AI Assignment I

import random
import math

##########Function##########

## (2-6)
def Vjl(weigth, dataInput, numOfHiden, x0):
    vjHidenNode = [0 for i in range(numOfHiden)]
    for i in range( numOfHiden ):
        for j in range( len(dataInput)):
            vjHidenNode[i] += weigth[j][i] * dataInput[j]
        vjHidenNode[i] -= x0
    return vjHidenNode

## (2-7)
def Yjl(n):
    temp2 = []
    for i in range(len(n)):
        temp = 1/(1+math.exp(-n[i]))
        temp2.append(temp)
        #print temp
    return temp2

## (2-10)
def Ej(Dj, Yj):
    temp = [0 for i in range(len(Dj))]
    for i in range(len(Dj)):
        temp[i] = Dj[i]-Yj[i]
        ##print temp[i]
    return temp

## (2-11)
def Sj_L(Ej,Yj):
    temp2 = []
    for i in range(len(Ej)):
        temp = (Ej[i]*Yj[i])*(1-Yj[i])
        temp2.append(temp)
    return temp2

## (2-12)
def Sj_Neural(Yj, Sk, Wkj):
    temp2 = []
    sumOf_Sk_Wj = 0.0

    for i in range(len(Yj)):
        for j in range(len(Sk)):
            sumOf_Sk_Wj += Sk[j]*Wkj[i][j]
        temp = Yj[i]*( 1.0 - Yj[i])*sumOf_Sk_Wj
        temp2.append(temp)
        sumOf_Sk_Wj = 0.0;

    return temp2

## (2-13)
def Wji(Sj, Yil__1, A, N, Wjn, Wjn_1):
    temp2 = [[0 for i in range(len(Wjn[0]))] for j in range(len(Wjn))]
    for i in range(len(Wjn)):
        for j in range(len(Wjn[0])):
           temp = Wjn[i][j] + A*(Wjn[i][j] - Wjn_1[i][j]) + N*Sj[j]*Yil__1[i]
           temp2[i][j] = temp
           #print temp
    return temp2

#
def printArray( name, _array ):
    print name
    for i in range( len(_array) ):
       print _array[i]
    print "----------------------------------------------------"

def chackIO(_input, _output):
    t = False
    for i in range( len(_input) ):
        if ( (_input[i]*1.0) != _output[i] ):
            t = True
            break
    return t


############main############

numOfInputNode = 8
numOfHidenNode = 3
numOfNeuronNode = 8
dataInput = [0, 0, 1, 0, 1, 0, 1, 0]
weigthX0 = 0.9
a = 0.9
n = 0.9
t = True;
last_weigth_hiden_Neuron = [[0 for i in range(numOfNeuronNode)] for j in range(numOfHidenNode)]
last_weigth_input_hiden = [[0 for i in range(numOfHidenNode)] for j in range(numOfInputNode)]

## step 1. random weigth between input layer and hiden layer
weigth_input_hiden = [[random.random() for i in range(numOfHidenNode)] for j in range(numOfInputNode)]
printArray("Weigth input and hiden", weigth_input_hiden)

## step 2. random weigth between hiden layer and output layer
weigth_hiden_Neuron = [[random.random() for i in range(numOfNeuronNode)] for j in range(numOfHidenNode)]
printArray("Weigth hiden and output", weigth_hiden_Neuron)

while(t):
    ## step 3. Calculate Vj and Yj of Hiden node
    vj_hidenNode = Vjl(weigth_input_hiden, dataInput, numOfHidenNode, weigthX0)
    #print vj_hidenNode
    yj_hidenNode = Yjl(vj_hidenNode)
    #print yj_hidenNode

    ## step 4. Calculate Vj and Yj of Neuron Node
    vj_neuronNode = Vjl(weigth_hiden_Neuron, yj_hidenNode, numOfNeuronNode, weigthX0)
    #print vj_outputNode
    yj_neuronNode = Yjl(vj_neuronNode)
    #print yj_neuronNode

    ## step 5. Calculate Error of Signal from Neuron node
    errorOfNeuron = Ej(dataInput, yj_neuronNode)
    #print errorOfNeuron

    ## step 6. Calculate
    Mj_L = Sj_L(errorOfNeuron, yj_neuronNode)
    #print Mj_L

    ## step 7. Calculate
    Mj_l = Sj_Neural(yj_hidenNode, Mj_L, weigth_hiden_Neuron)
    #print Mj_l

    weigth1 = weigth_hiden_Neuron
    weigth2 = weigth_input_hiden

    weigth_hiden_Neuron = Wji( Mj_L, yj_hidenNode, a, n, weigth_hiden_Neuron, last_weigth_hiden_Neuron )
    weigth_input_hiden = Wji( Mj_l, dataInput, a, n, weigth_input_hiden, last_weigth_input_hiden )

    last_weigth_hiden_Neuron = weigth1
    last_weigth_input_hiden = weigth2

    #printArray("Weigth hiden and output", weigth_hiden_Neuron)
    #printArray("Weigth input and hiden", weigth_input_hiden)

    printArray("Input", dataInput)
    printArray("Output", yj_neuronNode)

    t = chackIO(dataInput, yj_neuronNode)