Mailman 3 April 2008 - NumPy-Discussion

failure building numpy using icc
by Glen W. Mabey 15 May '08

15 May '08

Hello, I'm using svn numpy and get the following error upon executing /usr/local/bin/python2.5 setup.py config --noisy --cc=/opt/intel/cce/10.0.025/bin/icc --compiler=intel --fcompiler=intel build_clib build_ext I see: conv_template:> build/src.linux-x86_64-2.5/numpy/core/src/scalartypes.inc Traceback (most recent call last): File "setup.py", line 96, in <module> setup_package() File "setup.py", line 89, in setup_package configuration=configuration ) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/core.py", line 184, in setup return old_setup(**new_attr) File "/usr/local/lib/python2.5/distutils/core.py", line 151, in setup dist.run_commands() File "/usr/local/lib/python2.5/distutils/dist.py", line 974, in run_commands self.run_command(cmd) File "/usr/local/lib/python2.5/distutils/dist.py", line 994, in run_command cmd_obj.run() File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/command/build_ext.py", line 56, in run self.run_command('build_src') File "/usr/local/lib/python2.5/distutils/cmd.py", line 333, in run_command self.distribution.run_command(command) File "/usr/local/lib/python2.5/distutils/dist.py", line 994, in run_command cmd_obj.run() File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/command/build_src.py", line 130, in run self.build_sources() File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/command/build_src.py", line 147, in build_sources self.build_extension_sources(ext) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/command/build_src.py", line 252, in build_extension_sources sources = self.template_sources(sources, ext) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/command/build_src.py", line 359, in template_sources outstr = process_c_file(source) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/conv_template.py", line 185, in process_file % (sourcefile, process_str(''.join(lines)))) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/conv_template.py", line 150, in process_str newstr[sub[0]:sub[1]], sub[4]) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/conv_template.py", line 117, in expand_sub % (line, template_re.sub(namerepl, substr))) File "/home/gmabey/src/DiamondBack/Diamondback/src/numpy-20080228_svn/numpy/distutils/conv_template.py", line 113, in namerepl return names[name][thissub[0]] KeyError: 'PREFIX' And I do not see any errors when building the same svn version with gcc (on a different machine). I've unsuccessfully tried to follow that backtrace of functions to figure out exactly what is going on. Any hints/suggestions? Thanks, Glen Mabey

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very simple iteration question.
by a g 03 May '08

03 May '08

Hi. This is a very basic question, sorry if it's irritating. If i didn't find the answer written already somewhere on the site, please point me to it. That'd be great. OK: how do i iterate over an axis other than 0? I have a 3D array of data[year, week, location]. I want to iterate over each year at each location and run a series of stats on the columns (on the 52 weeks in a particular year at a particular location). 'for years in data:' will get the first one, but then how do i not iterate over the 1 axis and iterate over the 2 axis instead? thanks, alex.

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a possible way to implement a plogin system
by Lisandro Dalcin 03 May '08

03 May '08

David, in order to put clear what I was proposing to you in previous mail regarding to implementing plugin systems for numpy, please take a look at the attached tarball. The plugins are in charge of implementing the action of generic foo() and bar() functions in C. The example actually implements two different plugins in Cython. There is also an include file with some support declarations and some macro definitions wrap_foo and wrap_bar Next, in mymodule.pyx, I define python side foo() and bar() functions (calling funtins pointers in a struct via the macros wrap_xxx) and a use() for selecting the plugin at runtime. Finally, the test.py script is pure python code showing all this in action. If you want to give a try, then install Cython, next do 'make', and finally 'python test.py' Please note that I've implemented this is Cython just for convenience, it does not actually depend in any special Cython feature, and could be translated to pure C code with Python C/API calls. IMHO, this is the easier and cleaner way to deal inside python with plugins written in low-level C. It does not depend explicitely on 'dlopen' stuff from your side. Now tell me. What is in your mind that this is not general/robust enough as to have to explicitely deal with dlopen? It even works on systems with no dynload, provided that all is put inside the python executable. -- Lisandro Dalcín --------------- Centro Internacional de Métodos Computacionales en Ingeniería (CIMEC) Instituto de Desarrollo Tecnológico para la Industria Química (INTEC) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) PTLC - Güemes 3450, (3000) Santa Fe, Argentina Tel/Fax: +54-(0)342-451.1594

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types as functions convert 1 elm arrays to scalars
by Hoyt Koepke 01 May '08

