merge Lexi Birch's LRScore from mert_mtm5 branch. Compiles and run. Hack, must double check with barry or lexi

14 files changed, 192 insertions, 161 deletions

diff --git a/contrib/other-builds/mert_lib.xcodeproj/project.pbxproj b/contrib/other-builds/mert_lib.xcodeproj/project.pbxproj
index 16bdd3709..be1c27beb 100644
--- a/contrib/other-builds/mert_lib.xcodeproj/project.pbxproj
+++ b/contrib/other-builds/mert_lib.xcodeproj/project.pbxproj
@@ -105,6 +105,8 @@
 		1E3962211594CFF9006FE978 /* Permutation.h in Headers */ = {isa = PBXBuildFile; fileRef = 1E39621F1594CFF9006FE978 /* Permutation.h */; };
 		1E3962231594D0FF006FE978 /* SentenceLevelScorer.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 1E3962221594D0FF006FE978 /* SentenceLevelScorer.cpp */; };
 		1E3962251594D12C006FE978 /* SentenceLevelScorer.h in Headers */ = {isa = PBXBuildFile; fileRef = 1E3962241594D12C006FE978 /* SentenceLevelScorer.h */; };
+		1EE52B561596B3E4006DC938 /* StatisticsBasedScorer.h in Headers */ = {isa = PBXBuildFile; fileRef = 1EE52B551596B3E4006DC938 /* StatisticsBasedScorer.h */; };
+		1EE52B591596B3FC006DC938 /* StatisticsBasedScorer.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 1EE52B581596B3FC006DC938 /* StatisticsBasedScorer.cpp */; };
 /* End PBXBuildFile section */
 
 /* Begin PBXFileReference section */
@@ -207,6 +209,8 @@
 		1E39621F1594CFF9006FE978 /* Permutation.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = Permutation.h; path = ../../mert/Permutation.h; sourceTree = "<group>"; };
 		1E3962221594D0FF006FE978 /* SentenceLevelScorer.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; name = SentenceLevelScorer.cpp; path = ../../mert/SentenceLevelScorer.cpp; sourceTree = "<group>"; };
 		1E3962241594D12C006FE978 /* SentenceLevelScorer.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = SentenceLevelScorer.h; path = ../../mert/SentenceLevelScorer.h; sourceTree = "<group>"; };
+		1EE52B551596B3E4006DC938 /* StatisticsBasedScorer.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = StatisticsBasedScorer.h; path = ../../mert/StatisticsBasedScorer.h; sourceTree = "<group>"; };
+		1EE52B581596B3FC006DC938 /* StatisticsBasedScorer.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; name = StatisticsBasedScorer.cpp; path = ../../mert/StatisticsBasedScorer.cpp; sourceTree = "<group>"; };
 /* End PBXFileReference section */
 
 /* Begin PBXFrameworksBuildPhase section */
@@ -223,6 +227,8 @@
 		1E2CCF2815939E2D00D858D1 = {
 			isa = PBXGroup;
 			children = (
+				1EE52B581596B3FC006DC938 /* StatisticsBasedScorer.cpp */,
+				1EE52B551596B3E4006DC938 /* StatisticsBasedScorer.h */,
 				1E3962241594D12C006FE978 /* SentenceLevelScorer.h */,
 				1E3962221594D0FF006FE978 /* SentenceLevelScorer.cpp */,
 				1E39621E1594CFF9006FE978 /* Permutation.cpp */,
@@ -401,6 +407,7 @@
 				1E39621C1594CFD1006FE978 /* PermutationScorer.h in Headers */,
 				1E3962211594CFF9006FE978 /* Permutation.h in Headers */,
 				1E3962251594D12C006FE978 /* SentenceLevelScorer.h in Headers */,
+				1EE52B561596B3E4006DC938 /* StatisticsBasedScorer.h in Headers */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
 		};
@@ -497,6 +504,7 @@
 				1E39621B1594CFD1006FE978 /* PermutationScorer.cpp in Sources */,
 				1E3962201594CFF9006FE978 /* Permutation.cpp in Sources */,
 				1E3962231594D0FF006FE978 /* SentenceLevelScorer.cpp in Sources */,
+				1EE52B591596B3FC006DC938 /* StatisticsBasedScorer.cpp in Sources */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
 		};
diff --git a/mert/BleuScorer.cpp b/mert/BleuScorer.cpp
index a8a0256f2..8c68e362f 100644
--- a/mert/BleuScorer.cpp
+++ b/mert/BleuScorer.cpp
@@ -162,7 +162,7 @@ void BleuScorer::prepareStats(size_t sid, const string& text, ScoreStats& entry)
   entry.set(stats);
 }
 
