Hi, i dont agree with this pov. for example consider this mixed-mode calc: aFraction ln + aNumber. Fraction>>#ln returns a float and i suppose you dont want to change that eg by returning a quasi-NaN like "ResultNonRepresentableInTheSetOfFractionsError". if you suppress (2) and aNumber would be a Float youd get a float as result. if aNumber would be a fraction youd get a fraction as result and perhaps somebody could expect the result to be precise, but actually it can be less precise than in the first case (two roundings instead of one). this change just opens a can of worms. werner On 11/12/2017 08:15 AM, Tudor Girba wrote:
Hi,
Indeed, I agree with this point of view.
Can we distill a concrete path to action from this?
Cheers, Doru
On Nov 11, 2017, at 11:58 AM, raffaello.giulietti@lifeware.ch wrote:
On 2017-11-10 22:18, Nicolas Cellier wrote:
2017-11-10 20:58 GMT+01:00 Martin McClure <martin@hand2mouse.com <mailto:martin@hand2mouse.com>>:
On 11/10/2017 11:33 AM, raffaello.giulietti@lifeware.ch <mailto:raffaello.giulietti@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 properties.
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 --> '3602879701896397/36028797018963968'
Not incredibly friendly.
For those not practicing the litote: definitely a no go.
Regards, -Martin
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 problem. 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 detail. 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. We will then have to insert rounding operations manually for mitigating the problem, and somehow reinvent a more inconvenient Float... It's boring to allways play the role of Cassandra, but why do you think that Scheme and Lisp did not choose that path?
I don't know why Lisper got this way. They justify the conversion choice for comparison (equivalence of = and total ordering of <=) but for the arithmetic operations there does not seem to be a clearly stated rationale.
Are they happy with their choice? I haven't the foggiest idea.
Don't get me wrong: I understand the Fraction->Float choice for the sake of more speed.
But this increase in speed is not functionally transparent: it is not like an increase in the clock rate of a CPU, it's not like a better performing division algorithm, a faster implementation of sorting or a JIT compiler.
This increase in speed, rather, comes at the cost of a shift in functionality and cognitive load, because even + or 0.1 have not their conventional semantics. It's not that Floats are wrong by themselves, it's that their operations seem weird at first and at odd with the familiar behavior.
Again, I'm not addressing the experts in floating point computation here: they know how to deal with it. Thus, I expect that the developers of numerically intensive libraries or packages, like 2D or 3D graphics, are fully aware of the trade-offs and are in a position to make an explicit choice: either monster denominators in fractions or more care with floats, but always in control.
Here, I'm targeting the John Doe Smalltalker which usually uses well-crafted, well-performing libraries and probably only performs a few thousand mixed Fraction/Float computations on his own, and then speed trade-offs do not matter. He is better served with implicit, automatic Float->Fraction conversions in both comparisons and operations.
For him, less cognitive load and less surprises are probably an added value. -- www.tudorgirba.com www.feenk.com
"Every now and then stop and ask yourself if the war you're fighting is the right one."