Python，为什么i = + 1不会导致无限循环? [英] Python, why does i=+1 not result in an infinite loop?

问题描述

因此，前几天我因为错字而陷入一个问题.我没有使用i + = 1遍历嵌套循环，而是使用i = + 1.在开始打印步骤数并看到它是连续打印步骤1之前，我没有注意到这一点.因此，我得到的情节毫无意义.

So the other day I was stuck on a problem because of a typo. Instead of iterating through my nested loop with i += 1 I was using i=+1. I didn't notice this until I started printing the number of steps and saw it was printing step 1 continuously. The plots I was getting therefore weren't making any sense.

但是我不明白的是为什么我什么都没有，而且代码没有陷入无限循环中?另外，我应该只在完成步骤数的一半之后才开始计算数据，所以我根本不了解如何获得任何数据.还是我= + 1代表其他意思?我似乎在所有在线上都找不到关于i = + 1的太多信息

However what I don't understand is why I got any plots at all, and the code wasn't stuck in an infinite loop? Also, I should only have been calculating data after halfway through the number of steps, so I don't understand how I had any data at all. Or does i =+ 1 mean something else? I can't seem to find much information on i=+1 at all online

这是原始代码的精简版:

Here's a condensed version of the original code:

for temp in np.linspace(1.0,4.0,num=100):   
    energyarray = []
    for step in np.arange(0, sw*2):    
        for i in range(n-1):
           for j in range(n-1):

            H_old = -J*matrix[i,j]*(matrix[i,j-1] + matrix[i,j+1] + matrix[i-1,j] + matrix[i+1,j])
            H_new = J*matrix[i,j]*(matrix[i,j-1] + matrix[i,j+1] + matrix[i-1,j] + matrix[i+1,j])   
            del_H = H_old-H_new
            if del_H >= 0:
                matrix[i,j] = -matrix[i,j]
            elif del_H < 0:
                    prob = np.exp((del_H)/(temp))   
                    rand = random.random()
                    if rand < prob:
                        matrix[i,j] = -matrix[i,j]
                    else:
                        matrix[i,j] = matrix[i,j]  

        if step >= (sw):

            Ene = EnergyCal(matrix)
            energyarray.append(Ene)


        step =+ 1 


    energy_sum = []
    energy_sum = sum(energyarray)


    plt.figure(10)
    plt.plot(temp, energy_sum, 'ro')


plt.show()

推荐答案

Python for循环是基于迭代器的"for-each"循环.在每次迭代的开始重新分配迭代变量.换句话说，以下循环:

Python for-loops are iterator-based "for-each" loops. The iterating variable is reassigned at the beginning of each iteration. In other words, the following loop:

In [15]: nums = 1,2,5,8

In [16]: for num in nums:
    ...:     print(num)
    ...:
1
2
5
8

等效于:

In [17]: it = iter(nums)
    ...: while True:
    ...:     try:
    ...:         num = next(it)
    ...:     except StopIteration:
    ...:         break
    ...:     print(num)
    ...:
1
2
5
8

类似地，以下循环是等效的:

Similarly, the following loops are equivalent:

In [19]: for num in nums:
    ...:     print("num:", num)
    ...:     num += 1
    ...:     print("num + 1:", num)
    ...:
    ...:
num: 1
num + 1: 2
num: 2
num + 1: 3
num: 5
num + 1: 6
num: 8
num + 1: 9

In [20]: it = iter(nums)
    ...: while True:
    ...:     try:
    ...:         num = next(it)
    ...:     except StopIteration:
    ...:         break
    ...:     print("num:", num)
    ...:     num += 1
    ...:     print("num + 1:", num)
    ...:
num: 1
num + 1: 2
num: 2
num + 1: 3
num: 5
num + 1: 6
num: 8
num + 1: 9

注意，Python中不存在C样式的for循环，但是您可以随时编写while循环(c样式的for循环本质上是while循环的语法糖):

Note, C-style for-loops don't exist in Python, but you can always write a while-loop (c-style for loops are essentially syntactic sugar for while-loops):

for(int i = 0; i < n; i++){
    // do stuff
}

等效于:

i = 0
while i < n:
    # do stuff
    i += 1

请注意，不同之处在于，在这种情况下，迭代取决于i ，# do stuff中的任何修改i的内容都会影响迭代，而在前一种情况下，迭代取决于 iterator .注意，如果我们确实修改了迭代器，则会影响迭代:

Note, the difference is that in this case, iteration depends on i, anything in # do stuff that modifies i will impact iteration, whereas in the former case, iteration depends on the iterator. Note, if we do modify the iterator, then iteration is impacted:

In [25]: it = iter(nums) # give us an iterator
    ...: for num in it:
    ...:     print(num)
    ...:     junk = next(it) # modifying the iterator by taking next value
    ...:
    ...:
1
5

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