python - 给定比例将文件随机分发到训练/测试中

Question

我目前正在尝试制作一个设置脚本，能够为我设置一个工作区，这样我就不需要手动完成了。 我开始在 bash 中执行此操作，但很快意识到效果不佳。

我的下一个想法是使用 python 来完成它，但似乎无法以正确的方式做到这一点。我的想法是制作一个列表(列表是一个包含所有数据文件路径的 .txt 文件)，打乱这个列表，然后将每个文件移动到我的训练目录或测试目录，给定比率....

但这是 python，难道没有更简单的方法吗，似乎我只是为了拆分文件而做了一个不必要的解决方法。

代码:

# Partition data randomly into train and test. 
cd ${PATH_TO_DATASET}
SPLIT=0.5 #train/test split
NUMBER_OF_FILES=$(ls ${PATH_TO_DATASET} |  wc -l) ## number of directories in the dataset
even=1
echo ${NUMBER_OF_FILES}

if [ `echo "${NUMBER_OF_FILES} % 2" | bc` -eq 0 ]
then    
        even=1
        echo "Even is true"
else
        even=0
        echo "Even is false"
fi

echo -e "${BLUE}Seperating files in to train and test set!${NC}"

for ((i=1; i<=${NUMBER_OF_FILES}; i++))
do
    ran=$(python -c "import random;print(random.uniform(0.0, 1.0))")    
    if [[ ${ran} < ${SPLIT} ]]
    then 
        ##echo "test ${ran}"
        cp -R  $(ls -d */|sed "${i}q;d") ${WORKSPACE_SETUP_ROOT}/../${WORKSPACE}/data/test/
    else
        ##echo "train ${ran}"       
        cp -R  $(ls -d */|sed "${i}q;d") ${WORKSPACE_SETUP_ROOT}/../${WORKSPACE}/data/train/
    fi

    ##echo $(ls -d */|sed "${i}q;d")
done    

cd ${WORKSPACE_SETUP_ROOT}/../${WORKSPACE}/data
NUMBER_TRAIN_FILES=$(ls train/ |  wc -l)
NUMBER_TEST_FILES=$(ls test/ |  wc -l)

echo "${NUMBER_TRAIN_FILES} and ${NUMBER_TEST_FILES}..."
echo $(calc ${NUMBER_TRAIN_FILES}/${NUMBER_OF_FILES})

if [[ ${even} = 1  ]] && [[ ${NUMBER_TRAIN_FILES}/${NUMBER_OF_FILES} != ${SPLIT} ]]
    then 
    echo "Something need to be fixed!"
    if [[  $(calc ${NUMBER_TRAIN_FILES}/${NUMBER_OF_FILES}) > ${SPLIT} ]]
    then
        echo "Too many files in the TRAIN set move some to TEST"
        cd train
        echo $(pwd)
        while [[ ${NUMBER_TRAIN_FILES}/${NUMBER_TEST_FILES} != ${SPLIT} ]]
        do
            mv $(ls -d */|sed "1q;d") ../test/
            echo $(calc ${NUMBER_TRAIN_FILES}/${NUMBER_OF_FILES})
        done
    else
        echo "Too many files in the TEST set move some to TRAIN"
        cd test
        while [[ ${NUMBER_TRAIN_FILES}/${NUMBER_TEST_FILES} != ${SPLIT} ]]
        do
            mv $(ls -d */|sed "1q;d") ../train/
            echo $(calc ${NUMBER_TRAIN_FILES}/${NUMBER_OF_FILES})
        done
    fi

fi   

我的问题是最后一部分。由于我随机选择数字，因此我不确定数据是否会按预期进行分区，我的最后一个 if 语句是检查分区是否正确完成，如果不正确则修复它。这是不可能的，因为我正在检查 float ，一般来说解决方案变得更像是一个快速修复。

Answer 1

scikit-learn 来拯救 =)

>>> import numpy as np
>>> from sklearn.cross_validation import train_test_split
>>> X, y = np.arange(10).reshape((5, 2)), range(5)
>>> X
array([[0, 1],
       [2, 3],
       [4, 5],
       [6, 7],
       [8, 9]])
>>> y
[0, 1, 2, 3, 4]


# If i want 1/4 of the data for testing 
# and i set a random seed of 42.
>>> X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)
>>> X_train
array([[4, 5],
       [0, 1],
       [6, 7]])
>>> X_test
array([[2, 3],
       [8, 9]])
>>> y_train
[2, 0, 3]
>>> y_test
[1, 4]

参见 http://scikit-learn.org/stable/modules/generated/sklearn.cross_validation.train_test_split.html

---

演示:

alvas@ubi:~$ mkdir splitfileproblem
alvas@ubi:~$ cd splitfileproblem/
alvas@ubi:~/splitfileproblem$ mkdir original
alvas@ubi:~/splitfileproblem$ mkdir train
alvas@ubi:~/splitfileproblem$ mkdir test
alvas@ubi:~/splitfileproblem$ ls
original  train  test
alvas@ubi:~/splitfileproblem$ cd original/
alvas@ubi:~/splitfileproblem/original$ ls
alvas@ubi:~/splitfileproblem/original$ echo 'abc' > a.txt
alvas@ubi:~/splitfileproblem/original$ echo 'def\nghi' > b.txt
alvas@ubi:~/splitfileproblem/original$ cat a.txt 
abc
alvas@ubi:~/splitfileproblem/original$ echo -e 'def\nghi' > b.txt
alvas@ubi:~/splitfileproblem/original$ cat b.txt 
def
ghi
alvas@ubi:~/splitfileproblem/original$ echo -e 'jkl' > c.txt
alvas@ubi:~/splitfileproblem/original$ echo -e 'mno' > d.txt
alvas@ubi:~/splitfileproblem/original$ ls
a.txt  b.txt  c.txt  d.txt

在 Python 中:

alvas@ubi:~/splitfileproblem$ ls
original  test  train
alvas@ubi:~/splitfileproblem$ python
Python 2.7.12 (default, Jul  1 2016, 15:12:24) 
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> from sklearn.cross_validation import train_test_split
>>> os.listdir('original')
['b.txt', 'd.txt', 'c.txt', 'a.txt']
>>> X = y= os.listdir('original')
>>> X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=0)
>>> X_train
['a.txt', 'd.txt', 'b.txt']
>>> X_test
['c.txt']

现在移动文件:

>>> for x in X_train:
...     os.rename('original/'+x , 'train/'+x)
... 
>>> for x in X_test:
...     os.rename('original/'+x , 'test/'+x)
... 
>>> os.listdir('test')
['c.txt']
>>> os.listdir('train')
['b.txt', 'd.txt', 'a.txt']
>>> os.listdir('original')
[]

另请参阅:How to move a file in Python