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There are three multi-dimensional interpolation functions in Octave, with similar capabilities. Methods using Delaunay tessellation are described in Interpolation on Scattered Data.

- Function File:
`zi`=**interp2***(*`x`,`y`,`z`,`xi`,`yi`) - Function File:
`zi`=**interp2***(*`z`,`xi`,`yi`) - Function File:
`zi`=**interp2***(*`z`,`n`) - Function File:
`zi`=**interp2***(*`z`) - Function File:
`zi`=**interp2***(…,*`method`) - Function File:
`zi`=**interp2***(…,*`method`,`extrap`) -
Two-dimensional interpolation.

Interpolate reference data

`x`,`y`,`z`to determine`zi`at the coordinates`xi`,`yi`. The reference data`x`,`y`can be matrices, as returned by`meshgrid`

, in which case the sizes of`x`,`y`, and`z`must be equal. If`x`,`y`are vectors describing a grid then`length (`

and`x`) == columns (`z`)`length (`

. In either case the input data must be strictly monotonic.`y`) == rows (`z`)If called without

`x`,`y`, and just a single reference data matrix`z`, the 2-D region

is assumed. This saves memory if the grid is regular and the distance between points is not important.`x`= 1:columns (`z`),`y`= 1:rows (`z`)If called with a single reference data matrix

`z`and a refinement value`n`, then perform interpolation over a grid where each original interval has been recursively subdivided`n`times. This results in`2^`

additional points for every interval in the original grid. If`n`-1`n`is omitted a value of 1 is used. As an example, the interval [0,1] with

results in a refined interval with points at [0, 1/4, 1/2, 3/4, 1].`n`==2The interpolation

`method`is one of:`"nearest"`

Return the nearest neighbor.

`"linear"`

(default)Linear interpolation from nearest neighbors.

`"pchip"`

Piecewise cubic Hermite interpolating polynomial—shape-preserving interpolation with smooth first derivative.

`"cubic"`

Cubic interpolation (same as

`"pchip"`

).`"spline"`

Cubic spline interpolation—smooth first and second derivatives throughout the curve.

`extrap`is a scalar number. It replaces values beyond the endpoints with`extrap`. Note that if`extrapval`is used,`method`must be specified as well. If`extrap`is omitted and the`method`is`"spline"`

, then the extrapolated values of the`"spline"`

are used. Otherwise the default`extrap`value for any other`method`is`"NA"`

.

- Function File:
`vi`=**interp3***(*`x`,`y`,`z`,`v`,`xi`,`yi`,`zi`) - Function File:
`vi`=**interp3***(*`v`,`xi`,`yi`,`zi`) - Function File:
`vi`=**interp3***(*`v`,`n`) - Function File:
`vi`=**interp3***(*`v`) - Function File:
`vi`=**interp3***(…,*`method`) - Function File:
`vi`=**interp3***(…,*`method`,`extrapval`) -
Three-dimensional interpolation.

Interpolate reference data

`x`,`y`,`z`,`v`to determine`vi`at the coordinates`xi`,`yi`,`zi`. The reference data`x`,`y`,`z`can be matrices, as returned by`meshgrid`

, in which case the sizes of`x`,`y`,`z`, and`v`must be equal. If`x`,`y`,`z`are vectors describing a cubic grid then`length (`

,`x`) == columns (`v`)`length (`

, and`y`) == rows (`v`)`length (`

. In either case the input data must be strictly monotonic.`z`) == size (`v`, 3)If called without

`x`,`y`,`z`, and just a single reference data matrix`v`, the 3-D region

is assumed. This saves memory if the grid is regular and the distance between points is not important.`x`= 1:columns (`v`),`y`= 1:rows (`v`),`z`= 1:size (`v`, 3)If called with a single reference data matrix

`v`and a refinement value`n`, then perform interpolation over a 3-D grid where each original interval has been recursively subdivided`n`times. This results in`2^`

additional points for every interval in the original grid. If`n`-1`n`is omitted a value of 1 is used. As an example, the interval [0,1] with

results in a refined interval with points at [0, 1/4, 1/2, 3/4, 1].`n`==2The interpolation

`method`is one of:`"nearest"`

Return the nearest neighbor.

