Mailman 3 January 2012 - NumPy-Discussion

ANN: Numexpr 2.0 released
by Francesc Alted Jan. 8, 2012

Jan. 8, 2012

======================== Announcing Numexpr 2.0 ======================== Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It wears multi-threaded capabilities, as well as support for Intel's VML library, which allows for squeezing the last drop of performance out of your multi-core processors. What's new ========== This version comes with support for the new iterator in NumPy (introduced in NumPy 1.6), allowing for improved performance in practically all the scenarios (the exception being very small arrays), and most specially for operations implying broadcasting, fortran-ordered or non-native byte orderings. The carefully crafted mix of the new NumPy iterator and direct access to data buffers turned out to be so powerful and flexible, that the internal virtual machine has been completely revamped around this combination. The drawback is that you will need NumPy >= 1.6 to run numexpr 2.0. However, NumPy 1.6 has been released more than 6 months ago now, so we think this is a good time for taking advantage of it. Many thanks to Mark Wiebe for such an important contribution! For some benchmarks on the new virtual machine, see: http://code.google.com/p/numexpr/wiki/NewVM Also, Gaëtan de Menten contributed important bug fixes, code cleanup as well as speed enhancements. Francesc Alted contributed some fixes, and added compatibility code with existing applications (PyTables) too. In case you want to know more in detail what has changed in this version, see: http://code.google.com/p/numexpr/wiki/ReleaseNotes or have a look at RELEASE_NOTES.txt in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ You can get the packages from PyPI as well: http://pypi.python.org/pypi/numexpr Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted

3 2

numpy 1.7.0 release?
by Ralf Gommers Jan. 7, 2012

Jan. 7, 2012

Hi all, It's been a little over 6 months since the release of 1.6.0 and the NA debate has quieted down, so I'd like to ask your opinion on the timing of 1.7.0. It looks to me like we have a healthy amount of bug fixes and small improvements, plus three larger chucks of work: - datetime - NA - Bento support My impression is that both datetime and NA are releasable, but should be labeled "tech preview" or something similar, because they may still see significant changes. Please correct me if I'm wrong. There's still some maintenance work to do and pull requests to merge, but a beta release by Christmas should be feasible. What do you all think? Cheers, Ralf

9 19

PyInt and Numpy's int64 conversion
by xantares 09 Jan. 6, 2012

Jan. 6, 2012

Hi, I'm using Numpy from the C python api side while tweaking my SWIG interface to work with numpy array types. I want to convert a numpy array of integers (whose elements are numpy's 'int64') The problem is that it this int64 type is not compatible with the standard python integer type: I cannot use PyInt_Check, and PyInt_AsUnsignedLongMask to check and convert from int64: basically PyInt_Check returns false. I checked the numpy config header and npy_int64 does have a size of 8o, which should be the same as int on my x86_64. What is the correct way to do that ? I checked for a Int64_Check function and didn't find any in numpy headers. Regards, x.

3 6

what is the best way to pass c, c++ array to numpy in cython?
by Wonjun, Choi Jan. 5, 2012

Jan. 5, 2012

hello, what is the best way to pass c, c++ array to numpy in cython? or what is the best way to pass fortran multi-dimensional array to numpy in cython? Wonjun, Choi

3 5

Enum type
by Ognen Duzlevski Jan. 3, 2012

Jan. 3, 2012

Hello, I am playing with adding an enum dtype to numpy (to get my feet wet in numpy really). I have looked at the https://github.com/martinling/numpy_quaternion and I feel comfortable with my understanding of adding a simple type to numpy in technical terms. I am mostly a C programmer and have programmed in Python but not at the level where my code wcould be considered "pretty" or maybe even "pythonic". I know enums from C and have browsed around a few python enum implementations online. Most of them use hash tables or lists to associate names to numbers - these approaches just feel "heavy" to me. What would be a proper "numpy approach" to this? I am looking mostly for direction and advice as I would like to do the work myself :-) Any input appreciated :-) Ognen

