code: def unique_bvals(bvals, bmag=None, rbvals=False):
      """This function gives the unique rounded b-values of the data
  
      Parameters
      ----------
      bvals : ndarray
          Array containing the b-values
  
      bmag : int
          The order of magnitude that the bvalues have to differ to be
          considered an unique b-value. B-values are also rounded up to
          this order of magnitude. Default: derive this value from the
          maximal b-value provided: $bmag=log_{10}(max(bvals)) - 1$.
  
      rbvals : bool, optional
          If True function also returns all individual rounded b-values.
          Default: False
  
      Returns
      -------
      ubvals : ndarray
          Array containing the rounded unique b-values
      """
      b = round_bvals(bvals, bmag)
      if rbvals:
          return np.unique(b), b
  
      return np.unique(b)
  
imports: import logging
  from warnings import warn
  import numpy
  from scipy.linalg import inv, polar
  from dipy.io import gradients
  from dipy.core.onetime import auto_attr
  from dipy.core.geometry import vector_norm, vec2vec_rotmat
  from dipy.core.sphere import disperse_charges, HemiSphere
  from dipy.utils.deprecator import deprecate_with_version
label_desc: Use image node_id 1 for calling a global function with example usage: unique_bvals(bvals, bmag, rbvals) and returns: np, np,  b