Hi Neil,
Neil Crighton wrote:
Hi all,
I posted this message couple of days ago, but gmane grouped it with an old
thread and it hasn't shown up on the front page. So here it is again...
I'd really like to see the setmember1d_nu function in ticket 1036 get into
numpy. There's a patch
On Tue, Jun 2, 2009 at 10:56 PM, Ryan May rma...@gmail.com wrote:
On Tue, Jun 2, 2009 at 5:59 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David Cournapeau courn...@gmail.com
wrote:
Done in r7031 - correlate/PyArray_Correlate
Hi,
The RC1 for 0.7.1 scipy release has just been tagged. This is a
bug-only release, see below for the release notes. More information can
also be found on the trac website:
http://projects.scipy.org/scipy/milestone/0.7.1
Please test it !
The scipy developers
--
=
On 3-Jun-09, at 5:01 PM, Pauli Virtanen wrote:
Btw, are you able to change the status of the ticket to
needs_review?
I think this should be possible for everyone, and not restricted to
admins, but I'm not 100% sure...
Sorry Pauli, seems I _don't_ have permission on the numpy trac to
Hi,
is there a BigInteger equivalent in numpy? The largest integer type I
wound was dtype int64.
I'm using stats.linregress to perform a regression analysis. The return
stderr was nan because stas.ss(...) returned a negative number due to an
overflow. Setting dtype to int64 for my input data
a[(a==b[:,None]).sum(axis=0,dtype=bool)]
hth,
Alan Isaac
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On Thu, Jun 4, 2009 at 8:23 AM, Alan G Isaac ais...@american.edu wrote:
a[(a==b[:,None]).sum(axis=0,dtype=bool)]
this is my preferred way when b is small and has unique elements.
if the elements in b are not unique, then be can be replaced by np.unique(b)
If b is large this creates a huge
On Thu, Jun 4, 2009 at 8:19 AM, wierob wiero...@googlemail.com wrote:
Hi,
is there a BigInteger equivalent in numpy? The largest integer type I
wound was dtype int64.
I'm using stats.linregress to perform a regression analysis. The return
stderr was nan because stas.ss(...) returned a
2009/6/4 David Warde-Farley d...@cs.toronto.edu:
Sorry Pauli, seems I _don't_ have permission on the numpy trac to
change ticket status. The radio button shows up but then it gives me a
Warning: No permission to change ticket fields.
Should be fixed.
Cheers
Stéfan
Hi all,
I would be glad if someone could help me with
the following issue:
From what I've read on the web it appears to me
that numpy should be about as fast as matlab. However,
when I do simple matrix multiplication, it consistently
appears to be about 5 times slower. I tested this using
A =
Have a look at this thread:
http://www.mail-archive.com/numpy-discussion@scipy.org/msg13085.html
The speed difference is probably due to the fact that the matrix
multiplication does not call optimized an optimized blas routine, e.g.
the ATLAS blas.
Sebastian
On Thu, Jun 4, 2009 at 3:36 PM,
On Thu, Jun 4, 2009 at 8:23 AM, Alan G Isaac ais...@american.edu wrote:
a[(a==b[:,None]).sum(axis=0,dtype=bool)]
On 6/4/2009 8:35 AM josef.p...@gmail.com apparently wrote:
If b is large this creates a huge intermediate array
True enough, but one could then use fromiter:
setb = set(b)
itr =
On Thu, Jun 4, 2009 at 5:14 AM, David Cournapeau courn...@gmail.com wrote:
On Tue, Jun 2, 2009 at 10:56 PM, Ryan May rma...@gmail.com wrote:
On Tue, Jun 2, 2009 at 5:59 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Robin wrote:
On Tue, Jun 2, 2009 at 11:36 AM, David
On Thu, Jun 4, 2009 at 10:13 AM, Alan G Isaac ais...@american.edu wrote:
On Thu, Jun 4, 2009 at 8:23 AM, Alan G Isaac ais...@american.edu wrote:
a[(a==b[:,None]).sum(axis=0,dtype=bool)]
On 6/4/2009 8:35 AM josef.p...@gmail.com apparently wrote:
If b is large this creates a huge intermediate
Thanks for the responses. I did not realize that dot() would do matrix
multiplication which was the main reason I was looking for a matrix-like
class. Like you and Tom suggested, I think it's best to stick to arrays.
