下标（从另一个脚本实例化并调用的脚本）仅运行被调用函数，而不是整个脚本时出现问题

Question

目标：从上标开始，在for循环的每次迭代中，向下标中的函数发送一个列表，更新该列表，退出下标中的函数，并执行若干操作，然后进入下一次迭代

问题：只运行我从上标调用的函数，而不是整个下标

CrossValidationSmall.py（上标）

import subfileTest

data = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J','K']
n = 2

for start in range(0, len(data), n):
    stop = start + n
    test = data[start: stop]
    train = data[:start] + data[stop:]
    subfileTest.set_train_data(train)

subfileTest.py（下标）

train_data = []

def set_train_data(train):
    global train_data
    train_data = train

print(train_data) #should output the lists each time subfileTest is called.

预期产量

MacBook-Pro:SmallerEnviromentTest Me$ python CrossValidationSmall.py
['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'G', 'H', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'I', 'J', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'K']
['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J']

电流输出

MacBook-Pro:SmallerEnviromentTest Me$ python CrossValidationSmall.py
[]

Answer 1

据我所知，您需要在每次迭代中完整地调用您的下标

事情是这样的：

• 一旦找到一个新的模块，它就会被执行，并且初始执行的模块会被缓存
• 当相同的模块导入到不同的文件中时，将返回缓存的版本
• 此缓存版本在进程的整个生命周期内都有效

因为您需要在每次迭代时重新运行下标，所以可以使用一个类。类的一个对象，用于：

• 存储每次迭代的数据
• 编写处理此数据的任意数量的函数
• 根据需要保留每个对象的值

上标：

from subscript import ModelCrossValidator

trial = 0

data = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K']
n = 2

for start in range(0, len(data), n):
    trial += 1

    stop = start + n
    test = data[start: stop]

    # train_subset to be used for cross validation
    train_subset = data[:start] + data[stop:]

    cross_validator = ModelCrossValidator(train_subset)
    cross_val_score = cross_validator.calc_score()

print("CrossValSet: {}, Data: {}, Score: {:.2}".format(trial, cross_validator.data, cross_val_score))

下标：

import random

class ModelCrossValidator:

    def __init__(self, train_subset):
        self.data = train_subset     # your folded cross-val data
        self.model = None            # can pass in a model too here
        self.accuracy = 0            # other fields that you might need

    def calc_score(self):
        # you can have any number of functions like this.
        # all will deal with only the data from a single object.

        self.accuracy = 0.8 + (random.random()) % 0.2
        return self.accuracy

输出：

Macbook-Pro: chimichanga$ python superscript.py 
CrossValSet: 1, Data: ['C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K'], Score: 0.89
CrossValSet: 2, Data: ['A', 'B', 'E', 'F', 'G', 'H', 'I', 'J', 'K'], Score: 0.94
CrossValSet: 3, Data: ['A', 'B', 'C', 'D', 'G', 'H', 'I', 'J', 'K'], Score: 0.9
CrossValSet: 4, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'I', 'J', 'K'], Score: 0.84
CrossValSet: 5, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'K'], Score: 0.88
CrossValSet: 6, Data: ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'], Score: 0.94