text: import numpy as np
  import matplotlib as mpl
  import matplotlib.pyplot as plt
  from matplotlib.cm import get_cmap
  from matplotlib.colors import to_hex
  import periodispline.splines.green.univariate as green
  from periodispline.splines.ndsplines import UnivariateSpline
  
  # Set colors in plots
  cmap = get_cmap('tab10')
  mpl.rcParams['axes.prop_cycle'] = mpl.cycler(color=[to_hex(c) for c in cmap.colors])
  
  # Setup
  period = 2 * np.pi
  nogibbs = True
  nogibbs_method = 'fejer'
  resolution = 1024
  number_of_periods = 2
  
  order = [1, 2, 3, 4]
  epsilon = 0.5
  alpha = 1 / np.sqrt(epsilon)
  fig = plt.figure()
  
  for i, ord in enumerate(order):
      sobolev_spline = green.GreenSobolev(exponent=ord, period=period, alpha=alpha, nogibbs=nogibbs,
                                          nogibbs_method=nogibbs_method)
      matern_spline = green.GreenMatern(scale=epsilon, order=ord, period=period)
      plt.subplot(2, 2, i + 1)
      sobolev_spline.plot(nb_of_periods=number_of_periods, resolution=resolution, color=0, linewidth=1.5)
      matern_spline.plot(nb_of_periods=number_of_periods, resolution=resolution, color=1, linewidth=1.5)
      plt.title(f'$\\gamma={ord}$')
  
  fig.legend(['Sobolev', 'Matern'], loc='center right')
  plt.suptitle(f'Sobolev vs. Matern splines ($\\epsilon={epsilon}$, $\\alpha={np.round(alpha,2)}$).')
  