All,
* What versions of Python should be supported by what version of numpy ? Are we to expect users to rely on Python2.5 for the upcoming 1.3.x ? Could we have some kind of timeline on the trac site or elsewhere (and if such a timeline exists already, can I get the link?) ?
* Talking about 1.3.x, what's the timeline? Are we still shooting for a release in 2008 or could we wait till mid Jan. 2009 ?
Thx a lot in advance
On Sun, Dec 7, 2008 at 12:02 PM, Pierre GM pgmdevlist@gmail.com wrote:
- What versions of Python should be supported by what version of
numpy ? Are we to expect users to rely on Python2.5 for the upcoming 1.3.x ? Could we have some kind of timeline on the trac site or elsewhere (and if such a timeline exists already, can I get the link?) ?
NumPy 1.3.x should work with Python 2.4, 2.5, and 2.6. At some point we can drop 2.4, but I would like to wait a bit since we just dropped 2.3 support. The timeline is on the trac site: http://projects.scipy.org/scipy/numpy/milestone/1.3.0
- Talking about 1.3.x, what's the timeline? Are we still shooting for
a release in 2008 or could we wait till mid Jan. 2009 ?
I am fine with pushing the release back, if there is interest in doing that. I have been mainly focusing on getting SciPy 0.7.x out, so I haven't been following the NumPy development closely. But it is good that you are asking for more concrete details about the next NumPy release. We need to start making plans. Does anyone have any suggestions about whether we should push the release back? Is 1 month long enough? What is left to do?
Please feel free to update the release notes, which are checked into the trunk: http://scipy.org/scipy/numpy/browser/trunk/doc/release/1.3.0-notes.rst
Thanks,
On Dec 7, 2008, at 4:21 PM, Jarrod Millman wrote:
NumPy 1.3.x should work with Python 2.4, 2.5, and 2.6. At some point we can drop 2.4, but I would like to wait a bit since we just dropped 2.3 support. The timeline is on the trac site: http://projects.scipy.org/scipy/numpy/milestone/1.3.0
OK, great, thanks a lot.
- Talking about 1.3.x, what's the timeline? Are we still shooting for
a release in 2008 or could we wait till mid Jan. 2009 ?
I am fine with pushing the release back, if there is interest in doing that. I have been mainly focusing on getting SciPy 0.7.x out, so I haven't been following the NumPy development closely. But it is good that you are asking for more concrete details about the next NumPy release. We need to start making plans. Does anyone have any suggestions about whether we should push the release back? Is 1 month long enough? What is left to do?
Well, on my side, there's some doc to be updated, of course. Then, I'd like to put the rec_functions that were developed in matplotlib to manipulate recordarrays. I haven't started yet, might be able to do so before the end of the year (not much to do, just a clean up and some examples). And what should we do with the genloadtxt function ?
Please feel free to update the release notes, which are checked into the trunk: http://scipy.org/scipy/numpy/browser/trunk/doc/release/1.3.0- notes.rst
Will do in good time. Thx again
Hi,
I want to create a matrix based on a vector. It is difficult to describe the issue for me in english. Here is an example.
Suppose I have an array([3, 6, 8, 12]), I want to create a range based on each element. In this exampe, let us say want to create 4 number with step 2, so I will have
[3, 6, 8, 12 5, 8, 10,14 7, 10,12,16 9, 12,14,18]
It is a 4 by 4 maxtric in this example. My original array is quite large. but the range I want to create around the number is not big, it is about 30.
Does anyone know how to do this efficiently?
Thanks
Frank _________________________________________________________________ Send e-mail faster without improving your typing skills. http://windowslive.com/Explore/hotmail?ocid=TXT_TAGLM_WL_hotmail_acq_speed_1...
On Mon, Dec 8, 2008 at 11:27, frank wang f.yw@hotmail.com wrote:
Hi,
I want to create a matrix based on a vector. It is difficult to describe the issue for me in english. Here is an example.
Suppose I have an array([3, 6, 8, 12]), I want to create a range based on each element. In this exampe, let us say want to create 4 number with step 2, so I will have
[3, 6, 8, 12 5, 8, 10,14 7, 10,12,16 9, 12,14,18]
It is a 4 by 4 maxtric in this example. My original array is quite large. but the range I want to create around the number is not big, it is about 30.
Does anyone know how to do this efficiently?
In [1]: from numpy import *
In [2]: a = array([3, 6, 8, 12])
In [4]: b = arange(0, 4*2, 2)[:,newaxis]
In [5]: a+b Out[5]: array([[ 3, 6, 8, 12], [ 5, 8, 10, 14], [ 7, 10, 12, 16], [ 9, 12, 14, 18]])
I got a lof of help from the experts in this forum. I resitsted to send a thank you reply for fearing spaming the forum. This time I really want to let the people know that I am really appreciate the great help I got.
