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From: Paul B. <Ba...@st...> - 2001-02-09 15:45:42
|
I've been encouraged to set-up a BoF at Python 9 to discuss Numerical Python issues, specifically the design and implemenation of Numeric 2. I'd like to get a head count of those interested in attending such a BoF. So far there are 3 of us at STScI who are interested. -- Dr. Paul Barrett Space Telescope Science Institute Phone: 410-338-4475 ESS/Science Software Group FAX: 410-338-4767 Baltimore, MD 21218 |
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From: John J. L. <ph...@cs...> - 2001-02-08 21:01:25
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On Thu, 8 Feb 2001, David P Grote wrote: > What I meant by "not contiguous" is that the=A0 Numeric flag "contiguous" > is set to false. This flag is only true when Numeric arrays have their > strides in C ordering. Any rearrangement of the strides causes the flag > to be set to false - a transpose for example. The data in the fortran > arrays is contiguous in memory. Here's an example using ravel. [...] Oh, I see. > Ravel does make a copy when the array is not contiguous. I asked this > question before but didn't get any response - is there a way to get the > argmax/min or max/min of a non-contiguous multi-dimensional array without > making a contiguous copy? I use python as an interface to fortran code > and so I am constantly dealing with arrays that are not contiguous, i.e. > not with C ordering. Any help is appreciated. I don't know about doing it with one of the Numeric functions, but it's very easy to write in C -- just this week I wrote a max() that works on (contiguous or not) Numeric arrays. I think I wrote it as a C function (not callable from Python) for the function I was wrapping to use, but it would be easy to change it to be a proper Python function. I'll mail you a copy if you like. John |
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From: David P G. <dp...@lb...> - 2001-02-08 17:40:33
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<html><head></head><body><br>
What I meant by "not contiguous" is that the Numeric flag "contiguous" is
set to false. This flag is only true when Numeric arrays have their strides
in C ordering. Any rearrangement of the strides causes the flag to be set
to false - a transpose for example. The data in the fortran arrays is contiguous
in memory. Here's an example using ravel.<br>
<br>
>>> from Numeric import *<br>
>>> xx = ones((4,4))<br>
>>> yy = ravel(xx)<br>
>>> yy[2] = 6<br>
>>> xx<br>
array([[1, 1, 6, 1],<br>
[1, 1, 1, 1],<br>
[1, 1, 1, 1],<br>
[1, 1, 1, 1]])<br>
>>> zz = transpose(xx)<br>
>>> zz<br>
array([[1, 1, 1, 1],<br>
[1, 1, 1, 1],<br>
[6, 1, 1, 1],<br>
[1, 1, 1, 1]])<br>
>>> yy = ravel(zz)<br>
>>> yy[2] = 10 <br>
>>> zz<br>
array([[1, 1, 1, 1],<br>
[1, 1, 1, 1],<br>
[6, 1, 1, 1],<br>
[1, 1, 1, 1]])<br>
>>> yy<br>
array([ 1, 1, 10, 1, 1, 1, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1])<br>
<br>
As you can see, the second ravel has made a copy, whereas the first did not.
