Mailman 3 June 2008 - NumPy-Discussion

trace not in linalg namespace
by Alan G Isaac 29 Jun '08

29 Jun '08

I just reached for trace in the numpy.linalg namespace instead of the numpy namespace, once again, and it made me wonder: is the current location most natural? Related: is it surprising not to find it where I expected? Cheers, Alan Isaac

2 1

Eigenvectors in Matlab vs. Numpy
by Saket 29 Jun '08

29 Jun '08

Hi, I'm having this weird problem when computing eigenvalues/vectors with Numpy. I have the following symmetric matrix, B: -0.3462 0.6538 0.5385 -0.4615 0.6538 -0.3462 -0.3462 -0.3462 0.6538 -0.3462 0.5385 -0.4615 0.6538 -0.3462 -0.3462 -0.3462 0.5385 0.5385 -0.6154 0.3846 0.5385 -0.4615 -0.4615 -0.4615 -0.4615 -0.4615 0.3846 -0.6154 -0.4615 0.5385 0.5385 0.5385 0.6538 0.6538 0.5385 -0.4615 -0.3462 -0.3462 -0.3462 -0.3462 -0.3462 -0.3462 -0.4615 0.5385 -0.3462 -0.3462 0.6538 0.6538 -0.3462 -0.3462 -0.4615 0.5385 -0.3462 0.6538 -0.3462 0.6538 -0.3462 -0.3462 -0.4615 0.5385 -0.3462 0.6538 0.6538 -0.3462 I compute the eigenvalues and eigenvectors of B using numpy.linalg.eig(B). I get the following eigenvalues: [ 2.79128785e+00 -1.79128785e+00 1.64060486e-16 -3.07692308e-01 -1.00000000e+00 -1.00000000e+00 -1.00000000e+00 -1.00000000e+00] I do the same thing in Matlab and get the SAME eigenvalues. However, my eigenVECTORS in Matlab versus numpy are different. It makes no sense to me. In general, the following relationship should hold: Bx = Lx, where B is my matrix, x is an eigenvector, and L is the corresponding eigenvalue. For the eigenvectors that Matlab returns, I have confirmed that the relationship does hold. But for the Numpy eigenvectors, it doesn't! Any idea why this might be happening? I did some computations myself and it looks like the Matlab output is correct. Just seems like the eigenvectors that Numpy is returning are wrong... Thanks for any suggestions. Saket

3 7

copying in nanXXX
by Damian Eads 29 Jun '08

29 Jun '08

Hi there, I'm using nansum for some code and noticed it does a bit of copying. Specifically, the nanxxx functions copy the input array, create an isnan boolean mask, set the nan values to make them insignificant (nansum: 0, nanmin: inf, or nanmax: -inf), and then call xxx to compute the statistic. def nansum(a, axis=None): """Sum the array over the given axis, treating NaNs as 0. """ y = array(a,subok=True) if not issubclass(y.dtype.type, _nx.integer): y[isnan(a)] = 0 return y.sum(axis) Unless someone has already done this, I will offer to write C versions of these functions. Does anyone else think this is useful? Cheers, Damian

2 1

Ticket #164
by Charles R Harris 28 Jun '08

28 Jun '08

Is the patch ticket in #164<http://projects.scipy.org/scipy/numpy/ticket/164>still needed? There was some discussion along similar lines here not so long ago... Chuck

1 0

numpy.distutils problem with py2app/py2exe?
by Zachary Pincus 28 Jun '08

28 Jun '08

Hello all, I've noticed that py2app and py2exe work strangely on my project, which (having fortran code) is driven by the numpy distutils. Now, these two distutils commands need to peek into the build/lib. [whatever] directories to grab the files to package up. Indeed, the docs for py2exe and py2app say that the build directories are automatically added to the path. However, I found that for my project, I need to explicitly add lines to the setup.py file like: if have_py2exe: sys.path.insert(0, './build/lib.win32-%d.%d'%(sys.version_info[0], sys.version_info[1])) I got around to digging a little deeper, and at least in the py2app case, py2app distutils Command subclass gets the build dir information as follows: def run(self): build = self.reinitialize_command('build') build.run() [... snip ...] extra_paths.extend([build.build_platlib, build.build_lib]) Now, when I run py2app, the build.build_platlib and build.build_lib values are None. So py2app never finds the library directory, and thus packages the files incorrectly. Is this likely to be (a) a problem in numpy.distutils, (b) a problem with my local setup, or (c) a problem with py2app? Any thoughts? Zach

