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Why is PHP floating point calculation inaccurate?

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2023-04-23 10:09:121714browse

In PHP programming, you may encounter the problem of inaccurate floating point calculations. Understanding the cause and solution of this problem can improve the reliability and accuracy of your code.

1. Cause of the problem

Floating point numbers are a very convenient way to represent floating point numbers, but they also have some shortcomings. The main reason is that computers use binary to store numbers and cannot accurately represent all floating point numbers. This results in rounding errors and loss of precision.

For example, imagine a simple floating point calculation:

0.1 + 0.2 = 0.3

In PHP, the result of this code is as follows:

echo 0.1 + 0.2; //0.30000000000000004

Obviously, this result is not what we expected . This is because 0.1 and 0.2 cannot be accurately represented as binary numbers, which results in rounding errors. Although this error is usually small, it is enough to cause a loss of accuracy or create errors in some high-precision calculations.

2. Solution

For the problem of inaccurate floating-point calculations, we can adopt the following solutions:

  1. Use integer calculations

When performing precise calculations, you can first convert floating point numbers into integers before performing calculations. After the calculation is complete, the result is converted back to a floating point number.

For example, consider the following floating point calculation:

1.23 + 4.56 = 5.79

You can convert floating point numbers to integers for calculation:

$num1 = 123;
$num2 = 456;

$result = ($num1 + $num2) / 100; // 5.79
  1. Using BCMath

PHP provides a BCMath extension that can be used to accurately calculate arbitrary precision numbers. Floating point calculations can be performed using the BCMath library, which uses strings to represent numbers instead of floating point numbers.

For example, use the BCMath function library to calculate:

$val1 = '0.1';
$val2 = '0.2';

echo bcadd($val1, $val2, 1); // 0.3

In this example, we use the bcadd() function to perform exact floating point addition.

  1. Use the round() function

In some cases, you can use the round() function to reduce the precision error. The round() function rounds a floating point number to a specified number of decimal places.

For example, consider the following calculation:

$num1 = 0.1;
$num2 = 0.2;

$result = round($num1 + $num2, 1); // 0.3

This example uses the round() function to round the result to one decimal place. While this doesn't completely eliminate the accuracy error, the results are much closer to what was expected.

  1. Avoid direct comparison of floating point numbers

When comparing floating point numbers, some fault tolerance mechanism should be used. Because the precision of floating point numbers can suffer from rounding errors, it is generally unreliable to directly compare the values ​​of two floating point numbers.

For example, consider the following comparison of floating point numbers:

$val1 = 3.14159265;
$val2 = 3.14159267;

if ($val1 == $val2) {
  echo 'val1 等于 val2';
} else {
  echo 'val1 不等于 val2';
}

In this example, we compare two floating point numbers. Although these two numbers are close, they are not equal. Therefore, the code outputs "val1 is not equal to val2".

If you need to compare two floating point numbers, you can use a tolerance value or delta value. A tolerance value is a small number that can tolerate a small error in a floating point number.

For example, we can define a delta value, representing the maximum allowed precision error:

$delta = 0.00000001;

With the delta value, we can use the following code to compare floating point numbers:

$val1 = 3.14159265;
$val2 = 3.14159267;

if (abs($val1 - $val2) < $delta) {
  echo 'val1 等于 val2';
} else {
  echo 'val1 不等于 val2';
}

In this example, we use the abs() function to calculate the difference between two floating point numbers and compare it with the delta value. If the difference between two numbers is less than the delta value, they are considered equal.

In short, the problem of inaccurate floating point calculation is a common problem. In PHP, this problem can be solved using methods such as integer arithmetic, the BCMath function library, the round() function, and delta value tolerance. Depending on the situation, different solutions can be chosen.

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