parameters: (ar1, ar2, assume_unique=False)
docstring: Find the set difference of two arrays.
  
      Return the sorted, unique values in `ar1` that are not in `ar2`.
  
      Parameters
      ----------
      ar1 : array_like
          Input array.
      ar2 : array_like
          Input comparison array.
      assume_unique : bool
          If True, the input arrays are both assumed to be unique, which
          can speed up the calculation.  Default is False.
  
      Returns
      -------
      difference : ndarray
          Sorted 1D array of values in `ar1` that are not in `ar2`.
  
      See Also
      --------
      numpy.lib.arraysetops : Module with a number of other functions for
                              performing set operations on arrays.
  
      Examples
      --------
      >>> a = np.array([1, 2, 3, 2, 4, 1])
      >>> b = np.array([3, 4, 5, 6])
      >>> np.setdiff1d(a, b)
      array([1, 2])
docstring_summary: Find the set difference of two arrays.
docstring_tokens: Find the set difference of two arrays .
function: def setdiff1d(ar1, ar2, assume_unique=False):
      """
      Find the set difference of two arrays.
  
      Return the sorted, unique values in `ar1` that are not in `ar2`.
  
      Parameters
      ----------
      ar1 : array_like
          Input array.
      ar2 : array_like
          Input comparison array.
      assume_unique : bool
          If True, the input arrays are both assumed to be unique, which
          can speed up the calculation.  Default is False.
  
      Returns
      -------
      difference : ndarray
          Sorted 1D array of values in `ar1` that are not in `ar2`.
  
      See Also
      --------
      numpy.lib.arraysetops : Module with a number of other functions for
                              performing set operations on arrays.
  
      Examples
      --------
      >>> a = np.array([1, 2, 3, 2, 4, 1])
      >>> b = np.array([3, 4, 5, 6])
      >>> np.setdiff1d(a, b)
      array([1, 2])
  
      """
      if not assume_unique:
          ar1 = unique(ar1)
          ar2 = unique(ar2)
      aux = in1d(ar1, ar2, assume_unique=True)
      if aux.size == 0:
          return aux
      else:
          return np.asarray(ar1)[aux == 0]
function_tokens: def setdiff1d ( ar1 , ar2 , assume_unique = False ) : if not assume_unique : ar1 = unique ( ar1 ) ar2 = unique ( ar2 ) aux = in1d ( ar1 , ar2 , assume_unique = True ) if aux . size == 0 : return aux else : return np . asarray ( ar1 ) [ aux == 0 ]