-float BleuScorer::calculateScore(const vector<int>& comps) const
+statscore_t BleuScorer::calculateScore(const vector<int>& comps) const
 {
   CHECK(comps.size() == kBleuNgramOrder * 2 + 1);
 
diff --git a/mert/BleuScorer.h b/mert/BleuScorer.h
index 8f1384f5a..8e0acf366 100644
--- a/mert/BleuScorer.h
+++ b/mert/BleuScorer.h
@@ -7,7 +7,7 @@
 
 #include "Types.h"
 #include "ScoreData.h"
-#include "Scorer.h"
+#include "StatisticsBasedScorer.h"
 #include "ScopedVector.h"
 
 const int kBleuNgramOrder = 4;
@@ -32,7 +32,7 @@ public:
 
   virtual void setReferenceFiles(const std::vector<std::string>& referenceFiles);
   virtual void prepareStats(std::size_t sid, const std::string& text, ScoreStats& entry);
-  virtual float calculateScore(const std::vector<int>& comps) const;
+  virtual statscore_t calculateScore(const std::vector<int>& comps) const;
   virtual std::size_t NumberOfScores() const { return 2 * kBleuNgramOrder + 1; }
 
   int CalcReferenceLength(std::size_t sentence_id, std::size_t length);
diff --git a/mert/CderScorer.h b/mert/CderScorer.h
index 060243162..14cd96f12 100644
--- a/mert/CderScorer.h
+++ b/mert/CderScorer.h
@@ -4,7 +4,7 @@
 #include <string>
 #include <vector>
 #include "Types.h"
-#include "Scorer.h"
+#include "StatisticsBasedScorer.h"
 
 /**
  * CderScorer class can compute both CDER and WER metric.
diff --git a/mert/MergeScorer.h b/mert/MergeScorer.h
index 4031ad788..2abb8a285 100644
--- a/mert/MergeScorer.h
+++ b/mert/MergeScorer.h
@@ -4,7 +4,7 @@
 #include <string>
 #include <vector>
 
-#include "Scorer.h"
+#include "StatisticsBasedScorer.h"
 
 class PerScorer;
 class ScoreStats;
diff --git a/mert/PerScorer.h b/mert/PerScorer.h
index 7f9351f1a..83181014c 100644
--- a/mert/PerScorer.h
+++ b/mert/PerScorer.h
@@ -5,7 +5,7 @@
 #include <string>
 #include <vector>
 #include "Types.h"
-#include "Scorer.h"
+#include "StatisticsBasedScorer.h"
 
 class ScoreStats;
 
diff --git a/mert/PermutationScorer.cpp b/mert/PermutationScorer.cpp
index a7dc21484..ca385e912 100644
--- a/mert/PermutationScorer.cpp
+++ b/mert/PermutationScorer.cpp
@@ -6,7 +6,7 @@ using namespace std;
 const int PermutationScorer::SCORE_PRECISION = 5;
 
 PermutationScorer::PermutationScorer(const string &distanceMetric, const string &config)
-  :SentenceLevelScorer(distanceMetric,config)
+  :StatisticsBasedScorer(distanceMetric,config)
 {
   //configure regularisation
 
