NumPy-Discussion October 2001

numpy-discussion@python.org

22 participants
20 discussions

RE: Numeric2
by Perry Greenfield 01 Nov '01

01 Nov '01

> Date: Tue, 30 Oct 2001 14:58:38 -0500 > From: "Edward C. Jones" <edcjones(a)erols.com> > To: numpy-discussion(a)lists.sourceforge.net > Subject: [Numpy-discussion] Numeric2 > > What is the current status of Numeric2? > We are in the process of putting it up on sourceforge now. While you can actually download it from there now, I would strongly recommend waiting until we put some more current and up-to-date documentation about it there as well. We will announce it on this mailing list when it is ready (within a week?). But it isn't called Numeric2 any longer. We've called it numarray and it will be found under "python arrays" on Sourceforge. Perry Greenfield

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Undefined symbol in lapack_lite.so
by Edward C. Jones 31 Oct '01

31 Oct '01

The following Python program: import Numeric, LinearAlgebra a = Numeric.identity(5) v, s, wt = LinearAlgebra.singular_value_decomposition(a) gave the following error: Traceback (most recent call last): File "./silly.py", line 3, in ? import Numeric, LinearAlgebra File "/usr/lib/python2.2/site-packages/Numeric/LinearAlgebra.py", line 8, in ? import lapack_lite ImportError: /usr/lib/python2.2/site-packages/Numeric/lapack_lite.so: undefined symbol: dgesdd_ When I installed Numeric-20.2.0, I changed Setup.py to: # delete all but the first one in this list if using your own LAPACK/BLAS sourcelist = ['Src/lapack_litemodule.c',] # set these to use your own BLAS library_dirs_list = ['usr/lib'] libraries_list = ['/usr/lib/libblas.so', '/usr/lib/liblapack.so'] What is the problem? Thanks, Ed Jones

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Numeric2
by Edward C. Jones 30 Oct '01

30 Oct '01

What is the current status of Numeric2?

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Rank deficient matrices
by Nils Wagner 30 Oct '01

30 Oct '01

Hi, Let us assume that r = rank(C) < N (1) where C is a symmetric NxN matrix. This implies that the number of non-zero eigenvalues of C is r. Because C is a symmetric matrix there exists an orthogonal matrix U whose columns are the eigenvectors of C such that U^\top C U = [ d , O O , O]. (2) In the above equation d \in rxr is a diagonal matrix consisting of only the non-zero eigenvalues of C. For convenience, partition U as U = [U_1 | U_2] (3) where the columns of U_1 (Nxr) are the eigenvectors corresponding to the non-zero block d and the columns of U_2 are the eigenvectors corresponding to the rest (N-r) number of zero eigenvalues. Defining a rectangular transformation matrix R = U_1 (4) it is easy to show that R^\top C R = d. (5) Therefore, the matrix R in equation (4) transforms the originally rank deficient matrix C to a full-rank (diagonal) matrix of rank r. I am looking for an efficient Numpy implementation of this transformation. Thanks in advance Nils Wagner

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(real)**(2x2 general real matrix)
by Jean-Bernard Addor 26 Oct '01

26 Oct '01

Hey numpy people! Do you know the better way to compute with numpy: r**M where r is a positive real and M a 2x2 (rank 2) matrix, symmetric or not, with real or not eigenvalues. Help or comment are appreciated, Jean-Bernard

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Problem with Numeric?
by sag＠hydrosphere.com 25 Oct '01

25 Oct '01

I am using Numeric 20.2.0. I have found the following inconsistency. I am not a python guru and have no idea how I would fix it myself. The following code creates a series of arrays of data, and then applies maximum.reduce to the array to get the largest value. It then prints the type of returned max value. Most of the returns are typed as an array with a shape of (). If the array is created as a type of 'l' (long) or 'd' (double), the return type is not array. This seems wrong. Can someone tell me if this is expected, and if not, where would I look to change/fix it. --- CODE --- from Numeric import * print "++++" for tc in ('b', 'i', 'l', 's', 'f', 'd'): smallArray = array([1,2,3,4], tc) amax = maximum.reduce(smallArray) print smallArray.typecode(), smallArray, "Max:", amax, type(amax) if type(amax) == type(smallArray): print amax.shape --- OUTPUT --- >>>> ++++ b [1 2 3 4] Max: 4 <type 'array'> () i [1 2 3 4] Max: 4 <type 'array'> () l [1 2 3 4] Max: 4 <type 'int'> s [1 2 3 4] Max: 4 <type 'array'> () f [ 1. 2. 3. 4.] Max: 4.0 <type 'array'> () d [ 1. 2. 3. 4.] Max: 4.0 <type 'float'>

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RE: activity on NumPy
by Paul F. Dubois 16 Oct '01

