[Numpy-discussion] Warning: message 1Ggbsf-00056T-Ol delayed 48 hours
This message was created automatically by mail delivery software. A message that you sent has not yet been delivered to one or more of its recipients after more than 48 hours on the queue on externalmx-1.sourceforge.net. The message identifier is: 1Ggbsf-00056T-Ol The subject of the message is: faces and their former position. To be, sure. But question The date of the message is:Sun, 05 Nov 2006 16:01:50 +0900 The address to which the message has not yet been delivered is: numpy-discussion@lists.sourceforge.net Delay reason: SMTP error from remote mailer after RCPT TO:numpy-discussion@lists.sourceforge.net: host mail.sourceforge.net [66.35.250.206]: 451-Could not complete sender verify callout 451-Could not complete sender verify callout for 451-numpy-discussion@lists.sourceforge.net. 451-The mail server(s) for the domain may be temporarily unreachable, or 451-they may be permanently unreachable from this server. In the latter case, 451-you need to change the address or create an MX record for its domain 451-if it is No action is required on your part. Delivery attempts will continue for some time, and this warning may be repeated at intervals if the message remains undelivered. Eventually the mail delivery software will give up, and when that happens, the message will be returned to 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
[Numpy-discussion] numpy on wince
Hi all, do you know if numpy/Numeric is available on WinCE ? I'm thinking about the use of a numpy/Numeric app on a palmtop and I'm not sure it will be deployed on linux only devices. Thanks in advance, Emanuele P.S.: I know that Python is available on many many platforms, but I not so confident about many external libraries. - 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] More on Numexpr-unsupported objects
This is somehow related with this previous thread about raising
``TypeError`` on unsupported objects in Numexpr:
http://www.mail-archive.com/numpy-discussion@lists.sourceforge.net/msg03146.html
There is still a case where unsupported objects can get into expressions
without Numexpr noticing. For instance:
import numexpr
numexpr.evaluate('[]')
Traceback (most recent call last):
File stdin, line 1, in ?
File numexpr/compiler.py, line 594, in evaluate
_names_cache[expr_key] = getExprNames(ex, context)
File numexpr/compiler.py, line 570, in getExprNames
ast = expressionToAST(ex)
File numexpr/compiler.py, line 84, in expressionToAST
this_ast = ASTNode(ex.astType, ex.astKind, ex.value,
AttributeError: 'list' object has no attribute 'astType'
The attached patch makes the error clearer and more consistent with the
error added in the aforementioned thread:
import numpy
import numexpr
numexpr.evaluate('[]')
Traceback (most recent call last):
File stdin, line 1, in ?
File numexpr/compiler.py, line 596, in evaluate
_names_cache[expr_key] = getExprNames(ex, context)
File numexpr/compiler.py, line 571, in getExprNames
ex = stringToExpression(text, {}, context)
File numexpr/compiler.py, line 229, in stringToExpression
raise TypeError(unsupported expression type: %s % type(ex))
TypeError: unsupported expression type: type 'list'
Though I admit it may be strange for this error to be triggered.
(I had a little mess with using ``expressions.ExpressionNode`` instead
of ``expr.ExpressionNode``... I still don't see why the private copy of
the module is necessary.)
::
Ivan Vilata i Balaguer qo http://www.carabos.com/
Cárabos Coop. V. V V Enjoy Data
Index: compiler.py
===
--- compiler.py (revisión: 2307)
+++ compiler.py (copia de trabajo)
@@ -225,6 +225,8 @@
ex = eval(c, names)
if expressions.isConstant(ex):
ex = expr.ConstantNode(ex, expressions.getKind(ex))
+elif not isinstance(ex, expr.ExpressionNode):
+raise TypeError(unsupported expression type: %s % type(ex))
return ex
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[Numpy-discussion] Stacking arrays...
