[Yt-dev] filters for DerivedQuantities

Matthew Turk matthewturk at gmail.com
Thu Aug 26 07:37:31 PDT 2010


Hi John,

On Thu, Aug 26, 2010 at 7:00 AM, John Wise <jwise at astro.princeton.edu> wrote:
> Hi,
>
> I wanted to calculate volume filling fractions and mass fractions of gas that met some criteria.  Specifically, the fractions that have a certain metallicity.  The _Action routine looked promising, but I couldn't figure out how to use it.  I remember there was some talk about filters on the list, but I searched and found that it concerned the halo finder.
>
> I might have reinvented the wheel, but this is how I did it.
>
> http://paste.enzotools.org/show/1125/
>
> It's basically _TotalQuantity with a filter.  Also I wanted it to accept multiple limits to avoid re-reading the data for every filter.
>
> Was there an easier way to do this?

I think your best bet might be to use cut_region on a data object.
This accepts a list of filters and uses them as input to the data
region.

http://yt.enzotools.org/doc/api/generated/data_sources/yt.lagos.AMR3DData.cut_region.html

It's poorly documented, but I really think it's a useful object and
technique.  I'll fix this documentation issue ...  but it actually
performs the cuts as you go, rather than pre-storing a list of cut
grids, so it's relatively memory conserving.

field_cuts is a list of statements that get executed with "grid" in
the local namespace that should return logicals of the same size as
the grid's dimensions.  So, for instance:

In [8]: dd = pf.h.all_data()
yt         DEBUG      2010-08-26 08:36:42,780 Appending object to
RedshiftOutput0005 (type: <class 'yt.lagos.HierarchyType.AMRRegion'>)
yt         DEBUG      2010-08-26 08:36:42,780 Going to obtain []

In [9]: cr = dd.cut_region(["grid['Density'] > 1e-30",
"grid['Temperature'] > 1e4"])
yt         DEBUG      2010-08-26 08:36:51,151 Appending object to
RedshiftOutput0005 (type: <class
'yt.lagos.BaseDataTypes.InLineExtractedRegionBase'>)
yt         DEBUG      2010-08-26 08:36:51,152 Going to obtain []

In [10]: dd.quantities["Extrema"]("Temperature")
Out[10]: [(671.12800064096166, 391670.05340733693)]

In [11]: cr.quantities["Extrema"]("Temperature")
Out[11]: [(10000.132791838885, 391670.05340733693)]


Like I said, I'm sorry this is poorly documented, because I think it's
a pretty neat technique (and one I've used recently.)

Best,

Matt


>
> Thanks,
> John
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