Re: [Numpy-discussion] (no subject)
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Re: [Numpy-discussion] int64 wierdness
Andrew Straw wrote: An SVN checkout from a week or two ago looks OK on my amd64 machine: [EMAIL PROTECTED]:~$ python Python 2.4.3 (#2, Apr 27 2006, 14:43:32) [GCC 4.0.3 (Ubuntu 4.0.3-1ubuntu5)] on linux2 Type help, copyright, credits or license for more information. import numpy numpy.__version__ '0.9.9.2631' numpy.int64(9)**2 81 Confirmed to be fixed on my gentoo amd64 machine, numpy svn of couple of days ago: numpy.int64(9)**2 81 numpy.__version__ '0.9.9.2665' Cheers, Vincent. EI wrote: numpy.__version__ says 0.9.8. Python 2.4.2, GCC 4.1, OpenSuSE 10.1 (x86_64). Thanks Travis, Eugene On 6/27/06, *Travis Oliphant* [EMAIL PROTECTED] mailto:[EMAIL PROTECTED] wrote: EI wrote: Hi, I'm running python 2.4 on a 64bit linux and get strange results: (int(9))**2 is equal to 81, as it should, but (int64(9))**2 is equal to 0 Thanks for the bug-report. Please provide the version of NumPy you are using so we can track it down, or suggest an upgrade. -Travis Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
[Numpy-discussion] fread codes versus numpy types
Hello,
I see the following character codes defined in scipy (presumably) for
use with scipy.io.fread() :
In [20]:scipy.Complex
Out[20]:'D'
In [21]:scipy.Complex0
Out[21]:'D'
In [22]:scipy.Complex128
Out[22]:'G'
In [23]:scipy.Complex16
Out[23]:'F'
In [24]:scipy.Complex32
Out[24]:'F'
In [25]:scipy.Complex64
Out[25]:'D'
In [26]:scipy.Complex8
Out[26]:'F'
Then I see the following scalar types also defined:
In [27]:scipy.complex64
Out[27]:type 'complex64scalar'
In [28]:scipy.complex128
Out[28]:type 'complex128scalar'
In [29]:scipy.complex256
Out[29]:type 'complex256scalar'
which correspond to types that exist within the numpy module. These
names seem to conflict in that (unless I misunderstand what's going on)
scipy.complex64 actually occupies 64 bits of data (a 32-bit float for
each of {real, imag}) whereas scipy.Complex64 looks like it occupies 128
bits of data (a 64-bit double for each of {real, imag}).
Is there something I'm missing, or is this a naming inconsistency?
Glen
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Re: [Numpy-discussion] fread codes versus numpy types
Glen W. Mabey wrote:
Hello,
I see the following character codes defined in scipy (presumably) for
use with scipy.io.fread() :
In [20]:scipy.Complex
Out[20]:'D'
In [21]:scipy.Complex0
Out[21]:'D'
In [22]:scipy.Complex128
Out[22]:'G'
In [23]:scipy.Complex16
Out[23]:'F'
In [24]:scipy.Complex32
Out[24]:'F'
In [25]:scipy.Complex64
Out[25]:'D'
In [26]:scipy.Complex8
Out[26]:'F'
Then I see the following scalar types also defined:
In [27]:scipy.complex64
Out[27]:type 'complex64scalar'
In [28]:scipy.complex128
Out[28]:type 'complex128scalar'
In [29]:scipy.complex256
Out[29]:type 'complex256scalar'
which correspond to types that exist within the numpy module. These
names seem to conflict in that (unless I misunderstand what's going on)
scipy.complex64 actually occupies 64 bits of data (a 32-bit float for
each of {real, imag}) whereas scipy.Complex64 looks like it occupies 128
bits of data (a 64-bit double for each of {real, imag}).
Is there something I'm missing, or is this a naming inconsistency?
The Capitalized versions are actually old typecodes for backwards compatibility
with Numeric. In recent development versions of numpy, they are no longer
exposed except through the numpy.oldnumeric compatibility module. A decision
was
made for numpy to use the actual width of a type in its name instead of the
width of its component parts (when it has parts).
