[nengo-user] obtaining encoders and decoders used by Ensemble / Connection in Nengo2?

[Trevor Bekolay]

Hi Aditya,

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!

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.

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.

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).

Hope that helps,
Trevor

On Mon, Sep 28, 2015 at 3:57 PM, Aditya Gilra <aditya_gilra at yahoo.com>
wrote:

> Hi,
>
> 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.
>
> 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.
>
> 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?
>
> 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.
>
> Thanks,
> Aditya.
>
>
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