Fit with multiple independent variables function

Version Info

Minimum Origin Version Required: Origin 8.5 SR0

Need to do before Running Examples

Prior to running the following example, the nlsf_utils.c file need to be loaded and compiled. This can be done from script with the following command:

run.LoadOC(Originlab\nlsf_utils.c);

Examples

1. New a worksheet and import \Samples\Matrix Conversion and Gridding\XYZ Random Gaussian.dat. Add a new column and fill it with uniform random numbers as weight data.
2. Copy the following example codes to a c file and compile.
3. Run test_fit_with_multi_indep_func in Command Window. The fitting results will be output to Command Window.

#include <..\OriginLab\NLFitSession.h>

void test_fit_with_multi_indep_func()
{
        Worksheet wks = Project.ActiveLayer();
        if(!wks)
        {
                out_str("Not a valid worksheet!");
                return; // need to activate a worksheet with data
        }
 
        NLFitSession FitSession;
        if(!FitSession.SetFunction("Gauss2D"))
        {
                out_str("Set fitting function error!");
                return;
        }     
        vector<string> vsParamNames;
        int nNumParamsInFunction = FitSession.GetParamNamesInFunction(vsParamNames);
        
        // get data range
        DataRange drInputData;
        drInputData.Add(wks, 0, "X");  // x column
        drInputData.Add(wks, 1, "X");  // y column
        drInputData.Add(wks, 2, "Y");  // z column
        drInputData.Add(wks, 3, "W");  // optional, weight column
        
        // 2. set the dataset with tree   
        Tree trInputData;
        TreeNode trRange = trInputData.AddNode("Range1");
        drInputData.GetTree(trRange);
        
        bool bRet = FitSession.SetData(trInputData);

        // 3. Set parameter init values   
         // Way 1. to init parameter by running parameter initial code.
    if(!FitSession.ParamsInitValues())
        {
                out_str("Init values error!");
                return;
        }     
        
        // Way 2. to init parameter values one by one     
        /*
    vector vParams(nNumParamsInFunction);
    vParams[0] = 2; // z0
    vParams[1] = 9.45; // A
    vParams[2] = 15; // xc
    vParams[3] = 3.4; // w1
    vParams[4] = 14.7; // yc
    vParams[5] = 3.31; // w2
    int nErr = FitSession.SetParamValues(vParams);
    
    if(nErr != 0)
    {
        printf("Fail to set init parameters: err= %d.", nErr);
        return;
    }   
    */

    // set weight method
        if(!FitSession.SetWeightData(WEIGHT_INSTRUMENTAL, 0.0, 0.0, 0.0))
        {
                out_str("Set weight method error!");
                return;
        }

        // fit
        int nFitOutcome;
        if(!FitSession.Fit(&nFitOutcome))
        {
                string strOutcome = FitSession.GetFitOutCome(nFitOutcome);
                out_str("Fit error! "+strOutcome);
                return;
        }
        
        // get fit results
        RegStats fitStats;
        NLSFFitInfo fitInfo;
        vector vParamValues, vErrors;
        FitSession.GetFitResultsStats(&fitStats, &fitInfo, false, 0);
        FitSession.GetFitResultsParams(vParamValues, vErrors);

        printf("# Iterations = %d, Reduced Chisqr = %g\n", fitInfo.Iterations, fitStats.ReducedChiSq);
        for(int nParam=0; nParam<vParamValues.GetSize(); nParam++)
        {
                printf("# %s = %f, %s_error = %f\n", vsParamNames[nParam], vParamValues[nParam], vsParamNames[nParam], vErrors[nParam]);
        }
}