I know this is a minor point, and I apologize for taking up bandwidth, but
it would be nice if there were a way around this, short of writing my own
C routines for min and max.<br>
Dave<br>
<br>
John J. Lee wrote:<br>
<blockquote type="cite" cite="mid:Pin...@mi..."><pre wrap="">On Wed, 7 Feb 2001, David P Grote wrote:<br><br></pre>
<blockquote type="cite"><pre wrap="">Ravel does make a copy when the array is not contiguous. I asked this<br>question before but didn't get any response - is there a way to get the<br>argmax/min or max/min of a non-contiguous multi-dimensional array without<br>making a contiguous copy? I use python as an interface to fortran code<br>and so I am constantly dealing with arrays that are not contiguous, i.e.<br>not with C ordering. Any help is appreciated.<br></pre></blockquote>
<pre wrap=""><!----><br>Aren't FORTRAN arrays just stored in the reverse order to C? Isn't this<br>just dealt with by having the stride lengths of your Numeric array in the<br>opposite order? Or does FORTRAN sometimes allocate multidimensional<br>arrays with gaps in memory?? I don't see why they should not be<br>contiguous.<br><br><br>John<br><br></pre>
</blockquote>
<br>
</body></html>
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From: John J. L. <ph...@cs...> - 2001-02-08 08:58:41
|
On Wed, 7 Feb 2001, David P Grote wrote: > Ravel does make a copy when the array is not contiguous. I asked this > question before but didn't get any response - is there a way to get the > argmax/min or max/min of a non-contiguous multi-dimensional array without > making a contiguous copy? I use python as an interface to fortran code > and so I am constantly dealing with arrays that are not contiguous, i.e. > not with C ordering. Any help is appreciated. Aren't FORTRAN arrays just stored in the reverse order to C? Isn't this just dealt with by having the stride lengths of your Numeric array in the opposite order? Or does FORTRAN sometimes allocate multidimensional arrays with gaps in memory?? I don't see why they should not be contiguous. John |
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From: David P G. <dp...@lb...> - 2001-02-07 19:42:53
|
<html><head></head><body><br>
Ravel does make a copy when the array is not contiguous. I asked this question
before but didn't get any response - is there a way to get the argmax/min
or max/min of a non-contiguous multi-dimensional array without making a contiguous
copy? I use python as an interface to fortran code and so I am constantly
dealing with arrays that are not contiguous, i.e. not with C ordering. Any
help is appreciated.<br>
Thanks,<br>
Dave<br>
<br>
Konrad Hinsen wrote:<br>
<blockquote type="cite" cite="mid:200...@ch...">
<blockquote type="cite"><pre wrap="">element of a NumPy array. I seeked through the documentation and found the<br>argmax/argmin functions. However, they must be called recursively to find<br>the greatest(smallest) element of a multidimendional array. As I needed to<br></pre></blockquote>
<pre wrap=""><!----><br>You could run it on Numeric.ravel(array) (which shouldn't make a<br>copy), and then reconstruct the multidimensional indices from the<br>single index into the flattened array. The additional overhead<br>should be minimal, and you don't need any C code.<br><br>Konrad<br></pre>
</blockquote>
<br>
</body></html>
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From: Konrad H. <hi...@cn...> - 2001-02-07 14:20:19
|
> Well, we talked about it some but didn't want to break existing code. To my > recollection nobody has suggested the trick you suggest here. I think it > would work, although there are cases where people import Precision in a > given module but not Numeric (the numeric objects they deal with get > returned by C or Fortran calls). Anybody see any real downside here? At least not immediately. Importing Numeric involves almost no overhead when you use array-generating modules anyway (they need to import at least multiarray). I'll make this modification to my installation and see if I get any bad surprises. Konrad. -- ------------------------------------------------------------------------------- Konrad Hinsen | E-Mail: hi...@cn... Centre de Biophysique Moleculaire (CNRS) | Tel.: +33-2.38.25.56.24 Rue Charles Sadron | Fax: +33-2.38.63.15.17 45071 Orleans Cedex 2 | Deutsch/Esperanto/English/ France | Nederlands/Francais ------------------------------------------------------------------------------- |
|
From: Konrad H. <hi...@cn...> - 2001-02-07 14:17:50
|
> element of a NumPy array. I seeked through the documentation and found the > argmax/argmin functions. However, they must be called recursively to find > the greatest(smallest) element of a multidimendional array. As I needed to You could run it on Numeric.ravel(array) (which shouldn't make a copy), and then reconstruct the multidimensional indices from the single index into the flattened array. The additional overhead should be minimal, and you don't need any C code. Konrad -- ------------------------------------------------------------------------------- Konrad Hinsen | E-Mail: hi...@cn... Centre de Biophysique Moleculaire (CNRS) | Tel.: +33-2.38.25.56.24 Rue Charles Sadron | Fax: +33-2.38.63.15.17 45071 Orleans Cedex 2 | Deutsch/Esperanto/English/ France | Nederlands/Francais ------------------------------------------------------------------------------- |
|
From: <ho...@ge...> - 2001-02-06 15:55:51
|
"Paul F. Dubois" <pa...@pf...> writes:
> Two notes in regard to this thread:
> 1. I am in progress making Pyfort support Digital Visual Fortran on
> Windows.