Code in scipy which still requires actual string typecodes is a bug. Please
report such cases on the Trac:
http://projects.scipy.org/scipy/scipy
--
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
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Re: [Numpy-discussion] fread codes versus numpy types
On 6/28/06, Robert Kern [EMAIL PROTECTED] wrote: The Capitalized versions are actually old typecodes for backwards compatibility with Numeric. In recent development versions of numpy, they are no longer exposed except through the numpy.oldnumeric compatibility module. A decision was made for numpy to use the actual width of a type in its name instead of the width of its component parts (when it has parts). Code in scipy which still requires actual string typecodes is a bug. Please report such cases on the Trac: http://projects.scipy.org/scipy/scipy Well, an easy way to make all those poke their ugly heads in a hurry would be to remove line 32 in scipy's init: longs[Lib] grep -n oldnum *py __init__.py:31:import numpy.oldnumeric as _num __init__.py:32:from numpy.oldnumeric import * If we really want to push for the new api, I think it's fair to change those two lines by simply from numpy import oldnumeric so that scipy also exposes oldnumeric, and let all deprecated names be hidden there. I just tried this change: Index: __init__.py === --- __init__.py (revision 2012) +++ __init__.py (working copy) @@ -29,9 +29,8 @@ # Import numpy symbols to scipy name space import numpy.oldnumeric as _num -from numpy.oldnumeric import * -del lib -del linalg +from numpy import oldnumeric + __all__ += _num.__all__ __doc__ += Contents and scipy's test suite still passes (modulo the test_cobyla thingie Nils is currently fixing, which is not related to this). Should I apply this patch, so we push the cleaned-up API even a bit harder? Cheers, f Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Numpy Benchmarking
On Wed, 28 Jun 2006 03:22:28 -0500 Robert Kern [EMAIL PROTECTED] wrote: [EMAIL PROTECTED] wrote: Hi, [TO]: NumPy uses Numeric's old wrapper to lapack algorithms. [TO]: [TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the [TO]: NumPy wrapper). [TO]: [TO]: The numpy.dual library exists so you can use the SciPy calls if the [TO]: person has SciPy installed or the NumPy ones otherwise. It exists [TO]: precisely for the purpose of seamlessly taking advantage of [TO]: algorithms/interfaces that exist in NumPy but are improved in SciPy. This strikes me as a little bit odd. Why not just provide the best-performing function to both SciPy and NumPy? Would NumPy be more difficult to install if the SciPy algorithm for inv() was incorporated? That's certainly the case for the FFT algorithms. Scipy wraps more (and more complicated) FFT libraries that are faster than FFTPACK. Most of the linalg functionality should probably be wrapping the same routines if an optimized LAPACK is available. However, changing the routine used in numpy in the absence of an optimized LAPACK would require reconstructing the f2c'ed lapack_lite library that we include with the numpy source. That hasn't been touched in so long that I would hesitate to do so. If you are willing to do the work and the testing to ensure that it still works everywhere, we'd probably accept the change. Annoying to redo (as tracking down *good* LAPACK sources is a chore), but hardly as bad as it was. I added the scripts I used to generated lapack_lite.c et al to numpy/linalg/lapack_lite in svn. These are the same things that were used to generate those files in recent versions of Numeric (which numpy uses). You only need to specify the top-level routines; the scripts find the dependencies. I'd suggest using the source for LAPACK that Debian uses; the maintainer, Camm Maguire, has done a bunch of work adding patches to fix routines that have been floating around. For instance, eigenvalues works better than before (lot fewer segfaults). With this, the hard part is writing the wrapper routines. If someone wants to wrap extra routines, I can do the the lapack_lite generation for them. -- ||\/| /--\ |David M. Cooke http://arbutus.physics.mcmaster.ca/dmc/ |[EMAIL PROTECTED] Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] indexing bug in numpy r2694
