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fmod for Javascript, will work with any ECMA-262 implementation.If you need a precision higher than 8, please use another implementaion of fmod.
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/* | |
fmod for Javascript, will work with any ECMA-262 implementation. | |
If you need a precision higher than 8, please use another implementation of fmod. | |
1.05 % 0.05 | |
=> 0.04999999999999999 | |
Math.fmod(1.05, 0.05) | |
=> 0 | |
Math.fmod(1.05, 0.019) | |
=> 0.005 | |
Math.fmod(1.00000012, 0.00000005) | |
=> 0.00000002 | |
fmod will most likely fail, if (Math.log(a)/Math.log(10) - Math.log(b)/Math.log(10)) > 8 | |
Try to keep the difference in order of magnitudes as small as possible!: | |
Math.fmod(1000000.40, 0.07) | |
=> 0.07 | |
Math.fmod(10000000.40, 0.07) | |
=> 0.039999999 | |
*/ | |
/* TODO: fix for a=4.55 b=0.05 !!*/ | |
Math.fmod = function (a,b) { return Number((a - (Math.floor(a / b) * b)).toPrecision(8)); }; |
Great, thanks for sharing 👍
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No, it has the same issue of course -- which is primarily due to 4.55 and 0.05 not having finite representations in binary. The general solution would be to accept one digit less in precision:
Which is, annoyingly, off by one as one can see but that is caught easily enough.
However, mathjs is not immune to these round-off errors either, although it is likely to show in different ways due to different algorithms or sequences of operations (so maths.mod may end up showing rounding errors in edge cases where % doesn't). And of course one can always switch to arbitrary precision through decimal.js if necessary.