@@ -206,14 +206,8 @@ void PermutationScorer::prepareStats(size_t sid, const string& text, ScoreStats&
   //cout << tempStream.str();
 }
 
-void PermutationScorer::score(const candidates_t& candidates, const diffs_t& diffs,
-           statscores_t& scores) const
-{
-  assert(false);
-}
-
 //Will just be final score
-statscore_t PermutationScorer::calculateScore(const vector<statscore_t>& comps)
+statscore_t PermutationScorer::calculateScore(const vector<int>& comps) const
 {
   //cerr << "*******PermutationScorer::calculateScore" ;
   //cerr << " " << comps[0] << endl;
diff --git a/mert/PermutationScorer.h b/mert/PermutationScorer.h
index 30b3dcfb4..4aa8bda43 100644
--- a/mert/PermutationScorer.h
+++ b/mert/PermutationScorer.h
@@ -15,12 +15,12 @@
 #include "ScoreData.h"
 #include "Scorer.h"
 #include "Permutation.h"
-#include "SentenceLevelScorer.h"
+#include "StatisticsBasedScorer.h"
 
 /**
   * Permutation
  **/
-class PermutationScorer: public SentenceLevelScorer
+class PermutationScorer: public StatisticsBasedScorer
 {
 
 public:
@@ -39,11 +39,9 @@ public:
     return true;
   };
 
-  void score(const candidates_t& candidates, const diffs_t& diffs,
-             statscores_t& scores) const;
 
 protected:
-  statscore_t calculateScore(const std::vector<statscore_t>& scores);
+  statscore_t calculateScore(const std::vector<int>& scores) const;
   PermutationScorer(const PermutationScorer&);
   ~PermutationScorer() {};
   PermutationScorer& operator=(const PermutationScorer&);
diff --git a/mert/Scorer.cpp b/mert/Scorer.cpp
index fe568deb7..ba6ca1f6b 100644
--- a/mert/Scorer.cpp
+++ b/mert/Scorer.cpp
@@ -130,110 +130,10 @@ string Scorer::applyFilter(const string& sentence) const
   }
 }
 
-
-StatisticsBasedScorer::StatisticsBasedScorer(const string& name, const string& config)
-    : Scorer(name,config) {
-  //configure regularisation
-  static string KEY_TYPE = "regtype";
-  static string KEY_WINDOW = "regwin";
-  static string KEY_CASE = "case";
-  static string TYPE_NONE = "none";
-  static string TYPE_AVERAGE = "average";
-  static string TYPE_MINIMUM = "min";
-  static string TRUE = "true";
-  static string FALSE = "false";
-
-  string type = getConfig(KEY_TYPE,TYPE_NONE);
-  if (type == TYPE_NONE) {
-    m_regularization_type = NONE;
-  } else if (type == TYPE_AVERAGE) {
-    m_regularization_type = AVERAGE;
-  } else if (type == TYPE_MINIMUM) {
-    m_regularization_type = MINIMUM;
-  } else {
-    throw runtime_error("Unknown scorer regularisation strategy: " + type);
-  }
-  //    cerr << "Using scorer regularisation strategy: " << type << endl;
-
-  const string& window = getConfig(KEY_WINDOW, "0");
-  m_regularization_window = atoi(window.c_str());
-  //    cerr << "Using scorer regularisation window: " << m_regularization_window << endl;
-
-  const string& preserve_case = getConfig(KEY_CASE,TRUE);
-  if (preserve_case == TRUE) {
-    m_enable_preserve_case = true;
-  } else if (preserve_case == FALSE) {
-    m_enable_preserve_case = false;
-  }
-  //    cerr << "Using case preservation: " << m_enable_preserve_case << endl;
+float Scorer::score(const candidates_t& candidates) const {
+  diffs_t diffs;
+  statscores_t scores;
+  score(candidates, diffs, scores);
+  return scores[0];
 }
 
