import numpy as np


# iamtrask.github.io/2015/07/12/basic-python-network/

# ramalan cuaca
#
# 0 = cerah
# 1 = hujan
# 2 = mendung
#
#
# suhu
# 0 = panas
# 1 = sejuk
# 2 = dingin
#
#
# kelembaban
# 0 = tinggi
# 1 = normal
#
#
# angin
#
# 0 = ;emah
# 1 = kuat
#
#
#
# target
# 0 = tidak
# 1 = main



# fungsi sigmoid

def nonlin(x,deriv=False):
    if(deriv==True):
        return x*(1-x)
    return 1/(1+np.exp(-x))


# situasi cuaca
source  = np.array([
        [0,0,0,0],
       [0,0,0,1],
       [2,0,0,0],
       [1,1,0,0],
       [1,2,1,0],
       [1,2,0,1],
       [2,3,1,1],
       [0,1,0,0],
       [0,2,1,0],
       [1,1,1,0],
       [0,1,1,1],
       [2,1,0,1],
       [2,0,1,0],
       [1,1,0,1]
    ])

# target berermain
target = np.array([[0,0,1,1,1,0,1,0,1,1,1,1,1,0]]).T

np.random.seed(1)

syn0 = 2*np.random.random((4, 14)) - 1


# iterasi
for iter in xrange(10000):

    l0 = source
    l1 = nonlin(np.dot(l0,syn0))

    l1_error = target  - l1

    l1_delta = l1_error * nonlin(l1,True)

    syn0 += np.dot(l0.T,l1_delta)


print "Output After Training:"
print l1