diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/mixins.py | 101 |
1 files changed, 52 insertions, 49 deletions
diff --git a/numpy/lib/mixins.py b/numpy/lib/mixins.py index 08306cb02..52ad45b68 100644 --- a/numpy/lib/mixins.py +++ b/numpy/lib/mixins.py @@ -78,55 +78,58 @@ class NDArrayOperatorsMixin(object): class that simply wraps a NumPy array and ensures that the result of any arithmetic operation is also an ``ArrayLike`` object:: - >>> import numpy.lib - >>> 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])) + 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 |