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# numpy.log

`numpy.``log`(x[, out])

  Natural logarithm, element-wise.

  The natural logarithm log is the inverse of the exponential function, so that log(exp(x)) = x. The natural logarithm is logarithm in base e.

  Parameters: | x : array_like Input value.
  Returns: | y : ndarray The natural logarithm of x, element-wise.

  See also

  `log10`, `log2`, `log1p`

  Notes

  Logarithm is a multivalued function: for each x there is an infinite number of z such that exp(z) = x. The convention is to return the z whose imaginary part lies in [-pi, pi].

  For real-valued input data types, log always returns real output. For each value that cannot be expressed as a real number or infinity, it yields `nan` and sets the invalid floating point error flag.

  For complex-valued input, log is a complex analytical function that has a branch cut [-inf, 0] and is continuous from above on it. log handles the floating-point negative zero as an infinitesimal negative number, conforming to the C99 standard.

  References

  [44] | M. Abramowitz and I.A. Stegun, “Handbook of Mathematical Functions”, 10th printing, 1964, pp. 67. http://www.math.sfu.ca/~cbm/aands/

  [45] | Wikipedia, “Logarithm”. http://en.wikipedia.org/wiki/Logarithm

  Examples

      >>> np.log([1, np.e, np.e**2, 0])
      array([  0.,   1.,   2., -Inf])

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