<div dir="ltr">Hi Aditya,<div><br></div><div>The items that you're interested in are accessible in the step between creating the model and simulating it. When you create a simulator with nengo.Simulator(network), Nengo builds the model, which mostly fills in all of the details you're asking about. It exposes the results of building through the same sim.data dictionary as probed information, keyed with the object. I don't think this is documented anywhere though, sorry about that!</div><div><br></div><div>1) After you build the simulator, that data should be available with sim.data[my_ensemble].encoders, sim.data[my_ensemble].intercepts, and sim.data[my_ensemble].max_rates. That should tell you what Nengo's using.</div><div><br></div><div>Nengo does a bit of scaling internally if you pass in a distribution, compared to sampling the distributions and passing them in manually. That might be one source of why these are different for you, but it's hard to know without seeing the exact network.</div><div><br></div><div>2) You need to use probes to get access to the decoders and synaptic weights in a connection as learning is occuring. But, if you want to see the values that are used at the start of the simulation, you can use sim.data[my_connection].decoders (if you're using the latest version from Github, this has recently changed to sim.data[my_connection].weights). If you aren't already doing so, you'll need to store a handle to your connection; e.g., my_connection = nengo.Connection(pre, post).</div><div><br></div><div>Hope that helps,</div><div>Trevor</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Sep 28, 2015 at 3:57 PM, Aditya Gilra <span dir="ltr"><<a href="mailto:aditya_gilra@yahoo.com" target="_blank">aditya_gilra@yahoo.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div style="color:#000;background-color:#fff;font-family:times new roman,new york,times,serif;font-size:14px"><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px">Hi,</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr">I've just started using Nengo (version 2). I would like to know the encoders and decoders used by Nengo2 as below. Or construct them with a utility function.</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px">1) How can I access the encoders, intercepts and max_rates instantiated in an Ensemble? These are not in the probeable list. And in any case, I would like to access them before the simulation is run.</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr">When I construct and set encoders using  UniformHypersphere( surface=True ), and similarly ensembles and maxrates using Uniform(), as per the Ensemble defaults, the variables represented by the population are not as smooth as when Nengo instantiates the encoders itself. How do I know what Nengo used?</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr">2) How can I access the decoders and synaptic weights learnt/instantiated in a Connection given a transformation / function? decoders are in probeable, but ideally I'd like to know them while constructing my network, not after the simulation. Or maybe there's a utility function I can call that returns these without actually making a Connection.</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr"><br></div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr">Thanks,</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr">Aditya.</div><div style="color:rgb(34,34,34);font-family:arial,sans-serif;font-size:12.8px" dir="ltr"><br></div></div></div><br>_______________________________________________<br>
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