code: def _bin_medians(n_bins, scale=1.0):
      """Compute median value corresponding to SAX symbols for a given Gaussian
      scale.
  
      Examples
      --------
      >>> _bin_medians(n_bins=2)
      array([-0.67448975,  0.67448975])
      """
      return norm.ppf(
          [float(a) / (2 * n_bins) for a in range(1, 2 * n_bins, 2)],
          scale=scale,
      )
  
imports: import numpy
  from scipy.stats import norm
  from sklearn.base import TransformerMixin
  from sklearn.utils.validation import check_is_fitted, check_array
  from tslearn.bases import BaseModelPackage, TimeSeriesBaseEstimator
  from tslearn.metrics.cysax import cydist_sax, cyslopes, cydist_1d_sax, inv_transform_1d_sax, inv_transform_sax, inv_transform_paa
  from tslearn.utils import ts_size, check_dims
label_desc: Use image node_id 3 for calling a global function with example usage: _bin_medians(n_bins, scale) and returns: norm