GREAT
> 2. Pyfort does have a facility for automatic allocation of work
> space, at least in the case that the size can be computed using
> ordinary arithmetic from the sizes of other arguments or other
> integer arguments.
I know of that, but the optimal workspace size for LAPACK routines is
for optimal efficiency. The size can be returned by the routine or by
calling the FORTRAN function ILAENV. It would be great, if
workspacesize could be made depending on the result of functions.
Thanks
Berthold
--
email: ho...@Ge...
) tel. : +49 (40) 3 61 49 - 73 74
(
C[_] These opinions might be mine, but never those of my employer.
|
|
From: Paul F. D. <pa...@pf...> - 2001-02-06 15:31:36
|
Two notes in regard to this thread: 1. I am in progress making Pyfort support Digital Visual Fortran on Windows. 2. Pyfort does have a facility for automatic allocation of work space, at least in the case that the size can be computed using ordinary arithmetic from the sizes of other arguments or other integer arguments. -----Original Message----- From: num...@li... [mailto:num...@li...]On Behalf Of Janko Hauser Sent: Tuesday, February 06, 2001 4:08 AM To: Berthold Hollmann Cc: num...@li... Subject: Re: [Numpy-discussion] more general LAPACK support for NumPy There is an old binding to the complete CLapack package, which can be found at ftp://dirac.cnrs-orleans.fr/pub/PyLapack.tar.gz It does not seem to have special support for Windows, but one can perhaps start from there. I have tried cfortran ones and the wrapped function signatures become quite long and verbose. I think one important extension would be to make the automatic wrapper generators pyfort and f2py support some windows compilers, although I must admit, I have not looked into them for windows support yet. __Janko _______________________________________________ Numpy-discussion mailing list Num...@li... http://lists.sourceforge.net/lists/listinfo/numpy-discussion |
|
From: <ho...@ge...> - 2001-02-06 13:59:49
|
OK, I got, compiled and installed PyLapack.tar.gz. It looks quite
complete, for LAPACK 1 or 2, but, of course those routines I need are
new in LAPACK 3 :-(.
It seemes, Doug Heisterkamp used some kind of a script or program to
generate the wrapper. Is there anyone who knows, whether this program
is avaible anywhere, so it could be extended for LAPACK 3 and Win?
Thanks
Berthold
--
email: ho...@Ge...
) tel. : +49 (40) 3 61 49 - 73 74
(
C[_] These opinions might be mine, but never those of my employer.
