code: def _hist_bin_rice(x, range):
      """
      Rice histogram bin estimator.
  
      Another simple estimator with no normality assumption. It has better
      performance for large data than Sturges, but tends to overestimate
      the number of bins. The number of bins is proportional to the cube
      root of data size (asymptotically optimal). The estimate depends
      only on size of the data.
  
      Parameters
      ----------
      x : array_like
          Input data that is to be histogrammed, trimmed to range. May not
          be empty.
  
      Returns
      -------
      h : An estimate of the optimal bin width for the given data.
      """
      del range  # unused
      return _ptp(x) / (2.0 * x.size ** (1.0 / 3))
  
imports: import contextlib
  import functools
  import operator
  import warnings
  import numpy
  from numpy._core import overrides
label_desc: Use image node_id 4 for calling a global function with example usage: _hist_bin_rice(x, range) and returns: unknown