new_contents: 
  
  import ot
  import numpy as np
  
  # import pytest
  
  
  def test_plot1D_mat():
  
      n = 100  # nb bins
  
      # bin positions
      x = np.arange(n, dtype=np.float64)
  
      # Gaussian distributions
      a = ot.datasets.get_1D_gauss(n, m=20, s=5)  # m= mean, s= std
      b = ot.datasets.get_1D_gauss(n, m=60, s=10)
  
      # loss matrix
      M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
      M /= M.max()
  
      ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
  
  
  def test_plot2D_samples_mat():
  
      n = 50  # nb samples
  
      mu_s = np.array([0, 0])
      cov_s = np.array([[1, 0], [0, 1]])
  
      mu_t = np.array([4, 4])
      cov_t = np.array([[1, -.8], [-.8, 1]])
  
      xs = ot.datasets.get_2D_samples_gauss(n, mu_s, cov_s)
      xt = ot.datasets.get_2D_samples_gauss(n, mu_t, cov_t)
  
      G = 1.0 * (np.random.rand(n, n) < 0.01)
  
      ot.plot.plot2D_samples_mat(xs, xt, G, thr=1e-5)
  
subject: add test plot