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HomeBackend DevelopmentGolangUse math.Min function to get the minimum value in a set of numbers

Use math.Min function to get the minimum value in a set of numbers

Jul 25, 2023 pm 11:13 PM
Obtainminimum valuemathmin

Use the math.Min function to obtain the minimum value in a set of numbers

In programming, it is often necessary to find the minimum value in a set of numbers. In Go language, we can use the Min function under the math package to achieve this function.

math.Min function is defined as follows:

func Min(x, y float64) float64

This function accepts two float64 type parameters x and y, and returns the smaller number.

The following is a sample code that demonstrates how to use the math.Min function to obtain the minimum value in a set of numbers:

package main

import (
    "fmt"
    "math"
)

func main() {
    numbers := []float64{3.14, 2.718, 1.618, 0.577, 2.235, 1.414}
    
    min := math.Inf(1)   // 初始化为正无穷大
    for _, num := range numbers {
        min = math.Min(min, num)
    }
    
    fmt.Printf("最小值为:%f
", min)
}

In this example, we define a slice numbers, which contains A set of floating point numbers. We first initialize the variable min to positive infinity, then go through the numbers slice through a loop, comparing the elements to min one by one, and using the math.Min function to update the value of min.

Finally, we use the Printf function in the fmt package to print out the minimum value.

Run the above code, the output result is as follows:

最小值为:0.577

As can be seen from the output result, the minimum value in a set of numbers is successfully obtained using the math.Min function.

It should be noted that the math.Min function is only suitable for numerical comparison of float64 type. If you need to find the minimum value in other types of data, you need to implement a related comparison function yourself.

To sum up, by using the math.Min function, we can easily obtain the minimum value in a set of numbers. This function is very useful when writing and optimizing code, providing more efficient and concise solutions.

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