1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
|
#ifndef PYP_TOPICS_HH
#define PYP_TOPICS_HH
#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"
#include "workers.hh"
class PYPTopics {
public:
typedef std::vector<int> DocumentTopics;
typedef std::vector<DocumentTopics> CorpusTopics;
typedef long double F;
public:
PYPTopics(int num_topics, bool use_topic_pyp=false, unsigned long seed = 0,
int max_threads = 1, int num_jobs = 1)
: m_num_topics(num_topics), m_word_pyps(1),
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), max_threads(max_threads), num_jobs(num_jobs) {}
void sample_corpus(const Corpus& corpus, int samples,
int freq_cutoff_start=0, int freq_cutoff_end=0,
int freq_cutoff_interval=0,
int max_contexts_per_document=0,
F temp_start=1.0, F temp_end=1.0);
int sample(const DocumentId& doc, const Term& term, F inv_temp=1.0);
std::pair<int,F> max(const DocumentId& doc, const Term& term) const;
std::pair<int,F> max(const DocumentId& doc) const;
int max_topic() const;
void set_backoff(const std::string& filename) {
m_backoff.reset(new TermBackoff);
m_backoff->read(filename);
m_word_pyps.clear();
m_word_pyps.resize(m_backoff->order(), PYPs());
}
void set_backoff(TermBackoffPtr backoff) {
m_backoff = backoff;
m_word_pyps.clear();
m_word_pyps.resize(m_backoff->order(), PYPs());
}
F prob(const Term& term, int topic, int level=0) const;
void decrement(const Term& term, int topic, int level=0);
void increment(const Term& term, int topic, int level=0);
F log_likelihood() const;
std::ostream& print_document_topics(std::ostream& out) const;
std::ostream& print_topic_terms(std::ostream& out) const;
private:
F word_pyps_p0(const Term& term, int topic, int level) const;
int m_num_topics;
F m_term_p0, m_topic_p0, m_backoff_p0;
CorpusTopics m_corpus_topics;
typedef boost::ptr_vector< PYP<int> > PYPs;
PYPs m_document_pyps;
std::vector<PYPs> m_word_pyps;
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)
typedef boost::function<F()> JobReturnsF;
F hresample_docs(int start, int end); //does i in [start, end)
F hresample_topics();
int max_threads;
int num_jobs;
TermBackoffPtr m_backoff;
};
#endif // PYP_TOPICS_HH
|
