numpy.ma.dstack

numpy.ma.hsplit

# numpy.ma.hstack¶

`numpy.ma.``hstack`(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_seq object>

Stack arrays in sequence horizontally (column wise).

This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided by `hsplit`.

This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions `concatenate`, `stack` and block provide more general stacking and concatenation operations.

Parameters
tupsequence of ndarrays

The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.

Returns
stackedndarray

The array formed by stacking the given arrays.

`stack`

Join a sequence of arrays along a new axis.

`vstack`

Stack arrays in sequence vertically (row wise).

`dstack`

Stack arrays in sequence depth wise (along third axis).

`concatenate`

Join a sequence of arrays along an existing axis.

`hsplit`

Split array along second axis.

`block`

Assemble arrays from blocks.

Notes

The function is applied to both the _data and the _mask, if any.

Examples

```>>> a = np.array((1,2,3))
>>> b = np.array((2,3,4))
>>> np.hstack((a,b))
array([1, 2, 3, 2, 3, 4])
>>> a = np.array([,,])
>>> b = np.array([,,])
>>> np.hstack((a,b))
array([[1, 2],
[2, 3],
[3, 4]])
```