Perceptron

import math


trainFile = open("E:\\Studies\\4-2\\Pattern Recognition Sessional\\Train.txt", "r")

dataSet = []
weights = []

numOfFeatures = 3;
numOfClasses = 3;

LABEL_INDEX = numOfFeatures + 1;
PUNISH = -1;
REWARD = 1;
RO = 1;


def findLabel (sample, weights):
    label = 0;
    maxVal = -math.inf
    for i in range (numOfClasses):
        val = 1;
        for j in range(numOfFeatures + 1):
            val += sample[j]*weights[i][j]
        if val > maxVal:
            label = i;
            maxVal = val;
    return label+1  #classes are 1,2.. || you calculated 0,1...


def updateWeight (weightID, sample, type):  #type : punish = -1, reward = +1
    for i in range (numOfFeatures + 1):
        weights[weightID][i] += RO*type*sample[i]


def prepareDataset():
    count = 0;
    for line in trainFile:
         count+=1;
         if(count==1):  #dont take the first line
             continue
         sample = []
         for s in line.split():
             try:
                 sample.append(float(s))
             except ValueError:
                 pass
         if(len(sample)==numOfFeatures+1):
             sample.insert(numOfFeatures, 1)   #bias
             dataSet.append(sample)


def inintializeWeights():
    for i in range (numOfClasses):
        w = []
        for j in range (numOfFeatures):
            w.append(0)
        w.append(1)
        weights.append(w)



def main ():
    prepareDataset()
    inintializeWeights()

    for sample in dataSet:
        result = findLabel(sample, weights)
        print(sample, result)
        if (result != sample[LABEL_INDEX]):
            updateWeight(int(result)-1, sample, PUNISH)
            updateWeight(int(sample[LABEL_INDEX])-1, sample, REWARD)


    print("So the final vectors are:")
    for w in weights:
        print(w)

#main()