|
|
From: Janko H. <jh...@if...> - 2001-02-06 12:13:32
|
There is an old binding to the complete CLapack package, which can be found at ftp://dirac.cnrs-orleans.fr/pub/PyLapack.tar.gz It does not seem to have special support for Windows, but one can perhaps start from there. I have tried cfortran ones and the wrapped function signatures become quite long and verbose. I think one important extension would be to make the automatic wrapper generators pyfort and f2py support some windows compilers, although I must admit, I have not looked into them for windows support yet. __Janko |
|
From: <ho...@ge...> - 2001-02-06 09:36:27
|
Hello, From time to time we need an additional linear algebra routine to be avaible in Python. I find myself wrapping these functions then. As these are FORTRAN routines, doing this for Python version on Solaris (Sun CC/Sun F77), linux (gcc/g77) and Windows (VC++/Digital VF) becomes nontrivial. Neither f2py nor pyfort provide Win support and I doubt that automatic generation is usefull for many LAPACK routines, especially those that need workspace, because usually we want LWORK to be the optimal size. So my Question is, are there other users wrapping LAPACK routines for NumPy. If so, how are you doing it. For the C/FORTRAN wrapping I somehow like the approach used for cfortran.h (see http://www-zeus.desy.de/~burow/cfortran/index.html), but I'm afraid, the license is not acceptable. Is anyone aware of a C version of LAPACK besides the f2c version on netlib. I do like the approach used in the ATLAS clapack part, but there are only a very few LAPACK routines handeled there. If there is greater need for additional LAPACK routines for NumPy, should we bundle the efforts in (a) developing guidelines for how to write Python wrappers for LAPACK routines and (b) collecting routines provided by different users to provide a hopefully growing support for LAPACK in Python. Greetings Berthold -- email: ho...@Ge... ) tel. : +49 (40) 3 61 49 - 73 74 ( C[_] These opinions might be mine, but never those of my employer. |
|
From: Jon M. <jb...@oa...> - 2001-02-05 17:01:30
|
On Sun, Feb 04, 2001 at 02:45:51AM +0000, John J. Lee wrote: > Not sure aboout the latter, but couldn't the former just be done by > slicing? How does this relate to ufuncs? I'm probably being a little foggy on the distinction between the ufuncs (element-wise operations on arrays) and the array functions that sometimes allow you to specify an axis along which to apply the function. The problem I'm having with multipack.leastsq() is that the python function I supply as the model for the fit is expected to return a 1-d array or a single value. So if, for example, the independent variable is a 1-d array of shape (4,) and the data is a 3-d array of shape (4,256,256), to apply leastsq() along axis 0 you have to either loop in python or set things up so that you can map(leastsq, ....). It seems this kind of thing should properly be in the wrapper, and I would guess it should be in the C half of the wrapper for speed, unless there's some clever way to phrase it using native Numeric functions from python. > > They were only intended to be simple wrappings around the FORTRAN / C I > think, so I suspect Travis would say 'feel free to add it'. Maybe I should try. Is there any general objection (don't all barf at once) to using Fortran for an wrapper via pyfort (I don't know C)? -- Jon Moody |
|
From: Nils W. <nw...@is...> - 2001-02-05 14:37:55
|
Hi,
I am looking for Python routines for evaluation of special functions,
including Airy, Bessel, beta, exponential integrals, logarithmic
integrals.
Thanks
Nils
|
|
From: John J. L. <ph...@cs...> - 2001-02-04 02:45:47
|
On Sat, 3 Feb 2001, Jon Moody wrote: [...] > * Maybe I'm missing something, but is there any reason why multipack's > functions are not implemented as ufuncs? For example, it would be > useful to be able to use multipack.leastsq() along an axis of a 3-d > array, or to use multipack.quad() over a 2 or 3-d space of > integration parameters. [...] Not sure aboout the latter, but couldn't the former just be done by slicing? How does this relate to ufuncs? They were only intended to be simple wrappings around the FORTRAN / C I think, so I suspect Travis would say 'feel free to add it'. John |
|
From: Jon M. <jb...@oa...> - 2001-02-03 21:21:15
|
Two questions: * Has anyone been using the arraymap function that's in Travis's cephes 1.2 module? I think this is an interesting idea: giving arbitrary python functions ufunc-like (array broadcasting) properties when given numpy array arguments. (I noticed the Pearu's multipack CVS module has only cephes 1.1 which seems to be missing arraymap) * Maybe I'm missing something, but is there any reason why multipack's functions are not implemented as ufuncs? For example, it would be useful to be able to use multipack.leastsq() along an axis of a 3-d array, or to use multipack.quad() over a 2 or 3-d space of integration parameters. -- Jon Moody |
|
From: Paul F. D. <pa...@pf...> - 2001-02-02 15:21:38
|
