Na}{

File Content: `mixins.py`

"""Mixin classes for custom array types that don't inherit from ndarray."""
from __future__ import division, absolute_import, print_function

import sys

from numpy.core import umath as um

# Nothing should be exposed in the top-level NumPy module.
__all__ = []


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__ = '__{}__'.format(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__ = '__r{}__'.format(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__ = '__i{}__'.format(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__ = '__{}__'.format(name)
    return func


class NDArrayOperatorsMixin(object):
    """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.

    This class does not yet implement the special operators corresponding
    to ``matmul`` (``@``), because ``np.matmul`` is not yet a NumPy ufunc.

    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 :ref:`A Mechanism for Overriding Ufuncs
    <neps.ufunc-overrides>`.

    As an 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::

        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.
    """
    # 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')
    if sys.version_info.major < 3:
        # Python 3 uses only __truediv__ and __floordiv__
        __div__, __rdiv__, __idiv__ = _numeric_methods(um.divide, 'div')
    __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')

Name	Size	Permission
__pycache__	---	0755
tests	---	0755
__init__.py	1312 bytes	0644
_datasource.py	21268 bytes	0644
_iotools.py	31965 bytes	0644
_version.py	4867 bytes	0644
arraypad.py	51524 bytes	0644
arraysetops.py	20211 bytes	0644
arrayterator.py	7191 bytes	0644
financial.py	23890 bytes	0644
format.py	28679 bytes	0644
function_base.py	169604 bytes	0644
index_tricks.py	26673 bytes	0644
info.py	6616 bytes	0644
mixins.py	7284 bytes	0644
nanfunctions.py	50827 bytes	0644
npyio.py	75585 bytes	0644
polynomial.py	38749 bytes	0644
recfunctions.py	35934 bytes	0644
scimath.py	14085 bytes	0644
setup.py	379 bytes	0644
shape_base.py	27616 bytes	0644
stride_tricks.py	8785 bytes	0644
twodim_base.py	25584 bytes	0644
type_check.py	16418 bytes	0644
ufunclike.py	5738 bytes	0644
user_array.py	7817 bytes	0644
utils.py	36327 bytes	0644

File Content: mixins.py

File Content: `mixins.py`