Mailman 3 October 2011 - NumPy-Discussion

Crash on (un-orthodox) __import__
by Andrea Gavana 07 Oct '11

07 Oct '11

Hi All, I was fiddling here and there with some code doing dynamic import of stuff, and I noticed that this code: import os import sys init_name = r"C:\Python27\Lib\site-packages\numpy\__init__.py" directory, module_name = os.path.split(init_name) main = os.path.splitext(module_name)[0] sys.path.insert(0, os.path.normpath(directory)) # Crash here... mainmod = __import__(main) Produces a hard crash on Python (i.e., a dialog box with a "python.exe has stopped working" message). I know I am not supposed to import stuff like that, but I was curious to understand why Python should crash in this way. This happens on Python 2.7.2 with Numpy 1.6.1 and Python 2.5.4 with Numpy 1.5.0 Thank you for your suggestions :-D Andrea. "Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/ >>> import PyQt4.QtGui Traceback (most recent call last): File "<interactive input>", line 1, in <module> ImportError: No module named PyQt4.QtGui >>> >>> import pygtk Traceback (most recent call last): File "<interactive input>", line 1, in <module> ImportError: No module named pygtk >>> >>> import wx >>> >>>

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nditer: possible to manually handle dimensions with different lengths?
by John Salvatier 06 Oct '11

06 Oct '11

Using nditer, is it possible to manually handle dimensions with different lengths? For example, lets say I had an array A[5, 100] and I wanted to sample every 10 along the second axis so I would end up with an array B[5,10]. Is it possible to do this with nditer, handling the iteration over the second axis manually of course (probably in cython)? I want something like this (modified from http://docs.scipy.org/doc/numpy/reference/arrays.nditer.html#putting-the-in… ) @cython.boundscheck(False) def sum_squares_cy(arr): cdef np.ndarray[double] x cdef np.ndarray[double] y cdef int size cdef double value cdef int j axeslist = list(arr.shape) axeslist[1] = -1 out = zeros((arr.shape[0], 10)) it = np.nditer([arr, out], flags=['reduce_ok', 'external_loop', 'buffered', 'delay_bufalloc'], op_flags=[['readonly'], ['readwrite', 'no_broadcast']], op_axes=[None, axeslist], op_dtypes=['float64', 'float64']) it.operands[1][...] = 0 it.reset() for xarr, yarr in it: x = xarr y = yarr size = x.shape[0] j = 0 for i in range(size): #some magic here involving indexing into x[i] and y[j] return it.operands[1] Does this make sense? Is it possible to do?

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build errors
by Miah Wadud Dr (ITCS) 06 Oct '11

06 Oct '11

Hello numpy users, I am trying to build numpy 1.6.1 and am having problems. It prints the following error message: gcc -pthread -shared build/temp.linux-x86_64-2.4/numpy/core/blasdot/_dotblas.o -L/usr/lib64/atlas -Lbuild/temp.linux-x86_64-2.4 -lptf77blas -lptcblas -latlas -o build/lib.linux-x86_64-2.4/numpy/core/_dotblas.so /usr/bin/ld: /usr/lib64/atlas/libptcblas.a(cblas_dptgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC /usr/lib64/atlas/libptcblas.a: could not read symbols: Bad value collect2: ld returned 1 exit status /usr/bin/ld: /usr/lib64/atlas/libptcblas.a(cblas_dptgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC /usr/lib64/atlas/libptcblas.a: could not read symbols: Bad value collect2: ld returned 1 exit status error: Command "gcc -pthread -shared build/temp.linux-x86_64-2.4/numpy/core/blasdot/_dotblas.o -L/usr/lib64/atlas -Lbuild/temp.linux-x86_64-2.4 -lptf77blas -lptcblas -latlas -o build/lib.linux-x86_64-2.4/numpy/core/_dotblas.so" failed with exit status 1 I do not know anything about the setup.py script, so do not know how to add the -fPIC switch. Any help will be greatly appreciated. Regards, ---------- Wadud Miah, High Performance Computing Systems Developer Research Computing Services, University of East Anglia Web: http://www.uea.ac.uk/~xca10fju/ Telephone: 01603 593856 Information Services ----------

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simple vector->matrix question
by Neal Becker 06 Oct '11

06 Oct '11

Given a vector y, I want a matrix H whose rows are y - x0 y - x1 y - x2 ... where x_i are scalars Suggestion?

