Mailman 3 May 2010 - NumPy-Discussion

building numpy against Cray xt-libsci
by Amir 01 Jul '10

01 Jul '10

I am trying to build numpy against Cray's xt-libsci library on a Cray XT5. I am getting an error I am hoping for hints on how to resolve: In [1]: import numpy <snip> 20 isfinite, size 21 from numpy.lib import triu ---> 22 from numpy.linalg import lapack_lite 23 from numpy.matrixlib.defmatrix import matrix_power 24 ImportError: /opt/xt-libsci/10.4.0/gnu/lib/libsci.so: undefined symbol: fftw_version These are the symbols in libsci: % nm /opt/xt-libsci/10.4.0/gnu/lib/libsci.so | grep fftw_version 00000000010f9a30 B __crafft_internal__crafft_fftw_version_num U fftw_version 00000000005aa8a4 T get_fftw_version I first built numpy with no custom site.cfg file. It built correctly and all tests ran. But it was too slow. Then I tried building numpy against libsci, which has BLAS, LAPACK, FFTW3 among other things. I had to build a libcblas.a from the netlib src as libsci does not have cblas (using gcc, gfortran 4.3.3). Here is my site.cfg, accumulated from several nice tutorials on how to build numpy on these machines, which for some reason don't work for me. The instructions were based on numpy 1.2. [blas] blas_libs = cblas library_dirs = /global/homes/amir/local/lib [lapack] lapack_libs = sci library_dirs = /opt/xt-libsci/10.4.0/gnu/lib [blas_opt] blas_libs = cblas, sci libraries = cblas, sci [lapack_opt] libraries = sci [fftw] libraries = fftw3 Here is what is linked to lapack_lite.so: % ldd ./numpy/linalg/lapack_lite.so libsci.so => /opt/xt-libsci/10.4.0/gnu/lib/libsci.so (0x00002b4493325000) libgfortran.so.3 => /opt/gcc/4.3.3/snos/lib64/libgfortran.so.3 (0x00002b44a4579000) libm.so.6 => /lib64/libm.so.6 (0x00002b44a4770000) libgcc_s.so.1 => /opt/gcc/4.3.3/snos/lib64/libgcc_s.so.1 (0x00002b44a48c6000) libc.so.6 => /lib64/libc.so.6 (0x00002b44a49dd000) /lib64/ld-linux-x86-64.so.2 (0x0000555555554000) Thanks, Amir.

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[Job] research developer job opening at AQR Capital
by Wes McKinney 10 Jun '10

10 Jun '10

We are looking for a scientific Python developer to work on the design and implementation of AQR’s proprietary research and production systems. In this role you will work closely with researchers and portfolio managers to identify problems and create solutions addressing speed, scale, and usability. Most of our work goes into building back-testing infrastructure and other tools for quantitative portfolio analysis. As part of this you will become intimately familiar with financial concepts and AQR’s investment philosophy. Requirements ------------ * Degree in computer science, mathematics, or other technical discipline * Experience level: recent graduates up to 5 years * Experience using NumPy and/or SciPy libraries * Effective problem solving and quantitative skills * Well organized, detail oriented and able to focus in a dynamic environment * Ability to discuss and explain involved concepts in both verbal and written form * Able to work independently, as well as part of a team About AQR Capital Management ---------------------------- The founders of AQR were still Ph.D. candidates when they initially developed the complex financial models that are now at AQR’s core. Today, AQR Capital Management is a $24 billion asset management firm employing a disciplined multi-asset, global research process (AQR stands for Applied Quantitative Research). AQR's investment products are provided through a limited set of collective investment vehicles and separate accounts that deploy all or a subset of AQR's investment strategies. These investment products span from aggressive high volatility market-neutral hedge funds, to low volatility benchmark-driven traditional products. AQR is located in Greenwich, CT, a short commute from New York City. * If you are interested in applying for this position please submit your resume to matt.gombos(a)aqr.com and put "GAARD Candidate" in the subject line. * We are an affirmative action / equal opportunity employer.

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Bug in nanmin called with unsigned integers
by Tony S Yu 06 Jun '10

06 Jun '10

I got bit again by this bug with unsigned integers. (My original changes got overwritten when I updated from svn and, unfortunately, merged conflicts without actually looking over the changes.) In any case, I thought it'd be a good time to bump the issue (with patch). Cheers, -Tony PS: Just for context, this issue comes up when displaying images with Chaco (which converts images to unsigned integer arrays and calls nanmin).

