/*=========================================================================

Program:   Visualization Toolkit
Module:    vtkAutoCorrelativeStatistics.h

Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/Copyright.htm for details.

This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE.  See the above copyright notice for more information.

=========================================================================*/
// .NAME vtkAutoCorrelativeStatistics - A class for univariate auto-correlative statistics
//
// .SECTION Description
// Given a selection of columns of interest in an input data table, this
// class provides the following functionalities, depending on the chosen
// execution options:
// * Learn: calculate sample mean and M2 aggregates for each variable w.r.t. itself
//   (cf. P. Pebay, Formulas for robust, one-pass parallel computation of covariances
//   and Arbitrary-Order Statistical Moments, Sandia Report SAND2008-6212, Sep 2008,
//   http://infoserve.sandia.gov/sand_doc/2008/086212.pdf for details)
//   for each specified time lag.
// * Derive: calculate unbiased autocovariance matrix estimators and its determinant,
//   linear regressions, and Pearson correlation coefficient, for each specified
//   time lag.
// * Assess: given an input data set, two means and a 2x2 covariance matrix,
//   mark each datum with corresponding relative deviation (2-dimensional Mahlanobis
//   distance).
// 
//
// .SECTION Thanks
// This class was written by Philippe Pebay, Kitware SAS 2012

#ifndef __vtkAutoCorrelativeStatistics_h
#define __vtkAutoCorrelativeStatistics_h

#include "vtkFiltersStatisticsModule.h" // For export macro
#include "vtkStatisticsAlgorithm.h"

class vtkMultiBlockDataSet;
class vtkStringArray;
class vtkTable;
class vtkVariant;
class vtkDoubleArray;

class VTKFILTERSSTATISTICS_EXPORT vtkAutoCorrelativeStatistics : public vtkStatisticsAlgorithm
{
public:
  vtkTypeMacro(vtkAutoCorrelativeStatistics, vtkStatisticsAlgorithm);
  void PrintSelf(ostream& os, vtkIndent indent);
  static vtkAutoCorrelativeStatistics* New();

  // Description:
  // Set/get the cardinality of the data set at given time, i.e., of
  // any given time slice. It cannot be negative.
  // The input data set is assumed to have a cardinality which
  // is a multiple of this value.
  // The default is 0, meaning that the user must specify a value
  // that is consistent with the input data set.
  vtkSetClampMacro(SliceCardinality,vtkIdType,0,VTK_ID_MAX);
  vtkGetMacro(SliceCardinality,vtkIdType);

  // Description:
  // Given a collection of models, calculate aggregate model
  virtual void Aggregate( vtkDataObjectCollection*,
                          vtkMultiBlockDataSet* );

protected:
  vtkAutoCorrelativeStatistics();
  ~vtkAutoCorrelativeStatistics();

  // Description:
  // Execute the calculations required by the Learn option, given some input Data
  // NB: input parameters are unused.
  virtual void Learn( vtkTable*,
                      vtkTable*,
                      vtkMultiBlockDataSet* );

  // Description:
  // Execute the calculations required by the Derive option.
  virtual void Derive( vtkMultiBlockDataSet* );

  // Description:
  // Execute the calculations required by the Test option.
  virtual void Test( vtkTable*,
                     vtkMultiBlockDataSet*,
                     vtkTable* ) { return; };

  // Description:
  // Execute the calculations required by the Assess option.
  virtual void Assess( vtkTable* inData,
                       vtkMultiBlockDataSet* inMeta,
                       vtkTable* outData )
  { this->Superclass::Assess( inData, inMeta, outData, 1 ); }

//BTX
  // Description:
  // Calculate p-value. This will be overridden using the object factory with an
  // R implementation if R is present.
  virtual vtkDoubleArray* CalculatePValues(vtkDoubleArray*);

  // Description:
  // Provide the appropriate assessment functor.
  virtual void SelectAssessFunctor( vtkTable* outData,
                                    vtkDataObject* inMeta,
                                    vtkStringArray* rowNames,
                                    AssessFunctor*& dfunc );
//ETX

  vtkIdType SliceCardinality;

private:
  vtkAutoCorrelativeStatistics( const vtkAutoCorrelativeStatistics& ); // Not implemented
  void operator = ( const vtkAutoCorrelativeStatistics& );   // Not implemented
};

#endif
