Mailman 3 November 2010 - NumPy-Discussion

Workaround for Ticket #1504 (MKL linking)
by Felix 16 Nov '10

16 Nov '10

is there any workaround or fix for the problem described in Ticket 1504? http://projects.scipy.org/numpy/ticket/1504 Using static linking sounds like it could be the easiest solution. Can numpy.distutils be used to do that? Thank you for any tips Felix

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dtypes error in recfunctions
by Benjamin Root 16 Nov '10

16 Nov '10

Hello, I was using append_fields() in numpy.lib.recfunctions when I discovered a slight logic mistake in handling the dtypes argument. The code first checks to see if dtypes is None. If so, it then guesses the dtype info from the input data. Then, it goes to see if the dtypes is not a sequence and puts it into a list. This is where the logic breaks down. It then proceeds to use that dtypes to start merging the data. However, if you pass in a sequence of dtype, that condition gets skipped and the rest of the function has to figure out the dtype (and ignores the supplied names as well). I have attached a patch to fix this. I did not check the rest of the module to see if this mis-logic crops up anywhere else. Thanks, Ben Root

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--nocapture with numpy.testing.Tester
by David Warde-Farley 15 Nov '10

15 Nov '10

Hi, I'm trying to use numpy.testing.Tester to run tests for another, numpy-based project. It works beautifully, except for the fact that I can't seem to silence output (i.e. NOSE_NOCAPTURE/--nocapture/-s). I've tried to call test with extra_argv=['-s'] and also tried subclassing to muck with prepare_test_args but nothing seems to work, I still get stdout captured. Does anyone know what I'm doing wrong? David

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Problems testing the floating point flags
by Charles R Harris 15 Nov '10

15 Nov '10

Hi All, This is in reference to numpy ticket #1671<http://projects.scipy.org/numpy/ticket/1671>and the comments on pull request 13 <https://github.com/numpy/numpy/pull/13>. The original problem was that the gcc compiler was reordering the instructions so that the floating point flags were tested before the computation that needed to be checked. The compiler couldn't know that the flags were being tested in the original code because it didn't know that about PyUFunc_getfperr(), although the fact that floating point computations have side effects should probably have limited any code reordering given that unknown. However, even when the macro using the glibc function fetestexcept was used the problem persisted. This is a known bug <http://gcc.gnu.org/bugzilla/show_bug.cgi?id=29186>against gcc >= 4.1 that hasn't been addressed in the last four years and it seems unlikely that it will be fixed anytime soon. The upshot is that there is no reliable way to check the floating point flags using either PyUFunc_getfperr or the macro UFUNC_CHECK_STATUS. Enter the ugly workarounds. If a floating point operation produces a value, it is possible to pass a void pointer to that value as a dummy argument to a flag checking routine which will force the value to be computed before the function is called. There are other games that can be played with volatile but I am not convinced that they are robust or portable across compilers. An added complication is that PyUFunc_getfperr is part of the numpy API and the macro UFUNC_CHECK_STATUS is public so if we add workarounds they need new names. There is also the question if we want to expose them. In any case, suggestions as to names and approaches are welcome. And if anyone has a better solution it would be great to hear it. Chuck

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Printing formatted numerical values
by pv+numpy＠math.duke.edu 15 Nov '10

15 Nov '10

Hi, what is the best way to print (to a file or to stdout) formatted numerical values? Analogously to C's printf("%d %g",x,y) etc? Numpy Documentation only discusses input *from* a file, or output of entire arrays. (np.savetxt()) I just want tab or space-delimited output of selected formatted values. In the absence of numpy documentation on this matter, I tried to follow python documentation and find errors. Below is ipython -pylab transcript, which apparently complains that an int32 variable is an object of type 'str'. How should I understand this? Does python not understand that numpy.int32 is an integer? Thank you! In [2] import numpy as np In [3]: w = np.arange (1,5,dtype=np.int32).reshape((2,2)) In [4]: w Out[4]: array([[1, 2], [3, 4]], dtype=int32) In [5]: w[0,0] Out[5]: 1 In [6]: w[0,0].class Out[6]: <type 'numpy.int32'> In [7]: print('{0:2d}'.format(w[0,0])) ValueError? Traceback (most recent call last) /home/p/o/dev/thesis/python/wavelet/<ipython console> in <module>() ValueError?: Unknown format code 'd' for object of type 'str' --

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getitem and slice
by Keith Goodman 15 Nov '10

15 Nov '10

There is more than one way to form the same slice. For example, a[:2] and a[0:2] and a[0:2:] pass slice objects to getitem with the same start, stop and step. Is there any way to get a hold of the exact character sequence the user used to form the slice? That is, I'd like to know if the user entered ":2", "0:2" or "0:2:". Context: Say I have a 2d array-like object with axis 0 named 'space' and axis 1 named 'time', I'd like to be able to make the following distinctions: a['time':2] --> a[:,2] a['time':2:] --> a[:,2:] a['space':2] --> a[2] a['space':2:] --> a[2:]