Cheers,
Jason
On Sun, May 24, 2009 at 6:45 PM, David Warde-Farley
Hi,
The RC1 for 0.7.1 scipy release has just been tagged. This is a
bug-only release
I feel (y)our pain, but don't you mean 'bug-fix only release'? ;-)
Matthew
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On Thu, Jun 4, 2009 at 10:13 AM, Alan G Isaac ais...@american.edu wrote:
Or if a stable order is not important (I don't
recall if the OP specified), one could just
np.intersect1d(a, np.unique(b))
On 6/4/2009 10:50 AM josef.p...@gmail.com apparently wrote:
This requires that also `a` has only
On Thu, Jun 4, 2009 at 11:12 AM, Alan G Isaac ais...@american.edu wrote:
On Thu, Jun 4, 2009 at 10:13 AM, Alan G Isaac ais...@american.edu wrote:
Or if a stable order is not important (I don't
recall if the OP specified), one could just
np.intersect1d(a, np.unique(b))
On 6/4/2009 10:50 AM
On 6/4/2009 10:50 AM josef.p...@gmail.com apparently wrote:
intersect1d gives set intersection if both arrays have
only unique elements (i.e. are sets). I thought the
naming is pretty clear:
intersect1d(a,b) set intersection if a and b with unique elements
intersect1d_nu(a,b) set
Alan G Isaac wrote:
On 6/4/2009 10:50 AM josef.p...@gmail.com apparently wrote:
intersect1d gives set intersection if both arrays have
only unique elements (i.e. are sets). I thought the
naming is pretty clear:
intersect1d(a,b) set intersection if a and b with unique elements
On Thu, Jun 4, 2009 at 11:19 AM, Alan G Isaac ais...@american.edu wrote:
On 6/4/2009 10:50 AM josef.p...@gmail.com apparently wrote:
intersect1d gives set intersection if both arrays have
only unique elements (i.e. are sets). I thought the
naming is pretty clear:
intersect1d(a,b) set
After yesterdays discussion, I wanted to see if views of structured
arrays with mixed type can be easily used.
Is the following useful for the numpy user guide?
Josef
Calculations with mixed type structured arrays
--
import numpy as np
The
2009/6/4 Matthew Brett matthew.br...@gmail.com:
The RC1 for 0.7.1 scipy release has just been tagged. This is a
bug-only release
I feel (y)our pain, but don't you mean 'bug-fix only release'? ;-)
Thanks, guys! You made my weekend :-)
Cheers
Stéfan
On 4-Jun-09, at 9:28 AM, Stéfan van der Walt wrote:
2009/6/4 David Warde-Farley d...@cs.toronto.edu:
Sorry Pauli, seems I _don't_ have permission on the numpy trac to
change ticket status. The radio button shows up but then it gives
me a
Warning: No permission to change ticket fields.
On Sun, May 24, 2009 at 3:45 PM, David Warde-Farley d...@cs.toronto.edu wrote:
Anecdotally, it seems to me that lots of people (myself included) seem
to go through a phase early in their use of NumPy where they try to
use matrix(), but most seem to end up switching to using 2D arrays for
all
On Sun, May 24, 2009 at 3:45 PM, David Warde-Farley d...@cs.toronto.edu
wrote:
Anecdotally, it seems to me that lots of people (myself included) seem
to go through a phase early in their use of NumPy where they try to
use matrix(), but most seem to end up switching to using 2D arrays for
I really don't see any advantage of matrices over arrays for teaching. I
prefer to teach linear algebra with arrays.
I would also like matrices to disappear from numpy. But then one would need
a new implementation of scipy.sparse, which is (very unfortunately)
matrix-based at the moment.
==
On 6/4/2009 11:29 AM josef.p...@gmail.com apparently wrote:
intersect1d is the intersection between sets (which are stored as
arrays), just like in the mathematical definition the two sets only
have unique elements
Hmmm. OK, I see you and Robert believe this.
But it does not match the
On 6/4/2009 12:08 PM Olivier Verdier apparently wrote:
I really don't see any advantage of matrices over arrays for teaching. I
prefer to teach linear algebra with arrays.
beta = (X.T*X).I * X.T * Y
beta = np.dot(np.dot(la.inv(np.dot(X.T,X)),X.T),Y)
I rest my case.
I would have to switch
Has this been considered as a candidate for our fft?
http://sourceforge.net/projects/kissfft
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On Thu, Jun 4, 2009 at 12:32 PM, Alan G Isaac ais...@american.edu wrote:
On 6/4/2009 11:29 AM josef.p...@gmail.com apparently wrote:
intersect1d is the intersection between sets (which are stored as
arrays), just like in the mathematical definition the two sets only
have unique elements
On Thu, Jun 4, 2009 at 11:58, Neal Becker ndbeck...@gmail.com wrote:
Has this been considered as a candidate for our fft?
http://sourceforge.net/projects/kissfft
No. What would be the advantage of moving to Kiss FFT to offset the cost?
