in their own projects
I'm not sure what's the best place to put these in.
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(most recent call last):
File stdin, line 1, in module
UnicodeEncodeError: 'ascii' codec can't encode character u'\xe4' in
position 0: ordinal not in range(128)
You probably meant to use byte strings, though:
string = b.join(chr(i).encode('latin1') for i in range(256))
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Mon, 26 Jul 2010 13:57:36 +0900, David Cournapeau wrote:
I have finally prepared and uploaded a test repository containing numpy
code:
http://github.com/numpy/numpy_svn
Some observations based on a quick look:
1)
$ git branch -r
origin/maintenance/1.1.x_5227
Tue, 27 Jul 2010 00:26:51 +0800, Ralf Gommers wrote:
[clip]
Also, Ralf has the Git ID in format rgommers...email..., but I
guess that's correct?
My checkout failed so can't check this, but that looks a little odd. My
.gitconfig is normal:
user]
name = rgommers
email =
2
Aug 29: release
Seems OK. I don't remember any big changes that would still be needed.
One low-hanging fruit to fix could be np.fromfile raising MemoryError
when it encounters EOF, and other bugs in that part of the code.
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Tue, 27 Jul 2010 10:50:51 -0700, Christopher Barker wrote:
Pauli Virtanen wrote:
Tue, 27 Jul 2010 08:37:56 -0600, Jed Ludlow wrote:
On Tue, Jul 27, 2010 at 2:38 AM, Pauli Virtanen p...@iki.fi wrote:
One low-hanging fruit to fix could be np.fromfile raising MemoryError
when it encounters EOF
Wed, 28 Jul 2010 12:17:27 +0900, David Cournapeau wrote:
[clip]
http://github.com/numpy/numpy_svn
I put a new repostory (same location)
Some more notes:
- 1.1.x branch is missing.
This is maybe because in SVN something ugly was done with this branch?
- Something is still funny with some
Wed, 28 Jul 2010 12:17:27 +0900, David Cournapeau wrote:
[clip]
http://github.com/numpy/numpy_svn
I put a new repostory (same location)
Compared this against git-svn produced repository. There are a number of
commits missing from the early history, apparently because numpy trunk
was moved
the size
of the array item.
(or are recarrays pointers-of-pointers as opposed
to contiguous memory?)
No.
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citizens in the Python world. This sits less well with
Numpy: (i) Numpy tries to sit close to the hardware, and (ii) strictly
speaking, arbitrary-size integers cannot be a Numpy scalar type since
they by definition are not fixed-size in memory.
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? IIRC, the problem was that the ziggurat broke reproducibility of
random numbers with a given seed.
So, was the ziggurat algorithm pulled out, or is it still there?
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Thu, 29 Jul 2010 01:16:14 +0200, Sturla Molden wrote:
[clip]
Makes sense. But couldn't a ``dtype`` argument still be useful?
np.ceil(some_array).astype(int)
That's one temporary more. The dtype= argument for all ufuncs wouldn't
probably hurt too much.
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Thu, 29 Jul 2010 02:40:00 +0200, Sturla Molden wrote:
Mon, 26 Jul 2010 23:58:11 +0800, Ralf Gommers wrote:
Is the current algorithm in the trunk the ziggurat one, or the previous
one? IIRC, the problem was that the ziggurat broke reproducibility of
random numbers with a given seed.
Ziggurat
Thu, 29 Jul 2010 23:39:19 +0800, Ralf Gommers wrote:
The execfile builtin has disappeared in python 3.x, so I'm trying to
find another solution for the use of it in setupegg.py. So far I've
tried
I'd do something like this in setup.py:
...
+ if os.environ.get('USE_SETUPTOOLS'):
+
The above indeed shows that you are probably using 1.4.1, but the scipy
you import was compiled against either the SVN version of Numpy or 1.4.0.
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Fri, 30 Jul 2010 19:52:37 +0900, David wrote:
[clip]
Indeed, it is not, and that's expected. There are various pitfalls using
floating point. Rational and explanations:
http://docs.sun.com/source/806-3568/ncg_goldberg.html
In case of tl;dr, see also http://floating-point-gui.de/
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Fri, 30 Jul 2010 14:21:23 +0200, Guillaume Chérel wrote:
[clip]
As for the details about my problem, I'm trying to compute the total
surface of overlapping disks. I approximate the surface with a grid and
count how many points of the grid fall into at least one disk.
