Teach you a text to solve the problem of JS digital accuracy loss

One 、 About why we should solve the loss of accuracy

Let's look at an example , because js Loss of accuracy is also a common problem , Normally we can round or toFixed Keep decimals to solve

Now the problem is that we know that the calculation result is equal to 0.01 But the final result is indeed true, If we encounter arithmetic problems , Decimal value comparison problem , Then we have to deal with him , Otherwise, there will also be an upper case , There is a logical judgment error

Two 、 How to solve js Loss of calculation accuracy ？

Normally, if it is Keep the decimal point 2 position 、3 Bits, etc , We can use common * Hundreds of digits 、 thousands After realizing the integer result Divide the result by the corresponding digit to achieve the result , as follows

console.log(5.22 - 5.21);

 console.log((5.22 * 100 - 5.21 * 100) / 100);

According to the above description, let's look at our first example

The result is what we want

3、 ... and 、toPrecision A specific method returns a rounded length string

Of course toFixed It can also achieve the corresponding length selection effect , Because the major browsers are aimed at toFixed All kinds of results are different. Interested students can refer to the following article
toFixed Detailed explanation

Here we only introduce toPrecision Refer to the method in detail

Then we know what this method is used for
Of course, there is another point, that is, from left to right Not for 0 Start to calculate the position of

Example above Our result is 0.01

If we use toPrecision Words , Then the parameter to be filled in is 1

The result of the return is what we want 0.01

Then we match parseFloat After a floating-point numeric conversion of the string , Then compare and get the final result

console.log(5.22 - 5.21 < 0.01);
console.log((5.22 * 100 - 5.21 * 100) / 100 < 0.01);
var num = 5.22 - 5.21;
console.log(parseFloat(num.toPrecision(1)) < 0.01);

Conclusion

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