Created
August 2, 2014 09:13
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Under developing python code for NNEQ when XOR is used for testing
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import matplotlib.pyplot as plt | |
# input is 1, 0 | |
def NNEQ( x1, x2, w1, w2): | |
y = x1 * w1 + x2 * w2 | |
return y | |
def NNEQ_bias( x1, x2, w1, w2, w_bias): | |
y = x1 * w1 + x2 * w2 + w_bias | |
return y | |
def Desired_linaer_bias( x1, x2): | |
return x1 - 0.5 * x2 + 1.0 | |
def Desired_xor( x1, x2): | |
return x1 ^ x2 | |
def Desired( x1, x2): | |
return Desired_xor( x1, x2) | |
def Loop( w1, w2, mu = 0.01, iter_all = 100): | |
for iter in range( iter_all): | |
print '---------------' | |
print 'Iteration = ', iter | |
for x1 in [0, 1]: | |
for x2 in [0, 1]: | |
# This is computation part. | |
out = NNEQ( x1, x2, w1, w2) | |
des = Desired( x1, x2) | |
err = des - out | |
# This is calculation part | |
print 'x1, x2 =', x1, x2 | |
print 'w1, w2 =', w1, w2 | |
print 'Output = ', NNEQ( x1, x2, 0, 0) | |
print 'Desired = ', Desired( x1, x2) | |
print 'Error = ', err | |
# This is update part. | |
w1 = w1 + mu * err * x1 | |
w2 = w2 + mu * err * x2 | |
def LoopTrack( w1, w2, mu = 0.01, iter_all = 10): | |
# Tracking is started. | |
err_array = [] | |
for it in range( iter_all): | |
print '---------------' | |
print 'Iteration = ', it | |
for x1 in [0, 1]: | |
for x2 in [0, 1]: | |
# This is computation part. | |
out = NNEQ( x1, x2, w1, w2) | |
des = Desired( x1, x2) | |
err = des - out | |
# This is calculation part | |
print 'x1, x2 =', x1, x2 | |
print 'w1, w2 =', w1, w2 | |
print 'Output = ', NNEQ( x1, x2, 0, 0) | |
print 'Desired = ', Desired( x1, x2) | |
print 'Error = ', err | |
# This is update part. | |
w1 = w1 + mu * err * x1 | |
w2 = w2 + mu * err * x2 | |
err_array.append( err) | |
return err_array | |
def LoopTrack_bias( w1, w2, w_bias, mu = 0.01, iter_all = 10): | |
# Tracking is started. | |
err_array = [] | |
for it in range( iter_all): | |
# print '---------------' | |
# print 'Iteration = ', it | |
for x1 in [0, 1]: | |
for x2 in [0, 1]: | |
# This is computation part. | |
out = NNEQ_bias( x1, x2, w1, w2, w_bias) | |
des = Desired( x1, x2) | |
err = des - out | |
# This is calculation part | |
""" print 'x1, x2 =', x1, x2 | |
print 'w1, w2, w_bias =', w1, w2, w_bias | |
print 'Output = ', out | |
print 'Desired = ', des | |
print 'Error = ', err """ | |
# This is update part. | |
w1 = w1 + mu * err * x1 | |
w2 = w2 + mu * err * x2 | |
w_bias = w_bias + mu * err * 1 | |
err_array.append( err) | |
return err_array | |
#This is main function | |
def main_1st(): # 2017-8-2 5:47pm | |
w = [0, 0] | |
Loop( w[0], w[1]) | |
def main_2nd(): | |
w = [0.5, -0.5] | |
err_array = LoopTrack( w[0], w[1], mu = 0.02) | |
print err_array | |
plt.plot( err_array) | |
plt.show() | |
def main_3rd(): | |
w = [0.5, -0.5, 0.5] # the last element is bias value. | |
err_array = LoopTrack_bias( w[0], w[1], w[2], mu = 0.02, iter_all = 100) | |
# print err_array | |
plt.plot( err_array, '.-') | |
plt.show() | |
main_3rd() | |
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