Merge branch 'master' of https://github.com/redpony/cdec

33 files changed, 0 insertions, 9984 deletions

diff --git a/gi/pyp-topics/src/Makefile.am b/gi/pyp-topics/src/Makefile.am
deleted file mode 100644
index d3f95d0b..00000000
--- a/gi/pyp-topics/src/Makefile.am
+++ /dev/null
@@ -1,16 +0,0 @@
-bin_PROGRAMS = pyp-topics-train pyp-contexts-train #mpi-pyp-contexts-train
-
-contexts_lexer.cc: contexts_lexer.l
-	$(LEX) -s -CF -8 -o$@ $<
-
-pyp_topics_train_SOURCES = mt19937ar.c corpus.cc gzstream.cc pyp-topics.cc train.cc contexts_lexer.cc contexts_corpus.cc
-pyp_topics_train_LDADD = $(top_srcdir)/utils/libutils.a -lz
-
-pyp_contexts_train_SOURCES = mt19937ar.c corpus.cc gzstream.cc pyp-topics.cc contexts_lexer.cc contexts_corpus.cc train-contexts.cc
-pyp_contexts_train_LDADD = $(top_srcdir)/utils/libutils.a -lz
-
-#mpi_pyp_contexts_train_SOURCES = mt19937ar.c corpus.cc gzstream.cc mpi-pyp-topics.cc contexts_lexer.cc contexts_corpus.cc mpi-train-contexts.cc
-#mpi_pyp_contexts_train_LDADD = $(top_srcdir)/utils/libutils.a -lz
-
-AM_CPPFLAGS = -W -Wall -Wno-sign-compare -funroll-loops -I../../../utils
-
diff --git a/gi/pyp-topics/src/Makefile.mpi b/gi/pyp-topics/src/Makefile.mpi
deleted file mode 100644
index b7b8a290..00000000
--- a/gi/pyp-topics/src/Makefile.mpi
+++ /dev/null
@@ -1,26 +0,0 @@
-BLD_ARCH=$(shell uname -s)
--include macros.${BLD_ARCH}
-
-local_objs = mt19937ar.o corpus.o gzstream.o mpi-pyp-topics.o contexts_lexer.o contexts_corpus.o mpi-train-contexts.o
-
-all: mpi-pyp-contexts-train
-
--include makefile.depend
-
-#-----------------------#
-# Local stuff
-#-----------------------#
-
-mpi-pyp-contexts-train: mpi-train-contexts.o $(local_objs)
-	$(CXX) -o $@ $^ $(LDFLAGS)
-
-.PHONY: depend echo
-depend:
-#$(CXX) -MM $(CXXFLAGS) *.cc *.c | sed 's/^\(.*\.o:\)/obj\/\1/' > makefile.depend
-	$(CXX) -MM $(CXXFLAGS) *.cc *.c > makefile.depend
-
-clean:
-	rm -f *.o
-
-#clobber: clean
-#	rm makefile.depend ../bin/${ARCH}/*
diff --git a/gi/pyp-topics/src/clock_gettime_stub.c b/gi/pyp-topics/src/clock_gettime_stub.c
deleted file mode 100644
index 4883b7c1..00000000
--- a/gi/pyp-topics/src/clock_gettime_stub.c
+++ /dev/null
@@ -1,141 +0,0 @@
-/*
- * Copyright (c), MM Weiss
- * All rights reserved.
- * 
- * Redistribution and use in source and binary forms, with or without modification, 
- * are permitted provided that the following conditions are met:
- * 
- *     1. Redistributions of source code must retain the above copyright notice, 
- *     this list of conditions and the following disclaimer.
- *     
- *     2. Redistributions in binary form must reproduce the above copyright notice, 
- *     this list of conditions and the following disclaimer in the documentation 
- *     and/or other materials provided with the distribution.
- *     
- *     3. Neither the name of the MM Weiss nor the names of its contributors 
- *     may be used to endorse or promote products derived from this software without 
- *     specific prior written permission.
- * 
- * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY 
- * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 
- * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT 
- * SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 
- * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT 
- * OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) 
- * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR 
- * TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, 
- * EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- */
-
-/*
- *  clock_gettime_stub.c
- *  gcc -Wall -c clock_gettime_stub.c
- *  posix realtime functions; MacOS user space glue
- */
- 
-/*  @comment
- *  other possible implementation using intel builtin rdtsc
- *  rdtsc-workaround: http://www.mcs.anl.gov/~kazutomo/rdtsc.html
- *  
- *  we could get the ticks by doing this
- * 
- *  __asm __volatile("mov %%ebx, %%esi\n\t"
- *  		"cpuid\n\t"
- *  		"xchg %%esi, %%ebx\n\t"
- *  		"rdtsc"
- *  		: "=a" (a),
- *  		  "=d" (d)
- * 	);
- 
- *  we could even replace our tricky sched_yield call by assembly code to get a better accurency,
- *  anyway the following C stub will satisfy 99% of apps using posix clock_gettime call, 
- *  moreover, the setter version (clock_settime) could be easly written using mach primitives:
- *  http://www.opensource.apple.com/source/xnu/xnu-${VERSION}/osfmk/man/ (clock_[set|get]_time)
- *  
- *  hackers don't be crackers, don't you use a flush toilet?
- * 
- *
- *  @see draft: ./posix-realtime-stub/posix-realtime-stub.c
- *
- */
- 
-
-#ifdef __APPLE__
-
-#pragma weak clock_gettime
-
-#include <sys/time.h>
-#include <sys/resource.h>
-#include <mach/mach.h>
-#include <mach/clock.h>
-#include <mach/mach_time.h>
-#include <errno.h>
-#include <unistd.h>
-#include <sched.h>
-
-typedef enum {
-	CLOCK_REALTIME,
-	CLOCK_MONOTONIC,
-	CLOCK_PROCESS_CPUTIME_ID,
-	CLOCK_THREAD_CPUTIME_ID
-} clockid_t;
-
-static mach_timebase_info_data_t __clock_gettime_inf;
-
-static int clock_gettime(clockid_t clk_id, struct timespec *tp) {
-	kern_return_t   ret;
-	clock_serv_t    clk;
-	clock_id_t clk_serv_id;
-	mach_timespec_t tm;
-	
-	uint64_t start, end, delta, nano;
-	
-	//task_basic_info_data_t tinfo;
-	//task_thread_times_info_data_t ttinfo;
-	//mach_msg_type_number_t tflag;
-	
-	int retval = -1;
-	switch (clk_id) {
-		case CLOCK_REALTIME:
-		case CLOCK_MONOTONIC:
-			clk_serv_id = clk_id == CLOCK_REALTIME ? CALENDAR_CLOCK : SYSTEM_CLOCK;
-			if (KERN_SUCCESS == (ret = host_get_clock_service(mach_host_self(), clk_serv_id, &clk))) {
-				if (KERN_SUCCESS == (ret = clock_get_time(clk, &tm))) {
-					tp->tv_sec  = tm.tv_sec;
-					tp->tv_nsec = tm.tv_nsec;
-					retval = 0;
-				}
-			}
-			if (KERN_SUCCESS != ret) {
-				errno = EINVAL;
-				retval = -1;
-			}
-		break;
-		case CLOCK_PROCESS_CPUTIME_ID:
-		case CLOCK_THREAD_CPUTIME_ID:
-			start = mach_absolute_time();
-			if (clk_id == CLOCK_PROCESS_CPUTIME_ID) {
-				getpid();
-			} else {
-				sched_yield();
-			}
-			end = mach_absolute_time();
-			delta = end - start;	
-			if (0 == __clock_gettime_inf.denom) {
-				mach_timebase_info(&__clock_gettime_inf);
-			}
-			nano = delta * __clock_gettime_inf.numer / __clock_gettime_inf.denom;
-			tp->tv_sec = nano * 1e-9;  
-			tp->tv_nsec = nano - (tp->tv_sec * 1e9);
-			retval = 0;
-		break;
-		default:
-			errno = EINVAL;
-			retval = -1;
-	}
-	return retval;
-}
-
-#endif // __APPLE__
-
-/* EOF */
diff --git a/gi/pyp-topics/src/contexts_corpus.cc b/gi/pyp-topics/src/contexts_corpus.cc
deleted file mode 100644
index 92b1b34c..00000000
--- a/gi/pyp-topics/src/contexts_corpus.cc
+++ /dev/null
@@ -1,164 +0,0 @@
-#include <sstream>
-#include <iostream>
-#include <set>
-
-#include "contexts_corpus.hh"
-#include "gzstream.hh"
-#include "contexts_lexer.h"
-
-#include <boost/tuple/tuple.hpp>
-
-
-using namespace std;
-
-//////////////////////////////////////////////////
-// ContextsCorpus
-//////////////////////////////////////////////////
-
-bool read_callback_binary_contexts = false;
-
-void read_callback(const ContextsLexer::PhraseContextsType& new_contexts, void* extra) {
-  assert(new_contexts.contexts.size() == new_contexts.counts.size());
-
-  boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* >* extra_pair
-    = static_cast< boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* >* >(extra);
-
-  ContextsCorpus* corpus_ptr = extra_pair->get<0>();
-  BackoffGenerator* backoff_gen = extra_pair->get<1>();
-  //map<string,int>* counts = extra_pair->get<2>();
-
-  Document* doc(new Document());
-
-  //cout << "READ: " << new_contexts.phrase << "\t";
-  for (int i=0; i < (int)new_contexts.counts.size(); ++i) {
-    int cache_word_count = corpus_ptr->m_dict.max();
-
-    //string context_str = corpus_ptr->m_dict.toString(new_contexts.contexts[i]);
-    int context_index = new_contexts.counts.at(i).first;
-    string context_str = corpus_ptr->m_dict.toString(new_contexts.contexts[context_index]);
-
-    // filter out singleton contexts
-    //if (!counts->empty()) {
-    //  map<string,int>::const_iterator find_it = counts->find(context_str);
-    //  if (find_it == counts->end() || find_it->second < 2)
-    //    continue;
-    //}
-
-    WordID id = corpus_ptr->m_dict.Convert(context_str);
-    if (cache_word_count != corpus_ptr->m_dict.max()) {
-      corpus_ptr->m_backoff->terms_at_level(0)++;
-      corpus_ptr->m_num_types++;
-    }
-
-    //int count = new_contexts.counts[i];
-    int count = new_contexts.counts.at(i).second;
-    if (read_callback_binary_contexts) {
-      doc->push_back(id);
-      corpus_ptr->m_num_terms++;
-    }
-    else {
-      for (int j=0; j<count; ++j)
-        doc->push_back(id);
-      corpus_ptr->m_num_terms += count;
-    }
-
-    // generate the backoff map
-    if (backoff_gen) {
-      int order = 1;
-      WordID backoff_id = id;
-      //ContextsLexer::Context backedoff_context = new_contexts.contexts[i];
-      ContextsLexer::Context backedoff_context = new_contexts.contexts[context_index];
-      while (true) {
-        if (!corpus_ptr->m_backoff->has_backoff(backoff_id)) {
-          //cerr << "Backing off from " << corpus_ptr->m_dict.Convert(backoff_id) << " to ";
-          backedoff_context = (*backoff_gen)(backedoff_context);
-
-          if (backedoff_context.empty()) {
-            //cerr << "Nothing." << endl;
-            (*corpus_ptr->m_backoff)[backoff_id] = -1;
-            break;
-          }
-
-          if (++order > corpus_ptr->m_backoff->order())
-            corpus_ptr->m_backoff->order(order);
-
-          int cache_word_count = corpus_ptr->m_dict.max();
-          int new_backoff_id = corpus_ptr->m_dict.Convert(backedoff_context);
-          if (cache_word_count != corpus_ptr->m_dict.max())
-            corpus_ptr->m_backoff->terms_at_level(order-1)++;
-
-          //cerr << corpus_ptr->m_dict.Convert(new_backoff_id) << " ." << endl;
-
-          backoff_id = ((*corpus_ptr->m_backoff)[backoff_id] = new_backoff_id);
-        }
-        else break;
-      }
-    }
-    //cout << context_str << " (" << id << ") ||| C=" << count << " ||| ";
-  }
-  //cout << endl;
-
-  //if (!doc->empty()) {
-    corpus_ptr->m_documents.push_back(doc);
-    corpus_ptr->m_keys.push_back(new_contexts.phrase);
-  //}
-}
-
-void filter_callback(const ContextsLexer::PhraseContextsType& new_contexts, void* extra) {
-  assert(new_contexts.contexts.size() == new_contexts.counts.size());
-
-  map<string,int>* context_counts = (static_cast<map<string,int>*>(extra));
-
-  for (int i=0; i < (int)new_contexts.counts.size(); ++i) {
-    int context_index = new_contexts.counts.at(i).first;
-    int count = new_contexts.counts.at(i).second;
-    //if (read_callback_binary_contexts) count = 1;
-    //int count = new_contexts.counts[i];
-    pair<map<string,int>::iterator,bool> result 
-      = context_counts->insert(make_pair(Dict::toString(new_contexts.contexts[context_index]),count));
-      //= context_counts->insert(make_pair(Dict::toString(new_contexts.contexts[i]),count));
-    if (!result.second)
-      result.first->second += count;
-  }
-}
-
-
-unsigned ContextsCorpus::read_contexts(const string &filename, 
-                                       BackoffGenerator* backoff_gen_ptr,
-                                       bool /*filter_singeltons*/,
-                                       bool binary_contexts) {
-  read_callback_binary_contexts = binary_contexts;
-
-  map<string,int> counts;
-  //if (filter_singeltons) 
-  {
-  //  cerr << "--- Filtering singleton contexts ---" << endl;
-
-    igzstream in(filename.c_str());
-    ContextsLexer::ReadContexts(&in, filter_callback, &counts);
-  }
-
-  m_num_terms = 0;
-  m_num_types = 0;
-
-  igzstream in(filename.c_str());
-  boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* > extra_pair(this,backoff_gen_ptr,&counts);
-  ContextsLexer::ReadContexts(&in, read_callback, &extra_pair);
-
-  //m_num_types = m_dict.max();
-
-  cerr << "Read backoff with order " << m_backoff->order() << "\n";
-  for (int o=0; o<m_backoff->order(); o++)
-    cerr << "  Terms at " << o << " = " << m_backoff->terms_at_level(o) << endl;
-  //cerr << endl;
-
-  int i=0; double av_freq=0;
-  for (map<string,int>::const_iterator it=counts.begin(); it != counts.end(); ++it, ++i) {
-    WordID id = m_dict.Convert(it->first);
-    m_context_counts[id] = it->second;
-    av_freq += it->second;
-  }
-  cerr << "  Average term frequency = " << av_freq / (double) i << endl;
-
-  return m_documents.size();
-}
diff --git a/gi/pyp-topics/src/contexts_corpus.hh b/gi/pyp-topics/src/contexts_corpus.hh
deleted file mode 100644
index 2527f655..00000000
--- a/gi/pyp-topics/src/contexts_corpus.hh
+++ /dev/null
@@ -1,90 +0,0 @@
-#ifndef _CONTEXTS_CORPUS_HH
-#define _CONTEXTS_CORPUS_HH
-
-#include <vector>
-#include <string>
-#include <map>
-#include <tr1/unordered_map>
-
-#include <boost/ptr_container/ptr_vector.hpp>
-
-#include "corpus.hh"
-#include "contexts_lexer.h"
-#include "dict.h"
-
-
-class BackoffGenerator {
-public:
-  virtual ContextsLexer::Context
-    operator()(const ContextsLexer::Context& c) = 0;
-
-protected:
-  ContextsLexer::Context strip_edges(const ContextsLexer::Context& c) {
-    if (c.size() <= 1) return ContextsLexer::Context();
-    assert(c.size() % 2 == 1);
-    return ContextsLexer::Context(c.begin() + 1, c.end() - 1);
-  }
-};
-
-class NullBackoffGenerator : public BackoffGenerator {
-  virtual ContextsLexer::Context
-    operator()(const ContextsLexer::Context&) 
-    { return ContextsLexer::Context(); }
-};
-
-class SimpleBackoffGenerator : public BackoffGenerator {
-  virtual ContextsLexer::Context
-    operator()(const ContextsLexer::Context& c) { 
-      if (c.size() <= 3)
-        return ContextsLexer::Context();
-      return strip_edges(c); 
-    }
-};
-
-
-////////////////////////////////////////////////////////////////
-// ContextsCorpus
-////////////////////////////////////////////////////////////////
-
-class ContextsCorpus : public Corpus {
-  friend void read_callback(const ContextsLexer::PhraseContextsType&, void*);
-
-public:
-    ContextsCorpus() : m_backoff(new TermBackoff) {}
-    virtual ~ContextsCorpus() {}
-
-    virtual unsigned read_contexts(const std::string &filename, 
-                                   BackoffGenerator* backoff_gen=0,
-                                   bool filter_singeltons=false,
-                                   bool binary_contexts=false);
-
-    TermBackoffPtr backoff_index() {
-      return m_backoff;
-    }
-
-    std::vector<std::string> context2string(const WordID& id) const {
-      std::vector<std::string> res;
-      assert (id >= 0);
-      m_dict.AsVector(id, &res);
-      return res;
-    }
-
-    virtual int context_count(const WordID& id) const {
-      return m_context_counts.find(id)->second;
-    }
-
-
-    const std::string& key(const int& i) const {
-      return m_keys.at(i);
-    }
-
-    const Dict& dict() const { return m_dict; }
-
-protected:
-    TermBackoffPtr m_backoff;
-    Dict m_dict;
-    std::vector<std::string> m_keys;
-    std::tr1::unordered_map<int,int> m_context_counts;
-};
-
-#endif // _CONTEXTS_CORPUS_HH
diff --git a/gi/pyp-topics/src/contexts_lexer.h b/gi/pyp-topics/src/contexts_lexer.h
deleted file mode 100644
index 66004990..00000000
--- a/gi/pyp-topics/src/contexts_lexer.h
+++ /dev/null
@@ -1,22 +0,0 @@
-#ifndef _CONTEXTS_LEXER_H_
-#define _CONTEXTS_LEXER_H_ 
-
-#include <iostream>
-#include <vector>
-#include <string>
-
-#include "dict.h" 
-
-struct ContextsLexer {
-  typedef std::vector<std::string> Context;
-  struct PhraseContextsType {
-    std::string          phrase;
-    std::vector<Context> contexts;
-    std::vector< std::pair<int,int> >     counts;
-  };
-
-  typedef void (*ContextsCallback)(const PhraseContextsType& new_contexts, void* extra);
-  static void ReadContexts(std::istream* in, ContextsCallback func, void* extra);
-};
-
-#endif
diff --git a/gi/pyp-topics/src/contexts_lexer.l b/gi/pyp-topics/src/contexts_lexer.l
deleted file mode 100644
index 64cd7ca3..00000000
--- a/gi/pyp-topics/src/contexts_lexer.l
+++ /dev/null
@@ -1,113 +0,0 @@
-%{
-#include "contexts_lexer.h"
-
-#include <string>
-#include <iostream>
-#include <sstream>
-#include <cstring>
-#include <cassert>
-#include <algorithm>
-
-int lex_line = 0;
-std::istream* contextslex_stream = NULL;
-ContextsLexer::ContextsCallback contexts_callback = NULL;
-void* contexts_callback_extra = NULL;
-
-#undef YY_INPUT
-#define YY_INPUT(buf, result, max_size) (result = contextslex_stream->read(buf, max_size).gcount())
-
-#define YY_SKIP_YYWRAP 1
-int num_phrases = 0;
-int yywrap() { return 1; }
-
-#define MAX_TOKEN_SIZE 255
-std::string contextslex_tmp_token(MAX_TOKEN_SIZE, '\0');
-ContextsLexer::PhraseContextsType current_contexts;
-
-#define MAX_CONTEXT_SIZE 255
-//std::string tmp_context[MAX_CONTEXT_SIZE];
-ContextsLexer::Context tmp_context;
-
-
-void contextslex_reset() {
-  current_contexts.phrase.clear();
-  current_contexts.contexts.clear();
-  current_contexts.counts.clear();
-  tmp_context.clear();
-}
-
-%}
-
-INT [\-+]?[0-9]+|inf|[\-+]inf
-
-%x CONTEXT COUNT COUNT_END
-%%
-
-<INITIAL>[^\t]+	{ 
-    contextslex_reset();
-    current_contexts.phrase.assign(yytext, yyleng);
-    BEGIN(CONTEXT);
-  }
-<INITIAL>\t	{ 
-    ; 
-  }
-
-<INITIAL,CONTEXT,COUNT>\n	{
-    std::cerr << "ERROR: contexts_lexer.l: unexpected newline while trying to read phrase|context|count." << std::endl;
-    abort();
-  }
-
-<CONTEXT>\|\|\|	{
-    current_contexts.contexts.push_back(tmp_context);
-    tmp_context.clear();
-		BEGIN(COUNT);
-	}
-<CONTEXT>[^ \t]+	{ 
-		contextslex_tmp_token.assign(yytext, yyleng);
-    tmp_context.push_back(contextslex_tmp_token);
-  }
-<CONTEXT>[ \t]+	{ ; }
-
-<COUNT>[ \t]+	{ ; }
-<COUNT>C={INT} { 
-		current_contexts.counts.push_back(std::make_pair(current_contexts.counts.size(), atoi(yytext+2)));
-    BEGIN(COUNT_END);
-  }
-<COUNT>.	{ 
-    std::cerr << "ERROR: contexts_lexer.l: unexpected content while reading count." << std::endl;
-    abort();
-  }
-
-<COUNT_END>[ \t]+  { ; }
-<COUNT_END>\|\|\|	{
-		BEGIN(CONTEXT);
-  }
-<COUNT_END>\n {
-    //std::cerr << "READ:" << current_contexts.phrase << " with " << current_contexts.contexts.size() 
-    //  << " contexts, and " << current_contexts.counts.size() << " counts." << std::endl;
-    std::sort(current_contexts.counts.rbegin(), current_contexts.counts.rend()); 
-
-		contexts_callback(current_contexts, contexts_callback_extra);
-    current_contexts.phrase.clear();
-    current_contexts.contexts.clear();
-    current_contexts.counts.clear();
-		BEGIN(INITIAL);
-  }
-<COUNT_END>.  { 
-		contextslex_tmp_token.assign(yytext, yyleng);
-    std::cerr << "ERROR: contexts_lexer.l: unexpected content while looking for ||| closing count." << std::endl;
-    abort();
-  }
-
-%%
-
-#include "filelib.h" 
-
-void ContextsLexer::ReadContexts(std::istream* in, ContextsLexer::ContextsCallback func, void* extra) {
-  lex_line = 1;
-  contextslex_stream = in;
-  contexts_callback_extra = extra,
-  contexts_callback = func;
-  yylex();
-}
-
diff --git a/gi/pyp-topics/src/corpus.cc b/gi/pyp-topics/src/corpus.cc
deleted file mode 100644
index f182381f..00000000
--- a/gi/pyp-topics/src/corpus.cc
+++ /dev/null
@@ -1,104 +0,0 @@
-#include <sstream>
-#include <iostream>
-#include <set>
-
-#include "corpus.hh"
-#include "gzstream.hh"
-
-using namespace std;
-
-//////////////////////////////////////////////////
-// Corpus
-//////////////////////////////////////////////////
-
-Corpus::Corpus() : m_num_terms(0), m_num_types(0) {}
-
-unsigned Corpus::read(const std::string &filename) {
-  m_num_terms = 0;
-  m_num_types = 0;
-  std::set<int> seen_types;
-
-  igzstream in(filename.c_str());
-
-  string buf;
-  int token;
-  unsigned doc_count=0;
-  while (getline(in, buf)) {
-    Document* doc(new Document());
-    istringstream ss(buf);
-
-    ss >> token; // the number of unique terms
-
-    char delimeter;
-    int count;
-    while(ss >> token >> delimeter >> count) {
-      for (int i=0; i<count; ++i)
-        doc->push_back(token);
-      m_num_terms += count;
-      seen_types.insert(token);
-    }
-
-    m_documents.push_back(doc);
-    doc_count++;
-  }
-
-  m_num_types = seen_types.size();
-
-  return doc_count;
-}
-
-
-//////////////////////////////////////////////////
-// TestCorpus
-//////////////////////////////////////////////////
-
-TestCorpus::TestCorpus() {}
-
-void TestCorpus::read(const std::string &filename) {
-  igzstream in(filename.c_str());
-
-  string buf;
-  Term term;
-  DocumentId doc;
-  char delimeter;
-  while (getline(in, buf)) {
-    DocumentTerms* line(new DocumentTerms());
-    istringstream ss(buf);
-
-    while(ss >> doc >> delimeter >> term)
-      line->push_back(DocumentTerm(doc, term));
-
-    m_lines.push_back(line);
-  }
-}
-
-//////////////////////////////////////////////////
-// TermBackoff
-//////////////////////////////////////////////////
-
-void TermBackoff::read(const std::string &filename) {
-  igzstream in(filename.c_str());
-
-  string buf;
-  int num_terms;
-  getline(in, buf);
-  istringstream ss(buf); 
-  ss >> num_terms >> m_backoff_order;
-
-  m_dict.resize(num_terms, -1);
-  for (int i=0; i<m_backoff_order; ++i) {
-    int count; ss >> count;
-    m_terms_at_order.push_back(count);
-  }
-
-  Term term, backoff;
-  while (getline(in, buf)) {
-    istringstream ss(buf);
-    ss >> term >> backoff;
-
-    assert(term < num_terms);
-    assert(term >= 0);
-
-    m_dict[term] = backoff;
-  }
-}
diff --git a/gi/pyp-topics/src/corpus.hh b/gi/pyp-topics/src/corpus.hh
deleted file mode 100644
index 2aa03527..00000000
--- a/gi/pyp-topics/src/corpus.hh
+++ /dev/null
@@ -1,133 +0,0 @@
-#ifndef _CORPUS_HH
-#define _CORPUS_HH
-
-#include <vector>
-#include <string>
-#include <map>
-#include <limits>
-
-#include <boost/shared_ptr.hpp>
-#include <boost/ptr_container/ptr_vector.hpp>
-
-////////////////////////////////////////////////////////////////
-// Corpus
-////////////////////////////////////////////////////////////////
-typedef int Term;
-
-typedef std::vector<Term> Document;
-typedef std::vector<Term> Terms;
-
-class Corpus {
-public:
-    typedef boost::ptr_vector<Document>::const_iterator const_iterator;
-
-public:
-    Corpus();
-    virtual ~Corpus() {}
-
-    virtual unsigned read(const std::string &filename);
-
-    const_iterator begin() const { return m_documents.begin(); }
-    const_iterator end() const { return m_documents.end(); }
-
-    const Document& at(size_t i) const { return m_documents.at(i); }
-
-    int num_documents() const { return m_documents.size(); }
-    int num_terms() const { return m_num_terms; }
-    int num_types() const { return m_num_types; }
-
-    virtual int context_count(const int&) const {
-      return std::numeric_limits<int>::max();
-    }
-
-protected:
-    int m_num_terms, m_num_types;
-    boost::ptr_vector<Document> m_documents; 
-};
-
-typedef int DocumentId;
-struct DocumentTerm {
-  DocumentTerm(DocumentId d, Term t) : term(t), doc(d) {}
-  Term term;
-  DocumentId doc;
-};
-typedef std::vector<DocumentTerm> DocumentTerms;
-
-class TestCorpus {
-public:
-    typedef boost::ptr_vector<DocumentTerms>::const_iterator const_iterator;
-
-public:
-    TestCorpus();
-    ~TestCorpus() {}
-
-    void read(const std::string &filename);
-
-    const_iterator begin() const { return m_lines.begin(); }
-    const_iterator end() const { return m_lines.end(); }
-
-    int num_instances() const { return m_lines.size(); }
-
-protected:
-    boost::ptr_vector<DocumentTerms> m_lines; 
-};
-
-class TermBackoff {
-public:
-    typedef std::vector<Term> dictionary_type;
-    typedef dictionary_type::const_iterator const_iterator;
-    const static int NullBackoff=-1;
-
-public:
-    TermBackoff() { order(1); }
-    ~TermBackoff() {}
-
-    void read(const std::string &filename);
-
-    const_iterator begin() const { return m_dict.begin(); }
-    const_iterator end() const { return m_dict.end(); }
-
-    const Term& operator[](const Term& t) const {
-      assert(t < static_cast<int>(m_dict.size()));
-      return m_dict[t];
-    }
-
-    Term& operator[](const Term& t) {
-      if (t >= static_cast<int>(m_dict.size()))
-        m_dict.resize(t+1, -1);
-      return m_dict[t];
-    }
-
-    bool has_backoff(const Term& t) {
-      return t >= 0 && t < static_cast<int>(m_dict.size()) && m_dict[t] >= 0;
-    }
-
-    int order() const { return m_backoff_order; }
-    void order(int o) { 
-      if (o >= (int)m_terms_at_order.size())
-        m_terms_at_order.resize(o, 0);
-      m_backoff_order = o; 
-    }
-
-//    int levels() const { return m_terms_at_order.size(); }
-    bool is_null(const Term& term) const { return term < 0; }
-    int terms_at_level(int level) const { 
-      assert (level < (int)m_terms_at_order.size());
-      return m_terms_at_order.at(level);
-    }
-
-    int& terms_at_level(int level) { 
-      assert (level < (int)m_terms_at_order.size());
-      return m_terms_at_order.at(level);
-    }
-
-    int size() const { return m_dict.size(); }
-
-protected:
-    dictionary_type m_dict; 
-    int m_backoff_order;
-    std::vector<int> m_terms_at_order;
-};
-typedef boost::shared_ptr<TermBackoff> TermBackoffPtr;
-
-#endif // _CORPUS_HH
diff --git a/gi/pyp-topics/src/gammadist.c b/gi/pyp-topics/src/gammadist.c
deleted file mode 100644
index 4e260db8..00000000
--- a/gi/pyp-topics/src/gammadist.c
+++ /dev/null
@@ -1,247 +0,0 @@
-/* gammadist.c -- computes probability of samples under / produces samples from a Gamma distribution
- *
- * Mark Johnson, 22nd March 2008
- *
- * WARNING: you need to set the flag -std=c99 to compile
- *
- * gammavariate() was translated from random.py in Python library
- *
- * The Gamma distribution is:
- *
- *   Gamma(x | alpha, beta) = pow(x/beta, alpha-1) * exp(-x/beta) / (gamma(alpha)*beta)
- *
- * shape parameter alpha > 0 (also called c), scale parameter beta > 0 (also called s); 
- * mean is alpha*beta, variance is alpha*beta**2
- *
- * Note that many parameterizations of the Gamma function are in terms of an _inverse_
- * scale parameter beta, which is the inverse of the beta given here.