Keith Goodman wrote: On 6/28/06, Pau Gargallo [EMAIL PROTECTED] wrote: i don't know why 'where' is returning matrices. if you use: idx = where(y.A 0.5)[0] everything will work fine (I guess) What about the second issue? Is this expected behavior? idx array([0, 1, 2]) y matrix([[ 0.63731308], [ 0.34282663], [ 0.53366791]]) y[idx] matrix([[ 0.63731308], [ 0.34282663], [ 0.53366791]]) y[idx,0] matrix([[ 0.63731308, 0.34282663, 0.53366791]]) I was expecting a column vector. This should be better behaved now in SVN. Thanks for the reports. -Travis Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] fread codes versus numpy types
On 6/28/06, David M. Cooke [EMAIL PROTECTED] wrote: On Wed, 28 Jun 2006 11:22:38 -0600 Fernando Perez [EMAIL PROTECTED] wrote: Should I apply this patch, so we push the cleaned-up API even a bit harder? Yes please. I think all the modules that still use the oldnumeric names actually import numpy.oldnumeric themselves. Done, r2017. I also committed the simple one-liner: Index: weave/inline_tools.py === --- weave/inline_tools.py (revision 2016) +++ weave/inline_tools.py (working copy) @@ -402,7 +402,7 @@ def compile_function(code,arg_names,local_dict,global_dict, module_dir, compiler='', - verbose = 0, + verbose = 1, support_code = None, headers = [], customize = None, from a discussion we had a few weeks ago, I'd forgotten to put it in. I did it as a separate patch (r 2018) so it can be reverted separately if anyone objects. Cheers, f Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Setuptools leftover junk
On Wed, 28 Jun 2006 13:32:15 -0500 Robert Kern [EMAIL PROTECTED] wrote: Fernando Perez wrote: Is it really necessary to have all that setuptools junk left around, for those of us who aren't asking for it explicitly? My personal opinions on setuptools aside, I think it's just a sane practice not to create this kind of extra baggage unless explicitly requested. I scoured my home directory for any .file which might be triggering this inadvertedly, but I can't seem to find any, so I'm going to guess this is somehow being caused by numpy's own setup. If it's my own mistake, I'll be happy to be shown how to coexist peacefully with setuptools. Since this also affects user code (I think via f2py or something internal to numpy, since all I'm calling is f2py in my code), I really think it would be nice to clean it. numpy.distutils uses setuptools if it is importable in order to make sure that the two don't stomp on each other. It's probable that that test could probably be done with Andrew Straw's method: if 'setuptools' in sys.modules: have_setuptools = True from setuptools import setup as old_setup else: have_setuptools = False from distutils.core import setup as old_setup Tested patches welcome. Done. I've also added a 'setupegg.py' module that wraps running 'setup.py' with an import of setuptools (it's based on the one used in matplotlib). easy_install still works, also. -- ||\/| /--\ |David M. Cooke http://arbutus.physics.mcmaster.ca/dmc/ |[EMAIL PROTECTED] Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] fread codes versus numpy types
On Wed, 28 Jun 2006 11:22:38 -0600 Fernando Perez [EMAIL PROTECTED] wrote: On 6/28/06, Robert Kern [EMAIL PROTECTED] wrote: The Capitalized versions are actually old typecodes for backwards compatibility with Numeric. In recent development versions of numpy, they are no longer exposed except through the numpy.oldnumeric compatibility module. A decision was made for numpy to use the actual width of a type in its name instead of the width of its component parts (when it has parts). Code in scipy which still requires actual string typecodes is a bug. Please report such cases on the Trac: http://projects.scipy.org/scipy/scipy Well, an easy way to make all those poke their ugly heads in a hurry would be to remove line 32 in scipy's init: longs[Lib] grep -n oldnum *py __init__.py:31:import numpy.oldnumeric as _num __init__.py:32:from numpy.oldnumeric import * If we really want to push for the new api, I think it's fair to change those two lines by simply from numpy import oldnumeric so that scipy also exposes oldnumeric, and let all deprecated names be hidden there. I just tried this change: Index: __init__.py === --- __init__.py (revision 2012) +++ __init__.py (working copy) @@ -29,9 +29,8 @@ # Import numpy symbols to scipy name space import numpy.oldnumeric as _num -from numpy.oldnumeric import * -del lib -del linalg +from numpy import oldnumeric + __all__ += _num.__all__ __doc__ += Contents and scipy's test suite still passes (modulo the test_cobyla thingie Nils is currently fixing, which is not related to this). Should I apply this patch, so we push the cleaned-up API even a bit harder? Yes please. I think all the modules that still use the oldnumeric names actually import numpy.oldnumeric themselves. -- ||\/| /--\ |David M. Cooke http://arbutus.physics.mcmaster.ca/dmc/ |[EMAIL PROTECTED] Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Setuptools leftover junk
