Reformatting for readability.

1 files changed, 250 insertions, 225 deletions

diff --git a/moses/ConfusionNet.cpp b/moses/ConfusionNet.cpp
index dd2ac8795..34aa93284 100644
--- a/moses/ConfusionNet.cpp
+++ b/moses/ConfusionNet.cpp
@@ -14,268 +14,293 @@
 
 namespace Moses
 {
-struct CNStats {
-  size_t created,destr,read,colls,words;
+  struct CNStats {
+    size_t created,destr,read,colls,words;
+    
+    CNStats() : created(0),destr(0),read(0),colls(0),words(0) {}
+    ~CNStats() {
+      print(std::cerr);
+    }
 
-  CNStats() : created(0),destr(0),read(0),colls(0),words(0) {}
-  ~CNStats() {
-    print(std::cerr);
+    void createOne() {
+      ++created;
+    }
+    void destroyOne() {
+      ++destr;
+    }
+    
+    void collect(const ConfusionNet& cn) {
+      ++read;
+      colls+=cn.GetSize();
+      for(size_t i=0; i<cn.GetSize(); ++i)
+	words+=cn[i].size();
+    }
+    void print(std::ostream& out) const {
+      if(created>0) {
+	out<<"confusion net statistics:\n"
+	  " created:\t"<<created<<"\n"
+	  " destroyed:\t"<<destr<<"\n"
+	  " succ. read:\t"<<read<<"\n"
+	  " columns:\t"<<colls<<"\n"
+	  " words:\t"<<words<<"\n"
+	  " avg. word/column:\t"<<words/(1.0*colls)<<"\n"
+	  " avg. cols/sent:\t"<<colls/(1.0*read)<<"\n"
+	  "\n\n";
+      }
+    }
+  };
+  
+  CNStats stats;
+
+  size_t 
+  ConfusionNet::
+  GetColumnIncrement(size_t i, size_t j) const
+  {
+    (void) i;
+    (void) j;
+    return 1;
   }
 
-  void createOne() {
-    ++created;
-  }
-  void destroyOne() {
-    ++destr;
-  }
+  ConfusionNet::
+  ConfusionNet()
+    : InputType()
+  {
+    stats.createOne();
 
-  void collect(const ConfusionNet& cn) {
-    ++read;
-    colls+=cn.GetSize();
-    for(size_t i=0; i<cn.GetSize(); ++i)
-      words+=cn[i].size();
-  }
-  void print(std::ostream& out) const {
-    if(created>0) {
-      out<<"confusion net statistics:\n"
-         " created:\t"<<created<<"\n"
-         " destroyed:\t"<<destr<<"\n"
-         " succ. read:\t"<<read<<"\n"
-         " columns:\t"<<colls<<"\n"
-         " words:\t"<<words<<"\n"
-         " avg. word/column:\t"<<words/(1.0*colls)<<"\n"
-         " avg. cols/sent:\t"<<colls/(1.0*read)<<"\n"
-         "\n\n";
+    const StaticData& staticData = StaticData::Instance();
+    if (staticData.IsChart()) {
+      m_defaultLabelSet.insert(StaticData::Instance().GetInputDefaultNonTerminal());
     }
+    UTIL_THROW_IF2(&InputFeature::Instance() == NULL, "Input feature must be specified");
   }
 
-};
-
-CNStats stats;
-
-size_t ConfusionNet::GetColumnIncrement(size_t i, size_t j) const
-{
-  (void) i;
-  (void) j;
-  return 1;
-}
-
-ConfusionNet::ConfusionNet()
-  : InputType()
-{
-  stats.createOne();
-
-  const StaticData& staticData = StaticData::Instance();
-  if (staticData.IsChart()) {
-    m_defaultLabelSet.insert(StaticData::Instance().GetInputDefaultNonTerminal());
+  ConfusionNet::
+  ~ConfusionNet()
+  {
+    stats.destroyOne();
   }
-  UTIL_THROW_IF2(&InputFeature::Instance() == NULL, "Input feature must be specified");
-}
-ConfusionNet::~ConfusionNet()
-{
-  stats.destroyOne();
-}
 
-ConfusionNet::ConfusionNet(Sentence const& s)
-{
-  data.resize(s.GetSize());
-  for(size_t i=0; i<s.GetSize(); ++i) {
-    ScorePair scorePair;
-    std::pair<Word, ScorePair > temp = std::make_pair(s.GetWord(i), scorePair);
-    data[i].push_back(temp);
+  ConfusionNet::
+  ConfusionNet(Sentence const& s)
+  {
+    data.resize(s.GetSize());
+    for(size_t i=0; i<s.GetSize(); ++i) {
+      ScorePair scorePair;
+      std::pair<Word, ScorePair > temp = std::make_pair(s.GetWord(i), scorePair);
+      data[i].push_back(temp);
+    }
   }
-}
 