Please let me know if a simple thank you message is not appropriate in this forum.
Numpy makes Pyhton a great tools for processing signal.
Thank you very much.
Frank > Date: Mon, 8 Dec 2008 11:30:31 -0600> From: robert.kern@gmail.com> To: numpy-discussion@scipy.org> Subject: Re: [Numpy-discussion] how to create a matrix based on a vector?> > On Mon, Dec 8, 2008 at 11:27, frank wang f.yw@hotmail.com wrote:> > Hi,> >> > I want to create a matrix based on a vector. It is difficult to describe the> > issue for me in english. Here is an example.> >> > Suppose I have an array([3, 6, 8, 12]), I want to create a range based on> > each element. In this exampe, let us say want to create 4 number with step> > 2, so I will have> >> > [3, 6, 8, 12> > 5, 8, 10,14> > 7, 10,12,16> > 9, 12,14,18]> >> > It is a 4 by 4 maxtric in this example. My original array is quite large.> > but the range I want to create around the number is not big, it is about 30.> >> > Does anyone know how to do this efficiently?> > In [1]: from numpy import *> > In [2]: a = array([3, 6, 8, 12])> > In [4]: b = arange(0, 4*2, 2)[:,newaxis]> > In [5]: a+b> Out[5]:> array([[ 3, 6, 8, 12],> [ 5, 8, 10, 14],> [ 7, 10, 12, 16],> [ 9, 12, 14, 18]])> > -- > Robert Kern> > "I have come to believe that the whole world is an enigma, a harmless> enigma that is made terrible by our own mad attempt to interpret it as> though it had an underlying truth."> -- Umberto Eco> _______________________________________________> Numpy-discussion mailing list> Numpy-discussion@scipy.org> http://projects.scipy.org/mailman/listinfo/numpy-discussion _________________________________________________________________ Send e-mail faster without improving your typing skills. http://windowslive.com/Explore/hotmail?ocid=TXT_TAGLM_WL_hotmail_acq_speed_1...
On Mon, Dec 8, 2008 at 12:40, frank wang f.yw@hotmail.com wrote:
I got a lof of help from the experts in this forum. I resitsted to send a thank you reply for fearing spaming the forum. This time I really want to let the people know that I am really appreciate the great help I got.
Please let me know if a simple thank you message is not appropriate in this forum.
Thanks, public or otherwise, are always appreciated. You're quite welcome.
Hi,
I have a program with some variables consume a lot of memory. The first time I run it, it is fine. The second time I run it, I will get MemoryError. If I close the ipython and reopen it again, then I can run the program once. I am looking for a command to delete the intermediate variable once it is not used to save memory like in matlab clear command.
Thanks
Frank _________________________________________________________________ Send e-mail faster without improving your typing skills. http://windowslive.com/Explore/hotmail?ocid=TXT_TAGLM_WL_hotmail_acq_speed_1...
Try:
del(myvariable)
Travis
On Dec 8, 2008, at 7:15 PM, frank wang f.yw@hotmail.com wrote:
Hi,
I have a program with some variables consume a lot of memory. The first time I run it, it is fine. The second time I run it, I will get MemoryError. If I close the ipython and reopen it again, then I can run the program once. I am looking for a command to delete the intermediate variable once it is not used to save memory like in matlab clear command.
Thanks
Frank
Send e-mail faster without improving your typing skills. Get your Hotmail® account. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
I have the same problem. I tried the del command below, but foundon that it removes the names of the ndarrays from memory, but does not free up the memory on my XP system (python 2.5.2, numpy 1.2.1). Regular python objects release their memory when I use the del command, but it looks like the ndarray objects do not.
On Mon, Dec 8, 2008 at 22:00, Travis Vaught travis@enthought.com wrote:
Try:
del(myvariable)
Travis
On Dec 8, 2008, at 7:15 PM, frank wang f.yw@hotmail.com wrote:
Hi,
I have a program with some variables consume a lot of memory. The first time I run it, it is fine. The second time I run it, I will get MemoryError. If I close the ipython and reopen it again, then I can run the program once. I am looking for a command to delete the intermediate variable once it is not used to save memory like in matlab clear command.