On 6/28/06, David M. Cooke [EMAIL PROTECTED] wrote: Done. I've also added a 'setupegg.py' module that wraps running 'setup.py' with an import of setuptools (it's based on the one used in matplotlib). easy_install still works, also. You beat me to it :) However, your patch has slightly different semantics from mine: if bdist_egg fails to import, the rest of setuptools is still used. I don't know if that's safe. My patch would consider /any/ failure in the setuptools imports as a complete setuptools failure, and revert out to basic distutils. Let me know if you want me to put in my code instead, here's a patch from my code against current svn (after your patch), in case you'd like to try it out. Cheers, f Index: core.py === --- core.py (revision 2701) +++ core.py (working copy) @@ -1,20 +1,30 @@ - import sys from distutils.core import * -if 'setuptools' in sys.modules: -have_setuptools = True -from setuptools import setup as old_setup -# easy_install imports math, it may be picked up from cwd -from setuptools.command import develop, easy_install +# Don't pull setuptools in unless the user explicitly requests by having it +# imported (Andrew's trick). +have_setuptools = 'setuptools' in sys.modules + +# Even if setuptools is in, do a few things carefully to make sure the version +# is recent enough to have everything we need before assuming we can proceed +# using setuptools throughout +if have_setuptools: try: -# very old versions of setuptools don't have this +from setuptools import setup as old_setup +# very old setuptools don't have this from setuptools.command import bdist_egg +# easy_install imports math, it may be picked up from cwd +from setuptools.command import develop, easy_install except ImportError: +# Any failure here is probably due to an old or broken setuptools +# leftover in sys.modules, so treat it as if it simply weren't +# available. have_setuptools = False -else: + +# If setuptools was flagged as unavailable due to import problems, we need the +# basic distutils support +if not have_setuptools: from distutils.core import setup as old_setup -have_setuptools = False from numpy.distutils.extension import Extension from numpy.distutils.command import config Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Numpy Benchmarking
[EMAIL PROTECTED] wrote: Hi, [TO]: NumPy uses Numeric's old wrapper to lapack algorithms. [TO]: [TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the [TO]: NumPy wrapper). [TO]: [TO]: The numpy.dual library exists so you can use the SciPy calls if the [TO]: person has SciPy installed or the NumPy ones otherwise. It exists [TO]: precisely for the purpose of seamlessly taking advantage of [TO]: algorithms/interfaces that exist in NumPy but are improved in SciPy. This strikes me as a little bit odd. Why not just provide the best-performing function to both SciPy and NumPy? Would NumPy be more difficult to install if the SciPy algorithm for inv() was incorporated? The main issue is that SciPy can take advantage and use Fortran code, but NumPy cannot as it must build without a Fortran compiler. This is the primary driver to the current duality. -Travis Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] indexing bug in numpy r2694
On 6/28/06, Travis Oliphant [EMAIL PROTECTED] wrote: Keith Goodman wrote: On 6/28/06, Pau Gargallo [EMAIL PROTECTED] wrote: i don't know why 'where' is returning matrices. if you use: idx = where(y.A 0.5)[0] everything will work fine (I guess) What about the second issue? Is this expected behavior? idx array([0, 1, 2]) y matrix([[ 0.63731308], [ 0.34282663], [ 0.53366791]]) y[idx] matrix([[ 0.63731308], [ 0.34282663], [ 0.53366791]]) y[idx,0] matrix([[ 0.63731308, 0.34282663, 0.53366791]]) I was expecting a column vector. This should be better behaved now in SVN. Thanks for the reports. Now numpy can do y[y 0.5] instead of y[where(y.A 0.5)[0]] where, for example, y = asmatrix(rand(3,1)). I know I'm pushing my luck here. But one more feature would make this perfect. Currently y[y0.5,:] returns the first column even if y has more than one column. Returning all columns would make it perfect. Example: y matrix([[ 0.38828902, 0.91649964], [ 0.41074001, 0.7105919 ], [ 0.15460833, 0.16746956]]) y[y[:,1]0.5,:] matrix([[ 0.38828902], [ 0.41074001]]) A better answer for matrix users would be: y[(0,1),:] matrix([[ 0.38828902, 0.91649964], [ 0.41074001, 0.7105919 ]]) Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] Setuptools leftover junk
