#pragma numlittype(push, TRUE)
#pragma warning(error : 15618)
#include <origin.h>
#include <ONLSF.H>
#include <fft_utils.h>
 

//----------------------------------------------------------
// 
void _nlsfmeanfield_squareroot(
// Fit Parameter(s):
double A, double B, double C, double D,
// Independent Variable(s):
double x,
// Dependent Variable(s):
double& y)
{
	// Beginning of editable part
	//	if(x<C) {
	//		y = A+B*(C-x)^0.5
	//	} else {
	//		y = A;
	//	}
	Worksheet wks = Project.ActiveLayer();
	NLFitContext *pCtxt = Project.GetNLFitContext();
	
	if(pCtxt)
	{	
	    int i;
		  
		// Vector for the output signal in each iteration.
		static vector  vF;
		// If parameters were updated, we will recalculate the convolution result.
		BOOL bIsNewParamValues = pCtxt->IsNewParamValues();
		if ( bIsNewParamValues )
		{			 			
			// Read sampling  data from worksheet.
			Dataset dsSampling(wks, 0);
			 vector vSample,vG;
			 vSample = dsSampling;
			 
	 		int nSize = dsSampling.GetSize();
			vSample.SetSize(nSize);
			vF.SetSize(nSize);
			vG.SetSize(nSize); 
			 
			for(i=0;i<=nSize;i++)
			{
				if(vSample[i] < C)
				{
					vF[i]= B * (C-vSample[i])^0.5;
				}else{
					vF[i]=0;
				}
				vG[i]=exp(-(vSample[i]-C)^2/(2*D^2))/(0.39894*D); 
				 
	 		}
		 
			 	//vG=exp(-(vSample-C)^2/(2*D^2))/(0.39894*D); 
			
			int iRet = fft_fft_convolution(nSize, vF, vG);
 	 			
		}
		 	
		NLSFCURRINFO    stCurrInfo;
		pCtxt->GetFitCurrInfo(&stCurrInfo);
		// Get the data index for the iteration
	int nCurrentIndex = stCurrInfo.nCurrDataIndex;
		// Get the evaluated y value
		y = vF[nCurrentIndex]+A;
		// For compile the function, since we haven't use x here.
	 	x;
	//	 }}
	}
	// End of editable part
}