code: def _circular_standard_deviation(
      samples, high=2 * np.pi, low=0, skipna=False, axis=None
  ):
      ang = _circfunc(samples, high, low, skipna)
      s_s = np.sin(ang).mean(axis=axis)
      c_c = np.cos(ang).mean(axis=axis)
      r_r = np.hypot(s_s, c_c)
      return ((high - low) / 2.0 / np.pi) * np.sqrt(-2 * np.log(r_r))
  
imports: import warnings
  from collections.abc import Sequence
  from copy import copy
  from copy import deepcopy
  import numpy
  import pandas
  from scipy.fftpack import next_fast_len
  from scipy.interpolate import CubicSpline
  from scipy.stats.mstats import mquantiles
  from xarray import apply_ufunc
  from ..None import _log
  from ..utils import conditional_jit, conditional_vect, conditional_dask
  from .density_utils import histogram
label_desc: Use image node_id 15 for calling a global function with example usage: _circular_standard_deviation(samples, high, low, skipna, axis) and returns: unknown