Ondrej Certik wrote:
Hi,
since there was so much discussion whether bzr or hg, Mercurial has
now free hosting too:
http://freehg.org/
also Mercurial 1.0 was finally released yesterday.
That's really good news.
Bzr has Launchpad, that's one of the (main) reasons ipython is
On Wed, Mar 26, 2008 at 11:36:18AM +0200, Ville M. Vainio wrote:
I think the killer issue here is Launchpad. We get pretty much
everything for free, and it's something that we can expect to stay
around in the long haul (and will continue to improve). The slight
performance disadvantage of bzr
Gael Varoquaux wrote:
I have watch developpers switch to DVCS lately, and I must say it
requires a certain change in working habits. Let us wait for people to
get used to these new tools before discussing which one to you.
I personally think that the supposed difficulty of DVCS is greatly
On Wed, Mar 26, 2008 at 07:08:31PM +0900, David Cournapeau wrote:
Gael Varoquaux wrote:
I have watch developpers switch to DVCS lately, and I must say it
requires a certain change in working habits. Let us wait for people to
get used to these new tools before discussing which one to you.
Gael Varoquaux wrote:
Look, I am not talking about theory,
I was not talking about theory:
- svn co url - bzr co url
- svn commit -m bla bla - bzr ci -m bla bla
- svn up - bzr up
- svn log - bzr log
- svn blame - bzr blame
You cannot be more concrete than that :)
I agree
On Wed, Mar 26, 2008 at 07:26:13PM +0900, David Cournapeau wrote:
Gael Varoquaux wrote:
Look, I am not talking about theory,
I was not talking about theory:
- svn co url - bzr co url
- svn commit -m bla bla - bzr ci -m bla bla
- svn up - bzr up
- svn log - bzr log
-
2008/3/26, David Cournapeau [EMAIL PROTECTED]:
Gael Varoquaux wrote:
Except that very often when you do a bzr up you have to do a merge
because bzr makes obvious branching that is implicit with the svn model.
bzr does not branch implicitly, as far as I know, so I am not sure to
All,
What's the quickest way to create a diagonal matrix ? I already have the
elements above the main diagonal. Of course, I could use loops:
m=5
z = numpy.arange(m*m).reshape(m,m)
for k in range(m):
for j in range(k+1,m):
z[j,k] = z[k,j]
But I was looking for something more
Hi,
Did you try diag() ? Or are you saying a symmetric matrix ?
Matthieu
2008/3/26, Pierre GM [EMAIL PROTECTED]:
All,
What's the quickest way to create a diagonal matrix ? I already have the
elements above the main diagonal. Of course, I could use loops:
m=5
z =
On Wed, Mar 26, 2008 at 09:48:02AM -0400, Pierre GM wrote:
All,
What's the quickest way to create a diagonal matrix ? I already have the
elements above the main diagonal. Of course, I could use loops:
m=5
z = numpy.arange(m*m).reshape(m,m)
for k in range(m):
for j in range(k+1,m):
numpy.tri
In [31]: T = numpy.tri(m)
In [32]: z.T * T + z * T.T
Out[32]:
array([[ 0., 1., 2., 3., 4.],
[ 1., 12., 7., 8., 9.],
[ 2., 7., 24., 13., 14.],
[ 3., 8., 13., 36., 19.],
[ 4., 9., 14., 19., 48.]])
hth,
L.
On Wed, Mar 26,
On 26 Mar 2008, at 15:36, lorenzo bolla wrote:
numpy.tri
In [31]: T = numpy.tri(m)
In [32]: z.T * T + z * T.T
Out[32]:
array([[ 0., 1., 2., 3., 4.],
[ 1., 12., 7., 8., 9.],
[ 2., 7., 24., 13., 14.],
[ 3., 8., 13., 36., 19.],
[
Greetings,
I'm pleased to announce the release 00.41.03 of SfePy (formerly SFE)
SfePy is a finite element analysis software in Python, based primarily
on Numpy and SciPy.
Mailing lists, issue tracking, mercurial repository:
http://code.google.com/p/sfepy/
Home page: http://sfepy.kme.zcu.cz
I like obfuscating things! Maybe I should switch to perl :-)
you can use a one-liner like this:
scipy.linalg.triu(z) + scipy.linalg.triu(z,k=1).T
my %timeit gives roughly the same execution speed as your f(z):
In [79]: %timeit f(z)
1 loops, best of 3: 79.3 us per loop
In [80]: %timeit h(z)
Robert Cimrman wrote:
I'm pleased to announce the release 00.41.03 of SfePy (formerly SFE)
very cool!
Totally off-topic, but how did you build that nifty pdf slide show?
