dpnp.concatenate

dpnp.concatenate(arrays, /, *, axis=0, out=None, dtype=None, casting='same_kind')

Join a sequence of arrays along an existing axis.

Note that dpnp.concat is an alias of dpnp.concatenate.

For full documentation refer to numpy.concatenate.

Parameters:

• arrays ({Sequence of dpnp.ndarray or usm_ndarray}) -- The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).

• axis (int, optional) --

  The axis along which the arrays will be joined. If axis is None, arrays are flattened before use.

  Default: 0.

• out (dpnp.ndarray, optional) --

  If provided, the destination to place the result. The shape must be correct, matching that of what concatenate would have returned if no out argument were specified.

  Default: None.

• dtype ({None, str, dtype object}, optional) --

  If provided, the destination array will have this dtype. Cannot be provided together with out.

  Default: None.

• casting ({'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional) --

  Controls what kind of data casting may occur.

  Default: "same_kind".

Returns:

out -- The concatenated array.

Return type:

dpnp.ndarray

See also

dpnp.array_split

Split an array into multiple sub-arrays of equal or near-equal size.

dpnp.split

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

dpnp.hsplit

Split array into multiple sub-arrays horizontally (column wise).

dpnp.vsplit

Split array into multiple sub-arrays vertically (row wise).

dpnp.dsplit

Split array into multiple sub-arrays along the 3rd axis (depth).

dpnp.stack

Stack a sequence of arrays along a new axis.

dpnp.block

Assemble arrays from blocks.

dpnp.hstack

Stack arrays in sequence horizontally (column wise).

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.

Examples

>>> import dpnp as np
>>> a = np.array([[1, 2], [3, 4]])
>>> b = np.array([[5, 6]])
>>> np.concatenate((a, b), axis=0)
array([[1, 2],
       [3, 4],
       [5, 6]])
>>> np.concatenate((a, b.T), axis=1)
array([[1, 2, 5],
       [3, 4, 6]])
>>> np.concatenate((a, b), axis=None)
array([1, 2, 3, 4, 5, 6])