larray.logaddexp(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Logarithm of the sum of exponentiations of the inputs.

larray specific variant of numpy.logaddexp.

Documentation from numpy:

Calculates log(exp(x1) + exp(x2)). This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the logarithm of the calculated probability is stored. This function allows adding probabilities stored in such a fashion.

x1, x2array_like

Input values.

outndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

wherearray_like, optional

Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.


For other keyword-only arguments, see the ufunc docs.


Logarithm of exp(x1) + exp(x2). This is a scalar if both x1 and x2 are scalars.

See also


Logarithm of the sum of exponentiations of inputs in base 2.


New in version 1.3.0.


>>> prob1 = np.log(1e-50)
>>> prob2 = np.log(2.5e-50)
>>> prob12 = np.logaddexp(prob1, prob2)
>>> prob12
>>> np.exp(prob12)