On Wed, 28 Jun 2006 13:18:35 -0600 Fernando Perez [EMAIL PROTECTED] wrote: On 6/28/06, David M. Cooke [EMAIL PROTECTED] wrote: Done. I've also added a 'setupegg.py' module that wraps running 'setup.py' with an import of setuptools (it's based on the one used in matplotlib). easy_install still works, also. You beat me to it :) However, your patch has slightly different semantics from mine: if bdist_egg fails to import, the rest of setuptools is still used. I don't know if that's safe. My patch would consider /any/ failure in the setuptools imports as a complete setuptools failure, and revert out to basic distutils. Note that your patch will still import setuptools if the import of bdist_egg fails. And you can't get around that by putting the bdist_egg import first, as that imports setuptools first. (I think bdist_egg was added sometime after 0.5; if your version of setuptools is *that* old, you'd be better off not having it installed.) The use of setuptools by numpy.distutils is in two forms: explicitly (controlled by this patch of code), and implicitly (because setuptools goes and patches distutils). Disabling the explicit use won't actually fix your problem with the 'install' command leaving .egg_info directories (which, incidentally, are pretty small), as that's done by the implicit behaviour. [Really, distutils sucks. I think (besides refactoring) it needs it's API documented better, or least good conventions on where to hook into. setuptools and numpy.distutils do their best, but there's only so much you can do before everything goes fragile and breaks in unexpected ways.] With the if 'setuptools' in sys.modules test, if you *are* using setuptools, you must have explicitly requested that, and so I think a failure on import of setuptools shouldn't be silently passed over. -- ||\/| /--\ |David M. Cooke http://arbutus.physics.mcmaster.ca/dmc/ |[EMAIL PROTECTED] Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] matlab translation
I've been looking at a project called ANTLR (www.antlr.org) to do the translation. Unfortunately, although I may have a Matlab grammar, it would still be a lot of work to use ANTLR. I'll look at some of the links that have posted. Mathew Robert Kern wrote: Vinicius Lobosco wrote: Let's just let those who want to try to do that and give our support? I would be happy if I could some parts of my old matlab programs translated to Scipy. I do believe that, Show me, is an *encouragement*. I am explicitly encouraging Mathew to work towards that end. Sheesh. Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] indexing bug in numpy r2694
On 6/28/06, Travis Oliphant [EMAIL PROTECTED] wrote: This should be better behaved now in SVN. Thanks for the reports. I'm impressed by how quickly features are added and bugs are fixed. And by how quick it is to install a new version of numpy. Thank you. Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
Re: [Numpy-discussion] matlab translation
ANTLR was also used for GDL http://gnudatalanguage.sourceforge.net/ with amazing results. Erin On 6/28/06, Mathew Yeates [EMAIL PROTECTED] wrote: I've been looking at a project called ANTLR (www.antlr.org) to do the translation. Unfortunately, although I may have a Matlab grammar, it would still be a lot of work to use ANTLR. I'll look at some of the links that have posted. Mathew Robert Kern wrote: Vinicius Lobosco wrote: Let's just let those who want to try to do that and give our support? I would be happy if I could some parts of my old matlab programs translated to Scipy. I do believe that, Show me, is an *encouragement*. I am explicitly encouraging Mathew to work towards that end. Sheesh. Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnkkid=120709bid=263057dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
