code: def circmean(samples, high=2 * pi, low=0, axis=None):
      """
      Compute the circular mean for samples in a range.
  
      Parameters
      ----------
      samples : array_like
          Input array.
      high : float or int, optional
          High boundary for circular mean range.  Default is ``2*pi``.
      low : float or int, optional
          Low boundary for circular mean range.  Default is 0.
      axis : int, optional
          Axis along which means are computed.  The default is to compute
          the mean of the flattened array.
  
      Returns
      -------
      circmean : float
          Circular mean.
  
      Examples
      --------
      >>> from scipy.stats import circmean
      >>> circmean([0.1, 2*np.pi+0.2, 6*np.pi+0.3])
      0.2
  
      >>> from scipy.stats import circmean
      >>> circmean([0.2, 1.4, 2.6], high = 1, low = 0)
      0.4
  
      """
      samples, ang = _circfuncs_common(samples, high, low)
      S = sin(ang).sum(axis=axis)
      C = cos(ang).sum(axis=axis)
      res = arctan2(S, C)
      mask = res < 0
      if mask.ndim > 0:
          res[mask] += 2 * pi
      elif mask:
          res += 2 * pi
      return res * (high - low) / 2.0 / pi + low
  
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 37 for calling a global function with example usage: circmean(samples, high, low, axis) and returns: unknown