Well, we talked about it some but didn't want to break existing code. To my recollection nobody has suggested the trick you suggest here. I think it would work, although there are cases where people import Precision in a given module but not Numeric (the numeric objects they deal with get returned by C or Fortran calls). Anybody see any real downside here? -----Original Message----- Is there any reason why Numeric never became a "New" Python package with a __init__.py ? -Michel PS: I have been adding __init__.py to my installation for a long time now and it works just fine. For those who want to be able to import directly we could extend the python path in __init__ so that after an import Numeric all .so would be directly loadable -- ----------------------------------------------------------------------- >>>>>>>>>> AREA CODE CHANGE <<<<<<<<< we are now 858 !!!!!!! Michel F. Sanner Ph.D. The Scripps Research Institute Assistant Professor Department of Molecular Biology 10550 North Torrey Pines Road Tel. (858) 784-2341 La Jolla, CA 92037 Fax. (858) 784-2860 sa...@sc... http://www.scripps.edu/sanner ----------------------------------------------------------------------- _______________________________________________ Numpy-discussion mailing list Num...@li... http://lists.sourceforge.net/lists/listinfo/numpy-discussion |
|
From: Michel S. <sa...@sc...> - 2001-02-01 20:29:51
|
Hello, Is there any reason why Numeric never became a "New" Python package with a __init__.py ? -Michel PS: I have been adding __init__.py to my installation for a long time now and it works just fine. For those who want to be able to import directly we could extend the python path in __init__ so that after an import Numeric all .so would be directly loadable -- ----------------------------------------------------------------------- >>>>>>>>>> AREA CODE CHANGE <<<<<<<<< we are now 858 !!!!!!! Michel F. Sanner Ph.D. The Scripps Research Institute Assistant Professor Department of Molecular Biology 10550 North Torrey Pines Road Tel. (858) 784-2341 La Jolla, CA 92037 Fax. (858) 784-2860 sa...@sc... http://www.scripps.edu/sanner ----------------------------------------------------------------------- |
|
From: Pete S. <pe...@sh...> - 2001-01-30 08:19:08
|
just curious about the status on this. i've got this file still available, but i notice it hasn't shown up on the Numpy downloads on sourceforge. Last week, I wrote: > > This is the last planned release in the 17 family. Binary versions will > > appear later -- developers, please help. > > hello paul. i didn't see a changelog or anything in the new release? > > regardless, i've finally put together my precompiled ZIP for win32 > and python2.0. it is available here; > http://pygame.seul.org/ftp/contrib/Numeric-17.3-win32-2.0.zip > > once this file is available from the sourceforge site i will > remove it from my little server, so please don't go linking > this URL all over the world :] > > also note that i finally broke from the win32 binary naming > convention that had been in use since the 16.0 release. i > don't know if that was actually some sort of convention, or > just an old tradition that got accidentally started :] > either way, feel free to rename this file however you see fit. > > one last thing. in the "setup.py" for Numeric, one of the > extensions included "Libraries=['m']", but this is not needed > on windows. (in fact, there is no math library, so the > compile was failing). i took this library out for my build, > and everything seems happy. > > finally. unlike my previous release, i also have finally included > some quick information in the readme, i'll just snip out the new > information from that file... |
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From: David P G. <dp...@lb...> - 2001-01-29 19:30:39
|
<html><head></head><body><br>
So, what does one do for an array that is not contiguous?<br>
Dave Grote<br>
<br>
Paul F. Dubois wrote:<br>
<blockquote type="cite" cite="mid:ADE...@pf...">
<blockquote type="cite"><blockquote type="cite"><blockquote type="cite"><pre wrap="">import Numeric<br>x=Numeric.arange(24)<br>x.shape=(3,2,4)<br>print Numeric.maximum.reduce(x.flat)<br></pre></blockquote></blockquote></blockquote>
<pre wrap=""><!---->23<br><br>The .flat operator does not copy the data. <br>-----Original Message-----<br>From: <a class="moz-txt-link-abbreviated" href="mailto:num...@li...">num...@li...</a><br>[<a class="moz-txt-link-freetext" href="mailto:num...@li...">mailto:num...@li...</a>]On Behalf Of Jon<br>Saenz<br>Sent: Monday, January 29, 2001 6:47 AM<br>To: <a class="moz-txt-link-abbreviated" href="mailto:Numpy-Discussion@Lists">Numpy-Discussion@Lists</a>. Sourceforge. Net<br>Subject: [Numpy-discussion] Is this a wheel?<br><br><br>Hello, there.<br><br>I needed last Saturday a function which returns the greatest/smallest<br>element of a NumPy array. I seeked through the documentation and found the<br>argmax/argmin functions. However, they must be called recursively to find<br>the greatest(smallest) element of a multidimendional array. As I needed t!
