code: def dist0(n, method='lin_square'):
      
      res = 0
      if method == 'lin_square':
          x = np.arange(n, dtype=np.float64).reshape((n, 1))
          res = dist(x, x)
      return res
docs: Compute standard cost matrices of size (n,n) for OT problems
  
      Parameters
      ----------
  
      n : int
          size of the cost matrix
      method : str, optional
          Type of loss matrix chosen from:
  
          * 'lin_square' : linear sampling between 0 and n-1, quadratic loss
  
  
      Returns
      -------
  
      M : np.array (n1,n2)
          distance matrix computed with given metric