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-rw-r--r--gi/pyp-topics/src/pyp-topics.cc13
-rw-r--r--gi/pyp-topics/src/pyp-topics.hh23
-rw-r--r--gi/pyp-topics/src/pyp.hh32
-rw-r--r--gi/pyp-topics/src/train-contexts.cc8
-rw-r--r--gi/pyp-topics/src/train.cc8
5 files changed, 57 insertions, 27 deletions
diff --git a/gi/pyp-topics/src/pyp-topics.cc b/gi/pyp-topics/src/pyp-topics.cc
index 2ad9d080..2b96816e 100644
--- a/gi/pyp-topics/src/pyp-topics.cc
+++ b/gi/pyp-topics/src/pyp-topics.cc
@@ -5,7 +5,6 @@
#endif
#include "pyp-topics.hh"
-//#include "mt19937ar.h"
#include <boost/date_time/posix_time/posix_time_types.hpp>
#include <time.h>
@@ -46,13 +45,13 @@ void PYPTopics::sample_corpus(const Corpus& corpus, int samples,
{
m_word_pyps.at(i).reserve(m_num_topics);
for (int j=0; j<m_num_topics; ++j)
- m_word_pyps.at(i).push_back(new PYP<int>(0.5, 1.0));
+ m_word_pyps.at(i).push_back(new PYP<int>(0.5, 1.0, m_seed));
}
std::cerr << std::endl;
m_document_pyps.reserve(corpus.num_documents());
for (int j=0; j<corpus.num_documents(); ++j)
- m_document_pyps.push_back(new PYP<int>(0.5, 1.0));
+ m_document_pyps.push_back(new PYP<int>(0.5, 1.0, m_seed));
m_topic_p0 = 1.0/m_num_topics;
m_term_p0 = 1.0/corpus.num_types();
@@ -118,8 +117,10 @@ void PYPTopics::sample_corpus(const Corpus& corpus, int samples,
int tmp;
for (int i = corpus.num_documents()-1; i > 0; --i)
{
- int j = (int)(mt_genrand_real1() * i);
- tmp = randomDocIndices[i];
+ //i+1 since j \in [0,i] but rnd() \in [0,1)
+ int j = (int)(rnd() * (i+1));
+ assert(j >= 0 && j <= i);
+ tmp = randomDocIndices[i];
randomDocIndices[i] = randomDocIndices[j];
randomDocIndices[j] = tmp;
}
@@ -258,7 +259,7 @@ int PYPTopics::sample(const DocumentId& doc, const Term& term) {
sums.push_back(sum);
}
// Second pass: sample a topic
- F cutoff = mt_genrand_res53() * sum;
+ F cutoff = rnd() * sum;
for (int k=0; k<m_num_topics; ++k) {
if (cutoff <= sums[k])
return k;
diff --git a/gi/pyp-topics/src/pyp-topics.hh b/gi/pyp-topics/src/pyp-topics.hh
index 996ef4dd..9da49267 100644
--- a/gi/pyp-topics/src/pyp-topics.hh
+++ b/gi/pyp-topics/src/pyp-topics.hh
@@ -4,6 +4,11 @@
#include <vector>
#include <iostream>
#include <boost/ptr_container/ptr_vector.hpp>
+
+#include <boost/random/uniform_real.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <boost/random/mersenne_twister.hpp>
+
#include "pyp.hh"
#include "corpus.hh"
@@ -15,9 +20,12 @@ public:
typedef double F;
public:
- PYPTopics(int num_topics, bool use_topic_pyp=false)
+ PYPTopics(int num_topics, bool use_topic_pyp=false, unsigned long seed = 0)
: m_num_topics(num_topics), m_word_pyps(1),
- m_topic_pyp(0.5,1.0), m_use_topic_pyp(use_topic_pyp) {}
+ m_topic_pyp(0.5,1.0,seed), m_use_topic_pyp(use_topic_pyp),
+ m_seed(seed),
+ uni_dist(0,1), rng(seed == 0 ? (unsigned long)this : seed),
+ rnd(rng, uni_dist) {}
void sample_corpus(const Corpus& corpus, int samples,
int freq_cutoff_start=0, int freq_cutoff_end=0,
@@ -60,6 +68,17 @@ private:
PYP<int> m_topic_pyp;
bool m_use_topic_pyp;
