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 <ezi...@gmail.com> 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 <thomas.p.kra...@gmail.com> 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 <ralf.gomm...@gmail.com> >> 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 >>> NumPy-Discussion@scipy.org >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