`"linear"`

(default)Linear interpolation from nearest neighbors.

`"cubic"`

Piecewise cubic Hermite interpolating polynomial—shape-preserving interpolation with smooth first derivative (not implemented yet).

`"spline"`

Cubic spline interpolation—smooth first and second derivatives throughout the curve.

`extrapval`is a scalar number. It replaces values beyond the endpoints with`extrapval`. Note that if`extrapval`is used,`method`must be specified as well. If`extrapval`is omitted and the`method`is`"spline"`

, then the extrapolated values of the`"spline"`

are used. Otherwise the default`extrapval`value for any other`method`is`"NA"`

.

- Function File:
`vi`=**interpn***(*`x1`,`x2`, …,`v`,`y1`,`y2`, …) - Function File:
`vi`=**interpn***(*`v`,`y1`,`y2`, …) - Function File:
`vi`=**interpn***(*`v`,`m`) - Function File:
`vi`=**interpn***(*`v`) - Function File:
`vi`=**interpn***(…,*`method`) - Function File:
`vi`=**interpn***(…,*`method`,`extrapval`) -
Perform

`n`-dimensional interpolation, where`n`is at least two.Each element of the

`n`-dimensional array`v`represents a value at a location given by the parameters`x1`,`x2`, …,`xn`. The parameters`x1`,`x2`, …,`xn`are either`n`-dimensional arrays of the same size as the array`v`in the`"ndgrid"`

format or vectors. The parameters`y1`, etc. respect a similar format to`x1`, etc., and they represent the points at which the array`vi`is interpolated.If

`x1`, …,`xn`are omitted, they are assumed to be`x1 = 1 : size (`

, etc. If`v`, 1)`m`is specified, then the interpolation adds a point half way between each of the interpolation points. This process is performed`m`times. If only`v`is specified, then`m`is assumed to be`1`

.The interpolation

`method`is one of:`"nearest"`

Return the nearest neighbor.

`"linear"`

(default)Linear interpolation from nearest neighbors.

`"pchip"`

Piecewise cubic Hermite interpolating polynomial—shape-preserving interpolation with smooth first derivative (not implemented yet).

`"cubic"`

Cubic interpolation (same as

`"pchip"`

[not implemented yet]).`"spline"`

Cubic spline interpolation—smooth first and second derivatives throughout the curve.

The default method is

`"linear"`

.`extrapval`is a scalar number. It replaces values beyond the endpoints with`extrapval`. Note that if`extrapval`is used,`method`must be specified as well. If`extrapval`is omitted and the`method`is`"spline"`

, then the extrapolated values of the`"spline"`

are used. Otherwise the default`extrapval`value for any other`method`is`"NA"`

.

A significant difference between `interpn`

and the other two
multi-dimensional interpolation functions is the fashion in which the
dimensions are treated. For `interp2`

and `interp3`

, the y-axis is
considered to be the columns of the matrix, whereas the x-axis corresponds to
the rows of the array. As Octave indexes arrays in column major order, the
first dimension of any array is the columns, and so `interpn`

effectively
reverses the ’x’ and ’y’ dimensions. Consider the example,

x = y = z = -1:1; f = @(x,y,z) x.^2 - y - z.^2; [xx, yy, zz] = meshgrid (x, y, z); v = f (xx,yy,zz); xi = yi = zi = -1:0.1:1; [xxi, yyi, zzi] = meshgrid (xi, yi, zi); vi = interp3 (x, y, z, v, xxi, yyi, zzi, "spline"); [xxi, yyi, zzi] = ndgrid (xi, yi, zi); vi2 = interpn (x, y, z, v, xxi, yyi, zzi, "spline"); mesh (zi, yi, squeeze (vi2(1,:,:)));

where `vi`

and `vi2`

are identical. The reversal of the
dimensions is treated in the `meshgrid`

and `ndgrid`

functions
respectively.
The result of this code can be seen in Figure 29.4.

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