- *
- * To define a main() that tests the routines, uncomment the following #define:
- */
-/* #define GAMMATEST */
-
-#include <assert.h>
-#include <math.h> 
-
-#include "gammadist.h"
-#include "mt19937ar.h"
-
-/* gammadist() returns the probability density of x under a Gamma(alpha,beta) 
- * distribution
- */
-
-long double gammadist(long double x, long double alpha, long double beta) {
-  assert(alpha > 0);
-  assert(beta > 0);
-  return  pow(x/beta, alpha-1) * exp(-x/beta) / (tgamma(alpha)*beta);
-}
-
-/* lgammadist() returns the log probability density of x under a Gamma(alpha,beta)
- * distribution
- */
-
-long double lgammadist(long double x, long double alpha, long double beta) {
-  assert(alpha > 0);
-  assert(beta > 0);
-  return (alpha-1)*log(x) - alpha*log(beta) - x/beta - lgamma(alpha);
-}
-
-/* This definition of gammavariate is from Python code in
- * the Python random module.
- */
-
-long double gammavariate(long double alpha, long double beta) {
-
-  assert(alpha > 0);
-  assert(beta > 0);
-
-  if (alpha > 1.0) {
-    
-    /* Uses R.C.H. Cheng, "The generation of Gamma variables with
-       non-integral shape parameters", Applied Statistics, (1977), 26,
-       No. 1, p71-74 */
-
-    long double ainv = sqrt(2.0 * alpha - 1.0);
-    long double bbb = alpha - log(4.0);
-    long double ccc = alpha + ainv;
-    
-    while (1) {
-      long double u1 = mt_genrand_real3();
-      if (u1 > 1e-7  || u1 < 0.9999999) {
-	long double u2 = 1.0 - mt_genrand_real3();
-	long double v = log(u1/(1.0-u1))/ainv;
-	long double x = alpha*exp(v);
-	long double z = u1*u1*u2;
-	long double r = bbb+ccc*v-x;
-	if (r + (1.0+log(4.5)) - 4.5*z >= 0.0 || r >= log(z))
-	  return x * beta;
-      }
-    }
-  }
-  else if (alpha == 1.0) {
-    long double u = mt_genrand_real3();
-    while (u <= 1e-7)
-      u = mt_genrand_real3();
-    return -log(u) * beta;
-  }
-  else { 
-    /* alpha is between 0 and 1 (exclusive) 
-       Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle */
-    
-    while (1) {
-      long double u = mt_genrand_real3();
-      long double b = (exp(1) + alpha)/exp(1);
-      long double p = b*u;
-      long double x = (p <= 1.0) ? pow(p, 1.0/alpha) : -log((b-p)/alpha);
-      long double u1 = mt_genrand_real3();
-      if (! (((p <= 1.0) && (u1 > exp(-x))) ||
-	     ((p > 1.0)  &&  (u1 > pow(x, alpha - 1.0)))))
-	return x * beta;
-    }
-  }
-}
-
-/* betadist() returns the probability density of x under a Beta(alpha,beta)
- * distribution.
- */
-
-long double betadist(long double x, long double alpha, long double beta) {
-  assert(x >= 0);
-  assert(x <= 1);
-  assert(alpha > 0);
-  assert(beta > 0);
-  return pow(x,alpha-1)*pow(1-x,beta-1)*tgamma(alpha+beta)/(tgamma(alpha)*tgamma(beta));
-}
-
-/* lbetadist() returns the log probability density of x under a Beta(alpha,beta)
- * distribution.
- */
-
-long double lbetadist(long double x, long double alpha, long double beta) {
-  assert(x > 0);
-  assert(x < 1);
-  assert(alpha > 0);
-  assert(beta > 0);
-  return (alpha-1)*log(x)+(beta-1)*log(1-x)+lgamma(alpha+beta)-lgamma(alpha)-lgamma(beta);
-}
-
-/* betavariate() generates a sample from a Beta distribution with
- * parameters alpha and beta.
- *
- * 0 < alpha < 1, 0 < beta < 1, mean is alpha/(alpha+beta)
- */
-
-long double betavariate(long double alpha, long double beta) {
-  long double x = gammavariate(alpha, 1);
-  long double y = gammavariate(beta, 1);
-  return x/(x+y);
-}
-
-#ifdef GAMMATEST
-#include <stdio.h>
-
-int main(int argc, char **argv) {
-  int iteration, niterations = 1000;
-
-  for (iteration = 0; iteration < niterations; ++iteration) {
-    long double alpha = 100*mt_genrand_real3();
-    long double gv = gammavariate(alpha, 1);
-    long double pgv = gammadist(gv, alpha, 1);
-    long double pgvl = exp(lgammadist(gv, alpha, 1));
-    fprintf(stderr, "iteration = %d, gammavariate(%lg,1) = %lg, gammadist(%lg,%lg,1) = %lg, exp(lgammadist(%lg,%lg,1) = %lg\n",
-	    iteration, alpha, gv, gv, alpha, pgv, gv, alpha, pgvl);
-  }
-  return 0;
-}
-
-#endif /* GAMMATEST */
-
-
-/* Other routines I tried, but which weren't as good as the ones above */
-
-#if 0
-
-/*! gammavariate() returns samples from a Gamma distribution
- *! where alpha is the shape parameter and beta is the scale 
- *! parameter, using the algorithm described on p. 94 of 
- *! Gentle (1998) Random Number Generation and Monte Carlo Methods, 
- *! Springer.
- */
-
-long double gammavariate(long double alpha) {
-
-  assert(alpha > 0); 
-  
-  if (alpha > 1.0) {
-    while (1) {
-      long double u1 = mt_genrand_real3();
-      long double u2 = mt_genrand_real3();
-      long double v = (alpha - 1/(6*alpha))*u1/(alpha-1)*u2;
-      if (2*(u2-1)/(alpha-1) + v + 1/v <= 2 
-         || 2*log(u2)/(alpha-1) - log(v) + v <= 1)
-	return (alpha-1)*v;
-    }
-  } else if (alpha < 1.0) {  
-    while (1) {
-      long double t = 0.07 + 0.75*sqrt(1-alpha);
-      long double b = alpha + exp(-t)*alpha/t;
-      long double u1 = mt_genrand_real3();
-      long double u2 = mt_genrand_real3();
-      long double v = b*u1;
-      if (v <= 1) {
-	long double x = t*pow(v, 1/alpha);
-	if (u2 <= (2 - x)/(2 + x))
-	  return x;
-	if (u2 <= exp(-x))
-	  return x;
-      }
-      else {
-	long double x = log(t*(b-v)/alpha);
-	long double y = x/t;
-	if (u2*(alpha + y*(1-alpha)) <= 1)
-	  return x;
-	if (u2 <= pow(y,alpha-1))
-	  return x;
-      }
-    }
-  }
-  else  
-    return -log(mt_genrand_real3());
-} 
-
-
-/*! gammavariate() returns a deviate distributed as a gamma
- *! distribution of order alpha, beta, i.e., a waiting time to the alpha'th
- *! event in a Poisson process of unit mean.
- *!
- *! Code from Numerical Recipes
- */
-
-long double nr_gammavariate(long double ia) {
-  int j;
-  long double am,e,s,v1,v2,x,y;
-  assert(ia > 0);
-  if (ia < 10) { 
-    x=1.0; 
-    for (j=1;j<=ia;j++) 
-      x *= mt_genrand_real3();
-    x = -log(x);
-  } else { 
-    do {
-      do {
-	do { 
-	  v1=mt_genrand_real3();
-	  v2=2.0*mt_genrand_real3()-1.0;
-	} while (v1*v1+v2*v2 > 1.0); 
-	y=v2/v1;
-	am=ia-1;
-	s=sqrt(2.0*am+1.0);
-	x=s*y+am;
-      } while (x <= 0.0);
-      e=(1.0+y*y)*exp(am*log(x/am)-s*y);
-    } while (mt_genrand_real3() > e);
-  }
-  return x;
-} 
-
-#endif
diff --git a/gi/pyp-topics/src/gammadist.h b/gi/pyp-topics/src/gammadist.h
deleted file mode 100644
index b6ad6c40..00000000
--- a/gi/pyp-topics/src/gammadist.h
+++ /dev/null
@@ -1,72 +0,0 @@
-/* gammadist.h -- computes probability of samples under / produces samples from a Gamma distribution
- *
- * Mark Johnson, 22nd March 2008
- *
- * gammavariate() was translated from random.py in Python library
- *
- * The Gamma distribution is:
- *
- *   Gamma(x | alpha, beta) = pow(x/beta, alpha-1) * exp(-x/beta) / (gamma(alpha)*beta)
- *
- * shape parameter alpha > 0 (also called c), scale parameter beta > 0 (also called s); 
- * mean is alpha*beta, variance is alpha*beta**2
- *
- * Note that many parameterizations of the Gamma function are in terms of an _inverse_
- * scale parameter beta, which is the inverse of the beta given here.
- */
-
-#ifndef GAMMADIST_H
-#define GAMMADIST_H
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-  
-  /* gammadist() returns the probability density of x under a Gamma(alpha,beta) 
-   * distribution
-   */
-
-  long double gammadist(long double x, long double alpha, long double beta);
-
-  /* lgammadist() returns the log probability density of x under a Gamma(alpha,beta)
-   * distribution
-   */
-
-  long double lgammadist(long double x, long double alpha, long double beta);
-
-  /* gammavariate() generates samples from a Gamma distribution
-   * conditioned on the parameters alpha and beta.
-   * 
-   * alpha > 0, beta > 0, mean is alpha*beta, variance is alpha*beta**2
-   *
-   * Warning: a few older sources define the gamma distribution in terms
-   * of alpha > -1.0
-   */
-
-  long double gammavariate(long double alpha, long double beta);
-
-  /* betadist() returns the probability density of x under a Beta(alpha,beta)
-   * distribution.
-   */
-
-  long double betadist(long double x, long double alpha, long double beta);
-
-  /* lbetadist() returns the log probability density of x under a Beta(alpha,beta)
-   * distribution.
-   */
-  
-  long double lbetadist(long double x, long double alpha, long double beta);
-
-  /* betavariate() generates a sample from a Beta distribution with
-   * parameters alpha and beta.
-   *
-   * 0 < alpha < 1, 0 < beta < 1, mean is alpha/(alpha+beta)
-   */
-
-  long double betavariate(long double alpha, long double beta);
-
-#ifdef __cplusplus
-};
-#endif
-
-#endif /* GAMMADIST_H */
diff --git a/gi/pyp-topics/src/gzstream.cc b/gi/pyp-topics/src/gzstream.cc
deleted file mode 100644
index 7c4d3a12..00000000
--- a/gi/pyp-topics/src/gzstream.cc
+++ /dev/null
@@ -1,165 +0,0 @@
-// ============================================================================
-// gzstream, C++ iostream classes wrapping the zlib compression library.
-// Copyright (C) 2001  Deepak Bandyopadhyay, Lutz Kettner
-//
-// This library is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 2.1 of the License, or (at your option) any later version.
-//
-// This library is distributed in the hope that it will be useful,
-// but WITHOUT ANY WARRANTY; without even the implied warranty of
-// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-// Lesser General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License along with this library; if not, write to the Free Software
-// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
-// ============================================================================
-//
-// File          : gzstream.C
-// Revision      : $Revision: 1.1 $
-// Revision_date : $Date: 2006/03/30 04:05:52 $
-// Author(s)     : Deepak Bandyopadhyay, Lutz Kettner
-// 
-// Standard streambuf implementation following Nicolai Josuttis, "The 
-// Standard C++ Library".
-// ============================================================================
-
-#include "gzstream.hh"
-#include <iostream>
-#include <string.h>  // for memcpy
-
-#ifdef GZSTREAM_NAMESPACE
-namespace GZSTREAM_NAMESPACE {
-#endif
-
-// ----------------------------------------------------------------------------
-// Internal classes to implement gzstream. See header file for user classes.
-// ----------------------------------------------------------------------------
-
-// --------------------------------------
-// class gzstreambuf:
-// --------------------------------------
-
-gzstreambuf* gzstreambuf::open( const char* name, int open_mode) {
-    if ( is_open())
-        return (gzstreambuf*)0;
-    mode = open_mode;
-    // no append nor read/write mode
-    if ((mode & std::ios::ate) || (mode & std::ios::app)
-        || ((mode & std::ios::in) && (mode & std::ios::out)))
-        return (gzstreambuf*)0;
-    char  fmode[10];
-    char* fmodeptr = fmode;
-    if ( mode & std::ios::in)
-        *fmodeptr++ = 'r';
-    else if ( mode & std::ios::out)
-        *fmodeptr++ = 'w';
-    *fmodeptr++ = 'b';
-    *fmodeptr = '\0';
-    file = gzopen( name, fmode);
-    if (file == 0)
-        return (gzstreambuf*)0;
-    opened = 1;
-    return this;
-}
-
-gzstreambuf * gzstreambuf::close() {
-    if ( is_open()) {
-        sync();
-        opened = 0;
-        if ( gzclose( file) == Z_OK)
-            return this;
-    }
-    return (gzstreambuf*)0;
-}
-
-int gzstreambuf::underflow() { // used for input buffer only
-    if ( gptr() && ( gptr() < egptr()))
-        return * reinterpret_cast<unsigned char *>( gptr());
-
-    if ( ! (mode & std::ios::in) || ! opened)
-        return EOF;
-    // Josuttis' implementation of inbuf
-    int n_putback = gptr() - eback();
-    if ( n_putback > 4)
-        n_putback = 4;
-    memcpy( buffer + (4 - n_putback), gptr() - n_putback, n_putback);
-
-    int num = gzread( file, buffer+4, bufferSize-4);
-    if (num <= 0) // ERROR or EOF
-        return EOF;
-
-    // reset buffer pointers
-    setg( buffer + (4 - n_putback),   // beginning of putback area
-          buffer + 4,                 // read position
-          buffer + 4 + num);          // end of buffer
-
-    // return next character
-    return * reinterpret_cast<unsigned char *>( gptr());    
-}
-
-int gzstreambuf::flush_buffer() {
-    // Separate the writing of the buffer from overflow() and
-    // sync() operation.
-    int w = pptr() - pbase();
-    if ( gzwrite( file, pbase(), w) != w)
-        return EOF;
-    pbump( -w);
-    return w;
-}
-
-int gzstreambuf::overflow( int c) { // used for output buffer only
-    if ( ! ( mode & std::ios::out) || ! opened)
-        return EOF;
-    if (c != EOF) {
-        *pptr() = c;
-        pbump(1);
-    }
-    if ( flush_buffer() == EOF)
-        return EOF;
-    return c;
-}
-
-int gzstreambuf::sync() {
-    // Changed to use flush_buffer() instead of overflow( EOF)
-    // which caused improper behavior with std::endl and flush(),
-    // bug reported by Vincent Ricard.
-    if ( pptr() && pptr() > pbase()) {
-        if ( flush_buffer() == EOF)
-            return -1;
-    }
-    return 0;
-}
-
-// --------------------------------------
-// class gzstreambase:
-// --------------------------------------
-
-gzstreambase::gzstreambase( const char* name, int mode) {
-    init( &buf);
-    open( name, mode);
-}
-
-gzstreambase::~gzstreambase() {
-    buf.close();
-}
-
-void gzstreambase::open( const char* name, int open_mode) {
-    if ( ! buf.open( name, open_mode))
-        clear( rdstate() | std::ios::badbit);
-}
-
-void gzstreambase::close() {
-    if ( buf.is_open())
-        if ( ! buf.close())
-            clear( rdstate() | std::ios::badbit);
-}
-
-#ifdef GZSTREAM_NAMESPACE
-} // namespace GZSTREAM_NAMESPACE
-#endif
-
-// ============================================================================
-// EOF //
diff --git a/gi/pyp-topics/src/gzstream.hh b/gi/pyp-topics/src/gzstream.hh
deleted file mode 100644
index ad9785fd..00000000
--- a/gi/pyp-topics/src/gzstream.hh
+++ /dev/null
@@ -1,121 +0,0 @@
-// ============================================================================
-// gzstream, C++ iostream classes wrapping the zlib compression library.
-// Copyright (C) 2001  Deepak Bandyopadhyay, Lutz Kettner
-//
-// This library is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 2.1 of the License, or (at your option) any later version.
-//
-// This library is distributed in the hope that it will be useful,
-// but WITHOUT ANY WARRANTY; without even the implied warranty of
-// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-// Lesser General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License along with this library; if not, write to the Free Software
-// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
-// ============================================================================
-//
-// File          : gzstream.h
-// Revision      : $Revision: 1.1 $
-// Revision_date : $Date: 2006/03/30 04:05:52 $
-// Author(s)     : Deepak Bandyopadhyay, Lutz Kettner
-// 
-// Standard streambuf implementation following Nicolai Josuttis, "The 
-// Standard C++ Library".
-// ============================================================================
-
-#ifndef GZSTREAM_H
-#define GZSTREAM_H 1
-
-// standard C++ with new header file names and std:: namespace
-#include <iostream>
-#include <fstream>
-#include <zlib.h>
-
-#ifdef GZSTREAM_NAMESPACE
-namespace GZSTREAM_NAMESPACE {
-#endif
-
-// ----------------------------------------------------------------------------
-// Internal classes to implement gzstream. See below for user classes.
-// ----------------------------------------------------------------------------
-
-class gzstreambuf : public std::streambuf {
-private:
-    static const int bufferSize = 47+256;    // size of data buff
-    // totals 512 bytes under g++ for igzstream at the end.
-
-    gzFile           file;               // file handle for compressed file
-    char             buffer[bufferSize]; // data buffer
-    char             opened;             // open/close state of stream
-    int              mode;               // I/O mode
-
-    int flush_buffer();
-public:
-    gzstreambuf() : opened(0) {
-        setp( buffer, buffer + (bufferSize-1));
-        setg( buffer + 4,     // beginning of putback area
-              buffer + 4,     // read position
-              buffer + 4);    // end position      
-        // ASSERT: both input & output capabilities will not be used together
-    }
-    int is_open() { return opened; }
-    gzstreambuf* open( const char* name, int open_mode);
-    gzstreambuf* close();
-    ~gzstreambuf() { close(); }
-    
-    virtual int     overflow( int c = EOF);
-    virtual int     underflow();
-    virtual int     sync();
-};
-
-class gzstreambase : virtual public std::ios {
-protected:
-    gzstreambuf buf;
-public:
-    gzstreambase() { init(&buf); }
-    gzstreambase( const char* name, int open_mode);
-    ~gzstreambase();
-    void open( const char* name, int open_mode);
-    void close();
-    gzstreambuf* rdbuf() { return &buf; }
-};
-
-// ----------------------------------------------------------------------------
-// User classes. Use igzstream and ogzstream analogously to ifstream and
-// ofstream respectively. They read and write files based on the gz* 
-// function interface of the zlib. Files are compatible with gzip compression.