-void  StatisticsBasedScorer::score(const candidates_t& candidates, const diffs_t& diffs,
-                                   statscores_t& scores) const
-{
-  if (!m_score_data) {
-    throw runtime_error("Score data not loaded");
-  }
-  // calculate the score for the candidates
-  if (m_score_data->size() == 0) {
-    throw runtime_error("Score data is empty");
-  }
-  if (candidates.size() == 0) {
-    throw runtime_error("No candidates supplied");
-  }
-  int numCounts = m_score_data->get(0,candidates[0]).size();
-  vector<int> totals(numCounts);
-  for (size_t i = 0; i < candidates.size(); ++i) {
-    ScoreStats stats = m_score_data->get(i,candidates[i]);
-    if (stats.size() != totals.size()) {
-      stringstream msg;
-      msg << "Statistics for (" << "," << candidates[i] << ") have incorrect "
-          << "number of fields. Found: " << stats.size() << " Expected: "
-          << totals.size();
-      throw runtime_error(msg.str());
-    }
-    for (size_t k = 0; k < totals.size(); ++k) {
-      totals[k] += stats.get(k);
-    }
-  }
-  scores.push_back(calculateScore(totals));
-
-  candidates_t last_candidates(candidates);
-  // apply each of the diffs, and get new scores
-  for (size_t i = 0; i < diffs.size(); ++i) {
-    for (size_t j = 0; j < diffs[i].size(); ++j) {
-      size_t sid = diffs[i][j].first;
-      size_t nid = diffs[i][j].second;
-      size_t last_nid = last_candidates[sid];
-      for (size_t k  = 0; k < totals.size(); ++k) {
-        int diff = m_score_data->get(sid,nid).get(k)
-                   - m_score_data->get(sid,last_nid).get(k);
-        totals[k] += diff;
-      }
-      last_candidates[sid] = nid;
-    }
-    scores.push_back(calculateScore(totals));
-  }
-
-  // Regularisation. This can either be none, or the min or average as described in
-  // Cer, Jurafsky and Manning at WMT08.
-  if (m_regularization_type == NONE || m_regularization_window <= 0) {
-    // no regularisation
-    return;
-  }
-
-  // window size specifies the +/- in each direction
-  statscores_t raw_scores(scores);      // copy scores
-  for (size_t i = 0; i < scores.size(); ++i) {
-    size_t start = 0;
-    if (i >= m_regularization_window) {
-      start = i - m_regularization_window;
-    }
-    const size_t end = min(scores.size(), i + m_regularization_window + 1);
-    if (m_regularization_type == AVERAGE) {
-      scores[i] = score_average(raw_scores,start,end);
-    } else {
-      scores[i] = score_min(raw_scores,start,end);
-    }
-  }
-}
diff --git a/mert/Scorer.h b/mert/Scorer.h
index d1c658183..b75a5857d 100644
--- a/mert/Scorer.h
+++ b/mert/Scorer.h
@@ -79,12 +79,7 @@ class Scorer
    * Calculate the score of the sentences corresponding to the list of candidate
    * indices. Each index indicates the 1-best choice from the n-best list.
    */
-  float score(const candidates_t& candidates) const {
-    diffs_t diffs;
-    statscores_t scores;
-    score(candidates, diffs, scores);
-    return scores[0];
-  }
+  float score(const candidates_t& candidates) const; 
 
   const std::string& getName() const {
     return m_name;
@@ -167,36 +162,6 @@ class Scorer
 
 };
 
-/**
- * Abstract base class for Scorers that work by adding statistics across all
- * outout sentences, then apply some formula, e.g., BLEU, PER.
- */
-class StatisticsBasedScorer : public Scorer
-{
- public:
-  StatisticsBasedScorer(const std::string& name, const std::string& config);
-  virtual ~StatisticsBasedScorer() {}
-  virtual void score(const candidates_t& candidates, const diffs_t& diffs,
-                     statscores_t& scores) const;
-
- protected:
-
-  enum RegularisationType {
-    NONE,
-    AVERAGE,
-    MINIMUM
-  };
-
-  /**
-   * Calculate the actual score.
-   */
-  virtual statscore_t calculateScore(const std::vector<int>& totals) const = 0;
-
-  // regularisation
-  RegularisationType m_regularization_type;
-  std::size_t  m_regularization_window;
-};
-
 namespace {
   
