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/* --------------------------------------------------------------------------

        Function Name:          SurfaceInterpolation

        Description:            This function will interpolate our data.
                                It uses Alglib's rbfsetalgomultilayer to
                                estimate the point values in the file.

        Input Parameters:       None


        Return Value:           None

   -------------------------------------------------------------------------- */
void SurfaceInterpolation(void)
{
    //These are the calculated parameters for the algorithm call.
    double           Radius = 0 ;
    alglib::ae_int_t Layers = 0 ;
   
    //Debug - diagnostics
    TRACE("Entered function.\n") ;

    //We want to create the model
    alglib::rbfcreate(2, 1, model);

    //Debug - diagnostics
    TRACE("created model.\n") ;
   
    //We now need to set the XY points in our model.   
    alglib::rbfsetpoints(model, XY) ;

    //Debug - diagnostics
    TRACE("set points.\n") ;

    // After we've configured model, we should rebuild it -
    // it will change coefficients stored internally in the
    // rbfmodel structure.
    alglib::rbfreport rep ;

    //We now want to call rbfsetalgomultilayer but we need to calculate the parameters for this.
    //The first parameter is the model, which we have set up.
    //The second parameter is the radius base.
    //The third parameter is the number of layers.
    //The fourth parameter is lambdaV, which for now can be ignored and left as the default (hence not included)

    //The radius must be "several times" larger than the average distance between points
    Radius = 3 * AverageDistance ;

    //Debug - diagnostics
    TRACE("set radius : %f.\n", Radius) ;


    //The number of layers must be so that RLast = RBase/2^(NLayers-1) will be smaller than the typical distance between points.
    //For now, this is just double the radius.
    Layers = LAYER_VALUE ;

    //Debug - diagnostics
    TRACE("set layers : %i.\n", (int)Layers) ;

    //Now let's set up the model with this algorithm.
    alglib::rbfsetalgomultilayer(model, Radius, Layers) ;

    //Debug - diagnostics
    TRACE("set algorithm.\n") ;

    //And rebuild the model so the changes take effect.
    alglib::rbfbuildmodel(model, rep);

    //Debug - diagnostics
    TRACE("built model.\n") ;

    //Now we want to update our grid with the new values
    UpdateGrid() ;

    //Debug - diagnostics
    TRACE("updated grid.\n") ;
}

/* --------------------------------------------------------------------------

        Function Name:          PointsInterpolation

        Description:            This function will interpolate our data.
                                It uses Alglib's rbfsetakgoqnn to estimate
                                the point values in the file.

        Input Parameters:       None


        Return Value:           None

   -------------------------------------------------------------------------- */
void PointsInterpolation(void)
{ 
    //We want to create the model
    alglib::rbfcreate(2, 1, model) ;
   
    //We now need to set the XY points in our model.   
    alglib::rbfsetpoints(model, XY) ;

    // After we've configured model, we should rebuild it -
    // it will change coefficients stored internally in the
    // rbfmodel structure.
    alglib::rbfreport rep ;
    alglib::rbfsetalgoqnn(model) ;   
    alglib::rbfbuildmodel(model, rep) ;

    //Now we want to update our grid with the new values
    UpdateGrid() ;
}

/* --------------------------------------------------------------------------

        Function Name:          UpdateGrid

        Description:            This function will populate the grid array
                                with the new values from the interpolation
                                model. It will also ensure they are not negative.

        Input Parameters:       None


        Return Value:           None

   -------------------------------------------------------------------------- */
void UpdateGrid(void)
{
    double OurTempValue = 0 ;//Retrieved value from model
    double LowestValue  = 1 ;//Lowest number from mode

    //We want to loop through all our points, updating them from the model.
    for (int y = 0; y < GRID_Y; y++)
    {
        for (int x = 0; x < GRID_X; x++)
        {
            //We now want to retrieve our new value from the model,
            //and save it to our temp varaible.
            OurTempValue = alglib::rbfcalc2(model, y, x) ;

            Grid[y][x] = OurTempValue ;

            //Here we are checking if we have a negative number, because we are looking for the lowest.
            if(OurTempValue < 0)
            {
                //Yep, it's negative! But is it less than our previously found negative?
                if(OurTempValue < LowestValue)
                {
                    //Indeed it is, so let's add this as our lowest now.
                    LowestValue = OurTempValue ;
                }
            }
        }
    }

    //Now we want to add the lowest negative value to all values so let's make a call to do that,
    //but only if we found any.
    if(LowestValue < 1)
    {
        RaiseValues(LowestValue * -1) ;//* -1 to make it positive
    }
}