Extrapolation of a 2D data table with 3 input variables
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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.
.
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Githin John
le 27 Jan 2020
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.
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