6 8

numpy dgemm link error
by Amos Anderson Jan. 3, 2012

Jan. 3, 2012

Hello -- I've been having some problems building numpy. The first problem I had "error: unrecognizable insn", I was able to fix by following these instructions: http://www.mail-archive.com/numpy-discussion@scipy.org/msg34238.html > Could you try the following, at line 38, to add the following: > > #define EINSUM_USE_SSE1 0 > #define EINSUM_USE_SSE2 0 But now when I compile, I get a linker error against dgemm. I've pasted the full build output below. Amos. Running from numpy source directory.non-existing path in 'numpy/distutils': 'site.cfg' usage: svnversion [OPTIONS] WC_PATH [TRAIL_URL] Produce a compact "version number" for the working copy path WC_PATH. TRAIL_URL is the trailing portion of the URL used to determine if WC_PATH itself is switched (detection of switches within WC_PATH does not rely on TRAIL_URL). The version number is written to standard output. For example: $ svnversion . /repos/svn/trunk 4168 The version number will be a single number if the working copy is single revision, unmodified, not switched and with an URL that matches the TRAIL_URL argument. If the working copy is unusual the version number will be more complex: 4123:4168 mixed revision working copy 4168M modified working copy 4123S switched working copy 4123:4168MS mixed revision, modified, switched working copy If invoked on a directory that is not a working copy, an exported directory say, the program will output "exported". Valid options: -n [--no-newline] : do not output the trailing newline -c [--committed] : last changed rather than current revisions --version : show version information F2PY Version 2 blas_opt_info: blas_mkl_info: libraries mkl,vml,guide not found in /home/amosa/triad/tools/python/lib libraries mkl,vml,guide not found in /usr/local/lib64 libraries mkl,vml,guide not found in /usr/local/lib libraries mkl,vml,guide not found in /usr/lib64 libraries mkl,vml,guide not found in /usr/lib NOT AVAILABLE atlas_blas_threads_info: Setting PTATLAS=ATLAS libraries ptf77blas,ptcblas,atlas not found in /home/amosa/triad/tools/python/lib libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib64 libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib libraries ptf77blas,ptcblas,atlas not found in /usr/lib64 libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2 libraries ptf77blas,ptcblas,atlas not found in /usr/lib NOT AVAILABLE atlas_blas_info: libraries f77blas,cblas,atlas not found in /home/amosa/triad/tools/python/lib libraries f77blas,cblas,atlas not found in /usr/local/lib64 libraries f77blas,cblas,atlas not found in /usr/local/lib customize GnuFCompiler Found executable /usr/bin/g77 gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler using config compiling '_configtest.c': /* This file is generated from numpy/distutils/system_info.py */ void ATL_buildinfo(void); int main(void) { ATL_buildinfo(); return 0; } C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-c' gcc: _configtest.c gcc -pthread _configtest.o -L/usr/lib64 -lf77blas -lcblas -latlas -o _configtest ATLAS version 3.7.11 built by root on Mon Jun 5 10:14:12 EDT 2006: UNAME : Linux intel1.lsf.platform.com 2.6.9-34.ELsmp #1 SMP Fri Feb 24 16:56:28 EST 2006 x86_64 x86_64 x86_64 GNU/Linux INSTFLG : MMDEF : /export/madison/src/roll/hpc/BUILD/ATLAS/CONFIG/ARCHS/P4E64SSE3/gcc/gemm ARCHDEF : /export/madison/src/roll/hpc/BUILD/ATLAS/CONFIG/ARCHS/P4E64SSE3/gcc/misc F2CDEFS : -DAdd__ -DStringSunStyle CACHEEDGE: 393216 F77 : /usr/bin/g77, version GNU Fortran (GCC) 3.4.5 20051201 (Red Hat 3.4.5-2) F77FLAGS : -fomit-frame-pointer -O -m64 CC : /usr/bin/gcc, version gcc (GCC) 3.4.5 20051201 (Red Hat 3.4.5-2) CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops -m64 MCC : /usr/bin/gcc, version gcc (GCC) 3.4.5 20051201 (Red Hat 3.4.5-2) MCCFLAGS : -fomit-frame-pointer -O -m64 success! removing: _configtest.c _configtest.o _configtest FOUND: libraries = ['f77blas', 'cblas', 'atlas'] library_dirs = ['/usr/lib64'] language = c define_macros = [('ATLAS_INFO', '"\\"3.7.11\\""')] FOUND: libraries = ['f77blas', 'cblas', 'atlas'] library_dirs = ['/usr/lib64'] language = c define_macros = [('ATLAS_INFO', '"\\"3.7.11\\""')] usage: svnversion [OPTIONS] WC_PATH [TRAIL_URL] Produce a compact "version number" for the working copy path WC_PATH. TRAIL_URL is the trailing portion of the URL used to determine if WC_PATH itself is switched (detection of switches within WC_PATH does not rely on TRAIL_URL). The version number is written to standard output. For example: $ svnversion . /repos/svn/trunk 4168 The version number will be a single