+ unsigned long m_seed;
+
+ typedef boost::mt19937 base_generator_type;
+ typedef boost::uniform_real<> uni_dist_type;
+ typedef boost::variate_generator<base_generator_type&, uni_dist_type> gen_type;
+
+ uni_dist_type uni_dist;
+ base_generator_type rng; //this gets the seed
+ gen_type rnd; //instantiate: rnd(rng, uni_dist)
+ //call: rnd() generates uniform on [0,1)
+
TermBackoffPtr m_backoff;
};
diff --git a/gi/pyp-topics/src/pyp.hh b/gi/pyp-topics/src/pyp.hh
index 80c79fe1..64fb5b58 100644
--- a/gi/pyp-topics/src/pyp.hh
+++ b/gi/pyp-topics/src/pyp.hh
@@ -5,10 +5,13 @@
#include <map>
#include <tr1/unordered_map>
+#include <boost/random/uniform_real.hpp>
+#include <boost/random/variate_generator.hpp>
+#include <boost/random/mersenne_twister.hpp>
+
#include "log_add.h"
#include "gammadist.h"
#include "slice-sampler.h"
-#include "mt19937ar.h"
//
// Pitman-Yor process with customer and table tracking
@@ -23,7 +26,7 @@ public:
using std::tr1::unordered_map<Dish,int>::begin;
using std::tr1::unordered_map<Dish,int>::end;
- PYP(double a, double b, Hash hash=Hash());
+ PYP(double a, double b, unsigned long seed = 0, Hash hash=Hash());
int increment(Dish d, double p0);
int decrement(Dish d);
@@ -80,6 +83,16 @@ private:
DishTableType _dish_tables;
int _total_customers, _total_tables;
+ typedef boost::mt19937 base_generator_type;
+ typedef boost::uniform_real<> uni_dist_type;
+ typedef boost::variate_generator<base_generator_type&, uni_dist_type> gen_type;
+
+ uni_dist_type uni_dist;
+ base_generator_type rng; //this gets the seed
+ gen_type rnd; //instantiate: rnd(rng, uni_dist)
+ //call: rnd() generates uniform on [0,1)
+
+
// Function objects for calculating the parts of the log_prob for
// the parameters a and b
struct resample_a_type {
@@ -122,11 +135,12 @@ private:
};
template <typename Dish, typename Hash>
-PYP<Dish,Hash>::PYP(double a, double b, Hash)
+PYP<Dish,Hash>::PYP(double a, double b, unsigned long seed, Hash)
: std::tr1::unordered_map<Dish, int, Hash>(), _a(a), _b(b),
_a_beta_a(1), _a_beta_b(1), _b_gamma_s(1), _b_gamma_c(1),
//_a_beta_a(1), _a_beta_b(1), _b_gamma_s(10), _b_gamma_c(0.1),
- _total_customers(0), _total_tables(0)
+ _total_customers(0), _total_tables(0),
+ uni_dist(0,1), rng(seed == 0 ? (unsigned long)this : seed), rnd(rng, uni_dist)
{
// std::cerr << "\t##PYP<Dish,Hash>::PYP(a=" << _a << ",b=" << _b << ")" << std::endl;
}
@@ -211,7 +225,7 @@ PYP<Dish,Hash>::increment(Dish dish, double p0) {
assert (pshare >= 0.0);
//assert (pnew > 0.0);
- if (mt_genrand_res53() < pnew / (pshare + pnew)) {
+ if (rnd() < pnew / (pshare + pnew)) {
// assign to a new table
tc.tables += 1;
tc.table_histogram[1] += 1;
@@ -221,7 +235,7 @@ PYP<Dish,Hash>::increment(Dish dish, double p0) {
else {
// randomly assign to an existing table
// remove constant denominator from inner loop
- double r = mt_genrand_res53() * (c - _a*t);
+ double r = rnd() * (c - _a*t);
for (std::map<int,int>::iterator
hit = tc.table_histogram.begin();
hit != tc.table_histogram.end(); ++hit) {
