEL_H_
-#define _POISSON_UNIFORM_WORD_MODEL_H_
-
-#include <cmath>
-#include <vector>
-#include "prob.h"
-#include "m.h"
-
-// len ~ Poisson(lambda)
-//   for (1..len)
-//     e_i ~ Uniform({Vocabulary})
-struct PoissonUniformWordModel {
-  explicit PoissonUniformWordModel(const unsigned vocab_size,
-                                   const unsigned alphabet_size,
-                                   const double mean_len = 5) :
-    lh(prob_t::One()),
-    v0(-std::log(vocab_size)),
-    u0(-std::log(alphabet_size)),
-    mean_length(mean_len) {}
-
-  void ResampleHyperparameters(MT19937*) {}
-
-  inline prob_t operator()(const std::vector<WordID>& s) const {
-    prob_t p;
-    p.logeq(Md::log_poisson(s.size(), mean_length) + s.size() * u0);
-    //p.logeq(v0);
-    return p;
-  }
-
-  inline void Increment(const std::vector<WordID>& w, MT19937*) {
-    lh *= (*this)(w);
-  }
-
-  inline void Decrement(const std::vector<WordID>& w, MT19937 *) {
-    lh /= (*this)(w);
-  }
-
-  inline prob_t Likelihood() const { return lh; }
-
-  void Summary() const {}
-
- private:
-
-  prob_t lh;  // keeps track of the draws from the base distribution
-  const double v0;  // uniform log prob of generating a word
-  const double u0;  // uniform log prob of generating a letter
-  const double mean_length;  // mean length of a word in the base distribution
-};
-
-#endif