number if the working copy is single revision, unmodified, not switched and with an URL that matches the TRAIL_URL argument. If the working copy is unusual the version number will be more complex: 4123:4168 mixed revision working copy 4168M modified working copy 4123S switched working copy 4123:4168MS mixed revision, modified, switched working copy If invoked on a directory that is not a working copy, an exported directory say, the program will output "exported". Valid options: -n [--no-newline] : do not output the trailing newline -c [--committed] : last changed rather than current revisions --version : show version information lapack_opt_info: lapack_mkl_info: mkl_info: libraries mkl,vml,guide not found in /home/amosa/triad/tools/python/lib libraries mkl,vml,guide not found in /usr/local/lib64 libraries mkl,vml,guide not found in /usr/local/lib libraries mkl,vml,guide not found in /usr/lib64 libraries mkl,vml,guide not found in /usr/lib NOT AVAILABLE NOT AVAILABLE atlas_threads_info: Setting PTATLAS=ATLAS libraries ptf77blas,ptcblas,atlas not found in /home/amosa/triad/tools/python/lib libraries lapack_atlas not found in /home/amosa/triad/tools/python/lib libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib64 libraries lapack_atlas not found in /usr/local/lib64 libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/local/lib libraries ptf77blas,ptcblas,atlas not found in /usr/lib64 libraries lapack_atlas not found in /usr/lib64 libraries ptf77blas,ptcblas,atlas not found in /usr/lib/sse2 libraries lapack_atlas not found in /usr/lib/sse2 libraries ptf77blas,ptcblas,atlas not found in /usr/lib libraries lapack_atlas not found in /usr/lib numpy.distutils.system_info.atlas_threads_info NOT AVAILABLE atlas_info: libraries f77blas,cblas,atlas not found in /home/amosa/triad/tools/python/lib libraries lapack_atlas not found in /home/amosa/triad/tools/python/lib libraries f77blas,cblas,atlas not found in /usr/local/lib64 libraries lapack_atlas not found in /usr/local/lib64 libraries f77blas,cblas,atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/lib64 numpy.distutils.system_info.atlas_info FOUND: libraries = ['lapack', 'f77blas', 'cblas', 'atlas'] library_dirs = ['/usr/lib64'] language = f77 define_macros = [('ATLAS_INFO', '"\\"3.7.11\\""')] FOUND: libraries = ['lapack', 'f77blas', 'cblas', 'atlas'] library_dirs = ['/usr/lib64'] language = f77 define_macros = [('ATLAS_INFO', '"\\"3.7.11\\""')] running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building py_modules sources building library "npymath" sources customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler using config C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -c' gcc: _configtest.c gcc -pthread _configtest.o -o _configtest success! removing: _configtest.c _configtest.o _configtest C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -c' gcc: _configtest.c _configtest.c:1: warning: conflicting types for built-in function 'exp' gcc -pthread _configtest.o -o _configtest _configtest.o(.text+0x5): In function `main': /home/amosa/triad/tools/numpy/numpy-1.6.1/_configtest.c:6: undefined reference to `exp' collect2: ld returned 1 exit status _configtest.o(.text+0x5): In function `main': /home/amosa/triad/tools/numpy/numpy-1.6.1/_configtest.c:6: undefined reference to `exp' collect2: ld returned 1 exit status failure. removing: _configtest.c _configtest.o C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -c' gcc: _configtest.c _configtest.c:1: warning: conflicting types for built-in function 'exp' gcc -pthread _configtest.o -lm -o _configtest success! removing: _configtest.c _configtest.o _configtest building extension "numpy.core._sort" sources adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h' to sources. adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h' to sources. executing numpy/core/code_generators/generate_numpy_api.py adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h' to sources. numpy.core - nothing done with h_files = ['build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h'] building extension "numpy.core.multiarray" sources conv_template:> build/src.linux-x86_64-2.7/numpy/core/src/multiarray/scalartypes.c conv_template:> build/src.linux-x86_64-2.7/numpy/core/src/multiarray/arraytypes.c conv_template:> build/src.linux-x86_64-2.7/numpy/core/src/multiarray/nditer.c conv_template:> build/src.linux-x86_64-2.7/numpy/core/src/multiarray/lowlevel_strided_loops.c conv_template:> build/src.linux-x86_64-2.7/numpy/core/src/multiarray/einsum.c adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h' to sources. adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h' to