pyp lm, fixed hyperparameters inference

1 files changed, 26 insertions, 26 deletions

diff --git a/utils/ccrp_nt.h b/utils/ccrp_nt.h
index 63b6f4c2..79321493 100644
--- a/utils/ccrp_nt.h
+++ b/utils/ccrp_nt.h
@@ -18,20 +18,20 @@ class CCRP_NoTable {
  public:
   explicit CCRP_NoTable(double conc) :
     num_customers_(),
-    concentration_(conc),
-    concentration_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
-    concentration_prior_rate_(std::numeric_limits<double>::quiet_NaN()) {}
+    alpha_(conc),
+    alpha_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
+    alpha_prior_rate_(std::numeric_limits<double>::quiet_NaN()) {}
 
   CCRP_NoTable(double c_shape, double c_rate, double c = 10.0) :
     num_customers_(),
-    concentration_(c),
-    concentration_prior_shape_(c_shape),
-    concentration_prior_rate_(c_rate) {}
+    alpha_(c),
+    alpha_prior_shape_(c_shape),
+    alpha_prior_rate_(c_rate) {}
 
-  double concentration() const { return concentration_; }
+  double alpha() const { return alpha_; }
 
-  bool has_concentration_prior() const {
-    return !std::isnan(concentration_prior_shape_);
+  bool has_alpha_prior() const {
+    return !std::isnan(alpha_prior_shape_);
   }
 
   void clear() {
@@ -73,16 +73,16 @@ class CCRP_NoTable {
 
   double prob(const Dish& dish, const double& p0) const {
     const unsigned at_table = num_customers(dish);
-    return (at_table + p0 * concentration_) / (num_customers_ + concentration_);
+    return (at_table + p0 * alpha_) / (num_customers_ + alpha_);
   }
 
   double logprob(const Dish& dish, const double& logp0) const {
     const unsigned at_table = num_customers(dish);
-    return log(at_table + exp(logp0 + log(concentration_))) - log(num_customers_ + concentration_);
+    return log(at_table + exp(logp0 + log(alpha_))) - log(num_customers_ + alpha_);
   }
 
   double log_crp_prob() const {
-    return log_crp_prob(concentration_);
+    return log_crp_prob(alpha_);
   }
 
   static double log_gamma_density(const double& x, const double& shape, const double& rate) {
@@ -95,14 +95,14 @@ class CCRP_NoTable {
 
   // taken from http://en.wikipedia.org/wiki/Chinese_restaurant_process
   // does not include P_0's
-  double log_crp_prob(const double& concentration) const {
+  double log_crp_prob(const double& alpha) const {
     double lp = 0.0;
-    if (has_concentration_prior())
-      lp += log_gamma_density(concentration, concentration_prior_shape_, concentration_prior_rate_);
+    if (has_alpha_prior())
+      lp += log_gamma_density(alpha, alpha_prior_shape_, alpha_prior_rate_);
     assert(lp <= 0.0);
     if (num_customers_) {
-      lp += lgamma(concentration) - lgamma(concentration + num_customers_) +
-        custs_.size() * log(concentration);
+      lp += lgamma(alpha) - lgamma(alpha + num_customers_) +
+        custs_.size() * log(alpha);
       assert(std::isfinite(lp));
       for (typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator it = custs_.begin();
              it != custs_.end(); ++it) {
@@ -114,10 +114,10 @@ class CCRP_NoTable {
   }
 
   void resample_hyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) {
-    assert(has_concentration_prior());
+    assert(has_alpha_prior());
     ConcentrationResampler cr(*this);
     for (int iter = 0; iter < nloop; ++iter) {
-        concentration_ = slice_sampler1d(cr, concentration_, *rng, 0.0,
+        alpha_ = slice_sampler1d(cr, alpha_, *rng, 0.0,
                                std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
     }
   }
@@ -125,13 +125,13 @@ class CCRP_NoTable {
   struct ConcentrationResampler {
     ConcentrationResampler(const CCRP_NoTable& crp) : crp_(crp) {}
     const CCRP_NoTable& crp_;
-    double operator()(const double& proposed_concentration) const {
-      return crp_.log_crp_prob(proposed_concentration);
+    double operator()(const double& proposed_alpha) const {
+      return crp_.log_crp_prob(proposed_alpha);
     }
   };
 
   void Print(std::ostream* out) const {
-    (*out) << "DP(alpha=" << concentration_ << ") customers=" << num_customers_ << std::endl;
+    (*out) << "DP(alpha=" << alpha_ << ") customers=" << num_customers_ << std::endl;
     int cc = 0;
     for (typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator it = custs_.begin();
          it != custs_.end(); ++it) {
@@ -153,11 +153,11 @@ class CCRP_NoTable {
     return custs_.end();
   }
 
-  double concentration_;
+  double alpha_;
 
-  // optional gamma prior on concentration_ (NaN if no prior)
-  double concentration_prior_shape_;
-  double concentration_prior_rate_;
+  // optional gamma prior on alpha_ (NaN if no prior)
+  double alpha_prior_shape_;
+  double alpha_prior_rate_;
 };
 
 template <typename T,typename H>