STYLE: and fix test for gamma

Code/Markov/otbMRFEnergyFisherClassification.h

@@ -27,62 +27,65 @@
 namespace otb
 {
 
-/*
- \* class MRFEnergyFisherClassification
- \* This is the implementation of the Fisher model for Markov classification
- \* to be used for the fidelity (likelihood) term for the classification.
- \*
- \* This class is meant to be used in the MRF framework with the  otb:: MarkovRandomFieldFilter
-
+/**
+ * \class MRFEnergyFisherClassification
+ * \brief Fisher model for Markov classification
+ *
+ * This is the implementation of the Fisher model for Markov classification
+ * to be used for the fidelity (likelihood) term for the classification.
+ *
+ * This class is meant to be used in the MRF framework with the
+ * otb::MarkovRandomFieldFilter
+ *
  */
 template< class TInput1, class TInput2>
-class ITK_EXPORT MRFEnergyFisherClassification:public MRFEnergy< TInput1, TInput2>
+class ITK_EXPORT MRFEnergyFisherClassification: public MRFEnergy< TInput1, TInput2>
 {
 public:
-typedef MRFEnergyFisherClassification   Self;
-typedef MRFEnergy< TInput1, TInput2>    Superclass;
-typedef itk::SmartPointer<Self>         Pointer;
-typedef itk::SmartPointer<const Self>   ConstPointer;
-
-typedef TInput1                               InputImageType;
-typedef TInput2                               LabelledImageType;
-typedef typename InputImageType::PixelType    InputImagePixelType;
-typedef typename LabelledImageType::PixelType LabelledImagePixelType;
-typedef itk::Array < double >                 ParametersType;
-
-itkNewMacro(Self);
-itkTypeMacro(MRFEnergyFisherClassification, MRFEnergy);
-
-Gamma g;
-void SetNumberOfParameters(const unsigned int nParameters)
-{
-  Superclass::SetNumberOfParameters(nParameters);
-  this->m_Parameters.SetSize(nParameters);
-  this->Modified();
-}
-
-double GetSingleValue(const InputImagePixelType & value1,  const LabelledImagePixelType & value2)
-{
-  if ((unsigned int)value2 >= this->GetNumberOfParameters()/3)
-    {
-    itkExceptionMacro(<<"Number of parameters does not correspond to number of classes" );
-    }
-  double val1 = static_cast<double>(value1);
-  double mu = this->m_Parameters[3*static_cast<double>(value2)];
-  double l  = this->m_Parameters[3*static_cast<double>(value2)+1];
-  double m  = this->m_Parameters[3*static_cast<double>(value2)+2];
-
-  double result = -vcl_log((g.gamma(l+m)/(g.gamma(l)*g.gamma(m))) * (2/(mu)) * (vcl_sqrt(l/m)) *
-                           ((pow((vcl_sqrt(l/m)*(val1/mu)), ((2*l)-1))) /
-                               (pow(1+(vcl_sqrt(l/m)*(val1/mu)*vcl_sqrt(l/m)*(val1/mu)), (l+m)))));
-
-  return static_cast<double>( result );
-}
+  typedef MRFEnergyFisherClassification   Self;
+  typedef MRFEnergy< TInput1, TInput2>    Superclass;
+  typedef itk::SmartPointer<Self>         Pointer;
+  typedef itk::SmartPointer<const Self>   ConstPointer;
+
+  typedef TInput1                               InputImageType;
+  typedef TInput2                               LabelledImageType;
+  typedef typename InputImageType::PixelType    InputImagePixelType;
+  typedef typename LabelledImageType::PixelType LabelledImagePixelType;
+  typedef itk::Array < double >                 ParametersType;
+
+  itkNewMacro(Self);
+  itkTypeMacro(MRFEnergyFisherClassification, MRFEnergy);
+
+  Gamma g;
+  void SetNumberOfParameters(const unsigned int nParameters)
+  {
+    Superclass::SetNumberOfParameters(nParameters);
+    this->m_Parameters.SetSize(nParameters);
+    this->Modified();
+  }
+
+  double GetSingleValue(const InputImagePixelType & value1,  const LabelledImagePixelType & value2)
+  {
+    if ((unsigned int)value2 >= this->GetNumberOfParameters()/3)
+      {
+      itkExceptionMacro(<<"Number of parameters does not correspond to number of classes" );
+      }
+    double val1 = static_cast<double>(value1);
+    double mu = this->m_Parameters[3*static_cast<double>(value2)];
+    double l  = this->m_Parameters[3*static_cast<double>(value2)+1];
+    double m  = this->m_Parameters[3*static_cast<double>(value2)+2];
+
+    double result = -vcl_log((g.gamma(l+m)/(g.gamma(l)*g.gamma(m))) * (2/(mu)) * (vcl_sqrt(l/m)) *
+                             ((pow((vcl_sqrt(l/m)*(val1/mu)), ((2*l)-1))) /
+                              (pow(1+(vcl_sqrt(l/m)*(val1/mu)*vcl_sqrt(l/m)*(val1/mu)), (l+m)))));
+
+    return static_cast<double>( result );
+  }
 
 protected:
-// The constructor and destructor.
-MRFEnergyFisherClassification() {};
-virtual ~MRFEnergyFisherClassification() {};
+  // The constructor and destructor.
+  MRFEnergyFisherClassification() {};
+  virtual ~MRFEnergyFisherClassification() {};
 };
 }
 #endif

Testing/Code/Common/otbGammaTest.cxx

@@ -28,10 +28,13 @@ int otbGammaTest(int argc, char * argv[])
   //Instantiation
   GammaFunctionType * gam = new GammaFunctionType();
   const double epsilon = 0.0000000001;
+  int output = EXIT_SUCCESS;
 
-  if ( vcl_abs(gam->gamma(1) - 1) > epsilon ) return EXIT_FAILURE;
-  if ( vcl_abs(gam->gamma(0.5) - 1.77245385091) > epsilon ) return EXIT_FAILURE;
-  if ( vcl_abs(gam->gamma(4) - 6) > epsilon ) return EXIT_FAILURE;
+  if ( vcl_abs(gam->gamma(1) - 1) > epsilon ) output = EXIT_FAILURE;
+  if ( vcl_abs(gam->gamma(0.5) - 1.77245385091) > epsilon ) output = EXIT_FAILURE;
+  if ( vcl_abs(gam->gamma(4) - 6) > epsilon ) output = EXIT_FAILURE;
 
-  return EXIT_SUCCESS;
+  delete gam;
+
+  return output;
 }