On Mon, 24 Oct 2022 14:52:28 +0000, "Schachner, Joseph (US)"
<joseph.schach...@teledyne.com> declaimed the following:
>Floating point will always be a can of worms, as long as people expect it to
>represent real numbers with more precision that float has. Usually this is
>not an issue, but sometimes it is. And, although this example does not
>exhibit subtractive cancellation, that is the surest way to have less
>precision that the two values you subtracted. And if you try to add up lots
>of values, if your sum grows large enough, tiny values will not change it
>anymore, even if there are many of them - there are simple algorithms to
>avoid this effect. But all of this is because float has limited precision.
>
Might I suggest this to those affected...
https://www.amazon.com/Real-Computing-Made-Engineering-Calculations/dp/0486442217/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1666634371&sr=8-1
(Wow -- they want a fortune for the original hard-cover, which I own)
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Wulfraed Dennis Lee Bieber AF6VN
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