Count how many Loihi neurons are redundant

test_redundant_neurons.py

import matplotlib.pyplot as plt
import numpy as np
import nengo
import nengo_loihi


def test(n_trials=3):
    neurons = np.logspace(1, 3, 20).astype(int)

    result = np.zeros((len(neurons), n_trials))
    for i, n in enumerate(neurons):
        for k in range(n_trials):
            with nengo.Network() as net:
                nengo_loihi.config.set_defaults()

                u = nengo.Node(1.)
                a = nengo.Ensemble(n, 1)
                c = nengo.Connection(u, a)

            with nengo_loihi.Simulator(net) as sim:

                block = sim.model.objs[a.neurons]['out']
                comp = block.compartment
                assert len(block.synapses) == 1
                syn = block.synapses[0]
                keys = list(zip(comp.bias, syn.weights[0][0]))

            result[i, k] = len(np.unique(keys, axis=0)) / n

    return neurons, result


neurons, result = test(n_trials=5)

plt.semilogx(neurons, result.mean(axis=1))
plt.semilogx(neurons, result.max(axis=1))
plt.semilogx(neurons, result.min(axis=1))
plt.show()