python – 嵌套while循环的运行时间

要查找内部while循环的迭代次数,是否与查找内循环的运行时间相同？此外,内部循环依赖于外部循环,我知道我应该将内部while循环运行的次数乘以外部while循环以获得迭代的次数,对吧？我对如何计算while循环的迭代次数感到困惑.任何帮助,将不胜感激.谢谢！

def nested(n):
    b = 1 
    while b <= n:
        i = 1
        while i < b:
            print(i)
            i = i*3
        b += 1

感谢大家的帮助！

我想我明白答案是什么.因此,既然我们试图找到内循环迭代的次数(n-1),我还需要考虑外循环迭代内循环的次数(即n).因此,我们将迭代内循环(n-1),n次,因此如果我们使用求和符号,则给出(n(n-1))/ 2.希望这是对的.

解决方法:

你有两个问题,所以我把它们拆开了.

To find the number of iterations of the inner while loop, is it the same as finding the run time of inner loop?

不.我已经冒昧地修改你的代码,使用time.process_time测量运行时间而不受操作系统调度程序的干扰,并消除内部打印语句(I / O调用看起来很昂贵).

import time

def nested(n):
    loops = list()

    #Start outer timer
    func_start = time.process_time()

    b = 1 
    while b <= n:

        #Start loop timer
        loop_start = time.process_time()

        i = 1
        while i < b:
            #print(i)
            i = i*3
        b += 1

        #Finish loop timer
        loop_finish = time.process_time()
        loops.append(loop_finish - loop_start)

    #Finish outer timer
    func_finish = time.process_time()

然后我添加一个日志声明：

print("Function time: %f, Sum loop times: %f, iterations: %i, iterations by runtime: %.0f" 
        % (func_finish - func_start, 
            sum(loops), 
            len(loops), 
            (func_finish - func_start) / (sum(loops)/len(loops)))  )

最后,我运行了几次.结果如下：

Function time: 0.000019, Sum loop times: 0.000010, iterations: 10, iterations by runtime: 19
Function time: 0.000135, Sum loop times: 0.000102, iterations: 100, iterations by runtime: 132
Function time: 0.001461, Sum loop times: 0.000875, iterations: 1000, iterations by runtime: 1670
Function time: 0.017174, Sum loop times: 0.011532, iterations: 10000, iterations by runtime: 14892
Function time: 0.193567, Sum loop times: 0.133996, iterations: 100000, iterations by runtime: 144457

如您所见,随着迭代次数的增加,使用相对运行时间来尝试估计迭代次数变得不那么准确.

Also since, the inner loop is dependent on on the outer loop,I know I should multiply the number of times the inner while loop runs with the outer while loop to get the number of times it is iterated, right?

这适用于理论应用.如果我在内循环中有n个指令,并且内循环运行了m次,我预测总运行时间实际上是mn.但是,您必须记住,一行代码不等于单个指令.实际上,即使某些指令在执行时间方面也不等于其他指令(例如,浮点运算与整数运算).我们在我们的定时例子中看到了这一点.

为了计算Big-O运行时边界,建议将内循环语句计数乘以循环数的技术起作用.在现实世界中,对于像Python这样的解释性语言来说,它变得更复杂,更加复杂.

标签：python,python-3-x,algorithm,big-o
来源： https://codeday.me/bug/20190828/1753102.html