HI all, I'm trying to get the hang of this new r_ and c_ stuff. I need to take two MxN arrays, and stack them together into one MxNx2 arrays. I found this works: a = N.ones((3,4)) b = N.ones((3,4)) * 2 a array([[ 1., 1., 1., 1.], [ 1., 1., 1., 1.], [ 1., 1., 1., 1.]]) b array([[ 2., 2., 2., 2.], [ 2., 2., 2., 2.], [ 2., 2., 2., 2.]]) a.shape = (3,4,1) b.shape = (3,4,1) c = N.c_[a,b] c.shape (3, 4, 2) c[0,0] array([ 1., 2.]) What I'm wondering is if there is a way to do that without explicitly adding the extra dimension to a and b before calling c_ ? -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/ORR/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [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] Passing numpy arrays to matlab
Hi, Thank you very much, I think this added documentation is pretty recent; I have never seen it before, and I did a lot a mex programming at some point... This whole mxarray nonsense reminds me why I gave up on matlab :), I would be very happy to help with this. It would be great if we could get a standard well-maintained library of some sort towards scipy - we (http://neuroimaging.scipy.org/) have a great deal of matlab integration to do. Best, Matthew - 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] Passing numpy arrays to matlab
Hi all, ti, 2006-11-07 kello 11:23 +0900, David Cournapeau kirjoitti: I am trying to find a nice way to communicate between matlab and python. I am aware of pymat, which does that, but the code is deprecated, and I thing basing the code on ctypes would lead to much more robust code. http://claymore.engineer.gvsu.edu/%7Esteriana/Software/pymat.html I have a really simple prototype which can send and get back data from matlab, but I was wondering if it would be possible to use a scheme similar to ctypes instead of having to convert it by hand. A while ago I wrote a mex extension to embed the Python interpreter inside Matlab: http://www.iki.fi/pav/pythoncall I guess it's something like an inverse of pymat :) But I guess this is not really what you are looking for, since at present it just does a memory copy when passing arrays between Matlab and Python. Though, shared arrays might be just possible to implement if memory management is done carefully. BR, Pauli Virtanen signature.asc Description: Digitaalisesti allekirjoitettu viestin osa - 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] Stacking arrays...
dstack maybe? or does that add a dim on the other end?--bbOn 11/8/06, Christopher Barker [EMAIL PROTECTED] wrote:HI all,I'm trying to get the hang of this new r_ and c_ stuff. I need to take two MxN arrays, and stack them together into one MxNx2arrays. I found this works: a = N.ones((3,4)) b = N.ones((3,4)) * 2 aarray([[ 1.,1.,1.,1.], [ 1.,1.,1.,1.],[ 1.,1.,1.,1.]]) barray([[ 2.,2.,2.,2.],[ 2.,2.,2.,2.],[ 2.,2.,2.,2.]]) a.shape = (3,4,1) b.shape = (3,4,1) c = N.c_[a,b] c.shape(3, 4, 2) c[0,0]array([ 1.,2.])What I'm wondering is if there is a way to do that without explicitly adding the extra dimension to a and b before calling c_ ?-Chris--Christopher Barker, Ph.D.OceanographerNOAA/ORR/HAZMAT (206) 526-6959 voice7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA98115 (206) 526-6317 main reception[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 easierDownload 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.nethttps://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] Slicing recarrays
Hi all, I'm using a recarray to read a bunch of binary data out of a file. It's working great, but it seems there should be a more efficient way to slice the data. Here's what I've got: The binary data is essentially a dump of a 2-d array of structs. So I read it like this: DataType = N.dtype([(long,i4), (lat, i4), (flag,b1)]) data = N.fromfile(file, DataType) data.shape = (M, N) So I now have a MxN array of the structs. What I would like to do is extract a MxNx2 array of just the two 4-byte integers. It seems that I should be able to do that without copying -- by using a view into the original data. I can't figure out how, however. What I am doing is: LEs = N.empty((M, N, 2), dtype=N.int32) LEs[:,:,0] = data['long'] LEs[:,:,1] = data['lat'] This works, but these are BIG files, so it would be nice not to be doing that extra copying. Is that possible? Thanks, -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/ORR/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [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] A reimplementation of MaskedArray
On 10/25/06, Pierre GM [EMAIL PROTECTED] wrote: On Tuesday 24 October 2006 02:50, Michael Sorich wrote: I am currently running numpy rc2 (I haven't tried your reimplementation yet as I am still using python 2.3). I am wondering whether the new maskedarray is able to handle construction of arrays from masked scalar values (not sure if this is the correct term). The answer is no, unfortunately: both the new and old implementations fail at the same point, raising a TypeError: lists are processed through numpy.core.numeric.array, which doesn't handle that. I have finally gotten around to upgrading to python 2.4 and have had a chance to play with your new version of the MaskedArray. It is great to see that someone is working on this. I have a few thoughts on masked arrays that may or may no warrant discusion 1. It would be nice if the masked_singleton could be passed into a ndarray, as this would allow it to be passed into the MaskedArray e.g. import numpy as N import ma.maskedarray as MA test = N.array([1,2,MA.masked]) ValueError: setting an array element with a sequence If the masked_singleton was implemented as an object that is not a MakedArray (which is a sequence that numpy.array chokes on), then a valid numpy array with an object dtype could be produced. e.g. class MaskedScalar: def __str__(self): return 'masked' masked = MaskedScalar() test = N.array([1,2,masked]) print test.dtype, test object [1 2 masked] print test == masked [False False True] print test[2] == masked True print test[2] is masked True Then it would be possible to alternatively define a masked array as MA.array([1,2,masked]) or MA.array(N.array([1,2,masked])). In the __init__ of the MaskedArray if the ndarray has an object dtype simply calculate the mask from a==masked. 