1-D data interpolation (table lookup)

returns
interpolated values of a 1-D function at specific query points using
linear interpolation. Vector `vq`

= interp1(`x`

,`v`

,`xq`

)`x`

contains the sample
points, and `v`

contains the corresponding values, *v*(*x*).
Vector `xq`

contains the coordinates of the query
points.

If you have multiple sets of data that are sampled at the same
point coordinates, then you can pass `v`

as an array.
Each column of array `v`

contains a different set
of 1-D sample values.

specifies
a strategy for evaluating points that lie outside the domain of `vq`

= interp1(`x`

,`v`

,`xq`

,`method`

,`extrapolation`

)`x`

.
Set `extrapolation`

to `'extrap'`

when
you want to use the `method`

algorithm for extrapolation.
Alternatively, you can specify a scalar value, in which case, `interp1`

returns
that value for all points outside the domain of `x`

.

returns
interpolated values and assumes a default set of sample point coordinates.
The default points are the sequence of numbers from `vq`

= interp1(`v`

,`xq`

)`1`

to `n`

,
where `n`

depends on the shape of `v`

:

When v is a vector, the default points are

`1:length(v)`

.When v is an array, the default points are

`1:size(v,1)`

.

Use this syntax when you are not concerned about the absolute distances between points.

specifies
an extrapolation strategy and uses the default sample points.`vq`

= interp1(`v`

,`xq`

,`method`

,`extrapolation`

)

returns the piecewise polynomial form of
`pp`

= interp1(`x`

,`v`

,`method`

,'pp')*v*(*x*) using the
`method`

algorithm.

**Note**

This syntax is not recommended. Use `griddedInterpolant`

instead.

[1] Akima, Hiroshi. "A new method
of interpolation and smooth curve fitting based on local procedures." *Journal
of the ACM (JACM)* , 17.4, 1970, pp. 589-602.

[2] Akima, Hiroshi. "A method of
bivariate interpolation and smooth surface fitting based on local procedures."
*Communications of the ACM* , 17.1, 1974, pp. 18-20.