python中定义的类的方法调用老出现missing 1 postional argument 或者self的解决办法

import numpy as np

# 归一化
class StandardScaler:
    def __init__(self):
        '''初始化'''
        self.mean_ = None
        self.scale_ = None

    def fit(self,x):
        '''input x_train,train the data inputed,and get the mean and scale.return the mean and scale'''
        assert x.ndim == 2, "The dimension of x must be 2"
        self.mean_ = np.array([np.mean(x[:, i]) for i in range(x.shape[1])])  # mean_是返回列的平均值
        self.scale_ = np.array([np.std(x[:, i]) for i in range(x.shape[1])])
        return self

    def transform(self, x):
        '''输入矩阵x,对输入的矩阵归一化'''
        assert self.scale_ is not None and self.mean_ is not None, "在归一化前要先fit"
        assert x.ndim == 2, "The dimension of x must be 2"
        assert x.shape[1] == len(self.scale_), "x的列数,特征数要和方差数同"
        # 创建一个空矩阵，将归一化结果存入
        resX = np.empty(shape = x.shape, dtype=float)
        for col in range(x.shape[1]):
            resX[:,col] = (x[:,col]-self.mean_[col])/self.scale_[col]
            return resX

#!/C:/USers/C/PycharmProjects/Machine_Learning_1
# -*- coding:utf-8 -*-

# ModelSelectation.py
import numpy as np
from sklearn import datasets

def train_test_split(x,y,test_ratio=0.2,seed=None):
    '''训练测试集划分,将x,y划分成x_train,y_traion,x_test,y_test'''
    assert x.shape[0]==y.shape[0],\
    "样本个数要同"
    assert 0<= test_ratio<=1.0,\
    "test_ratio must be valid"
# 为了使得例子可以重复，用种子，permutation打乱顺序，返回索引值
    if seed is not None:
        np.random.seed(seed)
    shuffle_index=np.random.permutation(len(x))
# 把前len(x)*test_ratio作为测试集，后者作为训练集
    test_size=int(len(x)*test_ratio)
    train_index=shuffle_index[test_size:]
    test_index=shuffle_index[:test_size]
    x_train=x[train_index]
    y_train=y[train_index]
    x_test=x[test_index]
    y_test=y[test_index]
    return x_train,y_train,x_test,y_test

这里我定义了一个类用于归一化。和一个训练集验证集划分的类。但是当我调用时。

from sklearn import datasets
from Standardization import StandardScaler
iris=datasets.load_iris()
x=iris.data
y=iris.target
from ModelSelectation import train_test_split
x_train,y_train,x_test,y_test=train_test_split(x,y)
StandardScaler.fit(x_train)
Traceback (most recent call last):
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python36_64\lib\site-packages\IPython\core\interactiveshell.py", line 2963, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-32-23221b0e8939>", line 1, in <module>
    StandardScaler.fit(x_train)

StandardScaler.fit(x=x_train)
Traceback (most recent call last):
  File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python36_64\lib\site-packages\IPython\core\interactiveshell.py", line 2963, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-33-783e331fdef3>", line 1, in <module>
    StandardScaler.fit(x=x_train)
TypeError: fit() missing 1 required positional argument: 'self'

这种情况是因为在调用方法时，没有提前定义这个类的实例，导致无法返回。只要先定义一个实例就可以了

s=StandardScaler()
s.fit(x_train)
Out[35]: <Standardization.StandardScaler at 0x203d5ab0710>