answered by the documentation:
http://docs.python.org/library/re.html
In short, the (?P...) construct defines a named group.
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other doc fixes to 1.3.x tomorrow (if no
objections):
git://github.com/pv/numpy-work.git work-1.3.x
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].append('foo')
a
array([['foo'], [], [], [], []], dtype=object)
Possibly not any faster or cleaner than the for loop.
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/numpy/lib/io.py, line
436, in loadtxt
raise IOError('End-of-file reached before encountering data.')
}}}
There haven't been any changes to lib/io.py since branching off 1.3.x, so
I believe it should also work OK on 1.3.0.
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already been fixed.
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:
np.fft.ifft([1,0,0,0])
array([ 0.25+0.j, 0.25+0.j, 0.25+0.j, 0.25+0.j])
whereas that of the online reference guide is correct. (To avoid
confusion between the different docs, it's probably best to use refer to
the ebook by its name.)
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Fri, 27 Mar 2009 09:20:09 -0400, josef.pktd wrote:
[clip: numpy.random.exponential docstring]
I changed this a while ago in the documentation editor, but it hasn't
been merged yet to the source docstring
It is merged, but I forgot to regenerate the mtrand.c file.
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we'd like docs for newer versions
(possibly containing updates etc.) be labelled as compatible with all
XX.YY. versions.
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. The function is fairly
small.
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, it might be good not to keep commented-out code such as those
np.knownfail decorators in the repository, unless it's explained why it's
commented out...)
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the test is now fixed in trunk:
http://projects.scipy.org/numpy/changeset/6827
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in Numpy trunk.
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Wed, 08 Apr 2009 09:59:50 +0200, Gael Varoquaux kirjoitti:
On Wed, Apr 01, 2009 at 08:40:15PM +, Pauli Virtanen wrote:
It was an incompatibility of Numpy's autosummary extension and Sphinx
= 0.6. It should now be fixed in Numpy trunk.
autosummary is now in Sphinx (= 0.6). Shouldn't we
.
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!
***
However, for some reason, I don't see your contribution in the change
list:
http://docs.scipy.org/numpy/changes/
Can you check if the change you made went through? What page did you edit?
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it
was established that detecting when views really overlap is a problem
with no cheap solution. So walking up -base pointers or comparing -data
pointers seemed nearly the only feasible way.)
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bdist_egg
Does this help?
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Wed, 15 Apr 2009 16:36:09 -0400, josef.pktd wrote:
[clip]
Is there a list of gotchas for working with views that might produce
unexpected results?
I don't think there is. Also, the reference manual would probably need a
separate section about views.
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and raise a warning. (The user can silence these, if the behavior
is really relied on.) I don't know what is the performance impact of
Python warnings, though.
The alternative is to have really good documentation on views...
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Wed, 15 Apr 2009 15:27:21 -0600, Charles R Harris wrote:
I'm going to move the docstrings from mtrand.pyx to add_newdocs.py. Will
this require any fixes to the doc editor so that the docs don't get
readded to mtrand?
Go ahead, nothing should break.
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Hi,
buildbot.scipy.org says:
Service Temporarily Unavailable
The server is temporarily unable to service your request due to
maintenance downtime or capacity problems. Please try again later.
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)
--
Ran 2034 tests in 41.154s
FAILED (KNOWNFAIL=1, failures=2)
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Sat, 18 Apr 2009 13:19:39 -1000, Eric Firing wrote:
[clip]
This is a real pain. What is the simplest work-around?
apt-get install libatlas3gf-base
export LD_LIBRARY_PATH=/usr/lib/atlas
Or, just uninstall libatlas3gf-sse2 in favor of the *-base version.
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these issues in depth.
If you want to ensure no-copy, assign to shape:
a.shape = (6,)
Another remark against reshape:
OWNDATA flag is False, even if b is a copy !
Apparently, reshape first copies to a contiguous array and then reshapes.
This could be simplified.
