63 lines
1.3 KiB
Python
63 lines
1.3 KiB
Python
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import numpy as np
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import random
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from sobek.network import network
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random.seed()
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myNetwork = network(2, 1)
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learningRate = 3
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test = []
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result = []
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test[1][1] = 1.0
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test[2][0] = 1.0
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test[3][0] = 1.0
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test[3][1] = 1.0
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result.append(np.ones(1))
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result.append(np.ones(1))
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result.append(np.ones(1))
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result.append(np.zeros(1))
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for j in range(10000):
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inputs = []
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desiredOutputs = []
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if (j%1000 == 0):
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print(j)
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random.shuffle(test)
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for i in range(4):
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if (test[i][0] == 1.0) and (test[i][1] == 1.0):
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result[i][0] = 0.0
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else:
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result[i][0] = 1.0
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myNetwork.train(test, result, learningRate)
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test = []
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result = []
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test.append(np.zeros(2))
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test[1][1] = 1.0
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test[2][0] = 1.0
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test[3][0] = 1.0
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test[3][1] = 1.0
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result.append(np.ones(1))
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result.append(np.ones(1))
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result.append(np.ones(1))
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result.append(np.zeros(1))
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print(myNetwork.weights)
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print(myNetwork.biases)
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print("0 0 : " + str(myNetwork.process(test[0])) + " == 1 ?")
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print("0 1 : " + str(myNetwork.process(test[1])) + " == 1 ?")
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print("1 0 : " + str(myNetwork.process(test[2])) + " == 1 ?")
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print("1 1 : " + str(myNetwork.process(test[3])) + " == 0 ?")
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