HTH,
import numpy as np
as: mask[i0:j0,i1:j1] |= (grid_x[i0:j0,i1:j1] ...
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to be included in the source distribution --
tools/py3tool.py seems to be missing from the tarball.
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this part of the distutils code on Python 3, and indeed
it does not have any tests, so it's not a surprise that stuff like this
is left over :)
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of inspect (and hacks like this) into an
internal utility module that is fast to import.
We actually have `numpy.compat._inspect` and
from numpy.compat import getargspec
that could be used here.
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, category, stack_level);
(gdb)
That was probably fixed in r8394 in trunk.
But to be sure, can you supply the whole stack trace (type bt in the
gdb prompt).
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Mon, 02 Aug 2010 23:48:52 +0800, Ralf Gommers wrote:
I'm trying to get building to work with Python 3.1 under Wine on OS X.
The first thing you run into is a python distutils problem, which is
fixed by replacing line 379 of cygwinccompiler.py with
result =
Wed, 04 Aug 2010 23:34:15 +0800, Ralf Gommers wrote:
[clip]
I haven't started using py3k yet so I'm still a bit fuzzy about bytes
vs string. But it's easy to try in the interpreter:
import re
RE_VERSION = re.compile('(\d+\.\d+(\.\d+)*)')
In the Python 3.1 version I have, this line reads
since 1.4.x are unrelated.
I think the support for platform-provided complex functions was enabled
in r7986.
To be sure, we'd need to see the build log.
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of Numpy. On Python versions = 2.6 Numpy arrays expose the buffer
interface, and array(), asarray() and other functions accept new-style buffers
as input.
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Mon, 23 Aug 2010 15:30:19 -0500, Travis Oliphant wrote:
I'm curious as to the status of the Github migration and if there is
anything I can do to help. I have a couple of weeks right now and I
would love to see us make the transition of both NumPy and SciPy to GIT.
I think the more or less
Mon, 23 Aug 2010 23:31:14 +0200, Stéfan van der Walt wrote:
[clip]
Erk. What's the quickest route to go: compare the actual patches, or
bring a tree up to date for each revision and compute some sort of
working-copy checksum?
Working-copy checksumming is probably the easiest and most robust
Mon, 23 Aug 2010 21:15:55 +, Pauli Virtanen wrote:
[clip]
in the history to have the wrong content -- so to be sure, we have to do
a brute-force comparison of the tree against SVN for each commit. The
particular bug here was fixed in the conversion tool, but better safe
than sorry.
Also
-- it's the same issue. It's also a minor issue, IMHO, as I doubt
many people construct array scalars from strings, and even less do it in
bases other than 10. The fix is to change array scalar __new__, but this
is not completely straightforward to do. Patches are welcome.
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float96(0.0001), the result is not the float96 number
closest to 0.0001, but the 96-bit representation of the 64-bit number
closest to 0.0001. Indeed,
float96(0.0001), float96(1.0)/1000
(0.0001479, 0.0009996)
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-- if you need C-contiguity, you'll need to ensure it by using
`ascontiguousarray`.
Especially when we later on implement memory access pattern optimizations
for ufuncs, such assumptions will break down even more often.
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that call sscanf with the correct format string in the end.
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Thu, 02 Sep 2010 08:27:18 -0600, Charles R Harris wrote:
[clip]
Hi Pauli, I gave it a quick spin and it looks good so far. The cloning
was really fast, I like that ;) Is there any way to test out commiting?
I didn't have permissions to push to the repository.
You should have push permissions
branches/fix_float_format in SVN that got later on merged to
trunk. Github seems to show these in different colors, but in reality
they are just a part of the master branch history.
So all in all, it looks correct to me.
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be a problem. I'm not an
expert on this, however.
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Mon, 06 Sep 2010 10:41:38 +0200, Sebastian Haase wrote:
is there an URL of the weekly built CHM documentation file ?
It's the one linked from http://docs.scipy.org/doc/
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/to/liblapack.so ...
may work. This'll probably even make it to the documentation one day...
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not to include such a wrapper, so little
persuasion is needed. The only thing is that someone should spend some
time implementing this suggestion (and I probably won't -- I don't really
need that feature myself, and there are many other things that need to be
done).
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Fri, 10 Sep 2010 14:35:46 +0200, Radek Machulka wrote:
Thanks, but...
x = array([[0,0,0,0],[0,1,0,0],[0,0,1,1],[0,0,0,0]]) x
array([[0, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, 1, 1],
[0, 0, 0, 0]])
i, j = x.any(0).nonzero()[0], x.any(1).nonzero()[0]
Should be
j, i =
product.
