numpy.logaddexp — NumPy v1.11 Manual (original) (raw)
numpy.logaddexp(x1, _x2_[, _out_]) = <ufunc 'logaddexp'>¶
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.
| Parameters: | x1, x2 : array_like Input values. |
|---|---|
| Returns: | result : ndarray Logarithm of exp(x1) + exp(x2). |
See also
Logarithm of the sum of exponentiations of inputs in base 2.
Notes
New in version 1.3.0.
Examples
prob1 = np.log(1e-50) prob2 = np.log(2.5e-50) prob12 = np.logaddexp(prob1, prob2) prob12 -113.87649168120691 np.exp(prob12) 3.5000000000000057e-50