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propose nodes to merge non-uniformly #60
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Worked on this a bit today. As of now, using the guided merge pair proposal gives:
And the uniform pair proposal is giving:
This is with --bl-opt-steps 5 in both cases. |
Interesting. I do think that topology (rather than distance) guided proposals have some I think the current formulation in smctex is correct, but will check it 2012/11/12 Aaron Darling notifications@github.com
Frederick "Erick" Matsen, Assistant Member |
Well, I'm not sure the distance guide is implemented correctly just yet, and even if it is, it's not clear that its much better than uniform merging. 50LL units could be within the realm of normal run-to-run variation. One thing I'm noticing is that even though ESS is a little higher at the first few iters with the guided prop, that seems to get wiped out by iter 5. This could be that the bias distribution fails to adapt in the current implementation, or could be that distance bias is no longer useful after the first few joins, or a bit of both. The topology bias would surely guide proposal of internal nodes and anywhere that short internal branches make choosing close pairs of nodes to merge based on distance ambiguous or misleading. But I think for the first few iters under the natural forest extension, the topology guide only reduces our O(n^2) possible pairs problem to somewhere between O(n) and O(1) depending on topology while the distance guide may get us a little closer to O(1). Maybe the real underlying problem is the natural forest extension?? |
Hm, interesting. As I think you already note, the thing that scares me about a distance I'll also review and flesh out the smctex section on simulations on the On Tue, Nov 13, 2012 at 8:02 AM, Aaron Darling notifications@github.comwrote:
Frederick "Erick" Matsen, Assistant Member |
Do you think the distance approach is going to prevent the correct merge from being selected in such cases? Or will it just be less informative/efficient than a topology-guide? |
Less informative/efficient. I just made a pass through the smctex manuscript and I'm happy with the On Tue, Nov 13, 2012 at 9:14 AM, Aaron Darling notifications@github.comwrote:
Frederick "Erick" Matsen, Assistant Member |
w00t, only 100 log units to go baby!
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... and check out those ESS's! 2012/12/9 Aaron Darling notifications@github.com
Frederick "Erick" Matsen, Assistant Member |
yeah, the ESS really did come up. i guess the proposals are almost all equally good (or equally bad) under the natural forest extension. :^) |
Eked out another 40 log units with c700db8 : |
@koadman -- AG has implemented a nice way of visualizing particle history in sts-log-graph branch. I'd be curious about what your runs look like. |
good idea! trying to do it but having some trouble with the grapher:
I posted the log file in question here: This is based on a fork of master from a while back, has the log format changed? |
Did you just grab that script? You will need to merge in that branch in order to use it. There are some In fact, merging that branch into master then merging master into your On Tue, Dec 11, 2012 at 7:32 AM, Aaron Darling notifications@github.comwrote:
Frederick "Erick" Matsen, Assistant Member |
I think Erick's right about needing more than the script...it works on our http://cl.ly/image/322W47053h0Y/bobo10.png On Tue, Dec 11, 2012 at 8:06 AM, Erick Matsen notifications@github.comwrote:
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thanks for the graph link. any ideas on how it compares to others? i'll work on the merges... |
pretty sobering that all but 1 final generation particles in that graph have a common ancestor only 3 generations ago. dear great grandma: your particles need recombination! |
Seems a lot better than master: http://cl.ly/image/3d203R1D281e/thirty.master.png |
FYI, Aaron, http://cl.ly/image/3d203R1D281e/thirty.master.png was called |
I love it! |
At early generations there are a very large number O(n^2) of possible node pairs to merge and a very small number of good merge pairs O(1). This causes most of the particles produced in early generations to have low likelihood.
Rather than proposing joins uniformly we could bias the proposal toward joins that produce a high LL under the natural forest extension. In general these will be nodes with short branches in the true tree. One way to obtain a proposal distribution is to calculate all internode distances from a FastTree guide tree and use the inverse of distances to generate a sampling distribution for leaf pairs. At each merge, a pair could be sampled. If they are part of different trees in the forest, their trees could be joined at the root. If they belong to the same tree, zero or more additional proposals could be made until a valid merge is found. If a valid merge is not found, this proposal could fall back to the uniform merge.
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