import pandas as pd
import numpy as np
import matplotlib.pyplot
from sklearn import svm
num=17
def getData1(train_ratio=0.8,m=6,n=6):
    df=pd.read_excel("data1.xlsx",index_col=0)
    train_num=num*train_ratio
    test_num=num-train_num
    train_data=df.loc[:train_num-1,:]
    test_data=df.loc[train_num:,:]
    X=[df.iloc[i,:m].tolist() for i in train_data.index]
    y=[df.iloc[i,n].tolist() for i in train_data.index]
    X_test=[df.iloc[i,:m].tolist() for i in test_data.index]
    y_test=[df.iloc[i,n].tolist() for i in test_data.index]
    return X,y,X_test,y_test

def judgeTest(y_pred,y_test):
    rightnum=0
    for i in range(len(y_pred)):
        ans=0
        my=0
        if y_test[i]==1:
            ans=1
            print("答案:好瓜")
        else:
            print("答案:坏瓜")
        if y_pred[i]>=0.5:
            print("预测:好瓜")
            my=1
        else:
            print("预测:坏瓜")
            my=0
        if my==ans:
            rightnum+=1
    print("正确率:","%d%%"%(rightnum/len(y_test)*100))