code: def _bw_silverman(
      x, x_std=None, **kwargs
  ):  # pylint: disable=unused-argument
      """Silverman's Rule."""
      if x_std is None:
          x_std = np.std(x)
      q75, q25 = np.percentile(x, [75, 25])
      x_iqr = q75 - q25
      a = min(x_std, x_iqr / 1.34)
      bw = 0.9 * a * len(x) ** (-0.2)
      return bw
  
imports: import warnings
  import numpy
  from scipy.fftpack import fft
  from scipy.optimize import brentq
  from scipy.signal import convolve, convolve2d, gaussian
  from scipy.sparse import coo_matrix
  from scipy.special import ive
  from ..utils import _cov, _dot, _stack, conditional_jit
label_desc: Use image node_id 2 for calling a global function with example usage: _bw_silverman(x, x_std) and returns: bw