   //regularisation strategies
@@ -227,4 +192,5 @@ namespace {
   
 } // namespace
 
+
 #endif // MERT_SCORER_H_
diff --git a/mert/SemposScorer.h b/mert/SemposScorer.h
index 98c55fc41..9d1f418f9 100644
--- a/mert/SemposScorer.h
+++ b/mert/SemposScorer.h
@@ -15,6 +15,7 @@
 // However, currently SemposScorer uses a bunch of typedefs, which are
 // used in SemposScorer as well as inherited SemposOverlapping classes.
 #include "SemposOverlapping.h"
+#include "StatisticsBasedScorer.h"
 
 /**
  * This class represents sempos based metrics.
diff --git a/mert/StatisticsBasedScorer.cpp b/mert/StatisticsBasedScorer.cpp
new file mode 100644
index 000000000..2da5fd211
--- /dev/null
+++ b/mert/StatisticsBasedScorer.cpp
@@ -0,0 +1,119 @@
+//
+//  StatisticsBasedScorer.cpp
+//  mert_lib
+//
+//  Created by Hieu Hoang on 23/06/2012.
+//  Copyright 2012 __MyCompanyName__. All rights reserved.
+//
+
+#include <iostream>
+#include "StatisticsBasedScorer.h"
+
+using namespace std;
+
+StatisticsBasedScorer::StatisticsBasedScorer(const string& name, const string& config)
+: Scorer(name,config) {
+  //configure regularisation
+  static string KEY_TYPE = "regtype";
+  static string KEY_WINDOW = "regwin";
+  static string KEY_CASE = "case";
+  static string TYPE_NONE = "none";
+  static string TYPE_AVERAGE = "average";
+  static string TYPE_MINIMUM = "min";
+  static string TRUE = "true";
+  static string FALSE = "false";
+  
+  string type = getConfig(KEY_TYPE,TYPE_NONE);
+  if (type == TYPE_NONE) {
+    m_regularization_type = NONE;
+  } else if (type == TYPE_AVERAGE) {
+    m_regularization_type = AVERAGE;
+  } else if (type == TYPE_MINIMUM) {
+    m_regularization_type = MINIMUM;
+  } else {
+    throw runtime_error("Unknown scorer regularisation strategy: " + type);
+  }
+  //    cerr << "Using scorer regularisation strategy: " << type << endl;
+  
+  const string& window = getConfig(KEY_WINDOW, "0");
+  m_regularization_window = atoi(window.c_str());
+  //    cerr << "Using scorer regularisation window: " << m_regularization_window << endl;
+  
+  const string& preserve_case = getConfig(KEY_CASE,TRUE);
+  if (preserve_case == TRUE) {
+    m_enable_preserve_case = true;
+  } else if (preserve_case == FALSE) {
+    m_enable_preserve_case = false;
+  }
+  //    cerr << "Using case preservation: " << m_enable_preserve_case << endl;
+}
+
+void  StatisticsBasedScorer::score(const candidates_t& candidates, const diffs_t& diffs,
+                                   statscores_t& scores) const
+{
+  if (!m_score_data) {
+    throw runtime_error("Score data not loaded");
+  }
+  // calculate the score for the candidates
+  if (m_score_data->size() == 0) {
+    throw runtime_error("Score data is empty");
+  }
+  if (candidates.size() == 0) {
+    throw runtime_error("No candidates supplied");
+  }
+  int numCounts = m_score_data->get(0,candidates[0]).size();
+  vector<int> totals(numCounts);
+  for (size_t i = 0; i < candidates.size(); ++i) {
+    ScoreStats stats = m_score_data->get(i,candidates[i]);
+    if (stats.size() != totals.size()) {
+      stringstream msg;
+      msg << "Statistics for (" << "," << candidates[i] << ") have incorrect "
