numpy.ma.hstack¶

numpy.ma.hstack(tup) = <numpy.ma.extras._fromnxfunction_seq instance at 0x52d1dcec>¶

Stack arrays in sequence horizontally (column wise).

Take a sequence of arrays and stack them horizontally to make a single array. Rebuild arrays divided by hsplit.

This function continues to be supported for backward compatibility, but you should prefer np.concatenate or np.stack. The np.stack function was added in NumPy 1.10.

Parameters:

Parameters:	tup : sequence of ndarrays All arrays must have the same shape along all but the second axis.
Returns:	stacked : ndarray The array formed by stacking the given arrays.

tup : sequence of ndarrays

All arrays must have the same shape along all but the second axis.

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.

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]])