There is a no exact representation of 0.1 as a float or double. Because of this representation error the results are slightly different from what you expected. A couple of approaches you can use: When using the double type, only display as many digits as you need. When checking for equality allow for a small … Read more
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From this post: How to deal with floating point number precision in JavaScript? You have a few options: Use a special datatype for decimals, like decimal.js Format your result to some fixed number of significant digits, like this: (Math.floor(y/x) * x).toFixed(2) Convert all your numbers to integers
Update(2019-08-19): BigInt is now part of Firefox and Chrome; you no longer need a library: const bigInt1 = 1111111111111111111111111111111n; const bigInt2 = BigInt(“1111111111111111111111111111111″) console.log((bigInt1 + bigInt2)+””) Original answer: If you need arbitrary-precision decimal numbers, use Javascript-bignum, as it is correct and fast.
In the standard library, the decimal module may be what you’re looking for. Also, I have found mpmath to be quite helpful. The documentation has many great examples as well (unfortunately my office computer does not have mpmath installed; otherwise I would verify a few examples and post them). One caveat about the decimal module, … Read more
Because floating point arithmetic != real number arithmetic. An illustration of the difference due to imprecision is, for some floats a and b, (a+b)-b != a. This applies to any language using floats. Since floating point are binary numbers with finite precision, there’s a finite amount of representable numbers, which leads accuracy problems and surprises … Read more
the correct way to test floats for ‘equality’ is: if(Math.abs(sectionID – currentSectionID) < epsilon) where epsilon is a very small number like 0.00000001, depending on the desired precision.
You’re overflowing the capacity of JavaScript’s number type, see §8.5 of the spec for details. Those IDs will need to be strings. IEEE-754 double-precision floating point (the kind of number JavaScript uses) can’t precisely represent all numbers (of course). Famously, 0.1 + 0.2 == 0.3 is false. That can affect whole numbers just like it … Read more
First of all, floating point values are not “random” in their behavior. Exact comparison can and does make sense in plenty of real-world usages. But if you’re going to use floating point you need to be aware of how it works. Erring on the side of assuming floating point works like real numbers will get … Read more
There are basically two major pitfalls people stumble in with floating-point numbers. The problem of scale. Each FP number has an exponent which determines the overall “scale” of the number so you can represent either really small values or really larges ones, though the number of digits you can devote for that is limited. Adding … Read more