code: def Realization(M, C, *args, **kwargs):
      
      if isinstance(C, BasisCovariance):
          return BasisRealization(M, C, *args, **kwargs)
      else:
          return StandardRealization(M, C, *args, **kwargs)
docs: f = Realization(M, C[, init_mesh, init_vals, check_repeats = True, regularize = True])
  
  
      Returns a realization from a Gaussian process.
  
  
      :Arguments:
  
          -   `M`: A Gaussian process mean function.
  
          -   `C`: A Covariance instance.
  
          -   `init_mesh`: An optional ndarray giving mesh at which f's initial value will be specified.
  
          -   `init_vals`: An ndarray giving the value of f over init_mesh.
  
          -   `regularize`: If init_mesh is not shaped as (n, ndim), where ndim is the dimension of
              the space, regularize should be True.
  
          -   `check_repeats: Determines whether calls to the GP realization will be checked against
              previous calls before evaluation.
  
      :SeeAlso: Mean, Covariance, BasisCovariance, observe, GP