system cleaned up

.gitignore

@@ -0,0 +1,10 @@
+.deps
+Makefile
+config.h
+*.log
+*.o
+config.status
+stamp-h1
+test
+train
+Model

src/dataManager.cpp

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/dataManager.h

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/event.h

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/gisTrainer.cpp

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/gisTrainer.h

@@ -1,38 +1,38 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *
  *  Li Yun <nicyun@gmail.com>
  *  Chen Zhijie <ruoyu928@126.com>
  *  Yan Yuwen <ybbaigo@gmail.com>
  */
-#ifndef __GIS_TRAINER__
-#define __GIS_TRAINER__
-
-#include "dataManager.h"
-#include "maxEntTrainer.h"
-
-namespace maxent{
-
-class GisTrainer : public MaxEntTrainer
-{
-public:
-
+#ifndef __GIS_TRAINER__
+#define __GIS_TRAINER__
+
+#include "dataManager.h"
+#include "maxEntTrainer.h"
+
+namespace maxent{
+
+class GisTrainer : public MaxEntTrainer
+{
+public:
+
     GisTrainer(
             DataManager & _modelInfo,
             size_t _iter,
             double _tol,
             double _sigma2,
-            double _alpha);
-
-    bool train();
-
-private:
-    double _getSlowFactor();
-
-};
-
-}
-
-#endif
+            double _alpha);
+
+    bool train();
+
+private:
+    double _getSlowFactor();
+
+};
+
+}
+
+#endif

src/lbfgsTrainer.h

@@ -1,36 +1,36 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *
  *  Li Yun <nicyun@gmail.com>
  *  Chen Zhijie <ruoyu928@126.com>
  *  Yan Yuwen <ybbaigo@gmail.com>
  */
-#ifndef __LBFGS_TRAINER__
-#define __LBFGS_TRAINER__
-
-#include "dataManager.h"
+#ifndef __LBFGS_TRAINER__
+#define __LBFGS_TRAINER__
+
+#include "dataManager.h"
 #include "maxEntTrainer.h"
-#include "lbfgs.h"
-
-namespace maxent{
-
-class LbfgsTrainer : public MaxEntTrainer
-{
-public:
-
+#include "lbfgs.h"
+
+namespace maxent{
+
+class LbfgsTrainer : public MaxEntTrainer
+{
+public:
+
     LbfgsTrainer(
             DataManager & _modelInfo,
             size_t _iter,
             double _tol,
             double _sigma2,
             double _alpha);
 
-    ~LbfgsTrainer();
+    ~LbfgsTrainer();
 
 public:
-
+
     bool train();
 
 private:
@@ -81,14 +81,14 @@ class LbfgsTrainer : public MaxEntTrainer
     {
         return reinterpret_cast<LbfgsTrainer*>(instance)->
         			progress(x, g, fx, xnorm, gnorm, step, n, k, ls);
-    }
+    }
 
 private:
 	size_t mFfN;
 	lbfgsfloatval_t * mX;
-	lbfgs_parameter_t mLbfgsParam;
-};
-
-}
-
-#endif
+	lbfgs_parameter_t mLbfgsParam;
+};
+
+}
+
+#endif

src/maxEntMap.cpp

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/maxEntMap.h

@@ -1,34 +1,34 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *
  *  Li Yun <nicyun@gmail.com>
  *  Chen Zhijie <ruoyu928@126.com>
  *  Yan Yuwen <ybbaigo@gmail.com>
  */
-#ifndef __MAX_ENT_MAP__
-#define __MAX_ENT_MAP__
+#ifndef __MAX_ENT_MAP__
+#define __MAX_ENT_MAP__
 #undef  __DEPRECATED
 
 #include <ext/hash_map>
 #include <vector>
-
-namespace maxent
-{
-
-class MaxEntMap
-{
-public:
-
+
+namespace maxent
+{
+
+class MaxEntMap
+{
+public:
+
     MaxEntMap();
-    ~MaxEntMap();
-
-public:
-    size_t insertString(const std::string & str);
-    size_t str2num(const std::string & str) const;
+    ~MaxEntMap();
+
+public:
+    size_t insertString(const std::string & str);
+    size_t str2num(const std::string & str) const;
     std::string & num2str(const size_t Id, std::string & str) const;
-
+
 private:
     struct string_hash {
         size_t operator()(const std::string & str) const{
@@ -37,11 +37,11 @@ class MaxEntMap
     };
 
 private:
-    __gnu_cxx::hash_map<std::string, size_t, string_hash> mStr2Num;
-    std::vector<std::string> mNum2Str;
-    size_t mNumber; // auto increment
+    __gnu_cxx::hash_map<std::string, size_t, string_hash> mStr2Num;
+    std::vector<std::string> mNum2Str;
+    size_t mNumber; // auto increment
 };
-
-}
-
-#endif
+
+}
+
+#endif

