wrapc does look plausible - to avoid memory problems we could break
the processing of the problematic line so it chews on smaller chunks
of data.

And, I am expecting that one step of iteration have a computational
cost which is a multiple of the square of the number of distinct nodes
reached so far - I think that that's wired into the specification.

Anyways, I need to be doing real work, right now, not having fun, so
I'll have to come back to this later.

Thanks,

-- 
Raul

On Fri, Feb 15, 2013 at 2:55 PM, Mike Day <[email protected]> wrote:
> Yes,  "tree" is not the best word, though it does hint at the existence of
> branches - however its structure doesn't reveal the links.   Each row is a
> sorted list, I suppose. Whatever we call it,  I think you've got a big
> problem in finding all such "things" each with 100 unique members,  in a
> 2000-node graph.  At least I don't yet see how to do it given the memory
> problems at N=11!
>
> Better to look at wrapc than wrapb,  I suggest.  It does nub after sorting
> the lists as you suggest.
>
> I'm about to do the Times Listener Crossword now (a numerical one this
> week!) so won't be path hunting for a while.
>
> Good luck
>
> Mike
>
>
> On 15/02/2013 7:19 PM, Raul Miller wrote:
>>
>> Thank you, again.
>>
>> I have not yet had time to read through wrapb, but a quick glance
>> suggests that the "too many paths (or 'trees', maybe )" issue could
>> probably be resolved by sorting each "path" before determining
>> uniqueness.
>>
>> That said, I am more uncomfortable labelling these "visitable sets"
>> with the word "trees" rather than "paths".  A tree would imply, to me,
>> that I've retained a particular connection structure, and all I care
>> about is whether the node has been visited. Perhaps I should model
>> this as "when a connection is used the reverse connection is also made
>> available in the context of that path" - actually implementing that
>> seems computationally inefficient, but it would resolve the conflict
>> between this use of the word "path" and its use in other graph
>> problems.
>>
>> Thanks,
>>
>
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