dpnp.copysign

dpnp.copysign(x1, x2, /, out=None, *, where=True, order='K', dtype=None, subok=True, **kwargs)[source]

Change the sign of x1 to that of x2, element-wise.

For full documentation refer to numpy.copysign.

Parameters:

  • x1 ({dpnp.ndarray, usm_ndarray}) – First input array, expected to have a real floating-point data type.

  • x2 ({dpnp.ndarray, usm_ndarray}) – Second input array, also expected to have a real 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.

  • order ({"C", "F", "A", "K"}, optional) – Memory layout of the newly output array, if parameter out is None. Default: “K”.

Returns:

out – The values of x1 with the sign of x2.

Return type:

dpnp.ndarray

Limitations

Parameters x1 and x2 are supported as either scalar, dpnp.ndarray or dpctl.tensor.usm_ndarray, but both x1 and x2 can not be scalars at the same time. Parameters where, dtype and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise the function will be executed sequentially on CPU. Input array data types are limited by supported real-valued data types.

See also

dpnp.negative

Return the numerical negative of each element of x.

dpnp.positive

Return the numerical positive of each element of x.

Examples

>>> import dpnp as np
>>> np.copysign(np.array(1.3), np.array(-1))
array(-1.3)
>>> 1 / np.copysign(np.array(0), 1)
array(inf)
>>> 1 / np.copysign(np.array(0), -1)
array(-inf)

>>> x = np.array([-1, 0, 1])
>>> np.copysign(x, -1.1)
array([-1., -0., -1.])
>>> np.copysign(x, np.arange(3) - 1)
array([-1., 0., 1.])