Hi Dominik,
I think what you're looking for is an attribute (not a method)
print group._v_name
HTH,
Elias
From: Dominik Szczerba
e the data is
read-only. I'm running with mod_python 3.3.1 on Apache 2.2.0
Another possibility is the use of pydap (http://pydap.org). If it weren't
for the lack of support for VLARRAYs I would have been very keen to use it.
Just some food for thought.
--
Elias Collas
Stress Methods G
Bryan, in my previous reply, I should have noted that to see the attributes
in the AttributeSet, you'll have to iterate through them as well. The print
statement won't show the attributes themselves. Sorry about that!
If you're in an interactive session, you can just type the node without a
print
lt;--- this is dictionary-like class,
type AttributeSet
> ##print type(a)
> ##print a.getAttr()
> ##x=a.attrs._f_list('all')
> ##except: pass
Hope this helps.
Elias Collas
Gulfstream Aerospace Corp
--
that is the extensible axis) and I just take the
default, expectedrows=1000.
With gratitude,
Elias Collas
Stress Methods Group
Gulfstream Aerospace Corp.
This e-mail message, including all attachments, is for the sole use of the
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pts use numarray
(or even Numeric) to manipulate arrays pulled from the HDF5 files.
Bravo for amazing software and astonishing support!
Elias Collas
Stress Methods Group
Gulfstream Aerospace Corp
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This SF.net email is sponso
Thanks for your prompt reply.
[EMAIL PROTECTED] wrote on 08/24/2007 06:57:23
AM:
> Hi Elias,
>
> A Thursday 23 August 2007, escriguéreu:
> > Francesc,
> >
> > Here's my setup:
> > -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
> >=-=-=-= PyTables version: 1.3
> > HDF5 ve
improve throughput. but this is the only difference I could detect. It is
not a trivial matter to produce these large files, so I need to get it
right. I know it's not much to go on, but any suggestions are appreciated.
Elias Collas
Stress Methods
Gulfstream Aerospace Corp
>
> Yes. You've catched a bug (i.e. the array was saved without a
> byteorder check). This should be solved in r2118 of trunk. Try the
> patch available in:
>
> http://www.pytables.org/trac/changeset/2118/trunk
>
> and tell me how it goes.
>
> > Feliz Navidad y Prospero Año
>
> Bon Nadal per t
-1.14265963e+20, 9.80874033e-39, 3.69827696e-19],
type=Float32)
I end up with the correct shape, but the data is corrupt. I can work
around this by using numarray.concatenate and then just create a new node,
but if you have any idea what I'm doing wrong, I would love to have your
i
Array, so it is very natural for me to look up an offset in one dataset
and use is to find the corresponding data in another.
--
Elias Collas
Stress Methods
Gulfstream Aerospace
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g
> like:
>
> >>> f.mountFile('your_file_path_name', '/group/my_mount_point')
But this should be f.mountFile(where, name) in keeping with the rest of the
API, no?
> I definitely think that this would
python configuration file for each
database that simply points to each external file:
# database1.conf
common = "/path/to/shared.h5"
results1 = "/path/to/run1.h5"
# database2.conf
common = "/path/to/shared.h5"
results2 = "/path/to/run2.h5"
etc.
I suppo
ht, I can see how I would be able to accomplish
this by using an attribute in each results file to store a pathname of the
file containing the common data. However, the H5Fmount would be nice
because it is transparent and only one file handle would be
efficient, I came
across the H5Fmount capability while perusing the HDF5 documentation. I
couldn't find this in the PyTables docs so can you tell me if PyTables
supports this?
Thanks,
Elias Collas
Stress Methods
Gulfstream Aerospace
---
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