Julia Evans
today I'm thinking about how floating point numbers can be treacherous -- what are specific examples of when they've betrayed you?
so far I have:
* money calculations where you need to get the exact correct answer
* twitter's tweet IDs are bigger than 2^53 and can't be represented as a Javascript number, you have to use a string
* implementing numerical algorithms (like matrix multiplication) (I've never done this)
pettter
@b0rk Overall needing to do comparisons within some epsilon rather than exact, whether that's in money calculations or otherwise. I.e. 0 + 0.1 + 0.2 != 0.3
pettter
@b0rk It could be a bunch of things, like if you're making a game and have various bonuses and drawbacks, and want to check if you're back to zero for some reason, and then instead of checking "am I within epsilon of 0" you check "am I exactly zero", because "all" you're doing is +- some percentage so intuitively it _should_ work.
Julia Evans
@pettter do you have any other examples than money calculations? I'm struggling to come up with specific examples
pettter
@b0rk Physics calculations in games can have similar problems, e.g. in checking collisions or if you're at ground level or w/e. (this is why you use a game engine)
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