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Finding Star Images on a Photo (Video chip) Plate?
by Wayne Watson 01 Jun '10

01 Jun '10

Suppose I have a 640x480 pixel video chip and would like to find star images on it, possible planets and the moon. A possibility of noise exits, or bright pixels. Is there a known method for finding the centroids of these astro objects? -- Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet There are no statues or memorials dedicated to Thomas Paine for his substantial part in the American Revolution. -- An observation in The Science of Liberty by Timoth Ferris Web Page:<www.speckledwithstars.net/>

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Introduction to Scott, Jason, and (possibly) others from Enthought
by Travis Oliphant 31 May '10

31 May '10

Hi everyone, There has been some talk about re-factoring NumPy to separate out the Python C-API layer and make NumPy closer to a C-library. I know there are a few different ideas about what this means, and also that people are very busy. I also know there is a NumPy 2.0 release that is in the works. I'm excited to let everyone know that we (at Enthought) have been able to find resources (about 3 man months) to work on this re-factoring project and Scott and Jason (both very experienced C and Python programmers) are actively pursuing it. My hope is that NumPy 2.0 will contain this re-factoring (which should be finished just after SciPy 2010 --- where I'm going to organize a Sprint on NumPy which will include at least date-time improvements and re-factoring work). While we have specific goals for the re-factoring, we want this activity to be fully integrated with the NumPy community and Scott and Jason want to interact with the community as much as feasible as they suggest re-factoring changes (though they both have more experience with phone-conversations to resolve concerns than email chains and so some patience from everybody will be appreciated). Because Jason and Scott are new to this mailing list (but not new to NumPy), I wanted to introduce them so they would feel more comfortable posting questions and people would have some context as to what they were trying to do. Scott and Jason are both very proficient and skilled programmers and I have full confidence in their abilities. That said, we very much want the input of as many people as possible as we pursue the goal of grouping together more tightly the Python C-API interface layer to NumPy. I will be involved in some of the discussions, but am currently on a different project which has tight schedules and so I will only be able to provide limited "mailing-list" visibility. Best regards, -Travis

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linalg.det throws IndexError on 2.6.5
by Ilya Sterin 30 May '10

30 May '10

I'm not sure what's causing this at this point and before I dig deeper thought someone can shed some light... On my Mac OS X python 2.6.1, numpy.linalg.det functions properly... >>> numpy.linalg.det(numpy.array([[1, 2], [3, 4]])) -2.0 On Centos 5 python 2.6.5, I get and IndexError (out of bounds)... >>> numpy.linalg.det(numpy.array([[1, 2], [3, 4]])) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/opt/python2.6/lib/python2.6/site-packages/numpy/linalg/linalg.py", line 1507, in det return (1.-2.*sign)*multiply.reduce(diagonal(a), axis=-1) File "/opt/python2.6/lib/python2.6/site-packages/numpy/core/fromnumeric.py", line 949, in diagonal return asarray(a).diagonal(offset, axis1, axis2) IndexError: index 12884901888 out of bounds 0<=index<4 Any ideas? Thanks. Ilya

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ix_ and copies
by Keith Goodman 30 May '10

30 May '10

Will making changes to arr2 never change arr1 if arr2 = arr1[np.ix_(*lists)] where lists is a list of (index) lists? np.ix_ returns a tuple of arrays so I'm guessing (and hoping) the answer is yes.

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shuffle a slice
by Keith Goodman 29 May '10

29 May '10

np.random.shuffle: "Modify a sequence in-place by shuffling its contents." Matches doc string: >> a = np.arange(10) >> np.random.shuffle(a[:-1]) >> a array([0, 7, 8, 4, 3, 6, 2, 1, 5, 9]) Doesn't match doc string: >> l = range(10) >> np.random.shuffle(l[:-1]) >> l [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] Is there any way for numpy to catch this?

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assert_almost_equal and inf
by josef.pktd＠gmail.com 29 May '10

29 May '10

I'm getting some test failures in my code with infs in numpy 1.4, nan treatment has been corrected in numpy.testing >>> assert_almost_equal(np.array([-5.23722324, -np.nan, -5.23722324]), np.array([-5.23722324, -np.nan, -5.23722324])) but it seems that inf doesn't compare almost equal >>> assert_almost_equal(np.array([-5.23722324, -np.inf, -5.23722324]), np.array([-5.23722324, -np.inf, -5.23722324])) Traceback (most recent call last): ... ValueError: Arrays are not almost equal x: array([-5.23722324, -Inf, -5.23722324]) y: array([-5.23722324, -Inf, -5.23722324]) numpy 1.4.0 has this been changed already? or is it not desired? Josef

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Gauss-Newton Method in Python?
by Wayne Watson 28 May '10

28 May '10

Is Subject method available in Python? -- Wayne Watson (Watson Adventures, Prop., Nevada City, CA) (121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time) Obz Site: 39° 15' 7" N, 121° 2' 32" W, 2700 feet There are no statues or memorials dedicated to Thomas Paine for his substantial part in the American Revolution. -- An observation in The Science of Liberty by Timoth Ferris Web Page:<www.speckledwithstars.net/>

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NumPy-Discussion May 2010