openerp-expert-framework team mailing list archive

["Borja López Soilán (Pexego)" <borjals@xxxxxxxxx>]

Raphaël Valyi wrote:
> Well, of course, I made a small mistake in my mail, I meant 14 000 
> moves is ~10^5, meaning we expect a 10^-17* 10^5=10^12 error at first 
> when summing moves while we already get a 10^-9 error. The question 
> why is still open.
> And off course, how that 10^⁻9 propagates to 10^-2 in the chart of 
> accounts is still open and should be fixed...
I would say 10^⁻9  is the error to be expected with 14000 moves, not 10^12.
An easy example: summing 14000 times the same float vs using multiplying 
it by 14000 (mathematically they should be the same).

$ cat tmp.py
diffs=[]
for j in range(0, 10000):
   s=0.0
   k=j/14000.0
   for i in range(0, 14000):
       s+=k
   diffs.append(abs(k*14000.0-s))
  
print "max: ", max(diffs)
print "min: ", min(diffs)
print "avg: ", sum(diffs)/len(diffs)

$ python tmp.py
max:  3.71619535144e-09
min:  0.0
*avg:  8.2300255102e-10*

As you can see the average rounding error for 10000 floats is almost 10^-9 !

Anyway, I don't understand how Sharoon is getting a 10^-2 rounding error 
on __calculate :(


By the way, Decimal is a lot slower of what I thought. The same test as 
above, but done with Decimal gives a maximum 0.0 rounding error but 
takes about 100 times more time than using floats (53.28 vs 0.43 seconds 
for 100 'j' loops), wow, that's bad.

--
Borja López Soilán
borjals@xxxxxxxxx

Pexego Sistemas Informáticos S.L.
Avenida de Magoi 66 - 27002 Lugo (España)
Tel./Fax 982801517
http://www.pexego.es 


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