LinearRegression/MultipleLinearRegressionMulY.cpp at main · jinxinB/LinearRegression · GitHub

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#include "StdAfx.h"
#include "MultipleLinearRegressionMulY.h"

CMultipleLinearRegressionMulY::CMultipleLinearRegressionMulY(LR_CountT nRegressors , LR_CountT nY) : m_Core(nRegressors)
{
	m_pSumXnYList = NULL;
	ReInit(nRegressors , nY);
}
void CMultipleLinearRegressionMulY::ReInit(LR_CountT nRegressors , LR_CountT nY)
{
	LR_CountT nSize;
	if( nRegressors < 1 )
	{
		nRegressors = 1;
	}
	m_Core.ReInit(nRegressors);
	if( nY < 1 )
	{
		nY = 1;
	}
	m_nXY = nRegressors + 1;
	nSize = m_nXY * nY;
	if( m_pSumXnYList != NULL )
	{
		if( m_nRegressors != nRegressors || m_nY != nY )
		{
			delete []m_pSumXnYList;
			m_pSumXnYList = NULL;
		}
	}
	if( m_pSumXnYList == NULL )
	{
		m_pSumXnYList = new LR_DataT[nSize];
	}
	m_nRegressors = nRegressors;
	m_nY = nY;

	// for( LR_CountT i = 0 ; i < nSize ; i++ )
	// {
		// m_pSumXnYList[i] = 0.0;
	// }
	memset(m_pSumXnYList , 0 , nSize*sizeof(LR_DataT));
}

CMultipleLinearRegressionMulY::~CMultipleLinearRegressionMulY()
{
	delete []m_pSumXnYList;
	m_pSumXnYList = NULL;
}

BOOL CMultipleLinearRegressionMulY::AddXY(LR_DataT* pX , LR_DataT* pY)
{
	LR_CountT i , k;
	LR_DataT xy , y;
	LR_DataT* pSumXnYList;
	//for( i = 0 ; i < m_nY ; i++ )
	//{
	//	m_Core.GetSumXnYData()[i] = m_pSumXnYList[i];
	//}
	memcpy(m_Core.GetSumXnYData() , m_pSumXnYList , m_nXY*sizeof(LR_DataT));
	if( !m_Core.AddXY(pX , pY[0]) )
	{
		return FALSE;
	}
	//for( i = 0 ; i < m_nY ; i++ )
	//{
	//	m_pSumXnYList[i] = m_Core.GetSumXnYData()[i];
	//}
	memcpy(m_pSumXnYList , m_Core.GetSumXnYData() , m_nXY*sizeof(LR_DataT));
	pSumXnYList = &m_pSumXnYList[m_nXY];
	for( i = 1 ; i < m_nY ; i++ )
	{
		y = pY[i];
		*pSumXnYList += y;
		pSumXnYList++;
		for( k = 0 ; k < m_nRegressors ; k++ )
		{
			xy = pX[k];
			xy *= y;
			*pSumXnYList += xy;
			pSumXnYList++;
		}
	}

	/*
	// Output raw data
	CString str;
	for( i = 0 , k = (m_nXY*m_nY) ; i < k ; i++ )
	{
		str.Format(_T("%g  ") , (double)m_pSumXnYList[i]);
		TRACE(str);
	}
	*/

	return TRUE;
}

LR_DataT* CMultipleLinearRegressionMulY::GetResults(LR_CountT idx)
{
	if( idx >= m_nY )
	{
		return NULL;
	}
	//for( INT i = 0 ; i < m_nY ; i++ )
	//{
	//	m_Core.GetSumXnYData()[i] = m_pSumXnYList[(idx*m_nXY)+i];
	//}
	memcpy(m_Core.GetSumXnYData() , &m_pSumXnYList[idx*m_nXY] , m_nXY*sizeof(LR_DataT));
	m_Core.SetRefresh();
	return m_Core.GetResults();
}

LR_DataT* CMultipleLinearRegressionMulY::GetResultsInterceptZero(LR_CountT idx)
{
	if( idx >= m_nY )
	{
		return NULL;
	}
	//for( INT i = 0 ; i < m_nY ; i++ )
	//{
	//	m_Core.GetSumXnYData()[i] = m_pSumXnYList[(idx*m_nXY)+i];
	//}
	memcpy(m_Core.GetSumXnYData() , &m_pSumXnYList[idx*m_nXY] , m_nXY*sizeof(LR_DataT));
	m_Core.SetRefresh();
	return m_Core.GetResultsInterceptZero();
}