-// ----------------------------------------------------------------------------
-
-class igzstream : public gzstreambase, public std::istream {
-public:
-    igzstream() : std::istream( &buf) {} 
-    igzstream( const char* name, int open_mode = std::ios::in)
-        : gzstreambase( name, open_mode), std::istream( &buf) {}  
-    gzstreambuf* rdbuf() { return gzstreambase::rdbuf(); }
-    void open( const char* name, int open_mode = std::ios::in) {
-        gzstreambase::open( name, open_mode);
-    }
-};
-
-class ogzstream : public gzstreambase, public std::ostream {
-public:
-    ogzstream() : std::ostream( &buf) {}
-    ogzstream( const char* name, int mode = std::ios::out)
-        : gzstreambase( name, mode), std::ostream( &buf) {}  
-    gzstreambuf* rdbuf() { return gzstreambase::rdbuf(); }
-    void open( const char* name, int open_mode = std::ios::out) {
-        gzstreambase::open( name, open_mode);
-    }
-};
-
-#ifdef GZSTREAM_NAMESPACE
-} // namespace GZSTREAM_NAMESPACE
-#endif
-
-#endif // GZSTREAM_H
-// ============================================================================
-// EOF //
-
diff --git a/gi/pyp-topics/src/log_add.h b/gi/pyp-topics/src/log_add.h
deleted file mode 100644
index e0620c5a..00000000
--- a/gi/pyp-topics/src/log_add.h
+++ /dev/null
@@ -1,30 +0,0 @@
-#ifndef log_add_hh
-#define log_add_hh
-
-#include <limits>
-#include <iostream>
-#include <cassert>
-#include <cmath>
-
-template <typename T>
-struct Log
-{
-    static T zero() { return -std::numeric_limits<T>::infinity(); } 
-
-    static T add(T l1, T l2)
-    {
-        if (l1 == zero()) return l2;
-        if (l1 > l2) 
-            return l1 + std::log(1 + exp(l2 - l1));
-        else
-            return l2 + std::log(1 + exp(l1 - l2));
-    }
-
-    static T subtract(T l1, T l2)
-    {
-        //std::assert(l1 >= l2);
-        return l1 + log(1 - exp(l2 - l1));
-    }
-};
-
-#endif
diff --git a/gi/pyp-topics/src/macros.Linux b/gi/pyp-topics/src/macros.Linux
deleted file mode 100644
index 7c6e7fa7..00000000
--- a/gi/pyp-topics/src/macros.Linux
+++ /dev/null
@@ -1,18 +0,0 @@
-CC = /home/pblunsom/software/bin/mpicc
-CXX = /home/pblunsom/software/bin/mpicxx
-LD = /home/pblunsom/software/bin/mpicxx
-FC = /home/pblunsom/software/bin/mpif77
-
-SOFTWARE_DIR=/export/ws10smt/software
-
-CXXFLAGS = -Wall -I${SOFTWARE_DIR}/include
-CFLAGS = -Wall -I${SOFTWARE_DIR}/include
-FFLAGS = -Wall
-LDFLAGS = -lm -lz -L${SOFTWARE_DIR}/lib \
-	-lboost_program_options -lboost_mpi -lboost_serialization \
-  -lboost_regex -L../../../decoder -lcdec
-
-FFLAGS += -g -O6  -march=native
-CFLAGS += -g -O6  -march=native
-CXXFLAGS += -g -O6  -march=native
-LDFLAGS += -g -O6  -march=native
diff --git a/gi/pyp-topics/src/makefile.darwin b/gi/pyp-topics/src/makefile.darwin
deleted file mode 100644
index af608fd8..00000000
--- a/gi/pyp-topics/src/makefile.darwin
+++ /dev/null
@@ -1,15 +0,0 @@
-CC = /usr/bin/gcc
-CXX = /usr/bin/g++
-LD = /usr/bin/g++
-FC=/usr/bin/g77
-
-ARCH=i686-m64
-CXXFLAGS = -m64 -Wall -I/Users/pblunsom/packages/include 
-CFLAGS = -m64 -Wall -I/Users/pblunsom/packages/include 
-FFLAGS = -m64 -Wall
-LDFLAGS = -L/Users/pblunsom/packages/lib -lboost_program_options -lm -lz
-
-FFLAGS += -g -O3 -funroll-loops #-pg
-CFLAGS += -g -O3 -funroll-loops #-pg
-CXXFLAGS += -g -O3 -funroll-loops #-pg
-LDFLAGS += -g -O3 -funroll-loops #-pg
diff --git a/gi/pyp-topics/src/makefile.depend b/gi/pyp-topics/src/makefile.depend
deleted file mode 100644
index 9b8e306c..00000000
--- a/gi/pyp-topics/src/makefile.depend
+++ /dev/null
@@ -1,4042 +0,0 @@
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- /home/pblunsom/packages/include/boost/thread/condition.hpp timing.h \
- clock_gettime_stub.c contexts_corpus.hh contexts_lexer.h \
- ../../../decoder/dict.h \
- /home/pblunsom/packages/include/boost/functional/hash.hpp \
- /home/pblunsom/packages/include/boost/functional/hash/hash.hpp \
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- ../../../decoder/wordid.h gzstream.hh
-clock_gettime_stub.o: clock_gettime_stub.c
-gammadist.o: gammadist.c gammadist.h mt19937ar.h
-mt19937ar.o: mt19937ar.c mt19937ar.h
diff --git a/gi/pyp-topics/src/mpi-corpus.hh b/gi/pyp-topics/src/mpi-corpus.hh
deleted file mode 100644
index f5c478a9..00000000
--- a/gi/pyp-topics/src/mpi-corpus.hh
+++ /dev/null
@@ -1,69 +0,0 @@
-#ifndef _MPI_CORPUS_HH
-#define _MPI_CORPUS_HH
-
-#include <vector>
-#include <string>
-#include <map>
-#include <tr1/unordered_map>
-
-#include <boost/ptr_container/ptr_vector.hpp>
-#include <boost/mpi/environment.hpp>
-#include <boost/mpi/communicator.hpp>
-
-#include "contexts_corpus.hh"
-
-
-////////////////////////////////////////////////////////////////
-// MPICorpus
-////////////////////////////////////////////////////////////////
-
-class MPICorpus : public ContextsCorpus {
-public:
-  MPICorpus() : ContextsCorpus() {
-    boost::mpi::communicator world;
-    m_rank = world.rank();
-    m_size = world.size();
-    m_start = -1;
-    m_end = -1;
-  }
-  virtual ~MPICorpus() {}
-
-  virtual unsigned read_contexts(const std::string &filename, 
-                                 BackoffGenerator* backoff_gen=0,
-                                 bool filter_singeltons=false,
-                                 bool binary_contexts=false) {
-    unsigned result = ContextsCorpus::read_contexts(filename, backoff_gen, filter_singeltons, binary_contexts);
-
-    if (m_rank == 0) std::cerr << "\tLoad balancing terms per mpi segment:" << std::endl;
-    float segment_size = num_terms() / m_size;
-    float term_threshold = segment_size;
-    int seen_terms = 0;
-    std::vector<int> end_points;
-    for (int i=0; i < num_documents(); ++i) {
-      seen_terms += m_documents.at(i).size();
-      if (seen_terms >= term_threshold) {
-        end_points.push_back(i+1);
-        term_threshold += segment_size;
-        if (m_rank == 0) std::cerr << "\t\t" << i+1 << ": " <<  seen_terms << " terms, " << 100*seen_terms / (float)num_terms() << "%" << std::endl;
-      }
-    }
-    m_start = (m_rank == 0 ? 0 : end_points.at(m_rank-1));
-    m_end = (m_rank == m_size-1 ? num_documents() : end_points.at(m_rank));
-
-    return result;
-  }
-
-  void
-  bounds(int* start, int* end) const {
-    *start = m_start;
-    *end = m_end;
-  }
-
-
-
-protected:
-  int m_rank, m_size;
-  int m_start, m_end;
-};
-
-#endif // _MPI_CORPUS_HH
diff --git a/gi/pyp-topics/src/mpi-pyp-topics.cc b/gi/pyp-topics/src/mpi-pyp-topics.cc
deleted file mode 100644
index d6e22af6..00000000
--- a/gi/pyp-topics/src/mpi-pyp-topics.cc
+++ /dev/null
@@ -1,466 +0,0 @@
-#include <boost/mpi/communicator.hpp>
-
-#include "timing.h"
-#include "mpi-pyp-topics.hh"
-
-//#include <boost/date_time/posix_time/posix_time_types.hpp>
-void MPIPYPTopics::sample_corpus(const MPICorpus& corpus, int samples,
-                              int freq_cutoff_start, int freq_cutoff_end,
-                              int freq_cutoff_interval,
-                              int max_contexts_per_document) {
-  Timer timer;
-
-  //int documents = corpus.num_documents();
-  /*
-  m_mpi_start = 0;
-  m_mpi_end = documents;
-  if (m_size != 1) {
-      assert(documents < std::numeric_limits<int>::max());
-      m_mpi_start = (documents / m_size) * m_rank;
-      if (m_rank == m_size-1) m_mpi_end = documents;
-      else m_mpi_end = (documents / m_size)*(m_rank+1);
-  }
-  */
-  corpus.bounds(&m_mpi_start, &m_mpi_end);
-  int local_documents = m_mpi_end - m_mpi_start;
-
-  if (!m_backoff.get()) {
-    m_word_pyps.clear();
-    m_word_pyps.push_back(MPIPYPs());
-  }
-
-  if (m_am_root) std::cerr << "\n Training with " << m_word_pyps.size()-1 << " backoff level"
-    << (m_word_pyps.size()>1 ? ":" : "s:") << std::endl;
-
-  for (int i=0; i<(int)m_word_pyps.size(); ++i) {
-    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 MPIPYP<int>(0.5, 1.0));
-  }
-  if (m_am_root) std::cerr << std::endl;
-
-  m_document_pyps.reserve(local_documents);
-  //m_document_pyps.reserve(corpus.num_documents());
-  //for (int j=0; j<corpus.num_documents(); ++j)
-  for (int j=0; j<local_documents; ++j)
-    m_document_pyps.push_back(new PYP<int>(0.5, 1.0));
-
-  m_topic_p0 = 1.0/m_num_topics;
-  m_term_p0 = 1.0/corpus.num_types();
-  m_backoff_p0 = 1.0/corpus.num_documents();
-
-  if (m_am_root) std::cerr << " Documents: " << corpus.num_documents() << "(" 
-    << local_documents << ")" << " Terms: " << corpus.num_types() << std::endl;
-
-  int frequency_cutoff = freq_cutoff_start;
-  if (m_am_root) std::cerr << " Context frequency cutoff set to " << frequency_cutoff << std::endl;
-
-  timer.Reset();
-  // Initialisation pass
-  int document_id=0, topic_counter=0;
-  for (int i=0; i<local_documents; ++i) {
-    document_id = i+m_mpi_start;
-
-  //for (Corpus::const_iterator corpusIt=corpus.begin();
-  //     corpusIt != corpus.end(); ++corpusIt, ++document_id) {
-    m_corpus_topics.push_back(DocumentTopics(corpus.at(document_id).size(), 0));
-
-    int term_index=0;
-    for (Document::const_iterator docIt=corpus.at(document_id).begin();
-         docIt != corpus.at(document_id).end(); ++docIt, ++term_index) {
-      topic_counter++;
-      Term term = *docIt;
-
-      // sample a new_topic
-      //int new_topic = (topic_counter % m_num_topics);
-      int freq = corpus.context_count(term);
-      int new_topic = -1;
-      if (freq > frequency_cutoff
-          && (!max_contexts_per_document || term_index < max_contexts_per_document)) {
-        new_topic = sample(i, term);
-        //new_topic = document_id % m_num_topics;
-
-        // add the new topic to the PYPs
-        increment(term, new_topic);
-
-        if (m_use_topic_pyp) {
-          F p0 = m_topic_pyp.prob(new_topic, m_topic_p0);
-          int table_delta = m_document_pyps.at(i).increment(new_topic, p0);
-          if (table_delta)
-            m_topic_pyp.increment(new_topic, m_topic_p0, rnd);
-        }
-        else m_document_pyps.at(i).increment(new_topic, m_topic_p0);
-      }
-
-      m_corpus_topics.at(i).at(term_index) = new_topic;
-    }
-  }
-
-  // Synchronise the topic->word counds across the processes.
-  synchronise();
-
-  if (m_am_root) std::cerr << "  Initialized in " << timer.Elapsed() << " seconds\n";
-
-  int* randomDocIndices = new int[local_documents];
-  for (int i = 0; i < local_documents; ++i)
-	  randomDocIndices[i] = i;
-
-  // Sampling phase
-  for (int curr_sample=0; curr_sample < samples; ++curr_sample) {
-    if (freq_cutoff_interval > 0 && curr_sample != 1
-        && curr_sample % freq_cutoff_interval == 1
-        && frequency_cutoff > freq_cutoff_end) {
-      frequency_cutoff--;
-      if (m_am_root) std::cerr << "\n Context frequency cutoff set to " << frequency_cutoff << std::endl;
-    }
-
-    if (m_am_root) std::cerr << "\n  -- Sample " << curr_sample << " "; std::cerr.flush();
-
-    // Randomize the corpus indexing array
-    int tmp;
-    int processed_terms=0;
-    for (int i = (local_documents-1); i > 0; --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;
-    }
-
-    // for each document in the corpus
-    for (int rand_doc=0; rand_doc<local_documents; ++rand_doc) {
-    	int doc_index = randomDocIndices[rand_doc];
-    	int document_id = doc_index + m_mpi_start;
-      const Document& doc = corpus.at(document_id);
-
-      // for each term in the document
-      int term_index=0;
-      Document::const_iterator docEnd = doc.end();
-      for (Document::const_iterator docIt=doc.begin();
-           docIt != docEnd; ++docIt, ++term_index) {
-
-        if (max_contexts_per_document && term_index > max_contexts_per_document)
-          break;
-        
-        Term term = *docIt;
-        int freq = corpus.context_count(term);
-        if (freq < frequency_cutoff)
-          continue;
-
-        processed_terms++;
-
-        // remove the prevous topic from the PYPs
-        int current_topic = m_corpus_topics.at(doc_index).at(term_index);
-        // a negative label mean that term hasn't been sampled yet
-        if (current_topic >= 0) {
-          decrement(term, current_topic);
-
-          int table_delta = m_document_pyps.at(doc_index).decrement(current_topic);
-          if (m_use_topic_pyp && table_delta < 0)
-            m_topic_pyp.decrement(current_topic, rnd);
-        }
-
-        // sample a new_topic
-        int new_topic = sample(doc_index, term);
-
-        // add the new topic to the PYPs
-        m_corpus_topics.at(doc_index).at(term_index) = new_topic;
-        increment(term, new_topic);
-
-        if (m_use_topic_pyp) {
-          F p0 = m_topic_pyp.prob(new_topic, m_topic_p0);
-          int table_delta = m_document_pyps.at(doc_index).increment(new_topic, p0);
-          if (table_delta)
-            m_topic_pyp.increment(new_topic, m_topic_p0, rnd);
-        }
-        else m_document_pyps.at(doc_index).increment(new_topic, m_topic_p0);
-      }
-      if (document_id && document_id % 10000 == 0) {
-        if (m_am_root) std::cerr << "."; std::cerr.flush();
-      }
-    }
-    std::cerr << "|"; std::cerr.flush();  
-
-    // Synchronise the topic->word counds across the processes.
-    synchronise();
-
-    if (m_am_root) std::cerr << " ||| sampled " << processed_terms << " terms.";
-
-    if (curr_sample != 0 && curr_sample % 10 == 0) {
-      if (m_am_root) std::cerr << " ||| time=" << (timer.Elapsed() / 10.0) << " sec/sample" << std::endl;
-      timer.Reset();
-      if (m_am_root) std::cerr << "     ... Resampling hyperparameters"; std::cerr.flush();
-
-      // resample the hyperparamters
-      F log_p=0.0;
-      for (std::vector<MPIPYPs>::iterator levelIt=m_word_pyps.begin();
-           levelIt != m_word_pyps.end(); ++levelIt) {
-        for (MPIPYPs::iterator pypIt=levelIt->begin();
-             pypIt != levelIt->end(); ++pypIt) {
-          pypIt->resample_prior(rnd);
-          log_p += pypIt->log_restaurant_prob();
-        }
-      }
-
-      for (PYPs::iterator pypIt=m_document_pyps.begin();
-           pypIt != m_document_pyps.end(); ++pypIt) {
-        pypIt->resample_prior(rnd);
-        log_p += pypIt->log_restaurant_prob();
-      }
-
-      if (m_use_topic_pyp) {
-        m_topic_pyp.resample_prior(rnd);
-        log_p += m_topic_pyp.log_restaurant_prob();
-      }
-
-      std::cerr.precision(10);
-      if (m_am_root) std::cerr << " ||| LLH=" << log_p << " ||| resampling time=" << timer.Elapsed() << " sec" << std::endl;
-      timer.Reset();
-
-      int k=0;
-      if (m_am_root) std::cerr << "Topics distribution: ";
-      std::cerr.precision(2);
-      for (MPIPYPs::iterator pypIt=m_word_pyps.front().begin();
-           pypIt != m_word_pyps.front().end(); ++pypIt, ++k) {
-        if (m_am_root && k % 5 == 0) std::cerr << std::endl << '\t';
-        if (m_am_root) std::cerr << "<" << k << ":" << pypIt->num_customers() << ","
-          << pypIt->num_types() << "," << m_topic_pyp.prob(k, m_topic_p0) << "> ";
-      }
-      std::cerr.precision(4);
-      if (m_am_root) std::cerr << std::endl;
-    }
-  }
-  delete [] randomDocIndices;
-}
-
-void MPIPYPTopics::synchronise() {
-  // Synchronise the topic->word counds across the processes.
-  //for (std::vector<MPIPYPs>::iterator levelIt=m_word_pyps.begin();
-  //     levelIt != m_word_pyps.end(); ++levelIt) {
-//  std::vector<MPIPYPs>::iterator levelIt=m_word_pyps.begin(); 
-//  {
-//    for (MPIPYPs::iterator pypIt=levelIt->begin(); pypIt != levelIt->end(); ++pypIt) {
-    for (size_t label=0; label < m_word_pyps.at(0).size(); ++label) {
-      MPIPYP<int>& pyp = m_word_pyps.at(0).at(label);
-
-      //if (!m_am_root) boost::mpi::communicator().barrier();
-      //std::cerr << "Before Sync Process " << m_rank << ":";
-      //pyp.debug_info(std::cerr); std::cerr << std::endl;
-      //if (m_am_root) boost::mpi::communicator().barrier();
-
-      MPIPYP<int>::dish_delta_type delta;
-      pyp.synchronise(&delta);
-
-      for (MPIPYP<int>::dish_delta_type::const_iterator it=delta.begin(); it != delta.end(); ++it) {
-        int count = it->second;
-        if (count > 0)
-          for (int i=0; i < count; ++i) increment(it->first, label);
-        if (count < 0)
-          for (int i=0; i > count; --i) decrement(it->first, label);
-      }
-      pyp.reset_deltas();
-
-      //if (!m_am_root) boost::mpi::communicator().barrier();
-      //std::cerr << "After Sync Process " << m_rank << ":";
-      //pyp.debug_info(std::cerr); std::cerr << std::endl;
-      //if (m_am_root) boost::mpi::communicator().barrier();
-    }
-//  }
-    // Synchronise the hierarchical topic pyp
-    MPIPYP<int>::dish_delta_type topic_delta;
-    m_topic_pyp.synchronise(&topic_delta);
-    for (MPIPYP<int>::dish_delta_type::const_iterator it=topic_delta.begin(); it != topic_delta.end(); ++it) {
-      int count = it->second;
-      if (count > 0)
-        for (int i=0; i < count; ++i) 
-          m_topic_pyp.increment(it->first, m_topic_p0, rnd);
-      if (count < 0)
-        for (int i=0; i > count; --i) 
-          m_topic_pyp.decrement(it->first, rnd);
-    }
-    m_topic_pyp.reset_deltas();
-}
-
-void MPIPYPTopics::decrement(const Term& term, int topic, int level) {
-  //std::cerr << "MPIPYPTopics::decrement(" << term << "," << topic << "," << level << ")" << std::endl;
-  m_word_pyps.at(level).at(topic).decrement(term, rnd);
-  if (m_backoff.get()) {
-    Term backoff_term = (*m_backoff)[term];
-    if (!m_backoff->is_null(backoff_term))
-      decrement(backoff_term, topic, level+1);
-  }
-}
-
-void MPIPYPTopics::increment(const Term& term, int topic, int level) {
-  //std::cerr << "MPIPYPTopics::increment(" << term << "," << topic << "," << level << ")" << std::endl;
-  m_word_pyps.at(level).at(topic).increment(term, word_pyps_p0(term, topic, level), rnd);
-
-  if (m_backoff.get()) {
-    Term backoff_term = (*m_backoff)[term];
-    if (!m_backoff->is_null(backoff_term))
-      increment(backoff_term, topic, level+1);
-  }
-}
-
-int MPIPYPTopics::sample(const DocumentId& doc, const Term& term) {
-  // First pass: collect probs
-  F sum=0.0;
-  std::vector<F> sums;
-  for (int k=0; k<m_num_topics; ++k) {
-    F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp) topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    //F p_k_d = m_document_pyps[doc].prob(k, topic_prob);
-    F p_k_d = m_document_pyps.at(doc).unnormalised_prob(k, topic_prob);
-
-    sum += (p_w_k*p_k_d);
-    sums.push_back(sum);
-  }
-  // Second pass: sample a topic
-  F cutoff = rnd() * sum;
-  for (int k=0; k<m_num_topics; ++k) {
-    if (cutoff <= sums[k])
-      return k;
-  }
-  std::cerr << cutoff << " " << sum << std::endl;
-  assert(false);
-}
-
-MPIPYPTopics::F MPIPYPTopics::word_pyps_p0(const Term& term, int topic, int level) const {
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "MPIPYPTopics::word_pyps_p0(" << term << "," << topic << "," << level << ")" << std::endl;
-
-  F p0 = m_term_p0;
-  if (m_backoff.get()) {
-    //static F fudge=m_backoff_p0; // TODO
-
-    Term backoff_term = (*m_backoff)[term];
-    if (!m_backoff->is_null(backoff_term)) {
-      assert (level < m_backoff->order());
-      //p0 = (1.0/(double)m_backoff->terms_at_level(level))*prob(backoff_term, topic, level+1);
-      p0 = prob(backoff_term, topic, level+1);
-    }
-    else
-      p0 = m_term_p0;
-  }
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "MPIPYPTopics::word_pyps_p0(" << term << "," << topic << "," << level << ") = " << p0 << std::endl;
-  return p0;
-}
-
-MPIPYPTopics::F MPIPYPTopics::prob(const Term& term, int topic, int level) const {
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "MPIPYPTopics::prob(" << term << "," << topic << "," << level << " " << factor << ")" << std::endl;
-
-  F p0 = word_pyps_p0(term, topic, level);
-  F p_w_k = m_word_pyps.at(level).at(topic).prob(term, p0);
-
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "MPIPYPTopics::prob(" << term << "," << topic << "," << level << ") = " << p_w_k << std::endl;
-
-  return p_w_k;
-}
-
-int MPIPYPTopics::max_topic() const {
-  if (!m_use_topic_pyp)
-    return -1;
-
-  F current_max=0.0;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    F prob = m_topic_pyp.prob(k, m_topic_p0);
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  assert(current_max >= 0);
-  return current_max;
-}
-
-std::pair<int,MPIPYPTopics::F> MPIPYPTopics::max(const DocumentId& true_doc) const {
-  //std::cerr << "MPIPYPTopics::max(" << doc << "," << term << ")" << std::endl;
-  // collect probs
-  F current_max=0.0;
-  DocumentId local_doc = true_doc - m_mpi_start;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    //F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp)
-      topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    F prob = 0;
-    if (local_doc < 0) prob = topic_prob;
-    else               prob = m_document_pyps.at(local_doc).prob(k, topic_prob);
-
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  assert(current_max >= 0);
-  return std::make_pair(current_topic, current_max);
-}
-
-std::pair<int,MPIPYPTopics::F> MPIPYPTopics::max(const DocumentId& true_doc, const Term& term) const {
-  //std::cerr << "MPIPYPTopics::max(" << doc << "," << term << ")" << std::endl;
-  // collect probs
-  F current_max=0.0;
-  DocumentId local_doc = true_doc - m_mpi_start;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp)
-      topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    F p_k_d = 0;
-    if (local_doc < 0) p_k_d = topic_prob;
-    else               p_k_d = m_document_pyps.at(local_doc).prob(k, topic_prob);
-
-    F prob = (p_w_k*p_k_d);
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  assert(current_max >= 0);
-  return std::make_pair(current_topic, current_max);
-}
-
-std::ostream& MPIPYPTopics::print_document_topics(std::ostream& out) const {
-  for (CorpusTopics::const_iterator corpusIt=m_corpus_topics.begin();
-       corpusIt != m_corpus_topics.end(); ++corpusIt) {
-    int term_index=0;
-    for (DocumentTopics::const_iterator docIt=corpusIt->begin();
-         docIt != corpusIt->end(); ++docIt, ++term_index) {
-      if (term_index) out << " ";
-      out << *docIt;
-    }
-    out << std::endl;
-  }
-  return out;
-}
-
-std::ostream& MPIPYPTopics::print_topic_terms(std::ostream& out) const {
-  for (PYPs::const_iterator pypsIt=m_word_pyps.front().begin();
-       pypsIt != m_word_pyps.front().end(); ++pypsIt) {
-    int term_index=0;
-    for (PYP<int>::const_iterator termIt=pypsIt->begin();
-         termIt != pypsIt->end(); ++termIt, ++term_index) {
-      if (term_index) out << " ";
-      out << termIt->first << ":" << termIt->second;
-    }
-    out << std::endl;
-  }
-  return out;
-}
diff --git a/gi/pyp-topics/src/mpi-pyp-topics.hh b/gi/pyp-topics/src/mpi-pyp-topics.hh
deleted file mode 100644
index d96bc4e5..00000000
--- a/gi/pyp-topics/src/mpi-pyp-topics.hh
+++ /dev/null
@@ -1,106 +0,0 @@
-#ifndef MPI_PYP_TOPICS_HH
-#define MPI_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 <boost/random/inversive_congruential.hpp>
-#include <boost/random/linear_congruential.hpp>
-#include <boost/random/lagged_fibonacci.hpp>
-#include <boost/mpi/environment.hpp>
-#include <boost/mpi/communicator.hpp>
-
-
-#include "mpi-pyp.hh"
-#include "mpi-corpus.hh"
-
-class MPIPYPTopics {
-public:
-  typedef std::vector<int> DocumentTopics;
-  typedef std::vector<DocumentTopics> CorpusTopics;
-  typedef double F;
-
-public:
-  MPIPYPTopics(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_seed(seed),
-    uni_dist(0,1), rng(seed == 0 ? (unsigned long)this : seed), 
-    rnd(rng, uni_dist), m_mpi_start(-1), m_mpi_end(-1) {
-      boost::mpi::communicator m_world;
-      m_rank = m_world.rank(); 
-      m_size = m_world.size();
-      m_am_root = (m_rank == 0);
-    }
-
-  void sample_corpus(const MPICorpus& corpus, int samples,
-                     int freq_cutoff_start=0, int freq_cutoff_end=0, 
-                     int freq_cutoff_interval=0,
-                     int max_contexts_per_document=0);
-
-  int sample(const DocumentId& doc, const Term& term);
-  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(), MPIPYPs());
-  }
-  void set_backoff(TermBackoffPtr backoff) {
-    m_backoff = backoff;
-    m_word_pyps.clear();
-    m_word_pyps.resize(m_backoff->order(), MPIPYPs());
-  }
-
-  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);
-
-  std::ostream& print_document_topics(std::ostream& out) const;
-  std::ostream& print_topic_terms(std::ostream& out) const;
-
-  void synchronise();
-
-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;
-  typedef boost::ptr_vector< MPIPYP<int> > MPIPYPs;
-  PYPs m_document_pyps;
-  std::vector<MPIPYPs> m_word_pyps;
-  MPIPYP<int> m_topic_pyp;
-  bool m_use_topic_pyp;
-
-  unsigned long m_seed;
-
-  //typedef boost::mt19937 base_generator_type;
-  //typedef boost::hellekalek1995 base_generator_type;
-  typedef boost::lagged_fibonacci607 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;
-
-  boost::mpi::communicator m_world;
-  bool m_am_root;
-  int m_rank, m_size;
-  int m_mpi_start, m_mpi_end;
-};
-
-#endif // PYP_TOPICS_HH
diff --git a/gi/pyp-topics/src/mpi-pyp.hh b/gi/pyp-topics/src/mpi-pyp.hh
deleted file mode 100644
index c2341b9e..00000000
--- a/gi/pyp-topics/src/mpi-pyp.hh
+++ /dev/null
@@ -1,447 +0,0 @@
-#ifndef _mpipyp_hh
-#define _mpipyp_hh
-
-#include <math.h>
-#include <map>
-#include <tr1/unordered_map>
-//#include <google/sparse_hash_map>
-
-#include <boost/random/uniform_real.hpp>
-#include <boost/random/variate_generator.hpp>
-#include <boost/random/mersenne_twister.hpp>
-#include <boost/tuple/tuple.hpp>
-#include <boost/serialization/map.hpp>
-#include <boost/mpi.hpp>
-#include <boost/mpi/environment.hpp>
-#include <boost/mpi/communicator.hpp>
-#include <boost/mpi/operations.hpp>
-
-
-#include "pyp.hh"
-
-//
-// Pitman-Yor process with customer and table tracking
-//
-
-template <typename Dish, typename Hash=std::tr1::hash<Dish> >
-class MPIPYP : public PYP<Dish, Hash> {
-public:
-  typedef std::map<Dish, int> dish_delta_type;
-
-  MPIPYP(double a, double b, Hash hash=Hash());
-
-  template < typename Uniform01 >
-    int increment(Dish d, double p0, Uniform01& rnd);
-  template < typename Uniform01 >
-    int decrement(Dish d, Uniform01& rnd);
-
-  void clear();
-  void reset_deltas();
-
-  void synchronise(dish_delta_type* result);
-
-private:
-  typedef std::map<Dish, typename PYP<Dish,Hash>::TableCounter> table_delta_type;
-
-  dish_delta_type m_count_delta;
-  table_delta_type m_table_delta;
-};
-
-template <typename Dish, typename Hash>
-MPIPYP<Dish,Hash>::MPIPYP(double a, double b, Hash h)
-: PYP<Dish,Hash>(a, b, 0, h) {}
-
-template <typename Dish, typename Hash>
-  template <typename Uniform01>
-int 
-MPIPYP<Dish,Hash>::increment(Dish dish, double p0, Uniform01& rnd) {
-  //std::cerr << "-----INCREMENT DISH " << dish << std::endl;
-  int delta = 0;
-  int table_joined=-1;
-  typename PYP<Dish,Hash>::TableCounter &tc = PYP<Dish,Hash>::_dish_tables[dish];
-
-  // seated on a new or existing table?
