infinite precision

Floating point numbers are the ones with decimals, and they are not just numbers. when I use the payment interface, I have encountered the problem of floating point loss. let's take a look at the solution. let's take a look at the following code: $

Let's take a look at the following code:$ F = 0.57;Echo intval ($ f * 100); // 56The result may be a little unexpected. PHP follows IEEE 754 dual precision:Floating point number, expressed in 64-bit dual precision, with one-bit sign bit (E), 11

1. ScopeThe float and double ranges are determined by the number of digits of the index.The float index has eight digits, while the double index has 11 digits. The distribution is as follows:Float:1bit (symbol bit) 8 bits (index bit) 23 bits (tail

This article is divided into three parts Some typical problems of JS digital precision loss The reason for the loss of JS digital precision Solution (one object + one function) Some typical problems of JS digital precision loss 1.

PHP floating point precision problem summary, php floating point precision. PHP floating point number precision problem summary, php floating point precision 1, PHP floating point precision loss first look at the following code: Copy the code: $ f0.5

Reason: JS in accordance with the 2 to deal with decimal subtraction, on the basis of arg1 arg2 precision extension or reverse expansion matching, so will appear as follows. JavaScript (JS) decimal point subtraction problem, is a JS bug such as 0.3*

Engaged in the financial industry, capital operations frequently, here I met the pit .... Slightly inattentive, the user funds may lose hundreds of thousands of, even more terrible ... Go directly to the example:Javascript0.1 + 0.2 Why isn't it

Author: jillzhang Contact: jillzhang@126.com This article is original and reposted. Please retain the source and author. Thank you. In C and C # languages, float and double types are used for data of the floating point type for storage. float data

This article is mainly to share with you PHP to achieve high-precision computing, engaged in the financial industry, capital operations frequently, here I met the pit .... Slightly inattentive, the user funds may lose hundreds of thousands of, even

PHP floating point Precision problem summary, php floating point Precision I. Precision loss of PHP floating point numbers Let's take a look at the following code:Copy codeThe Code is as follows:$ F = 0.57;Echo intval ($ f * 100); // 56 The result