!
o<br>process a BIG dataset of multidimensional arrays, I wrote a function in C<br>which returns as a NumPy array shaped (2,) the [smallest one,biggest one]<br>elements in an arbitrarily shaped NumPy array. It is pure C and works for<br>multidimensional arrays. The return typecode is the same of the input<br>array (except with complex numbers, which compare numbers through their<br>modules).<br><br>I can make this function available to general public by means of my WEB<br>page or my starship account as a module. However, I wonder:<br>a) Is this a wheel already invented some 40,000 years ago? May be I missed<br>something in the manual?<br>b) If the answer to the previous question is NO, would you (main<br>developers) be interested in making it available as one of the "general<br>purpose" NumPy functions? It is quite general-purpose, indeed. I have<br>needed it five times or so in the last two years...<br><br>Looking after your comments.<br><br><br>Jon Saenz. | Tfno: +34 94601!
!
2470<br>Depto. Fisica Aplicada II | Fax: +34 944648500<br>Facultad de Ciencias. \\ Universidad del Pais Vasco \\<br>Apdo. 644 \\ 48080 - Bilbao \\ SPAIN<br><br><br>_______________________________________________<br>Numpy-discussion mailing list<br><a class="moz-txt-link-abbreviated" href="mailto:Num...@li...">Num...@li...</a><br><a class="moz-txt-link-freetext" href="http://lists.sourceforge.net/lists/listinfo/numpy-discussion">http://lists.sourceforge.net/lists/listinfo/numpy-discussion</a><br><br><br>_______________________________________________<br>Numpy-discussion mailing list<br><a class="moz-txt-link-abbreviated" href="mailto:Num...@li...">Num...@li...</a><br><a class="moz-txt-link-freetext" href="http://lists.sourceforge.net/lists/listinfo/numpy-discussion">http://lists.sourceforge.net/lists/listinfo/numpy-discussion</a><br></pre>
</blockquote>
<br>
</body></html>
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From: Paul F. D. <pa...@pf...> - 2001-01-29 15:27:08
|
>>> import Numeric >>> x=Numeric.arange(24) >>> x.shape=(3,2,4) >>> print Numeric.maximum.reduce(x.flat) 23 The .flat operator does not copy the data. -----Original Message----- From: num...@li... [mailto:num...@li...]On Behalf Of Jon Saenz Sent: Monday, January 29, 2001 6:47 AM To: Numpy-Discussion@Lists. Sourceforge. Net Subject: [Numpy-discussion] Is this a wheel? Hello, there. I needed last Saturday a function which returns the greatest/smallest element of a NumPy array. I seeked through the documentation and found the argmax/argmin functions. However, they must be called recursively to find the greatest(smallest) element of a multidimendional array. As I needed to process a BIG dataset of multidimensional arrays, I wrote a function in C which returns as a NumPy array shaped (2,) the [smallest one,biggest one] elements in an arbitrarily shaped NumPy array. It is pure C and works for multidimensional arrays. The return typecode is the same of the input array (except with complex numbers, which compare numbers through their modules). I can make this function available to general public by means of my WEB page or my starship account as a module. However, I wonder: a) Is this a wheel already invented some 40,000 years ago? May be I missed something in the manual? b) If the answer to the previous question is NO, would you (main developers) be interested in making it available as one of the "general purpose" NumPy functions? It is quite general-purpose, indeed. I have needed it five times or so in the last two years... Looking after your comments. Jon Saenz. | Tfno: +34 946012470 Depto. Fisica Aplicada II | Fax: +34 944648500 Facultad de Ciencias. \\ Universidad del Pais Vasco \\ Apdo. 644 \\ 48080 - Bilbao \\ SPAIN _______________________________________________ Numpy-discussion mailing list Num...@li... http://lists.sourceforge.net/lists/listinfo/numpy-discussion |
