Have you performed simple arithmetic operations like 0.1 + 0.2? You might have gotten something strange: 0.1 + 0.2 = 0.30000000000000004.

  • @[email protected]
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    81 day ago

    Ugh, i thought this was a question, not a link. So i spent time googling for a good tutorial on floats (because I didn’t click the link)…

    Now i hate myself, and this post.

  • @[email protected]
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    51 day ago

    It’s how CPUs do floating point calculations. It’s not just javascript. Long story short, a float is stored in the format of one bit for the +/-, some bits for a base value (mantissa), and some bits for the exponent. As a result, some numbers aren’t quite representable exactly.

  • Zagorath
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    41 day ago

    A good way to think of it is to compare something similar in decimal. .1 and .2 are precise values in decimal, but can’t be represented as perfectly in binary. 1/3 might be a pretty good similar-enough example. With a lack of precision, that might become 0.33333333, which when added in the expression 1/3 + 1/3 + 1/3 will give you 0.99999999, instead of the correct answer of 1.

    • @toasteecup
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      -61 day ago

      Python has no issues representing

      1/3 + 1/3 + 1/3

      as 1. I just opened a python interpreter, imported absolutely no libraries and typed

      1/3 + 1/3 + 1/3 enter and got 1 as the result. Seems like if python could do that, JavaScript should be able to as well.

      • Zagorath
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        41 day ago

        I thought it was a rather simple analogue, but I guess it was too complicated for some?

        I said nothing about JavaScript or Python or any other language with my 1/3 example. I wasn’t even talking about binary. It was an example of something that might be problematic if you added numbers in an imprecise way in decimal, the same way binary floating point fails to accurately represent 1/10 + 1/5 from the OP.

        • @[email protected]
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          1 day ago

          Perhaps the following rewording of your last sentence would be easier for readers to follow along:

          With a lack of precision, 1/3 might become 0.33333333. When evaluating the expression 1/3 + 1/3 + 1/3, using 0.33333333 as an approximate representation of 1/3 will return a result of 0.99999999, instead of the correct answer of 1.

        • @toasteecup
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          11 day ago

          I’ll pass on the js interpreter. I don’t feel like learning the arcane runes.

          To your point, Python handles those by giving you 0.300000004 might have missed a zero but valid point nonetheless

      • @[email protected]
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        1 day ago

        That’s because the nearest representable float to 0.99999999999999 is 1.0 - not because Python is handling rationals correctly.

        This is a float imprecision issue that just happens to work out in this case.

        It’s worth wondering why, if Python is OK with “/“ producing a result of a different type than its arguments, don’t they implement a ratio type. e.g. https://www.cs.cmu.edu/Groups/AI/html/cltl/clm/node18.html#SECTION00612000000000000000

  • @[email protected]
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    1 day ago

    JavaScript is truly a bizarre language - we don’t need to go as far as arbitrary-precision decimal, it does not even feature integers.

    I have to wonder why it ever makes the cut as a backend language.