src/maxEntModel.cpp

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/maxEntModel.h

@@ -1,5 +1,5 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *

src/maxEntTrainer.cpp

@@ -1,64 +1,65 @@
 /**
- *  maxent toolkit
+ *  easyME -- a Maximum Entropy toolkit
  *
  *  Copyright(C) 2009
  *
  *  Li Yun <nicyun@gmail.com>
  *  Chen Zhijie <ruoyu928@126.com>
  *  Yan Yuwen <ybbaigo@gmail.com>
  */
-#include <iostream>
-#include <math.h>
-#include "maxEntTrainer.h"
-
-namespace maxent{
-
-using namespace std;
-
-MaxEntTrainer::MaxEntTrainer(DataManager & _modelInfo, size_t _iter,
-        double _tol, double _sigma2, double _alpha)
-        : mModelInfo(_modelInfo), mIter(_iter), mEps(_tol), mSigma2(_sigma2), mAlpha(_alpha)
-{
-    _initTrainer();
-}
-
-void MaxEntTrainer::_initTrainer(void)
-{
-    mEventNum = mModelInfo.getEventNum();
-    mMaxFid = mModelInfo.getFetNum();
+#include <iostream>
+#include <math.h>
+#include "maxEntTrainer.h"
+
+namespace maxent{
+
+using namespace std;
+
+MaxEntTrainer::MaxEntTrainer(DataManager & _modelInfo, size_t _iter,
+        double _tol, double _sigma2, double _alpha)
+        : mModelInfo(_modelInfo), mIter(_iter), mEps(_tol), mSigma2(_sigma2), mAlpha(_alpha)
+{
+    _initTrainer();
+}
+
+void MaxEntTrainer::_initTrainer(void)
+{
+    mEventNum = mModelInfo.getEventNum();
+    mMaxFid = mModelInfo.getFetNum();
     mMaxCid = mModelInfo.getClassNum();
-    mTotEvent = mModelInfo.getAllEventFreq();
-    mModelInfo.getObserves(mObserved);
-}
-
-// Calculate the ith GIS parameter updates with Gaussian prior
-// using Newton-Raphson method
-// the update rule is the solution of the following equation:
-//                                   lambda_i + delta_i
-// E_ref = E_q * exp (C * delta_i) + ------------------ * N
-//                                       sigma_i^2
-// note: E_ref and E_q were not divided by N
-double MaxEntTrainer::_newton(double f_q, double f_ref, double lambdaNow, double mEps)
-{
-    size_t maxiter = 50;
-    double x0 = 0.0;
-    double x = 0.0;
-
-    for (size_t mIter = 1; mIter <= maxiter; ++mIter) {
-        double t = f_q * exp(mSlowF * x0);
-        double fval = t + mTotEvent * (lambdaNow + x0) / mSigma2 - f_ref;
-        double fpval = t * mSlowF + mTotEvent / mSigma2;
-        if (fpval == 0) {
-            cerr << "Warning: zero-derivative encountered in newton() method." << endl;
-            return x0;
-        }
-        x = x0 - fval/fpval;
-        if (fabs(x-x0) < mEps)
-            return x;
-        x0 = x;
-    }
-    cerr << "Failed to converge after 50 iterations in newton() method" << endl;
-    exit(-1);
-}
-
-}
+    mTotEvent = mModelInfo.getAllEventFreq();
+    mModelInfo.getObserves(mObserved);
+}
+
+// Calculate the ith GIS parameter updates with Gaussian prior
+// using Newton-Raphson method
+// the update rule is the solution of the following equation:
+//                                   lambda_i + delta_i
+// E_ref = E_q * exp (C * delta_i) + ------------------ * N
+//                                       sigma_i^2
+// note: E_ref and E_q were not divided by N
+// this function is copied from Le Zhang's work
+double MaxEntTrainer::_newton(double f_q, double f_ref, double lambdaNow, double mEps)
+{
+    size_t maxiter = 50;
+    double x0 = 0.0;
+    double x = 0.0;
+
+    for (size_t mIter = 1; mIter <= maxiter; ++mIter) {
+        double t = f_q * exp(mSlowF * x0);
+        double fval = t + mTotEvent * (lambdaNow + x0) / mSigma2 - f_ref;
+        double fpval = t * mSlowF + mTotEvent / mSigma2;
+        if (fpval == 0) {
+            cerr << "Warning: zero-derivative encountered in newton() method." << endl;
+            return x0;
+        }
+        x = x0 - fval/fpval;
+        if (fabs(x-x0) < mEps)
+            return x;
+        x0 = x;
+    }
+    cerr << "Failed to converge after 50 iterations in newton() method" << endl;
+    exit(-1);
+}
+
+}