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From: Jon S. <js...@wm...> - 2001-01-29 14:46:58
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Hello, there. I needed last Saturday a function which returns the greatest/smallest element of a NumPy array. I seeked through the documentation and found the argmax/argmin functions. However, they must be called recursively to find the greatest(smallest) element of a multidimendional array. As I needed to process a BIG dataset of multidimensional arrays, I wrote a function in C which returns as a NumPy array shaped (2,) the [smallest one,biggest one] elements in an arbitrarily shaped NumPy array. It is pure C and works for multidimensional arrays. The return typecode is the same of the input array (except with complex numbers, which compare numbers through their modules). I can make this function available to general public by means of my WEB page or my starship account as a module. However, I wonder: a) Is this a wheel already invented some 40,000 years ago? May be I missed something in the manual? b) If the answer to the previous question is NO, would you (main developers) be interested in making it available as one of the "general purpose" NumPy functions? It is quite general-purpose, indeed. I have needed it five times or so in the last two years... Looking after your comments. Jon Saenz. | Tfno: +34 946012470 Depto. Fisica Aplicada II | Fax: +34 944648500 Facultad de Ciencias. \\ Universidad del Pais Vasco \\ Apdo. 644 \\ 48080 - Bilbao \\ SPAIN |
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From: Michael H. <mh...@al...> - 2001-01-27 17:10:55
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This is to announce the release of version 1.5 of Gnuplot.py.
Gnuplot.py is a Python [1] package that allows you to create graphs
from within Python using the gnuplot [2] plotting program.
Gnuplot.py can be obtained from
http://gnuplot-py.sourceforge.net/
Prerequisites (see footnotes):
the Python interpreter [1]
the Python Numeric module [3]
the gnuplot program [2]
Some ways this package can be used:
1. Interactive data processing: Use Python's excellent Numeric package
to create and manipulate arrays of numbers, and use Gnuplot.py to
visualize the results.
2. Web graphics: write CGI scripts in Python that use gnuplot to
output plots in GIF format and return them to the client.
3. Glue for numerical applications (this is my favorite): wrap your
C++/C/Fortran subroutines so that they are callable from Python,
then you can perform numerical computations interactively from
scripts or from the command line and use Gnuplot.py to plot the
output on the fly.
4. Compute a series of datasets in Python and plot them one after the
other using Gnuplot.py to produce a crude animation.
New features in this version:
+ Added distutils support.
+ Broke up the module a bit for better maintainability. The most
commonly-used facilities are still available through "import
Gnuplot", but some specialized things have been moved to separate
modules, in particular funcutils.py and PlotItems.py.
+ funcutils.tabulate_function() can be used to evaluate a function
on a 1-D or 2-D grid of points (this replaces grid_function,
which only worked with 2-D grids).
+ Added two helper functions, funcutils.compute_Data and
funcutils.compute_GridData, which compute a function's values on
a set of points and package the results into a PlotItem.
