dask 2021.10.0

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

Some inconsistencies with the Dask version may exist.

Logarithm of the sum of exponentiations of the inputs.

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.

Notes

versionadded

Parameters

x1, x2 : array_like

Input values. If x1.shape != x2.shape , they must be broadcastable to a common shape (which becomes the shape of the output).

out : ndarray, 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.

where : array_like, optional

This condition is broadcast over the input. At locations where the condition is True, the :None:None:`out` array will be set to the ufunc result. Elsewhere, the :None:None:`out` array will retain its original value. Note that if an uninitialized :None:None:`out` array is created via the default out=None , locations within it where the condition is False will remain uninitialized.

**kwargs :

For other keyword-only arguments, see the ufunc docs <ufuncs.kwargs> .

Returns

result : ndarray

Logarithm of exp(x1) + exp(x2) . This is a scalar if both :None:None:`x1` and :None:None:`x2` are scalars.

This docstring was copied from numpy.logaddexp.

See Also

logaddexp2

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

Examples

This example is valid syntax, but we were not able to check execution
>>> prob1 = np.log(1e-50)  # doctest: +SKIP
... prob2 = np.log(2.5e-50) # doctest: +SKIP
... prob12 = np.logaddexp(prob1, prob2) # doctest: +SKIP
... prob12 # doctest: +SKIP -113.87649168120691
This example is valid syntax, but we were not able to check execution
>>> np.exp(prob12)  # doctest: +SKIP
3.5000000000000057e-50
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.ufunc.logaddexp2

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