dpnp.logaddexp

dpnp.logaddexp(x1, x2, /, out=None, *, where=True, order='K', dtype=None, subok=True, **kwargs)

Calculates log(exp(x1) + exp(x2)), element-wise.

For full documentation refer to numpy.logaddexp.

Returns:

out – Logarithm of exp(x1) + exp(x2), element-wise.

Return type:

dpnp.ndarray

Limitations

Parameters x1 and x2 are supported as either scalar, dpnp.ndarray or dpctl.tensor.usm_ndarray, but both x1 and x2 can not be scalars at the same time. Parameters where, dtype and subok are supported with their default values. Keyword arguments kwargs are currently unsupported. Otherwise the function will be executed sequentially on CPU. Input array data types are limited by real-valued data types.

See also

dpnp.log

Natural logarithm, element-wise.

dpnp.exp

Exponential, element-wise.

dpnp.logsumdexp

Logarithm of the sum of exponentials of elements in the input array.

Examples

>>> import dpnp as np
>>> prob1 = np.log(np.array(1e-50))
>>> prob2 = np.log(np.array(2.5e-50))
>>> prob12 = np.logaddexp(prob1, prob2)
>>> prob12
array(-113.87649168)
>>> np.exp(prob12)
array(3.5e-50)