# log function

(Shortest import: `from brian2 import log)`

brian2.units.unitsafefunctions.log(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature])

  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.

    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 `out` array will be set to the ufunc result. Elsewhere, the `out` array will retain its original value. Note that if an uninitialized `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.

  Returns:

    y : ndarray

    > The natural logarithm of `x`, element-wise. This is a scalar if `x` is a scalar.

  See also

  `log10()`, `log2`, `log1p()`, `emath.log`

  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.

  In the cases where the input has a negative real part and a very small negative complex part (approaching 0), the result is so close to `-pi` that it evaluates to exactly `-pi`.

  References

  [R1]

  M. Abramowitz and I.A. Stegun, “Handbook of Mathematical Functions”, 10th printing, 1964, pp. 67. https://personal.math.ubc.ca/~cbm/aands/page_67.htm

  [R2]

  Wikipedia, “Logarithm”. https://en.wikipedia.org/wiki/Logarithm

  Examples

      >>> import numpy as np
      >>> np.log([1, np.e, np.e**2, 0])
      array([  0.,   1.,   2., -inf])