sources. executing numpy/core/code_generators/generate_numpy_api.py adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h' to sources. numpy.core - nothing done with h_files = ['build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h'] building extension "numpy.core.umath" sources adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h' to sources. adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h' to sources. executing numpy/core/code_generators/generate_ufunc_api.py adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__ufunc_api.h' to sources. adding 'build/src.linux-x86_64-2.7/numpy/core/src/umath' to include_dirs. numpy.core - nothing done with h_files = ['build/src.linux-x86_64-2.7/numpy/core/src/umath/funcs.inc', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__ufunc_api.h'] building extension "numpy.core.scalarmath" sources adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h' to sources. adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h' to sources. executing numpy/core/code_generators/generate_numpy_api.py adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h' to sources. executing numpy/core/code_generators/generate_ufunc_api.py adding 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__ufunc_api.h' to sources. numpy.core - nothing done with h_files = ['build/src.linux-x86_64-2.7/numpy/core/include/numpy/config.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/_numpyconfig.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__multiarray_api.h', 'build/src.linux-x86_64-2.7/numpy/core/include/numpy/__ufunc_api.h'] building extension "numpy.core._dotblas" sources adding 'numpy/core/blasdot/_dotblas.c' to sources. building extension "numpy.core.umath_tests" sources building extension "numpy.core.multiarray_tests" sources building extension "numpy.lib._compiled_base" sources building extension "numpy.numarray._capi" sources building extension "numpy.fft.fftpack_lite" sources building extension "numpy.linalg.lapack_lite" sources adding 'numpy/linalg/lapack_litemodule.c' to sources. adding 'numpy/linalg/python_xerbla.c' to sources. building extension "numpy.random.mtrand" sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -c' gcc: _configtest.c gcc -pthread _configtest.o -o _configtest _configtest failure. removing: _configtest.c _configtest.o _configtest building data_files sources build_src: building npy-pkg config files running build_py copying numpy/version.py -> build/lib.linux-x86_64-2.7/numpy copying build/src.linux-x86_64-2.7/numpy/__config__.py -> build/lib.linux-x86_64-2.7/numpy copying build/src.linux-x86_64-2.7/numpy/distutils/__config__.py -> build/lib.linux-x86_64-2.7/numpy/distutils running build_clib customize UnixCCompiler customize UnixCCompiler using build_clib running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler gnu: no Fortran 90 compiler found gnu: no Fortran 90 compiler found customize GnuFCompiler using build_ext building 'numpy.core.multiarray' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/include -Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -Ibuild/src.linux-x86_64-2.7/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.7/numpy/core/src/umath -c' gcc: numpy/core/src/multiarray/multiarraymodule_onefile.c In file included from numpy/core/src/multiarray/multiarraymodule_onefile.c:42: numpy/core/src/multiarray/einsum.c.src:39:1: warning: "EINSUM_USE_SSE1" redefined numpy/core/src/multiarray/einsum.c.src:25:1: warning: this is the location of the previous definition numpy/core/src/multiarray/einsum.c.src:40:1: warning: "EINSUM_USE_SSE2" redefined numpy/core/src/multiarray/einsum.c.src:34:1: warning: this is the location of the previous definition numpy/core/src/multiarray/descriptor.c: In function `_convert_divisor_to_multiple': numpy/core/src/multiarray/descriptor.c:606: warning: 'q' might be used uninitialized in this function numpy/core/src/multiarray/nditer.c.src: In function `npyiter_allocate_arrays': numpy/core/src/multiarray/nditer.c.src:4923: warning: 'innershape' might be used uninitialized in this function numpy/core/src/multiarray/multiarraymodule_onefile.c: At top level: numpy/core/src/multiarray/scalartypes.c.src:2550: warning: 'longlong_arrtype_hash' defined but not used numpy/core/src/multiarray/mapping.c:75: warning: '_array_ass_item' defined but not used build/src.linux-x86_64-2.7/numpy/core/include/numpy/__ufunc_api.h:227: warning: '_import_umath' defined but not used gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/src/multiarray/multiarraymodule_onefile.o -L/state/partition1/home/amosa/triad/tools/python/lib -Lbuild/temp.linux-x86_64-2.7 -lnpymath -lm -lpython2.7 -o build/lib.linux-x86_64-2.7/numpy/core/multiarray.so building 'numpy.core.umath' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC creating build/temp.linux-x86_64-2.7/numpy/core/src/umath compile options: '-Ibuild/src.linux-x86_64-2.7/numpy/core/src/umath -Inumpy/core/include -Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -Ibuild/src.linux-x86_64-2.7/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.7/numpy/core/src/umath -c' gcc: numpy/core/src/umath/umathmodule_onefile.c numpy/core/include/numpy/npy_3kcompat.h:392: warning: 'simple_capsule_dtor' defined but not used numpy/core/src/private/lowlevel_strided_loops.h:36: warning: 'PyArray_FreeStridedTransferData' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:43: warning: 'PyArray_CopyStridedTransferData' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:64: warning: 'PyArray_GetStridedCopyFn' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:78: warning: 'PyArray_GetStridedCopySwapFn' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:92: warning: 'PyArray_GetStridedCopySwapPairFn' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:109: warning: 'PyArray_GetStridedZeroPadCopyFn' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:120: warning: 'PyArray_GetStridedNumericCastFn' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:174: warning: 'PyArray_GetDTypeTransferFunction' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:227: warning: 'PyArray_TransferNDimToStrided' declared `static' but never defined numpy/core/src/private/lowlevel_strided_loops.h:237: warning: 'PyArray_TransferStridedToNDim' declared `static' but never defined gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/src/umath/umathmodule_onefile.o -L/state/partition1/home/amosa/triad/tools/python/lib -Lbuild/temp.linux-x86_64-2.7 -lnpymath -lm -lpython2.7 -o build/lib.linux-x86_64-2.7/numpy/core/umath.so building 'numpy.core.scalarmath' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/include -Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -Ibuild/src.linux-x86_64-2.7/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.7/numpy/core/src/umath -c' gcc: build/src.linux-x86_64-2.7/numpy/core/src/scalarmathmodule.c numpy/core/src/scalarmathmodule.c.src:1054: warning: function declaration isn't a prototype numpy/core/include/numpy/npy_3kcompat.h:392: warning: 'simple_capsule_dtor' defined but not used gcc -pthread -shared build/temp.linux-x86_64-2.7/build/src.linux-x86_64-2.7/numpy/core/src/scalarmathmodule.o -L/state/partition1/home/amosa/triad/tools/python/lib -Lbuild/temp.linux-x86_64-2.7 -lnpymath -lm -lpython2.7 -o build/lib.linux-x86_64-2.7/numpy/core/scalarmath.so building 'numpy.core._dotblas' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC creating build/temp.linux-x86_64-2.7/numpy/core/blasdot compile options: '-DATLAS_INFO="\"3.7.11\"" -Inumpy/core/blasdot -Inumpy/core/include -Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy -Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/include -I/home/amosa/triad/tools/python/include/python2.7 -Ibuild/src.linux-x86_64-2.7/numpy/core/src/multiarray -Ibuild/src.linux-x86_64-2.7/numpy/core/src/umath -c' gcc: numpy/core/blasdot/_dotblas.c numpy/core/blasdot/_dotblas.c: In function `dotblas_matrixproduct': numpy/core/blasdot/_dotblas.c:239: warning: comparison of distinct pointer types lacks a cast numpy/core/blasdot/_dotblas.c:257: warning: passing arg 3 of pointer to function from incompatible pointer type numpy/core/blasdot/_dotblas.c:292: warning: passing arg 3 of pointer to function from incompatible pointer type gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/blasdot/_dotblas.o -L/usr/lib64 -L/state/partition1/home/amosa/triad/tools/python/lib -Lbuild/temp.linux-x86_64-2.7 -lf77blas -lcblas -latlas -lpython2.7 -o build/lib.linux-x86_64-2.7/numpy/core/_dotblas.so /usr/bin/ld: /usr/lib64/libcblas.a(cblas_dgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC /usr/lib64/libcblas.a: could not read symbols: Bad value collect2: ld returned 1 exit status /usr/bin/ld: /usr/lib64/libcblas.a(cblas_dgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC /usr/lib64/libcblas.a: could not read symbols: Bad value collect2: ld returned 1 exit status error: Command "gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/blasdot/_dotblas.o -L/usr/lib64 -L/state/partition1/home/amosa/triad/tools/python/lib -Lbuild/temp.linux-x86_64-2.7 -lf77blas -lcblas -latlas -lpython2.7 -o build/lib.linux-x86_64-2.7/numpy/core/_dotblas.so" failed with exit status 1