01 May '08

Hello, I have a quick question that I'm hoping will improve my numpy understanding. I noticed some behavior when using float64 to convert a matrix type that I didn't expect: In [35]: b1 = array([1.0]) In [36]: float64(b1) Out[36]: 1.0 In [37]: b2 = array([1.0, 2.0]) In [38]: float64(b2) Out[38]: array([ 1., 2.]) I didn't expect calling float64 would convert b1 to a scalar. Seems like an inconsistency. I assume this is intentional, as someone would have noticed it a long time ago if not, so could someone explain the reasoning behind it? (or point me to a source that will help?) Thanks! --Hoyt -- +++++++++++++++++++++++++++++++++++ Hoyt Koepke UBC Department of Computer Science http://www.cs.ubc.ca/~hoytak/ hoytak(a)gmail.com +++++++++++++++++++++++++++++++++++

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recarray fun
by Christopher Barker 01 May '08

01 May '08

Hi folks, Someone on the wxPython list posted a nifty recarray example that I don't quite understand. The idea is to have an array for an RGBA image: rgbarec = numpy.dtype({'r':(numpy.uint8,0), 'g':(numpy.uint8,1), 'b':(numpy.uint8,2), 'a':(numpy.uint8,3)}) A = numpy.zeros(shape, dtype=(numpy.uint32, rgbarec) ) what I don't understand is having BOTH numpy.uint32 and rgbrec as the dtype. How does that work? Actually, with a bit of testing, it's pretty cool -- if you index like: A[i,j] ==> uint32 A['r'][i,j] ==> uint8 pretty cool really. it seems that numpy is treating it as both a recarray and a regular uint32 array, which makes some sense, but I'm still confused by the semantics. also: >>> A array([[4278190080, ... [4278190080, 4278190080, 4278190080, 4278190080, 4278190080]], dtype=uint32) but: >>> A.dtype dtype(('>u4', [('r', '|u1'), ('g', '|u1'), ('b', '|u1'), ('a', '|u1')])) so what is the dtype? Also, I see advantages and disadvantages to either way. If you do: A = numpy.zeros(shape, dtype=(numpy.uint32, rgbarec) ) then you can do: A[i,j]['r'] to get the red value of a pixel A[i,j] = (red, green, blue, alpha) to set a pixel A[:,:] = (red, green, blue, alpha) to make the whole image one color With the "dual dtype" approach: A = numpy.zeros(shape, dtype=(numpy.uint32, rgbarec) ) You need to set the pixels separately: A['r'][i,j] = red B['r'][i,j] = green ... or construct uint32 values: C = numpy.uint32(red) C += numpy.uint32(green) << 8 C += numpy.uint32(blue) << 16 Which is really ugly! (and I may not even have it right!). Is there a better way? One more idea -- is there a way to have two arrays, each with a different dtype, that point to the same data? maybe: RGBImage = numpy.zeros(shape, dtype=rgbarec ) IntImage = RGBImage.view() IntImage.dtype = numpy.uint32 That way you could work with it either way, whichever was easier in the context. So -- what are folks' thoughts about how best to deal with images as numpy arrays? (I'll put it in a Wiki page if I get some good comments) -Chris -- 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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numpy release
by Ondrej Certik 30 Apr '08

30 Apr '08

Hi Jarrod, any news with the 1.0.5? If you have same prerelease, I'd like to test it. Debian has just moved from python2.4 to python2.5 yesterday, so I'd like to test numpy in advance, I am sure there will be some issues to fix. Ondrej

22 152

numpy.ma question
by Charles Doutriaux 30 Apr '08

30 Apr '08

Hello i have a quick question about MA ans scalar the following works: import numpy.ma as MA a0= MA.array(0)/1 a1= MA.array((0,0))/1 but not: import numpy.ma as MA a0= MA.array(0)/0 a1= MA.array((0,0))/0 Is that a bug ? I'm using numpy 1.0.5.dev4958 and also whats in trunk right now (1.1.0.dev5113) C.

2 3

oldnumeric.MA behaviour broken ?
by Charles Doutriaux 30 Apr '08

30 Apr '08

HI, import numpy.oldnumeric.ma as MA a0= MA.array(0)/0 sh0=list(a0.shape) sh0.insert(0,1) b0=MA.resize(a0,sh0) Does not work anymore, I believe it used to work It does works using numpy.ma (but i can't subclass these yet...) C.

1 0

[ANN] EuroSciPy Abstracts Deadline Reminder
by Travis Vaught 30 Apr '08

30 Apr '08

Greetings, Just a reminder: the abstracts for the EuroSciPy Conference in Leipzig are due by midnight tonight (CST, US [UTC -6]) April, 30. If you'd like to present, please submit your abstract as a PDF, MS Word or plain text file to euroabstracts(a)scipy.org. For more information on the EuroSciPy Conference, please see: http://www.scipy.org/EuroSciPy2008

1 0

should outer take an output argument?
by Alan G Isaac 30 Apr '08

30 Apr '08

As I was looking at Bill's conjugate gradient posting, I found myself wondering if there would be a payoff to an output argument for ``numpy.outer``. (It is fairly natural to repeatedly recreate the outer product of the adjusted residuals, which is only needed during a single iteration.) Cheers, Alan Isaac

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