def build(self):
# check if we have the legal dimension
if self.x == 0:
print('ERROR! You have to assign a cluster size.')
# 1-dimensional
elif self.y == 0:
for i in range(self.x):
self.cluster.append(Neurons.LIF())
# check whether the cluster size is correct
if len(self.cluster) != self.x:
print('ERROR! Size of cluster is not correct.')
self.dimension = 1
# 2-dimensional
else:
for i in range(self.x):
self.cluster.append([])
for j in range(self.y):
self.cluster[i].append(Neurons.LIF())
# check whether the cluster size is correct
if len(self.cluster) * len(self.cluster[0]) != self.x * self.y:
print('ERROR! Size of cluster is not correct.')
self.dimension = 2
# @Email : [email protected] # @GitHub : https://github.com/hello-roderickwang import Neurons import Synapse import Cluster import numpy as np import matplotlib.pyplot as plt if __name__ == '__main__': x = np.linspace(-np.pi, np.pi, 201) sin = (np.sin(x)+1)/2 a = Neurons.LIF() b = Neurons.LIF() weight = 2 connection = Synapse.Synapse(a, b) connection.set_weight(weight) v_a = [] v_b = [] for step in range(0, len(sin)): a.stimulate(sin[step]) a.go() v_a.append(a.out) connection.go()