python3-numpy-1.17.3-150400.28.37<>,Gpd$p9|-᝗Vl6$薾biPaߓTֻZR+tvsv8답=$E ڣ7IkO JޟrlӷrQ-m/S [z/C{%I:#Rz8Ȉ]E(lE`EQ$r) p9_28|AkCT_rVQ@W͛Ffva[R2J"ئ9tBj.2-ς;T\P?;TD{GD>B?d $ e :PV^` x      Ld(8&9&:H&>3@;FCGXHpI X"Y"\"]*^P-bZcZd[Oe[Tf[Wl[Yu[lvcwpxxy*zXhlrCpython3-numpy1.17.3150400.28.37NumPy array processing for numbers, strings, records and objectsNumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose data-base applications. There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation.d$xinomavro jSUSE Linux Enterprise 15SUSE LLC BSD-3-Clausehttps://www.suse.com/Development/Libraries/Pythonhttp://www.numpy.org/linuxppc64le# python3_install_alternative: update-alternatives --quiet --install /usr/bin/f2py f2py /usr/bin/f2py-3.6 36# python3_uninstall_alternative: if [ ! -e "/usr/bin/f2py-3.6" ]; then update-alternatives --quiet --remove "f2py" "/usr/bin/f2py-3.6" fiuw{#q  n78>'ybK KUBYh~xo<&' *Z +7=,b|R:J6 W'@J@L]Y*cE&% xj :h @ '#7 TGê@.I܈Th*l-F EyEypqD%D  Z qK $;Q l 80S5? > 5kJT mv41H5a  R4MenxPS ]& &Y* o\ <$36 X ,b tQDq 08gkF % bC3b N9>W,-':n?&{hKpI+$Kx'9>%/go3U  W6F6<-Nfs7 A -U-zY%`]&e#> w/? @NXiZU(U9`bO{smE*f- allow building numpy on fedora by making fdupes dependency optional- Update to version 1.12.1 * Fix wrong future nat warning and equiv type logic error... * Fix wrong masked median for some special cases * Place np.average in inline code * Work around isfinite inconsistency on i386 * Guard against replacing constants without '_' spec in f2py. * Fix mean for float 16 non-array inputs for 1.12 * Fix calling python api with error set and minor leaks for... * Make iscomplexobj compatible with custom dtypes again * Fix undefined behaviour induced by bad __array_wrap__ * Fix MaskedArray.__setitem__ * PPC64el machines are POWER for Fortran in f2py * Look up methods on MaskedArray in `_frommethod` * Remove extra digit in binary_repr at limit * Fix deepcopy regression for empty arrays. * Fix ma.median for empty ndarrays - Further updates to macro usage.- Fix macro usage.- Fix -devel package dependency- Switch to single-spec version- update to version 1.12.0: * Highlights + Order of operations in np.einsum can now be optimized for large speed improvements. + New signature argument to np.vectorize for vectorizing with core dimensions. + The keepdims argument was added to many functions. + New context manager for testing warnings + Support for BLIS in numpy.distutils + Much improved support for PyPy (not yet finished) * full changelog at: https://github.com/numpy/numpy/blob/master/doc/release/1.12.0-notes.rst - changes from version 1.11.3: * #8341: BUG: Fix ndarray.tofile large file corruption in append mode. * #8346: TST: Fix tests in PR #8341 for NumPy 1.11.x - update to version 1.11.2: * #7736 BUG: Many functions silently drop 'keepdims' kwarg. * #7738 ENH: Add extra kwargs and update doc of many MA methods. * #7778 DOC: Update Numpy 1.11.1 release notes. * #7793 BUG: MaskedArray.count treats negative axes incorrectly. * #7816 BUG: Fix array too big error for wide dtypes. * #7821 BUG: Make sure npy_mul_with_overflow_ detects overflow. * #7824 MAINT: Allocate fewer bytes for empty arrays. * #7847 MAINT,DOC: Fix some imp module uses and update f2py.compile docstring. * #7849 MAINT: Fix remaining uses of deprecated Python imp module. * #7851 BLD: Fix ATLAS version detection. * #7896 BUG: Construct ma.array from np.array which contains padding. * #7904 BUG: Fix float16 type not being called due to wrong ordering. * #7917 BUG: Production install of numpy should not require nose. * #7919 BLD: Fixed MKL detection