TensorAverage.h

#ifndef UTIL_TENSOR_AVERAGE_H
#define UTIL_TENSOR_AVERAGE_H
 
/*
* Util Package - C++ Utilities for Scientific Computation
*
* Copyright 2010 - 2017, The Regents of the University of Minnesota
* Distributed under the terms of the GNU General Public License.
*/
 
#include <util/global.h>
#include <util/param/ParamComposite.h>  // base class
#include <util/accumulators/Average.h>  // member template argument
#include <util/containers/FArray.h>     // member template
 
#include <vector>
 
namespace Util
{
 
   class Tensor;
 
   class TensorAverage : public ParamComposite
   {
 
   public:
 
      TensorAverage(int blockFactor = 2);
 
      virtual ~TensorAverage();
 
      void setNSamplePerBlock(int nSamplePerBlock);
 
      void readParameters(std::istream& in);
 
      virtual void loadParameters(Serializable::IArchive &ar);
 
      virtual void save(Serializable::OArchive &ar);
 
      template <class Archive>
      void serialize(Archive& ar, const unsigned int version);
 
      void clear();
 
      void sample(const Tensor& value);
 
      const Average& operator () (int i, int j);
 
      int nSamplePerBlock() const;
 
      int iBlock() const;
 
      bool isBlockComplete() const;
 
   private:
 
      FArray<Average, Dimension*Dimension> accumulators_;
 
      int nSamplePerBlock_;
 
      int iBlock_;
 
      TensorAverage(const TensorAverage& other);
 
      TensorAverage& operator = (const TensorAverage& other);
 
   };
 
   // Inline method definitions
 
   /*
   * Get nSamplePerBlock, number of samples per block average.
   */
   inline int TensorAverage::nSamplePerBlock() const
   {  return nSamplePerBlock_; }
 
   /*
   * Get iBlock, number of samples in current block average.
   */
   inline int TensorAverage::iBlock() const
   {  return iBlock_; }
 
   /*
   * Is the current block average complete?
   */
   inline bool TensorAverage::isBlockComplete() const
   { return (iBlock_ && (iBlock_ == nSamplePerBlock_)); }
 
   /*
   * Serialize this Average.
   */
   template <class Archive>
   void TensorAverage::serialize(Archive& ar, const unsigned int version)
   {
      ar & nSamplePerBlock_;
      ar & iBlock_;
      int i, j, k;
      k = 0;
      for (i = 0; i < Dimension; ++i) {
         for (j = 0; j < Dimension; ++j) {
            ar & accumulators_[k];
            ++k;
         }
      }
   }
 
}
#endif