code: def circ_axial(angles, n):
      """Transforms n-axial data to a common scale.
  
      Parameters
      ----------
      angles : array
          Sample of angles in radians
      n : int
          Number of modes
  
      Returns
      -------
      angles : 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')
      >>> angles = df['Orientation'].to_numpy()
      >>> angles = circ_axial(np.deg2rad(angles), 2)
      """
      angles = np.asarray(angles)
      return np.remainder(angles * n, 2 * np.pi)
  
file_path: pingouin/pingouin/circular.py
imports: import numpy
  from scipy.stats import norm
  from .utils import remove_na
label_desc: Use image node_id 3 for calling a global function with example usage: circ_axial(angles, n) and returns: np