-  int c = PYP<Dish,Hash>::count(dish); 
-  int t = PYP<Dish,Hash>::num_tables(dish); 
-  int T = PYP<Dish,Hash>::num_tables();
-  double& a = PYP<Dish,Hash>::_a;
-  double& b = PYP<Dish,Hash>::_b;
-  double pshare = (c > 0) ? (c - a*t) : 0.0;
-  double pnew = (b + a*T) * p0;
-  if (pshare < 0.0) {
-    std::cerr << pshare << " " << c << " " << a << " " << t << std::endl;
-    assert(false);
-  }
-
-  if (rnd() < pnew / (pshare + pnew)) {
-    // assign to a new table
-    tc.tables += 1;
-    tc.table_histogram[1] += 1;
-    PYP<Dish,Hash>::_total_tables += 1;
-    delta = 1;
-    table_joined = 1;
-  }
-  else {
-    // randomly assign to an existing table
-    // remove constant denominator from inner loop
-    double r = rnd() * (c - a*t);
-    for (std::map<int,int>::iterator
-         hit = tc.table_histogram.begin();
-         hit != tc.table_histogram.end(); ++hit) {
-      r -= ((hit->first - a) * hit->second);
-      if (r <= 0) {
-        tc.table_histogram[hit->first+1] += 1;
-        hit->second -= 1;
-        table_joined = hit->first+1;
-        if (hit->second == 0)
-          tc.table_histogram.erase(hit);
-        break;
-      }
-    }
-    if (r > 0) {
-      std::cerr << r << " " << c << " " << a << " " << t << std::endl;
-      assert(false);
-    }
-    delta = 0;
-  }
-
-  std::tr1::unordered_map<Dish,int,Hash>::operator[](dish) += 1;
-  //google::sparse_hash_map<Dish,int,Hash>::operator[](dish) += 1;
-  PYP<Dish,Hash>::_total_customers += 1;
-
-  // MPI Delta handling
-  // track the customer entering
-  typename dish_delta_type::iterator customer_it; 
-  bool customer_insert_result; 
-  boost::tie(customer_it, customer_insert_result) 
-    = m_count_delta.insert(std::make_pair(dish,0)); 
-
-  customer_it->second += 1;
-  if (customer_it->second == 0)
-    m_count_delta.erase(customer_it);
-
-  // increment the histogram bar for the table joined
-  /*
-  typename PYP<Dish,Hash>::TableCounter &delta_tc = m_table_delta[dish];
-
-  std::map<int,int> &histogram = delta_tc.table_histogram;
-  assert (table_joined > 0);
-
-  typename std::map<int,int>::iterator table_it; bool table_insert_result; 
-  boost::tie(table_it, table_insert_result) = histogram.insert(std::make_pair(table_joined,0)); 
-  table_it->second += 1;
-  if (delta == 0) {
-    // decrement the histogram bar for the table left 
-    typename std::map<int,int>::iterator left_table_it; 
-    boost::tie(left_table_it, table_insert_result) 
-      = histogram.insert(std::make_pair(table_joined-1,0)); 
-    left_table_it->second -= 1;
-    if (left_table_it->second == 0) histogram.erase(left_table_it);
-  }
-  else delta_tc.tables += 1;
-
-  if (table_it->second == 0) histogram.erase(table_it);
-
-    //std::cerr << "Added (" << delta << ") " << dish << " to table " << table_joined << "\n"; 
-    //std::cerr << "Dish " << dish << " has " << count(dish) << " customers, and is sitting at " << PYP<Dish,Hash>::num_tables(dish) << " tables.\n"; 
-    //for (std::map<int,int>::const_iterator 
-    //     hit = delta_tc.table_histogram.begin();
-    //     hit != delta_tc.table_histogram.end(); ++hit) {
-    //  std::cerr << "    " << hit->second << " tables with " << hit->first << " customers." << std::endl; 
-    //}
-    //std::cerr << "Added (" << delta << ") " << dish << " to table " << table_joined << "\n"; 
-    //std::cerr << "Dish " << dish << " has " << count(dish) << " customers, and is sitting at " << PYP<Dish,Hash>::num_tables(dish) << " tables.\n"; 
-    int x_num_customers=0, x_num_table=0;
-    for (std::map<int,int>::const_iterator 
-         hit = delta_tc.table_histogram.begin();
-         hit != delta_tc.table_histogram.end(); ++hit) {
-      x_num_table += hit->second;
-      x_num_customers += (hit->second*hit->first);
-    }
-    int tmp_c = PYP<Dish,Hash>::count(dish);
-    int tmp_t = PYP<Dish,Hash>::num_tables(dish);
-    assert (x_num_customers <= tmp_c); 
-    assert (x_num_table <= tmp_t); 
-
-  if (delta_tc.table_histogram.empty()) {
-    assert (delta_tc.tables == 0);
-    m_table_delta.erase(dish);
-  }
-  */
-
-  //PYP<Dish,Hash>::debug_info(std::cerr);
-  //std::cerr << "   Dish " << dish << " has count " << PYP<Dish,Hash>::count(dish) << " tables " << PYP<Dish,Hash>::num_tables(dish) << std::endl;
-
-  return delta;
-}
-
-template <typename Dish, typename Hash>
-  template <typename Uniform01>
-int 
-MPIPYP<Dish,Hash>::decrement(Dish dish, Uniform01& rnd)
-{
-  //std::cerr << "-----DECREMENT DISH " << dish << std::endl;
-  typename std::tr1::unordered_map<Dish, int>::iterator dcit = find(dish);
-  //typename google::sparse_hash_map<Dish, int>::iterator dcit = find(dish);
-  if (dcit == PYP<Dish,Hash>::end()) {
-    std::cerr << dish << std::endl;
-    assert(false);
-  } 
-
-  int delta = 0, table_left=-1;
-
-  typename std::tr1::unordered_map<Dish, typename PYP<Dish,Hash>::TableCounter>::iterator dtit 
-    = PYP<Dish,Hash>::_dish_tables.find(dish);
-  //typename google::sparse_hash_map<Dish, TableCounter>::iterator dtit = _dish_tables.find(dish);
-  if (dtit == PYP<Dish,Hash>::_dish_tables.end()) {
-    std::cerr << dish << std::endl;
-    assert(false);
-  } 
-  typename PYP<Dish,Hash>::TableCounter &tc = dtit->second;
-
-  double r = rnd() * PYP<Dish,Hash>::count(dish);
-  for (std::map<int,int>::iterator hit = tc.table_histogram.begin();
-       hit != tc.table_histogram.end(); ++hit) {
-    r -= (hit->first * hit->second);
-    if (r <= 0) {
-      table_left = hit->first;
-      if (hit->first > 1) {
-        tc.table_histogram[hit->first-1] += 1;
-      }
-      else {
-        delta = -1;
-        tc.tables -= 1;
-        PYP<Dish,Hash>::_total_tables -= 1;
-      }
-
-      hit->second -= 1;
-      if (hit->second == 0) tc.table_histogram.erase(hit);
-      break;
-    }
-  }
-  if (r > 0) {
-    std::cerr << r << " " << PYP<Dish,Hash>::count(dish) << " " << PYP<Dish,Hash>::_a << " " 
-      << PYP<Dish,Hash>::num_tables(dish) << std::endl;
-    assert(false);
-  }
-
-  // remove the customer
-  dcit->second -= 1;
-  PYP<Dish,Hash>::_total_customers -= 1;
-  assert(dcit->second >= 0);
-  if (dcit->second == 0) {
-    PYP<Dish,Hash>::erase(dcit);
-    PYP<Dish,Hash>::_dish_tables.erase(dtit);
-  }
-
-  // MPI Delta processing
-  typename dish_delta_type::iterator it; 
-  bool insert_result; 
-  boost::tie(it, insert_result) = m_count_delta.insert(std::make_pair(dish,0)); 
-  it->second -= 1;
-  if (it->second == 0) m_count_delta.erase(it);
-
-  assert (table_left > 0);
-  typename PYP<Dish,Hash>::TableCounter& delta_tc = m_table_delta[dish];
-  if (table_left > 1) {
-    std::map<int,int>::iterator tit;
-    boost::tie(tit, insert_result) = delta_tc.table_histogram.insert(std::make_pair(table_left-1,0));
-    tit->second += 1;
-    if (tit->second == 0) delta_tc.table_histogram.erase(tit);
-  }
-  else delta_tc.tables -= 1;
-
-  std::map<int,int>::iterator tit;
-  boost::tie(tit, insert_result) = delta_tc.table_histogram.insert(std::make_pair(table_left,0));
-  tit->second -= 1;
-  if (tit->second == 0) delta_tc.table_histogram.erase(tit);
-
-  //  std::cerr << "Dish " << dish << " has " << count(dish) << " customers, and is sitting at " << PYP<Dish,Hash>::num_tables(dish) << " tables.\n"; 
-  //  for (std::map<int,int>::const_iterator 
-  //       hit = delta_tc.table_histogram.begin();
-  //       hit != delta_tc.table_histogram.end(); ++hit) {
-  //    std::cerr << "    " << hit->second << " tables with " << hit->first << " customers." << std::endl; 
-  //  }
-    int x_num_customers=0, x_num_table=0;
-    for (std::map<int,int>::const_iterator 
-         hit = delta_tc.table_histogram.begin();
-         hit != delta_tc.table_histogram.end(); ++hit) {
-      x_num_table += hit->second;
-      x_num_customers += (hit->second*hit->first);
-    }
-    int tmp_c = PYP<Dish,Hash>::count(dish);
-    int tmp_t = PYP<Dish,Hash>::num_tables(dish);
-    assert (x_num_customers <= tmp_c); 
-    assert (x_num_table <= tmp_t); 
-
-  if (delta_tc.table_histogram.empty()) {
-  //  std::cerr << "   DELETING " << dish << std::endl;
-    assert (delta_tc.tables == 0);
-    m_table_delta.erase(dish);
-  }
-
-  //PYP<Dish,Hash>::debug_info(std::cerr);
-  //std::cerr << "   Dish " << dish << " has count " << PYP<Dish,Hash>::count(dish) << " tables " << PYP<Dish,Hash>::num_tables(dish) << std::endl;
-  return delta;
-}
-
-template <typename Dish, typename Hash>
-void 
-MPIPYP<Dish,Hash>::clear() {
-  PYP<Dish,Hash>::clear();
-  reset_deltas();
-}
-
-template <typename Dish, typename Hash>
-void 
-MPIPYP<Dish,Hash>::reset_deltas() { 
-  m_count_delta.clear(); 
-  m_table_delta.clear();
-}
-
-template <typename Dish>
-struct sum_maps {
-  typedef std::map<Dish,int> map_type;
-  map_type& operator() (map_type& l, map_type const & r) const {
-    for (typename map_type::const_iterator it=r.begin(); it != r.end(); it++)
-      l[it->first] += it->second;
-    return l;
-  }
-};
-
-template <typename Dish>
-struct subtract_maps {
-  typedef std::map<Dish,int> map_type;
-  map_type& operator() (map_type& l, map_type const & r) const {
-    for (typename map_type::const_iterator it=r.begin(); it != r.end(); it++)
-      l[it->first] -= it->second;
-    return l;
-  }
-};
-
-// Needed Boost definitions
-namespace boost { 
-  namespace mpi {
-    template <>
-    struct is_commutative< sum_maps<int>, std::map<int,int> > : mpl::true_ {};
-  }
-
-  namespace serialization {
-    template<class Archive>
-    void serialize(Archive & ar, PYP<int>::TableCounter& t, const unsigned int version) {
-      ar & t.table_histogram;
-      ar & t.tables;
-    }
-
-  } // namespace serialization
-} // namespace boost
-
-template <typename A, typename B, typename C>
-struct triple {
-  triple() {}
-  triple(const A& a, const B& b, const C& c) : first(a), second(b), third(c) {}
-  A first;
-  B second;
-  C third;
-
-  template<class Archive>
-  void serialize(Archive &ar, const unsigned int version){
-      ar & first;
-      ar & second;
-      ar & third;
-  }
-};
-
-BOOST_IS_BITWISE_SERIALIZABLE(MPIPYP<int>::dish_delta_type)
-BOOST_CLASS_TRACKING(MPIPYP<int>::dish_delta_type,track_never)
-
-template <typename Dish, typename Hash>
-void 
-MPIPYP<Dish,Hash>::synchronise(dish_delta_type* result) {
-  boost::mpi::communicator world; 
-  //int rank = world.rank(), size = world.size();
-
-  boost::mpi::all_reduce(world, m_count_delta, *result, sum_maps<Dish>());
-  subtract_maps<Dish>()(*result, m_count_delta);
- 
-/*
-  // communicate the customer count deltas
-  dish_delta_type global_dish_delta;
-  boost::mpi::all_reduce(world, m_count_delta, global_dish_delta, sum_maps<Dish>());
-
-  // update this restaurant
-  for (typename dish_delta_type::const_iterator it=global_dish_delta.begin(); 
-       it != global_dish_delta.end(); ++it) {
-    int global_delta = it->second - m_count_delta[it->first];
-    if (global_delta == 0) continue;
-    typename std::tr1::unordered_map<Dish,int,Hash>::iterator dit; bool inserted;
-    boost::tie(dit, inserted) 
-      = std::tr1::unordered_map<Dish,int,Hash>::insert(std::make_pair(it->first, 0));
-    dit->second += global_delta;
-    assert(dit->second >= 0);
-    if (dit->second == 0) {
-      std::tr1::unordered_map<Dish,int,Hash>::erase(dit);
-    }
-
-    PYP<Dish,Hash>::_total_customers += (it->second - m_count_delta[it->first]);
-    int tmp = PYP<Dish,Hash>::_total_customers;
-    assert(tmp >= 0);
-    //std::cerr << "Process " << rank << " adding " <<  (it->second - m_count_delta[it->first]) << " of customer " << it->first << std::endl;
-  }
-*/
-/*
-  // communicate the table count deltas
-  for (int process = 0; process < size; ++process) {
-    typename std::vector< triple<Dish, int, int> > message;
-    if (rank == process) {
-      // broadcast deltas
-      for (typename table_delta_type::const_iterator dish_it=m_table_delta.begin(); 
-           dish_it != m_table_delta.end(); ++dish_it) {
-        //assert (dish_it->second.tables > 0);
-        for (std::map<int,int>::const_iterator it=dish_it->second.table_histogram.begin(); 
-             it != dish_it->second.table_histogram.end(); ++it) {
-          triple<Dish, int, int> m(dish_it->first, it->first, it->second);
-          message.push_back(m);
-        }
-        // append a special message with the total table delta for this dish
-        triple<Dish, int, int> m(dish_it->first, -1, dish_it->second.tables);
-        message.push_back(m);
-      }
-      boost::mpi::broadcast(world, message, process);
-    }
-    else {
-      // receive deltas
-      boost::mpi::broadcast(world, message, process);
-      for (typename std::vector< triple<Dish, int, int> >::const_iterator it=message.begin(); it != message.end(); ++it) {
-        typename PYP<Dish,Hash>::TableCounter& tc = PYP<Dish,Hash>::_dish_tables[it->first];
-        if (it->second >= 0) {
-          std::map<int,int>::iterator tit; bool inserted;
-          boost::tie(tit, inserted) = tc.table_histogram.insert(std::make_pair(it->second, 0));
-          tit->second += it->third;
-          if (tit->second < 0) {
-            std::cerr << tit->first << " " << tit->second << " " << it->first << " " << it->second << " " << it->third << std::endl;
-            assert(tit->second >= 0);
-          }
-          if (tit->second == 0) {
-            tc.table_histogram.erase(tit);
-          }
-        }
-        else {
-          tc.tables += it->third;
-          PYP<Dish,Hash>::_total_tables += it->third;
-          assert(tc.tables >= 0);
-          if (tc.tables == 0) assert(tc.table_histogram.empty());
-          if (tc.table_histogram.empty()) {
-            assert (tc.tables == 0);
-            PYP<Dish,Hash>::_dish_tables.erase(it->first);
-          }
-        }
-      }
-    }
-  }
-*/
-
-//  reset_deltas();
-}
-
-#endif
diff --git a/gi/pyp-topics/src/mpi-train-contexts.cc b/gi/pyp-topics/src/mpi-train-contexts.cc
deleted file mode 100644
index e05e0eac..00000000
--- a/gi/pyp-topics/src/mpi-train-contexts.cc
+++ /dev/null
@@ -1,201 +0,0 @@
-// STL
-#include <iostream>
-#include <fstream>
-#include <algorithm>
-#include <iterator>
-
-// Boost
-#include <boost/program_options/parsers.hpp>
-#include <boost/program_options/variables_map.hpp>
-#include <boost/scoped_ptr.hpp>
-#include <boost/mpi/environment.hpp>
-#include <boost/mpi/communicator.hpp>
-#include <boost/lexical_cast.hpp>
-
-// Local
-#include "mpi-pyp-topics.hh"
-#include "corpus.hh"
-#include "mpi-corpus.hh"
-#include "gzstream.hh"
-
-static const char *REVISION = "$Rev: 170 $";
-
-// Namespaces
-using namespace boost;
-using namespace boost::program_options;
-using namespace std;
-
-int main(int argc, char **argv)
-{
-  mpi::environment env(argc, argv);
-  mpi::communicator world;
-  int rank = world.rank();
-  bool am_root = (rank==0);
-  if (am_root) cout << "Pitman Yor topic models: Copyright 2010 Phil Blunsom\n";
-  if (am_root) std::cout << "I am process " << world.rank() << " of " << world.size() << "." << std::endl;
-  if (am_root) cout << REVISION << '\n' <<endl;
-
-  ////////////////////////////////////////////////////////////////////////////////////////////
-  // Command line processing
-  variables_map vm; 
-
-  // Command line processing
-  {
-    options_description cmdline_specific("Command line specific options");
-    cmdline_specific.add_options()
-      ("help,h", "print help message")
-      ("config,c", value<string>(), "config file specifying additional command line options")
-      ;
-    options_description config_options("Allowed options");
-    config_options.add_options()
-      ("help,h", "print help message")
-      ("data,d", value<string>(), "file containing the documents and context terms")
-      ("topics,t", value<int>()->default_value(50), "number of topics")
-      ("document-topics-out,o", value<string>(), "file to write the document topics to")
-      ("default-topics-out", value<string>(), "file to write default term topic assignments.")
-      ("topic-words-out,w", value<string>(), "file to write the topic word distribution to")
-      ("samples,s", value<int>()->default_value(10), "number of sampling passes through the data")
-      ("backoff-type", value<string>(), "backoff type: none|simple")
-//      ("filter-singleton-contexts", "filter singleton contexts")
-      ("hierarchical-topics", "Use a backoff hierarchical PYP as the P0 for the document topics distribution.")
-      ("binary-counts,b", "Use binary rather than integer counts for contexts.")
-      ("freq-cutoff-start", value<int>()->default_value(0), "initial frequency cutoff.")
-      ("freq-cutoff-end", value<int>()->default_value(0), "final frequency cutoff.")
-      ("freq-cutoff-interval", value<int>()->default_value(0), "number of iterations between frequency decrement.")
-      ("max-contexts-per-document", value<int>()->default_value(0), "Only sample the n most frequent contexts for a document.")
-      ;
-
-    cmdline_specific.add(config_options);
-
-    store(parse_command_line(argc, argv, cmdline_specific), vm); 
-    notify(vm);
-
-    if (vm.count("config") > 0) {
-      ifstream config(vm["config"].as<string>().c_str());
-      store(parse_config_file(config, config_options), vm); 
-    }
-
-    if (vm.count("help")) { 
-      cout << cmdline_specific << "\n"; 
-      return 1; 
-    }
-  }
-  ////////////////////////////////////////////////////////////////////////////////////////////
-
-  if (!vm.count("data")) {
-    cerr << "Please specify a file containing the data." << endl;
-    return 1;
-  }
-
-  // seed the random number generator: 0 = automatic, specify value otherwise
-  unsigned long seed = 0; 
-  MPIPYPTopics model(vm["topics"].as<int>(), vm.count("hierarchical-topics"), seed);
-
-  // read the data
-  BackoffGenerator* backoff_gen=0;
-  if (vm.count("backoff-type")) {
-    if (vm["backoff-type"].as<std::string>() == "none") {
-      backoff_gen = 0;
-    }
-    else if (vm["backoff-type"].as<std::string>() == "simple") {
-      backoff_gen = new SimpleBackoffGenerator();
-    }
-    else {
-     cerr << "Backoff type (--backoff-type) must be one of none|simple." <<endl;
-      return(1);
-    }
-  }
-
-  //ContextsCorpus contexts_corpus;
-  MPICorpus contexts_corpus;
-  contexts_corpus.read_contexts(vm["data"].as<string>(), backoff_gen, /*vm.count("filter-singleton-contexts")*/ false, vm.count("binary-counts"));
-  int mpi_start = 0, mpi_end = 0;
-  contexts_corpus.bounds(&mpi_start, &mpi_end);
-  std::cerr << "\tProcess " << rank << " has documents " << mpi_start << " -> " << mpi_end << "." << std::endl;
-
-  model.set_backoff(contexts_corpus.backoff_index());
-
-  if (backoff_gen) 
-    delete backoff_gen;
-
-  // train the sampler
-  model.sample_corpus(contexts_corpus, vm["samples"].as<int>(),
-                      vm["freq-cutoff-start"].as<int>(),
-                      vm["freq-cutoff-end"].as<int>(),
-                      vm["freq-cutoff-interval"].as<int>(),
-                      vm["max-contexts-per-document"].as<int>());
-
-  if (vm.count("document-topics-out")) {
-    std::ofstream documents_out((vm["document-topics-out"].as<string>() + ".pyp-process-" + boost::lexical_cast<std::string>(rank)).c_str());
-    //int documents = contexts_corpus.num_documents();
-    /*
-    int mpi_start = 0, mpi_end = documents;
-    if (world.size() != 1) {
-      mpi_start = (documents / world.size()) * rank;
-      if (rank == world.size()-1) mpi_end = documents;
-      else mpi_end = (documents / world.size())*(rank+1);
-    }
-    */
-
-    map<int,int> all_terms;
-    for (int document_id=mpi_start; document_id<mpi_end; ++document_id) {
-      assert (document_id < contexts_corpus.num_documents());
-      const Document& doc = contexts_corpus.at(document_id);
-      vector<int> unique_terms;
-      for (Document::const_iterator docIt=doc.begin(); docIt != doc.end(); ++docIt) {
-        if (unique_terms.empty() || *docIt != unique_terms.back())
-          unique_terms.push_back(*docIt);
-        // increment this terms frequency
-        pair<map<int,int>::iterator,bool> insert_result = all_terms.insert(make_pair(*docIt,1));
-        if (!insert_result.second) 
-          all_terms[*docIt] = all_terms[*docIt] + 1;
-      }
-      documents_out << contexts_corpus.key(document_id) << '\t';
-      documents_out << model.max(document_id).first << " " << doc.size() << " ||| ";
-      for (std::vector<int>::const_iterator termIt=unique_terms.begin(); termIt != unique_terms.end(); ++termIt) {
-        if (termIt != unique_terms.begin())
-          documents_out << " ||| ";
-        vector<std::string> strings = contexts_corpus.context2string(*termIt);
-        copy(strings.begin(), strings.end(),ostream_iterator<std::string>(documents_out, " "));
-        std::pair<int,MPIPYPTopics::F> maxinfo = model.max(document_id, *termIt);
-        documents_out << "||| C=" << maxinfo.first << " P=" << maxinfo.second;
-      }
-      documents_out <<endl;
-    }
-    documents_out.close();
-    world.barrier();
-
-    if (am_root) {
-      ogzstream root_documents_out(vm["document-topics-out"].as<string>().c_str());
-      for (int p=0; p < world.size(); ++p) {
-        std::string rank_p_prefix((vm["document-topics-out"].as<string>() + ".pyp-process-" + boost::lexical_cast<std::string>(p)).c_str());
-        std::ifstream rank_p_trees_istream(rank_p_prefix.c_str(), std::ios_base::binary);
-        root_documents_out << rank_p_trees_istream.rdbuf();
-        rank_p_trees_istream.close();
-        remove((rank_p_prefix).c_str());
-      }
-      root_documents_out.close();
-    }
-
-    if (am_root && vm.count("default-topics-out")) {
-      ofstream default_topics(vm["default-topics-out"].as<string>().c_str());
-      default_topics << model.max_topic() <<endl;
-      for (std::map<int,int>::const_iterator termIt=all_terms.begin(); termIt != all_terms.end(); ++termIt) {
-        vector<std::string> strings = contexts_corpus.context2string(termIt->first);
-        default_topics << model.max(-1, termIt->first).first << " ||| " << termIt->second << " ||| ";
-        copy(strings.begin(), strings.end(),ostream_iterator<std::string>(default_topics, " "));
-        default_topics <<endl;
-      }
-    }
-  }
-
-  if (am_root && vm.count("topic-words-out")) {
-    ogzstream topics_out(vm["topic-words-out"].as<string>().c_str());
-    model.print_topic_terms(topics_out);
-    topics_out.close();
-  }
-
-  cout <<endl;
-
-  return 0;
-}
diff --git a/gi/pyp-topics/src/mt19937ar.c b/gi/pyp-topics/src/mt19937ar.c
deleted file mode 100644
index 6551ea39..00000000
--- a/gi/pyp-topics/src/mt19937ar.c
+++ /dev/null
@@ -1,194 +0,0 @@
-/* 
-   A C-program for MT19937, with initialization improved 2002/1/26.