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).astype(i4).dtype
dtype('i4')
np.array(42, dtype=i4).astype('i4').dtype
dtype('int32')
Doesn't seem correct -- please file a bug ticket.
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Mon, 13 Sep 2010 15:33:11 -0500, Travis Oliphant wrote:
Are we ready to do this yet?
I know there were some outstanding questions. Are there major concerns
remaining?
As far as the conversion is concerned, things should be OK.
The bugs in svn-all-fast-export have been fixed in the meantime,
Mon, 13 Sep 2010 21:41:18 +, Pauli Virtanen wrote:
[clip]
I can upload a final repository today/tomorrow. If it seems OK, we can
freeze SVN trunk a few days after that.
Or we can freeze the trunk sooner than that after the final repo is
up, and patch up things manually, if something
Mon, 13 Sep 2010 18:08:39 -0600, Charles R Harris wrote:
[clip]
What is the suggested work flow for the new repositories? Is the best
way to use a github fork and push and pull from that?
Yes, I'd personally work like that. Easier to keep private stuff separate.
Pauli
Mon, 13 Sep 2010 18:15:01 -0600, Charles R Harris wrote:
[clip]
I think we should freeze the svn repo as soon as possible. Pierre is
still making commits there and unless there is an easy way to update the
git repo from svn those sort of commits might be a small hassle.
It needs re-generation
Also look at CPython's objimpl.h, union _gc_head, you will see an
unprotected usage of 'long double', so it seems that CPython requires
that the C compiler to support 'long double'.
Long double is IIRC in C89, so compiler support is probably not a problem
nowadays.
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. But let's do this directly in Git, so that I don't
have to bother regenerating the Numpy repo.
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Dear all,
Numpy SVN repository is now frozen, and does not accept new commits.
Future development should end up in the Git repository:
http://github.com/numpy/numpy
The next things on the TODO list:
- Update any links that point to http://svn.scipy.org/svn/numpy
or talk about SVN.
Thu, 16 Sep 2010 08:58:46 +, Pauli Virtanen wrote:
The next things on the TODO list:
- Update any links that point to http://svn.scipy.org/svn/numpy
or talk about SVN.
E.g. numpy.org needs updating.
- Put up documentation on how to contribute to Numpy via Git
Mon, 20 Sep 2010 23:34:58 +0200, Hagen Fürstenau wrote:
I don't know if I'm overlooking something obvious, but is there a
compact way of computing the 3-array
X_{ijk} = \sum_{l} A_{il}*B_{jl}*C_{kl}
out of the 2-arrays A, B, and C?
?
It probably shouldn't do *that* at the least.
http://projects.scipy.org/numpy/ticket/1618
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the reason for
x.real is x
True
x.imag
array([0], dtype=object)
But it is a minor corner case, and there may be backward compatibility
issues in changing it.
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approaching a release.
Ticket #633 is likely mostly solved now. There's a patch fixing bugs in
object array refcounting at http://scipy.org/scipy/numpy/ticket/633
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to be solved. But I'm afraid I'm not
intimate enough with the mecanisms of Numpys arrays to solve it.
I wrote a second patch that I think fixes the problem, and it seems to
work at least for the testcases I tried.
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, adding it also to the docstring is extraneous.
For functions implemented in C in extension modules, help() cannot find
the signature automatically. However, the CodingStyleGuidelines does say
that in this case including the function signature to the documentation
is mandatory.
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.
scipy.optimize.fmin_slsqp
Minimize a function using Sequential Least SQuares Programming
... more results, shown in a pager ...
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-BEGIN PGP SIGNATURE-
Version: GnuPG v1.4.6 (GNU/Linux)
Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org
iD8DBQFH/n
Travis E. Oliphant kirjoitti:
Pauli Virtanen wrote:
[clip]
I think this is a good idea: full-namespace docstring search à la Matlab
lookfor. I wrote a quick implementation for numpy here:
http://scipy.org/scipy/numpy/ticket/734
Cool. I started scipy.misc.info a long time ago to try
it. (Download the file, and import ipy_lookfor.py to
get a magic %lookfor command.)
It's a bit rough right now, but I don't have time to finish it today.
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there's the possibility that this is a
compiler bug.
