dpnp.log

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

Computes the natural logarithm element-wise.

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}, 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 – 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])