# Applying coordinate transforms with nibabel.affines.apply_affine

# Applying coordinate transforms with `nibabel.affines.apply_affine`

#

We often want to apply an affine to an array of coordinates, where the last axis of the array is length 3, containing the x, y and z coordinates.

Nibabel uses `nibabel.affines.apply_affine`

for this.

For background see: The nibabel.affines module.

```
import numpy as np
from nibabel.affines import from_matvec, to_matvec, apply_affine
```

```
points = np.array([[0, 1, 2], [2, 2, 4], [3, -2, 1], [5, 3, 1]])
points
```

```
array([[ 0, 1, 2],
[ 2, 2, 4],
[ 3, -2, 1],
[ 5, 3, 1]])
```

```
zooms_plus_translations = from_matvec(np.diag([3, 4, 5]),
[11, 12, 13])
zooms_plus_translations
```

```
array([[ 3, 0, 0, 11],
[ 0, 4, 0, 12],
[ 0, 0, 5, 13],
[ 0, 0, 0, 1]])
```

```
apply_affine(zooms_plus_translations, points)
```

```
array([[11, 16, 23],
[17, 20, 33],
[20, 4, 18],
[26, 24, 18]])
```

Of course, this is the same as:

```
mat, vec = to_matvec(zooms_plus_translations)
(mat @ points.T).T + np.reshape(vec, (1, 3))
```

```
array([[11, 16, 23],
[17, 20, 33],
[20, 4, 18],
[26, 24, 18]])
```

The advantage of `nib.affines.apply_affine`

is that it can deal with arrays
of more than two dimensions, and it transposes the transformation matrices for
you to apply the transforms correctly.

A typical use is when applying extra affine transformations to a X by Y by Z by 3 array of coordinates.