code: def _maamp_discretize(a, a_min, a_max, n_bit=8):  # pragma: no cover
      """
      Discretize each row of the input array
  
      This distribution is best suited for non-normalized time series data
  
      Parameters
      ----------
      a : numpy.ndarray
          The input array
  
      a_min : float
          The minimum value
  
      a_max : float
          The maximum value
  
      n_bit : int, default 8
          The number of bits to use for computing the bit size
  
      Returns
      -------
      out : numpy.ndarray
          Discretized array
      """
      return (
          np.round(
              ((a - a_min) / (a_max - a_min)) * ((2**n_bit) - 1.0)
          ).astype(np.int64)
          + 1
      )
  
file_path: stumpy/stumpy/maamp.py
imports: from functools import partial
  import numpy
  from numba import njit, prange
  from .None import config, core
label_desc: Use image node_id 3 for calling a global function with example usage: _maamp_discretize(a, a_min, a_max, n_bit) and returns: unknown