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Wed, 22 Apr 2009 15:12:20 -0400, josef.pktd wrote:
On Wed, Apr 22, 2009 at 2:37 PM, Pauli Virtanen p...@iki.fi wrote:
[clip]
If you want to ensure no-copy, assign to shape:
a.shape = (6,)
[clip]
Is the difference between assigning to the attribute and using the
method call explained
.
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shipped with Ubuntu 9.04 are broken:
https://bugs.launchpad.net/bugs/363510
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the branches, would help this.
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coefficients.
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with minor changes, so I see no
reason not to make sure we're consistent with duck typing.
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Fri, 24 Apr 2009 19:04:50 +, Pauli Virtanen wrote:
Well, Numpy's poly1d will work fine with minor changes, so I see no
reason not to make sure we're consistent with duck typing.
polyint fixed in r6883, there doesn't seem anything else to fix:
import numpy as np
from fractions import
constructor, and feed it initializer data. Works for any classes.
I'm undecided whether it'd be a good idea to add a specialized routine
for doing this...
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then be merged.
I don't think broken trunk has often been a significant problem in Numpy
in the past. Anyway, feature branches are good, and we have the
buildbot.scipy.org, so there's no reason not to check it after committing.
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Fri, 08 May 2009 11:45:51 +0400, Ilya A. Kozyreff kirjoitti:
$ python setup.py install --prefix=/nethome/ia/usr/
$ python -c 'import numpy; numpy.test()'
[clip]
ImportError: No module named numpy
[clip]
What I do wrong?
://trac-hacks.org/ticket/3233
I applied the patch from the ticket; I think password resets should work
now, so you can try using your old accounts again.
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Buildbot can't. I'd suggest removing your build/ directory and
rebuilding, to see if it's caused by some file not rebuilding properly.
Otherwise, what is the platform you are using?
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Mon, 11 May 2009 16:22:37 +0200, Nils Wagner kirjoitti:
On Mon, 11 May 2009 14:05:13 + (UTC)
Pauli Virtanen p...@iki.fi wrote:
Mon, 11 May 2009 14:06:07 +0200, Nils Wagner kirjoitti:
Can someone reproduce the following failure ? I am using
numpy.__version__
'1.4.0.dev6983
Wed, 13 May 2009 13:18:45 -0700, David J Strozzi kirjoitti:
[clip]
Many of you probably know of the interpreter yorick by Dave Munro. As a
Livermoron, I use it all the time. There are some built-in functions
there, analogous to but above and beyond numpy's sum() and diff(), which
are quite
think you should re-check that you are doing what you think you are
doing. Preparing a self-contained code example could help here, at least
this would make pinpointing where the error is more easy.
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://yorick.sourceforge.net/manual/yorick_47.php#SEC47
I must say that I don't see many functions missing in Numpy...
David (Strozzi): are these the functions you meant? Are there more?
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Hi,
Sat, 16 May 2009 16:01:00 +0300, Quilby wrote:
[clip]
http://www.scipy.org/doc/numpy_api_docs/numpy.linalg.linalg.html#lstsq
[clip]
Could we take these old Endo-generated docs down, and make the URL
redirect to docs.scipy.org?
I believe they are more harmful than helpful...
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Sat, 16 May 2009 14:02:34 +, Pauli Virtanen wrote:
Hi,
Sat, 16 May 2009 16:01:00 +0300, Quilby wrote: [clip]
http://www.scipy.org/doc/numpy_api_docs/numpy.linalg.linalg.html#lstsq
[clip]
Could we take these old Endo-generated docs down, and make the URL
redirect to docs.scipy.org
actually be a bug in matplotlib; perhaps you should ask the
people on the matplotlib lists if this is really the intended behavior.
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,
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] http://www.scilab.org/platform/index_platform.php?page=history
.. [3] http://en.wikipedia.org/wiki/GNU_Octave#History
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, it should be x[1,:].copy(). Please feel free to correct it.
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Thu, 21 May 2009 01:45:54 -0700, dmitrey wrote:
I have updated numpy to latest '1.4.0.dev7008', but the bug still
remains.
