首页 > 解决方案 > 下标问题(脚本实例化并从另一个脚本调用)仅运行被调用函数,而不是整个脚本

问题描述

目标:从上标开始,在 for 循环的每次迭代中,将一个列表发送到下标中的函数,更新该列表,退出下标中的函数,并执行几个操作,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.

预期产出

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
[]

标签: python

解决方案


据我了解,您需要在每次迭代中完整调用您的下标。

事情是这样的:

  • 一旦找到一个新模块就会被执行,并且最初执行的模块会被缓存
  • 当在不同的文件中导入相同的模块时,将返回缓存的版本。
  • 此缓存版本存在于整个过程的生命周期中。

由于您需要在每次迭代时重新运行下标,因此可以使用 Class。类的对象:

  • 存储每次迭代的数据
  • 编写任意数量的函数来处理这些数据
  • 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

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