dpnp.absolute

dpnp.absolute(x, out=None, order='K', dtype=None, casting='same_kind', **kwargs)

Calculates the absolute value for each element x_i of input array x.

For full documentation refer to numpy.absolute.

Parameters:

  • x ({dpnp.ndarray, usm_ndarray}) -- Input arrays, expected to have numeric 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 ({None, "C", "F", "A", "K"}, optional) -- Memory layout of the newly output array, Cannot be provided together with out. Default: "K".

  • dtype ({None, dtype}, 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. Cannot be provided together with out. Default: "safe".

Returns:

out -- An array containing the element-wise absolute values. For complex input, the absolute value is its magnitude. If x has a real-valued data type, the returned array has the same data type as x. If x has a complex floating-point data type, the returned array has a real-valued floating-point data type whose precision matches the precision of x.

Return type:

dpnp.ndarray

Limitations

Keyword arguments where and subok are supported with their default values. Other keyword arguments is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.fabs

Calculate the absolute value element-wise excluding complex types.

Notes

dpnp.abs is a shorthand for this function.

Examples

>>> import dpnp as np
>>> a = np.array([-1.2, 1.2])
>>> np.absolute(a)
array([1.2, 1.2])

>>> a = np.array(1.2 + 1j)
>>> np.absolute(a)
array(1.5620499351813308)