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1""" 

2Dict of expired attributes that are discontinued since 2.0 release. 

3Each item is associated with a migration note. 

4""" 

5 

6__expired_attributes__ = { 

7 "geterrobj": "Use the np.errstate context manager instead.", 

8 "seterrobj": "Use the np.errstate context manager instead.", 

9 "cast": "Use `np.asarray(arr, dtype=dtype)` instead.", 

10 "source": "Use `inspect.getsource` instead.", 

11 "lookfor": "Search NumPy's documentation directly.", 

12 "who": "Use an IDE variable explorer or `locals()` instead.", 

13 "fastCopyAndTranspose": "Use `arr.T.copy()` instead.", 

14 "set_numeric_ops": 

15 "For the general case, use `PyUFunc_ReplaceLoopBySignature`. " 

16 "For ndarray subclasses, define the ``__array_ufunc__`` method " 

17 "and override the relevant ufunc.", 

18 "NINF": "Use `-np.inf` instead.", 

19 "PINF": "Use `np.inf` instead.", 

20 "NZERO": "Use `-0.0` instead.", 

21 "PZERO": "Use `0.0` instead.", 

22 "add_newdoc": 

23 "It's still available as `np.lib.add_newdoc`.", 

24 "add_docstring": 

25 "It's still available as `np.lib.add_docstring`.", 

26 "add_newdoc_ufunc": 

27 "It's an internal function and doesn't have a replacement.", 

28 "safe_eval": "Use `ast.literal_eval` instead.", 

29 "float_": "Use `np.float64` instead.", 

30 "complex_": "Use `np.complex128` instead.", 

31 "longfloat": "Use `np.longdouble` instead.", 

32 "singlecomplex": "Use `np.complex64` instead.", 

33 "cfloat": "Use `np.complex128` instead.", 

34 "longcomplex": "Use `np.clongdouble` instead.", 

35 "clongfloat": "Use `np.clongdouble` instead.", 

36 "string_": "Use `np.bytes_` instead.", 

37 "unicode_": "Use `np.str_` instead.", 

38 "Inf": "Use `np.inf` instead.", 

39 "Infinity": "Use `np.inf` instead.", 

40 "NaN": "Use `np.nan` instead.", 

41 "infty": "Use `np.inf` instead.", 

42 "issctype": "Use `issubclass(rep, np.generic)` instead.", 

43 "maximum_sctype": 

44 "Use a specific dtype instead. You should avoid relying " 

45 "on any implicit mechanism and select the largest dtype of " 

46 "a kind explicitly in the code.", 

47 "obj2sctype": "Use `np.dtype(obj).type` instead.", 

48 "sctype2char": "Use `np.dtype(obj).char` instead.", 

49 "sctypes": "Access dtypes explicitly instead.", 

50 "issubsctype": "Use `np.issubdtype` instead.", 

51 "set_string_function": 

52 "Use `np.set_printoptions` instead with a formatter for " 

53 "custom printing of NumPy objects.", 

54 "asfarray": "Use `np.asarray` with a proper dtype instead.", 

55 "issubclass_": "Use `issubclass` builtin instead.", 

56 "tracemalloc_domain": "It's now available from `np.lib`.", 

57 "mat": "Use `np.asmatrix` instead.", 

58 "recfromcsv": "Use `np.genfromtxt` with comma delimiter instead.", 

59 "recfromtxt": "Use `np.genfromtxt` instead.", 

60 "deprecate": "Emit `DeprecationWarning` with `warnings.warn` directly, " 

61 "or use `typing.deprecated`.", 

62 "deprecate_with_doc": "Emit `DeprecationWarning` with `warnings.warn` " 

63 "directly, or use `typing.deprecated`.", 

64 "disp": "Use your own printing function instead.", 

65 "find_common_type": 

66 "Use `numpy.promote_types` or `numpy.result_type` instead. " 

67 "To achieve semantics for the `scalar_types` argument, use " 

68 "`numpy.result_type` and pass the Python values `0`, `0.0`, or `0j`.", 

69 "round_": "Use `np.round` instead.", 

70 "get_array_wrap": "", 

71 "DataSource": "It's still available as `np.lib.npyio.DataSource`.", 

72 "nbytes": "Use `np.dtype(<dtype>).itemsize` instead.", 

73 "byte_bounds": "Now it's available under `np.lib.array_utils.byte_bounds`", 

74 "compare_chararrays": 

75 "It's still available as `np.char.compare_chararrays`.", 

76 "format_parser": "It's still available as `np.rec.format_parser`.", 

77 "alltrue": "Use `np.all` instead.", 

78 "sometrue": "Use `np.any` instead.", 

79}