# Documentation

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## Interpolation of Multiple 1-D Value Sets

This example shows how to interpolate three 1-D data sets in a single pass using `griddedInterpolant`. This is a faster alternative to looping over your data sets.

Define the x-coordinates that are common to all value sets.

```x = (1:5)'; ```

Define the sets of sample points along the columns of matrix V.

```V = [x, 2*x, 3*x] ```
```V = 1 2 3 2 4 6 3 6 9 4 8 12 5 10 15 ```

Create a 2-D grid of sample points.

```samplePoints = {x, 1:size(V,2)}; ```

This compact notation specifies a full 2-D grid. The first element, `samplePoints{1}`, contains the x-coordinates for `V`, and `samplePoints{2}` contains the y-coordinates. The orientation of each coordinate vector does not matter.

Create the interpolant, `F`, by passing the sample points and sample values to `griddedInterpolant`.

```F = griddedInterpolant(samplePoints,V); ```

Create a 2-D query grid with `0.5` spacing along `x` over all columns of `V`.

```queryPoints = {(1:0.5:5),1:size(V,2)}; ```

Evaluate the interpolant at the x-coordinates for each value set.

```Vq = F(queryPoints) ```
```Vq = 1.0000 2.0000 3.0000 1.5000 3.0000 4.5000 2.0000 4.0000 6.0000 2.5000 5.0000 7.5000 3.0000 6.0000 9.0000 3.5000 7.0000 10.5000 4.0000 8.0000 12.0000 4.5000 9.0000 13.5000 5.0000 10.0000 15.0000 ```