2.1.18.1 ocmath_2d_kriging_grid

1 Description
2 Syntax
3 Parameters
4 Return
5 Examples
6 Remark
7 See Also
8 Header to Include
9 Reference

Description

This function perform random matrix conversion using Kriging algorithm.

Syntax

int ocmath_2d_kriging_grid( int npts, double* x, double* y, double* z, int noctMin, double radius, double dSmooth, int nXgrid, double* Xgrid, int nYgrid, double* Ygrid, double* Zvalue, int noctMax = -1 );

Parameters

npts: [Input]the number of given points
x: [Input]the x position and value of each given point
y: [Input]the y position and value of each given point
z: [Input]the z position and value of each given point
noctMin: [Input]the minimum points in each quarter, if the number of points; in any quarter is less than noctMin, the search radius will be enlarged.
radius: [Input]the search radius in the unit of 2 * Mean-distance-of-any-two-given-points.; It means that, the z-value of the unknown points will be evaluated using about; (2 * radius * 2)^2 points.
dSmooth: [Input]the parameter in the power semivariogram.
nXgrid: [Input]the number of grids in the x direction.
Xgrid: [Input]the x grid coordinates
nYgrid: [Input]the number of grids in the y direction.
Ygrid: [Input]the y grid coordinates
Zvalue: [Output]the evaluated matrix in row order.
noctMax: [Input]the maximun points in each quarter, if the number of points in any quarter is larger than noctMax, the search will be stopped.

Return

Examples

EX1

void ocmath_2d_kriging_grid_ex1()
{
    int i, j, m, n, nx, ny;
    double xhi, xlo, yhi, ylo;

    nx = 20;
    ny = 20;
    xlo = 0.0;
    ylo = 0.0;
    xhi = 1.0;
    yhi = 1.0;

    double x[400], y[400], f[400];
    
    m = 0;
      for (j=0; j<ny; ++j)
    {
        for (i=0; i<nx; ++i)
        {
            x[m] = (1.0 * (nx-i-1) / (nx-1)) * xlo + (1.0*i / (nx-1)) * xhi;
            y[m] = (1.0 * (ny-j-1) / (ny-1)) * ylo +    (1.0* j / (ny-1)) * yhi;
            f[m]= x[m]*x[m]+y[m]*y[m]+x[m]*y[m];
            ++m;
        }
    }
    
    double px[100], py[100], pf[10000];

    n=0;
    nx = 100;
    ny = 100;
    for (j=0; j<ny; ++j)
        py[j] = (1.0 * (ny-j-1) / (ny-1)) * ylo +    (1.0* j / (ny-1)) * yhi;

    for (i=0; i<nx; ++i)
        px[i] = (1.0 * (nx-i-1) / (nx-1)) * xlo + (1.0*i / (nx-1)) * xhi +0.0005;


    int nret;
    nret = ocmath_2d_kriging_grid(m, x, y, f, 3, 2, 1.8, nx, px, ny, py, pf);
        printf("nret = %d\n",nret);
}

EX2

//assume there are x, y, z data in the first three columns of active worksheet
//this example will create a new matrix storing gridding data using krigging algorithm
#include <wks2mat.h>
#include <wksheet.h>
void ocmath_2d_kriging_grid_ex2()
{
    Worksheet    wks = Project.ActiveLayer();
    if(!wks)
    {
        out_str("found no active worksheet");
        return;
    }
    Dataset    dsX(wks, 0);
    Dataset    dsY(wks, 1);
    Dataset dsZ(wks, 2);
    int npts = dsX.GetSize();
    vector vX = dsX;
    vector vY = dsY;
    vector vZ = dsZ;
    
    //set parameters
    int noctMin = 3;//set the minimum points in each quarter
    double radius = 2.0;//set the search radius
    double dSmooth = 1.8;//set smoothing parameter
    
    //set X and Y of the gridding
    double dXMin, dXMax, dYMin, dYMax;
    vX.GetMinMax(dXMin, dXMax);
    vector vXgrid, vYgrid;
    vXgrid.Data(dXMin, dXMax, (dXMax - dXMin)/99);
    vY.GetMinMax(dYMin, dYMax);
    vYgrid.Data(dYMin, dYMax, (dYMax - dYMin)/199);
    int nXgrid = vXgrid.GetSize();
    int nYgrid = vYgrid.GetSize();
    
    //perform random matrix conversion using Kriging algorithm
    matrix    mZ(nXgrid, nYgrid);
    int iRet = ocmath_2d_kriging_grid(npts, vX, vY, vZ, noctMin, radius, dSmooth, nXgrid, vXgrid, nYgrid, vYgrid, mZ);
    if(iRet)
    {
        out_str("error code is " + iRet);
        return;
    }
    
    //create Matrix storing the result
    MatrixLayer    mResultLayer;
    mResultLayer.Create();
    Matrix    matResult(mResultLayer);
    matResult = mZ;
    MatrixObject mo = mResultLayer.MatrixObjects(0);
    mo.SetXY(dXMin, dYMin, dXMax, dYMax);//set X and Y range of Matrix
}