Suresh Pillai wrote:
That's a good comparison for the general question I posed. Thanks.
Although I do believe lists are less than ideal here and a different data
structure should be used.
To be more specific to my case:
As mentioned in my original post, I also have the specific condition that
one does not know which nodes to turn ON until after all the
probabilities are calculated (lets say we take the top m for example).
In this case, the second and third will perform worse as the second one
will require a remove from the list after the fact and the third will
require another loop through the nodes to build the new list.
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It seems like the probability calculation applies to all three equally,
and can therefore be ignored for the simulations. You said that your
algorithm must be a two-stage process: (A) calculate the probabilities
then (B) turn on some nodes. Iain's simulations assume (A) is already
done. He just addressed the performance of (B). Part (A) is invariant
for all his simulations, because your requirement forces it to be.
As for different data structures, it largely depends on how you need to
access the data. If you don't need to index the data, just loop through
it, you might try a linked list. The performance hit in (2) is coming
from the list del; using a linked list would make the removal constant
rather than O(n), and may even execute faster than (3) as well.
-Matt
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