Layer

import numpy as np
class Layer:
    def __init__(self):
        self.input = np.matrix([]).astype(np.float)

        self.output = np.matrix([]).astype(np.float)

class affineLayer(Layer):
    def __init__(self, neuronsNumber, inputsPerNeuron, isBias, functionName):
        super(affineLayer,self).__init__()

        self.weights = np.asmatrix(np.random.random((neuronsNumber, inputsPerNeuron))).astype(np.float)
            # (2 * np.asmatrix(np.random.random((neuronsNumber, inputsPerNeuron))).astype(np.float) - 1) / 16

        self.weightsChanges = np.asmatrix(np.zeros((neuronsNumber, inputsPerNeuron))).astype(np.float)

        self.isBias = isBias
        if(self.isBias):
            self.bias = np.asmatrix(np.random.random((neuronsNumber, 1))).astype(np.float)
                # (2 * np.asmatrix(np.random.random((neuronsNumber, 1))).astype(np.float) - 1) / 16

            self.biasChanges = np.asmatrix(np.zeros((neuronsNumber, 1))).astype(np.float)

        self.z = np.matrix([]).astype(np.float)

        self.error = np.matrix([]).astype(np.float)
        self.activator = functionName

class rbfLayer(Layer):
    def __init__(self,centroids,widths):
        super(rbfLayer, self).__init__()
        self.centroids = centroids
        self.widths = widths