I use KUBUNTU 9.04, compilers - gcc (using build-essential), gfortran.
Worksforme on Ubuntu 9.04, on python2.6 and python2.5. Should be the same
platform.
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Thu, 21 May 2009 09:26:18 +, Pauli Virtanen wrote:
Thu, 21 May 2009 01:45:54 -0700, dmitrey wrote:
I have updated numpy to latest '1.4.0.dev7008', but the bug still
remains.
I use KUBUNTU 9.04, compilers - gcc (using build-essential), gfortran.
Worksforme on Ubuntu 9.04, on python2.6
, you should check that
you don't have an ulimit set for virtual/RSS memory.
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://projects.scipy.org/numpy/ticket/1115
which is maybe related.
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Thu, 21 May 2009 10:54:21 -0700, Grant Kelly wrote:
It's an immutable page. Can someone who already has access make the
edit?
Umm, are you sure? I don't see any ACL's on the page. (Though you need to
register an account on the wiki before editing.)
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-
array objects so that all their attributes etc. are exposed in the hdf5
file and can be read by non-Python applications.
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the following output for
you:
np.arctanh(np.array([1e-5 + 1e-5j], np.complex64))
array([ 9.9975e-06 +9.9975e-06j], dtype=complex64)
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(it is a subclass of
AxisConcatenator) would make more sense. I'm not sure this change is
worth the trouble though.
I think the RClass is a private implementation detail, and shouldn't be
documented in the reference guide.
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is in place.
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? (Let's forget the names of
the new keyword arguments for the present, and assume they have
perfectly fitting names.)
I'd vote for (e) if the slate was clean, but since it's not:
+1 for (a) or (b)
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Wed, 03 Jun 2009 16:05:51 -0400, David Warde-Farley wrote:
On 2-Jun-09, at 3:06 PM, Pauli Virtanen wrote:
+0
I don't see any drawbacks, and the implementation looks good.
Thanks Pauli. I realized I was missing values() and itervalues() (though
I can't conceive of a scenario where I'd
of printing them to
stderr.
***
I added this to 0.7.1-notes.rst.
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behavior doesn't seem correct.
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representing the binary data. Also, I doubt that this would be very
useful: representing large amounts of data as text is not efficient. I
also think few people have interest in this feature.
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/docs/numpy-docs/reference/routines.set.rst/
in order to be included in the final documentation.
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://docs.scipy.org/numpy/docs/numpy-docs/reference/c-api.array.rst/#array-iterators
Probably as a new subsection.
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that should report the
status, but it's currently broken.
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= x - y;
is -inf or not. And if it is, just to return -inf.
That's not the correct fix.
Anyway, fixed in r7059.
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On 2009-06-19, Nils Wagner nwag...@iam.uni-stuttgart.de wrote:
Is this a known failure ?
I am using 1.4.0.dev7069
Check the tickets:
http://projects.scipy.org/numpy/ticket/1108
Cause is not known yet, but that bug most likely has been around for a long
time.
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to be fixed by looking at the source.)
I don't see many relevant changes in scipy.lib recently, so I'm
not sure what change you mean by the above.
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On 2009-06-24, Robert Kern robert.k...@gmail.com wrote:
[clip]
Yes. The HOWTO_BUILD_DOCS.txt is unfortunately out of date.
So it is.
Rewritten.
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interface
could be added (by keyword) for those who want an exception raised whenever
the
requested read count could not be completed.
+1
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the program crash on C-level, which is
clearly undesirable in a Python program as it cannot be handled.
Raising an error here seems to be the proper thing to do.
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in memory, before writing it to disk. Linux has at
least some system-wide parameters available that tune the aggressiveness
of data cachine. I suppose there may also be some file-specific settings,
but I have no idea what they are.
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.
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with GNU Libc 2.9.)
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tests even if
buildbots are OK... After repeating this cycle a couple of times,
IIRC only some special cases of log survived :)
Of course, if you meant to merge the tests first to the new
implementations and that to trunk, this sounds better.