--
Robert Kern
I have come to believe that the whole
Hi -
thanks for all the good work on this!
I have been using an older version of the ETS, which I got when I installed
the EPD (4.0.30001) and now I have finally gotten around to trying to update
my ETS to this version.
I have a question - how do I go about uninstalling my previous version of
Robert Kern wrote:
On Thu, Jun 4, 2009 at 11:58, Neal Becker ndbeck...@gmail.com wrote:
Has this been considered as a candidate for our fft?
http://sourceforge.net/projects/kissfft
No. What would be the advantage of moving to Kiss FFT to offset the cost?
I was reading this:
On 6/4/2009 1:27 PM josef.p...@gmail.com apparently wrote:
Note: there are two versions of the docs for np.intersect1d, the
currently published docs which describe the actual behavior (for the
non-unique case), and the new docs on the doc editor
Howdy,
2009/6/3 Stéfan van der Walt ste...@sun.ac.za:
however i seem to lose simple operations such as multiplication (a_array*2)
or powers (a_array**2).
As a workaround, you can have two views on your data:
I was thinking about this yesterday, because I'm dealing with exactly
this same
On Thu, Jun 4, 2009 at 13:30, Neal Becker ndbeck...@gmail.com wrote:
Robert Kern wrote:
On Thu, Jun 4, 2009 at 11:58, Neal Becker ndbeck...@gmail.com wrote:
Has this been considered as a candidate for our fft?
http://sourceforge.net/projects/kissfft
No. What would be the advantage of
On Jun 4, 2009, at 3:12 PM, Fernando Perez wrote:
Howdy,
I was thinking about this yesterday, because I'm dealing with exactly
this same problem in a local project. How hard would it be to allow
structured arrays to support ufuncs/arithmetic for the case where
their dtype is actually a
On Thu, Jun 4, 2009 at 2:58 PM, Alan G Isaac ais...@american.edu wrote:
On 6/4/2009 1:27 PM josef.p...@gmail.com apparently wrote:
Note: there are two versions of the docs for np.intersect1d, the
currently published docs which describe the actual behavior (for the
non-unique case), and the new
On Thu, Jun 04, 2009 at 11:03:36AM -0700, Ariel Rokem wrote:
I have a question - how do I go about uninstalling my previous version of
the ETS? A more general question to anyone - what's the right way of
uninstalling any old python package? In the past, I have been advised to
go in
Thu, 04 Jun 2009 19:24:32 +0900, David Cournapeau wrote:
[clip]
=
SciPy 0.7.1 Release Notes
=
.. contents::
SciPy 0.7.1 is a bug-fix release with no new features compared to 0.7.0.
scipy.special
=
Several bugs of varying
Concerning the name setmember1d_nu, I personally find it quite verbose
and not the name I would expect as a non-insider coming to numpy and
not knowing all the names of the more special hidden-away functions
and not being a python-wiz either.
I think ain(a,b) would be the name I had expected as
On Thu, Jun 04, 2009 at 10:27:11PM +0200, Kim Hansen wrote:
in(b) or in_iterable(b) method, such that you could do a.in(b)
which would return a boolean array of the same shape as a with
elements true if the equivalent a members were members in the iterable
b.
That would really by what I would
2009/6/4 josef.p...@gmail.com:
intersect1d should throw a domain error if you give it arrays with
non-unique elements, which is not done for speed reasons
It seems to me that this is the basic source of the problem. Perhaps
this can be addressed? I realize maintaining compatibility with the
On Thu, Jun 4, 2009 at 4:30 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jun 04, 2009 at 10:27:11PM +0200, Kim Hansen wrote:
in(b) or in_iterable(b) method, such that you could do a.in(b)
which would return a boolean array of the same shape as a with
elements true if the
On Thu, Jun 04, 2009 at 04:43:39PM -0400, josef.p...@gmail.com wrote:
Just using in might promise more than it does, eg. it works only for
one dimensional arrays, maybe in1d. With in,
Then 'in_1d'
I found arraysetops because of unique1d, but I didn't figure out what
the subpackage really
Sebastian is right.
Since Matlab r2007 (i think that's the version) it has included support for
multi-core architecture. On my core2 Quad here at the office, r2008b has no
problem utilizing 100% cpu for large matrix multiplications.