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numpy.genfromtxt converters issue
by Damien Moore 15 Nov '10

15 Nov '10

Hi List, I'm trying to import csv data as a numpy array using genfromtxt. The csv file contains mixed data, some floating point, others string codes and dates that I want to convert to floating point. The strange thing is that when I use the 'converters' argument to convert a subset of the columns the resulting output of genfromtxt becomes a 1d array of tuples instead of the desired 2d array of floats. I've provided a simple example below. The output I want should be numpy.array([[1,2],[3,4]]). Any thoughts on how to get my desired output would be appreciated. thanks, Damien import numpy, StringIO s=StringIO.StringIO('q1,2\nq3,4') a=numpy.genfromtxt(s,delimiter=',',converters={0:lambda s:float(s[1:])}) s=StringIO.StringIO('q1,2\nq3,4') b=numpy.genfromtxt(s,delimiter=',') a.shape (2,) b.shape (2,2) >>> a array([(1.0, 2.0), (3.0, 4.0)], dtype=[('f0', '|O4'), ('f1', '<f8')]) >>> b array([[ NaN, 2.], [ NaN, 4.]])

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Simple broadcasting? Or not so simple?? [SEC=UNCLASSIFIED]
by Ross.Wilson＠ga.gov.au 15 Nov '10

15 Nov '10

Dear list, I thought I understood broadcasting, but now I'm not so sure. I've simplified as much as I can, so here goes. I have two input arrays of shape (1, 3, 1). I want to select elements from one or other of the input arrays depending on whether the corresponding element of a third array exceeds a threshold. My simplest code is: --------- import numpy as np a = np.array([[[1],[2],[3]]]) b = np.array([[[4],[5],[6]]]) x = np.array([[[1],[1],[2]]]) result = np.where(x > 1.5, a, b) ---------- and works as expected. Now, my understanding of broadcasting is that if the 'x' array is defined as np.array([[[1]]]) then broadcasting will ensure the result array will contain elements from array 'b'. That is, the program will behave as if 'x' had shape of (1,3,1) with three elements each of value 1. I tested that and got the result I expected. However, when I ran the test on another machine, it failed with an "array dimensions must agree" error. On the failing machine numpy.__version__ returns '1.2.0'. Machines on which the broadcasting works as I expect I see '1.3.0' (or later) in numpy.__version__. Have broadcast rules changed since 1.2.0? Or maybe I just don't understand broadcasting? Thanks in advance, Ross Wilson

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Re: [Numpy-discussion] Where did the github numpy repository go?
by Robin Kraft 14 Nov '10

14 Nov '10

Git is having some kind of major outage: http://status.github.com/ "The site and git access is unavailable due to a database failure. We're researching the issue." On Nov 14, 2010, at 3:29 PM, numpy-discussion-request(a)scipy.org wrote: > > Message: 5 > Date: Sun, 14 Nov 2010 13:29:03 -0700 > From: Charles R Harris <charlesr.harris(a)gmail.com> > Subject: [Numpy-discussion] Where did the github numpy repository go? > To: numpy-discussion <numpy-discussion(a)scipy.org> > Message-ID: > <AANLkTi=Cpz752y88+sFSoH3wTm9POQPhOkyXC55DPpH1(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > I keep getting page does not exist. > > Chuck >

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pyc and pyo files in dmg and other python3 questions also a dmg for python3.1 to try
by Vincent Davis 14 Nov '10

14 Nov '10

The questions below regard the osx dmg installer, not sure about how this applies to other installers. I noticed that pyc and pyo files are included in the binaries. Is there a reason for this? I have removed them in the dmg for python3.1 I see that f2py is installed in /usr/local/bin/. f2py is also located in versions/2.7/bin/ but I am not sure when it gets installed there (versions/2.7/bin/) and why id does not from the dmg installer. Any insight into this? What should the permissions be on the installed numpy files. When I install via $python3.1 setup.py install the owner = VMD(me) group=admin. To match the other dmg installs I have to run $sudo python3.1 setup.py install to get owner=root and group=admin I am kind of working backwords. That is the numpy-1.5.1rc2-py3.1.2-python.org-macosx10.3.dmg was created by replacing the pkg installer file in the dmg from numpy/python2.7 with that from for numpy/python3.1 created with packagemaker gui. The packagemaker setup can be saved as a packagemaker document *.pmdoc which is just a collection of xml files. I can't find any python packages/scripts to edit/create .pmdoc files but that should be easy. Then I still need to have an automated script for the dmg (packagemaker only builds the installer) I have not looked for a python script for this but I assume bdist can be used as a guide (not sure about license issues) Are there better tools build dmgs using python? I realize there is a lot I don't know about building binaries but I am interested so any advice on how to proceed or what the plans are for building py3 binaries would be appreciated and I will try to contribute. Finally here is a py3 binary to try. http://vincentdavis.info/installers/numpy-1.5.1rc2-py3.1.2-python.org-macos… -- Thanks Vincent Davis 720-301-3003

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