(introduction_slide.pdf)
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR
If the rest of the matrix is already zeros and memory wasn't a
problem, you could just use
A_sym = A + A.T - diag(diag(A))
If memory was an issue, I'd suggest weave.inline (if that's a viable
option) or pyrex to do the loop, which would be about as fast as you
could get.
--Hoyt
On Wed, Mar
Hello,
I used to be able to inherit form nump.oldnumeric.ma.array, it looks
like you can't any longer.
I replaced it with:
numpy.ma.MaskedArray
i'm getting:
result = result.reorder(order).regrid(grid)
AttributeError: 'MaskedArray' object has no attribute 'reorder'
Should I inherit from
Matt Knox wrote:
data = [1., 2., 3., np.nan, 5., 6.]
mask = [0, 0, 0, 1, 0, 0]
I'm creating the ma with ma.masked_where...
marr = ma.array(data, mask=mask)
marr.set_fill_value(55)
print marr[0] is ma.masked # False
print marr[3] # ma.masked constant
Yeah, and this is where I have the
On Fri, Mar 21, 2008 at 9:32 AM, Stéfan van der Walt [EMAIL PROTECTED] wrote:
Not exactly. What do people think of the way I organized the numpy
functions by category page? Apart from the sore-thumb other
category, it does seem like the kind of grouping we might hope for.
I can see
Pierre GM wrote:
My bad, I neglected an overall doc for the functions and their docstring. But
you know what ? As you're now at an intermediary level,
That's pretty unkind to your userbase. I know a lot about python, but
I'm a total novice with numpy and even the maths it's based on.
help:
All,
Yes, I was talking about symmetric matrices. Sorry for the confusion.
Thanks a lot for your answers. The slices approach looks the best indeed. I
was hoping that there was some way to use smart indexing, but it really looks
like too complicated.
Thx again
P.
P.
Charles,
result = result.reorder(order).regrid(grid)
AttributeError: 'MaskedArray' object has no attribute 'reorder'
Should I inherit from soemtihng else ?
Mmh, .reorder is not a regular ndarray method, so that won't work. What is it
supposed to do ? And regrid ?
Aslo I used to import a
The reorder is a function we implement. By digging a bit into this my
guess is that all the missing function in numpy.ma are causing to fail
at some point in our init and returning the wrong object type.
But the whole idea was to keep a backward compatible layer with Numeric
and MA. It worked
On Wednesday 26 March 2008 15:42:41 Chris Withers wrote:
Pierre GM wrote:
My bad, I neglected an overall doc for the functions and their docstring.
But you know what ? As you're now at an intermediary level,
That's pretty unkind to your userbase. I know a lot about python, but
I'm a total
Charles Doutriaux wrote:
The reorder is a function we implement. By digging a bit into this my
guess is that all the missing function in numpy.ma are causing to fail
at some point in our init and returning the wrong object type.
But the whole idea was to keep a backward compatible layer
Charles,
numpy.ma is supposed to replace numpy.core.ma only. I don't know what happened
to numpy.oldnumeric.ma, more exactly when it was dropped. A quick search on
the trac indicates it happens a while ago (before version 1.0.1)...
In short, the major difference between the old (numpy.core.ma)
Hi folks-
Can anyone offer any tips on how I can get epydoc to produce
API documentation for functions in an f2py-produced module?
Currently they get listed in the generated docs as Variables:
Variables
psigc = fortran object at 0xa3e46b0
sigctp = fortran object at 0xa3e4698
Does numpy have something like Matlab's accumarray?
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/accumarray.html
Best, Gabriel
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
On Wed, Mar 26, 2008 at 5:20 PM, Gabriel J.L. Beckers
[EMAIL PROTECTED] wrote:
Does numpy have something like Matlab's accumarray?
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/accumarray.html
No.
--
Robert Kern
I have come to believe that the whole world is an enigma, a
Hi all,
The docstring for vander() seems to contradict what the function does. In
particular, the columns in the vander() output seem reversed wrt its
docstring. I feel like one of the two needs to be fixed, or is there
something I'm not seeing?
This here is fresh from the Numpy examples
On Wed, Mar 26, 2008 at 5:22 PM, Andreas Klöckner [EMAIL PROTECTED]
wrote:
Hi all,
The docstring for vander() seems to contradict what the function does. In
particular, the columns in the vander() output seem reversed wrt its
docstring. I feel like one of the two needs to be fixed, or is
On Wed, Mar 26, 2008 at 5:20 PM, Gabriel J.L. Beckers [EMAIL PROTECTED]
wrote:
Does numpy have something like Matlab's accumarray?
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/accumarray.html
On Wed, 26 Mar 2008, Robert Kern apparently wrote:
No.
But of course you can do
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