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/*
//
// Copyright 1997-2009 Torsten Rohlfing
//
// Copyright 2004-2010 SRI International
//
// This file is part of the Computational Morphometry Toolkit.
//
// http://www.nitrc.org/projects/cmtk/
//
// The Computational Morphometry Toolkit is free software: you can
// redistribute it and/or modify it under the terms of the GNU General Public
// License as published by the Free Software Foundation, either version 3 of
// the License, or (at your option) any later version.
//
// The Computational Morphometry Toolkit is distributed in the hope that it
// will be useful, but WITHOUT ANY WARRANTY; without even the implied
// warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License along
// with the Computational Morphometry Toolkit. If not, see
// <http://www.gnu.org/licenses/>.
//
// $Revision: 5436 $
//
// $LastChangedDate: 2018-12-10 19:01:20 -0800 (Mon, 10 Dec 2018) $
//
// $LastChangedBy: torstenrohlfing $
//
*/
#ifndef __cmtkGeneralLinearModel_h_included_
#define __cmtkGeneralLinearModel_h_included_
#include <cmtkconfig.h>
#include <Base/cmtkTypedArray.h>
#include <Base/cmtkMatrix.h>
#include <System/cmtkSmartPtr.h>
#include <System/cmtkThreads.h>
#include <vector>
namespace
cmtk
{
/** \addtogroup Base */
//@{
/** Pixelwise linear modeling and t statistics of data.
* \note This class formerly contained a method for
* getting the covariance matrix of an SVD. It has
* been removed due to obsolete implementation
* (Numerical Recipes) and un-use
*/
class GeneralLinearModel
{
public:
/// This class.
typedef GeneralLinearModel Self;
/// Smart pointer type.
typedef SmartPointer<Self> SmartPtr;
/** Constructor.
* This will take care of SVD of the design matrix and perform all necessary
* pre-computations for the actual modeling.
*/
GeneralLinearModel( const size_t nParameters, const size_t nData, const double* designMatrix );
/// Destructor.
~GeneralLinearModel();
/** Get singular value of the SVD decomposition of the design matrix.
*\param n Index of the model parameter [0..NParameters-1].
*\return The singular value for parameter n.
*/
double GetSingularValue( const size_t n ) const
{
return (*(this->W))[n];
}
/** Get the parameter correlation matrix from design matrix.
*/
Matrix2D<double>* GetCorrelationMatrix() const;
/** Model y[] distribution and return model parameters a[].
*\param y A vector of TypedArray smart pointers. Each object in this
* vector points to a pixel array from a different subject in a population.
*\param normalizeParameters If this flag is set (default), then the
* linear model parameters are normalized w.r.t. the maghnitudes of the
* respective measurements.
*/
void FitModel( std::vector<TypedArray::SmartPtr>& y, const bool normalizeParameters = true );
/// Get pointer to n-th model parameter array.
TypedArray::SmartPtr& GetModel( const size_t n )
{
return this->Model[n];
}
/// Get normalization factor for parameter number 'p'.
double GetNormFactor( const size_t p )
{
// do not normalize constant part
if ( this->VariableSD[p] > 0 )
return this->VariableSD[p];
else
return 1.0;
}
/// Get pointer to n-th parameter t statistics array.
TypedArray::SmartPtr& GetTStat( const size_t n )
{
return this->TStat[n];
}
/// Get pointer to n-th parameter t statistics array.
TypedArray::SmartPtr& GetFStat()
{
return this->FStat;
}
private:
/// Solve least-squares problem.
void LeastSquares();
/// Initialize results arrays with the correct number of pixels.
void InitResults( const size_t nPixels );
/// Number of model parameters.
size_t NParameters;
/// Number of data items.
size_t NData;
/// Design matrix.
Matrix2D<double> DesignMatrix;
/// Matrix U of the design matrix SVD.
Matrix2D<double>* U;
/// Array of partial design matrices.
std::vector< Matrix2D<double>* > Up;
/// Matrix V the design matrix SVD.
Matrix2D<double>* V;
/// SVD of partial design matrices.
std::vector< Matrix2D<double>* > Vp;
/// Vector W (workspace).
std::vector<double>* W;
/// Workspace vectors for partial regressions.
std::vector< std::vector<double>* > Wp;
/// Means of variables.
std::vector<double> VariableMean;
/// Standard deviations of variables.
std::vector<double> VariableSD;
/// Computed model coefficients.
std::vector<TypedArray::SmartPtr> Model;
/// Computed model t statistics coefficients.
std::vector<TypedArray::SmartPtr> TStat;
/// Computed model F statistics.
TypedArray::SmartPtr FStat;
};
//@}
} // namespace cmtk
#endif // #ifndef __cmtkGeneralLinearModel_h_included_
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