-bool ConfusionNet::ReadF(std::istream& in,
-                         const std::vector<FactorType>& factorOrder,
-                         int format)
-{
-  VERBOSE(1, "read confusion net with format "<<format<<"\n");
-  switch(format) {
-  case 0:
-    return ReadFormat0(in,factorOrder);
-  case 1:
-    return ReadFormat1(in,factorOrder);
-  default:
-    std::stringstream strme;
-    strme << "ERROR: unknown format '"<<format
-          <<"' in ConfusionNet::Read";
-    UserMessage::Add(strme.str());
+  bool 
+  ConfusionNet::
+  ReadF(std::istream& in, const std::vector<FactorType>& factorOrder, int format)
+  {
+    VERBOSE(1, "read confusion net with format "<<format<<"\n");
+    switch(format) {
+    case 0:
+      return ReadFormat0(in,factorOrder);
+    case 1:
+      return ReadFormat1(in,factorOrder);
+    default:
+      std::stringstream strme;
+      strme << "ERROR: unknown format '"<<format
+	    <<"' in ConfusionNet::Read";
+      UserMessage::Add(strme.str());
+    }
+    return false;
   }
-  return false;
-}
-
-int ConfusionNet::Read(std::istream& in,
-                       const std::vector<FactorType>& factorOrder)
-{
-  int rv=ReadF(in,factorOrder,0);
-  if(rv) stats.collect(*this);
-  return rv;
-}
 
+  int 
+  ConfusionNet::
+  Read(std::istream& in,
+       const std::vector<FactorType>& factorOrder)
+  {
+    int rv=ReadF(in,factorOrder,0);
+    if(rv) stats.collect(*this);
+    return rv;
+  }
 
-void ConfusionNet::String2Word(const std::string& s,Word& w,
-                               const std::vector<FactorType>& factorOrder)
-{
-  std::vector<std::string> factorStrVector = Tokenize(s, "|");
-  for(size_t i=0; i<factorOrder.size(); ++i)
-    w.SetFactor(factorOrder[i],
-                FactorCollection::Instance().AddFactor(Input,factorOrder[i],
-                    factorStrVector[i]));
-}
 
-bool ConfusionNet::ReadFormat0(std::istream& in,
-                               const std::vector<FactorType>& factorOrder)
-{
-  Clear();
-
-  const StaticData &staticData = StaticData::Instance();
-  const InputFeature &inputFeature = InputFeature::Instance();
-  size_t numInputScores = inputFeature.GetNumInputScores();
-  size_t numRealWordCount = inputFeature.GetNumRealWordsInInput();
-
-  size_t totalCount = numInputScores + numRealWordCount;
-  bool addRealWordCount = (numRealWordCount > 0);
-
-  std::string line;
-  while(getline(in,line)) {
-    std::istringstream is(line);
-    std::string word;
-
-    Column col;
-    while(is>>word) {
-      Word w;
-      String2Word(word,w,factorOrder);
-      std::vector<float> probs(totalCount, 0.0);
-      for(size_t i=0; i < numInputScores; i++) {
-        double prob;
-        if (!(is>>prob)) {
-          TRACE_ERR("ERROR: unable to parse CN input - bad link probability, or wrong number of scores\n");
-          return false;
-        }
-        if(prob<0.0) {
-          VERBOSE(1, "WARN: negative prob: "<<prob<<" ->set to 0.0\n");
-          prob=0.0;
-        } else if (prob>1.0) {
-          VERBOSE(1, "WARN: prob > 1.0 : "<<prob<<" -> set to 1.0\n");
-          prob=1.0;
-        }
-        probs[i] = (std::max(static_cast<float>(log(prob)),LOWEST_SCORE));
+  void 
+  ConfusionNet::
+  String2Word(const std::string& s,Word& w,
+	      const std::vector<FactorType>& factorOrder)
+  {
+    std::vector<std::string> factorStrVector = Tokenize(s, "|");
+    for(size_t i=0; i<factorOrder.size(); ++i)
+      w.SetFactor(factorOrder[i],
+		  FactorCollection::Instance().AddFactor
+		  (Input,factorOrder[i], factorStrVector[i]));
+  }
 
