Hi Egor - I just read through your blog post, thanks for describing those new list-of-array type maps. It helps to see your motivation and some examples. I'll keep it in mind if I ever have a list of large arrays to process for which creating a numpy array first is not desirable. - Tom
On Tue, Jun 18, 2013 at 6:36 AM, Egor Zindy <[email protected]> wrote: > Dear all, > > after some code clean-up / testing and a few additions, I've now sent > a pull request to numpy:master (#3451). > https://github.com/numpy/numpy/pull/3451 > > I also made a blog post to explain the new typemaps I would like included: > > http://egorzindy.blogspot.co.uk/2013/06/new-numpyi-typemaps-for-working-with.html > > Any comments appreciated. > > Kind regards, > Egor > > > On 9 June 2013 09:20, Egor Zindy <[email protected]> wrote: > > Thanks Tom, > > > > before we ship it, I'd love to have some feedback on the new ARGOUT_VIEWM > > type. > > > > I used to create my managed arrays using > > > > PyObject* cap = PyCObject_FromVoidPtr((void*)(*$1), free); > > > > but since this function is deprecated, and because of Bill's background > work > > to bring numpy.i up to date, I now use capsules for this: > > > > PyObject* cap = PyCapsule_New((void*)(*$1), SWIGPY_CAPSULE_NAME, > > free_cap); > > > > ... I'll admit it took longer than expected to get this right. > > > > Would you mind testing my latest numpy.i changes hosted on github? > > https://github.com/zindy/numpy/tree/numpy-swig/doc/swig > > > > It's great that you are testing on a mac, I don't have one to test on > yet. > > > > > >> It worked fine, although I use only a fraction of the capabilities that > it > >> includes. > > > > Same here, but overall, it should be quit easy to choose the data type > you > > need. Narrow down it down to a type between IN_ARRAY / INPLACE_ / > ARGOUT_ / > > ARGOUT_VIEW/VIEWM > > http://wiki.scipy.org/Cookbook/SWIG_NumPy_examples > > http://wiki.scipy.org/Cookbook/SWIG_Memory_Deallocation (I'll update > these > > when I have a sec) > > > > ... and choose the number of dimensions you need (1/2/3/4). I can't > comment > > on the Fortran arrays data types though as I don't use them. > > > > Also I've introduced a few of my more esoteric data types in this week, > but > > I have no idea how popular they will be. If you ever need to speed-up: > > > > a = numpy.ones((1024,1024),numpy.uint8) > > la = [a]*100 > > b = numpy.mean(numpy.array(la,float),axis=0).astype(numpy.uint8) > > > > I have just the right type for that :) > > DATA_TYPE** IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3 > > > > Kind regards, > > Egor > > > > > > On 9 June 2013 03:33, Tom Krauss <[email protected]> wrote: > >> > >> Hi folks, > >> > >> I just downloaded Bill's numpy.i at commit 4dcb0679, and tried it out a > >> bit on some of my personal projects. It worked fine, although I use > only a > >> fraction of the capabilities that it includes. > >> > >> And, it made the warning go away! > >> > >> I used to get this warning > >> > >> g++ -g -fPIC -c simple_wrap.cpp -I/usr/include/python2.7 > >> > -I/Users/tkrauss/projects/dev_env/lib/python2.7/site-packages/numpy-1.8.0.dev_f2f0ac0_20120725-py2.7-macosx-10.8-x86_64.egg/numpy/core/include > >> In file included from > >> > /Users/tkrauss/projects/dev_env/lib/python2.7/site-packages/numpy-1.8.0.dev_f2f0ac0_20120725-py2.7-macosx-10.8-x86_64.egg/numpy/core/include/numpy/ndarraytypes.h:1722, > >> from > >> > /Users/tkrauss/projects/dev_env/lib/python2.7/site-packages/numpy-1.8.0.dev_f2f0ac0_20120725-py2.7-macosx-10.8-x86_64.egg/numpy/core/include/numpy/ndarrayobject.h:17, > >> from > >> > /Users/tkrauss/projects/dev_env/lib/python2.7/site-packages/numpy-1.8.0.dev_f2f0ac0_20120725-py2.7-macosx-10.8-x86_64.egg/numpy/core/include/numpy/arrayobject.h:15, > >> from simple_wrap.cpp:3062: > >> > >> > /Users/tkrauss/projects/dev_env/lib/python2.7/site-packages/numpy-1.8.0.dev_f2f0ac0_20120725-py2.7-macosx-10.8-x86_64.egg/numpy/core/include/numpy/npy_deprecated_api.h:11:2: > >> warning: #warning "Using deprecated NumPy API, disable it by #defining > >> NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" > >> > >> but not with this version. > >> > >> You can see which version of numpy I am using there, and that I am on > Mac > >> OS X 10.8. (10.8.4 specifically) Python 2.7.2 > >> > >> I'd say SHIP IT! > >> > >> Nice work, thanks for all your work on numpy and numpy.i. > >> > >> - Tom Krauss > >> > >> > >> > >> On Tue, Jun 4, 2013 at 3:13 PM, Ralf Gommers <[email protected]> > >> wrote: > >>> > >>> Hi, > >>> > >>> If you're using or are very familiar with SWIG and the numpy.i > interface > >>> to it, please help to test and/or review > >>> https://github.com/numpy/numpy/pull/3148. It's a fairly major update > to > >>> numpy.i by Bill Spotz, containing the following: > >>> - support for 4D arrays and memory managed output arguments > >>> - rework for the deprecated API's in numpy 1.6 and 1.7 > >>> - a bug fix in a 3D typemap > >>> - documentation improvements > >>> > >>> It would be good to have this merged before branching 1.8.x. Not many > of > >>> the regular reviewers of numpy PRs are familiar with numpy.i, > therefore help > >>> would be much appreciated. > >>> > >>> Thanks, > >>> Ralf > >>> > >>> > >>> _______________________________________________ > >>> NumPy-Discussion mailing list > >>> [email protected] > >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion > >>> > >> > >> > >> _______________________________________________ > >> NumPy-Discussion mailing list > >> [email protected] > >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > >> > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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