code: def circ_axial(alpha, n):
      
      alpha = np.array(alpha)
      return np.remainder(alpha * n, 2 * np.pi)
docs: Transforms n-axial data to a common scale.
  
      Parameters
      ----------
      alpha : array
          Sample of angles in radians
      n : int
          Number of modes
  
      Returns
      -------
      alpha : float
          Transformed angles
  
      Notes
      -----
      Tranform data with multiple modes (known as axial data) to a unimodal
      sample, for the purpose of certain analysis such as computation of a
      mean resultant vector (see Berens 2009).
  
      Examples
      --------
      Transform degrees to unimodal radians in the Berens 2009 neuro dataset.
  
      >>> import numpy as np
      >>> from pingouin import read_dataset
      >>> from pingouin.circular import circ_axial
      >>> df = read_dataset('circular')
      >>> alpha = df['Orientation'].values
      >>> alpha = circ_axial(np.deg2rad(alpha), 2)