# N-dimensional representation classes¶

For code blocks below and any pages linked below, we’ll assume the following imports have already been executed:

```
>>> import astropy.units as u
>>> import numpy as np
>>> import gala.dynamics as gd
```

## Introduction¶

The Astropy representations framework presently only support 3D positions and differential
objects. The `NDCartesianRepresentation`

and
`NDCartesianDifferential`

classes add Cartesian representation
classes that can handle arbitrary numbers of dimensions. For example, 2D
coordinates:

```
>>> xy = np.arange(16).reshape(2, 8) * u.kpc
>>> rep = gd.NDCartesianRepresentation(xy)
>>> rep
<NDCartesianRepresentation (x1, x2) in kpc
[(0., 8.), (1., 9.), (2., 10.), (3., 11.), (4., 12.), (5., 13.),
(6., 14.), (7., 15.)]>
```

4D coordinates:

```
>>> x = np.arange(16).reshape(4, 4) * u.kpc
>>> rep = gd.NDCartesianRepresentation(x)
>>> rep
<NDCartesianRepresentation (x1, x2, x3, x4) in kpc
[(0., 4., 8., 12.), (1., 5., 9., 13.), (2., 6., 10., 14.),
(3., 7., 11., 15.)]>
```

These can be passed in to the `PhaseSpacePosition`

or `Orbit`

classes as with any of the Astropy
core representation objects:

```
>>> xy = np.arange(16).reshape(2, 8) * u.kpc
>>> vxy = np.arange(16).reshape(2, 8) / 10. * u.kpc / u.Myr
>>> w = gd.PhaseSpacePosition(pos=xy, vel=vxy)
>>> fig = w.plot()
```

(Source code, png, hires.png, pdf)

However, certain functionality such as representation transformations, dynamical quantity calculation, and coordinate frame transformations are disabled when the number of dimensions is not 3 (i.e. when not using the Astropy core representation classes).

### N-dimensional representations API¶

#### Classes¶

`NDCartesianRepresentation` (x[, …]) |
Representation of points in ND cartesian coordinates. |

`NDCartesianDifferential` (d_x[, unit, copy]) |
Differentials in of points in ND cartesian coordinates. |