OT: Re: is dwt alive?

["Jérôme M. Berger"]

aarti_pl wrote:
> W dniu 2010-07-11 23:39, aarti_pl pisze:
>> W dniu 2010-07-11 22:45, "Jérôme M. Berger" pisze:
>>> aarti_pl wrote:
>>>> I just would like to say that it is a great news! After discovering
>>>> that
>>>> for Java:
>>>> ----
>>>> double sum = 0.0;
>>>> for (int i = 0; i< 10; i++) sum += 0.1;
>>>> ----
>>>>
>>>> sum is equal: 0.9999999999999999
>>>>
>>>> I am looking at D with greater and greater sentiment :-) SWT and good
>>>> precision of calculations is necessary for my program...
>>>>
>>> Are you sure D is better? In C, you get 0.99999999999999988898 (not
>>> surprising since 0.1 cannot be represented exactly in base 2) and I
>>> would expect D to give the same result...
>>>
>>> Jerome
>>
>> On my computer it is exactly 1.0 (one).
>>
>> I know that there is explanation of why it is like that, as I found
>> article about it. I did not get deeper into it (good few pages of text)
>> as I believe there must better solution for programmers.
>>
>> My calculator shows proper results, spreadsheet shows proper results and
>> I think that calculations in my program for such a big fractions should
>> also give correct result.
>>
>> Just thought: maybe calculations in D are done internally in more than
>> 64bits and then casted into 64bits? It's a bit surprising for me that C
>> is also wrong about this sum...
>>
>> BR
>> Marcin Kuszczak
>> (aarti_pl)
> 
> Ok. You are right. D is not better in this case. It seems that it's just
> writeln cut number of decimal digits and printed 1.
> 
> Using:
> writefln("%.25f", sum);
> 
> we get:
> 0.99999999999999988897
> 
> Does it mean that the only way to get better precision is to use some
> custom classes like BigDecimal in Java?
> 
	AFAIK, yes. The problem is that 0.1 cannot be represented exactly
in base 2, no matter what precision you use. So your choices are
(from fastest to slowest):

- decide that the precision of a double is enough for your
application after all;

- use some arbitrary precision library like gmp to increase
precision, being aware that no matter how much you increase the
precision, the loop above will *never* give 1 (although it can come
close enough that conversion to a double will give 1)

- use some symbolic computations library. This will give you
absolute precision, but may be slow and won't always give you a
numerical result, i.e sqrt(2) is sqrt(2) and that's that, if you try
to get a numerical result out of it, then you wind up with the same
limitations as the other solutions.

		Jerome
-- 
mailto:jeberger at free.fr
http://jeberger.free.fr
Jabber: jeberger at jabber.fr

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