# IGRID

## Purpose:

Grids irregular XYZ data to a uniform grid using the inverse distance method.

## Syntax:

IGRID(x, y, z, gridsize, interp, weights, radius)

 x - A series, the X or horizontal range. y - A series, the Y or vertical range. z - A series, the Z or height data. gridsize - Optional. An integer or series, the size of output grid. Defaults to sqrt(length(x)). interp - Optional. An integer, the cubic spline smoothing factor. Defaults to 1 (no smoothing). weights - Optional. A series, the weights of distance function. Defaults to {0, 0, 1, 1, 1}. radius - Optional. A real, the maximum radius to include in the interpolation. Defaults to -1, all.

An array.

## Example:

x = grand(100, 1)*2 - 1;

y = grand(100, 1)*2 - 1;

z = cos(x*y);

xyz = igrid(x, y, z);

Grids the function cos(x*y) over the range -1 to 1 with an interpolated grid of 11x11.

## Example:

xyz2 = igrid(x, y, z, 20)

Same as above but the interpolated grid is 20x20.

## Example:

xyz2 = igrid(x[..], y[..], z[..], {20, 30}, 3)

Same as above but the interpolated grid is 20x30 and the surface is further interpolated by a factor of 3 using cubic spline interpolation.

## Example:

IGRID also accepts a single XYZ series as input:

xyzser = xyz(x, y, z)

xyz3 = igrid(xyzser)

Same as first example.

xyz3 = igrid(xyzser, 20)

Same as second example.

xyz3 = igrid(xyzser, {20, 30}, 3)

Same as third example.

xyz4 = igrid(xyzser, {20, 30}, 3, {0, 1})

Same as above except the classical inverse squared distance weighting function is used instead of the default.

## Remarks:

IGRID uses INVDISTANCE, the inverse distance method of gridding irregularly spaced data.

If GRIDSIZE is a series, the first element specifies the output number of columns and the second element specifies the output number of rows.

The optional WEIGHTS series specifies the weighting of the radius terms:

{r^-1, r^-2, r^-3, r^-4, ...}.

The default of {0, 0, 1, 1, 1} specifies a linear combination of r-3 + r-4 + r-5 terms. Use the series {0, 1} to specify the classical inverse squared distance weighting function.

See INVDISTANCE for algorithmic details.