import numpy as np
import random

def step(x):
    if x < 0:
        res = 0
    else:
        res = 1
        
    return res

step(0)

step(-1)

step(1)

train = [(np.array([0, 0, 1]), 0), (np.array([0, 1, 1]), 1), (np.array([1, 0, 1]), 1), (np.array([1, 1, 1]), 1)]
train2 = [(np.array([0, 0, 1]), 0), (np.array([0, 1, 1]), 0), (np.array([1, 0, 1]), 0), (np.array([1, 1, 1]), 1)]

train

train2

randNumWeight = np.random.rand(3)
randNumWeight2 = np.random.rand(3)

print "OR weights (random number array)", randNumWeight
print "AND weights(random number array)", randNumWeight2

learnRate = 0.1
itter = 10000

a = random.choice(train)
a2 = random.choice(train2)

print "OR:", a
print "AND:", a2
print "\n"
print randNumWeight
print randNumWeight2

for i in xrange(itter):
    a, b = random.choice(train)
    a2, b2 = random.choice(train2)
    c = np.dot(randNumWeight, a)
    c2 = np.dot(randNumWeight2, a2)
    err = b - step(c)
    err2 = b2 - step(c2)
    randNumWeight += learnRate * err * a
    randNumWeight2 += learnRate * err2 * a2

print "\n"
print "Results for logical OR"
print "\n"
for x, c in train:
    c = dot(x, randNumWeight)
    print "Logical Input: ", x[:2]
    print "Update Weight: ", c
    print "Logical Result: ", step(c)
    print "\n"
    
print "\n"
print "Results for logical AND"
print "\n"
for x, c2 in train2:
    c2 = dot(x, randNumWeight2)
    print "Logical Input: ", x[:2]
    print "Update Weight: ", c2
    print "Logical Result: ", step(c2)
    print "\n"