code: 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)
  
imports: from __future__ import division, print_function, absolute_import
  import math
  import warnings
  from collections import namedtuple
  import numpy
  from numpy import isscalar, r_, log, around, unique, asarray, zeros, arange, sort, amin, amax, any, atleast_1d, sqrt, ceil, floor, array, compress, pi, exp, ravel, count_nonzero, sin, cos, arctan2, hypot
  from scipy._lib.six import string_types
  from scipy import optimize
  from scipy import special
  from .None import statlib
  from .None import stats
  from .stats import find_repeats, _contains_nan
  from .contingency import chi2_contingency
  from .None import distributions
  from ._distn_infrastructure import rv_generic
label_desc: Use image node_id 38 for calling a global function with example usage: circvar(samples, high, low, axis) and returns: unknown