Let's talk about javascript division precision

For many programmers, JavaScript's numeric types seem to be a very simple part. But in fact, JavaScript division accuracy is a long-standing problem among developers.

The emergence of this problem stems from the data type design of JavaScript on the one hand, and the compromises made by ECMAScript to handle various special situations on the other hand. Specifically, the ECMAScript specification defines two number types: integers and floating point numbers. Floating-point numbers are divided into single-precision floating-point numbers (ie, 32-bit floating-point numbers) and double-precision floating-point numbers (ie, 64-bit floating-point numbers). In JavaScript, floating point numbers are of the Number type, and the only difference lies in the number of digits they occupy.

For example, let’s take a look at a simple division calculation:

console.log(1/3); // 输出 0.3333333333333333

This looks fine, but if we expand it:

console.log(1/3 + 1/3 + 1/3); // 输出 0.9999999999999999

The result is obviously not what we expected result. This is because JavaScript uses double-precision floating-point numbers when calculating, and the precision limit of double-precision floating-point numbers is limited. In particular, rounding errors occur when JavaScript operates on numbers that cannot be accurately represented as double-precision floating point numbers. This problem will not only affect the comparison of numerical values, but also have a negative impact on the correctness of data processing.

So how to avoid this problem?

In actual development, we can choose to use some libraries to handle calculation problems, such as BigDecimal.js. Such a library is suitable for performing floating point operations on large numbers and can obtain more accurate results. However, its use must also weigh the balance between calculation accuracy and memory usage.

In addition, another common solution is to convert floating point numbers into integers for calculation, and finally convert the results back. For example:

// 令计算精度到小数点后 2 位
var precision = 100;
console.log(Math.round((1/3) * precision + (1/3) * precision + (1/3) * precision) / precision); // 输出 0.33

This method can avoid the precision problem of floating point number operations to a certain extent, but the precision value needs to be selected according to the specific situation.

In addition, we can also use the new Number.EPSILON constant and toFixed() method in ES6 to make up for the precision problem of JavaScript.

console.log(Math.abs((1/3 + 1/3 + 1/3) - 1) < Number.EPSILON); // 输出 true
console.log((1/3 + 1/3 + 1/3).toFixed(2)); // 输出 "1.00"

Both of the above methods require attention to their applicable scope and limitations.

In general, the division precision problem in JavaScript is a common and difficult to deal with. Getting the details right requires some knowledge of mathematical operations and a deep understanding of the JavaScript language. I hope this article can help readers better avoid JavaScript division precision problems and improve the quality of their code.

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