numpy.ma.hstack¶

numpy.ma.hstack(tup) = <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-Darrays where it concatenates along the first axis. Rebuilds arrays dividedbyhsplit.

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

Parameters:	tup:sequence 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:	stacked:ndarray The array formed by stacking the given arrays.

See also

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