nengo_fifth_test

# based on https://www.nengo.ai/nengo/examples/basic/combining.html
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="2D representation")

with model:
    A = nengo.Ensemble(100, dimensions=1) #neurons, dimensions
    B = 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))
    sin = nengo.Node(output=np.sin)
    cos = nengo.Node(output=np.cos)

    #****************
    # 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(sin, A)
    nengo.Connection(cos, B)

    nengo.Connection(A, output[0])
    nengo.Connection(B, output[1])

    #****************
    # PROBES
    #****************
    # The original input
    #input_signal_probe = nengo.Probe(input_signal)
    sin_probe = nengo.Probe(sin, "output")
    cos_probe = nengo.Probe(cos, "output")

    A_probe = nengo.Probe(A, synapse=0.01)  # 10ms filter
    B_probe = nengo.Probe(B, synapse=0.01)  # 10ms filter
    out_probe = nengo.Probe(output, 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[out_probe][:, 0], "b", label="2D output[0]")
plt.plot(sim.trange(), sim.data[out_probe][:, 1], "g", label="2D output[1]")
plt.plot(sim.trange(), sim.data[A_probe], "r", label="A output")
plt.plot(sim.trange(), sim.data[sin_probe], "k", label="Sine")

plt.legend()
plt.show()