1 0

sampling based on running sums
by John Hunter 27 Jun '08

27 Jun '08

I would like to find the sample points where the running sum of some vector exceeds some threshold -- at those points I want to collect all the data in the vector since the last time the criteria was reached and compute some stats on it. For example, in python tot = 0. xs = [] ys = [] samples1 = [] for thisx, thisy in zip(x, y): tot += thisx xs.append(thisx) ys.append(thisy) if tot>=threshold: samples1.append(func(xs,ys)) tot = 0. xs = [] ys = [] The following is close in numpy sx = np.cumsum(x) n = (sx/threshold).astype(int) ind = np.nonzero(np.diff(n)>0)[0]+1 lasti = 0 samples2 = [] for i in ind: xs = x[lasti:i+1] ys = y[lasti:i+1] samples2.append(func(xs, ys)) lasti = i But the sample points in ind do no guarantee that at least threshold points are between the sample points due to truncation error. What is a good numpy way to do this? Thanks, JDH

2 1

SciPy Conference Updates
by Travis Vaught 27 Jun '08

27 Jun '08

Greetings, The SciPy Conference is not too far away. I thought I'd summarize some recent news about the conference in case some of you missed it: - Accommodations (news!): We've negotiated a group rate with a nearby Marriott hotel, for those that would like to take advantage of it. The hotel has set up a web site for our event here: http://cwp.marriott.com/laxot/scipyworkshop/ - Student Sponsorship: As you may have seen, the Python Software Foundation has agreed to partner with Enthought to sponsor 10 students' travel, registration, and accommodation for the tutorials, conference and (most importantly) sprints. If you're in college or a graduate program, please check out the details here: http://conference.scipy.org/sponsoring - Abstracts Submission Deadline Extended: The review committee is extending the deadline to Monday, June 30th. Please see the Call for Papers for instructions on abstract submission here: http://conference.scipy.org/call_for_papers Please drop me an email if you have any questions or comments. Best, Travis

1 0

Should the fields in void scalars be available?
by Charles R Harris 27 Jun '08

27 Jun '08

Question, In [24]: x = array(('1', u'2'), dtype=[('a', '|S4'), ('b', '<U2')]) In [25]: x.shape Out[25]: () In [26]: x['a'] Out[26]: array('1', dtype='|S4') Shouldn't the last be a string? Chuck

3 3

Scipy08 Paper submission deadline extention to Monday 30th
by Gael Varoquaux 27 Jun '08

27 Jun '08

The deadline for submitting abstracts to the Scipy conference was tonight. In order to give you more time to submit excellent abstracts, the review committee is extending the deadline to Monday (June 30th), and will work hastily to get all of them reviewed in time for the program announcement, on Thursday July 3rd. ---- The SciPy 2008 Conference will be held 21-22 August 2008 at the California Institute of Technology, Pasadena, California. SciPy is a scientific computing package, written in the Python language. It is widely used in research, the industry and academia. The program features tutorials, contributed papers, lightning talks, and bird-of-a-feather sessions. We are soliciting talks and accompanying papers (either formal academic or magazine-style articles) that discuss topics which center around scientific computing using Python. These include applications, teaching, future development directions and research. A collection of peer-reviewed articles will be published as part of the proceedings. Proposals for talks are submitted as extended abstracts. There are two categories of talks: Lightning talks These talks are 10 minutes in duration. An abstract of between 300 and 700 words should describe the topic and motivate its relevance to scientific computing. Lightning talks do not require an accompanying article (although, if submitted, these will still be published). Paper presentations These talks are 35 minutes in duration (including questions). A one page abstract of no less than 500 words (excluding figures and references) should give an outline of the final paper. Papers are due two weeks before the conference, and may be in a formal academic style, or in a more relaxed magazine-style format. If you wish to present a talk at the conference, please create an account on the website http://conference.scipy.org. You may then submit an abstract by logging in, clicking on your profile and following the " Submit an abstract " link. Gaël, on behalf on the SciPy08 organizing committee.

2 2

Windows_XP_x86_64_MSVC buildbot
by Thomas Heller 27 Jun '08

27 Jun '08

I'm going to have a 2 or 3-weeks vacation, and will shut down the Windows_XP_x86_64_MSVC during this time. I will restart it when I come back, sorry for the inconvenience. Thanks, Thomas

1 0