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""" Mixin classes for custom array types that don't inherit from ndarray. """ from numpy._core import umath as um __all__ = ['NDArrayOperatorsMixin'] def _disables_array_ufunc(obj): """True when __array_ufunc__ is set to None.""" try: return obj.__array_ufunc__ is None except AttributeError: return False def _binary_method(ufunc, name): """Implement a forward binary method with a ufunc, e.g., __add__.""" def func(self, other): if _disables_array_ufunc(other): return NotImplemented return ufunc(self, other) func.__name__ = f'__{name}__' return func def _reflected_binary_method(ufunc, name): """Implement a reflected binary method with a ufunc, e.g., __radd__.""" def func(self, other): if _disables_array_ufunc(other): return NotImplemented return ufunc(other, self) func.__name__ = f'__r{name}__' return func def _inplace_binary_method(ufunc, name): """Implement an in-place binary method with a ufunc, e.g., __iadd__.""" def func(self, other): return ufunc(self, other, out=(self,)) func.__name__ = f'__i{name}__' return func def _numeric_methods(ufunc, name): """Implement forward, reflected and inplace binary methods with a ufunc.""" return (_binary_method(ufunc, name), _reflected_binary_method(ufunc, name), _inplace_binary_method(ufunc, name)) def _unary_method(ufunc, name): """Implement a unary special method with a ufunc.""" def func(self): return ufunc(self) func.__name__ = f'__{name}__' return func class NDArrayOperatorsMixin: """Mixin defining all operator special methods using __array_ufunc__. This class implements the special methods for almost all of Python's builtin operators defined in the `operator` module, including comparisons (``==``, ``>``, etc.) and arithmetic (``+``, ``*``, ``-``, etc.), by deferring to the ``__array_ufunc__`` method, which subclasses must implement. It is useful for writing classes that do not inherit from `numpy.ndarray`, but that should support arithmetic and numpy universal functions like arrays as described in :external+neps:doc:`nep-0013-ufunc-overrides`. As a trivial example, consider this implementation of an ``ArrayLike`` class that simply wraps a NumPy array and ensures that the result of any arithmetic operation is also an ``ArrayLike`` object: >>> import numbers >>> class ArrayLike(np.lib.mixins.NDArrayOperatorsMixin): ... def __init__(self, value): ... self.value = np.asarray(value) ... ... # One might also consider adding the built-in list type to this ... # list, to support operations like np.add(array_like, list) ... _HANDLED_TYPES = (np.ndarray, numbers.Number) ... ... def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): ... out = kwargs.get('out', ()) ... for x in inputs + out: ... # Only support operations with instances of ... # _HANDLED_TYPES. Use ArrayLike instead of type(self) ... # for isinstance to allow subclasses that don't ... # override __array_ufunc__ to handle ArrayLike objects. ... if not isinstance( ... x, self._HANDLED_TYPES + (ArrayLike,) ... ): ... return NotImplemented ... ... # Defer to the implementation of the ufunc ... # on unwrapped values. ... inputs = tuple(x.value if isinstance(x, ArrayLike) else x ... for x in inputs) ... if out: ... kwargs['out'] = tuple( ... x.value if isinstance(x, ArrayLike) else x ... for x in out) ... result = getattr(ufunc, method)(*inputs, **kwargs) ... ... if type(result) is tuple: ... # multiple return values ... return tuple(type(self)(x) for x in result) ... elif method == 'at': ... # no return value ... return None ... else: ... # one return value ... return type(self)(result) ... ... def __repr__(self): ... return '%s(%r)' % (type(self).__name__, self.value) In interactions between ``ArrayLike`` objects and numbers or numpy arrays, the result is always another ``ArrayLike``: >>> x = ArrayLike([1, 2, 3]) >>> x - 1 ArrayLike(array([0, 1, 2])) >>> 1 - x ArrayLike(array([ 0, -1, -2])) >>> np.arange(3) - x ArrayLike(array([-1, -1, -1])) >>> x - np.arange(3) ArrayLike(array([1, 1, 1])) Note that unlike ``numpy.ndarray``, ``ArrayLike`` does not allow operations with arbitrary, unrecognized types. This ensures that interactions with ArrayLike preserve a well-defined casting hierarchy. """ __slots__ = () # Like np.ndarray, this mixin class implements "Option 1" from the ufunc # overrides NEP. # comparisons don't have reflected and in-place versions __lt__ = _binary_method(um.less, 'lt') __le__ = _binary_method(um.less_equal, 'le') __eq__ = _binary_method(um.equal, 'eq') __ne__ = _binary_method(um.not_equal, 'ne') __gt__ = _binary_method(um.greater, 'gt') __ge__ = _binary_method(um.greater_equal, 'ge') # numeric methods __add__, __radd__, __iadd__ = _numeric_methods(um.add, 'add') __sub__, __rsub__, __isub__ = _numeric_methods(um.subtract, 'sub') __mul__, __rmul__, __imul__ = _numeric_methods(um.multiply, 'mul') __matmul__, __rmatmul__, __imatmul__ = _numeric_methods( um.matmul, 'matmul') __truediv__, __rtruediv__, __itruediv__ = _numeric_methods( um.true_divide, 'truediv') __floordiv__, __rfloordiv__, __ifloordiv__ = _numeric_methods( um.floor_divide, 'floordiv') __mod__, __rmod__, __imod__ = _numeric_methods(um.remainder, 'mod') __divmod__ = _binary_method(um.divmod, 'divmod') __rdivmod__ = _reflected_binary_method(um.divmod, 'divmod') # __idivmod__ does not exist # TODO: handle the optional third argument for __pow__? __pow__, __rpow__, __ipow__ = _numeric_methods(um.power, 'pow') __lshift__, __rlshift__, __ilshift__ = _numeric_methods( um.left_shift, 'lshift') __rshift__, __rrshift__, __irshift__ = _numeric_methods( um.right_shift, 'rshift') __and__, __rand__, __iand__ = _numeric_methods(um.bitwise_and, 'and') __xor__, __rxor__, __ixor__ = _numeric_methods(um.bitwise_xor, 'xor') __or__, __ror__, __ior__ = _numeric_methods(um.bitwise_or, 'or') # unary methods __neg__ = _unary_method(um.negative, 'neg') __pos__ = _unary_method(um.positive, 'pos') __abs__ = _unary_method(um.absolute, 'abs') __invert__ = _unary_method(um.invert, 'invert')