dpnp.log2

dpnp.log2(x, out=None, where=True, order='K', dtype=None, subok=True, **kwargs)

Computes the base-2 logarithm for each element x_i of input array x.

For full documentation refer to numpy.log2.

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 base-2 logarithm 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.

See also

dpnp.log

Natural logarithm, element-wise.

dpnp.log10

Return the base 10 logarithm of the input array, element-wise.

dpnp.log1p

Return the natural logarithm of one plus the input array, element-wise.

Examples

>>> import dpnp as np
>>> x = np.array([0, 1, 2, 2**4])
>>> np.log2(x)
array([-inf, 0.0, 1.0, 4.0])

>>> xi = np.array([0+1.j, 1, 2+0.j, 4.j])
>>> np.log2(xi)
array([ 0.+2.26618007j,  0.+0.j        ,  1.+0.j        ,  2.+2.26618007j])