1 0

strange nan in np.ma.average
by Chao YUE Jan. 3, 2012

Jan. 3, 2012

Dear all numpy users, I have 10 90X720 arrays. let's say they are in a list 'a' with each element a 90X720 numpy masked array. then I create a new empty ndarray: data data=np.empty([10,90,720]) ##first I store all the 10 ndarray in a 10X90X720 array: for i,d in enumerate(a): data[i]=a data.shape=(10, 90, 720) then I use data_av=np.ma.average(data, axis=0) to get the average. The strange thing is, I don't have any 'nan' in all the 10 90X720 array, but I have nan value in the final data_av. how does this come? In [26]: np.nonzero(np.isnan(data_av)) Out[26]: (array([ 0, 0, 2, 2, 3, 5, 5, 6, 6, 6, 6, 7, 8, 8, 8, 9, 10, 10, 10, 11, 11, 12, 13, 13, 14, 17, 17, 19, 22, 22, 44, 63, 64, 64, 67, 68, 71, 72, 73, 76, 77, 77, 78, 79, 80, 80, 81, 82, 82, 84, 85, 85, 86, 86, 87, 87, 88, 89, 89, 89]), array([159, 541, 497, 548, 90, 97, 170, 244, 267, 587, 590, 150, 126, 168, 477, 240, 271, 277, 588, 99, 179, 528, 52, 256, 230, 109, 190, 617, 377, 389, 707, 539, 193, 361, 262, 465, 100, 232, 206, 90, 87, 93, 522, 229, 200, 482, 325, 195, 239, 228, 159, 194, thanks, Chao -- *********************************************************************************** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ************************************************************************************

1 1

nested_iters does not accept length zero nest (also doesn't have documentation)
by John Salvatier Jan. 3, 2012

Jan. 3, 2012

Hellow, while using the nested_iters function, I've noticed that it does not accept length zero nestings. For example, the following fails: nested_iters([ones(3),ones(3)], [[], [0]]) with "ValueError: If 'op_axes' or 'itershape' is not NULL in theiterator constructor, 'oa_ndim' must be greater than zero" This makes a certain amount of sense to me, but I think having the iterator with the empty axes have a single iteration would be more useful. For example, if you are using nested_iters to ally a function along a specific set of axes, you'll otherwise have to special case the case where those axes take up the whole array (which is my use case). This is not much of a hassle for me, but I thought other people might like to know. Also, I could not find any nested_iters documentation.

1 0

choose -> segfault
by Neal Becker Jan. 3, 2012

Jan. 3, 2012

I made 2 mistakes here, the 1st argument had the wrong shape, and I really wanted to use 'where', not 'choose'. But shouldn't segfault: ValueError: Need between 2 and (32) array objects (inclusive). Segmentation fault (core dumped)

2 1

polynomial package update
by Charles R Harris Jan. 3, 2012

Jan. 3, 2012

Hi All, I've made a pull request for a rather large update of the polynomial package. The new features are 1) Bug fixes 2) Improved documentation in the numpy reference 3) Preliminary support for multi-dimensional coefficient arrays 4) Support for NA in the fitting routines 5) Improved testing and test coverage 6) Gauss quadrature 7) Weight functions 8) (Mostly) Symmetrized companion matrices 9) Add cast and basis as static functions of convenience classes 10) Remove deprecated import from package *init*.py If anyone has an interest in that package, please take some time and review it here <https://github.com/numpy/numpy/pull/181>. Chuck

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