Thanks
Frank
Send e-mail faster without improving your typing skills. Get your Hotmail(R) account.http://windowslive.com/Explore/hotmail?ocid=TXT_TAGLM_WL_hotmail_acq_speed_122008
Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
On Tue, Dec 9, 2008 at 20:40, Vagabond_Aero vagabondaero@gmail.com wrote:
I have the same problem. I tried the del command below, but foundon that it removes the names of the ndarrays from memory, but does not free up the memory on my XP system (python 2.5.2, numpy 1.2.1). Regular python objects release their memory when I use the del command, but it looks like the ndarray objects do not.
It's not guaranteed that the regular Python objects return memory to the OS, either. The memory should be reused when Python allocates new memory, though, so I suspect that this is not the problem that Frank is seeing.
On Mon, Dec 8, 2008 at 19:15, frank wang f.yw@hotmail.com wrote:
Hi,
I have a program with some variables consume a lot of memory. The first time I run it, it is fine. The second time I run it, I will get MemoryError. If I close the ipython and reopen it again, then I can run the program once. I am looking for a command to delete the intermediate variable once it is not used to save memory like in matlab clear command.
How are you running this program? Be aware that IPython may be holding on to objects and preventing them from being deallocated. For example:
In [7]: !cat memtest.py class A(object): def __del__(self): print 'Deleting %r' % self
a = A()
In [8]: %run memtest.py
In [9]: %run memtest.py
In [10]: %run memtest.py
In [11]: del a
In [12]: Do you really want to exit ([y]/n)?
$ python memtest.py Deleting <__main__.A object at 0x915ab0>
You can remove some of these references with %reset and maybe a gc.collect() for good measure.
In [1]: %run memtest
In [2]: %run memtest
In [3]: %run memtest
In [4]: %reset Once deleted, variables cannot be recovered. Proceed (y/[n])? y Deleting <__main__.A object at 0xf3e950> Deleting <__main__.A object at 0xf3e6d0> Deleting <__main__.A object at 0xf3e930>
2008/12/10 Robert Kern robert.kern@gmail.com: On Mon, Dec 8, 2008 at 19:15, frank wang f.yw@hotmail.com wrote:
Hi,
I have a program with some variables consume a lot of memory. The first time I run it, it is fine. The second time I run it, I will get MemoryError. If I close the ipython and reopen it again, then I can run the program once. I am looking for a command to delete the intermediate variable once it is not used to save memory like in matlab clear command.
How are you running this program? Be aware that IPython may be holding on to objects and preventing them from being deallocated. For example:
In [7]: !cat memtest.py class A(object): def __del__(self): print 'Deleting %r' % self
a = A()
In [8]: %run memtest.py
In [9]: %run memtest.py
In [10]: %run memtest.py
In [11]: del a
In [12]: Do you really want to exit ([y]/n)?
$ python memtest.py Deleting <__main__.A object at 0x915ab0>
You can remove some of these references with %reset and maybe a gc.collect() for good measure.
Of course, if you don't need to have access to the variables created in your program from the IPython session, you can run the program in a separate python process:
In [1]: !python memtest.py Deleting <__main__.A object at 0xb7da5ccc>
In [2]: !python memtest.py Deleting <__main__.A object at 0xb7e5fccc>
Cheers, Scott
I am running in ipython. Now I do not have the problem anymore. %reset commands is a good solution.
Thanks
Frank> Date: Tue, 9 Dec 2008 21:03:00 -0600> From: robert.kern@gmail.com> To: numpy-discussion@scipy.org> Subject: Re: [Numpy-discussion] how do I delete unused matrix to save the memory?> > On Mon, Dec 8, 2008 at 19:15, frank wang f.yw@hotmail.com wrote:> > Hi,> >> > I have a program with some variables consume a lot of memory. The first time> > I run it, it is fine. The second time I run it, I will get MemoryError. If I> > close the ipython and reopen it again, then I can run the program once. I am> > looking for a command to delete the intermediate variable once it is not> > used to save memory like in matlab clear command.> > How are you running this program? Be aware that IPython may be holding> on to objects and preventing them from being deallocated. For example:> > In [7]: !cat memtest.py> class A(object):> def __del__(self):> print 'Deleting %r' % self> > > a = A()> > In [8]: %run memtest.py> > In [9]: %run memtest.py> > In [10]: %run memtest.py> > In [11]: del a> > In [12]:> Do you really want to exit ([y]/n)?> > $ python memtest.py> Deleting <__main__.A object at 0x915ab0>> > > You can remove some of these references with %reset and maybe a> gc.collect() for good measure.> > > In [1]: %run memtest> > In [2]: %run memtest> > In [3]: %run memtest> > In [4]: %reset> Once deleted, variables cannot be recovered. Proceed (y/[n])? y> Deleting <__main__.A object at 0xf3e950>> Deleting <__main__.A object at 0xf3e6d0>> Deleting <__main__.A object at 0xf3e930>> > -- > Robert Kern> > "I have come to believe that the whole world is an enigma, a harmless> enigma that is made terrible by our own mad attempt to interpret it as> though it had an underlying truth."> -- Umberto Eco> _______________________________________________> Numpy-discussion mailing list> Numpy-discussion@scipy.org> http://projects.scipy.org/mailman/listinfo/numpy-discussion _________________________________________________________________ Send e-mail faster without improving your typing skills. http://windowslive.com/Explore/hotmail?ocid=TXT_TAGLM_WL_hotmail_acq_speed_1...