@@ -283,7 +297,7 @@ PYP<Dish,Hash>::decrement(Dish dish)
//std::cerr << "count: " << count(dish) << " ";
//std::cerr << "tables: " << tc.tables << "\n";
- double r = mt_genrand_res53() * count(dish);
+ double r = rnd() * count(dish);
for (std::map<int,int>::iterator hit = tc.table_histogram.begin();
hit != tc.table_histogram.end(); ++hit)
{
@@ -467,7 +481,7 @@ PYP<Dish,Hash>::resample_prior_b() {
int niterations = 10; // number of resampling iterations
//std::cerr << "\n## resample_prior_b(), initial a = " << _a << ", b = " << _b << std::endl;
resample_b_type b_log_prob(_total_customers, _total_tables, _a, _b_gamma_c, _b_gamma_s);
- _b = slice_sampler1d(b_log_prob, _b, mt_genrand_res53, (double) 0.0, std::numeric_limits<double>::infinity(),
+ _b = slice_sampler1d(b_log_prob, _b, rnd, (double) 0.0, std::numeric_limits<double>::infinity(),
(double) 0.0, niterations, 100*niterations);
//std::cerr << "\n## resample_prior_b(), final a = " << _a << ", b = " << _b << std::endl;
}
@@ -481,7 +495,7 @@ PYP<Dish,Hash>::resample_prior_a() {
int niterations = 10;
//std::cerr << "\n## Initial a = " << _a << ", b = " << _b << std::endl;
resample_a_type a_log_prob(_total_customers, _total_tables, _b, _a_beta_a, _a_beta_b, _dish_tables);
- _a = slice_sampler1d(a_log_prob, _a, mt_genrand_res53, std::numeric_limits<double>::min(),
+ _a = slice_sampler1d(a_log_prob, _a, rnd, std::numeric_limits<double>::min(),
(double) 1.0, (double) 0.0, niterations, 100*niterations);
}
diff --git a/gi/pyp-topics/src/train-contexts.cc b/gi/pyp-topics/src/train-contexts.cc
index 481f8926..8a0c8949 100644
--- a/gi/pyp-topics/src/train-contexts.cc
+++ b/gi/pyp-topics/src/train-contexts.cc
@@ -14,7 +14,6 @@
#include "corpus.hh"
#include "contexts_corpus.hh"
#include "gzstream.hh"
-#include "mt19937ar.h"
static const char *REVISION = "$Rev$";
@@ -78,10 +77,9 @@ int main(int argc, char **argv)
return 1;
}
- // seed the random number generator
- //mt_init_genrand(time(0));
-
- PYPTopics model(vm["topics"].as<int>(), vm.count("hierarchical-topics"));
+ // seed the random number generator: 0 = automatic, specify value otherwise
+ unsigned long seed = 0;
+ PYPTopics model(vm["topics"].as<int>(), vm.count("hierarchical-topics"), seed);
// read the data
BackoffGenerator* backoff_gen=0;
diff --git a/gi/pyp-topics/src/train.cc b/gi/pyp-topics/src/train.cc
index c94010f2..3462f26c 100644
--- a/gi/pyp-topics/src/train.cc
+++ b/gi/pyp-topics/src/train.cc
@@ -12,7 +12,6 @@
#include "corpus.hh"
#include "contexts_corpus.hh"
#include "gzstream.hh"
-#include "mt19937ar.h"
static const char *REVISION = "$Rev$";
@@ -69,10 +68,9 @@ int main(int argc, char **argv)
return 1;
}
- // seed the random number generator
- //mt_init_genrand(time(0));
-
- PYPTopics model(vm["topics"].as<int>());
+ // seed the random number generator: 0 = automatic, specify value otherwise
+ unsigned long seed = 0;
+ PYPTopics model(vm["topics"].as<int>(), false, seed);
// read the data
Corpus corpus;
generated by cgit v1.2.3 (git 2.46.0) at 2025-10-31 00:14:11 +0000