Mailman 3 October 2013 - NumPy-Discussion

Redirecting f2py output to a logfile (when called via distutils)
by David Ketcheson 23 Oct '13

23 Oct '13

In Clawpack, we use numpy.distutils to handle compilation and wrapping of Fortran source files via f2py. This generates a huge amount of output (warnings generated by f2py in intermediate steps) that (it seems) can safely be ignored. However, it's problematic to have pages of warnings fly by whenever a user installs the package. I would like to redirect this output to a log file. I have tried adding sys.stdout = open('install.log', 'w') in the setup.py file. This redirects some of the output, but not all of it. Below I've pasted an example of output that still prints to the terminal. How can I force all of this output to go into a log file and not be printed to the screen? An example setup.py file is here: https://github.com/clawpack/pyclaw/blob/master/src/pyclaw/setup.py Some example output that I can't redirect is here: In file included from > build/src.macosx-10.5-x86_64-2.7/clawpack/riemann/euler_4wave_2Dmodule.c:18: > > In file included from > build/src.macosx-10.5-x86_64-2.7/fortranobject.h:13: > > In file included from > /Users/ketch/anaconda/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:15: > > In file included from > /Users/ketch/anaconda/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:17: > > In file included from > /Users/ketch/anaconda/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1728: > > > /Users/ketch/anaconda/lib/python2.7/site-packages/numpy/core/include/numpy/npy_deprecated_api.h:11:2: > warning: "Using deprecated NumPy API, disable it by #defining > NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings] > > #warning "Using deprecated NumPy API, disable it by #defining > NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" > > ^ > > > build/src.macosx-10.5-x86_64-2.7/clawpack/riemann/euler_4wave_2Dmodule.c:111:12: > warning: unused function 'f2py_size' [-Wunused-function] > > static int f2py_size(PyArrayObject* var, ...) > > ^ > > 2 warnings generated. > > clawpack/riemann/src/rpn2_euler_4wave.f90:2.59: > > > > subroutine > rpn2(ixy,maxm,meqn,mwaves,maux,mbc,mx,ql,qr,auxl,auxr,wave,s,amdq,ap > > 1 > > Warning: Unused dummy argument 'auxl' at (1) > > clawpack/riemann/src/rpn2_euler_4wave.f90:2.64: > > > > subroutine > rpn2(ixy,maxm,meqn,mwaves,maux,mbc,mx,ql,qr,auxl,auxr,wave,s,amdq,ap > > 1 > Warning: Unused dummy argument 'auxr' at (1) > There is a LOT more of it, of course.

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Numpy 1.8.0 release
by Charles R Harris 22 Oct '13

22 Oct '13

Hi All, I'm planning on releasing Numpy 1.8.0 next weekend. There have been a few minor fixes since 1.8.0rc2, but nothing that I think warrants another rc release. Please make sure to test the 1.8.0rc2 or maintenance/1.8.x branch with your code, for after next weekend it will be too late. Chuck

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Contiguous memory zone with C API
by Marc.Poinot＠onera.fr 22 Oct '13

22 Oct '13

Hi all, I try to change my old C API numpy code to the 'new' API. I used to hack some internal stuff in Numpy (yes it's bad...) and I wonder now how to change it. Let's take an example: I have ocount numpy arrays with data allocated elsewhere than numpy, the data pointer of the PyArrayObject is set with the malloc'd zone. Now I select one of these array to be the memory base for all of them, then I realloc each data pointer to make sure the ocount of them have a contiguous zone. The code is now 'rejected' by the new API, how can I do that without hacking into the PyArray_Object? first=(PyArrayObject*)context->ctg_obj[0]; psize=PyArray_NBYTES(first); for (j=1;j<ocount;j++) { current=(PyArrayObject*)context->ctg_obj[j]; tsize=PyArray_NBYTES(current); psize+=tsize; ((PyArrayObject*)first)->data=realloc(PyArray_DATA(first),psize); /* *** how to do that with the API ? */ memcpy(PyArray_DATA(first)+psize-tsize,PyArray_DATA(current),tsize); free(PyArray_DATA(current)); ((PyArrayObject*)current)->data=PyArray_DATA(first)+psize-tsize; } I use that trick to make sure that separate numpy each representing a coordinate of a vector can be gather in a single array. I've had a look at PyArray_resize but it requires a own_data flag which I do not have... Any hint, remark? -- -- ---------------------------------------------------------------------------- -- Marc POINOT [ONERA/DSNA] Tel:+33.1.46.73.42.84 Fax:+33.1.46.73.41.66 -- Avertissement/disclaimer http://www.onera.fr/en/emails-terms -- ---------------------------------------------------------------------------- --

