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DISPATCHED_UFUNCS = {
"add",
"sub",
"mul",
"pow",
"mod",
"floordiv",
"truediv",
"divmod",
"eq",
"ne",
"lt",
"gt",
"le",
"ge",
"remainder",
"matmul",
"or",
"xor",
"and",
"neg",
"pos",
"abs",
}
UNARY_UFUNCS = {
"neg",
"pos",
"abs",
}
UFUNC_ALIASES = {
"subtract": "sub",
"multiply": "mul",
"floor_divide": "floordiv",
"true_divide": "truediv",
"power": "pow",
"remainder": "mod",
"divide": "truediv",
"equal": "eq",
"not_equal": "ne",
"less": "lt",
"less_equal": "le",
"greater": "gt",
"greater_equal": "ge",
"bitwise_or": "or",
"bitwise_and": "and",
"bitwise_xor": "xor",
"negative": "neg",
"absolute": "abs",
"positive": "pos",
}
# For op(., Array) -> Array.__r{op}__
REVERSED_NAMES = {
"lt": "__gt__",
"le": "__ge__",
"gt": "__lt__",
"ge": "__le__",
"eq": "__eq__",
"ne": "__ne__",
}
def maybe_dispatch_ufunc_to_dunder_op(
object self, object ufunc, str method, *inputs, **kwargs
):
"""
Dispatch a ufunc to the equivalent dunder method.
Parameters
----------
self : ArrayLike
The array whose dunder method we dispatch to
ufunc : Callable
A NumPy ufunc
method : {'reduce', 'accumulate', 'reduceat', 'outer', 'at', '__call__'}
inputs : ArrayLike
The input arrays.
kwargs : Any
The additional keyword arguments, e.g. ``out``.
Returns
-------
result : Any
The result of applying the ufunc
"""
# special has the ufuncs we dispatch to the dunder op on
op_name = ufunc.__name__
op_name = UFUNC_ALIASES.get(op_name, op_name)
def not_implemented(*args, **kwargs):
return NotImplemented
if kwargs or ufunc.nin > 2:
return NotImplemented
if method == "__call__" and op_name in DISPATCHED_UFUNCS:
if inputs[0] is self:
name = f"__{op_name}__"
meth = getattr(self, name, not_implemented)
if op_name in UNARY_UFUNCS:
assert len(inputs) == 1
return meth()
return meth(inputs[1])
elif inputs[1] is self:
name = REVERSED_NAMES.get(op_name, f"__r{op_name}__")
meth = getattr(self, name, not_implemented)
result = meth(inputs[0])
return result
else:
# should not be reached, but covering our bases
return NotImplemented
else:
return NotImplemented
|
