quote:

---

How are we supposed to deal with undocumented (and possibly untested) features?

---

while(xx[index] == xx[index-1])

void GenMeanSexyTwo(Dataset &xdataset, Dataset &ydataset, Dataset &meanxdataset, Dataset &meandataset, Dataset &sddataset)
{

	// assume x y sorted by x

	int NumData=xdataset.GetSize();
	meandataset.SetSize(NumData);
	meanxdataset.SetSize(NumData);
	sddataset.SetSize(NumData);

	vector y;
	int NumXValue=0;
	int NumValue=1;
	int EstSD=0;
	y.Add(ydataset[0]);

	for(NumValue=2; NumValue<=NumData; NumValue++)
	{
		EstSD=1;
		if(xdataset[NumValue-1] == xdataset[NumValue-2])
		{
			y.Add(ydataset[NumValue-1]);
			EstSD=0;
			if(NumValue==NumData) EstSD=1;
		};
		if(EstSD==1)
		{ // Estimate SD and mean
			
			int dsSize = y.GetSize();
			NumXValue++; // Number of 'X groups'
			// definition of some variables
			double ysd,yskew, ykurt, wsum, ymean, ymax, ymin;
			double *wt;
			int sucess, weight, nvalid = dsSize;
			wt = NULL;
			
			if(y.GetSize() > 1)
			{
				sucess = nag_summary_stats_1var(nvalid, y, wt, &nvalid, &ymean, &ysd, &yskew, &ykurt, &ymin, &ymax, &wsum);

				meandataset[NumXValue-1]=ymean;
				meanxdataset[NumXValue-1]=xdataset[NumValue-2];
				sddataset[NumXValue-1]=ysd;

			}
			if(y.GetSize()==1) {
				meandataset[NumXValue-1]=ydataset[NumValue-2];
				meanxdataset[NumXValue-1]=xdataset[NumValue-2];
				sddataset[NumXValue-1]=0;
			}

			y.RemoveAll();
			y.Add(ydataset[NumValue-1]);
			
		}
	}
	
	

	meandataset.SetSize(NumXValue);
	meanxdataset.SetSize(NumXValue);
	sddataset.SetSize(NumXValue);
}

sucess = nag_summary_stats_1var(nvalid, y, wt, &nvalid, &ymean, &ysd)

quote:

---

ExtractOneGroup is inside wksheet.h and not included in documentation as it was one of those developing functions that are not fully tested.

---

void test_one_group(int nGroupVal = 1, int nGroupCol = 0, int nDataCol = 1)
{
	Worksheet wks = Project.ActiveLayer();
	Dataset dGroup(wks, nGroupCol);
	vector<ushort> vRowMap;
	vRowMap = dGroup;// assume group col already contain group numeric values like 1,2,3 etc

	vector vResult;
	if(wks.ExtractOneGroup(vResult, nDataCol, vRowMap, 0, 0, vRowMap.GetSize()-1, nGroupVal))
	{
		// save result into new wks to view
		Worksheet wResult("Test");
		if(wResult == NULL)
		{
			wResult.Create();
			wResult.GetPage().Rename("Test");
			wResult.SetSize(-1, 0);
		}
		int nCol = wResult.AddCol();
		Dataset dOut(wResult, nCol);
		dOut = vResult;
	}
}

...

test_peter()
{
	Dataset xx(Project.WorksheetPages(0).GetName(),0); // read in column 1 as Dataset
	Dataset yy(Project.WorksheetPages(0).GetName(),1); // read in column 1 as Dataset
	//Dataset cannot be used as a parameter, but vector can.
	vector x, y;
	int index = 0;
	while(index<=xx.GetSize())
	{
		if(index == 0)
		{
	  		x.Add(xx[index]);
	  		y.Add(yy[index]);
	  		index++;
		}
	 	else
	 	{
	 		if(index != xx.GetSize())
	 		{
			  	while(xx[index] == xx[index-1])
			  	{
			   	x.Add(xx[index]);
			   	y.Add(yy[index]);
			   	index++;
			  	}
	 		}
		  	int dsSize = x.GetSize();
		  	// definition of some variables
		  	double xsd,xskew, xkurt, wsum, xmean, xmax, xmin;
		  	double *wt;
		  	int sucess, weight, nvalid = dsSize;
		  	wt = NULL;
			
		  	if(y.GetSize() != 1)
		  	{
			  	sucess = nag_summary_stats_1var(nvalid, y, wt, &nvalid,
			            &xmean, &xsd, &xskew,
			            &xkurt, &xmin, &xmax, &wsum);
			   printf("x-value: %i -> means: %0.2f\tsd: %0.2f\n",(int)x[index-1], xmean, xsd);
		  	}
		  	else
		  		printf("x-value: %i -> means: %0.2f\tsd: %0.2f\n",(int)x[index-1], y[0], 0.);
		   y.RemoveAll();
		   
			if(index != xx.GetSize())
	 		{		   
			   x.Add(xx[index]);
			   y.Add(yy[index]);
	 		}
	 		index++;
	 	}
	}
}