Hello, I'm thinking differently about this issue. For me, the problem is not "how much is the error on floating calculation" because we know that a rounding error is a difference of 1 on the last digit, I mean 1.01 $ instead of 1.00
I think the question is how often this small error results in a rounding error. let's take this example which a three digit precision : python : 1.0-(1.0-0.001/2)+0.1 =0.100 while the correct answer 0.101 funny thing is that this 1.0+0.1-(1.0-0.001/2) = 0.101 results in the correct correct answer. You can make this calculation 1000 times, you'll get 1000 rounding errors, ie 10$ ;-) If a customer never uses 10% value, which is known as toxic for binary computing, then he may hope get everything correct ? Thank you for your comments. regards -- View this message in context: http://openerp-expert-framework.71550.n3.nabble.com/float-errors-propagating-to-10-2-in-OpenERP-v5-tp1175425p1202230.html Sent from the openerp-expert-framework mailing list archive at Nabble.com. _______________________________________________ Mailing list: https://launchpad.net/~openerp-expert-framework Post to : [email protected] Unsubscribe : https://launchpad.net/~openerp-expert-framework More help : https://help.launchpad.net/ListHelp
