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RIVET plots of metric data #139

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delooper opened this issue Oct 7, 2018 · 8 comments
Closed

RIVET plots of metric data #139

delooper opened this issue Oct 7, 2018 · 8 comments

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@delooper
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delooper commented Oct 7, 2018

When I ask rivet to compute the persistent homology of a finite metric space with a secondary parameter I notice one odd feature. In the RIPS complex direction (in the line selection window, let me call this parameter epsilon) the minimum epsilon value chosen appears to be the minimum distance between all distinct pairs of points in my point cloud.

Wouldn't it be more natural to start at epsilon=0? Then along the epsilon=0 line you would see the number of points in your point cloud. With the way RIVET is set up right now, if I compute the PH of a 400-point point cloud, the min(epsilon) line often has ranks much smaller than 400, even when the secondary parameter includes all the points.

@mlesnick
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mlesnick commented Oct 7, 2018 via email

@delooper
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delooper commented Oct 7, 2018

Thanks. Yes I'm coarsening.

I'll try re-running my computations without coarsening but I was having some memory issues, so it might not work.

@delooper
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delooper commented Oct 8, 2018

Okay, I see why I was coarsening. My laptop is frozen by swapping.

@delooper
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delooper commented Oct 9, 2018

If I make the plot using rivet_python (calling rivet_console with the --betti option) I can plot the epsilon=0 line, even with coarsening. This suits my needs better than using the RIVET GUI.

@mlesnick
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For data sets of non-negligible size, we do expect the RIVET augmented arrangement computation to eat too much memory if it is run without coarsening. For a computation run with the --betti or --minpres flags, the situation should be better. However, see issue #104.

@delooper
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I don't understand the internals well-enough I suppose but I have found one thing to be curious. If I use no coarsening RIVET tends to use much more memory compared to using an extremely fine mesh with coarsening. i.e. like -x 400 -y 400 compared with no coarsening at all.

I imagine what's going on is that my data perhaps fairly irregular set of pairs of distances. So the grid (with no coarsening) is likely enormous. Perhaps more like -x 40000 -y 40000

@mlesnick
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That's consistent what I'd expect. You usually get a very large grid with no coarsening, and that leads to huge line arrangements. Did you also have memory problems with no coarsening for your examples even using --Betti?

@mlesnick
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mlesnick commented May 3, 2019

This is Issue #84.

@mlesnick mlesnick closed this as completed May 3, 2019
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