human
What is a the Python program you requested given the following:
I am working on the file "SYDE 556 Lecture 9 Action Selection.ipynb".
The first task is:
Better behaviour
But there's still situations where there's too much memory (see the visualizer)
We can reduce this by reducing e
Can you write Python program for it?
assistant
#Here is the Python program you requested.

%pylab inline
import nengo

def stimulus(t):
    if t<.3:
        return [.5,.4]
    elif .3<t<.5:
        return [.3,.5]
    else:
        return [0,0] 
    
model = nengo.Network('Selection')

with model:
    stim = nengo.Node(stimulus)
        
    s = nengo.Ensemble(200, dimensions=2)
    Qs = nengo.networks.EnsembleArray(50, n_ensembles=4)
    Action = nengo.networks.EnsembleArray(50, n_ensembles=4)
    
    nengo.Connection(s, Qs.input, transform=[[1,0],[-1,0],[0,1],[0,-1]])
    nengo.Connection(Qs.output, Action.input)
    
    e = 0.1
    i = -1

    recur = [[e, i, i, i], [i, e, i, i], [i, i, e, i], [i, i, i, e]]    

    def positive(x):
        if x[0]<0: return [0]
        else: return x
    pos = Action.add_output('positive', positive)
    
    nengo.Connection(pos, Action.input, transform=recur)
    
    def select(x):
        if x[0]>=0: return [1]
        else: return [0]
    sel = Action.add_output('select', select)
        
    aValues = nengo.networks.EnsembleArray(50, n_ensembles=4)
    
    nengo.Connection(sel, aValues.input)   
    nengo.Connection(stim, s)
    
    model.config[nengo.Probe].synapse = nengo.Lowpass(0.01)
    qs_p = nengo.Probe(Qs.output)
    action_p = nengo.Probe(Action.output)
    aValues_p = nengo.Probe(aValues.output)
    s_p = nengo.Probe(s)
    
#sim = nengo.Simulator(model)
#sim.run(1.)

from nengo_gui.ipython import IPythonViz
IPythonViz(model, "configs/bg_simple1.py.cfg")