[Pharo-dev] summary of "float & fraction equality bug"
nicolas.cellier.aka.nice at gmail.com
Fri Nov 10 17:05:34 EST 2017
2017-11-10 22:42 GMT+01:00 Florin Mateoc <fmateoc at gmail.com>:
> On 11/10/2017 4:18 PM, Nicolas Cellier wrote:
> 2017-11-10 20:58 GMT+01:00 Martin McClure <martin at hand2mouse.com>:
>> On 11/10/2017 11:33 AM, raffaello.giulietti at lifeware.ch wrote:
>>> Doing only Fraction->Float conversions in mixed mode won't preserve = as
>>> an equivalence relation and won't enable a consistent ordering with <=,
>>> which probably most Smalltalkers consider important and enjoyable
>> Good point. I agree that Float -> Fraction is the more desirable mode for
>> implicit conversion, since it can always be done without changing the value.
>>> Nicolas gave some convincing examples on why most
>>> programmers might want to rely on them.
>>> Also, as I mentioned, most Smalltalkers might prefer keeping away from
>>> the complex properties of Floats. Doing automatic, implicit
>>> Fraction->Float conversions behind the scenes only exacerbates the
>>> probability of encountering Floats and of having to deal with their
>>> weird and unfamiliar arithmetic.
>> One problem is that we make it easy to create Floats in source code
>> (0.1), and we print Floats in a nice decimal format but by default print
>> Fractions in their reduced fractional form. If we didn't do this,
>> Smalltalkers might not be working with Floats in the first place, and if
>> they did not have any Floats in their computation they would never run into
>> an implicit conversion to *or* from Float.
>> As it is, if we were to uniformly do Float -> Fraction conversion on
>> mixed-mode operations, we would get things like
>> (0.1 * (1/1)) printString -->
>> Not incredibly friendly.
> For those not practicing the litote: definitely a no go.
> At the risk of repeating myself, unique choice for all operations is a
> nice to have but not a goal per se.
> I mostly agree with Florin: having 0.1 representing a decimal rather than
> a Float might be a better path meeting more expectations.
> But thinking that it will magically eradicate the problems is a myth.
> Shall precision be limited or shall we use ScaledDecimals ?
> With limited precision, we'll be back to having several Fraction
> converting to same LimitedDecimal, so it won't solve anything wrt original
> I don't think people have problems with understanding limited precision.
> We do know that when we write 3.14.. we did not write Pi.
> As long as it does not contradict the intuition that we developed early on
> (and that's the problem with the binary representation of floats, not that
> it is limited)...
> With illimted precision we'll have the bad property that what we print
> does not re-interpret to the same ScaledDecimal (0.1s / 0.3s), but that's a
> The worse thing is that long chain of operations will tend to produce
> monster numerators denominators.
> And we will all have long chain when resizing a morph with proportional
> layout in scalable graphics.
> But I did not propose to drop floats, just to change the visible
> representation of literals: 0.1 would mean a ScaledDecimal literal and 0.1f
> would mean a float literal. The extra "f" would be a constant reminder that
> something special is going on (the dangers of interpreting the literal as
> an exact representation in base 10).
> We will then have to insert rounding operations manually for mitigating
> the problem, and somehow reinvent a more inconvenient Float...
> I don't think we would have to reinvent Float - this one would stay
> exactly the same (other than printing the extra f (or d)).
> But I agree that you raise an important point with precision/scale. We
> would indeed need to make ScaledDecimal more complicated.
> Because today 0.1s * 0.1s is printed as 0.0s1, even though 0.1s * 0.1s =
> (1/100) evaluates to true, which is nice.
> It's boring to allways play the role of Cassandra, but why do you think
> that Scheme and Lisp did not choose that path?
> Oh. come on, if Scheme and Lisp did it all already, why are we all here? :)
Not at all, here it what it means:
We must analyze why some decisions were taken, and analyze what condition
changed to enable different solutions.
Maths did not change so much, so it must be something else...
Fast CPU and huge memory could be a game changer, but how do the
LargeInteger operations scale?
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