I would go over the properties of the SP and create tests accordingly. The
output, for instance, should be tolerant to spatial noise. So show an
instance a set of very different spatial patterns over and over a number of
times. Then show one of the patterns with a single bit flipped and make
sure the output is very close (possibly identical if columns are saturated)
to the same.

There are a bunch of similar things you could check.

Ian had a hackathon demo showing the connected bits for each column. He was
able to validate different aspects of the SP visually by using different
numbers of columns and % overlap.

You could do something similar to make sure you see the right behavior but
I don't know if you could make an automated test out of it.

http://numenta.org/blog/2013/11/06/2013-fall-hackathon-outcome.html#sp_viewer
On Feb 4, 2014 11:23 AM, "Jeff Hawkins" <[email protected]> wrote:

> Kevin,
>
> Adding on to what Fergal said....
>
>
>
> Here is what we did.  We started with a fixed number of columns and no
> topology.  In this situation we picked the n% most innervated columns as
> the output of the SP.  Thus we were *guaranteed* to get the correct
> sparsity of active columns.  With this setup we did a lot of other tests to
> verify that the SP was forming good representations.
>
>
>
> The tricky part is if you want to do this with topology and local learning
> rules.   Is that your concern?
>
>
>
> With topology we didn't try to guarantee the entire layer of cells will
> have exactly n% active columns.  Exact numbers are not essential.  We tried
> several different local learning rules, all of them produced about the
> right level of sparsity.  We than ran the other tests to make sure that
> local learning rules didn't cause the SP to form poor representations.  You
> won't get exactly the same results with topology and without topology but
> my recollection was we were able to come up with a set of local inhibition
> rules that produced good results.
>
> Jeff
>
>
>
> *From:* nupic [mailto:[email protected]] *On Behalf Of *Fergal
> Byrne
> *Sent:* Tuesday, February 04, 2014 10:43 AM
> *To:* NuPIC general mailing list.
> *Subject:* Re: [nupic-discuss] Tests for spatial pooling
>
>
>
> Hi Kevin,
>
>
>
> If you're using no topology (and no local inhibition) then the fraction of
> active columns (2% in NuPIC) is the only important factor. With topology,
> you should choose winners relative to their neighbours. In either case, the
> first test is to count the fraction of active columns. In the second case,
> measure the average distance between active columns.
>
>
>
> Regards,
>
>
>
> Fergal Byrne
>
>
>
> On Tue, Feb 4, 2014 at 6:05 PM, Kevin Martin <[email protected]>
> wrote:
>
> Hi,
>
> I'm writing my own version of the CLA. I have not reached anywhere
> significant and I have been playing with a very small number of columns
> until now. I am starting by implementing a spatial pooler and spatial
> pooling requires a large number of columns. So far it has been easy to
> manually check if the synapses are distributed throughout the input, if the
> winning columns are really sparse etc. But it is going to be impossible
> when, say,I use 1000 columns. Have somebody used a test to check if the
> spatial pooler outputs a sparse distribution? Any suggestions on how to
> write a test?
>
> Thanks,
>
> Kevin Martin Jose
>
>
> _______________________________________________
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>
>
>
>
>
> --
>
>
> Fergal Byrne, Brenter IT
>
>
>
> http://inbits.com - Better Living through Thoughtful Technology
>
>
>
> e:[email protected] t:+353 83 4214179
>
> Formerly of Adnet [email protected] http://www.adnet.ie
>
> _______________________________________________
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>
>
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