improve comment

mcmc/FitterBase.cpp

@@ -444,7 +444,6 @@ void FitterBase::DragRace() {
     MACH3LOG_INFO("It took {:.6f} s for a single GetLikelihood of sample:  {}", clockRace.RealTime(), samples[ivs]->GetName());
   }
 
-
   for (size_t s = 0; s < systematics.size(); ++s) {
     TStopwatch clockRace;
     clockRace.Start();
@@ -461,7 +460,6 @@ void FitterBase::DragRace() {
     MACH3LOG_INFO("It took {:.6f} s for a single get likelihood of cov:  {}", clockRace.RealTime(), systematics[s]->getName());
   }
   MACH3LOG_INFO("End of race");
-
 }
 
 // *************************
@@ -488,7 +486,6 @@ void FitterBase::RunLLHScan() {
 
   // Now finally get onto the LLH scan stuff
   // Very similar code to MCMC but never start MCMC; just scan over the parameter space
-
   std::vector<TDirectory *> Cov_LLH(systematics.size());
   for(unsigned int ivc = 0; ivc < systematics.size(); ivc++ )
   {

mcmc/FitterBase.h

@@ -25,7 +25,7 @@ class FitterBase {
   /// @brief Constructor
   /// @param fitMan A pointer to a manager object, which will handle all settings.
   FitterBase(manager * const fitMan);
-  /// @brief Destructor
+  /// @brief Destructor for the FitterBase class.
   virtual ~FitterBase();
 
   /// @brief This function adds a sample PDF object to the analysis framework. The sample PDF object will be utilized in fitting procedures or likelihood scans.
@@ -48,7 +48,7 @@ class FitterBase {
   /// @brief The specific fitting algorithm implemented in this function depends on the derived class. It could be Markov Chain Monte Carlo (MCMC), MinuitFit, or another algorithm.
   virtual void runMCMC() = 0;
 
-  /// @brief Checks how much time we need for every sample/covariance object
+  /// @brief Calculates the required time for each sample or covariance object in a drag race simulation. Inpsired by Dan's feature
   void DragRace();
 
   /// @brief Perform a 1D likelihood scan.