Mailman 3 October 2007 - NumPy-Discussion

Re: [Numpy-discussion] numpy/Windows shared arrays between processes?
by Ray S 09 Oct '07

09 Oct '07

On 10/9/07, Sebastian Haase replied: > > Did you find that locks > > or semaphores were needed? > Maybe that's why it crashed ;-) !? But for simple use it seems fine. I just did some code (below) that does read/write to the array AFAP, and there is no crash, or any other issue (Win2000, py2.4, numpy 1.0b1). Without the print statements, it does max both processors; with printing I/O only 58%. Both processes can modify the array without issue either. I'll experiment with I had seen the Win mmap in this thread: http://objectmix.com/python/127666-shared-memory-pointer.html and here: http://www.codeproject.com/cpp/embedpython_2.asp Note also that the Python mmap docs read "In either case you must provide a file descriptor for a file opened for update." and no mention of the integer zero descriptor option. Access options behave as presented. Because *NIX has MAP_SHARED as an option you'd think that there might be cross-platform share behavior with some platform checking if statements. Without a tag though, how does another process reference the same memory on NIX, a filename? (It seems) > > But I had the same > > issue as Mark Heslep > > http://aspn.activestate.com/ASPN/Mail/Message/ctypes-users/3192422 > > of creating a numpy array from a raw address (not a c_array). >I assume this is a different issue, but haven't looked into it yet. Yes, a different methodology attempt. It would be interesting to know anyway how to create a numpy array from an address; it's probably buried in the undocumented C-API that I don't grok, and likely frowned upon. Thanks, Ray

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Warnings
by Tommy Grav 09 Oct '07

09 Oct '07

How can I get the line number of where a numpy warning message is envoked in my code? Cheers Tommy

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Install Numpy with Lapack library -- compiling error on solaris 9
by danielhuang 09 Oct '07

09 Oct '07

Hi, I am trying to install numpy with lapack/altas library support and got following error on a solaris 9 box. http://www.scipy.org/Download The error I got during compiling is as following: ********** ATL_dset 0x1494 /usr/local/lib/atlas/libatlas.a(ATL_zCtrsmKL.o) ATL_dset 0x14ac /usr/local/lib/atlas/libatlas.a(ATL_zCtrsmKL.o) ATL_dset 0xdec /usr/local/lib/atlas/libatlas.a(ATL_zCtrsmKR.o) ATL_dset 0xe04 /usr/local/lib/atlas/libatlas.a(ATL_zCtrsmKR.o) ATL_dset_xp0yp0aXbX 0xd4 /usr/local/lib/atlas/libatlas.a(ATL_dset.o) ld: fatal: relocations remain against allocatable but non-writable sectionscollect2: ld returned 1 exit status error: Command "gcc -shared build/temp.solaris-2.9-sun4u-2.5/numpy/core/blasdot/_dotblas.o -L/usr/local/lib/atlas -lptf77blas -lptcblas -latlas -o build/lib.sol aris-2.9-sun4u-2.5/numpy/core/_dotblas.so" failed with exit status 1 *********** I am using gcc 3.4.6, any one has insight what might cause this error ? thanks a lot. - Daniel

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numpy/Windows shared arrays between processes?
by Ray S 09 Oct '07

09 Oct '07

Is anyone sharing arrays between processes on Windows? I tried compiling the posh sources (once, so far) with the new MS toolkit and failed... What other solutions are in use? Have a second process create an array view from an address would suffice for this particular purpose. I could pass the address as a parameter of the second process's argv. I've also tried things like pb=pythonapi.PyBuffer_FromReadWriteMemory(9508824, 9*sizeof(c_int)) N.frombuffer(pb, N.int32) which fails since pb is and int. What are my options? Ray Schumacher

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Convert array type
by Adam Mercer 08 Oct '07

08 Oct '07

Hi I am fairly new to using numpy and am running into a problem regarding the type of an array. The array in question is created using the following code: values = array(wavearray.split()) where wavearray is a string containing a series of floats separated by white space, it appears that the individual elements of the values array are strings, where I need them to be floats. How can I ensure that the individual elements of the values array are floats, not strings? I have tried using values = array(wavearray.split(), dtype=float) but that results in the error: ValueError: setting an array element with a sequence. Cheers Adam

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dot product not behaving as expected
by Robin 08 Oct '07

08 Oct '07

Hi, I have a problem using numpy.dot, see below: In [151]: m=5 In [152]: n=5 In [153]: x=(m*ones((1,5)))**arange(0,n) In [154]: y=test.order_length[::-1] In [155]: x Out[155]: array([[ 1., 5., 25., 125., 625.]]) In [156]: y Out[156]: array([[ 1024.], [ 1280.], [ 640.], [ 160.], [ 20.]]) In [157]: numpy.dot(x,y) Out[157]: array([[ 640000.]]) In [158]: sum(x*y.T) Out[158]: 55924.0 Am I missing something? Thanks, Robin

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Iterate over all 1-dim views
by Neal Becker 08 Oct '07

08 Oct '07

Suppose I have a function F(), which is defined for 1-dim arguments. If the user passes an n>1 dim array, I want to apply F to each 1-dim view. For example, for a 2-d array, apply F to each row and return a 2-d result. For a 3-d array, select each 2-d subarray and see above. Return 3-d result. Any suggestions on how to code something like this in numpy?

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Memory leak in vectorize ?
by Cyrille Rosset 08 Oct '07

08 Oct '07

Hello, the following code seems to create a memory leak in Python. (around 230 MB). Any ideas what's wrong ? I'm using python 2.5 and numpy 1.0.3 ------------------- def toto(x): return x**2 tutu=vectorize(toto) Nbins=10000 for i in xrange(1000): c=tutu(arange(Nbins)) ------------------- Thanks, Cyrille.

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Python Magazine
by Christopher Barker 08 Oct '07

08 Oct '07

Hey folks, There is a new Python Magazine out there: http://www.pythonmagazine.com/ Let's get a numpy article in there! NOTE: I have nothing to do with the production of the magazine, I'd just like to have it be a success so I can read it. -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker(a)noaa.gov

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Interested in adding new data type
by Neal Becker 07 Oct '07

07 Oct '07

I'm interested in experimenting with adding complex<int> data type. I have "Guide to Numpy". I'm looking at section 15.3. It looks like the first thing is a PyArray_Desc. There doesn't seem to be much info on what needs to go in this. Does anyone have any examples I could look at?

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