Changeset 3641 for trunk/MagicSoft/Mars/mcalib/MHGausEvents.h

Timestamp:

04/04/04 17:41:10 (21 years ago)

Author:

gaug

Message:

*** empty log message ***

File:

• trunk/MagicSoft/Mars/mcalib/MHGausEvents.h (modified) (4 diffs)

trunk/MagicSoft/Mars/mcalib/MHGausEvents.h

@@ -67 +67 @@
   Float_t  fPickupLimit;               // Upper number of sigmas from the mean until events are considered as pickup
 
-  Float_t *CreateEventXaxis(Int_t n);  //   Create an x-axis for the Event TGraphs
-  Float_t *CreatePSDXaxis(Int_t n);    //   Create an x-axis for the PSD TGraphs
+  Float_t *CreateEventXaxis(Int_t n);  // Create an x-axis for the Event TGraphs
+  Float_t *CreatePSDXaxis(Int_t n);    // Create an x-axis for the PSD TGraphs
 
-  void DrawEvents();                               // Draw graph of fEvents
+  void DrawEvents();                                  // Draw graph of fEvents
   void DrawPowerSpectrum(TVirtualPad &pad, Int_t i);  // Draw graph of fPowerSpectrum and fHPowerProbability
 
@@ -94 +94 @@
   void  SetSigmaErr( const Double_t d )   { fSigmaErr = d;   }
   void  SetProb    ( const Double_t d )   { fProb     = d;   }
-  void  SetPixId    ( const Int_t i    )   { fPixId    = i;   }
+  void  SetPixId   ( const Int_t i    )   { fPixId    = i;   }
 
-  void  SetNbins    ( const Int_t i    )   { fNbins    = i;   }  
+  void  SetNbins   ( const Int_t i    )   { fNbins    = i;   }  
   void  SetFirst   ( const Double_t d )   { fFirst    = d;   }
   void  SetLast    ( const Double_t d )   { fLast     = d;   }
   
-  void  SetNDFLimit(  const Int_t   lim=fgNDFLimit  ) {  fNDFLimit = lim;  }  
-  void  SetPickupLimit( const Float_t  lim =fgPickupLimit)  { fPickupLimit  = lim;   }
-  void  SetProbLimit( const Float_t lim=fgProbLimit ) {  fProbLimit = lim; }
+  void  SetNDFLimit    ( const Int_t   lim=fgNDFLimit    ) { fNDFLimit    = lim; }  
+  void  SetPickupLimit ( const Float_t lim=fgPickupLimit ) { fPickupLimit = lim; }
+  void  SetProbLimit   ( const Float_t lim=fgProbLimit   ) { fProbLimit   = lim; }
 
   // Setters ONLY for MC:
@@ -164 +164 @@
   // Fits
   Bool_t FitGaus(Option_t *option="RQ0",
-                 const Double_t xmin=0., const Double_t xmax=0.); // Fit the histogram HGausHist with a Gaussian
-  Bool_t RepeatFit(const Option_t *option="RQ0");      // Repeat fit within limits defined by fPickupLimit
-  void BypassFit();                                    // Take mean and RMS from the histogram
+                 const Double_t xmin=0., 
+                 const Double_t xmax=0.);         // Fit the histogram HGausHist with a Gaussian
+  Bool_t RepeatFit(const Option_t *option="RQ0"); // Repeat fit within limits defined by fPickupLimit
+  void BypassFit();                               // Take mean and RMS from the histogram
   
   // Draws
-  virtual void Draw(Option_t *option="");        // Default Draw 
+  virtual void Draw(Option_t *option="");         // Default Draw 
   
   // Prints
@@ -175 +176 @@
   
   // Miscelleaneous
-  virtual void ChangeHistId(const Int_t id);   // Changes names and titles of the histogram
-  virtual void Renorm();                    // Re-normalize the results 
+  virtual void ChangeHistId(const Int_t id); // Changes names and titles of the histogram
+  virtual void Renorm();                     // Re-normalize the results 
   
-  void CreateFourierSpectrum();             // Create the fourier spectrum out of fEvents
-  void CreateGraphEvents();                 // Create the TGraph fGraphEvents of fEvents 
-  void CreateGraphPowerSpectrum();          // Create the TGraph fGraphPowerSpectrum out of fPowerSpectrum
+  void CreateFourierSpectrum();              // Create the fourier spectrum out of fEvents
+  void CreateGraphEvents();                  // Create the TGraph fGraphEvents of fEvents 
+  void CreateGraphPowerSpectrum();           // Create the TGraph fGraphPowerSpectrum out of fPowerSpectrum
   
-  ClassDef(MHGausEvents, 1)                 // Base class for events with Gaussian distributed values
+  ClassDef(MHGausEvents, 1) // Base class for events with Gaussian distributed values
 };