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oblique text
by Alexandre Leray 05 Oct '11

05 Oct '11

Dear all, I'm trying to create oblique texts by reordering their letters. Here is an exemple to illustrate this (to be display in a monospaced font): >>> text = """\ ... This ... is ... a ... test""" >>> print(make_oblique(text)) T i h a s i t s e s t So far I have this: def make_oblique(text): words = text.splitlines() matrix = [[" " for i in xrange(len(words) + len(max(words)))] \ for j in xrange(len(words) + len(max(words)))] for i, word in enumerate(words): for j, letter in enumerate(word): matrix[j + i][j] = letter matrix = map(lambda x: "".join(x), matrix) return "\n".join(matrix) But it is not very flexible. For instance, I'd like to control the "line spacing" (by adding extra spaces in between letters since it isn't real lines). I just found numpy and I have the intuition that it could do the job since it deals with matrices. Am I right? If so how would you do such a thing? Thanks! Alex

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A Foundation for the support of NumPy and SciPy
by Travis Oliphant 05 Oct '11

05 Oct '11

Hi all, At the recent US SciPy conference and at other times in the past I have been approached about the possibility of creating a foundation to support the development of SciPy and NumPy. I know there are varying opinions about that, but I am generally very supportive of the idea and would like to encourage it as much as I can. It would be interesting to have a public discussion of the issues, but these discussions should not clog the main list of either NumPy or SciPy. As a result, there has been set up a public mailing list for discussion of the creation of a Foundation for the Advancement of Scientific, Technical, and Engineering Computing Using High Level Abstractions (FASTECUHLA). The list is fastecuhla(a)googlegroups.com This is a place-holder name that can be replaced if somebody comes up with a better one. Please sign up for that list if you would like to contribute to the discussion. The items to discuss include: * where to organize * what the purposes should be * who should be members * where should money come from * what other organizations exist that we could either piggy-back on or emulate * what are the pitfalls on starting a foundation to support NumPy and SciPy versus other approaches * who has time to participate in its organization and maintenance One important feature is that I see this foundation as a service opportunity and obligation and not as a "feather-in-the-cap" or something to join lightly. I'm hopeful that it can be a place where people and organizations can donate money and know that it will be going directly to further the core packages for Scientific Computing with Python. Thank you, -Travis

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should the return type of matlib.reshape be ndarray or matrix?
by Alan G Isaac 04 Oct '11

04 Oct '11

Is this the intended behavior? >>> from numpy import matlib >>> m = matlib.reshape([1,2],(2,1)) >>> type(m) <type 'numpy.ndarray'> For any 2d shape, I expected a matrix. (And probably an exception if the shape is not 2d.) Thanks, Alan Isaac

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(no subject)
by Alex Ter-Sarkissov 03 Oct '11

03 Oct '11

I got a problem running NumPy in Eclipse. I recently installed PyDev, but after downloading NumPy the installation attempt failed since python 2.6 was not found. I've installed Python 2.7. Do I need to replace it with Python 2.6?

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[ANN] SciPy India 2011 Call for Presentations
by Jarrod Millman 02 Oct '11

02 Oct '11

=============================== SciPy 2011 India Call for Papers =============================== The third `SciPy India Conference <http://scipy.in>`_ will be held from December 4th through the 7th at the `Indian Institute of Technology, Bombay (IITB) <http://www.iitb.ac.in/>`_ in Mumbai, Maharashtra India. At this conference, novel applications and breakthroughs made in the pursuit of science using Python are presented. Attended by leading figures from both academia and industry, it is an excellent opportunity to experience the cutting edge of scientific software development. The conference is followed by two days of tutorials and a code sprint, during which community experts provide training on several scientific Python packages. We invite you to take part by submitting a talk abstract on the conference website at: http://scipy.in Talk/Paper Submission --------------------- We solicit talks and accompanying papers (either formal academic or magazine-style articles) that discuss topics regarding scientific computing using Python, including applications, teaching, development and research. We welcome contributions from academia as well as industry. Keynote Speaker --------------- Eric Jones will deliver the keynote address this year. Eric has a broad background in engineering and software development and leads Enthought's product engineering and software design. Prior to co-founding Enthought, Eric worked with numerical electromagnetics and genetic optimization in the Department of Electrical Engineering at Duke University. He has taught numerous courses on the use of Python for scientific computing and serves as a member of the Python Software Foundation. He holds M.S. and Ph.D. degrees from Duke University in electrical engineering and a B.S.E. in mechanical engineering from Baylor University. Eric was the Keynote Speaker at SciPy US 2011. Important Dates --------------- October 26, 2011, Wednesday: Abstracts Due October 31, 2011, Monday: Schedule announced November 21, 2011, Monday: Proceedings paper submission due December 4-5, 2011, Sunday-Monday: Conference December 6-7 2011, Tuesday-Wednesday: Tutorials/Sprints Organizers ---------- * Jarrod Millman, Neuroscience Institute, UC Berkeley, USA (Conference Co-Chair) * Prabhu Ramachandran, Department of Aerospace Engineering, IIT Bombay, India (Conference Co-Chair) * FOSSEE Team

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iterate over multiple arrays
by David Froger 01 Oct '11

01 Oct '11

Hy everybody, I'm wondering what is the (best) way to apply the same function to multiple arrays. For example, in the following code: from numpy import * def f(arr): return arr*2 a = array( [1,1,1] ) b = array( [2,2,2] ) c = array( [3,3,3] ) d = array( [4,4,4] ) a = f(a) b = f(b) c = f(c) d = f(d) I would like to replace : a = f(a) b = f(b) c = f(c) d = f(d) with something like that, but which really modify a,b,c and d: for x in [a,b,c,d]: x = f(x) So having something like a pointer on the arrays. Thanks for your help ! David --

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NumPy-Discussion October 2011