Re: [Yt-dev] Geometry, RAMSES and non-patch datasets
Hi,
This is in reply to Matt's e-mail from 3 weeks ago (I only just realised
I forgot to hit "confirm" on the yt-dev mailing list signup).
I guess one solution to the problem would be to abstract what a "grid"
is (I'm guessing a grid is a container for a geometrically consistent
chunk of the entire simulation volume?) Then allow it to answer queries
about its geometric properties itself. So for example, ask it
"myGrid.IsInRegion(myWeirdGeometricConstruct)". I guess the trick is to
figure out a flexible but simple interface for this, depending on how
well you know the requirements for what the grid should be able to do.
In general, I think this is the ideal situation, because as Matt says
hammering every code into the same structure in memory creates
slowdowns. One possibility is to create a few template memory
structures, etc, to allow people to bolt together new implementations
for each code.
In terms of choosing algorithms for different types of fluid blob (e.g.
one for particles, one for grids), this can be done using functionoids
for the algorithms (or at least functionoid wrappers) and then a
functionoid factory for spawning the correct functionoid to use with the
container. You'd have to wrap all this up in a simple interface again,
otherwise it'd be impossible to use.
I also suggested to Matt to create a "fluid blob" iterator that works
for all types of fluid blob (SPH particle, octree grid cell, voronoi
tessellation cell) but this might be very slow in Python. That said,
iterating over "grid"s as chunks of the amr grid instead is a
possibility. Having some kind of iterator option might be good, though,
as doing things like tracking particles through different snapshots is
something I've been doing extensively in my (pre-YT) work.
I don't know how much of this is already known; my domain is Ramses,
which is still very slow to use with my dataset (although Matthew has
been very helpful in working on the Ramses side of things). I thus
haven't looked too much at YT yet as it's still prohibitively slow to
load my dataset and play with it.
Cheers,
Sam
On Tue, Jun 7, 2011 at 16:15 AM, Matthew Turk
participants (3)
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j s oishi
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Matthew Turk
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Sam Geen