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
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! ;)
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
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
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
net email is sponsored by: Microsoft
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> http://clk.atdmt.com/MRT/go/vse012070mrt/direct/01/
> ___
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> Pytables-users@lists.sourceforge.net
> http
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)
--
>0,0<
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
ase, but I can't
promise it.
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
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Don
> 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
"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
), 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
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
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
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
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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V V Cárabos Coop. V. Enjoy Data
"
ience
=
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.
--
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arriba?
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Defy all challenges. Microsoft(R) Visual S
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
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
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,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V.
% 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
s
is not implemented yet (and we have no plans to do it anytime soon).
Sorry about that.
Cheers,
--
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= 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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V V Cárabos Coop. V. Enjoy Data
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-
This mailing list is for HDF software users discussion.
To subscribe to this list, send a message to
[EMAIL PROTECTED]
To unsubscribe, send a message to [EMAIL PROTECTED]
-------
--
>0,0< Francesc
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!
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
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--
ot so direct, but after thinking a lot, it
is the best suggestion I can do to you.
Cheers,
--
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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
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
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
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
> &
ist, but it is not implemented yet, sorry.
Cheers,
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Defy all challenge
...
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
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,
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
, 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,
--
Pro in:
http://www.carabos.com/products/pytables-pro
Happy Hollidays for everybody!
--
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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
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
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 :-/
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".
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,
>
&
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
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/
V V Cárabos Coop. V. Enjoy Data
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
Hi List,
Here you have the official announcement for PyTables (& Pro) 2.0.2.
Please have a try at the packages and report back any problem you may
notice. If not issues are detected with the packages, we will proceed
tomorrow with the announcement in more general lists.
Enjoy!
=
t recent call last):
[snip]
> NotImplementedError: sorry, but multidimensional atoms are not
> supported in this context yet.
Yeah. Finally a possible reason for supporting multidimensional atoms
in CArray/EArray objects ;-). I've opened a ticket on this:
http://www.
dimension" mean for multidimensional arrays.
Yeah. Wise advices.
> Allowing an order="C" or order="F" flag to CArray constructor in the
> future could also handle the two most common logical orderings more
> conveniently than having to specify a chunkshape. Actu
is feedback, I promise to setup
a wiki page in the pytables.org site so that these opinions would be
reflected there (and people can add more stuff, if they want so). As
the time goes, we will use all the info/conclusions gathered and will
try to add a section the chapter 5 (Optimization Tips) of U
A Wednesday 14 November 2007, Francesc Altet escrigué:
> A Tuesday 13 November 2007, Michael Hoffman escrigué:
> > Is there a preferred citation for PyTables in a scientific paper?
>
> Well, although it is not properly a FAQ, I've added an entry in the
> FAQ about this:
>
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
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Still grepping through log files to find problems? Sto
A Wednesday 17 October 2007, Francesc Altet escrigué:
> A Wednesday 17 October 2007, Darren Dale escrigué:
> > > Mmm, I'm curious about which datatype should be causing this.
> > > Can you try applying the attached patch and send me the output?
>
> [snip]
tforms.
> The manual does not indicate that Numeric is required for netcdf3.
You are right. I've added a ticket on this:
http://www.pytables.org/trac/ticket/124
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
7;ve never seen this error before (and normally run PyTables on 64-bit
Linux machines, but under SuSe, not Gentoo), and as far as I know,
there should be no dependency on ctypes at all. Sorry but I'm puzzled
here.
> Is the netcdf error a known pytables bug, or is it maybe a
>
e "utilsExtension.pyx", line 328, in utilsExtension.getNestedField
ValueError: field named c_int16 not found.
--
I installed ctypes-1.0.2, which took care of 660 of the failures. Should
a
ctypes version be listed in th
bles version) in which
this is happening? It seems like if you are trying to use an object
that cannot be converted into a long integer.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coo
ospection. However, I agree that, for programatic
uses, implementing a __getitem__ would look better:
for a in ff:
x = a._v_attrs
l = x._f_list()
for i in l:
print x[i]
I've added a ticket (http://www.pytables.org/trac/ticket/120) so that we
can consider this addition for
epository of PyTables packages. This file should also be
created in future releases.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
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This SF
A Monday 24 September 2007, Michael Hoffman escrigué:
> Francesc Altet wrote:
> > A Monday 24 September 2007, Francesc Altet escrigué:
> >> A Monday 24 September 2007, Michael Hoffman escrigué:
> >>> Perhaps it would still take the same time over the whole file,
>
A Monday 24 September 2007, Francesc Altet escrigué:
> A Monday 24 September 2007, Michael Hoffman escrigué:
> > Hi Francesc. Thanks for the explanation.
