dpnp.ndarray.view

method

ndarray.view(dtype=None, *, type=None)

New view of array with the same data.

For full documentation refer to numpy.ndarray.view.

Parameters:

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

The desired data type of the returned view, e.g. dpnp.float32 or dpnp.int16. By default, it results in the view having the same data type.

Default: None.

Notes

Passing None for dtype is the same as omitting the parameter, opposite to NumPy where they have different meaning.

view(some_dtype) or view(dtype=some_dtype) constructs a view of the array's memory with a different data type. This can cause a reinterpretation of the bytes of memory.

Only the last axis has to be contiguous.

Limitations

Parameter type is supported only with default value None. Otherwise, the function raises NotImplementedError exception.

Examples

>>> import dpnp as np
>>> x = np.ones((4,), dtype=np.float32)
>>> xv = x.view(dtype=np.int32)
>>> xv[:] = 0
>>> xv
array([0, 0, 0, 0], dtype=int32)

However, views that change dtype are totally fine for arrays with a contiguous last axis, even if the rest of the axes are not C-contiguous:

>>> x = np.arange(2 * 3 * 4, dtype=np.int8).reshape(2, 3, 4)
>>> x.transpose(1, 0, 2).view(np.int16)
array([[[ 256,  770],
        [3340, 3854]],

    [[1284, 1798],
        [4368, 4882]],

    [[2312, 2826],
        [5396, 5910]]], dtype=int16)