code: def _replace_zeros(arr, default_min_value):
      
      min_nonzero_value = min(default_min_value, np.min(arr[arr > 0]))
      closest_to_zero = np.nextafter(min_nonzero_value, min_nonzero_value - 1)
      arr[arr == 0] = closest_to_zero
      return arr
docs: Substitute 0s in the list with a near-zero value.
  
      Parameters
      -----------
      arr : numpy.array(float)
      default_min_value : float
          If the smallest non-zero element in `arr` is greater than the default,
          use the default instead.
  
      Returns
      -----------
      numpy.array(float)