+  bool 
+  ConfusionNet::
+  ReadFormat0(std::istream& in, const std::vector<FactorType>& factorOrder)
+  {
+    Clear();
+
+    const StaticData   &staticData   = StaticData::Instance();
+    const InputFeature &inputFeature = InputFeature::Instance();
+    size_t numInputScores   = inputFeature.GetNumInputScores();
+    size_t numRealWordCount = inputFeature.GetNumRealWordsInInput();
+
+    size_t totalCount = numInputScores + numRealWordCount;
+    bool addRealWordCount = (numRealWordCount > 0);
+
+    std::string line;
+    while(getline(in,line)) {
+      std::istringstream is(line);
+      std::string word;
+
+      Column col;
+      while(is>>word) {
+	Word w;
+	String2Word(word,w,factorOrder);
+	std::vector<float> probs(totalCount, 0.0);
+	for(size_t i=0; i < numInputScores; i++) {
+	  double prob;
+	  if (!(is>>prob)) {
+	    TRACE_ERR("ERROR: unable to parse CN input - bad link probability, or wrong number of scores\n");
+	    return false;
+	  }
+	  if(prob<0.0) {
+	    VERBOSE(1, "WARN: negative prob: "<<prob<<" ->set to 0.0\n");
+	    prob=0.0;
+	  } else if (prob>1.0) {
+	    VERBOSE(1, "WARN: prob > 1.0 : "<<prob<<" -> set to 1.0\n");
+	    prob=1.0;
+	  }
+	  probs[i] = (std::max(static_cast<float>(log(prob)),LOWEST_SCORE));
+
+	}
+	//store 'real' word count in last feature if we have one more weight than we do arc scores and not epsilon
+	if (addRealWordCount && word!=EPSILON && word!="")
+	  probs.back() = -1.0;
+
+	ScorePair scorePair(probs);
+
+	col.push_back(std::make_pair(w,scorePair));
       }
-      //store 'real' word count in last feature if we have one more weight than we do arc scores and not epsilon
-      if (addRealWordCount && word!=EPSILON && word!="")
-        probs.back() = -1.0;
-
-      ScorePair scorePair(probs);
-
-      col.push_back(std::make_pair(w,scorePair));
+      if(col.size()) {
+	data.push_back(col);
+	ShrinkToFit(data.back());
+      } else break;
     }
-    if(col.size()) {
-      data.push_back(col);
-      ShrinkToFit(data.back());
-    } else break;
+    return !data.empty();
   }
-  return !data.empty();
-}
-bool ConfusionNet::ReadFormat1(std::istream& in,
-                               const std::vector<FactorType>& factorOrder)
-{
-  Clear();
-  std::string line;
-  if(!getline(in,line)) return 0;
-  size_t s;
-  if(getline(in,line)) s=atoi(line.c_str());
-  else return 0;
-  data.resize(s);
-  for(size_t i=0; i<data.size(); ++i) {
+
+  bool 
+  ConfusionNet::
+  ReadFormat1(std::istream& in, const std::vector<FactorType>& factorOrder)
+  {
+    Clear();
+    std::string line;
     if(!getline(in,line)) return 0;
-    std::istringstream is(line);
-    if(!(is>>s)) return 0;
-    std::string word;
-    double prob;
-    data[i].resize(s);
-    for(size_t j=0; j<s; ++j)
-      if(is>>word>>prob) {
-        //TODO: we are only reading one prob from this input format, should read many... but this function is unused anyway. -JS
-        data[i][j].second.denseScores = std::vector<float> (1);
-        data[i][j].second.denseScores.push_back((float) log(prob));
-        if(data[i][j].second.denseScores[0]<0) {
-          VERBOSE(1, "WARN: neg costs: "<<data[i][j].second.denseScores[0]<<" -> set to 0\n");
-          data[i][j].second.denseScores[0]=0.0;
-        }
-        String2Word(word,data[i][j].first,factorOrder);
-      } else return 0;
+    size_t s;
+    if(getline(in,line)) s=atoi(line.c_str());
+    else return 0;
+    data.resize(s);
+    for(size_t i=0; i<data.size(); ++i) {
+      if(!getline(in,line)) return 0;
+      std::istringstream is(line);
+      if(!(is>>s)) return 0;
+      std::string word;
+      double prob;
+      data[i].resize(s);
+      for(size_t j=0; j<s; ++j)
+	if(is>>word>>prob) {
+	  //TODO: we are only reading one prob from this input format, should read many... but this function is unused anyway. -JS
+	  data[i][j].second.denseScores = std::vector<float> (1);
+	  data[i][j].second.denseScores.push_back((float) log(prob));
+	  if(data[i][j].second.denseScores[0]<0) {
+	    VERBOSE(1, "WARN: neg costs: "<<data[i][j].second.denseScores[0]<<" -> set to 0\n");
+	    data[i][j].second.denseScores[0]=0.0;
+	  }
+	  String2Word(word,data[i][j].first,factorOrder);
+	} else return 0;
+    }
+    return !data.empty();
   }
-  return !data.empty();
-}
 