Jarrod Millman wrote:
On Sun, Dec 7, 2008 at 12:02 PM, Pierre GM pgmdevlist@gmail.com wrote:
- What versions of Python should be supported by what version of
numpy ? Are we to expect users to rely on Python2.5 for the upcoming 1.3.x ? Could we have some kind of timeline on the trac site or elsewhere (and if such a timeline exists already, can I get the link?) ?
NumPy 1.3.x should work with Python 2.4, 2.5, and 2.6. At some point we can drop 2.4, but I would like to wait a bit since we just dropped 2.3 support. The timeline is on the trac site: http://projects.scipy.org/scipy/numpy/milestone/1.3.0
I am strongly against dropping 2.4 support anytime soon. I haven't seen a strong rationale for using >= 2.5 features in numpy, supporting 2.4 is not so hard, and 2.4 is still the default python version on many OS (mac os X 10.4 I believe, RHEL for sure, open solaris).
David
On Sun, Dec 7, 2008 at 9:42 PM, David Cournapeau david@ar.media.kyoto-u.ac.jp wrote:
I am strongly against dropping 2.4 support anytime soon. I haven't seen a strong rationale for using >= 2.5 features in numpy, supporting 2.4 is not so hard, and 2.4 is still the default python version on many OS (mac os X 10.4 I believe, RHEL for sure, open solaris).
While my feelings aren't as strong as David's, they are pretty much identical.
As a point of reference, Red Hat Enterprise Linux 6 won't come out until at least the first quarter of 2010. Until then we should make a serious effort to support Python 2.4, which ships with RHEL 5. It looks like RHEL 6 will be based on the upcoming Fedora 11 release, which will ship with Python 2.6. That gives us a minimum of one year for 2.4 support. Once RHEL 6 is released, it will take several months before a sizable number of users upgrade.
Moin has a detailed list of Python versions for various OSes and hosting services: http://moinmo.in/PollAboutRequiringPython24
While my feelings aren't as strong as David's, they are pretty much identical.
As a point of reference, Red Hat Enterprise Linux 6 won't come out until at least the first quarter of 2010. Until then we should make a serious effort to support Python 2.4, which ships with RHEL 5. It looks like RHEL 6 will be based on the upcoming Fedora 11 release, which will ship with Python 2.6. That gives us a minimum of one year for 2.4 support. Once RHEL 6 is released, it will take several months before a sizable number of users upgrade.
Moin has a detailed list of Python versions for various OSes and hosting services: http://moinmo.in/PollAboutRequiringPython24
At least several months, if not years. RedHat supports each version 7 years, for instance (I don't ask for that long). Currently, I'm still using a RHEL 4, although it is planned to migrate to RHEL 5 next year. So we should still support 2.4 for at least 18 months, in case some big firms use RHEL and Python+Numpy for their tools.
Matthieu Brucher wrote:
At least several months, if not years. RedHat supports each version 7 years, for instance (I don't ask for that long). Currently, I'm still using a RHEL 4, although it is planned to migrate to RHEL 5 next year. So we should still support 2.4 for at least 18 months, in case some big firms use RHEL and Python+Numpy for their tools.
+1
On Sun, Dec 7, 2008 at 23:42, David Cournapeau david@ar.media.kyoto-u.ac.jp wrote:
I am strongly against dropping 2.4 support anytime soon. I haven't seen a strong rationale for using >= 2.5 features in numpy, supporting 2.4 is not so hard, and 2.4 is still the default python version on many OS (mac os X 10.4 I believe, RHEL for sure, open solaris).
Mac OS X 10.4 uses python-2.3, 10.5 uses python-2.5.
Cheers
Adam
participants (11)
-
Adam Mercer -
David Cournapeau -
frank wang -
Jarrod Millman -
Matthieu Brucher -
Pierre GM -
Robert Kern -
Scott Sinclair -
Steven H. Rogers -
Travis Vaught -
Vagabond_Aero