-   Coded by Takuji Nishimura and Makoto Matsumoto.
-
-   Before using, initialize the state by using mt_init_genrand(seed)  
-   or mt_init_by_array(init_key, key_length).
-
-   Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
-   All rights reserved.                          
-
-   Redistribution and use in source and binary forms, with or without
-   modification, are permitted provided that the following conditions
-   are met:
-
-     1. Redistributions of source code must retain the above copyright
-        notice, this list of conditions and the following disclaimer.
-
-     2. Redistributions in binary form must reproduce the above copyright
-        notice, this list of conditions and the following disclaimer in the
-        documentation and/or other materials provided with the distribution.
-
-     3. The names of its contributors may not be used to endorse or promote 
-        products derived from this software without specific prior written 
-        permission.
-
-   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
-   A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-   CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-   EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-   PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
-   PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
-   LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
-   NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
-   SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-
-   Any feedback is very welcome.
-   http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html
-   email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space)
-*/
-
-#include "mt19937ar.h"   /* XXX MJ 17th March 2006 */
-
-/* Period parameters */  
-#define N 624
-#define M 397
-#define MATRIX_A 0x9908b0dfUL   /* constant vector a */
-#define UPPER_MASK 0x80000000UL /* most significant w-r bits */
-#define LOWER_MASK 0x7fffffffUL /* least significant r bits */
-
-static unsigned long mt[N]; /* the array for the state vector  */
-static int mti=N+1; /* mti==N+1 means mt[N] is not initialized */
-
-/* initializes mt[N] with a seed */
-void mt_init_genrand(unsigned long s)
-{
-    mt[0]= s & 0xffffffffUL;
-    for (mti=1; mti<N; mti++) {
-        mt[mti] = 
-	    (1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti); 
-        /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
-        /* In the previous versions, MSBs of the seed affect   */
-        /* only MSBs of the array mt[].                        */
-        /* 2002/01/09 modified by Makoto Matsumoto             */
-        mt[mti] &= 0xffffffffUL;
-        /* for >32 bit machines */
-    }
-}
-
-/* initialize by an array with array-length */
-/* init_key is the array for initializing keys */
-/* key_length is its length */
-/* slight change for C++, 2004/2/26 */
-void mt_init_by_array(unsigned long init_key[], int key_length)
-{
-    int i, j, k;
-    mt_init_genrand(19650218UL);
-    i=1; j=0;
-    k = (N>key_length ? N : key_length);
-    for (; k; k--) {
-        mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL))
-          + init_key[j] + j; /* non linear */
-        mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
-        i++; j++;
-        if (i>=N) { mt[0] = mt[N-1]; i=1; }
-        if (j>=key_length) j=0;
-    }
-    for (k=N-1; k; k--) {
-        mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL))
-          - i; /* non linear */
-        mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
-        i++;
-        if (i>=N) { mt[0] = mt[N-1]; i=1; }
-    }
-
-    mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ 
-}
-
-/* generates a random number on [0,0xffffffff]-interval */
-unsigned long mt_genrand_int32(void)
-{
-    unsigned long y;
-    static unsigned long mag01[2]={0x0UL, MATRIX_A};
-    /* mag01[x] = x * MATRIX_A  for x=0,1 */
-
-    if (mti >= N) { /* generate N words at one time */
-        int kk;
-
-        if (mti == N+1)   /* if mt_init_genrand() has not been called, */
-            mt_init_genrand(5489UL); /* a default initial seed is used */
-
-        for (kk=0;kk<N-M;kk++) {
-            y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
-            mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1UL];
-        }
-        for (;kk<N-1;kk++) {
-            y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
-            mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1UL];
-        }
-        y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK);
-        mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL];
-
-        mti = 0;
-    }
-  
-    y = mt[mti++];
-
-    /* Tempering */
-    y ^= (y >> 11);
-    y ^= (y << 7) & 0x9d2c5680UL;
-    y ^= (y << 15) & 0xefc60000UL;
-    y ^= (y >> 18);
-
-    return y;
-}
-
-/* generates a random number on [0,0x7fffffff]-interval */
-long mt_genrand_int31(void)
-{
-    return (long)( mt_genrand_int32()>>1);
-}
-
-/* generates a random number on [0,1]-real-interval */
-double mt_genrand_real1(void)
-{
-    return mt_genrand_int32()*(1.0/4294967295.0); 
-    /* divided by 2^32-1 */ 
-}
-
-/* generates a random number on [0,1)-real-interval */
-double mt_genrand_real2(void)
-{
-    return mt_genrand_int32()*(1.0/4294967296.0); 
-    /* divided by 2^32 */
-}
-
-/* generates a random number on (0,1)-real-interval */
-double mt_genrand_real3(void)
-{
-    return (((double) mt_genrand_int32()) + 0.5)*(1.0/4294967296.0); 
-    /* divided by 2^32 */
-}
-
-/* generates a random number on [0,1) with 53-bit resolution*/
-double mt_genrand_res53(void) 
-{ 
-    unsigned long a=mt_genrand_int32()>>5, b=mt_genrand_int32()>>6; 
-    return(a*67108864.0+b)*(1.0/9007199254740992.0); 
-} 
-/* These real versions are due to Isaku Wada, 2002/01/09 added */
-
-/*
-#include <stdio.h>
-
-int main(void)
-{
-    int i;
-    unsigned long init[4]={0x123, 0x234, 0x345, 0x456}, length=4;
-    mt_init_by_array(init, length);
-    printf("1000 outputs of genrand_int32()\n");
-    for (i=0; i<1000; i++) {
-      printf("%10lu ", mt_genrand_int32());
-      if (i%5==4) printf("\n");
-    }
-    printf("\n1000 outputs of genrand_real2()\n");
-    for (i=0; i<1000; i++) {
-      printf("%10.8f ", mt_genrand_real2());
-      if (i%5==4) printf("\n");
-    }
-    return 0;
-}
-*/
diff --git a/gi/pyp-topics/src/mt19937ar.h b/gi/pyp-topics/src/mt19937ar.h
deleted file mode 100644
index caab4045..00000000
--- a/gi/pyp-topics/src/mt19937ar.h
+++ /dev/null
@@ -1,44 +0,0 @@
-/* mt19937ar.h
- *
- * Mark Johnson, 17th March 2006
- */
-
-#ifndef MT19937AR_H
-#define MT19937AR_H
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-  /* initializes mt[N] with a seed */
-  void mt_init_genrand(unsigned long s);
-
-  /* initialize by an array with array-length */
-  /* init_key is the array for initializing keys */
-  /* key_length is its length */
-  /* slight change for C++, 2004/2/26 */
-  void mt_init_by_array(unsigned long init_key[], int key_length);
-
-  /* generates a random number on [0,0xffffffff]-interval */
-  unsigned long mt_genrand_int32(void);
-
-  /* generates a random number on [0,0x7fffffff]-interval */
-  long mt_genrand_int31(void);
-
-  /* generates a random number on [0,1]-real-interval */
-  double mt_genrand_real1(void);
-
-  /* generates a random number on [0,1)-real-interval */
-  double mt_genrand_real2(void);
-
-  /* generates a random number on (0,1)-real-interval */
-  double mt_genrand_real3(void);
-
-  /* generates a random number on [0,1) with 53-bit resolution*/
-  double mt_genrand_res53(void);
-
-#ifdef __cplusplus
-};
-#endif
-
-#endif /* MT19937AR_H */
diff --git a/gi/pyp-topics/src/pyp-topics.cc b/gi/pyp-topics/src/pyp-topics.cc
deleted file mode 100644
index 4de52fd7..00000000
--- a/gi/pyp-topics/src/pyp-topics.cc
+++ /dev/null
@@ -1,499 +0,0 @@
-#include "timing.h"
-#include "pyp-topics.hh"
-#include "contexts_corpus.hh"
-
-//Dict const *dict;
-
-//#include <boost/date_time/posix_time/posix_time_types.hpp>
-void PYPTopics::sample_corpus(const Corpus& corpus, int samples,
-                              int freq_cutoff_start, int freq_cutoff_end,
-                              int freq_cutoff_interval,
-                              int max_contexts_per_document,
-                              F temp_start, F temp_end) {
-  Timer timer;
-  //dict = &((ContextsCorpus*) &corpus)->dict();
-
-  if (!m_backoff.get()) {
-    m_word_pyps.clear();
-    m_word_pyps.push_back(PYPs());
-  }
-
-  std::cerr << "\n Training with " << m_word_pyps.size()-1 << " backoff level"
-    << (m_word_pyps.size()==2 ? ":" : "s:") << std::endl;
-
-
-  for (int i=0; i<(int)m_word_pyps.size(); ++i)
-  {
-    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>(0.01, 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>(0.01, 1.0, m_seed));
-
-  m_topic_p0 = 1.0/m_num_topics;
-  m_term_p0 = 1.0/(F)m_backoff->terms_at_level(m_word_pyps.size()-1);
-  //m_term_p0 = 1.0/corpus.num_types();
-  m_backoff_p0 = 1.0/corpus.num_documents();
-
-  std::cerr << " Documents: " << corpus.num_documents() << " Terms: "
-    << corpus.num_types() << std::endl;
-
-  int frequency_cutoff = freq_cutoff_start;
-  std::cerr << " Context frequency cutoff set to " << frequency_cutoff << std::endl;
-
-  timer.Reset();
-  // Initialisation pass
-  int document_id=0, topic_counter=0;
-  for (Corpus::const_iterator corpusIt=corpus.begin();
-       corpusIt != corpus.end(); ++corpusIt, ++document_id) {
-    m_corpus_topics.push_back(DocumentTopics(corpusIt->size(), 0));
-
-    int term_index=0;
-    for (Document::const_iterator docIt=corpusIt->begin();
-         docIt != corpusIt->end(); ++docIt, ++term_index) {
-      topic_counter++;
-      Term term = *docIt;
-
-      // sample a new_topic
-      //int new_topic = (topic_counter % m_num_topics);
-      int freq = corpus.context_count(term);
-      int new_topic = -1;
-      if (freq > frequency_cutoff
-          && (!max_contexts_per_document || term_index < max_contexts_per_document)) {
-        //new_topic = sample(document_id, term);
-        //new_topic = document_id % m_num_topics;
-        new_topic = (int) (rnd() * m_num_topics);
-
-        // add the new topic to the PYPs
-        increment(term, new_topic);
-
-        if (m_use_topic_pyp) {
-          F p0 = m_topic_pyp.prob(new_topic, m_topic_p0);
-          int table_delta = m_document_pyps[document_id].increment(new_topic, p0);
-          if (table_delta)
-            m_topic_pyp.increment(new_topic, m_topic_p0);
-        }
-        else m_document_pyps[document_id].increment(new_topic, m_topic_p0);
-      }
-
-      m_corpus_topics[document_id][term_index] = new_topic;
-    }
-  }
-  std::cerr << "  Initialized in " << timer.Elapsed() << " seconds\n";
-
-  int* randomDocIndices = new int[corpus.num_documents()];
-  for (int i = 0; i < corpus.num_documents(); ++i)
-	  randomDocIndices[i] = i;
-
-  if (num_jobs < max_threads)
-    num_jobs = max_threads;
-  int job_incr = (int) ( (float)m_document_pyps.size() / float(num_jobs) );
-
-  // Sampling phase
-  for (int curr_sample=0; curr_sample < samples; ++curr_sample) {
-    if (freq_cutoff_interval > 0 && curr_sample != 1
-        && curr_sample % freq_cutoff_interval == 1
-        && frequency_cutoff > freq_cutoff_end) {
-      frequency_cutoff--;
-      std::cerr << "\n Context frequency cutoff set to " << frequency_cutoff << std::endl;
-    }
-
-    F temp = 1.0 / (temp_start - curr_sample*(temp_start-temp_end)/samples);
-    std::cerr << "\n  -- Sample " << curr_sample << " (T=" << temp << ") "; std::cerr.flush();
-
-    // Randomize the corpus indexing array
-    int tmp;
-    int processed_terms=0;
-    /*
-    for (int i = corpus.num_documents()-1; i > 0; --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;
-    }
-    */
-
-    // for each document in the corpus
-    int document_id;
-    for (int i=0; i<corpus.num_documents(); ++i) {
-    	document_id = randomDocIndices[i];
-
-      // for each term in the document
-      int term_index=0;
-      Document::const_iterator docEnd = corpus.at(document_id).end();
-      for (Document::const_iterator docIt=corpus.at(document_id).begin();
-           docIt != docEnd; ++docIt, ++term_index) {
-        if (max_contexts_per_document && term_index > max_contexts_per_document)
-          break;
-        
-        Term term = *docIt;
-
-        int freq = corpus.context_count(term);
-        if (freq < frequency_cutoff)
-          continue;
-
-        processed_terms++;
-
-        // remove the prevous topic from the PYPs
-        int current_topic = m_corpus_topics[document_id][term_index];
-        // a negative label mean that term hasn't been sampled yet
-        if (current_topic >= 0) {
-          decrement(term, current_topic);
-
-          int table_delta = m_document_pyps[document_id].decrement(current_topic);
-          if (m_use_topic_pyp && table_delta < 0)
-            m_topic_pyp.decrement(current_topic);
-        }
-
-        // sample a new_topic
-        int new_topic = sample(document_id, term, temp);
-        //std::cerr << "TERM: " << dict->Convert(term) << " (" << term << ") " << " Old Topic: " 
-        //  << current_topic << " New Topic: " << new_topic << "\n" << std::endl;
-
-        // add the new topic to the PYPs
-        m_corpus_topics[document_id][term_index] = new_topic;
-        increment(term, new_topic);
-
-        if (m_use_topic_pyp) {
-          F p0 = m_topic_pyp.prob(new_topic, m_topic_p0);
-          int table_delta = m_document_pyps[document_id].increment(new_topic, p0);
-          if (table_delta)
-            m_topic_pyp.increment(new_topic, m_topic_p0);
-        }
-        else m_document_pyps[document_id].increment(new_topic, m_topic_p0);
-      }
-      if (document_id && document_id % 10000 == 0) {
-        std::cerr << "."; std::cerr.flush();
-      }
-    }
-    std::cerr << " ||| LLH= " << log_likelihood();
-
-    if (curr_sample != 0 && curr_sample % 10 == 0) {
-    //if (true) {
-      std::cerr << " ||| time=" << (timer.Elapsed() / 10.0) << " sec/sample" << std::endl;
-      timer.Reset();
-      std::cerr << "     ... Resampling hyperparameters (";
-      
-      // resample the hyperparamters
-      F log_p=0.0;
-      if (max_threads == 1)
-      { 
-        std::cerr << "1 thread)" << std::endl; std::cerr.flush();
-        log_p += hresample_topics();
-        log_p += hresample_docs(0, m_document_pyps.size());
-      }
-      else
-      { //parallelize
-        std::cerr << max_threads << " threads, " << num_jobs << " jobs)" << std::endl; std::cerr.flush();
-        
-        WorkerPool<JobReturnsF, F> pool(max_threads); 
-        int i=0, sz = m_document_pyps.size();
-        //documents...
-        while (i <= sz - 2*job_incr)
-        {    
-          JobReturnsF job = boost::bind(&PYPTopics::hresample_docs, this, i, i+job_incr);
-          pool.addJob(job);
-          i += job_incr;
-        }
-        //  do all remaining documents
-        JobReturnsF job = boost::bind(&PYPTopics::hresample_docs, this, i,sz);
-        pool.addJob(job);
-        
-        //topics...
-        JobReturnsF topics_job = boost::bind(&PYPTopics::hresample_topics, this);
-        pool.addJob(topics_job);
-
-        log_p += pool.get_result(); //blocks
-
-      }
-
-      if (m_use_topic_pyp) {
-        m_topic_pyp.resample_prior(rnd);
-        log_p += m_topic_pyp.log_restaurant_prob();
-      }
-
-      std::cerr.precision(10);
-      std::cerr << " ||| LLH=" << log_likelihood() << " ||| resampling time=" << timer.Elapsed() << " sec" << std::endl;
-      timer.Reset();
-
-      int k=0;
-      std::cerr << "Topics distribution: ";
-      std::cerr.precision(2);
-      for (PYPs::iterator pypIt=m_word_pyps.front().begin();
-           pypIt != m_word_pyps.front().end(); ++pypIt, ++k) {
-        if (k % 5 == 0) std::cerr << std::endl << '\t';
-        std::cerr << "<" << k << ":" << pypIt->num_customers() << ","
-          << pypIt->num_types() << "," << m_topic_pyp.prob(k, m_topic_p0) << "> ";
-      }
-      std::cerr.precision(10);
-      std::cerr << std::endl;
-    }
-  }
-  delete [] randomDocIndices;
-}
-
-PYPTopics::F PYPTopics::hresample_docs(int start, int end)
-{
-  int resample_counter=0;
-  F log_p = 0.0;
-  assert(start >= 0);
-  assert(end >= 0);
-  assert(start <= end);
-  for (int i=start; i < end; ++i)
-  {
-    m_document_pyps[i].resample_prior(rnd);
-    log_p += m_document_pyps[i].log_restaurant_prob();
-    if (resample_counter++ % 5000 == 0) {
-      std::cerr << "."; std::cerr.flush();
-    }
-  }
-  return log_p;
-}
-
-PYPTopics::F PYPTopics::hresample_topics()
-{
-  F log_p = 0.0;
-  for (std::vector<PYPs>::iterator levelIt=m_word_pyps.begin();
-      levelIt != m_word_pyps.end(); ++levelIt) {
-    for (PYPs::iterator pypIt=levelIt->begin();
-        pypIt != levelIt->end(); ++pypIt) {
-
-      pypIt->resample_prior(rnd);
-      log_p += pypIt->log_restaurant_prob();
-    }
-    std::cerr << log_p << std::endl;
-  }
-  return log_p;
-}
-
-PYPTopics::F PYPTopics::log_likelihood() const 
-{
-  F log_p = 0.0;
-
-  // LLH of topic term distribution
-  size_t i=0;
-  for (std::vector<PYPs>::const_iterator levelIt=m_word_pyps.begin();
-      levelIt != m_word_pyps.end(); ++levelIt, ++i) {
-    for (PYPs::const_iterator pypIt=levelIt->begin();
-        pypIt != levelIt->end(); ++pypIt, ++i) {
-      log_p += pypIt->log_restaurant_prob();
-
-      if (i == m_word_pyps.size()-1)
-        log_p += (pypIt->num_tables() * -log(m_backoff->terms_at_level(i)));
-      else
-        log_p += (pypIt->num_tables() * log(m_term_p0));
-    }
-  }
-  std::cerr << " TERM LLH: " << log_p << " "; //std::endl;
-
-  // LLH of document topic distribution
-  for (size_t i=0; i < m_document_pyps.size(); ++i) {
-    log_p += m_document_pyps[i].log_restaurant_prob();
-    if (!m_use_topic_pyp) log_p += (m_document_pyps[i].num_tables() * m_topic_p0);
-  }
-  if (m_use_topic_pyp) {
-    log_p += m_topic_pyp.log_restaurant_prob();
-    log_p += (m_topic_pyp.num_tables() * log(m_topic_p0));
-  }
-
-  return log_p;
-}
-
-void PYPTopics::decrement(const Term& term, int topic, int level) {
-  //std::cerr << "PYPTopics::decrement(" << term << "," << topic << "," << level << ")" << std::endl;
-  int table_delta = m_word_pyps.at(level).at(topic).decrement(term);
-  if (table_delta && m_backoff.get()) {
-    Term backoff_term = (*m_backoff)[term];
-    if (!m_backoff->is_null(backoff_term))
-      decrement(backoff_term, topic, level+1);
-  }
-}
-
-void PYPTopics::increment(const Term& term, int topic, int level) {
-  //std::cerr << "PYPTopics::increment(" << term << "," << topic << "," << level << ")" << std::endl;
-  int table_delta = m_word_pyps.at(level).at(topic).increment(term, word_pyps_p0(term, topic, level));
-
-  if (table_delta && m_backoff.get()) {
-    Term backoff_term = (*m_backoff)[term];
-    if (!m_backoff->is_null(backoff_term))
-      increment(backoff_term, topic, level+1);
-  }
-}
-
-int PYPTopics::sample(const DocumentId& doc, const Term& term, F inv_temp) {
-  // First pass: collect probs
-  F sum=0.0;
-  std::vector<F> sums;
-  for (int k=0; k<m_num_topics; ++k) {
-    F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp) topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    //F p_k_d = m_document_pyps[doc].prob(k, topic_prob);
-    F p_k_d = m_document_pyps[doc].unnormalised_prob(k, topic_prob);
-
-    F prob = p_w_k*p_k_d;
-    /*
-    if (prob < 0.0) { std::cerr << "\n\n" << prob << " " << p_w_k << " " << p_k_d << std::endl; assert(false); }
-    if (prob > 1.0) { std::cerr << "\n\n" << prob << " " << p_w_k << " " << p_k_d << std::endl; assert(false); }
-    assert (pow(prob, inv_temp) >= 0.0);
-    assert (pow(prob, inv_temp) <= 1.0);
-    */
-    sum += pow(prob, inv_temp);
-    sums.push_back(sum);
-  }
-  // Second pass: sample a topic
-  F cutoff = rnd() * sum;
-  for (int k=0; k<m_num_topics; ++k) {
-    if (cutoff <= sums[k])
-      return k;
-  }
-  assert(false);
-}
-
-PYPTopics::F PYPTopics::word_pyps_p0(const Term& term, int topic, int level) const {
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "PYPTopics::word_pyps_p0(" << term << "," << topic << "," << level << ")" << std::endl;
-
-  F p0 = m_term_p0;
-  if (m_backoff.get()) {
-    //static F fudge=m_backoff_p0; // TODO
-
-    Term backoff_term = (*m_backoff)[term];
-    //std::cerr << "T: " << term << " BO: " << backoff_term << std::endl;
-    if (!m_backoff->is_null(backoff_term)) {
-      assert (level < m_backoff->order());
-      //p0 = (1.0/(F)m_backoff->terms_at_level(level))*prob(backoff_term, topic, level+1);
-      p0 = m_term_p0*prob(backoff_term, topic, level+1);
-      p0 = prob(backoff_term, topic, level+1);
-    }
-    else
-      p0 = (1.0/(F) m_backoff->terms_at_level(level));
-      //p0 = m_term_p0;
-  }
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "PYPTopics::word_pyps_p0(" << term << "," << topic << "," << level << ") = " << p0 << std::endl;
-  return p0;
-}
-
-PYPTopics::F PYPTopics::prob(const Term& term, int topic, int level) const {
-  //for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  //std::cerr << "PYPTopics::prob(" << dict->Convert(term) << "," << topic << "," << level << ")" << std::endl;
-
-  F p0 = word_pyps_p0(term, topic, level);
-  F p_w_k = m_word_pyps.at(level).at(topic).prob(term, p0);
-
-  /*
-  for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  std::cerr << "PYPTopics::prob(" << dict->Convert(term) << "," << topic << "," << level << ") = " << p_w_k << std::endl;
-  for (int i=0; i<level+1; ++i) std::cerr << "  ";
-  m_word_pyps.at(level).at(topic).debug_info(std::cerr);
-  */
-  return p_w_k;
-}
-
-int PYPTopics::max_topic() const {
-  if (!m_use_topic_pyp)
-    return -1;
-
-  F current_max=0.0;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    F prob = m_topic_pyp.prob(k, m_topic_p0);
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  return current_topic;
-}
-
-std::pair<int,PYPTopics::F> PYPTopics::max(const DocumentId& doc) const {
-  //std::cerr << "PYPTopics::max(" << doc << "," << term << ")" << std::endl;
-  // collect probs
-  F current_max=0.0;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    //F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp)
-      topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    F prob = 0;
-    if (doc < 0) prob = topic_prob;
-    else         prob = m_document_pyps[doc].prob(k, topic_prob);
-
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  assert(current_max >= 0);
-  return std::make_pair(current_topic, current_max);
-}
-
-std::pair<int,PYPTopics::F> PYPTopics::max(const DocumentId& doc, const Term& term) const {
-  //std::cerr << "PYPTopics::max(" << doc << "," << term << ")" << std::endl;
-  // collect probs
-  F current_max=0.0;
-  int current_topic=-1;
-  for (int k=0; k<m_num_topics; ++k) {
-    F p_w_k = prob(term, k);
-
-    F topic_prob = m_topic_p0;
-    if (m_use_topic_pyp)
-      topic_prob = m_topic_pyp.prob(k, m_topic_p0);
-
-    F p_k_d = 0;
-    if (doc < 0) p_k_d = topic_prob;
-    else         p_k_d = m_document_pyps[doc].prob(k, topic_prob);
-
-    F prob = (p_w_k*p_k_d);
-    if (prob > current_max) {
-      current_max = prob;
-      current_topic = k;
-    }
-  }
-  assert(current_topic >= 0);
-  assert(current_max >= 0);
-  return std::make_pair(current_topic,current_max);
-}
-
-std::ostream& PYPTopics::print_document_topics(std::ostream& out) const {
