t;[EMAIL PROTECTED]>
To: Francesc Altet <[EMAIL PROTECTED]>
Hi Francesc,
On Nov 23, 2007, at 2:06 PM, Francesc Altet wrote:
> Hi,
>
> Some time ago, a Pytables user complained about that the next simple
> operation was hogging gigantics amounts of memory:
>
> import tab
ould not be the case). It is strange,
because PyTables used to work perfectly up to HDF5 1.8.0 beta3 (i.e.
all tests passed).
If we do more progress on this issue, I'll let you know.
Thanks!
--
>0,0< Francesc Altet http://www.carabos.com/
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exit status 1
>
> Is there a quick fix?
I don't know. It seems that PyTables has recognized LZO2 installed in
your system, but for some reason, the API doesn't match the LZO2
version, which is very strange. Which version of LZO do you have
installed? It is possible t
ssatge transmès --
Subject: Re: Writing to a dataset with 'wrong' chunksize
Date: Thursday 29 November 2007
From: Quincey Koziol <[EMAIL PROTECTED]>
To: Francesc Altet <[EMAIL PROTECTED]>
Hi Francesc,
On Nov 28, 2007, at 10:44 AM, Francesc Altet wrote:
> Hi Quincey,
>
&
le.
>
> >>> for row in tab.iterrows():
>
> if row['time'] < 1: print type(row)
>
> returns
>
Well, the solution for this is a bit buried in the reference manual:
http://www.pytables.org/docs/manual/ch04.html#RowClassDescr
section "Special Methods".
when H5Dwrite is called.
Ups, I've ended with a similar program and send it to the
[EMAIL PROTECTED] list past Saturday. I'm attaching my own version
(which is pretty similar to yours). Sorry for not sending you a copy
of my previous message, because it could saved you some work :-/
A Monday 03 December 2007, Francesc Altet escrigué:
> Ups, I've ended with a similar program and send it to the
> [EMAIL PROTECTED] list past Saturday. I'm attaching my own
> version (which is pretty similar to yours). Sorry for not sending
> you a copy of my previous mes
hen you
> slice it another way you really do, would call
> for a chunk to be shaped accordingly.
>
> Mike
>
> At 11:01 AM 12/4/2007, Quincey Koziol wrote:
> >Hi Francesc,
> >
> >On Dec 3, 2007, at 11:21 AM, Francesc Altet wrote:
> >>A Monday 03 December
Pro in:
http://www.carabos.com/products/pytables-pro
Happy Hollidays for everybody!
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, but it would be really convenient if CArray provided a
> flat view of the data.
Well, this should be the 'correct' way to update the CArray. Feel free
to open a ticket (http://www.pytables.org/trac/) for implementing the
flat iterator and we will see what we can do.
Cheers,
--
r, if you prefer using the field index instead of the name:
mytable.cols._f_col(mytable.colnames[2])[1] = 5
BTW, a Table.flush() is only needed when you append/modify the Table
using an iterator, so you don't need to is
is, to say the least, not easy, that should wait until we have time and
resources enough (or someone steps ahead and contributes one!).
Doing 3) should not require column-wise tables at all, but it is not
implemented yet (and should be not very difficult; volunteers?).
Ciao,
...
Option 1) doesn't need to rebuild the table, but selections can be
expensive. With option 2) you have to regenerate the table, but once
this is done, selects can be very fast because you can use in-kernel
selectio
ist, but it is not implemented yet, sorry.
Cheers,
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A Thursday 31 January 2008, escriguéreu:
> On Thursday 31 January 2008 3:06:58 am Francesc Altet wrote:
> > A Wednesday 30 January 2008, Darren Dale escrigué:
> > > Hello,
> > >
> > > Is it possible to create hard and soft links in pytables files? I
> &
27;node paths'
instead of 'inodes'. Still, there is the problem of metadata cache
coherency, but we could think about maintaining lists of 'soft links'
pointing to each 'real' node, so that we can update them on each
modification of the real node. Or perhaps
need an identifier that would be provided by HDF5 so that it
would be the same across all the links to the actual data in disk (kind
of a 'inode' in a filesystem).
