Hi Geoffrey,

A question: is this actually an Enzo dataset (as in, .cpuNNNN files, with the parameter, hierarchy, etc. files as well), or are you talking about monolothic HDF5 files containing a single field that was created by some third party?  If it's the latter, you're better off just using, say, h5py to read each file in separately, and divide them by each other.  I don't think that the yt machinery is designed for brick-of-bytes HDF5 files (though I may very well be wrong).

--B

On Mon, Jul 18, 2011 at 5:27 PM, <gso@physics.ucsd.edu> wrote:
Hi,

I was wondering if it is possible to specify two different sources of
input to create a derived field.  Currently with a single source, I have a
derived field defined as:

def _HII_HFraction(field, data):
  return data["HII_Density"]/(data["HI_Density"]+data["HII_Density"])

add_field("HII_HFraction", function=_HII_HFraction,
units=r"\frac{\rho_{HII}}{\rho_H}")

And I can access the total quantity in parallel

pf=load(file)

dd = pf.h.all_data()

dd.quantities["TotalQuantity"]("HII_HFraction")[0]

But I'm dealing with

pf1=load(file1)
pf2=load(file2)

pf1 has the HI_Density field data and pf2 has the HII_Density field data.
Is there a way to create a derived field and use TotalQuantity to operate
on the data in parallel?

From
G.S.

PS. I guess my alternative is to glue the two HDF5 files into one, but
want to avoid it if possible.


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