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Re: [igraph] searching by node index: runtime analysis


From: Ahmed Abdeen Hamed
Subject: Re: [igraph] searching by node index: runtime analysis
Date: Mon, 5 Jan 2015 17:54:38 -0500

Great to receive this clarification, thank you!

If I now call the get_shortest_paths(id_a, id_b), from within the algorithm, to find all shortest paths. What is the runtime analysis for this one? I found in this 2 years old publication that it can be done in O(n^2.4) vs O(n^3) ["http://www.utdallas.edu/~edsha/papers/bin/ISCA03.pdf"]. Have you guys done this with better runtime? or I should report O(n^2.4) as the official runtime?

Thanks again :-)


-Ahmed




On Mon, Jan 5, 2015 at 4:43 PM, Tamas Nepusz <address@hidden> wrote:
> I did mean the Python implementation yes. If this is the case, what the
> runtime complexity for 2 vertices if we use g.vs.find("name")?
Same as a lookup in a Python dictionary. According to the Python wiki, lookups
are O(1) on average in a Python dictionary, although it could be O(n) amortized
worst case (but you shouldn't need to worry about this):

https://wiki.python.org/moin/TimeComplexity

However, I wouldn't fret about that too much if you are just describing
a generic algorithm -- the point is that you _could_ do a name-to-index lookup
in O(1) on average if you use a hash table, even if the particular Python
dictionary implementation does not use a hash table. So, in your publication,
you could simply say that name-to-index lookups can be done in O(1) without
mentioning that igraph _happens_ to use a Python dict for this. If I were lazy
and did not implement this in the Python interface, it would not make your
algorithm any worse, although it would make the _implementation_ of your
algorithm worse of course.

All the best,
Tamas

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