Mailman 3 July 2007 - NumPy-Discussion

Problems with RandomArray
by Alexander Dietz 07 Jul '07

07 Jul '07

Hi, I am not sure how to subscribe to this mailing list (there was no link for that, just this email adress), but hopefully someone will get this email and can me subscribe to this list, answer my question or ask someone else. Anyway, here is my question: I am using python with matplotlib version 0.90.1 and with numpy (as recommended), on a Linux box. So far matplotlib and numpy is working, but I need to use RandomArray! So, RandomArray can be found in the "Numerical Python" documentation and RandomArray.py can also be found within the "numeric" directory. If including this to my PYTHONPATH variable I can import RandomArray and also use some of the functions! But the function I am interested in is: multivariate_normal. When I try to use this function python stops responding, I have to kill python from outside! Is there a way to make this function work? Or maybe there is a quick workaround using functions in random and else? That would be really great! Cheers Alex

2 1

Aligning an array on Windows
by Francesc Altet 07 Jul '07

07 Jul '07

Hi, Some time ago I made an improvement in speed on the numexpr version of PyTables so as to accelerate the operations with unaligned arrays (objects that can appear quite commonly when dealing with columns of recarrays, as PyTables does). This improvement has demostrated to work correctly and flawlessly in Linux machines (using GCC 4.x and in both 32-bit and 64-bit Linux boxes) for several weeks of intensive testing. Moreover, its speed-up is ranging from a 40% on modern processors and up to a 70% in older ones, so I'd like to keep it. The surprise came today when I tried to compile the same code on a Windows box (Win XP Service Pack 2) using MSVC 7.1, through the free (as in beer) Toolkit 2003. The compilation process went fine, but the problem is that I'm getting crashes from time to time when running the numexpr test suite. After some in-depth investigation, I'm pretty sure that the problem is in a concrete part of the code that I'd modified for this improvement. IMO, the affected code is in numexpr/interp_body.c and reads like: case OP_COPY_II: VEC_ARG1(memcpy(dest, x1, sizeof(int)); dest += sizeof(int); x1 += stride1); case OP_COPY_LL: VEC_ARG1(memcpy(dest, x1, sizeof(long long)); dest += sizeof(long long); x1 += stride1); case OP_COPY_FF: VEC_ARG1(memcpy(dest, x1, sizeof(double)); dest += sizeof(double); x1 += stride1); case OP_COPY_CC: VEC_ARG1(memcpy(dest, x1, sizeof(double)*2); dest += sizeof(double)*2; x1 += stride1); This might seem complicated, but it is not. Each of the OP_COPY_XX is a function that has to copy source (x1) to destination (dest) for int, long long, double and complex data types (this function will be called in a loop for copying all the data in array). The code for the original numexpr reads as: case OP_COPY_BB: VEC_ARG1(b_dest = b1); case OP_COPY_II: VEC_ARG1(i_dest = i1); case OP_COPY_FF: VEC_ARG1(f_dest = f1); case OP_COPY_CC: VEC_ARG1(cr_dest = c1r; ci_dest = c1i); i.e. the copy is done through direct assignment. This can be done because, in the original numexpr, an array is always guaranteed to reach this part of the code (the computing kernel) in the aligned form. But in my code, this is not guaranteed (the copy is made precisely for alignment purposes), so this is why I need to make use of memcpy/memmove calls. The thing I don't see is why my version of the code can create problems on Windows platforms and work perfectly on Linux ones. I've tried to use memmove instead of memcpy, but the problem persists. I've had a look at how numpy makes an 'aligned' copy of an unaligned array, and it seems to me that it uses memcpy/memmove (not sure when you should use one or another) just as I use it above. It might be possible that the problem is in another place, but my tests reaffirm me in the possibility that something is wrong with my copy code above (but again, I can't see where). Of course, we can get rid of this optimization but it is a bit depressing to have renounce to it just because it doesn't work on Windows :( Thanks in advance for any hint you may provide! -- Francesc Altet | Be careful about using the following code -- Carabos Coop. V. | I've only proven that it works, www.carabos.com | I haven't tested it. -- Donald Knuth