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wilson kirjoitti:
hi
what exactly does diagonalising a matrix mean?
http://en.wikipedia.org/wiki/Matrix_diagonalization
how do you do it on a symmetric numpy array?
Compute the eigenvalues and eigenvectors using numpy.linalg.eigh.
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) and
just fix the docstring and the normed=True bug? (I have a patch doing
this.)
So which one (or something else) do we choose for 1.1.0?
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functions are the same.
So, which one of these is correct? Or, does ndarray.reshape always
return a view? This is not immediately obvious looking at the code...
I'll fix up the docstrings once I know.
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enabled Atlas, this sounds like bug #551
(http://scipy.org/scipy/numpy/ticket/551#comment:22) to me. Is this the
case? Can you reproduce a segmentation fault with the simple C-only test
case?
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that much effort.
Small thing: would it be possible to use only two colors in the figleaf
output, eg. uncovered code red, everything else black. The black bits in
between are now slightly distracting.
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Hi,
Something seems to be wrong with the Trac:
http://scipy.org/scipy/numpy/timeline
Internal Error
Ticket changes event provider (TicketModule) failed:
SubversionException: (Can't open file
'/home/scipy/svn/numpy/db/revprops/5159': Permission denied, 13)
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ti, 2008-05-13 kello 23:00 -0700, Jarrod Millman kirjoitti:
On Tue, May 13, 2008 at 1:37 AM, Pauli Virtanen [EMAIL PROTECTED] wrote:
Something seems to be wrong with the Trac:
http://scipy.org/scipy/numpy/timeline
Internal Error
Ticket changes event provider (TicketModule) failed
benchmark led to believe.
Benchmark files attached, in case someone wants to contest my analysis.
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from mybench import *
a = bench_array()
b = bench_array()
print a.typecode:,a.typecode(),, a.shape:,a.shape
print b.typecode:,b.typecode(),, b.shape:,b.shape
print calculating
Hi,
su, 2008-05-18 kello 07:16 -0600, Steven H. Rogers kirjoitti:
Joe Harrington wrote:
NUMPY/SCIPY DOCUMENTATION MARATHON 2008
...
5. Write a new help function that optionally produces ASCII or points
the user's PDF or HTML reader to the right page (either local or
global).
ti, 2008-05-20 kello 20:06 +0200, Rob Hetland kirjoitti:
On May 20, 2008, at 7:30 PM, Stéfan van der Walt wrote:
and send us your UserName.
Oh, and my username is RobHetland
You're in now.
Regards,
Pauli
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to concentrate on
improving the documentation in English before thinking about spending
much effort on i18n or l10n.
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ke, 2008-05-21 kello 10:08 +0200, Stéfan van der Walt kirjoitti:
[clip]
This will parse better (as the line with the semicolon is bold, the
next lines are not). Also, would it be possible to put function and
next_function in double back-ticks, so that they are referenced, like
modules?
to, 2008-05-22 kello 11:28 -0700, joep kirjoitti:
[clip]
However, when I do a search on the DocWiki for example for arccos (or
log, log10, exp, tan,...), I see it 9 times, and it is not clear which
ones refer to the same docstring and where several imports of the same
function are picked up
= type(object)
...
Is it possible to make one of the above conditions True for ufuncs?
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, 0.77487798]])
fn()
*** glibc detected *** python: munmap_chunk(): invalid pointer:
0x08439d28 ***
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to, 2008-05-29 kello 10:53 -0700, Keith Goodman kirjoitti:
On Thu, May 29, 2008 at 9:26 AM, Stéfan van der Walt [EMAIL PROTECTED]
wrote:
2008/5/23 Keith Goodman [EMAIL PROTECTED]:
On Fri, May 23, 2008 at 11:44 AM, Robert Kern [EMAIL PROTECTED] wrote:
[clip]
That makes sense. Hopefully it
Hi,
I'd like to adjust the way numpy.core.umath ufunc docstrings are defined
to make them more easy to handle in the ongoing documentation marathon:
- Remove the signature magic in ufunc_get_doc
- Define ufunc docstrings in a separate module
instead of in generate_umath.py, in the same format
la, 2008-05-31 kello 15:02 -0500, Travis E. Oliphant kirjoitti:
Pauli Virtanen wrote:
Hi,
I'd like to adjust the way numpy.core.umath ufunc docstrings are
defined to make them more easy to handle in the ongoing
documentation marathon:
Thanks for your efforts here. It would be good
la, 2008-05-31 kello 17:56 -0400, Tony Yu kirjoitti:
[clip]
I've been playing around with some software using numpy 1.0.4 and took
a crack at upgrading it to numpy 1.1.0, but I ran into some strange
behavior when assigning to slices of a masked array.