-  for (CorpusTopics::const_iterator corpusIt=m_corpus_topics.begin();
-       corpusIt != m_corpus_topics.end(); ++corpusIt) {
-    int term_index=0;
-    for (DocumentTopics::const_iterator docIt=corpusIt->begin();
-         docIt != corpusIt->end(); ++docIt, ++term_index) {
-      if (term_index) out << " ";
-      out << *docIt;
-    }
-    out << std::endl;
-  }
-  return out;
-}
-
-std::ostream& PYPTopics::print_topic_terms(std::ostream& out) const {
-  for (PYPs::const_iterator pypsIt=m_word_pyps.front().begin();
-       pypsIt != m_word_pyps.front().end(); ++pypsIt) {
-    int term_index=0;
-    for (PYP<int>::const_iterator termIt=pypsIt->begin();
-         termIt != pypsIt->end(); ++termIt, ++term_index) {
-      if (term_index) out << " ";
-      out << termIt->first << ":" << termIt->second;
-    }
-    out << std::endl;
-  }
-  return out;
-}
diff --git a/gi/pyp-topics/src/pyp-topics.hh b/gi/pyp-topics/src/pyp-topics.hh
deleted file mode 100644
index 3a910540..00000000
--- a/gi/pyp-topics/src/pyp-topics.hh
+++ /dev/null
@@ -1,98 +0,0 @@
-#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
diff --git a/gi/pyp-topics/src/pyp.hh b/gi/pyp-topics/src/pyp.hh
deleted file mode 100644
index b1cb62be..00000000
--- a/gi/pyp-topics/src/pyp.hh
+++ /dev/null
@@ -1,566 +0,0 @@
-#ifndef _pyp_hh
-#define _pyp_hh
-
-#include "slice-sampler.h"
-#include <math.h>
-#include <map>
-#include <tr1/unordered_map>
-//#include <google/sparse_hash_map>
-
-#include <boost/random/uniform_real.hpp>
-#include <boost/random/variate_generator.hpp>
-#include <boost/random/mersenne_twister.hpp>
-
-#include "log_add.h"
-#include "mt19937ar.h"
-
-//
-// Pitman-Yor process with customer and table tracking
-//
-
-template <typename Dish, typename Hash=std::tr1::hash<Dish> >
-class PYP : protected std::tr1::unordered_map<Dish, int, Hash>
-//class PYP : protected google::sparse_hash_map<Dish, int, Hash>
-{
-public:
-  using std::tr1::unordered_map<Dish,int>::const_iterator;
-  using std::tr1::unordered_map<Dish,int>::iterator;
-  using std::tr1::unordered_map<Dish,int>::begin;
-  using std::tr1::unordered_map<Dish,int>::end;
-//  using google::sparse_hash_map<Dish,int>::const_iterator;
-//  using google::sparse_hash_map<Dish,int>::iterator;
-//  using google::sparse_hash_map<Dish,int>::begin;
-//  using google::sparse_hash_map<Dish,int>::end;
-
-  PYP(double a, double b, unsigned long seed = 0, Hash hash=Hash());
-
-  virtual int increment(Dish d, double p0);
-  virtual int decrement(Dish d);
-
-  // lookup functions
-  int count(Dish d) const;
-  double prob(Dish dish, double p0) const;
-  double prob(Dish dish, double dcd, double dca, 
-              double dtd, double dta, double p0) const;
-  double unnormalised_prob(Dish dish, double p0) const;
-
-  int num_customers() const { return _total_customers; }
-  int num_types() const { return std::tr1::unordered_map<Dish,int>::size(); }
-  //int num_types() const { return google::sparse_hash_map<Dish,int>::size(); }
-  bool empty() const { return _total_customers == 0; }
-
-  double log_prob(Dish dish, double log_p0) const;
-  // nb. d* are NOT logs
-  double log_prob(Dish dish, double dcd, double dca, 
-                       double dtd, double dta, double log_p0) const;
-
-  int num_tables(Dish dish) const;
-  int num_tables() const;
-
-  double a() const { return _a; }
-  void set_a(double a) { _a = a; }
-
-  double b() const { return _b; }
-  void set_b(double b) { _b = b; }
-
-  virtual void clear();
-  std::ostream& debug_info(std::ostream& os) const;
-
-  double log_restaurant_prob() const;
-  double log_prior() const;
-  static double log_prior_a(double a, double beta_a, double beta_b);
-  static double log_prior_b(double b, double gamma_c, double gamma_s);
-
-  template <typename Uniform01>
-    void resample_prior(Uniform01& rnd);
-  template <typename Uniform01>
-    void resample_prior_a(Uniform01& rnd);
-  template <typename Uniform01>
-    void resample_prior_b(Uniform01& rnd);
-
-protected:
-  double _a, _b; // parameters of the Pitman-Yor distribution
-  double _a_beta_a, _a_beta_b; // parameters of Beta prior on a
-  double _b_gamma_s, _b_gamma_c; // parameters of Gamma prior on b
-
-  struct TableCounter {
-    TableCounter() : tables(0) {};
-    int tables;
-    std::map<int, int> table_histogram; // num customers at table -> number tables
-  };
-  typedef std::tr1::unordered_map<Dish, TableCounter, Hash> DishTableType;
-  //typedef google::sparse_hash_map<Dish, TableCounter, Hash> DishTableType;
-  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 {
-    int n, m; double b, a_beta_a, a_beta_b;
-    const DishTableType& dish_tables;
-    resample_a_type(int n, int m, double b, double a_beta_a, 
-                    double a_beta_b, const DishTableType& dish_tables)
-      : n(n), m(m), b(b), a_beta_a(a_beta_a), a_beta_b(a_beta_b), dish_tables(dish_tables) {}
-
-    double operator() (double proposed_a) const {
-      double log_prior = log_prior_a(proposed_a, a_beta_a, a_beta_b);
-      double log_prob = 0.0;
-      double lgamma1a = lgamma(1.0 - proposed_a);
-      for (typename DishTableType::const_iterator dish_it=dish_tables.begin(); dish_it != dish_tables.end(); ++dish_it) 
-        for (std::map<int, int>::const_iterator table_it=dish_it->second.table_histogram.begin(); 
-             table_it !=dish_it->second.table_histogram.end(); ++table_it) 
-          log_prob += (table_it->second * (lgamma(table_it->first - proposed_a) - lgamma1a));
-
-      log_prob += (proposed_a == 0.0 ? (m-1.0)*log(b) 
-                   : ((m-1.0)*log(proposed_a) + lgamma((m-1.0) + b/proposed_a) - lgamma(b/proposed_a)));
-      assert(std::isfinite(log_prob));
-      return log_prob + log_prior;
-    }
-  };
-
-  struct resample_b_type {
-    int n, m; double a, b_gamma_c, b_gamma_s;
-    resample_b_type(int n, int m, double a, double b_gamma_c, double b_gamma_s)
-      : n(n), m(m), a(a), b_gamma_c(b_gamma_c), b_gamma_s(b_gamma_s) {}
-
-    double operator() (double proposed_b) const {
-      double log_prior = log_prior_b(proposed_b, b_gamma_c, b_gamma_s);
-      double log_prob = 0.0;
-      log_prob += (a == 0.0  ? (m-1.0)*log(proposed_b) 
-                  : ((m-1.0)*log(a) + lgamma((m-1.0) + proposed_b/a) - lgamma(proposed_b/a)));
-      log_prob += (lgamma(1.0+proposed_b) - lgamma(n+proposed_b));
-      return log_prob + log_prior;
-    }
-  };
-   
-  /* lbetadist() returns the log probability density of x under a Beta(alpha,beta)
-   * distribution. - copied from Mark Johnson's gammadist.c
-   */
-  static long double lbetadist(long double x, long double alpha, long double beta);
-
-  /* lgammadist() returns the log probability density of x under a Gamma(alpha,beta)
-   * distribution - copied from Mark Johnson's gammadist.c
-   */
-  static long double lgammadist(long double x, long double alpha, long double beta);
-
-};
-
-template <typename Dish, typename Hash>
-PYP<Dish,Hash>::PYP(double a, double b, unsigned long seed, Hash)
-: std::tr1::unordered_map<Dish, int, Hash>(10), _a(a), _b(b), 
-//: google::sparse_hash_map<Dish, int, Hash>(10), _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)//,
-  //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;
-  //set_deleted_key(-std::numeric_limits<Dish>::max());
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::prob(Dish dish, double p0) const
-{
-  int c = count(dish), t = num_tables(dish);
-  double r = num_tables() * _a + _b;
-  //std::cerr << "\t\t\t\tPYP<Dish,Hash>::prob(" << dish << "," << p0 << ") c=" << c << " r=" << r << std::endl;
-  if (c > 0)
-    return (c - _a * t + r * p0) / (num_customers() + _b);
-  else
-    return r * p0 / (num_customers() + _b);
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::unnormalised_prob(Dish dish, double p0) const
-{
-  int c = count(dish), t = num_tables(dish);
-  double r = num_tables() * _a + _b;
-  if (c > 0) return (c - _a * t + r * p0);
-  else       return r * p0;
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::prob(Dish dish, double dcd, double dca, 
-                     double dtd, double dta, double p0)
-const
-{
-  int c = count(dish) + dcd, t = num_tables(dish) + dtd;
-  double r = (num_tables() + dta) * _a + _b;
-  if (c > 0)
-    return (c - _a * t + r * p0) / (num_customers() + dca + _b);
-  else
-    return r * p0 / (num_customers() + dca + _b);
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_prob(Dish dish, double log_p0) const
-{
-  using std::log;
-  int c = count(dish), t = num_tables(dish);
-  double r = log(num_tables() * _a + b);
-  if (c > 0)
-    return Log<double>::add(log(c - _a * t), r + log_p0)
-      - log(num_customers() + _b);
-  else
-    return r + log_p0 - log(num_customers() + b);
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_prob(Dish dish, double dcd, double dca, 
-                         double dtd, double dta, double log_p0)
-const
-{
-  using std::log;
-  int c = count(dish) + dcd, t = num_tables(dish) + dtd;
-  double r = log((num_tables() + dta) * _a + b);
-  if (c > 0)
-    return Log<double>::add(log(c - _a * t), r + log_p0)
-      - log(num_customers() + dca + _b);
-  else
-    return r + log_p0 - log(num_customers() + dca + b);
-}
-
-template <typename Dish, typename Hash>
-int 
-PYP<Dish,Hash>::increment(Dish dish, double p0) {
-  int delta = 0;
-  TableCounter &tc = _dish_tables[dish];
-
-  // seated on a new or existing table?
-  int c = count(dish), t = num_tables(dish), T = num_tables();
-  double pshare = (c > 0) ? (c - _a*t) : 0.0;
-  double pnew = (_b + _a*T) * p0;
-  assert (pshare >= 0.0);
-  //assert (pnew > 0.0);
-
-  //if (rnd() < pnew / (pshare + pnew)) {
-  if (mt_genrand_res53() < pnew / (pshare + pnew)) {
-    // assign to a new table
-    tc.tables += 1;
-    tc.table_histogram[1] += 1;
-    _total_tables += 1;
-    delta = 1;
-  }
-  else {
-    // randomly assign to an existing table
-    // remove constant denominator from inner loop
-    //double r = rnd() * (c - _a*t);
-    double r = mt_genrand_res53() * (c - _a*t);
-    for (std::map<int,int>::iterator
-         hit = tc.table_histogram.begin();
-         hit != tc.table_histogram.end(); ++hit) {
-      r -= ((hit->first - _a) * hit->second);
-      if (r <= 0) {
-        tc.table_histogram[hit->first+1] += 1;
-        hit->second -= 1;
-        if (hit->second == 0)
-          tc.table_histogram.erase(hit);
-        break;
-      }
-    }
-    if (r > 0) {
-      std::cerr << r << " " << c << " " << _a << " " << t << std::endl;
-      assert(false);
-    }
-    delta = 0;
-  }
-
-  std::tr1::unordered_map<Dish,int,Hash>::operator[](dish) += 1;
-  //google::sparse_hash_map<Dish,int,Hash>::operator[](dish) += 1;
-  _total_customers += 1;
-
-  return delta;
-}
-
-template <typename Dish, typename Hash>
-int 
-PYP<Dish,Hash>::count(Dish dish) const
-{
-  typename std::tr1::unordered_map<Dish, int>::const_iterator 
-  //typename google::sparse_hash_map<Dish, int>::const_iterator 
-    dcit = find(dish);
-  if (dcit != end())
-    return dcit->second;
-  else
-    return 0;
-}
-
-template <typename Dish, typename Hash>
-int 
-PYP<Dish,Hash>::decrement(Dish dish)
-{
-  typename std::tr1::unordered_map<Dish, int>::iterator dcit = find(dish);
-  //typename google::sparse_hash_map<Dish, int>::iterator dcit = find(dish);
-  if (dcit == end()) {
-    std::cerr << dish << std::endl;
-    assert(false);
-  } 
-
-  int delta = 0;
-
-  typename std::tr1::unordered_map<Dish, TableCounter>::iterator dtit = _dish_tables.find(dish);
-  //typename google::sparse_hash_map<Dish, TableCounter>::iterator dtit = _dish_tables.find(dish);
-  if (dtit == _dish_tables.end()) {
-    std::cerr << dish << std::endl;
-    assert(false);
-  } 
-  TableCounter &tc = dtit->second;
-
-  //std::cerr << "\tdecrement for " << dish << "\n";
-  //std::cerr << "\tBEFORE histogram: " << tc.table_histogram << " ";
-  //std::cerr << "count: " << count(dish) << " ";
-  //std::cerr << "tables: " << tc.tables << "\n";
-
-  //double r = rnd() * count(dish);
-  double r = mt_genrand_res53() * count(dish);
-  for (std::map<int,int>::iterator hit = tc.table_histogram.begin();
-       hit != tc.table_histogram.end(); ++hit)
-  {
-    //r -= (hit->first - _a) * hit->second;
-    r -= (hit->first) * hit->second;
-    if (r <= 0)
-    {
-      if (hit->first > 1)
-        tc.table_histogram[hit->first-1] += 1;
-      else
-      {
-        delta = -1;
-        tc.tables -= 1;
-        _total_tables -= 1;
-      }
-
-      hit->second -= 1;
-      if (hit->second == 0) tc.table_histogram.erase(hit);
-      break;
-    }
-  }
-  if (r > 0) {
-    std::cerr << r << " " << count(dish) << " " << _a << " " << num_tables(dish) << std::endl;
-    assert(false);
-  }
-
-  // remove the customer
-  dcit->second -= 1;
-  _total_customers -= 1;
-  assert(dcit->second >= 0);
-  if (dcit->second == 0) {
-    erase(dcit);
-    _dish_tables.erase(dtit);
-    //std::cerr << "\tAFTER histogram: Empty\n";
-  }
-  else {
-    //std::cerr << "\tAFTER histogram: " << _dish_tables[dish].table_histogram << " ";
-    //std::cerr << "count: " << count(dish) << " ";
-    //std::cerr << "tables: " << _dish_tables[dish].tables << "\n";
-  }
-
-  return delta;
-}
-
-template <typename Dish, typename Hash>
-int 
-PYP<Dish,Hash>::num_tables(Dish dish) const
-{
-  typename std::tr1::unordered_map<Dish, TableCounter, Hash>::const_iterator 
-  //typename google::sparse_hash_map<Dish, TableCounter, Hash>::const_iterator 
-    dtit = _dish_tables.find(dish);
-
-  //assert(dtit != _dish_tables.end());
-  if (dtit == _dish_tables.end())
-    return 0;
-
-  return dtit->second.tables;
-}
-
-template <typename Dish, typename Hash>
-int 
-PYP<Dish,Hash>::num_tables() const
-{
-  return _total_tables;
-}
-
-template <typename Dish, typename Hash>
-std::ostream&
-PYP<Dish,Hash>::debug_info(std::ostream& os) const
-{
-  int hists = 0, tables = 0;
-  for (typename std::tr1::unordered_map<Dish, TableCounter, Hash>::const_iterator 
-  //for (typename google::sparse_hash_map<Dish, TableCounter, Hash>::const_iterator 
-       dtit = _dish_tables.begin(); dtit != _dish_tables.end(); ++dtit)
-  {
-    hists += dtit->second.table_histogram.size();
-    tables += dtit->second.tables;
-
-//    if (dtit->second.tables <= 0)
-//      std::cerr << dtit->first << " " << count(dtit->first) << std::endl;
-    assert(dtit->second.tables > 0);
-    assert(!dtit->second.table_histogram.empty());
-
-//    os << "Dish " << dtit->first << " has " << count(dtit->first) << " customers, and is sitting at " << dtit->second.tables << " tables.\n"; 
-    for (std::map<int,int>::const_iterator 
-         hit = dtit->second.table_histogram.begin();
-         hit != dtit->second.table_histogram.end(); ++hit) {
-//      os << "    " << hit->second << " tables with " << hit->first << " customers." << std::endl; 
-      assert(hit->second > 0);
-    }
-  }
-
-  os << "restaurant has " 
-    << _total_customers << " customers; "
-    << _total_tables << " tables; " 
-    << tables << " tables'; " 
-    << num_types() << " dishes; "
-    << _dish_tables.size() << " dishes'; and "
-    << hists << " histogram entries\n";
-
-  return os;
-}
-
-template <typename Dish, typename Hash>
-void 
-PYP<Dish,Hash>::clear()
-{
-  this->std::tr1::unordered_map<Dish,int,Hash>::clear();
-  //this->google::sparse_hash_map<Dish,int,Hash>::clear();
-  _dish_tables.clear();
-  _total_tables = _total_customers = 0;
-}
-
-// log_restaurant_prob returns the log probability of the PYP table configuration.
-// Excludes Hierarchical P0 term which must be calculated separately.
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_restaurant_prob() const {
-  if (_total_customers < 1)
-    return (double)0.0;
-
-  double log_prob = 0.0;
-  double lgamma1a = lgamma(1.0-_a);
-
-  //std::cerr << "-------------------\n" << std::endl;
-  for (typename DishTableType::const_iterator dish_it=_dish_tables.begin(); 
-       dish_it != _dish_tables.end(); ++dish_it) {
-    for (std::map<int, int>::const_iterator table_it=dish_it->second.table_histogram.begin(); 
-         table_it !=dish_it->second.table_histogram.end(); ++table_it) {
-      log_prob += (table_it->second * (lgamma(table_it->first - _a) - lgamma1a));
-      //std::cerr << "|" << dish_it->first->parent << " --> " << dish_it->first->rhs << " " << table_it->first << " " << table_it->second << " " << log_prob;
-    }
-  }
-  //std::cerr << std::endl;
-
-  log_prob += (_a == (double)0.0 ? (_total_tables-1.0)*log(_b) : (_total_tables-1.0)*log(_a) + lgamma((_total_tables-1.0) + _b/_a) - lgamma(_b/_a));
-  //std::cerr << "\t\t" << log_prob << std::endl;
-  log_prob += (lgamma(1.0 + _b) - lgamma(_total_customers + _b));
-
-  //std::cerr << _total_customers << " " << _total_tables << " " << log_prob << " " << log_prior() << std::endl;
-  //std::cerr << _a << " " << _b << std::endl;
-  if (!std::isfinite(log_prob)) {
-    assert(false);
-  }
-  //return log_prob;
-  if (log_prob > 0.0)
-    std::cerr << log_prob << std::endl;
-  return log_prob;// + log_prior();
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_prior() const {
-  double prior = 0.0;
-  if (_a_beta_a > 0.0 && _a_beta_b > 0.0 && _a > 0.0)
-    prior += log_prior_a(_a, _a_beta_a, _a_beta_b);
-  if (_b_gamma_s > 0.0 && _b_gamma_c > 0.0)
-    prior += log_prior_b(_b, _b_gamma_c, _b_gamma_s);
-
-  return prior;
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_prior_a(double a, double beta_a, double beta_b) {
-  return lbetadist(a, beta_a, beta_b); 
-}
-
-template <typename Dish, typename Hash>
-double 
-PYP<Dish,Hash>::log_prior_b(double b, double gamma_c, double gamma_s) {
-  return lgammadist(b, gamma_c, gamma_s); 
-}
-
-template <typename Dish, typename Hash>
-long double PYP<Dish,Hash>::lbetadist(long double x, long double alpha, long double beta) {
-  assert(x > 0);
-  assert(x < 1);
-  assert(alpha > 0);
-  assert(beta > 0);
-  return (alpha-1)*log(x)+(beta-1)*log(1-x)+lgamma(alpha+beta)-lgamma(alpha)-lgamma(beta);
-//boost::math::lgamma
-}
-
-template <typename Dish, typename Hash>
-long double PYP<Dish,Hash>::lgammadist(long double x, long double alpha, long double beta) {
-  assert(alpha > 0);
-  assert(beta > 0);
-  return (alpha-1)*log(x) - alpha*log(beta) - x/beta - lgamma(alpha);
-}
-
-
-template <typename Dish, typename Hash>
-  template <typename Uniform01>
-void 
-PYP<Dish,Hash>::resample_prior(Uniform01& rnd) {
-  for (int num_its=5; num_its >= 0; --num_its) {
-    resample_prior_b(rnd);
-    resample_prior_a(rnd);
-  }
-  resample_prior_b(rnd);
-}
-
-template <typename Dish, typename Hash>
-  template <typename Uniform01>
-void 
-PYP<Dish,Hash>::resample_prior_b(Uniform01& rnd) {
-  if (_total_tables == 0) 
-    return;
-
-  //int niterations = 10;   // number of resampling iterations
-  int niterations = 5;   // 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, rnd, (double) 0.0, std::numeric_limits<double>::infinity(), 
-  //_b = slice_sampler1d(b_log_prob, _b, mt_genrand_res53, (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;
-}
-
-template <typename Dish, typename Hash>
-  template <typename Uniform01>
-void 
-PYP<Dish,Hash>::resample_prior_a(Uniform01& rnd) {
-  if (_total_tables == 0) 
-    return;
-
-  //int niterations = 10;
-  int niterations = 5;
-  //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, rnd, std::numeric_limits<double>::min(), 
-  //_a = slice_sampler1d(a_log_prob, _a, mt_genrand_res53, std::numeric_limits<double>::min(), 
-                       (double) 1.0, (double) 0.0, niterations, 100*niterations);
-}
-
-#endif
diff --git a/gi/pyp-topics/src/slice-sampler.h b/gi/pyp-topics/src/slice-sampler.h
deleted file mode 100644
index 3108a0f7..00000000
--- a/gi/pyp-topics/src/slice-sampler.h
+++ /dev/null
@@ -1,192 +0,0 @@
-//! slice-sampler.h is an MCMC slice sampler
-//!
-//! Mark Johnson, 1st August 2008
-
-#ifndef SLICE_SAMPLER_H
-#define SLICE_SAMPLER_H
-
-#include <algorithm>
-#include <cassert>
-#include <cmath>
-#include <iostream>
-#include <limits>
-
-//! slice_sampler_rfc_type{} returns the value of a user-specified
-//! function if the argument is within range, or - infinity otherwise
-//
-template <typename F, typename Fn, typename U>
-struct slice_sampler_rfc_type {
-  F min_x, max_x;
-  const Fn& f;
-  U max_nfeval, nfeval;
-  slice_sampler_rfc_type(F min_x, F max_x, const Fn& f, U max_nfeval) 
-    : min_x(min_x), max_x(max_x), f(f), max_nfeval(max_nfeval), nfeval(0) { }
-    
-  F operator() (F x) {
-    if (min_x < x && x < max_x) {
-      assert(++nfeval <= max_nfeval);
-      F fx = f(x);
-      assert(std::isfinite(fx));
-      return fx;
-    }
-    else
-      return -std::numeric_limits<F>::infinity();
-  }
-};  // slice_sampler_rfc_type{}
-
-//! slice_sampler1d() implements the univariate "range doubling" slice sampler
-//! described in Neal (2003) "Slice Sampling", The Annals of Statistics 31(3), 705-767.
-//
-template <typename F, typename LogF, typename Uniform01>
-F slice_sampler1d(const LogF& logF0,               //!< log of function to sample
-		  F x,                             //!< starting point
-		  Uniform01& u01,                  //!< uniform [0,1) random number generator
-		  F min_x = -std::numeric_limits<F>::infinity(),  //!< minimum value of support
-		  F max_x = std::numeric_limits<F>::infinity(),   //!< maximum value of support
-		  F w = 0.0,                       //!< guess at initial width
-		  unsigned nsamples=1,             //!< number of samples to draw
-		  unsigned max_nfeval=200)         //!< max number of function evaluations
-{
-  typedef unsigned U;
-  slice_sampler_rfc_type<F,LogF,U> logF(min_x, max_x, logF0, max_nfeval);
-
-  assert(std::isfinite(x));
-
-  if (w <= 0.0) {                           // set w to a default width 
-    if (min_x > -std::numeric_limits<F>::infinity() && max_x < std::numeric_limits<F>::infinity())
-      w = (max_x - min_x)/4;
-    else
-      w = std::max(((x < 0.0) ? -x : x)/4, (F) 0.1);
-  }
-  assert(std::isfinite(w));
-
-  F logFx = logF(x);
-  for (U sample = 0; sample < nsamples; ++sample) {
-    F logY = logFx + log(u01()+1e-100);     //! slice logFx at this value
-    assert(std::isfinite(logY));
-
-    F xl = x - w*u01();                     //! lower bound on slice interval
-    F logFxl = logF(xl);
-    F xr = xl + w;                          //! upper bound on slice interval
-    F logFxr = logF(xr);
-
-    while (logY < logFxl || logY < logFxr)  // doubling procedure
-      if (u01() < 0.5) 
-	logFxl = logF(xl -= xr - xl);
-      else
-	logFxr = logF(xr += xr - xl);
-	
-    F xl1 = xl;
-    F xr1 = xr;
-    while (true) {                          // shrinking procedure
-      F x1 = xl1 + u01()*(xr1 - xl1);
-      if (logY < logF(x1)) {
-	F xl2 = xl;                         // acceptance procedure
-	F xr2 = xr; 
-	bool d = false;
-	while (xr2 - xl2 > 1.1*w) {
-	  F xm = (xl2 + xr2)/2;
-	  if ((x < xm && x1 >= xm) || (x >= xm && x1 < xm))
-	    d = true;
-	  if (x1 < xm)
-	    xr2 = xm;
-	  else
-	    xl2 = xm;
-	  if (d && logY >= logF(xl2) && logY >= logF(xr2))
-	    goto unacceptable;
-	}
-	x = x1;
-	goto acceptable;
-      }
-      goto acceptable;
-    unacceptable:
-      if (x1 < x)                           // rest of shrinking procedure
-	xl1 = x1;
-      else 
-	xr1 = x1;
-    }
-  acceptable:
-    w = (4*w + (xr1 - xl1))/5;              // update width estimate
-  }
-  return x;
-}
-
-/*
-//! slice_sampler1d() implements a 1-d MCMC slice sampler.
