dpnp.log

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

Computes the natural logarithm for each element x_i of input array x.

For full documentation refer to numpy.log.

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 natural logarithm values. 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. Otherwise NotImplementedError exception will be raised.

See also

dpnp.log10

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

dpnp.log2

Base-2 logarithm of x.

dpnp.log1p

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

Examples

>>> import dpnp as np
>>> x = np.array([1, np.e, np.e**2, 0])
>>> np.log(x)
array([  0.,   1.,   2., -inf])