Is there a way to get such a unique identifier?
Thanks!
--
>0,0< Francesc Altet http://www.carabos.com/
V
AIL PROTECTED]>
To: Francesc Altet <[EMAIL PROTECTED]>, [EMAIL PROTECTED]
Hi Francesc,
please look at H5Gget_objinfo in 1.6 and at H5Oget_info and H5Lget _info
in 1.8
objno (addr) is what you probably looking for
(address of the object in the file)
Elena
At 9:02 PM +0100 1/31/08, Fra
ot so direct, but after thinking a lot, it
is the best suggestion I can do to you.
Cheers,
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your best bet would be to ask in the Python list, I'm
sure that somebody will be able to provide an answer.
Good luck!
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>0,0< Francesc
= 0
for earray in f.walkNodes(where="/", classname="EArray"):
for j in xrange(earray.nrows):
element_j = earray[j]
print "\r[%04d/%04d]" % (i, 1000),
sys.stdout.flush()
i += 1
f.close()
des, 4096 does not seem to consume
too much resources. Are you experiencing some catastrophic resource
consumption with 4096?
Cheers,
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s
is not implemented yet (and we have no plans to do it anytime soon).
Sorry about that.
Cheers,
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% i
row['info2/info3/y'] = i
# All the rest will be filled with defaults
row.append()
***
This is an excert of the examples/nested-tut.py
x27;]
listofBadRows = []
for row in DryExp:
if row['CatalogNum'] in listofBadNums:
listofBadRows.append(row.nrow)
for i in listofBadRows:
DryExp.removeRows(i)
Hope this helps,
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This has been sent to the PyTables users' list, but bounced. Please,
remember to always subscribe to the list before sending messages.
Thanks,
-- Missatge transmès --
Subject: Float32 accuracy
Date: Sunday 02 March 2008
From: "Christiaan Putter" <[EMAIL PROTECTED]>
To: pytabl
A Monday 03 March 2008, Francesc Altet escrigué:
> This has been sent to the PyTables users' list, but bounced. Please,
> remember to always subscribe to the list before sending messages.
>
> Thanks,
>
> -- Missatge transmès --
>
> Subject: Float
arriba?
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Let us know of any bugs, suggestions, gripes, kudos, etc. you may
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an 'isolated' type (much like a string
type).
We are mostly inclined to implement 2) behaviour, but before proceed,
I'd like to know what other people think about this.
Thanks,
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"
A Tuesday 11 March 2008, Francesc Altet escrigué:
> The thing that makes uint64 so special is that it is the largest
> integer (in current processors) that has a native representation
> (i.e. the processor can operate directly on them, so they can be
> processed very fast), and besid
->int64 and int-->uint64), as has
been suggested by Timothy Hochberg in the NumPy list, and adopting
modular arithmetic for dealing with overflows/underflows is probably
the most sensible solution. I don't know how difficult it would be to
implem
A Tuesday 11 March 2008, Charles R Harris escrigué:
> On Tue, Mar 11, 2008 at 4:00 AM, Francesc Altet <[EMAIL PROTECTED]>
wrote:
> > A Tuesday 11 March 2008, Francesc Altet escrigué:
> > > The thing that makes uint64 so special is that it is the largest
> > > int
EST.h5...
> done
>
> I used "Col.from_type" for creating columns. As I
> looked up in the manual the Type Code for char is
> String. I have problems only with this type. Any
> suggestions on how to solve this?
Try 'string' instead. In table A.1 it is written
), dflt=0j, pos=1)},
"y": Float64Col(shape=(2, 2), dflt=1.0, pos=4),
"z": UInt8Col(shape=(), dflt=1, pos=5)}
byteorder := 'little'
chunkshape := (56,)
.
