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# numpy.sign

`numpy.``sign`(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'sign'>

  Returns an element-wise indication of the sign of a number.

  The `sign` function returns `-1 if x < 0, 0 if x==0, 1 if x > 0`. nan is returned for nan inputs.

  For complex inputs, the `sign` function returns `sign(x.real) + 0j if x.real != 0 else sign(x.imag) + 0j`.

  complex(nan, 0) is returned for complex nan inputs.

  Parameters: | x : array_like Input values. 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 Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.
  Returns: | y : ndarray The sign of x.

  Notes

  There is more than one definition of sign in common use for complex numbers. The definition used here is equivalent to which is different from a common alternative, .

  Examples

      >>> np.sign([-5., 4.5])
      array([-1.,  1.])
      >>> np.sign(0)
      0
      >>> np.sign(5-2j)
      (1+0j)