dpnp.hstack

dpnp.hstack(tup, *, dtype=None, casting='same_kind')

Stack arrays in sequence horizontally (column wise).

For full documentation refer to numpy.hstack.

Parameters:

• tup ({dpnp.ndarray, usm_ndarray}) -- The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.

• dtype (str or dtype) -- If provided, the destination array will have this dtype.

• casting ({'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional) -- Controls what kind of data casting may occur. Defaults to 'same_kind'.

Returns:

out -- The stacked array which has one more dimension than the input arrays.

Return type:

dpnp.ndarray

See also

dpnp.concatenate

Join a sequence of arrays along an existing axis.

dpnp.stack

Join a sequence of arrays along a new axis.

dpnp.vstack

Stack arrays in sequence vertically (row wise).

dpnp.dstack

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

dpnp.column_stack

Stack 1-D arrays as columns into a 2-D array.

dpnp.block

Assemble an ndarray from nested lists of blocks.

dpnp.split

Split array into a list of multiple sub-arrays of equal size.

Examples

>>> import dpnp as np
>>> a = np.array((1, 2, 3))
>>> b = np.array((4, 5, 6))
>>> np.hstack((a, b))
array([1, 2, 3, 4, 5, 6])

>>> a = np.array([[1], [2], [3]])
>>> b = np.array([[4], [5], [6]])
>>> np.hstack((a, b))
array([[1, 4],
       [2, 5],
       [3, 6]])