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)
A[j, j+1] = 0.5
A[j, j-1] = 0.5
A[-1,:] = -0.5*a[:-1]/a[-1]
A[-1,-2] += 0.5
and the zeros are
x = linalg.eig(A)[0]
See eg. http://dx.doi.org/10.1016/j.apnum.2005.09.007 for more.
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keep track of which features are supported in
which version.
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that either this
list doesn't want me or there is some other problem.
Anyway it seems impossible to reach the right people.
I don't think I am able to help you here. Forwarding this to the ML, so
the list admins know.
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also here: instead of a
file random.py, you have a package named 'random' in the working
directory.
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it as an exercise for the reader to
implement the data file parser in Matlab. I doubt it can be easily done
in 20 lines :)
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Hi,
Ticket #1143 points out that Numpy's reduction operations are not
always cache friendly. I worked a bit on tuning them.
Just to tickle some interest, a pathological case before optimization:
In [1]: import numpy as np
In [2]: x = np.zeros((8, 256))
In [3]: %timeit
copying the data. If so, then it
probably hits similar cache problems as the non-optimized
reduction operation.
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, or even have
tunable parameters chosen at build or compile time. (Unless, of
course, we want to bring a monster into the world -- think about
cross-breeding distutils with the ATLAS build system :)
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. Anyway, it seems there is some auditing to do
before this change can be safely considered.
Also, the speedups obtained were fairly modest, 20%. Are they
larger for more complicated expressions? (Ie. is there an
expression whose execution time is halved?)
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that none of them
is problematic. (We know already that at least PyArray_Conjugate is.)
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Thu, 09 Jul 2009 09:54:26 +0200, Matthieu Brucher kirjoitti:
2009/7/9 Pauli Virtanen pav...@iki.fi:
[clip]
I'm still kind of hoping that it's possible to make some minimal
assumptions about CPU caches in general, and have a rule that decides a
code path that is good enough, if not optimal
,
and I don't see ways in which one could distinguish between temporary
arrays and refcount-1 arrays used in extension modules.
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new references of the contained objects.
[CPython itself creates a new tuple when doing
a = (np.zeros((4,)), np.zeros((5,)))
np.add(*a)
so that also in this case the refcounts of the two arrays in the
tuple are 1.]
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always traverses the array in virtual
C-order, not in the order it's laid out in memory.
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Wed, 08 Jul 2009 22:16:22 +, Pauli Virtanen kirjoitti:
[clip]
On an older CPU (slower, smaller cache), the situation is slightly
different:
http://www.iki.fi/pav/tmp/athlon.png
http://www.iki.fi/pav/tmp/athlon.txt
On average, it's still an improvement in many cases. However
expected it to raise a
NotImplementedError exception.
Can anybody cast some light on this issue ? Thanks a lot in advance
Seems like a bug. As I understand, NotImplemented is intended to be
returned only from __lt__ etc. comparison methods.
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.. rubric:: Notes
to make the headings to appear.
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of the reduction operations. Also these would be
more efficient if the striding of the output array could be
chosen freely.
I wonder if it would be OK to make this change...
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% sure this is a wise route to go, but oh well...
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On 2009-07-20, Keith Goodman kwgood...@gmail.com wrote:
[clip]
Oh, sorry, I misunderstood. Yes, a similar change was made to eye but
not to identity.
Nasty, duplicated code there it seems...
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to little-endian order.
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implementations for functions
that are missing in it.
Are they platform independent?
In practice, yes. There are some possible obscure corner cases
currently in complex-valued inf/nan handling, though.
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. It probably doesn't
describe all points of Numpy accurately. Of course, the URL is
misleading...
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, and personally I believe this should be same as numpy's default
float.
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a list of ndarrays. It didn't complain, but when I
loaded the data back, the list had been turned into an ndarray. Is this
behaviour expected? It did surprise me. Below there is an example:
[clip]
It is expected. savez casts its input to arrays before saving.
--
Pauli Virtanen
ahead and create one -- there's little harm
done even if it's a duplicate.
--
Pauli Virtanen
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