If you download and build atlas and lapack from source and
I should update after reading the thread Sebastian linked:
The current 1.3 version of numpy (don't know about previous versions) uses
the optimized Atlas BLAS routines for numpy.dot() if numpy was compiled with
these libraries. I've verified this on linux only, thought it shouldnt be
any
2009/6/4 David Paul Reichert d.p.reich...@sms.ed.ac.uk:
Hi all,
I would be glad if someone could help me with
the following issue:
From what I've read on the web it appears to me
that numpy should be about as fast as matlab. However,
when I do simple matrix multiplication, it consistently
Keith Goodman wrote:
Maybe announcing that numpy will drop support for matrices in a future
version (3.0, ...) would save a lot of pain in the long run.
Or make them better. There was a pretty good discussion of this a while
back on this list. We all had a lot of opinions, and there were some
On Jun 4, 2009, at 5:25 PM, Christopher Barker wrote:
Keith Goodman wrote:
Maybe announcing that numpy will drop support for matrices in a
future
version (3.0, ...) would save a lot of pain in the long run.
Or make them better. There was a pretty good discussion of this a
while
back
On 6/4/2009 5:27 PM Tommy Grav apparently wrote:
Or the core development team split the matrices out of numpy and make it
as separate package that the people that use them could pick up and
run with.
This too would be a mistake, I believe.
But it depends on whether a goal is to
have more
On Jun 4, 2009, at 5:41 PM, Alan G Isaac wrote:
On 6/4/2009 5:27 PM Tommy Grav apparently wrote:
Or the core development team split the matrices out of numpy and
make it
as separate package that the people that use them could pick up and
run with.
This too would be a mistake, I believe.
Matthew Brett wrote:
Hi,
The RC1 for 0.7.1 scipy release has just been tagged. This is a
bug-only release
I feel (y)our pain, but don't you mean 'bug-fix only release'? ;-)
Actually, there is one big bug on python 2.6 for mac os x, so maybe the
bug-only is appropriate :)
Neal Becker wrote:
Has this been considered as a candidate for our fft?
http://sourceforge.net/projects/kissfft
I looked at it when I was looking for a BSD-compatible FFT with support
for prime factors (which fftpack does not handle). As Robert mentioned,
I did not see any compelling
On 4-Jun-09, at 5:03 PM, Anne Archibald wrote:
Apart from the implementation issues people have chimed in about
already, it's worth noting that the speed of matrix multiplication
depends on the memory layout of the matrices. So generating B instead
directly as a 100 by 500 matrix might affect
David Warde-Farley wrote:
On 4-Jun-09, at 5:03 PM, Anne Archibald wrote:
Apart from the implementation issues people have chimed in about
already, it's worth noting that the speed of matrix multiplication
depends on the memory layout of the matrices. So generating B instead
directly as a
On Thu, Jun 4, 2009 at 4:52 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jun 04, 2009 at 04:43:39PM -0400, josef.p...@gmail.com wrote:
Just using in might promise more than it does, eg. it works only for
one dimensional arrays, maybe in1d. With in,
Then 'in_1d'
No, if the
josef.p...@gmail.com wrote:
On Thu, Jun 4, 2009 at 2:58 PM, Alan G Isaac ais...@american.edu wrote:
On 6/4/2009 1:27 PM josef.p...@gmail.com apparently wrote:
Note: there are two versions of the docs for np.intersect1d, the
currently published docs which describe the actual behavior (for the
Kim Hansen wrote:
Concerning the name setmember1d_nu, I personally find it quite verbose
and not the name I would expect as a non-insider coming to numpy and
not knowing all the names of the more special hidden-away functions
and not being a python-wiz either.
To explain the naming: those
Anne Archibald wrote:
2009/6/4 josef.p...@gmail.com:
intersect1d should throw a domain error if you give it arrays with
non-unique elements, which is not done for speed reasons
It seems to me that this is the basic source of the problem. Perhaps
this can be addressed? I realize
josef.p...@gmail.com wrote:
On Thu, Jun 4, 2009 at 4:30 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jun 04, 2009 at 10:27:11PM +0200, Kim Hansen wrote:
in(b) or in_iterable(b) method, such that you could do a.in(b)
which would return a boolean array of the same shape as a
On Fri, Jun 5, 2009 at 1:48 AM, Robert Cimrman cimrm...@ntc.zcu.cz wrote:
josef.p...@gmail.com wrote:
On Thu, Jun 4, 2009 at 4:30 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Jun 04, 2009 at 10:27:11PM +0200, Kim Hansen wrote:
in(b) or in_iterable(b) method, such that you
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