-//! It should be correct for unimodal distributions, but
-//! not for multimodal ones.
-//
-template <typename F, typename LogP, typename Uniform01>
-F slice_sampler1d(const LogP& logP,     //!< log of distribution to sample
-		  F x,                  //!< initial sample
-		  Uniform01& u01,       //!< uniform random number generator
-		  F min_x = -std::numeric_limits<F>::infinity(),  //!< minimum value of support
-		  F max_x = std::numeric_limits<F>::infinity(),   //!< maximum value of support
-		  F w = 0.0,            //!< guess at initial width
-		  unsigned nsamples=1,  //!< number of samples to draw
-		  unsigned max_nfeval=200)  //!< max number of function evaluations
-{
-  typedef unsigned U;
-  assert(std::isfinite(x));
-  if (w <= 0.0) {
-    if (min_x > -std::numeric_limits<F>::infinity() && max_x < std::numeric_limits<F>::infinity())
-      w = (max_x - min_x)/4;
-    else
-      w = std::max(((x < 0.0) ? -x : x)/4, 0.1);
-  }
-  // TRACE4(x, min_x, max_x, w);
-  F logPx = logP(x);
-  assert(std::isfinite(logPx));
-  U nfeval = 1;
-  for (U sample = 0; sample < nsamples; ++sample) {
-    F x0 = x;
-    F logU = logPx + log(u01()+1e-100);
-    assert(std::isfinite(logU));
-    F r = u01();
-    F xl = std::max(min_x, x - r*w);
-    F xr = std::min(max_x, x + (1-r)*w);
-    // TRACE3(x, logPx, logU);
-    while (xl > min_x && logP(xl) > logU) {
-      xl -= w;
-      w *= 2;
-      ++nfeval;
-      if (nfeval >= max_nfeval)
-	std::cerr << "## Error: nfeval = " << nfeval << ", max_nfeval = " << max_nfeval << ", sample = " << sample << ", nsamples = " << nsamples << ", r = " << r << ", w = " << w << ", xl = " << xl << std::endl;
-      assert(nfeval < max_nfeval);
-    }
-    xl = std::max(xl, min_x);
-    while (xr < max_x && logP(xr) > logU) {
-      xr += w;
-      w *= 2;
-      ++nfeval;
-      if (nfeval >= max_nfeval)
-	std::cerr << "## Error: nfeval = " << nfeval << ", max_nfeval = " << max_nfeval << ", sample = " << sample << ", nsamples = " << nsamples << ", r = " << r << ", w = " << w << ", xr = " << xr << std::endl;
-      assert(nfeval < max_nfeval);
-    }
-    xr = std::min(xr, max_x);
-    while (true) {
-      r = u01();
-      x = r*xl + (1-r)*xr;
-      assert(std::isfinite(x));
-      logPx = logP(x);
-      // TRACE4(logPx, x, xl, xr);
-      assert(std::isfinite(logPx));
-      ++nfeval;
-      if (nfeval >= max_nfeval)
-	std::cerr << "## Error: nfeval = " << nfeval << ", max_nfeval = " << max_nfeval << ", sample = " << sample << ", nsamples = " << nsamples << ", r = " << r << ", w = " << w << ", xl = " << xl << ", xr = " << xr << ", x = " << x << std::endl;
-      assert(nfeval < max_nfeval);
-      if (logPx > logU)
-        break;
-      else if (x > x0)
-          xr = x;
-        else
-          xl = x;
-    }
-    // w = (4*w + (xr-xl))/5;   // gradually adjust w
-  }
-  // TRACE2(logPx, x);
-  return x;
-}  // slice_sampler1d()
-*/
-
-#endif  // SLICE_SAMPLER_H
diff --git a/gi/pyp-topics/src/timing.h b/gi/pyp-topics/src/timing.h
deleted file mode 100644
index 08360b0f..00000000
--- a/gi/pyp-topics/src/timing.h
+++ /dev/null
@@ -1,37 +0,0 @@
-#ifndef TIMING_H
-#define TIMING_H
-
-#ifdef __CYGWIN__
-# ifndef _POSIX_MONOTONIC_CLOCK
-#  define _POSIX_MONOTONIC_CLOCK
-// this modifies <time.h>
-# endif
-// in case someone included <time.h> before we got here (this is lifted from time.h>)
-# ifndef CLOCK_MONOTONIC
-#  define CLOCK_MONOTONIC (clockid_t)4
-# endif
-#endif
-
-
-#include <time.h>
-#include <sys/time.h>
-#include "clock_gettime_stub.c"
-
-struct Timer {
-  Timer() { Reset(); }
-  void Reset()
-  {
-    clock_gettime(CLOCK_MONOTONIC, &start_t);
-  }
-  double Elapsed() const {
-    timespec end_t;
-    clock_gettime(CLOCK_MONOTONIC, &end_t);
-    const double elapsed = (end_t.tv_sec - start_t.tv_sec)
-                + (end_t.tv_nsec - start_t.tv_nsec) / 1000000000.0;
-    return elapsed;
-  }
- private:
-  timespec start_t;
-};
-
-#endif
diff --git a/gi/pyp-topics/src/train-contexts.cc b/gi/pyp-topics/src/train-contexts.cc
deleted file mode 100644
index 9463f9fc..00000000
--- a/gi/pyp-topics/src/train-contexts.cc
+++ /dev/null
@@ -1,174 +0,0 @@
-// STL
-#include <iostream>
-#include <fstream>
-#include <algorithm>
-#include <iterator>
-
-// Boost
-#include <boost/program_options/parsers.hpp>
-#include <boost/program_options/variables_map.hpp>
-#include <boost/scoped_ptr.hpp>
-
-// Local
-#include "pyp-topics.hh"
-#include "corpus.hh"
-#include "contexts_corpus.hh"
-#include "gzstream.hh"
-
-static const char *REVISION = "$Rev$";
-
-// Namespaces
-using namespace boost;
-using namespace boost::program_options;
-using namespace std;
-
-int main(int argc, char **argv)
-{
- cout << "Pitman Yor topic models: Copyright 2010 Phil Blunsom\n";
- cout << REVISION << '\n' <<endl;
-
-  ////////////////////////////////////////////////////////////////////////////////////////////
-  // Command line processing
-  variables_map vm; 
-
-  // Command line processing
-  {
-    options_description cmdline_specific("Command line specific options");
-    cmdline_specific.add_options()
-      ("help,h", "print help message")
-      ("config,c", value<string>(), "config file specifying additional command line options")
-      ;
-    options_description config_options("Allowed options");
-    config_options.add_options()
-      ("data,d", value<string>(), "file containing the documents and context terms")
-      ("topics,t", value<int>()->default_value(50), "number of topics")
-      ("document-topics-out,o", value<string>(), "file to write the document topics to")
-      ("default-topics-out", value<string>(), "file to write default term topic assignments.")
-      ("topic-words-out,w", value<string>(), "file to write the topic word distribution to")
-      ("samples,s", value<int>()->default_value(10), "number of sampling passes through the data")
-      ("backoff-type", value<string>(), "backoff type: none|simple")
-//      ("filter-singleton-contexts", "filter singleton contexts")
-      ("hierarchical-topics", "Use a backoff hierarchical PYP as the P0 for the document topics distribution.")
-      ("freq-cutoff-start", value<int>()->default_value(0), "initial frequency cutoff.")
-      ("freq-cutoff-end", value<int>()->default_value(0), "final frequency cutoff.")
-      ("freq-cutoff-interval", value<int>()->default_value(0), "number of iterations between frequency decrement.")
-      ("max-threads", value<int>()->default_value(1), "maximum number of simultaneous threads allowed")
-      ("max-contexts-per-document", value<int>()->default_value(0), "Only sample the n most frequent contexts for a document.")
-      ("num-jobs", value<int>()->default_value(1), "allows finer control over parallelization")
-      ("temp-start", value<double>()->default_value(1.0), "starting annealing temperature.")
-      ("temp-end", value<double>()->default_value(1.0), "end annealing temperature.")
-      ;
-
-    cmdline_specific.add(config_options);
-
-    store(parse_command_line(argc, argv, cmdline_specific), vm); 
-    notify(vm);
-
-    if (vm.count("config") > 0) {
-      ifstream config(vm["config"].as<string>().c_str());
-      store(parse_config_file(config, config_options), vm); 
-    }
-
-    if (vm.count("help")) { 
-      cout << cmdline_specific << "\n"; 
-      return 1; 
-    }
-  }
-  ////////////////////////////////////////////////////////////////////////////////////////////
-
-  if (!vm.count("data")) {
-    cerr << "Please specify a file containing the data." << endl;
-    return 1;
-  }
-  assert(vm["max-threads"].as<int>() > 0);
-  assert(vm["num-jobs"].as<int>() > -1);
-  // 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, vm["max-threads"].as<int>(), vm["num-jobs"].as<int>());
-
-  // read the data
-  BackoffGenerator* backoff_gen=0;
-  if (vm.count("backoff-type")) {
-    if (vm["backoff-type"].as<std::string>() == "none") {
-      backoff_gen = 0;
-    }
-    else if (vm["backoff-type"].as<std::string>() == "simple") {
-      backoff_gen = new SimpleBackoffGenerator();
-    }
-    else {
-     cerr << "Backoff type (--backoff-type) must be one of none|simple." <<endl;
-      return(1);
-    }
-  }
-
-  ContextsCorpus contexts_corpus;
-  contexts_corpus.read_contexts(vm["data"].as<string>(), backoff_gen, /*vm.count("filter-singleton-contexts")*/ false);
-  model.set_backoff(contexts_corpus.backoff_index());
-
-  if (backoff_gen) 
-    delete backoff_gen;
-
-  // train the sampler
-  model.sample_corpus(contexts_corpus, vm["samples"].as<int>(),
-                      vm["freq-cutoff-start"].as<int>(),
-                      vm["freq-cutoff-end"].as<int>(),
-                      vm["freq-cutoff-interval"].as<int>(),
-                      vm["max-contexts-per-document"].as<int>(),
-                      vm["temp-start"].as<double>(), vm["temp-end"].as<double>());
-
-  if (vm.count("document-topics-out")) {
-    ogzstream documents_out(vm["document-topics-out"].as<string>().c_str());
-
-    int document_id=0;
-    map<int,int> all_terms;
-    for (Corpus::const_iterator corpusIt=contexts_corpus.begin(); 
-         corpusIt != contexts_corpus.end(); ++corpusIt, ++document_id) {
-      vector<int> unique_terms;
-      for (Document::const_iterator docIt=corpusIt->begin();
-           docIt != corpusIt->end(); ++docIt) {
-        if (unique_terms.empty() || *docIt != unique_terms.back())
-          unique_terms.push_back(*docIt);
-        // increment this terms frequency
-        pair<map<int,int>::iterator,bool> insert_result = all_terms.insert(make_pair(*docIt,1));
-        if (!insert_result.second) 
-          all_terms[*docIt] = all_terms[*docIt] + 1;
-          //insert_result.first++;
-      }
-      documents_out << contexts_corpus.key(document_id) << '\t';
-      documents_out << model.max(document_id).first << " " << corpusIt->size() << " ||| ";
-      for (std::vector<int>::const_iterator termIt=unique_terms.begin();
-           termIt != unique_terms.end(); ++termIt) {
-        if (termIt != unique_terms.begin())
-          documents_out << " ||| ";
-       vector<std::string> strings = contexts_corpus.context2string(*termIt);
-       copy(strings.begin(), strings.end(),ostream_iterator<std::string>(documents_out, " "));
-        std::pair<int,PYPTopics::F> maxinfo = model.max(document_id, *termIt);
-        documents_out << "||| C=" << maxinfo.first << " P=" << maxinfo.second;
-
-      }
-      documents_out <<endl;
-    }
-    documents_out.close();
-
-    if (vm.count("default-topics-out")) {
-      ofstream default_topics(vm["default-topics-out"].as<string>().c_str());
-      default_topics << model.max_topic() <<endl;
-      for (std::map<int,int>::const_iterator termIt=all_terms.begin(); termIt != all_terms.end(); ++termIt) {
-       vector<std::string> strings = contexts_corpus.context2string(termIt->first);
-        default_topics << model.max(-1, termIt->first).first << " ||| " << termIt->second << " ||| ";
-       copy(strings.begin(), strings.end(),ostream_iterator<std::string>(default_topics, " "));
-        default_topics <<endl;
-      }
-    }
-  }
-
-  if (vm.count("topic-words-out")) {
-    ogzstream topics_out(vm["topic-words-out"].as<string>().c_str());
-    model.print_topic_terms(topics_out);
-    topics_out.close();
-  }
-
- cout <<endl;
-
-  return 0;
-}
diff --git a/gi/pyp-topics/src/train.cc b/gi/pyp-topics/src/train.cc
deleted file mode 100644
index db7ca46e..00000000
--- a/gi/pyp-topics/src/train.cc
+++ /dev/null
@@ -1,135 +0,0 @@
-// STL
-#include <iostream>
-#include <fstream>
-
-// Boost
-#include <boost/program_options/parsers.hpp>
-#include <boost/program_options/variables_map.hpp>
-#include <boost/scoped_ptr.hpp>
-
-// Local
-#include "pyp-topics.hh"
-#include "corpus.hh"
-#include "contexts_corpus.hh"
-#include "gzstream.hh"
-
-static const char *REVISION = "$Rev$";
-
-// Namespaces
-using namespace boost;
-using namespace boost::program_options;
-using namespace std;
-
-int main(int argc, char **argv)
-{
-  std::cout << "Pitman Yor topic models: Copyright 2010 Phil Blunsom\n";
-  std::cout << REVISION << '\n' << std::endl;
-
-  ////////////////////////////////////////////////////////////////////////////////////////////
-  // Command line processing
-  variables_map vm; 
-
-  // Command line processing
-  options_description cmdline_specific("Command line specific options");
-  cmdline_specific.add_options()
-    ("help,h", "print help message")
-    ("config,c", value<string>(), "config file specifying additional command line options")
-    ;
-  options_description generic("Allowed options");
-  generic.add_options()
-    ("documents,d", value<string>(), "file containing the documents")
-    ("topics,t", value<int>()->default_value(50), "number of topics")
-    ("document-topics-out,o", value<string>(), "file to write the document topics to")
-    ("topic-words-out,w", value<string>(), "file to write the topic word distribution to")
-    ("samples,s", value<int>()->default_value(10), "number of sampling passes through the data")
-    ("test-corpus", value<string>(), "file containing the test data")
-    ("backoff-paths", value<string>(), "file containing the term backoff paths")
-    ;
-  options_description config_options, cmdline_options;
-  config_options.add(generic);
-  cmdline_options.add(generic).add(cmdline_specific);
-
-  store(parse_command_line(argc, argv, cmdline_options), vm); 
-  if (vm.count("config") > 0) {
-    ifstream config(vm["config"].as<string>().c_str());
-    store(parse_config_file(config, cmdline_options), vm); 
-  }
-  notify(vm);
-  ////////////////////////////////////////////////////////////////////////////////////////////
-
-  if (vm.count("documents") == 0) {
-    cerr << "Please specify a file containing the documents." << endl;
-    cout << cmdline_options << "\n"; 
-    return 1;
-  }
-
-  if (vm.count("help")) { 
-    cout << cmdline_options << "\n"; 
-    return 1; 
-  }
-
-  // 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;
-  corpus.read(vm["documents"].as<string>());
-
-  // read the backoff dictionary
-  if (vm.count("backoff-paths"))
-    model.set_backoff(vm["backoff-paths"].as<string>());
-
-  // train the sampler
-  model.sample_corpus(corpus, vm["samples"].as<int>());
-
-  if (vm.count("document-topics-out")) {
-    ogzstream documents_out(vm["document-topics-out"].as<string>().c_str());
-    //model.print_document_topics(documents_out);
-
-    int document_id=0;
-    for (Corpus::const_iterator corpusIt=corpus.begin(); 
-         corpusIt != corpus.end(); ++corpusIt, ++document_id) {
-      std::vector<int> unique_terms;
-      for (Document::const_iterator docIt=corpusIt->begin();
-           docIt != corpusIt->end(); ++docIt) {
-        if (unique_terms.empty() || *docIt != unique_terms.back())
-          unique_terms.push_back(*docIt);
-      }
-      documents_out << unique_terms.size();
-      for (std::vector<int>::const_iterator termIt=unique_terms.begin();
-           termIt != unique_terms.end(); ++termIt)
-        documents_out << " " << *termIt << ":" << model.max(document_id, *termIt).first;
-      documents_out << std::endl;
-    }
-    documents_out.close();
-  }
-
-  if (vm.count("topic-words-out")) {
-    ogzstream topics_out(vm["topic-words-out"].as<string>().c_str());
-    model.print_topic_terms(topics_out);
-    topics_out.close();
-  }
-
-  if (vm.count("test-corpus")) {
-    TestCorpus test_corpus;
-    test_corpus.read(vm["test-corpus"].as<string>());
-    ogzstream topics_out((vm["test-corpus"].as<string>() + ".topics.gz").c_str());
-
-    for (TestCorpus::const_iterator corpusIt=test_corpus.begin(); 
-         corpusIt != test_corpus.end(); ++corpusIt) {
-      int index=0;
-      for (DocumentTerms::const_iterator instanceIt=corpusIt->begin();
-           instanceIt != corpusIt->end(); ++instanceIt, ++index) {
-        int topic = model.max(instanceIt->doc, instanceIt->term).first;
-        if (index != 0) topics_out << " ";
-        topics_out << topic;
-      }
-      topics_out << std::endl;
-    }
-    topics_out.close();
-  }
-  std::cout << std::endl;
-
-  return 0;
-}
diff --git a/gi/pyp-topics/src/utility.h b/gi/pyp-topics/src/utility.h
deleted file mode 100644
index 405a5b0a..00000000
--- a/gi/pyp-topics/src/utility.h
+++ /dev/null
@@ -1,962 +0,0 @@
-// utility.h
-//
-// (c) Mark Johnson, 24th January 2005
-//
-// modified 6th May 2002 to ensure write/read consistency, fixed 18th July 2002
-// modified 14th July 2002 to include insert() (generic inserter)
-// modified 26th September 2003 to use mapped_type instead of data_type
-// 25th August 2004 added istream >> const char*
-// 24th January 2005 added insert_newkey()
-//
-// Defines:
-//  loop macros foreach, cforeach
-//  dfind (default find function)
-//  afind (find function that asserts key exists)
-//  insert_newkey (inserts a new key into a map)
-//  insert (generic inserter into standard data structures)
-//  disjoint (set operation)
-//  first_lessthan and second_lessthan (compares elements of pairs)
-//
-// Simplified interfaces to STL routines:
-//
-//  includes (simplified interface)
-//  set_intersection (simplified interface)
-//  inserter (simplified interface)
-//  max_element (simplified interface)
-//  min_element (simplified interface)
-//  hash functions for pairs, vectors, lists, slists and maps
-//  input and output for pairs and vectors
-//  resource_usage (interface improved)
-
-
-#ifndef UTILITY_H
-#define UTILITY_H
-
-#include <algorithm>
-// #include <boost/smart_ptr.hpp>    // Comment out this line if boost is not used
-#include <cassert>
-#include <cmath>
-#include <cctype>
-#include <cstdio>
-#include <unordered_map>
-#include <unordered_set>
-#include <ext/slist>
-#include <iostream>
-#include <iterator>
-#include <list>
-#include <map>
-#include <set>
-#include <string>
-#include <utility>
-#include <vector>
-#include <memory>
-
-#if (__GNUC__ > 3) || (__GNUC__ >= 3 && __GNUC_MINOR__ >= 1)
-#define EXT_NAMESPACE __gnu_cxx
-#else
-#define EXT_NAMESPACE std
-#endif
-
-namespace ext = EXT_NAMESPACE;
-
-inline float power(float x, float y) { return powf(x, y); }
-inline double power(double x, double y) { return pow(x, y); }
-inline long double power(long double x, long double y) { return powl(x, y); }
-
-typedef unsigned U;
-typedef long double F;  // slower than double, but underflows less
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                              Looping constructs                       //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-// foreach is a simple loop construct
-//
-//   STORE should be an STL container
-//   TYPE is the typename of STORE
-//   VAR will be defined as a local variable of type TYPE::iterator
-//
-#define foreach(TYPE, VAR, STORE) \
-  for (TYPE::iterator VAR = (STORE).begin(); VAR != (STORE).end(); ++VAR)
-
-// cforeach is just like foreach, except that VAR is a const_iterator
-//
-//   STORE should be an STL container
-//   TYPE is the typename of STORE
-//   VAR will be defined as a local variable of type TYPE::const_iterator
-//
-#define cforeach(TYPE, VAR, STORE) \
-  for (TYPE::const_iterator VAR = (STORE).begin(); VAR != (STORE).end(); ++VAR)
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                             Map searching                             //
-//                                                                       //
-// dfind(map, key) returns the key's value in map, or map's default      //
-//   value if no such key exists (the default value is not inserted)     //
-//                                                                       //
-// afind(map, key) returns a reference to the key's value in map, and    //
-//    asserts that this value exists                                     //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-// dfind(Map, Key) returns the value Map associates with Key, or the
-//  Map's default value if no such Key exists
-//
-template <class Map, class Key>
-inline typename Map::mapped_type dfind(Map& m, const Key& k)
-{
-  typename Map::iterator i = m.find(k);
-  if (i == m.end())
-    return typename Map::mapped_type();
-  else
-    return i->second;
-}
-
-template <class Map, class Key>
-inline const typename Map::mapped_type dfind(const Map& m, const Key& k)
-{
-  typename Map::const_iterator i = m.find(k);
-  if (i == m.end())
-    return typename Map::mapped_type();
-  else
-    return i->second;
-}
-
-
-// afind(map, key) returns a reference to the value associated
-//  with key in map.  It uses assert to check that the key's value
-//  is defined.
-//
-template <class Map, class Key>
-inline typename Map::mapped_type& afind(Map& m, const Key& k)
-{
-  typename Map::iterator i = m.find(k);
-  assert(i != m.end());
-  return i->second;
-}
-
-template <class Map, class Key>
-inline const typename Map::mapped_type& afind(const Map& m, const Key& k)
-{
-  typename Map::const_iterator i = m.find(k);
-  assert(i != m.end());
-  return i->second;
-}
-
-//! insert_newkey(map, key, value) checks that map does not contain
-//! key, and binds key to value.