16 Oct '01

No, I just have a major release coming up of cdat (cdat.sf.net) so I've been busy. -----Original Message----- From: nobody [mailto:nobody@sourceforge.net] On Behalf Of Alessandro MIRONE Sent: Tuesday, October 16, 2001 2:22 AM To: paul(a)pfdubois.com Subject: activity on NumPy Hi, I have noticed that that developer activity has almost stopped ( bugs and patches are no more processed) after 11/9. Did you get some restriction at your lab? Best regards Alessandro Mirone

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Problems with pickling an array with type Object
by sag＠hydrosphere.com 15 Oct '01

15 Oct '01

Greetings, I am trying to pickle an array of objects with a typecode of Object. Ultimately this array will be in a class I create based on UserArray, but the following illustrates a problem I am having. See code at the end of the message. I am working in Windows 2000, Service Pack 1, using PythonWin, win32all build 140. I am using the following versions of python stuff Python: 2.1.1 (#20, Jul 20 2001, 01:19:29) [MSC 32 bit (Intel)] Numeric: 20.2.0 cPickle: 1.71 I create a simple array with a type of Object, pickle it to a file using cPickle. I then run this script in PythonWin. I can unpickle this file from PythonWin, but not from DOS window. Alternatively, I can pickle the array from DOS, and unpickle it from DOS, but not from PythonWin. If I save both versions of the file and compare them, they are the same size, but not the same bytes. This does not happen with other types for the array. When unpickling, I get a GPF, either from PythonWin.exe or Python.exe. Any ideas? My ultimate goal is to be able to store simple class objects in the array and be able to pickle and unpickle them. ----- CODE ---- # simple test for pickling problem import Numeric import cPickle import sys basePath = "c:\\python21\\scripts\\pickle\\" print "++++++" # create a simple array of object, populated by integer data ds1 = Numeric.array([1,2,3,4], 'O') print ds1, ds1.typecode() print "Python: ", sys.version print "Numeric: " , Numeric.__version__ print "cPickle: ", cPickle.__version__ pickle = 1 # change to 0 to skip the pickling step for ii in (range(1,2)): if pickle: fileName = "%s%s%d%s" % (basePath, "simple", ii, ".pck") print "pickling ", fileName fp = open(fileName, 'wb') cPickle.dump(ds1, fp, 1) fp.close() for ii in range(1,2): fileName = "%s%s%d%s" % (basePath, "simple", ii, ".pck") print "unpickling ", fileName fp = open(fileName, 'rb') obj = cPickle.load(fp) fp.close() print obj, obj.typecode()

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sign of modulo
by Eric Nodwell 12 Oct '01

12 Oct '01

The Numpy version of modulo uses a different sign convention for negative arguments than does Python itself: >>> -5 % 3 1 >>> array((-5,-5)) % 3 array([-2, -2]) (Numpy version 20.2.0, Python version 1.5.2 and version 2.2a4.) Is there a reason for this (hard to imagine), or is this a bug? Eric

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drawing with NumPy and PythonCard
by Kevin Altis 10 Oct '01

10 Oct '01

Hi, I'm the coordinator for the PythonCard project, which is at: http://pythoncard.sourceforge.net/ PythonCard provides a GUI framework for building Python applications. The project is relatively new, but there are a large number of sample applications, including a number of drawing and visualization samples. PythonCard already supports loading and drawing of common formats like XBM, GIF, JPEG, PNG, etc. from disk files. Last month I started a BitmapCanvas for the framework to simplify interactive drawing. Rather than duplicate all of the functionality of the Python Imaging Library (PIL) or the various plotting packages already available, I want to make it easy to display results created with other drawing packages and numPy in PythonCard. To that end, the Bitmap and BitmapCanvas class already support PIL. You can convert a PIL RGB image to/from a PythonCard bitmap and you can draw a PIL RGB image in a BitmapCanvas at a given x, y location. If you're already converting from numPy to PIL, you should be able to show your results in PythonCard today. I will be making a related post about this on the image-sig. Anyway, what I would like to do is provide similar methods to make it easy to convert numPy arrays to images or a bitmap to numPy without having to go to PIL first. I don't currently use numPy since I don't do any scientific computing (and my math skills are pretty pathetic) and most of my programs are text or database-oriented, so I'm relying on others to spec out the features they need or want. Eventually, I would like to add some visual effects to PythonCard such as wipes and fades which would be a perfect use of arrays. I want to make sure that PythonCard provides a good GUI framework for the scientific community. I would appreciate any suggestions, pointers to related resources, etc. PythonCard currently sits on top of wxPython, so if you are already working with numPy and wxPython I would be very interested to hear about it. If you would like to get more actively involved, please join the PythonCard mailing list, which is probably a better place for longer-term discussions than the numPy list. http://lists.sourceforge.net/lists/listinfo/pythoncard-users Thanks, ka --- Kevin Altis altis(a)semi-retired.com

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NumPy-Discussion October 2001