dpnp.spacing

dpnp.spacing(x, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Return the distance between x and the nearest adjacent number.

For full documentation refer to numpy.spacing.

Parameters:

  • x ({dpnp.ndarray, usm_ndarray}) -- The array of values to find the spacing of, expected to have a real-valued floating-point data type.

  • out ({None, dpnp.ndarray, usm_ndarray}, optional) --

    Output array to populate. Array must have the correct shape and the expected data type.

    Default: None.

  • order ({None, "C", "F", "A", "K"}, optional) --

    Memory layout of the newly output array, if parameter out is None.

    Default: "K".

Returns:

out -- The spacing of values of x. The data type of the returned array is determined by the Type Promotion Rules.

Return type:

dpnp.ndarray

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

Notes

It can be considered as a generalization of EPS: dpnp.spacing(dpnp.float64(1)) == dpnp.finfo(dpnp.float64).eps, and there should not be any representable number between x + spacing(x) and x for any finite x.

Spacing of +- inf and NaN is NaN.

Examples

>>> import dpnp as np
>>> a = np.array(1)
>>> b = np.spacing(a)
>>> b == np.finfo(b.dtype).eps
array(True)