[clip]
In [1]: import numpy
In [2]:
la, 2008-05-31 kello 22:49 +0300, Pauli Virtanen kirjoitti:
Hi,
I'd like to adjust the way numpy.core.umath ufunc docstrings are defined
to make them more easy to handle in the ongoing documentation marathon:
- Remove the signature magic in ufunc_get_doc
- Define ufunc docstrings
ma, 2008-06-09 kello 11:11 -0400, Tommy Grav kirjoitti:
With the most recent change in numpy 1.1 it seems that numpy.histogram
was broken when wanting a normalized histogram. I thought the idea was
to leave the functionality of histogram as it was in 1.1 and then
break the api in 1.2?
[clip]
is useful for reducing the whitespace in array
printout.
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.
Another idea (in addition to whitelisting): how easy would it be to
subclass doctest.DocTestParser so that it would eg. automatically +IGNORE
any doctest lines containing plt.?
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the ability to run
also the matplotlib examples as (optional) doctests, to make sure also
they execute correctly. Also, using two different markups in the
documentation to work around a shortcoming of doctest is IMHO not very
elegant.
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...) and submitted a patch
that got applied.
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=== First the preliminary set up: ===
In [3]: A = numpy.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10],
[11, 12]]])
In [4]: A
Out[4]:
array([[[ 1, 2],
[ 3, 4]],
[[ 5, 6],
[ 7, 8
:
[clip]
I put this report in as ticket #843
http://scipy.org/scipy/numpy/ticket/843
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if I actually registered twice...
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Tue, 08 Jul 2008 23:03:52 -0500, Robert Kern wrote:
On Tue, Jul 8, 2008 at 14:01, Keith Goodman [EMAIL PROTECTED] wrote:
I don't know what to write for a doc string for alterdot and
restoredot.
Then maybe you're the best one to figure it out. What details do you
think are missing from the
Mon, 14 Jul 2008 18:05:27 -0600, Charles R Harris wrote:
All,
The rc release of numpy-1.1.1 is due out next Sunday. I have gone
through the commits made to the trunk since the 1.1.x branch to pull out
backport candidates. If you find your name here could you make the
backport or say why you
http://scipy.org/scipy/numpy/ticket/837
Infinite loop in fromfile and fromstring with sep=' ' and malformed input.
I committed a fix to trunk. Does this need a 1.1.1 backport?
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Wed, 16 Jul 2008 15:43:00 -0600, Charles R Harris wrote:
On Wed, Jul 16, 2008 at 3:05 PM, Pauli Virtanen [EMAIL PROTECTED] wrote:
http://scipy.org/scipy/numpy/ticket/837
Infinite loop in fromfile and fromstring with sep=' ' and malformed
input.
I committed a fix to trunk. Does
Hi,
Since r5443 the Sparc buildbots show a Bus error in the test phase:
http://buildbot.scipy.org/builders/Linux_SPARC_64_Debian/
builds/102/steps/shell_2/logs/stdio
while the one on FreeBSD-64 passes.
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533, in __init__
self.root = fs.revision_root(fs_ptr, rev, self.pool())
SubversionException: (Can't open file '/home/scipy/svn/numpy/db/revs/5447':
Permission denied, 13)
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to backport at the moment.
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tests for all the functions with branch cuts to verify
that the cuts and their continuity are correct. (Where correct bears
some resemblance to ISO C standard, I think...)
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, skipped.
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thing is the second test in test_clog,
which is (+0., 0.), (-inf, 0.). Does this vanish if you comment it out?
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Tue, 22 Jul 2008 15:13:09 -0500, Robert Kern wrote:
On Tue, Jul 22, 2008 at 14:57, Pauli Virtanen [EMAIL PROTECTED] wrote:
Tue, 22 Jul 2008 00:34:46 -0600, Charles R Harris wrote:
FAIL: test_umath.TestC99.test_clog(ufunc 'log', (-0.0, -0.0), (-inf,
-0.0), 'divide')
AssertionError: ('(-inf
according to a binary decomposition.
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numpy versions the same on these platforms? Do you have two
numpy versions installed. Could it be possible that somehow running the
scripts switches between numpy versions? (Sounds very strange, and of
course, this is easy to check for in test.py...)
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