parameters: (samples, high=2*pi, low=0, axis=None)
return_statement: return ((high - low)/2.0/pi)**2 * 2 * log(1/R)
docstring: Compute the circular variance for samples assumed to be in a range
  
      Parameters
      ----------
      samples : array_like
          Input array.
      low : float or int, optional
          Low boundary for circular variance range.  Default is 0.
      high : float or int, optional
          High boundary for circular variance range.  Default is ``2*pi``.
      axis : int, optional
          Axis along which variances are computed.  The default is to compute
          the variance of the flattened array.
  
      Returns
      -------
      circvar : float
          Circular variance.
  
      Notes
      -----
      This uses a definition of circular variance that in the limit of small
      angles returns a number close to the 'linear' variance.
  
      Examples
      --------
      >>> from scipy.stats import circvar
      >>> circvar([0, 2*np.pi/3, 5*np.pi/3])
      2.19722457734
docstring_summary: Compute the circular variance for samples assumed to be in a range
docstring_tokens: Compute the circular variance for samples assumed to be in a range
function: def circvar(samples, high=2*pi, low=0, axis=None):
      """
      Compute the circular variance for samples assumed to be in a range
  
      Parameters
      ----------
      samples : array_like
          Input array.
      low : float or int, optional
          Low boundary for circular variance range.  Default is 0.
      high : float or int, optional
          High boundary for circular variance range.  Default is ``2*pi``.
      axis : int, optional
          Axis along which variances are computed.  The default is to compute
          the variance of the flattened array.
  
      Returns
      -------
      circvar : float
          Circular variance.
  
      Notes
      -----
      This uses a definition of circular variance that in the limit of small
      angles returns a number close to the 'linear' variance.
  
      Examples
      --------
      >>> from scipy.stats import circvar
      >>> circvar([0, 2*np.pi/3, 5*np.pi/3])
      2.19722457734
  
      """
      samples, ang = _circfuncs_common(samples, high, low)
      S = sin(ang).mean(axis=axis)
      C = cos(ang).mean(axis=axis)
      R = hypot(S, C)
      return ((high - low)/2.0/pi)**2 * 2 * log(1/R)
function_tokens: def circvar ( samples , high = 2 * pi , low = 0 , axis = None ) : samples , ang = _circfuncs_common ( samples , high , low ) S = sin ( ang ) . mean ( axis = axis ) C = cos ( ang ) . mean ( axis = axis ) R = hypot ( S , C ) return ( ( high - low ) / 2.0 / pi ) ** 2 * 2 * log ( 1 / R )