Extrapolation of a 2D data table with 3 input variables

I have a table 'V' that is m x n dimensions. However, the m dimension is dependont on (x,y) and the n dimension is dependent on z. I am able to interpolate data in the table by using griddata. Where

griddata(x_grid, y_grid, z_grid, V)

x_grid, y_grid_ and z_grid are mxn double arrays that contain the specific x y and z coordinates.

Griddata allows me to interpolate between points within the dataset but I would also like to extrapolate data as well. Any help would be greatly appreciated. I have had no luck with griddedInterpoant or scatteredInterpolant: I get the following errors:

griddedInterpolant(x_grid,y_grid,z_grid,V, 'linear', 'linear')

"Error using griddedInterpolant

The number of input coordinate arrays does not equal the number of dimensions (NDIMS) of these arrays"

K>> scatteredInterpolant({x_grid,y_grid,z_grid},V)

Error using scatteredInterpolant

The input points must be a double array.

.

Answer 1

[Githin John]

The scatteredInterpolant function takes the x_grid, y_grid and z_grid inputs as column vectors. You can provide the inputs in that form rather than a mxn array.

For griddedInterpolation, the x_grid, y_grid and z_grid values should be something like those generated using ndgrid.

For more information on the format of inputs, you can check the examples section in the documentation.

[Crystal Green]

I have tried scatteredInterpolant using column vectors. I get the following error

Error using scatteredInterpolant

Data point coordinates have inconsistent dimension.

I have also tried griddedInterpolant usign the x_grid, y_grid and z_grid inputs which are in in the ndgrid format

Error using griddedInterpolant

The number of input coordinate arrays does not equal the number of dimensions (NDIMS) of these arrays.

And I have run everything using the ndims command and all are the same number of dimensions so I'm not sure why it is not working