[swift-dev] Rationalizing FloatingPoint conformance to Equatable
xiaodi.wu at gmail.com
Thu Oct 26 11:34:24 CDT 2017
On Thu, Oct 26, 2017 at 10:57 AM, Jonathan Hull <jhull at gbis.com> wrote:
> On Oct 26, 2017, at 8:19 AM, Xiaodi Wu <xiaodi.wu at gmail.com> wrote:
> On Thu, Oct 26, 2017 at 07:52 Jonathan Hull <jhull at gbis.com> wrote:
>> On Oct 25, 2017, at 11:22 PM, Xiaodi Wu <xiaodi.wu at gmail.com> wrote:
>> On Wed, Oct 25, 2017 at 11:46 PM, Jonathan Hull <jhull at gbis.com> wrote:
>>> As someone mentioned earlier, we are trying to square a circle here. We
>>> can’t have everything at once… we will have to prioritize. I feel like the
>>> precedent in Swift is to prioritize safety/correctness with an option
>>> ignore safety and regain speed.
>>> I think the 3 point solution I proposed is a good compromise that
>>> follows that precedent. It does mean that there is, by default, a small
>>> performance hit for floats in generic contexts, but in exchange for that,
>>> we get increased correctness and safety. This is the exact same tradeoff
>>> that Swift makes for optionals! Any speed lost can be regained by
>>> providing a specific override for FloatingPoint that uses ‘&==‘.
>> My point is not about performance. My point is that `Numeric.==` must
>> continue to have IEEE floating-point semantics for floating-point types and
>> integer semantics for integer types, or else existing uses of `Numeric.==`
>> will break without any way to fix them. The whole point of *having*
>> `Numeric` is to permit such generic algorithms to be written. But since
>> `Numeric.==` *is* `Equatable.==`, we have a large constraint on how the
>> semantics of `==` can be changed.
>> It would also conform to the new protocol and have it’s Equatable
>> conformance depreciated. Once we have conditional conformances, we can add
>> Equatable back conditionally. Also, while we are waiting for that, Numeric
>> can provide overrides of important methods when the conforming type is
>> Equatable or FloatingPoint.
>> For example, if someone wants to write a generic function that works both
>>> on Integer and FloatingPoint, then they would have to use the new protocol
>>> which would force them to correctly handle cases involving NaN.
>> What "new protocol" are you referring to, and what do you mean about
>> "correctly handling cases involving NaN"? The existing API of `Numeric`
>> makes it possible to write generic algorithms that accommodate both integer
>> and floating-point types--yes, even if the value is NaN. If you change the
>> definition of `==` or `<`, currently correct generic algorithms that use
>> `Numeric` will start to _incorrectly_ handle NaN.
>> #1 from my previous email (shown again here):
>> Currently, I think we should do 3 things:
>>>> 1) Create a new protocol with a partial equivalence relation with
>>>> signature of (T, T)->Bool? and automatically conform Equatable things to it
>>>> 2) Depreciate Float, etc’s… Equatable conformance with a warning that
>>>> it will eventually be removed (and conform Float, etc… to the partial
>>>> equivalence protocol)
>>>> 3) Provide an '&==‘ relation on Float, etc… (without a protocol) with
>>>> the native Float IEEE comparison
>> In this case, #2 would also apply to Numeric. You can think of the new
>> protocol as a failable version of Equatable, so in any case where it can’t
>> meet equatable’s rules, it returns nil.
> Again, Numeric makes possible the generic use of == with floating-point
> semantics for floating-point values and integer semantics for integer
> values; this design would not.
> Correct. I view this as a good thing, because another way of saying that
> is: “it makes possible cases where == sometimes conforms to the rules of
> Equatable and sometimes doesn’t." Under the solution I am advocating,
> Numeric would instead allow generic use of '==?’.
> I suppose an argument could be made that we should extend ‘&==‘ to Numeric
> from FloatingPoint, but then we would end up with the Rust situation you
> were talking about earlier…
This would break any `Numeric` algorithms that currently use `==`
correctly. There are useful guarantees that are common to integer `==` and
IEEE floating-point `==`; namely, they each model equivalence of their
respective types at roughly what IEEE calls "level 1" (as numbers, rather
than as their representation or encoding). Breaking that utterly
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