2. What happens if a masked array is passed into a ndarray or passed into a MaskedArray with another mask? test_ma1 = MA.array([1,2,3], mask=[False, False, True]) print test_ma1 [1 2 --] print N.array(test_ma1) [1 2 3] test_ma2 = MA.array(test_ma1, mask=[True, False, False]) print test_ma2 [-- 2 3] I suppose it depends on whether you are masking useful data, or the masks represent missing data. In the former it may make sense to change or remove the mask. However in the latter case the original data entered is a bogus value which should never be unmasked. In this case, when converting to a ndarray I think it make more sense to make an object ndarray with the missing value containing the masked singleton. Additionally, if the MaskedArray is holding missing data, it does not make much sense to be able to pass in to the MA constructor both an existing ma and a mask. - 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] More on Numexpr-unsupported objects
Ivan Vilata i Balaguer wrote: [SNIP] Though I admit it may be strange for this error to be triggered. (I had a little mess with using ``expressions.ExpressionNode`` instead of ``expr.ExpressionNode``... I still don't see why the private copy of the module is necessary.) It's an attempt to make things thread safe. Since we are mucking around with the internals of the expression module, if there were multiple threads one might thread might change get_context out from under the other one. Giving each call to stringToExpression its own copy of the expression module prevents this. It is, admittedly, a kind of stupid way to do this. A more sane thing to do would probably to have some sort of expression object that we instantiate for each call to stringToExpression instead of mucking around with modules, which really aren't meant to be (ab)used this way. However, this would require a major rewrite of the expression module and I was feeling lazy at the time (and still am), so I resorted to questionable hackery. -tim - 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] Passing numpy arrays to matlab
Pauli Virtanen wrote: Hi all, ti, 2006-11-07 kello 11:23 +0900, David Cournapeau kirjoitti: I am trying to find a nice way to communicate between matlab and python. I am aware of pymat, which does that, but the code is deprecated, and I thing basing the code on ctypes would lead to much more robust code. http://claymore.engineer.gvsu.edu/%7Esteriana/Software/pymat.html I have a really simple prototype which can send and get back data from matlab, but I was wondering if it would be possible to use a scheme similar to ctypes instead of having to convert it by hand. A while ago I wrote a mex extension to embed the Python interpreter inside Matlab: http://www.iki.fi/pav/pythoncall I guess it's something like an inverse of pymat :) Yes, but at the end, I think they enable similar things. Thanks for the link ! But I guess this is not really what you are looking for, since at present it just does a memory copy when passing arrays between Matlab and Python. Though, shared arrays might be just possible to implement if memory management is done carefully. In my case, it is much worse: 1 first, you have numpy data that you have to copy to mxArray, the structure representing arrays in matlab C api. 2 then when you send data to the matlab engine, this is done automatically through pipe by the matlab engine API (maybe pipe does not imply copying; I don't know much about pipe from a programming point of view, actually) 3 The arrays you get back from matlab are in matlab mxArray structures: right now, I copy their data to new numpy arrays. At first, I just developed a prototype without thinking too much, and the result was much slower than I thought: sending a numpy with 2e5x10 double takes around 100 ms on my quite powerful machine (around 14 cycles per item for the best case). I suspect it is because I copy memory in a non contiguous manner (matlab arrays have a internal F storage for real arrays, but complex arrays are really two different arrays, which is different than Fortran convention I think, making the copy cost really expensive for complex arrays). To see if I was doing something wrong, I compared with numpy.require(ar, requirements = 'F_CONTIGUOUS'), which is even much slower There is not much I can do about 2, it looks like there is a way to avoid copying for 1, and my question was more specific to 3 (but reusable in 1, maybe, if I am smart enough). Basically: * how to create an object which has the same interface than numpy arrays, but owns the data from a foreign structure, which data are availble when building the object (The idea was to create a class which implements the array interface from python, kind of proxy class, which owns the data from mxArray; owns here is from a memory management point of view). David - 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] Passing numpy arrays to matlab
Josh Marshall wrote: Hi David, Did you have a look at mlabwrap? It's quite hard to find on the net, which is a shame, since it is a much more up to date version, enhancing pymat with the things that you are trying to do. It allows passing arrays and getting arrays back. http://mlabwrap.sourceforge.net/ I didn't know that, thanks. Unfortunately, it is not really what I am trying to do: mlabwrap is just a python interface a bit more high level than pymat, with many fancy tricks, but still do copies. What I would like is to avoid completely the copying by using proxy classes around data from numpy so that I can pass automatically numpy arrays to matlab C api, and a proxy class around data from matlab so that they look like numpy arrays. I don't care that much about the actual api from python point of view, because I intend to use this mainly to compare matlab vs numpy implementation, not as a way to use matlab inside python regularly. And once the copy problem is solved, adding syntactic sugar using python is easy anyway, I think (it should be easy to do something similar to mlabwrap at that point), cheers, David - 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