--
Ran 1 test in 0.087s
OK
Could yo
"Info": {
> "value": ComplexCol(itemsize=16, shape=(), dflt=(0.0+0.0j),
> pos=0), "y2": Float64Col(shape=(), dflt=1.0, pos=1),
> "Info2": {
> "name": StringCol(itemsize=2, shape=(), dflt='', pos=0),
> &q
> attribute 'ctx'
>
> Any idea what's going on?
>
> Cheers, Dragan.
Curiosly enough this very same problem has been reported by another user
some hours ago ;-) Have a look at:
http://www.pytables.org/trac/ticket/164
This has been fixed in all branches of PyTable
ase, but I can't
promise it.
Cheers,
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Don
tr
In [6]: b2 = f.getNodeAttr(a2, 'attr.var')
In [7]: a2
Out[7]:
/node.var (Array(2,)) ''
atom := Int32Atom(shape=(), dflt=0)
maindim := 0
flavor := 'python'
byteorder := 'little'
chunkshape := None
In [8]: b2
Out[8]: 3
Note that the warnings ar
ounce soon.
Finally, we want to thank everybody who has worked with Carabos all
these years, and let us say that it has been a great pleasure for us
to help you out.
Thank you!
The Carabos crew:
Ivan Vilata (Member)
Vicent Mas (Secretary)
Francesc Alted (President)
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> ___
> Pytables-users mailing list
> [email protected]
> http
During the last week, the www.pytables.org site has been giving many
headaches. I think I've fixed the issues, so it should behave
correctly from now on.
Thanks to those that warned me about the problem!
--
Francesc Altet
Freelance developer
Tel +34-964-28
A Wednesday 21 May 2008, Francesc Altet escrigué:
> A Wednesday 21 May 2008, Glenn escrigué:
[snip]
> > Thank you for the suggestion, but this also seems clumsy, because
> > my routine still needs to parts, one to replace the original
> > values, and then a second to add the n
cessary []'s
In [75]: normI.append(a[numpy.newaxis,:]) # using newaxis (no data
copy)
In [76]: normI
Out[76]:
/normI (EArray(2L, 512)) ''
atom := Float32Atom(shape=(), dflt=0.0)
maindim := 0
flavor := 'numpy'
byteorder
5 developers, warned me some months ago that this was fixed in HDF5
1.8.0 beta2. I have had a quick check on this and it seems to work
flawlessly. See:
http://www.pytables.org/trac/ticket/171
for more info (and a patch! ;)
close()
h5file = tables.openFile('tester.hdf5','r')
mtab = h5file.root.random
print type(mtab)
print mtab.read()
###
Hope it helps,
PS: Your code is a very nice start of how to s
open(self.parent_id, self.name)
instead of the current
self.dataset_id = H5Dopen(self.parent_id, self.name)
After this, everything in the logic of writing, reading.. should work
fine, because it will use the self.dataset_id. Perhaps in some (few, I
think) cases, the name would be needed as
d if
not, then the default would be to return RecArrays instead of
NestedRecArrays. Do you have a preference to that matter?.
Cheers,
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, 5.], type=Float32)
In [35]: numarray.array(ra._data, type='f4', shape=(len(ra),2))
Out[35]:
array([[ 1., 2.],
[ 3., 4.],
[ 5., 6.]], type=Float32)
Cheers,
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0486&dat=121642
> ___
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> [EMAIL PROTECTED]
> https://lists.sourceforge.net/lists/listinfo/pytables-users
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"
(beware, I'm an impenitent optimistic ). The
update of documentation is still pending...
Cheers,
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classes). Then, you can easily access to these columns by using
the .cols accessor:
table.cols.your_multidim_col[...]
HTH,
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Hello George,
El dg 22 de 01 del 2006 a les 21:30 +, en/na [EMAIL PROTECTED] va
escriure:
> Quoting Francesc Altet <[EMAIL PROTECTED]>:
> The patch seems to be in CVS. It didn't quite work. It needs an extra lib in
> the
> definition of libfile on line 91, and using
name can be assigned to
'/table'+'/ATTRS'+'/DIMENSION_LIST/'+forged_name
Assigning these four attributes to your node, and applying the attached
patch (it gets rid of _v_parentID that was not useful at all), you can
succeed making AttributeSet to think t
eting such a "referenced objects" does not grow the memory
consumption (I hope not).