2 4

PEP 368: Standard image protocol and class
by Lino Mastrodomenico 06 Jul '07

06 Jul '07

[Sorry for the cross-posting, but I think this may be relevant for both NumPy and ndimage.] Hello everyone, I have submitted to the Python core developers a new PEP (Python Enhancement Proposal): http://www.python.org/dev/peps/pep-0368/ It proposes two things: * the creation of a standard image protocol/interface that can be hopefully implemented interoperably by most Python libraries that manipulate images; * the addition to the Python standard library of a basic implementation of the new protocol. The new image protocol is heavily inspired by a subset of the NumPy array interface, with a few image-specific additions and changes (e.g. the "size" attribute of an image is a tuple (width, height)). Of course it would be wonderful if these new image objects could interoperate out-of-the-box with numpy arrays and ndimage functions. There is another proposal that would be very useful for that, PEP 3118 by Travis Oliphant and Carl Banks: http://www.python.org/dev/peps/pep-3118/ The image PEP (368) currently lists only modes based on uint8/16/32 numbers, but the final version will probably also include modes based on float32 and float16 (converted in software to/from float32/64 when necessary). A discussion about it is currently going on in the python-3000 mailing list: <http://mail.python.org/pipermail/python-3000/2007-July/thread.html#8648> Any suggestion, comment or criticism from the NumPy/SciPy people would be very useful, but IMHO keeping the discussion only on the python-3000 ML may be a good idea, to avoid duplicating answers on different mailing lists. Thanks in advance. -- Lino Mastrodomenico E-mail: l.mastrodomenico(a)gmail.com

2 2

how do I configure with gfortran
by Mathew Yeates 06 Jul '07

06 Jul '07

Does anyone know how to run python setup.py build and have gfortran used? It is in my path. Mathew

6 17

ANN: SciPy Conference Early Registration Reminder
by Travis Vaught 06 Jul '07

06 Jul '07

Greetings, The *SciPy 2007 Conference on Scientific Computing with Python* early registration deadline is July 15, 2007. After this date, the price for registration will increase from $150 to $200. More information on the Conference is here: http://www.scipy.org/ SciPy2007 The registration page is here: https://www.enthought.com/scipy07/ The Conference is to be held on August 16-17. Tutorial Sessions are being offered on August 14-15 (http://www.scipy.org/SciPy2007/ Tutorials). The price to attend Tutorials is $75. The Saturday following the Conference will hold a Sprint session for those interested in pitching in on particular development efforts. (suggestions welcome: http://www.scipy.org/SciPy2007/Sprints) Today is the deadline for abstract submissions for those wanting to present at the conference. Please email to abstracts(a)scipy.org by midnight US Central Time. From the conference web page: "If you are using Python in Scientific Computing, we'd love to hear from you. If you are interested in presenting at the conference, you may submit an abstract in Plain Text, PDF or MS Word formats to abstracts(a)scipy.org -- the deadline for abstract submission is July 6, 2007. Papers and/or presentation slides are acceptable and are due by August 3, 2007. Presentations will be allowed 30-35 minutes, depending on the final schedule." We're looking forward to another great gathering. Best, Travis

1 0

What is an empty matrix ?
by David Cournapeau 05 Jul '07

05 Jul '07

Hi, I was wondering what an empty matrix is, and what it is useful for (by empty matrix, I mean something created by numpy.matrix([])) ? Using those crash some functions (see for example scipy ticket #381), and I am not sure how to fix this bug. David

5 7

f2py and openmp
by lorenzo bolla 05 Jul '07

05 Jul '07

hi all, I'm using f2py to compile a f90 function, parallelized with openmp, into a shared object, that I can import in python. the question is: when I call the function from python, how can I specify the number of threads to use? the usual way of doing it, with a common fortran executable, is setting the enviroment variable OMP_NUM_THREADS to the desired value. using os.environ to set it from python does not seem to work: the function is always executed using 4 processors (that is quite strange in itself: where does "4" comes from?). any hints? thank you all in advance, lorenzo.

1 0

Re: [Numpy-discussion] [SciPy-dev] numpy.cumproduct() documentation: bug?
by Alan G Isaac 04 Jul '07

04 Jul '07

On Wed, 04 Jul 2007, dmitrey apparently wrote: > cumproduct(x, axis=None, dtype=None, out=None) > Sum the array over the given axis. Docstring bug. But it behaves right. Cheers, Alan Isaac

1 0

Scipy release
by John Reid 04 Jul '07

04 Jul '07

Hi, Is there going to be a scipy release anytime soon? I'm using numpy 1.0.3 with scipy 0.5.2 and I get these ugly warnings all the time: c:\apps\python25\lib\site-packages\scipy\misc\__init__.py:25: DeprecationWarning: ScipyTest is now called NumpyTest; please update your code test = ScipyTest().test These are the latest downloadable versions right? I'm beginning to wonder whether I shouldn't start building scipy myself. Thanks, John.

4 8

Does Numpy's covariance function numpy.cov() work for complex data?
by Rudolph van der Merwe 04 Jul '07

04 Jul '07

Does anyone know if Numpy's covariance calculation function, cov(), which is located in /numpy/lib/function_base.py calculate the covariance matrix of complex data correctly? I.e., does it implement something like , P = cov(X) = 1/(N-1) * \Sum_i ( X[:,i] * transpose(X[:,i].conj()) ) -- Rudolph van der Merwe

1 0