## Documentation Center |

Data gridding and hypersurface fitting (dimension ≥ 2)

`yi = griddatan(x,y,xi)yi = griddatan(x,y,xi,method)yi = griddatan(x,y,xi,method,options)`

`yi = griddatan(x,y,xi)` fits
a hyper-surface of the form *y * = *f(x)* to
the data in the (usually) nonuniformly-spaced vectors (`x`, `y`). `griddatan` interpolates
this hyper-surface at the points specified by `xi` to
produce `yi`. `xi` can be nonuniform.

`X` is of dimension `m`-by-`n`,
representing `m` points in n-dimensional space. `y` is
of dimension `m`-by-`1`, representing `m` values
of the hyper-surface *f*(`X`). `xi` is
a vector of size `p`-by-`n`, representing `p` points
in the n-dimensional space whose surface value is to be fitted. `yi` is
a vector of length `p` approximating the values *f*(`xi`).
The hypersurface always goes through the data points (`X`,`y`). `xi` is
usually a uniform grid (as produced by `meshgrid`).

`yi = griddatan(x,y,xi,method)` defines
the type of surface fit to the data, where `'method'` is
one of:

Triangulation-based linear interpolation (default) | |

Nearest neighbor interpolation |

All the methods are based on a Delaunay triangulation of the data.

If `method` is `[]`, the default `'linear'` method
is used.

`yi = griddatan(x,y,xi,method,options)` specifies
a cell array of strings `options` to be used in Qhull
via `delaunayn`.

If `options` is `[]`, the
default options are used. If `options` is `{''}`,
no options are used, not even the default.

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