Salut,
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to have a look at it, you can download it with:
svn co http://pytables.carabos.com/svn/pytables/branches/std-dimension-scales
Salut,
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This
not been checked very toughfully for leaks). I'll look into this
as soon as I get some time.
Thanks for reporting this!
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_pid, data)
*after* the numarray creation. However, this implies a refactoring of
the VLArray._readArray in hdf5Extension.pyx because you need to access
to the space_id and xfer_pid (you already have access to type_id and
data in Pyrex space). Maybe you want to have a try at
l PyTables version, and operating system.
Cheers,
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A Divendres 27 Gener 2006 19:28, Yann Le Du va escriure:
> On Fri, 27 Jan 2006, Francesc Altet wrote:
> > A Divendres 27 Gener 2006 18:46, Yann Le Du va escriure:
> >> Hello,
> >>
> >> I've juste installed Pytables, but I get this error (cf. att
ted the changes to SVN anyway, so
if you want to have a look, your suggestions are welcome.
SVN: http://pytables.carabos.com/svn/pytables/trunk
Cheers,
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El dv 27 de 01 del 2006 a les 21:01 +0100, en/na Francesc Altet va
escriure:
> I'm working on
> a different implementation (inspired on your patch), but some tests
> are still giving problems. I've commited the changes to SVN anyway, so
> if you want to have a look, your s
or more info.
Thanks,
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for problems? Stop! Dow
backward compatible as possible, so that files with
old values of flavors can properly be read in the new version of
PyTables.
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umpy and report
any error or glitch that you may notice, so that it can get as stable
as possible in order to easy the transition numarray-->numpy.
Cheers,
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array1-numpy.py
Descrip
(but of course,
this is not for the faint-hearted ;-). It is the magic of array
interface:
http://numeric.scipy.org/array_interface.html
that allows doing this in a very efficient manner.
Cheers,
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>0,0< Francesc Altet http:/
s.
>
> Lastly, There only seems to be the HDF5 help desk
> ([EMAIL PROTECTED]). I wonder why there is not any type of
> mail-list or forum for researching and discussing hdf5
> particularities. Are you aware of any?
Well, hdfhelp is a good
f. It is the equivalent of
a 'mv' in Unix. Of course, if you are using moveNode between files,
then, a copy of the data is made (in the same way than a 'mv' between
different filesystems).
Cheers,
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.
**Enjoy data!**
-- The PyTables Team
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o not
hesitate to report it back.
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g on my part or a bug.
Well, I can't reproduce your problem. The test suite pass for you?.
Also, it might help if you send the output of
$ python test/test_all.py --show-versions
Cheers,
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ion: 1.6.2
I think this is the problem. You will need HDF5 1.6.4 or newer in order
to run latests versions of PyTables. Perhaps issuing a warning during
tests execution would be a good idea.
HTH,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárab
path').read()
buff.tofile('the_pathname_of_your_binary_file')
You can even save the file name of your binary file in an HDF5
attribute and use it afterward in PyTables to re-create it.
HTH,
--
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7;ll try to focus on this
as soon as things will be a bit quieter, although, unfortunately
enough, I cannot commit on a fixed date :-/
Cheers,
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have.
**Enjoy data!**
-- The PyTables Team
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tly after 1 minute an 1
second.
Again, I'm not an expert on threading, so perhaps you can get some
feedback about your problem in the general python list.
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ime == t and x['lab'] == 'SC']
>
> would work, but I get a bunch of fake records instead.
This does not change anything (?). Uh... I'm a bit lost on what you
are trying to do.
Cheers,
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condition:
lab.II_0.cols.time == t
instead of:
x['time'] == t
?
Note that the first condition is badly stated (lab.II_0.cols.time is
an accessor to the *whole* column, not the value of the field in the
actual row).