-void ConfusionNet::Print(std::ostream& out) const
-{
-  out<<"conf net: "<<data.size()<<"\n";
-  for(size_t i=0; i<data.size(); ++i) {
-    out<<i<<" -- ";
-    for(size_t j=0; j<data[i].size(); ++j) {
-      out<<"("<<data[i][j].first.ToString()<<", ";
-
-      // dense
-      std::vector<float>::const_iterator iterDense;
-      for(iterDense = data[i][j].second.denseScores.begin(); iterDense < data[i][j].second.denseScores.end(); ++iterDense) {
-        out<<", "<<*iterDense;
+  void ConfusionNet::Print(std::ostream& out) const
+  {
+    out<<"conf net: "<<data.size()<<"\n";
+    for(size_t i=0; i<data.size(); ++i) {
+      out<<i<<" -- ";
+      for(size_t j=0; j<data[i].size(); ++j) {
+	out<<"("<<data[i][j].first.ToString()<<", ";
+
+	// dense
+	std::vector<float>::const_iterator iterDense;
+	for(iterDense = data[i][j].second.denseScores.begin(); 
+	    iterDense < data[i][j].second.denseScores.end(); 
+	    ++iterDense) {
+	  out<<", "<<*iterDense;
+	}
+
+	// sparse
+	std::map<StringPiece, float>::const_iterator iterSparse;
+	for(iterSparse = data[i][j].second.sparseScores.begin(); 
+	    iterSparse != data[i][j].second.sparseScores.end(); 
+	    ++iterSparse) {
+	  out << ", " << iterSparse->first << "=" << iterSparse->second;
+	}
+
+	out<<") ";
       }
-
-      // sparse
-      std::map<StringPiece, float>::const_iterator iterSparse;
-      for(iterSparse = data[i][j].second.sparseScores.begin(); iterSparse != data[i][j].second.sparseScores.end(); ++iterSparse) {
-        out << ", " << iterSparse->first << "=" << iterSparse->second;
-      }
-
-      out<<") ";
+      out<<"\n";
     }
-    out<<"\n";
+    out<<"\n\n";
   }
-  out<<"\n\n";
-}
 
 #ifdef _WIN32
 #pragma warning(disable:4716)
 #endif
-Phrase ConfusionNet::GetSubString(const WordsRange&) const
-{
-  UTIL_THROW2("ERROR: call to ConfusionNet::GetSubString\n");
-  //return Phrase(Input);
-}
+  Phrase 
+  ConfusionNet::
+  GetSubString(const WordsRange&) const
+  {
+    UTIL_THROW2("ERROR: call to ConfusionNet::GetSubString\n");
+    //return Phrase(Input);
+  }
 
-std::string ConfusionNet::GetStringRep(const std::vector<FactorType> /* factorsToPrint */) const  //not well defined yet
-{
-  TRACE_ERR("ERROR: call to ConfusionNet::GeStringRep\n");
-  return "";
-}
+  std::string 
+  ConfusionNet::
+  GetStringRep(const std::vector<FactorType> /* factorsToPrint */) const  //not well defined yet
+  {
+    TRACE_ERR("ERROR: call to ConfusionNet::GeStringRep\n");
+    return "";
+  }
 #ifdef _WIN32
 #pragma warning(disable:4716)
 #endif
-const Word& ConfusionNet::GetWord(size_t) const
-{
-  UTIL_THROW2("ERROR: call to ConfusionNet::GetFactorArray\n");
-}
+  const Word& ConfusionNet::GetWord(size_t) const
+  {
+    UTIL_THROW2("ERROR: call to ConfusionNet::GetFactorArray\n");
+  }
 #ifdef _WIN32
 #pragma warning(default:4716)
 #endif
-std::ostream& operator<<(std::ostream& out,const ConfusionNet& cn)
-{
-  cn.Print(out);
-  return out;
-}
+  std::ostream& operator<<(std::ostream& out,const ConfusionNet& cn)
+  {
+    cn.Print(out);
+    return out;
+  }
 
-TranslationOptionCollection*
-ConfusionNet::CreateTranslationOptionCollection() const
-{
-  size_t maxNoTransOptPerCoverage = StaticData::Instance().GetMaxNoTransOptPerCoverage();
-  float translationOptionThreshold = StaticData::Instance().GetTranslationOptionThreshold();
-  TranslationOptionCollection *rv= new TranslationOptionCollectionConfusionNet(*this, maxNoTransOptPerCoverage, translationOptionThreshold);
-  assert(rv);
-  return rv;
-}
+  TranslationOptionCollection*
+  ConfusionNet::
+  CreateTranslationOptionCollection() const
+  {
+    size_t maxNoTransOptPerCoverage 
+      = StaticData::Instance().GetMaxNoTransOptPerCoverage();
+    float translationOptionThreshold 
+      = StaticData::Instance().GetTranslationOptionThreshold();
+    TranslationOptionCollection *rv 
+      = new TranslationOptionCollectionConfusionNet
+      (*this, maxNoTransOptPerCoverage, translationOptionThreshold);
+    assert(rv);
+    return rv;
+  }
 
 }