> >
> > Francesc Altet wrote:
> > >> Additionally, what would you think about allowing the user to
> > &g
A Monday 24 September 2007, Michael Hoffman escrigué:
> Hi Francesc. Thanks for the explanation.
>
> Francesc Altet wrote:
> >> Additionally, what would you think about allowing the user to
> >> specify a depth-first iteration in the walk functions? That is how
> >
e are appearing relatively cheap solid state
disks, based on flash memory, showing a very low latency (around 0.1
ms, see [2]), which will greatly accelerate your access needs (probably
as much as 100x).
[1]http://www.pytables.org/docs/NewObjectTreeCache.pdf
[2]http://www.tomshardware.com/2007/08
Hello Michael,
A Friday 21 September 2007, Michael Hoffman escrigué:
> Great, I look forward to using this release.
>
> Francesc Altet wrote:
> > Also, binaries have been compiled against the latest stable
> > version of HDF5, 1.6.6, released during the past August
.
Share your experience
=
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
"-"
--
Please apply the attached patch and tell me whether it cures the
problem or not.
Cheers,
--
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"-"
Index: tables/table.py
===
---
mmon type. For example, if you are using NumPy, you can do:
In [12]: numpy.float32(a) == b
Out[12]: True
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
"-"
-
ersion of
Pyrex and see if it goes better (remember to re-generate the
C-files; 'touch src/*.pyx' will do the trick).
In any case, it is known that numarray has problems when working with
64-bit platforms and Python2.5, so upgrading to PyTables 2.0 (with
NumPy at its core) is stron
ulate chunkshape in
order to adapt to general uses, that could not coincide with your
specific needs (as it is generally the case when you want to find
extremely fine-tuned chunkshape parameters).
Mmm, I'm thinking that perhaps adding a 'chunkshape' argument to
Leaf.copy()
n Leaf.copy() operation) should have in account the
optimal sizes for copied leaves, so there is no need for you to
recreate the tables/arrays manually.
Cheers,
--
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---
PyTables (actually, by the integrated numexpr package),
and it is not in our plans to implement it anytime soon.
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
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---
ric objects out of PyTables 2.0. So, if you
want to continue using numarray (which I do not recommend, at least for
the long run), just don't pass the '--upgrade-flavors' flag
to 'ptrepack'.
> Bravo for amazing software and astonishing support!
Thanks! :)
--
r.py", line 16, in ?
> fh.find_gpfb('121731')
> File "/cluster/stress/u308168/public_html/pyloads/model/finder.py",
> line 210, in find_gpfb
> r = nasob.NodalResult(self.fileh, g, balance=not oelop)
> File "../nasob.py", line 375, in __in
#x27; arrays. My
> > recommendation, though, is you to switch to 2.0 as there are more
> > optimizations (like using numpy natively and others) that can help
> > improving your times still more.
>
> Well, I have 2.0 built but not installed. My reluctance is to avoid
> brea
or it can be as high as 600KB, putting too much stress on the
shuffle filter. This has been somewhat bettered in 2.x series, so that
the chunksize for your files (~2.2 GB) would be something like 32KB or
64KB, which is a more reasonable figure for shuffling (besides of
allowing far better performan
7;, "'", 7), 49.0) (('I', '(', 8), 64.0)
(('J', ')', 9), 81.0)]
nested column:
[('A', ' ', 0) ('B', '!', 1) ('C', '"', 2) ('D', '#', 3) ('E', '
A Tuesday 21 August 2007, Francesc Altet escrigué:
> Indeed it seems that there is a problem with the MacOSX platform, but
> the fact that this is not reproducible on Linux is unfortunate.
> Anyone that is reading this can try David's script on a Windows
> machine? That could
,
>
> ciao,
>
> David
>
> On 16/08/2007, at 3:49 AM, Francesc Altet wrote:
> > A Wednesday 15 August 2007, Francesc Altet escrigué:
> >> A Wednesday 15 August 2007, David Worrall escrigué:
> >>> All that aside,
> >>> 1. it is a worry that there
Hi List,
This has been sent to the [EMAIL PROTECTED] list, but it should of
interest to this list too.
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
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--- Original message -
A Wednesday 15 August 2007, Francesc Altet escrigué:
> A Wednesday 15 August 2007, David Worrall escrigué:
> > All that aside,
> > 1. it is a worry that there is no exception generated, by python,
> > at least, don't you agree?
>
> Yes, I do.
>
> > 2.
hon, at
> least, don't you agree?
Yes, I do.
> 2. Is there a way of purging memory after a flush or are we up
> against python's memory management?
I think the thing to try first would be lowering NODE_MAX_SLOTS. Have
you tried this already?
