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# numpy.sin

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

  Trigonometric sine, element-wise.

  Parameters: | x : array_like Angle, in radians ( rad equals 360 degrees). 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 : array_like The sine of each element of x.

  See also

  `arcsin`, `sinh`, `cos`

  Notes

  The sine is one of the fundamental functions of trigonometry (the mathematical study of triangles). Consider a circle of radius 1 centered on the origin. A ray comes in from the axis, makes an angle at the origin (measured counter-clockwise from that axis), and departs from the origin. The coordinate of the outgoing ray’s intersection with the unit circle is the sine of that angle. It ranges from -1 for to +1 for The function has zeroes where the angle is a multiple of . Sines of angles between and are negative. The numerous properties of the sine and related functions are included in any standard trigonometry text.

  Examples

  Print sine of one angle:

      >>> np.sin(np.pi/2.)
      1.0

  Print sines of an array of angles given in degrees:

      >>> np.sin(np.array((0., 30., 45., 60., 90.)) * np.pi / 180. )
      array([ 0.        ,  0.5       ,  0.70710678,  0.8660254 ,  1.        ])

  Plot the sine function:

      >>> import matplotlib.pylab as plt
      >>> x = np.linspace(-np.pi, np.pi, 201)
      >>> plt.plot(x, np.sin(x))
      >>> plt.xlabel('Angle [rad]')
      >>> plt.ylabel('sin(x)')
      >>> plt.axis('tight')
      >>> plt.show()

  (Source code, png, pdf)