Call custom function on Object at every timestep

Getting Started
5

Thanks again for all your input!

First, I’d like to signal a bug I’ve found in nengo_extra.graphviz.net_diagram(): with the updated code you posted, I’m getting the following output graph:
test.gv
but nengo_gui renders correctly.

Returning to my problem, with this setup the input to memristor_plus and memristor_minus are the weights associated to each neuron in the pre ensemble? Or the some sort of “neural activity” (what does this term mean in this context, exactly?)?
I have checked the output of the pre = nengo.Ensemble(100, dimensions=1, label="Pre") population and it is a (100,) vector. What does each element represent, exactly?

I’m asking this because I’m trying to understand how to actually “filter” using the memristor function:

# filter the input
def filter( self, t, x ):
    self.history.append( self.R )
    
    # scale weights for filtering
    w = (self.R - self.r0) / (self.r1 - self.r0)
    
    import time
    time.sleep(0.01)
    
    return w * x

Until I’m sure what x actually is, I’ll have some trouble conceptualising if what I’m doing is correct or not…

Thanks again!