mag=1),
n_basis=n_basis_2d,
n_samples=n_samples)
model = nengo.Network(seed=13)
model.config[nengo.Ensemble].neuron_type = nengo.Direct(
) #TODO: temp, just use direct for debugging
ps_neuron_type = nengo.LIF(
) #nengo.Direct()#nengo.LIF() # neuron type for posecells
with model:
# Node that handles ROS communication
# in: best_x, best_y, best_th
# out: vtrans, vrot, stim_x, stim_y, stim_th, energy
if __name__ == '__main__':
posecell_node = nengo.Node(NengoPosecellNetwork(),
size_in=3,
size_out=6)
else: # ROS can't register signals within nengo_gui
posecell_node = nengo.Node(NengoPosecellNetwork(disable_signals=True),
size_in=3,
size_out=6)
# Splitting posecell network into x, y, and th components to reduce
# computational burden. Some representational power is lost, but it is
# hopefully good enough to still work.
posecells_xy = nengo.Ensemble(n_neurons=n_neurons_xy,
dimensions=fs2d.n_basis + 2,
neuron_type=ps_neuron_type)
posecells_xy.encoders = nengo.dists.Combined([
fs2d.project(
return x[0] * np.cos(x[1])
def y_component(x):
# convert trans velocity into y component
return x[0] * np.sin(x[1])
model = nengo.Network(seed=13)
model.config[nengo.Ensemble].neuron_type = nengo.Direct() #TODO: temp, just use direct for debugging
ps_neuron_type = nengo.LIF() # neuron type for posecells
with model:
# Node that handles ROS communication
# in: best_x, best_y, best_th
# out: vtrans, vrot, stim_x, stim_y, stim_th, energy
if __name__ == '__main__':
posecell_node = nengo.Node(NengoPosecellNetwork(), size_in=3, size_out=6)
else: # ROS can't register signals within nengo_gui
posecell_node = nengo.Node(NengoPosecellNetwork(disable_signals=True), size_in=3, size_out=6)
# Splitting posecell network into x, y, and th components to reduce
# computational burden. Some representational power is lost, but it is
# hopefully good enough to still work.
#posecells_x = nengo.Ensemble(n_neurons=n_neurons, dimensions=3, neuron_type=ps_neuron_type)
posecells = nengo.Ensemble(n_neurons=n_neurons, dimensions=4, neuron_type=ps_neuron_type)
#posecells_th = nengo.Ensemble(n_neurons=n_neurons, dimensions=3,neuron_type=ps_neuron_type)
#added
#posecells_xy=nengo.Ensemble(n_neurons=n_neurons, dimensions=3, neuron_type=ps_neuron_type)
# Handles injected current
stim = nengo.Ensemble(100, 2)