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>0,0< Francesc Altet http://www
ions of bzip2 and lzo that are compatible with the versions that
have been compiled with the PyTables binaries (currently bzip2 1.0.3 and
lzo 1.0.8).
So, for those of you that are experiencing these sort of problems,
please, go to:
http://gnuwin32.sourceforge.net
and upgrade your dll's. This
elp
improving the lookup times:
$ python2.4 -m timeit -s "import tables;
t=tables.openFile('data.nobackup/test-1M-idx.h5').root.table"
"coords=t.getWhereList(t.cols.var2 == 998);frames =
t.readCoordinates(coords, 'var3')"
100 loops, best of 3: 11.8 msec p
the
PyTables extensions (for example, hdf5Extension.pyd) live, but I'm not
entirely sure about this, so you may want to experiment ;-). I'm not in
Windows right now, but this directory should be something like:
\your_python_installation_path\...\site-packages\tables\
Cheers,
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>0,0<
any rate, Atoms itself
cannot have associated metadata: you can only associate metadata to
primary objects (Table or *Array).
HTH,
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est technique to not loose many data when working with HDF5 files is to
take a defensive approach and create backup files from time to time.
I know that somebody in this list was also worried by these kind of
issues, and perhaps he can say more on this.
Sorry about that,
--
>0,0< France
nes of code.
Right, in fact I thought about something like this some time ago, but
never implemented it :-(
Well, thanks for the suggestion! We will definitely look forward to
include it in forthcoming 1.3 release.
Cheers,
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>0,0< Francesc Altet h
to convert numarray objects to/from NumPy, and, as
there is no data copy involved in the process, this additional
conversion step should not be a worry to the vast majority of PyTables
users (i.e. generally the bottlenecks are in other places).
Good Luck!
--
Francesc Altet
dimension scales implementation. With a bit of luck,
some of us would be able to better realize your current work and be
able to better help on this.
Cheers,
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crash.py
Description: application/python
th this is that I need to search over
> 20-30 individual time bins (like above), and I cannot figure out a
> way to bin up the data
> in one pass, e.g., I am calling the above loop 20-30 times, so to
> data mine this table I have a longer wait than I thought I would
Well, o
but we don't have a definitive pricing/licensing schema yet.
But, just for your information, the prices will be around one thousand
euros (maybe a little more or a little less, but in that order of
magnitude) for one license.
Regards,
--
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ude "lzo/lzo1x.h"
+# include "lzo1x.h"
# define HAVE_LZO_LIB /* The API for LZO and LZO2 are mostly
identical */
#endif
-----
and, hopefuly, your problem should go away.
Regards,
ng hdf files, maybe the
> lzo and ucl are not so necessary.
Yeah, not at all. LZO and UCL are there just for those users interested
in taking the maximum from (de-)compression speed. But if you want to
stick with maximum HDF5 compatibility, then it is much better to not use
them.
Cheers,
--
&
s
> supports this?
Right now we have no plans to add this feature. Can you explain a little
under which situations do you need this?
Regards,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
---
ot;mount capability" to
our TODO list. BTW, I see that you discovered by yourself that running
File.copyFile() is an equivalent way of running h5repack ;-)
Chers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
--
suggesting, I think, is something like:
mountpoint = file1.mountFile('/common', file1.root._v_attrs.commom)
for having access to the shared file in file1.root.common.
Mmm, now that I think more about this, I'm not so sure that the later
approach would be much better than the former. Do you
mplemented it :-(
> >
> >Well, thanks for the suggestion! We will definitely look forward to
> >include it in forthcoming 1.3 release.
Done in SVN.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
--
ternal 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 suppose this is one of the n
El dv 17 de 03 del 2006 a les 15:20 -0700, en/na Mike Romberg va
escriure:
> >>>>> " " == Francesc Altet <[EMAIL PROTECTED]> writes:
>
> [snip]
>
> > Mmm, right now, I think that PyTables can reclaim the space
> > free
tasets, I
think it wouldn't be too difficult to add this feature.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
---
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