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# numpy.logaddexp2

`numpy.``logaddexp2`(x1, x2[, out])

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

  Calculates `log2(2**x1 + 2**x2)`. This function is useful in machine learning when the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the base-2 logarithm of the calculated probability can be used instead. This function allows adding probabilities stored in such a fashion.

  Parameters : | x1, x2 : array_like Input values. out : ndarray, optional Array to store results in.
  Returns : | result : ndarray Base-2 logarithm of `2**x1 + 2**x2`.

  See also

  `logaddexp`
    Logarithm of the sum of exponentiations of the inputs.

  Notes

  New in version 1.3.0.

  Examples

      >>> prob1 = np.log2(1e-50)
      >>> prob2 = np.log2(2.5e-50)
      >>> prob12 = np.logaddexp2(prob1, prob2)
      >>> prob1, prob2, prob12
      (-166.09640474436813, -164.77447664948076, -164.28904982231052)
      >>> 2**prob12
      3.4999999999999914e-50

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