import math
import numpy as np
import pandas as pd
from pandas import DataFrame,Series
def sigmoid(x):
return 1/(1+math.exp(-x))
x1=[0.29,0.50,0.00,0.21,0.10,0.06,0.13,0.24,0.28]
x2=[0.23,0.62,0.53,0.53,0.33,0.15,0.03,0.23,0.03]
y=[0.14,0.64,0.28,0.33,0.12,0.03,0.02,0.11,0.08]
yita=0.1
for i in range(9):
Net_in =DataFrame(0.6,index=['input1','input2','theata'],columns=['a'])
Out_in = DataFrame(0,index=['input1','input2','input3','input4','theata'],columns=['a'])
Net_in.loc['input1'] =x1[i]
Net_in.loc['input2']=x2[i]
real=y[i]
Net_in.loc['theata'] = -1
Out_in.loc['theata'] = -1
W_mid=DataFrame(0.7,index=['input1','input2','theata'],columns=['mid1','mid2','mid3','mid4'])
W_out=DataFrame(0.7,index=['input1','input2','input3','input4','theata'],columns=['a'])
W_mid_delta=DataFrame(0,index=['input1','input2','theata'],columns=['mid1','mid2','mid3','mid4'])
W_out_delta=DataFrame(0,index=['input1','input2','input3','input4','theata'],columns=['a'])
for i in range(0,4):
Out_in.iloc[i,0] = sigmoid(sum(W_mid.iloc[:,i]*Net_in.iloc[:,0]))
res = sigmoid(sum(Out_in.iloc[:,0]*W_out.iloc[:,0]))
error = abs(res-real)
W_out_delta.iloc[:,0] = yita*res*(1-res)*(real-res)*Out_in.iloc[:,0]
W_out_delta.iloc[4,0] = -(yita*res*(1-res)*(real-res))
W_out = W_out + W_out_delta
for i in range(0,4):
W_mid_delta.iloc[:,i] = yita*Out_in.iloc[i,0]*(1-Out_in.iloc[i,0])*W_out.iloc[i,0]*res*(1-res)*(real-res)*Net_in.iloc[:,0]
W_mid_delta.iloc[2,i] = -(yita*Out_in.iloc[i,0]*(1-Out_in.iloc[i,0])*W_out.iloc[i,0]*res*(1-res)*(real-res))
W_mid = W_mid + W_mid_delta
testx1=[0.38,0.29]
testx2=[0.49,0.47]
for i in range(2):
Net_in =DataFrame(0.6,index=['input1','input2','theata'],columns=['a'])
Out_in = DataFrame(0,index=['input1','input2','input3','input4','theata'],columns=['a'])
Net_in.loc['input1'] =testx1[i]
Net_in.loc['input2']=testx2[i]
Net_in.loc['theata'] = -1
Out_in.loc['theata'] = -1
for i in range(0,4):
Out_in.iloc[i,0] = sigmoid(sum(W_mid.iloc[:,i]*Net_in.iloc[:,0]))
res = sigmoid(sum(Out_in.iloc[:,0]*W_out.iloc[:,0]))
print(res)