nengo-sixth_test

import matplotlib.pyplot as plt
import numpy as np
import nengo
from nengo.dists import Uniform
from nengo.utils.matplotlib import rasterplot


model = nengo.Network(label="overlay_test")

with model:
    A = nengo.Ensemble(100, dimensions=1) #neurons, dimensions
    B = nengo.Ensemble(100, dimensions=1) #neurons, dimensions
    C = nengo.Ensemble(100, dimensions=1) #neurons, dimensions

    output = nengo.Ensemble(100, dimensions=2, label="2D Population") #neurons, dimensions

    #****************
    # PROVIDE INPUT
    #****************
    #input_signal = nengo.Node(lambda t: np.cos(8 * t))
    input_a = nengo.Node(output=0.5)
    input_b = nengo.Node(output=0.3)

    #****************
    # CONNECT ELEMENTS
    #****************
    #Connect the input signal to the neuron
    # The indices in neurons define which dimension the input will project to

    #nengo.Connection(input_signal, A, synapse=0.01)
    #nengo.Connection(sin, neurons[0])
    #nengo.Connection(cos, neurons[1])
    nengo.Connection(input_a, A)
    nengo.Connection(input_b, B)


    nengo.Connection(A, C)
    nengo.Connection(B, C)

    #****************
    # PROBES
    #****************
    # The original input
    #input_signal_probe = nengo.Probe(input_signal)
    input_a_probe = nengo.Probe(input_a)
    input_b_probe = nengo.Probe(input_b)

    A_probe = nengo.Probe(A, synapse=0.01)  # 10ms filter
    B_probe = nengo.Probe(B, synapse=0.01)  # 10ms filter
    C_probe = nengo.Probe(C, synapse=0.01)  # 10ms filter


with nengo.Simulator(model) as sim:  # Create the simulator
    #****************
    # Run
    #****************
    sim.run(5)  # Run it for 1 second

#****************
# plot the results
#****************
t =  sim.trange()
# Plot the decoded output of the ensemble


plt.figure()

plt.plot(sim.trange(), sim.data[input_a_probe], label="input a")
plt.plot(sim.trange(), sim.data[input_b_probe], label="input b")

plt.plot(sim.trange(), sim.data[A_probe], label="A output")
plt.plot(sim.trange(), sim.data[B_probe], label="B output")
plt.plot(sim.trange(), sim.data[C_probe], label="C output")


plt.legend()
plt.show()