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Is there a contributors agreement for numypy?
by Mounir E. Bsaibes 21 Oct '13

21 Oct '13

I am checking whether there is a Contributor's agreement that new contributors have to sign. Or, whether there was one for the documentation marathon. Does anyone knows the answer to this question or can point me to where I can possibly find the answer? Thanks, Mounir

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Porting to the new C-API (1.7)
by Mads Ipsen 21 Oct '13

21 Oct '13

Hi, I've been using the numpy-1.6 C-API as part of a large C++ based OpenGL application. The C++ classes are exposed in Python by using SWIG, and utilize numpy arrays both as inputs to methods and method return values to the Python caller. To enable numpy in the SWIG generated Python module, the SWIG generated C++ file define #define PY_ARRAY_UNIQUE_SYMBOL PyArray_API whereas all other C++ files that need access to the numpy C-API contain #define NO_IMPORT_ARRAY #include "numpy/arrayobject.h" I have now updated to numpy-1.7, and receive warnings of the form #warning "Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" This is basically fine with me, and I don't mind doing an update of my code to the new C-API. I have a few questions though: 1) Since I am apparently using the old API, where can I find a list of the deprecated things I use? That would make the upgrade easier. 2) Do I still have to use the PY_ARRAY_UNIQUE_SYMBOL approach when using the new C-API. 3) According to some websites you can do something like #define PY_ARRAY_UNIQUE_SYMBOL PyArrayXXX This puzzles me a bit. Is there a doc somewhere where this whole thing is explained in detail. I must admit, its somewhat hard to grasp what's going on. Best regards, Mads -- +-----------------------------------------------------+ | Mads Ipsen | +----------------------+------------------------------+ | Gåsebæksvej 7, 4. tv | | | DK-2500 Valby | phone: +45-29716388 | | Denmark | email: mads.ipsen(a)gmail.com | +----------------------+------------------------------+

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ANN: scikit-image 0.9 release
by Stéfan van der Walt 21 Oct '13

