import numpy

#neural network class definition
class neuralNetwork:

    #initialize the neural network
    def __init__(self, inputnodes, hiddennodes, outputnodes, learningrate):
        # set number of nodes in each input, hidden, output layer
        self.inodes = inputnodes
        self.hnodes = hiddennodes
        self.onodes = outputnodes

        #learning rate
        self.lr = learningrate
        pass

    #train the neural network
    def train():
        pass

    #query the neural network
    def query():
        pass

#number of input, hidden and output nodes
input_nodes = 3
hidden_nodes = 3
output_nodes = 3

#learning rate is 0.3
learning_rate = 0.3

#create instance of neural network
n = neuralNetwork(input_nodes, hidden_nodes, output_nodes, learning_rate)

numpy.random.rand(3, 3)-0.5

#link weight matrices, wih and who
#weights inside the arrays are w_i_j, where link is from node i to node j in
the next layer
#w11 w21
#w12 w22 etc
self.wih = (numpy.random.rand(self.hnodes, self.inodes) - 0.5)
self.who = (numpy.random.rand(self.onodes, self.hnodes) - 0.5)