+ GridFunc is no longer an independent class; it is now a factory
function that returns a GridData. GridFunc is deprecated in
favor of funcutils.compute_GridData.
+ Changed set_option to work from a table, so that it doesn't need
to be overloaded so often.
+ Implemented test_persist for each platform to make it easier for
users to determine whether the `-persist' option is supported.
+ Added a prefer_persist option to serve as the default `persist'
choice.
+ Following a suggestion by Jannie Hofmeyr, use "from os import
popen" for Python 2.0 under Windows. I don't use Windows, so let
me know how this works.
+ Added support for the `axes' and `smooth' options of the `plot'
command.
+ Reworked the comment strings in an effort to make them work
nicely with happydoc.
Features already present in older versions:
+ Two and three-dimensional plots.
+ Plot data from memory, from a file, or from an expression.
+ Support for multiple simultaneous gnuplot sessions.
+ Can pass arbitrary commands to the gnuplot program.
+ Object oriented, extensible design with several built-in types
of plot items.
+ Portable and easy to install (nothing to compile except on
Windows).
+ Support for MS Windows, using the `pgnuplot.exe' program.
+ Support for sending data to gnuplot as `inline' or `binary' data.
These are optimizations that also remove the need for temporary
files. Temporary files are still the default.
Footnotes:
----------
[1] Python <http://www.python.org> is an excellent object-oriented
scripting/rapid development language that is also especially good
at gluing programs together.
[2] gnuplot <http://www.gnuplot.org/> is a free, popular, very
portable plotting program with a command-line interface. It can
make 2-d and 3-d plots and can output to myriad printers and
graphics terminals.
[3] The Numeric Python extension <http://numpy.sourceforge.net/> is a
Python module that adds fast and convenient array manipulations to
the Python language.
--
Michael Haggerty
mh...@al...
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From: Pete S. <pe...@sh...> - 2001-01-24 17:11:12
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> This is the last planned release in the 17 family. Binary versions will > appear later -- developers, please help. hello paul. i didn't see a changelog or anything in the new release? regardless, i've finally put together my precompiled ZIP for win32 and python2.0. it is available here; http://pygame.seul.org/ftp/contrib/Numeric-17.3-win32-2.0.zip once this file is available from the sourceforge site i will remove it from my little server, so please don't go linking this URL all over the world :] also note that i finally broke from the win32 binary naming convention that had been in use since the 16.0 release. i don't know if that was actually some sort of convention, or just an old tradition that got accidentally started :] either way, feel free to rename this file however you see fit. one last thing. in the "setup.py" for Numeric, one of the extensions included "Libraries=['m']", but this is not needed on windows. (in fact, there is no math library, so the compile was failing). i took this library out for my build, and everything seems happy. finally. unlike my previous release, i also have finally included some quick information in the readme, i'll just snip out the new information from that file... """ This build of Numeric 17.3.0 was built by Pete Shinners (pe...@sh...) on January 24, 2001 To install, extract the ZIP file into your Python folder. (for example, on my system this is C:\python20\) Unfortunately, I do not make use of the scientific packages like FFT, MA, and RNG, so I cannot test that they work, but I do know the base ArrayObject works well, and these extra packages have worked fine on my previous releases. <plug style=shameless> I am also the maintainer of the pygame library. Pygame is a great library for writing games in python, and includes a numeric module for directly accessing pixel values with numeric arrays. http://pygame.seul.org </plug> Following is the original README included with the Numeric source ----------------------------------------------------------------- """ + open('numeric-17.3/readme').read() |
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From: Paul F. D. <pa...@pf...> - 2001-01-24 15:51:08
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Numeric Python 17.3.0 is available in source form at http://sourceforge.net/projects/numpy This is the last planned release in the 17 family. Binary versions will appear later -- developers, please help. Release 18 will require Python 2.1. Several of the new features in Python 2.1 are specifically meant to enable improvements in Numeric and we are going to try to take advantage of them. Paul F. Dubois Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory |
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