-//
-template <class Map, class Key, class Value>
-inline typename Map::value_type& 
-insert_newkey(Map& m, const Key& k,const Value& v) 
-{
-  std::pair<typename Map::iterator, bool> itb 
-    = m.insert(Map::value_type(k, v));
-  assert(itb.second);
-  return *(itb.first);
-}  // insert_newkey()
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                        Insert operations                              //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-
-template <typename T>
-void insert(std::list<T>& xs, const T& x) {
-  xs.push_back(x);
-}
-
-template <typename T>
-void insert(std::set<T>& xs, const T& x) {
-  xs.insert(x);
-}
-
-template <typename T>
-void insert(std::vector<T>& xs, const T& x) {
-  xs.push_back(x);
-}
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                Additional versions of standard algorithms             //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-template <typename Set1, typename Set2>
-inline bool includes(const Set1& set1, const Set2& set2)
-{
-  return std::includes(set1.begin(), set1.end(), set2.begin(), set2.end());
-}
-
-template <typename Set1, typename Set2, typename Compare>
-inline bool includes(const Set1& set1, const Set2& set2, Compare comp)
-{
-  return std::includes(set1.begin(), set1.end(), set2.begin(), set2.end(), comp);
-}
-
-
-template <typename InputIter1, typename InputIter2>
-bool disjoint(InputIter1 first1, InputIter1 last1,
-              InputIter2 first2, InputIter2 last2)
-{
-  while (first1 != last1 && first2 != last2)
-    if (*first1 < *first2)
-      ++first1;
-    else if (*first2 < *first1)
-      ++first2;
-    else // *first1 == *first2
-      return false;
-  return true;
-}
-
-template <typename InputIter1, typename InputIter2, typename Compare>
-bool disjoint(InputIter1 first1, InputIter1 last1,
-              InputIter2 first2, InputIter2 last2, Compare comp)
-{
-  while (first1 != last1 && first2 != last2)
-    if (comp(*first1, *first2))
-      ++first1;
-    else if (comp(*first2, *first1))
-      ++first2;
-    else // *first1 == *first2
-      return false;
-  return true;
-}
-
-template <typename Set1, typename Set2>
-inline bool disjoint(const Set1& set1, const Set2& set2)
-{
-  return disjoint(set1.begin(), set1.end(), set2.begin(), set2.end());
-}
-
-template <typename Set1, typename Set2, typename Compare>
-inline bool disjoint(const Set1& set1, const Set2& set2, Compare comp)
-{
-  return disjoint(set1.begin(), set1.end(), set2.begin(), set2.end(), comp);
-}
-
-
-template <typename Set1, typename Set2, typename OutputIterator>
-inline OutputIterator set_intersection(const Set1& set1, const Set2& set2, 
-                                       OutputIterator result)
-{
-  return set_intersection(set1.begin(), set1.end(), set2.begin(), set2.end(), result);
-}
-
-template <typename Set1, typename Set2, typename OutputIterator, typename Compare>
-inline OutputIterator set_intersection(const Set1& set1, const Set2& set2, 
-                                       OutputIterator result, Compare comp)
-{
-  return set_intersection(set1.begin(), set1.end(), set2.begin(), set2.end(), result, comp);
-}
-
-
-template <typename Container>
-inline std::insert_iterator<Container> inserter(Container& container)
-{
-  return std::inserter(container, container.begin());
-}
-
-// max_element
-//
-template <class Es> inline typename Es::iterator max_element(Es& es)
-{
-  return std::max_element(es.begin(), es.end());
-}
-
-template <class Es> inline typename Es::const_iterator max_element(const Es& es)
-{
-  return std::max_element(es.begin(), es.end());
-}
-
-template <class Es, class BinaryPredicate> 
-inline typename Es::iterator max_element(Es& es, BinaryPredicate comp)
-{
-  return std::max_element(es.begin(), es.end(), comp);
-}
-
-template <class Es, class BinaryPredicate> 
-inline typename Es::const_iterator max_element(const Es& es, BinaryPredicate comp)
-{
-  return std::max_element(es.begin(), es.end(), comp);
-}
-
-// min_element
-//
-template <class Es> inline typename Es::iterator min_element(Es& es)
-{
-  return std::min_element(es.begin(), es.end());
-}
-
-template <class Es> inline typename Es::const_iterator min_element(const Es& es)
-{
-  return std::min_element(es.begin(), es.end());
-}
-
-template <class Es, class BinaryPredicate> 
-inline typename Es::iterator min_element(Es& es, BinaryPredicate comp)
-{
-  return std::min_element(es.begin(), es.end(), comp);
-}
-
-template <class Es, class BinaryPredicate> 
-inline typename Es::const_iterator min_element(const Es& es, BinaryPredicate comp)
-{
-  return std::min_element(es.begin(), es.end(), comp);
-}
-
-// first_lessthan and second_lessthan
-//
-struct first_lessthan {
-  template <typename T1, typename T2>
-    bool operator() (const T1& e1, const T2& e2) {
-      return e1.first < e2.first;
-    }
-};
-
-struct second_lessthan {
-  template <typename T1, typename T2>
-    bool operator() (const T1& e1, const T2& e2) {
-      return e1.second < e2.second;
-    }
-};
-
-// first_greaterthan and second_greaterthan
-//
-struct first_greaterthan {
-  template <typename T1, typename T2>
-    bool operator() (const T1& e1, const T2& e2) {
-      return e1.first > e2.first;
-    }
-};
-
-struct second_greaterthan {
-  template <typename T1, typename T2>
-    bool operator() (const T1& e1, const T2& e2) {
-      return e1.second > e2.second;
-    }
-};
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                          hash<> specializations                       //
-//                                                                       //
-// These must be in namespace std.   They permit the corresponding STL   //
-// container to be used as a key in an STL hash table.                   //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-//namespace EXT_NAMESPACE {
-namespace std {
-  /*
-  // hash function for bool
-  //
-  template <> struct hash<bool>
-  {
-  size_t operator() (bool b) const 
-  {
-  return b;
-  } // operator()
-  }; // hash<bool>{}
-
-  // hash function for double
-  //
-  template <> struct hash<double>
-  {
-  size_t operator() (double d) const 
-  {
-  int exponent;
-  double fraction = frexp(d, &exponent);
-  return size_t(exponent) ^ size_t(1000000.0*(fabs(fraction-0.5)));
-  } // operator()
-  }; // hash<double>{}
-
-  // hash function for strings
-  //
-  template <> struct hash<std::string> 
-  {
-  size_t operator()(const std::string& s) const 
-  {
-  typedef std::string::const_iterator CI;
-
-  unsigned long h = 0; 
-  unsigned long g;
-  CI p = s.begin();
-  CI end = s.end();
-
-  while (p!=end) {
-  h = (h << 4) + (*p++);
-  if ((g = h&0xf0000000)) {
-  h = h ^ (g >> 24);
-  h = h ^ g;
-  }}
-  return size_t(h);
-  }  // operator()
-  };  // hash<string>{}
-
-*/
-  // hash function for arbitrary pairs
-  //
-  template<class T1, class T2> struct hash<std::pair<T1,T2> > {
-    size_t operator()(const std::pair<T1,T2>& p) const
-    {
-      size_t h1 = hash<T1>()(p.first);
-      size_t h2 = hash<T2>()(p.second);
-      return h1 ^ (h1 >> 1) ^ h2 ^ (h2 << 1);
-    }
-  };
-
-
-  // hash function for vectors
-  //
-  template<class T> struct hash<std::vector<T> > 
-  { //  This is the fn hashpjw of Aho, Sethi and Ullman, p 436.
-    size_t operator()(const std::vector<T>& s) const 
-    {
-      typedef typename std::vector<T>::const_iterator CI;
-
-      unsigned long h = 0; 
-      unsigned long g;
-      CI p = s.begin();
-      CI end = s.end();
-
-      while (p!=end) {
-        h = (h << 5) + hash<T>()(*p++);
-        if ((g = h&0xff000000)) {
-          h = h ^ (g >> 23);
-          h = h ^ g;
-        }}
-        return size_t(h);
-    }
-  };
-
-  // hash function for slists
-  //
-  template<class T> struct hash<ext::slist<T> > 
-  { //  This is the fn hashpjw of Aho, Sethi and Ullman, p 436.
-    size_t operator()(const ext::slist<T>& s) const 
-    {
-      typedef typename ext::slist<T>::const_iterator CI;
-
-      unsigned long h = 0; 
-      unsigned long g;
-      CI p = s.begin();
-      CI end = s.end();
-
-      while (p!=end) {
-        h = (h << 7) + hash<T>()(*p++);
-        if ((g = h&0xff000000)) {
-          h = h ^ (g >> 23);
-          h = h ^ g;
-        }}
-        return size_t(h);
-    }
-  };
-
-  // hash function for maps
-  //
-  template<typename T1, typename T2> struct hash<std::map<T1,T2> >
-  {
-    size_t operator()(const std::map<T1,T2>& m) const
-    {
-      typedef typename std::map<T1,T2> M;
-      typedef typename M::const_iterator CI;
-
-      unsigned long h = 0;
-      unsigned long g;
-      CI p = m.begin();
-      CI end = m.end();
-
-      while (p != end) {
-        h = (h << 11) + hash<typename M::value_type>()(*p++);
-        if ((g = h&0xff000000)) {
-          h = h ^ (g >> 23);
-          h = h ^ g;
-        }}
-        return size_t(h);
-    }
-  };
-
-} // namespace EXT_NAMESPACE
-
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                           Write/Read code                             //
-//                                                                       //
-// These routines should possess write/read invariance IF their elements //
-// also have write-read invariance.  Whitespace, '(' and ')' are used as //
-// delimiters.                                                           //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-
-// Define istream >> const char* so that it consumes the characters from the
-// istream.  Just as in scanf, a space consumes an arbitrary amount of whitespace.
-//
-inline std::istream& operator>> (std::istream& is, const char* cp)
-{
-  if (*cp == '\0')
-    return is;
-  else if (*cp == ' ') {
-    char c;
-    if (is.get(c)) {
-      if (isspace(c))
-        return is >> cp;
-      else {
-        is.unget();
-        return is >> (cp+1);
-      }
-    }
-    else {
-      is.clear(is.rdstate() & ~std::ios::failbit);  // clear failbit
-      return is >> (cp+1);
-    }
-  }
-  else {
-    char c;
-    if (is.get(c)) {
-      if (c == *cp)
-        return is >> (cp+1);
-      else {
-        is.unget();
-        is.setstate(std::ios::failbit);
-      }
-    }
-    return is;
-  }
-}
-
-
-// Write out an auto_ptr object just as you would write out the pointer object
-//
-template <typename T> 
-inline std::ostream& operator<<(std::ostream& os, const std::auto_ptr<T>& sp)
-{
-  return os << sp.get();
-}
-
-
-// Pairs
-//
-template <class T1, class T2> 
-std::ostream& operator<< (std::ostream& os, const std::pair<T1,T2>& p)
-{
-  return os << '(' << p.first << ' ' << p.second << ')';
-}
-
-template <class T1, class T2>
-std::istream& operator>> (std::istream& is, std::pair<T1,T2>& p)
-{
-  char c;
-  if (is >> c) {
-    if (c == '(') {
-      if (is >> p.first >> p.second >> c && c == ')')
-        return is;
-      else 
-        is.setstate(std::ios::badbit);
-    }
-    else
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-// Lists
-//
-template <class T>
-std::ostream& operator<< (std::ostream& os, const std::list<T>& xs)
-{
-  os << '(';
-  for (typename std::list<T>::const_iterator xi = xs.begin(); xi != xs.end(); ++xi) {
-    if (xi != xs.begin())
-      os << ' ';
-    os << *xi;
-  }
-  return os << ')';
-}
-
-template <class T>
-std::istream& operator>> (std::istream& is, std::list<T>& xs)
-{
-  char c;                          // This code avoids unnecessary copy
-  if (is >> c) {                   // read the initial '('
-    if (c == '(') {
-      xs.clear();                  // clear the list
-      do {
-        xs.push_back(T());         // create a new elt in list
-        is >> xs.back();           // read element
-      }
-      while (is.good());           // read as long as possible
-      xs.pop_back();               // last read failed; pop last elt
-      is.clear(is.rdstate() & ~std::ios::failbit);  // clear failbit
-      if (is >> c && c == ')')     // read terminating ')'
-        return is;                 // successful return
-      else 
-        is.setstate(std::ios::badbit); // something went wrong, set badbit
-    }
-    else                           // c is not '('
-      is.putback(c);               //  put c back into input
-  }
-  is.setstate(std::ios::failbit);  // read failed, set failbit
-  return is;
-}
-
-// Vectors
-//
-template <class T>
-std::ostream& operator<< (std::ostream& os, const std::vector<T>& xs)
-{
-  os << '(';
-  for (typename std::vector<T>::const_iterator xi = xs.begin(); xi != xs.end(); ++xi) {
-    if (xi != xs.begin())
-      os << ' ';
-    os << *xi;
-  }
-  return os << ')';
-}
-
-template <class T>
-std::istream& operator>> (std::istream& is, std::vector<T>& xs)
-{
-  char c;                          // This code avoids unnecessary copy
-  if (is >> c) {                   // read the initial '('
-    if (c == '(') {
-      xs.clear();                  // clear the list
-      do {
-        xs.push_back(T());         // create a new elt in list
-        is >> xs.back();           // read element
-      }
-      while (is.good());           // read as long as possible
-      xs.pop_back();               // last read failed; pop last elt
-      is.clear(is.rdstate() & ~std::ios::failbit);  // clear failbit
-      if (is >> c && c == ')')     // read terminating ')'
-        return is;                 // successful return
-      else 
-        is.setstate(std::ios::badbit); // something went wrong, set badbit
-    }
-    else                           // c is not '('
-      is.putback(c);               //  put c back into input
-  }
-  is.setstate(std::ios::failbit);  // read failed, set failbit
-  return is;
-}
-
-// Slists
-//
-template <class T>
-std::ostream& operator<< (std::ostream& os, const ext::slist<T>& xs)
-{
-  os << '(';
-  for (typename ext::slist<T>::const_iterator xi = xs.begin(); xi != xs.end(); ++xi) {
-    if (xi != xs.begin())
-      os << ' ';
-    os << *xi;
-  }
-  return os << ')';
-}
-
-template <class T>
-std::istream& operator>> (std::istream& is, ext::slist<T>& xs)
-{
-  char c; 
-  if (is >> c) { 
-    if (c == '(') {
-      xs.clear();
-      T e;
-      if (is >> e) {   
-        xs.push_front(e);
-        typename ext::slist<T>::iterator xi = xs.begin();
-        while (is >> e)
-          xi = xs.insert_after(xi, e);
-        is.clear(is.rdstate() & ~std::ios::failbit);
-        if (is >> c && c == ')')
-          return is;
-        else 
-          is.setstate(std::ios::badbit); 
-      }
-      else { // empty list
-        is.clear(is.rdstate() & ~std::ios::failbit);
-        if (is >> c && c == ')')
-          return is;
-        else  // didn't see closing ')'
-          is.setstate(std::ios::badbit);
-      }
-    }
-    else  // didn't read '('
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-// Sets
-//
-template <class T>
-std::ostream& operator<< (std::ostream& os, const std::set<T>& s)
-{
-  os << '(';
-  for (typename std::set<T>::const_iterator i = s.begin(); i != s.end(); ++i) {
-    if (i != s.begin())
-      os << ' ';
-    os << *i;
-  }
-  return os << ')';
-}
-
-template <class T>
-std::istream& operator>> (std::istream& is, std::set<T>& s)
-{
-  char c;
-  if (is >> c) {
-    if (c == '(') {
-      s.clear();
-      T e;
-      while (is >> e)
-        s.insert(e);
-      is.clear(is.rdstate() & ~std::ios::failbit);
-      if (is >> c && c == ')')
-        return is;
-      else
-        is.setstate(std::ios::badbit);
-    }
-    else
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-// Hash_sets
-//
-template <class T>
-std::ostream& operator<< (std::ostream& os, const std::unordered_set<T>& s)
-{
-  os << '(';
-  for (typename std::unordered_set<T>::const_iterator i = s.begin(); i != s.end(); ++i) {
-    if (i != s.begin())
-      os << ' ';
-    os << *i;
-  }
-  return os << ')';
-}
-
-template <class T>
-std::istream& operator>> (std::istream& is, std::unordered_set<T>& s)
-{
-  char c;
-  if (is >> c) {
-    if (c == '(') {
-      s.clear();
-      T e;
-      while (is >> e)
-        s.insert(e);
-      is.clear(is.rdstate() & ~std::ios::failbit);
-      if (is >> c && c == ')')
-        return is;
-      else
-        is.setstate(std::ios::badbit);
-    }
-    else
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-
-// Maps
-//
-template <class Key, class Value>
-std::ostream& operator<< (std::ostream& os, const std::map<Key,Value>& m)
-{
-  typedef std::map<Key,Value> M;
-  os << '(';
-  for (typename M::const_iterator it = m.begin(); it != m.end(); ++it) {
-    if (it != m.begin())
-      os << ' ';
-    os << *it;
-  }
-  return os << ")";
-}
-
-template <class Key, class Value>
-std::istream& operator>> (std::istream& is, std::map<Key,Value>& m)
-{
-  char c;
-  if (is >> c) {
-    if (c == '(') {
-      m.clear();
-      std::pair<Key,Value> e;
-      while (is >> e)
-        m.insert(e);
-      is.clear(is.rdstate() & ~std::ios::failbit);
-      if (is >> c && c == ')')
-        return is;
-      else
-        is.setstate(std::ios::badbit);
-    }
-    else
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-// Hash_maps
-//
-template <class Key, class Value>
-std::ostream& operator<< (std::ostream& os, const std::unordered_map<Key,Value>& m)
-{
-  typedef std::unordered_map<Key,Value> M;
-  os << '(';
-  for (typename M::const_iterator it = m.begin(); it != m.end(); ++it) {
-    if (it != m.begin())
-      os << ' ';
-    os << *it;
-  }
-  return os << ")";
-}
-
-template <class Key, class Value>
-std::istream& operator>> (std::istream& is, std::unordered_map<Key,Value>& m)
-{
-  char c;
-  if (is >> c) {
-    if (c == '(') {
-      m.clear();
-      std::pair<Key,Value> e;
-      while (is >> e)
-        m.insert(e);
-      is.clear(is.rdstate() & ~std::ios::failbit);
-      if (is >> c && c == ')')
-        return is;
-      else
-        is.setstate(std::ios::badbit);
-    }
-    else
-      is.putback(c);
-  }
-  is.setstate(std::ios::failbit);
-  return is;
-}
-
-
-///////////////////////////////////////////////////////////////////////////
-//                                                                       //
-//                       Boost library additions                         //
-//                                                                       //
-///////////////////////////////////////////////////////////////////////////
-
-#ifdef BOOST_SHARED_PTR_HPP_INCLUDED
-
-// enhancements to boost::shared_ptr so it can be used with hash
-//
-namespace std {
-  template <typename T> struct equal_to<boost::shared_ptr<T> > 
-    : public binary_function<boost::shared_ptr<T>, boost::shared_ptr<T>, bool> {
-      bool operator() (const boost::shared_ptr<T>& p1, const boost::shared_ptr<T>& p2) const {
-        return equal_to<T*>()(p1.get(), p2.get());
-      }
-    };
-}  // namespace std
-
-//namespace EXT_NAMESPACE {
-namespace std {
-  template <typename T> struct hash<boost::shared_ptr<T> > {
-    size_t operator() (const boost::shared_ptr<T>& a) const {
-      return hash<T*>()(a.get());
-    }
-  };
-}  // namespace ext
-
-template <typename T> 
-inline std::ostream& operator<< (std::ostream& os, const boost::shared_ptr<T>& sp)
-{
-  return os << sp.get();
-}
-
-#endif  // BOOST_SHARED_PTR_HPP_INCLUDED
-
-struct resource_usage { };
-
-#ifndef __i386
-inline std::ostream& operator<< (std::ostream& os, resource_usage r)
-{
-  return os;
-}
-#else // Assume we are on a 586 linux
-inline std::ostream& operator<< (std::ostream& os, resource_usage r)
-{
-  FILE* fp = fopen("/proc/self/stat", "r");
-  assert(fp);
-  int utime;
-  int stime;
-  unsigned int vsize;
-  unsigned int rss;
-  int result = 
-    fscanf(fp, "%*d %*s %*c %*d %*d %*d %*d %*d %*u %*u %*u %*u %*u %d %d %*d %*d %*d %*d"
-           "%*u %*u %*d %u %u", &utime, &stime, &vsize, &rss);
-  assert(result == 4);
-  fclose(fp);
-  // s << "utime = " << utime << ", stime = " << stime << ", vsize = " << vsize << ", rss = " << rss
-  ;
-  // return s << "utime = " << utime << ", vsize = " << vsize;
-  return os << "utime " << float(utime)/1.0e2 << "s, vsize " 
-    << float(vsize)/1048576.0 << " Mb.";
-}
-#endif
-
-//! A default_value_type{} object is used to read an object from a stream,
-//! assigning a default value if the read fails.  Users should not need to
-//! construct such objects, but should use default_value() instead.
-//
-template <typename object_type, typename default_type>
-struct default_value_type {
-  object_type& object;
-  const default_type defaultvalue;
-  default_value_type(object_type& object, const default_type defaultvalue)
-    : object(object), defaultvalue(defaultvalue) { }
-};
-
-//! default_value() is used to read an object from a stream, assigning a
-//! default value if the read fails.  It returns a default_value_type{}
-//! object, which does the actual reading.
-//
-template <typename object_type, typename default_type>
-default_value_type<object_type,default_type>
-default_value(object_type& object, const default_type defaultvalue=default_type()) {
-  return default_value_type<object_type,default_type>(object, defaultvalue);
-}
-
-//! This version of operator>>() reads default_value_type{} from an input stream.
-//
-template <typename object_type, typename default_type>
-std::istream& operator>> (std::istream& is, 
-                          default_value_type<object_type, default_type> dv) {
-  if (is) {
-    if (is >> dv.object)
-      ;
-    else {
-      is.clear(is.rdstate() & ~std::ios::failbit);  // clear failbit
-      dv.object = dv.defaultvalue;
-    }
-  }
-  return is;
-}
-
-// inline F random1() { return rand()/(RAND_MAX+1.0); }
-inline F random1() { return mt_genrand_res53(); }
-
-#endif  // UTILITY_H
diff --git a/gi/pyp-topics/src/workers.hh b/gi/pyp-topics/src/workers.hh
deleted file mode 100644
index 95b18947..00000000
--- a/gi/pyp-topics/src/workers.hh
+++ /dev/null
@@ -1,275 +0,0 @@
-/**
-  Basic thread-pool tools using Boost.Thread.
-  (Jan Botha, 7/2010)
-
-  --Simple usage--
-  Use SimpleWorker.
-    Example, call a function that returns an int in a new thread:
-    typedef boost::function<int()> JobType;
-    JobType job = boost::bind(funcname);
-      //or boost::bind(&class::funcname, this) for a member function
-    SimpleWorker<JobType, int> worker(job);
-    int result = worker.getResult(); //blocks until result is ready
-
-  --Extended usage--
-  Use WorkerPool, which uses Queuemt (a synchronized queue) and Worker.
-  Example:
-    (same context and typedef
-    WorkerPool<JobType, int> pool(num_threads);
-    JobType job = ...
-    pool.addJob(job);
-    ...
-    pool.get_result(); //blocks until all workers are done, returns the some of their results.  
-    
-    Jobs added to a WorkerPool need to be the same type. A WorkerPool instance should not be reused (e.g. adding jobs) after calling get_result(). 
-*/
-
-#ifndef WORKERS_HH
-#define WORKERS_HH
-
-#include <iostream>
-#include <boost/bind.hpp>
-#include <boost/function.hpp>
-#include <queue>
-#include <boost/ptr_container/ptr_vector.hpp>
-#include <boost/thread/thread.hpp>
-#include <boost/thread/mutex.hpp>
-#include <boost/thread/shared_mutex.hpp>
-#include <boost/thread/future.hpp>
-#include <boost/thread/condition.hpp>
-
-#include <boost/date_time/posix_time/posix_time_types.hpp>
-#include "timing.h"
-
-/** Implements a synchronized queue*/
-template<typename J>
-class Queuemt
-{
-
-public:
-    boost::condition_variable_any cond;
-    const bool& running;
-
-    Queuemt() { }
-    Queuemt(const bool& running) : running(running), maxsize(0), qsize(0) 
-    { 
-    }
-
-    ~Queuemt() { 
-     }
-
-    J pop()
-    {
-        J job;
-        {
-            boost::unique_lock<boost::shared_mutex> qlock(q_mutex);
-            while (running && qsize == 0)
-                cond.wait(qlock);
-
-            if (qsize > 0)
-            {
-                job = q.front();
-                q.pop();
-                --qsize;      
-            }
-        }
-        if (job)
-            cond.notify_one();
-        return job;
-
-    }
-
-    void push(J job)
-    {
-        {
-            boost::unique_lock<boost::shared_mutex> lock(q_mutex);
-            q.push(job);
-            ++qsize;
-        }
-        if (qsize > maxsize)
-            maxsize = qsize;
-        
-        cond.notify_one();
-    }
-
-    int getMaxsize()
-    {
-        return maxsize;
-    }
-
-    int size()
-    {
-        return qsize;
-    }
-
-private:
-    boost::shared_mutex q_mutex;
-    std::queue<J> q;
-    int maxsize;
-    volatile int qsize;
-};
-
-
-template<typename J, typename R>
-class Worker
-{
-typedef boost::packaged_task<R> PackagedTask;
-public:
-    Worker(Queuemt<J>& queue, int id, int num_workers) :  
-      q(queue), tasktime(0.0), id(id), num_workers(num_workers)
-    {
-        PackagedTask task(boost::bind(&Worker<J, R>::run, this));
-        future = task.get_future();
-        boost::thread t(boost::move(task));
-    }
-
-    R run() //this is called upon thread creation
-    {
-        R wresult = 0;
-        while (isRunning())
-        {
-            J job = q.pop();
-
-            if (job)
-            {
-                timer.Reset();
-                wresult += job();
-                tasktime += timer.Elapsed();
-            }
-        }
-        return wresult;
-    }
-
-    R getResult()
-    {
-        if (!future.is_ready())
-            future.wait();
-        assert(future.is_ready());
-        return future.get();
-    }
-
-    double getTaskTime()
-    {
-        return tasktime;
-    }
-
-private:
-
-    Queuemt<J>& q;
-
-    boost::unique_future<R> future;
-
-    bool isRunning()
-    {
-        return q.running || q.size() > 0;
-    }
-    
-    Timer timer;
-    double tasktime;
-    int id;
-    int num_workers;
-};
-
-template<typename J, typename R>
-class WorkerPool
-{
-typedef boost::packaged_task<R> PackagedTask;
-typedef Worker<J,R> WJR;
-typedef boost::ptr_vector<WJR> WorkerVector;
-public:
-
-    WorkerPool(int num_workers)
-    {
-        q.reset(new Queuemt<J>(running));
-        running = true;
-        for (int i = 0; i < num_workers; ++i)
-            workers.push_back( new Worker<J, R>(*q, i, num_workers) );
-    }
-
-    ~WorkerPool()
-    {
-    }
-
-    R get_result()
-    {
-        running = false;
-        q->cond.notify_all();
-        R tmp = 0;
-        double tasktime = 0.0;
-        for (typename WorkerVector::iterator it = workers.begin(); it != workers.end(); it++)
-        {
-            R res = it->getResult();
-            tmp += res;
-            //std::cerr << "tasktime: " << it->getTaskTime() << std::endl; 
-            tasktime += it->getTaskTime();
-        }
-//        std::cerr << " maxQ = " << q->getMaxsize() << std::endl;
-        return tmp;
-    }
-
-    void addJob(J job)
-    {
-        q->push(job);
-    }
-
-private:
-
-    WorkerVector workers;
-
-    boost::shared_ptr<Queuemt<J> > q;
-
-    bool running;
-};
-
-///////////////////
-template <typename J, typename R>
-class SimpleWorker
-{
-typedef boost::packaged_task<R> PackagedTask;
-public:
-    SimpleWorker(J& job) : job(job), tasktime(0.0)
-    {
-        PackagedTask task(boost::bind(&SimpleWorker<J, R>::run, this));
-        future = task.get_future();
-        boost::thread t(boost::move(task));
-    }
-
-    R run() //this is called upon thread creation
-    {
-        R wresult = 0;
-
-        assert(job);
-        timer.Reset();
-        wresult = job();
-        tasktime = timer.Elapsed();
-        std::cerr << tasktime << " s" << std::endl; 
-        return wresult;
-    }
-
-    R getResult()
-    {
-        if (!future.is_ready())
-            future.wait();
-        assert(future.is_ready());
-        return future.get();
-    }
-
-    double getTaskTime()
-    {
-        return tasktime;
-    }
-
-private:
-
-    J job;
-
-    boost::unique_future<R> future;
-
-    Timer timer;
-    double tasktime;
-
-};
-
-
-
-#endif