Yokohama deep learning 03

import numpy as np

class Neuron:
    def __init__(self, w, b, f):
        self.w = np.concatenate((w, b), axis =1)
        self.f = f
    
    def output(self, x):
        x = np.concatenate((x, [[1,],]))
        return self.f(self.w.dot(x))
    
def f(u):
        u[u>0] = 1
        u[u<=0] = -1
        return u
    
if __name__ == '__main__':
    neuron = Neuron([[1,],],[[0.1,],], f)
    print(neuron.output([[-0.1,],]))
    
    neuron  = Neuron ([[0.5, 0.8, ],[-0.1, -0.3,]],[[0.1,],[0.1, ]], f)
    print(neuron.output([[-1,],[0.2, ]]))