21 Oct '13

We're happy to announce the release of scikit-image v0.9.0! scikit-image is an image processing toolbox for SciPy that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. For more information, examples, and documentation, please visit our website: http://scikit-image.org New Features ------------ `scikit-image` now runs without translation under both Python 2 and 3. In addition to several bug fixes, speed improvements and examples, the 204 pull requests merged for this release include the following new features (PR number in brackets): Segmentation: - 3D support in SLIC segmentation (#546) - SLIC voxel spacing (#719) - Generalized anisotropic spacing support for random_walker (#775) - Yen threshold method (#686) Transforms and filters: - SART algorithm for tomography reconstruction (#584) - Gabor filters (#371) - Hough transform for ellipses (#597) - Fast resampling of nD arrays (#511) - Rotation axis center for Radon transforms with inverses. (#654) - Reconstruction circle in inverse Radon transform (#567) - Pixelwise image adjustment curves and methods (#505) Feature detection: - [experimental API] BRIEF feature descriptor (#591) - [experimental API] Censure (STAR) Feature Detector (#668) - Octagon structural element (#669) - Add non rotation invariant uniform LBPs (#704) Color and noise: - Add deltaE color comparison and lab2lch conversion (#665) - Isotropic denoising (#653) - Generator to add various types of random noise to images (#625) - Color deconvolution for immunohistochemical images (#441) - Color label visualization (#485) Drawing and visualization: - Wu's anti-aliased circle, line, bezier curve (#709) - Linked image viewers and docked plugins (#575) - Rotated ellipse + bezier curve drawing (#510) - PySide & PyQt4 compatibility in skimage-viewer (#551) Other: - Python 3 support without 2to3. (#620) - 3D Marching Cubes (#469) - Line, Circle, Ellipse total least squares fitting and RANSAC algorithm (#440) - N-dimensional array padding (#577) - Add a wrapper around `scipy.ndimage.gaussian_filter` with useful default behaviors. (#712) - Predefined structuring elements for 3D morphology (#484) API changes ----------- The following backward-incompatible API changes were made between 0.8 and 0.9: - No longer wrap ``imread`` output in an ``Image`` class - Change default value of `sigma` parameter in ``skimage.segmentation.slic`` to 0 - ``hough_circle`` now returns a stack of arrays that are the same size as the input image. Set the ``full_output`` flag to True for the old behavior. - The following functions were deprecated over two releases: `skimage.filter.denoise_tv_chambolle`, `skimage.morphology.is_local_maximum`, `skimage.transform.hough`, `skimage.transform.probabilistic_hough`,`skimage.transform.hough_peaks`. Their functionality still exists, but under different names. Contributors to this release ---------------------------- This release was made possible by the collaborative efforts of many contributors, both new and old. They are listed in alphabetical order by surname: - Ankit Agrawal - K.-Michael Aye - Chris Beaumont - François Boulogne - Luis Pedro Coelho - Marianne Corvellec - Olivier Debeir - Ferdinand Deger - Kemal Eren - Jostein Bø Fløystad - Christoph Gohlke - Emmanuelle Gouillart - Christian Horea - Thouis (Ray) Jones - Almar Klein - Xavier Moles Lopez - Alexis Mignon - Juan Nunez-Iglesias - Zachary Pincus - Nicolas Pinto - Davin Potts - Malcolm Reynolds - Umesh Sharma - Johannes Schönberger - Chintak Sheth - Kirill Shklovsky - Steven Silvester - Matt Terry - Riaan van den Dool - Stéfan van der Walt - Josh Warner - Adam Wisniewski - Yang Zetian - Tony S Yu

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pull request: organization of the npyio.recfromcsv function arguments
by Yaron de Leeuw 20 Oct '13

20 Oct '13

Hi all. I've submitted a pull request to organise the recfromcsv arguments. It closes a known bug, and is a bit more sane in my opinion. I would appreciate your feedback. https://github.com/numpy/numpy/pull/3830 Thank you, Yaron

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Preparing for 1.7.2 release
by Charles R Harris 20 Oct '13

20 Oct '13

Hi All, After the release of Numpy 1.8.0 there will be a point release of the long term stable branch, Numpy 1.7.2. There have been some 86 non-merge commits since 1.7.1 was released, see the attached list. If anyone thinks something is missing and needs a backport, please reply on the list. Chuck

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OT: How are SVG data converted into curves
by David Goldsmith 19 Oct '13

19 Oct '13

Does anyone on this list know how Scalable Vector Graphics C, S, etc. command data are translated into curves (i.e., pixel maps) and might you be willing to answer some questions off-list? Thanks! DG PS: I receive numpy-discussion in digest mode, so if you "qualify," please reply directly to my email. Thanks again.

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switching from Numeric to numpy
by john fernando 18 Oct '13

18 Oct '13

I have the following C code which is an extension to my python code. The python and C code use #include <Numeric/arrayobject.h> what is the equivalent I can use in numpy that causes the minimum code change? I did look through the old messages but didn't really find the answer-any help to a novice just starting out in numpy/python/C is much appreciated. ____________________________________________________________ FREE ONLINE PHOTOSHARING - Share your photos online with your friends and family! Visit http://www.inbox.com/photosharing to find out more!

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