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# numpy.arcsin

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

  Inverse sine, element-wise.

  Parameters: | x : array_like y-coordinate on the unit circle. 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: | angle : ndarray The inverse sine of each element in x, in radians and in the closed interval `[-pi/2, pi/2]`. If x is a scalar, a scalar is returned, otherwise an array.

  See also

  `sin`, `cos`, `arccos`, `tan`, `arctan`, `arctan2`, `emath.arcsin`

  Notes

  `arcsin` is a multivalued function: for each x there are infinitely many numbers z such that . The convention is to return the angle z whose real part lies in [-pi/2, pi/2].

  For real-valued input data types, arcsin 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, `arcsin` is a complex analytic function that has, by convention, the branch cuts [-inf, -1] and [1, inf] and is continuous from above on the former and from below on the latter.

  The inverse sine is also known as asin or sin^{-1}.

  References

  Abramowitz, M. and Stegun, I. A., Handbook of Mathematical Functions, 10th printing, New York: Dover, 1964, pp. 79ff. http://www.math.sfu.ca/~cbm/aands/

  Examples

      >>> np.arcsin(1)     # pi/2
      1.5707963267948966
      >>> np.arcsin(-1)    # -pi/2
      -1.5707963267948966
      >>> np.arcsin(0)
      0.0