dpnp.acos

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

Computes inverse cosine for each element x_i for input array x.

The inverse of dpnp.cos so that, if y = cos(x), then x = arccos(y). Note that dpnp.acos is an alias of dpnp.arccos.

For full documentation refer to numpy.arccos.

Parameters:

  • x ({dpnp.ndarray, usm_ndarray}) -- Input array, 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. Default: None.

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

Returns:

out -- An array containing the element-wise inverse cosine, in radians and in the closed interval [-pi/2, pi/2]. 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.

See also

dpnp.cos

Trigonometric cosine, element-wise.

dpnp.arctan

Trigonometric inverse tangent, element-wise.

dpnp.arcsin

Trigonometric inverse sine, element-wise.

dpnp.arccosh

Hyperbolic inverse cosine, element-wise.

Notes

dpnp.arccos is a multivalued function: for each x there are infinitely many numbers z such that cos(z) = x. The convention is to return the angle z whose real part lies in [0, pi].

For real-valued input data types, dpnp.arccos always returns real output. For each value that cannot be expressed as a real number or infinity, it yields nan.

For complex-valued input, dpnp.arccos is a complex analytic function that has, by convention, the branch cuts [-inf, -1] and [1, inf] and is continuous from above on the former and from below on the latter.

The inverse cos is also known as \(acos\) or \(cos^{-1}\).

Examples

>>> import dpnp as np
>>> x = np.array([1, -1])
>>> np.arccos(x)
array([0.0,  3.14159265])