+      << "number of fields. Found: " << stats.size() << " Expected: "
+      << totals.size();
+      throw runtime_error(msg.str());
+    }
+    for (size_t k = 0; k < totals.size(); ++k) {
+      totals[k] += stats.get(k);
+    }
+  }
+  scores.push_back(calculateScore(totals));
+  
+  candidates_t last_candidates(candidates);
+  // apply each of the diffs, and get new scores
+  for (size_t i = 0; i < diffs.size(); ++i) {
+    for (size_t j = 0; j < diffs[i].size(); ++j) {
+      size_t sid = diffs[i][j].first;
+      size_t nid = diffs[i][j].second;
+      size_t last_nid = last_candidates[sid];
+      for (size_t k  = 0; k < totals.size(); ++k) {
+        int diff = m_score_data->get(sid,nid).get(k)
+        - m_score_data->get(sid,last_nid).get(k);
+        totals[k] += diff;
+      }
+      last_candidates[sid] = nid;
+    }
+    scores.push_back(calculateScore(totals));
+  }
+  
+  // Regularisation. This can either be none, or the min or average as described in
+  // Cer, Jurafsky and Manning at WMT08.
+  if (m_regularization_type == NONE || m_regularization_window <= 0) {
+    // no regularisation
+    return;
+  }
+  
+  // window size specifies the +/- in each direction
+  statscores_t raw_scores(scores);      // copy scores
+  for (size_t i = 0; i < scores.size(); ++i) {
+    size_t start = 0;
+    if (i >= m_regularization_window) {
+      start = i - m_regularization_window;
+    }
+    const size_t end = min(scores.size(), i + m_regularization_window + 1);
+    if (m_regularization_type == AVERAGE) {
+      scores[i] = score_average(raw_scores,start,end);
+    } else {
+      scores[i] = score_min(raw_scores,start,end);
+    }
+  }
+}
diff --git a/mert/StatisticsBasedScorer.h b/mert/StatisticsBasedScorer.h
new file mode 100644
index 000000000..fe73f8b5e
--- /dev/null
+++ b/mert/StatisticsBasedScorer.h
@@ -0,0 +1,45 @@
+//
+//  StatisticsBasedScorer.h
+//  mert_lib
+//
+//  Created by Hieu Hoang on 23/06/2012.
+//  Copyright 2012 __MyCompanyName__. All rights reserved.
+//
+
+#ifndef mert_lib_StatisticsBasedScorer_h
+#define mert_lib_StatisticsBasedScorer_h
+
+#include "Scorer.h"
+/**
+ * Abstract base class for Scorers that work by adding statistics across all
+ * outout sentences, then apply some formula, e.g., BLEU, PER.
+ */
+class StatisticsBasedScorer : public Scorer
+{
+public:
+  StatisticsBasedScorer(const std::string& name, const std::string& config);
+  virtual ~StatisticsBasedScorer() {}
+  virtual void score(const candidates_t& candidates, const diffs_t& diffs,
+                     statscores_t& scores) const;
+  
+protected:
+  
+  enum RegularisationType {
+    NONE,
+    AVERAGE,
+    MINIMUM
+  };
+  
+  /**
+   * Calculate the actual score.
+   */
+  virtual statscore_t calculateScore(const std::vector<int>& totals) const = 0;
+  
+  // regularisation
+  RegularisationType m_regularization_type;
+  std::size_t  m_regularization_window;
+};
+
+
+
+#endif
diff --git a/mert/TerScorer.h b/mert/TerScorer.h
index 5f2cf6ae1..48ef5e2b0 100644
--- a/mert/TerScorer.h
+++ b/mert/TerScorer.h
@@ -6,7 +6,7 @@
 #include <vector>
 
 #include "Types.h"
-#include "Scorer.h"
+#include "StatisticsBasedScorer.h"
 
 class ScoreStats;