Cheers,
--
>0,0<
s really a
very large amount of memory (>= 8GB) available, you may want to set
NODE_MAX_SLOTS to 0 so that the node cache is completely disabled.
Please, report back your experiences.
Also, can you send the output of tables.print_versions()?
Cheers,
--
>0,0< Francesc Altet h
A Monday 13 August 2007, Fernando Perez escrigué:
> On 8/13/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
> > I've checked that test_all.py returns a value of 0 when it exits (i.e. $?
> > variable has a 0 value, as it should). Perhaps IPython is (wrongly)
> >
A Monday 13 August 2007, Fernando Perez escrigué:
> On 4/26/07, Fernando Perez <[EMAIL PROTECTED]> wrote:
> > On 4/26/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
> > > El dj 26 de 04 del 2007 a les 09:28 -0600, en/na Brian Granger va
> > >
> > >
A Saturday 11 August 2007, Francesc Altet escrigué:
[snip]
> When doing this, it is also more efficient to use:
>
> row = table.row
> for i in xrange(1000):
> row.append()
> table.flush()
>
> than:
>
> for i in xrange(1000):
> table.row.append()
> table
ject is instanciated on each
iteration, but in the former only once (see tutorials).
Cheers,
--
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V V Cárabos Coop. V. Enjoy Data
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This SF.net email is s
A Divendres 13 Juliol 2007 20:17, Francesc Altet escrigué:
> [I'm forwarding this message that the list has rebounded (sending from
> unsubscribed address?)]
>
> ---
>-- From: "Alain
[I'm forwarding this message that the list has rebounded (sending from
unsubscribed address?)]
-
From: "Alain Fagot" <[EMAIL PROTECTED]>
To: pytables-users@lists.sourceforge.net
Date: Today 17:37:29
Hi,
etain format compatibility with HL. But anyway, the goals
for PyTables and HL were different from the very beginning.
Anyway, if you need help for looking into this you can always contract us.
For details, see http://www.carabos.com/services.
Regards,
--
>
And last, but not least thanks a lot to the HDF5 and NumPy
(and numarray!) makers. Without them PyTables simply would not exist.
Share your experience
=====
Let us know of any bugs, suggestions, gripes, kudos, etc. you m
aling with different alignments, it seems that it
is not sophisticated enough for dealing with all cases, most specially nested
records.
Perhaps you could try creating a contiguous nested record by removing all the
alignment in fields (this is the way PyTables creates the tables on-disk).
HT
El dt 10 de 07 del 2007 a les 09:26 -0400, en/na Ken Dere va escriure:
> Numeric (version 24.2) is present. Adding the Numeric test
> suite.
BTW, there was a Numeric package for Python2.5 included in your ubuntu
box, or have you compiled it by hand? Just curious.
--
Francesc Altet
t; complete error message which is quite long.
Yeah. This is known flaw with IPython running Doctests. See:
http://lists.ipython.scipy.org/pipermail/ipython-dev/2007-April/002859.html
Unfortunately, I don't think they have found a fix for this yet.
--
Francesc Altet| Be car
bc detected *** python: free(): invalid pointer:
> 0x0a871aa0 ***
We know that running Numeric with Python 2.5 is a sure receipt for
disaster (we don't know exactly the cause of this, but it might be just
an ageing effect; you should start migrating to NumPy
PATH. By looking at your description, the
versions of HDF5 and zlib DLLs seems fine.
To say the truth, I don't really know what's going on in your system. Can
you try with a the latest version of binaries:
http://www.pytables.org/download/preliminary/tables-2.0-of20070706.win32-
> > HDF5 version: 1.6.4
Yes, this should be the reason of the failures
> PyTables 2.0 requires HDF5 1.6.5. Perhaps this should also be warned.
Added the warning when running the tests.
Thanks for the testing work!
--
Francesc Altet| Be careful about using the following code --
quot;"
If you want to keep a *unique* identifier of a dataset that remains the
same from run to run, you may want to use: node._v_pathname (or a hash
of it, in case you want a numerical value).
Cheers,
--
Francesc Altet| Be careful about using the followi
El dl 02 de 07 del 2007 a les 23:06 -0700, en/na Andrew Straw va
escriure:
> Francesc Altet wrote:
>
> > Perhaps somebody in the list knows a clean way of deleting the
> > extensions created with the 'build_ext --inplace' flags?
>
> Not exactly what you ask
El dl 02 de 07 del 2007 a les 13:50 +0100, en/na Michael Hoffman va
escriure:
> Francesc Altet wrote:
> > El dl 02 de 07 del 2007 a les 12:41 +0100, en/na Michael Hoffman va
> > escriure:
> >> The instructions indicate that one should use python setup.py build_ext
> &
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