for recent versions of this library. * #7920 BUG: Fix for issue #7835 (ma.median of 1d). * #7932 BUG: Monkey-patch _msvccompile.gen_lib_option like other compilers. * #7939 BUG: Check for HAVE_LDOUBLE_DOUBLE_DOUBLE_LE in npy_math_complex. * #7953 BUG: Guard against buggy comparisons in generic quicksort. * #7954 BUG: Use keyword arguments to initialize Extension base class. * #7955 BUG: Make sure numpy globals keep identity after reload. * #7972 BUG: MSVCCompiler grows 'lib' & 'include' env strings exponentially. * #8005 BLD: Remove __NUMPY_SETUP__ from builtins at end of setup.py. * #8010 MAINT: Remove leftover imp module imports. * #8020 BUG: Fix return of np.ma.count if keepdims is True and axis is None. * #8024 BUG: Fix numpy.ma.median. * #8031 BUG: Fix np.ma.median with only one non-masked value. * #8044 BUG: Fix bug in NpyIter buffering with discontinuous arrays. - update copyright year - changed from tar.gz to zip on pypi - Remove long-unused atlas support. - Use preferrered pypi.io download url. - Add openBLAS support. This can improve performance in many situations. - Remove numpy-1.10.4-cblas.patch since openblas handles this.- Fix cblas handling for SLES 12.- use pypi.io as Source URL- Don't include cblas-devel on SLES 12- update to 1.11.1: - #7506 BUG: Make sure numpy imports on python 2.6 when nose is unavailable. - #7530 BUG: Floating exception with invalid axis in np.lexsort. - #7535 BUG: Extend glibc complex trig functions blacklist to glibc < 2.18. - #7551 BUG: Allow graceful recovery for no compiler. - #7558 BUG: Constant padding expected wrong type in constant_values. - #7578 BUG: Fix OverflowError in Python 3.x. in swig interface. - #7590 BLD: Fix configparser.InterpolationSyntaxError. - #7597 BUG: Make np.ma.take work on scalars. - #7608 BUG: linalg.norm(): Don't convert object arrays to float. - #7638 BLD: Correct C compiler customization in system_info.py. - #7654 BUG: ma.median of 1d array should return a scalar. - #7656 BLD: Remove hardcoded Intel compiler flag -xSSE4.2. - #7660 BUG: Temporary fix for str(mvoid) for object field types. - #7665 BUG: Fix incorrect printing of 1D masked arrays. - #7670 BUG: Correct initial index estimate in histogram. - #7671 BUG: Boolean assignment no GIL release when transfer needs API. - #7676 BUG: Fix handling of right edge of final histogram bin. - #7680 BUG: Fix np.clip bug NaN handling for Visual Studio 2015. - #7724 BUG: Fix segfaults in np.random.shuffle. - #7731 MAINT: Change mkl_info.dir_env_var from MKL to MKLROOT.specfile: * require setuptools - update to version 1.11.0: * Highlights + The datetime64 type is now timezone naive. + A dtype parameter has been added to randint. + Improved detection of two arrays possibly sharing memory. + Automatic bin size estimation for np.histogram. + Speed optimization of A @ A.T and dot(A, A.T). + New function np.moveaxis for reordering array axes. * full changelog at https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst- Add numpy-1.10.4-cblas.patch to build against system cblas. Numpy assumes either libblas.so or libcblas.so to contain all CBLAS and BLAS functions. However the cblas-devel in Leap and Tumbleweed contains only the CBLAS interface and libblas.so is also needed.- update to version 1.10.4: * see https://github.com/numpy/numpy/blob/master/doc/release/1.10.4-notes.rst * There is no 1.10.3 due to packaging issues. - update to version 1.10.2: * see https://github.com/numpy/numpy/blob/master/doc/release/1.10.2-notes.rst- Update to 1.10.1 + Bugfix for build problems * Compiling with msvc9 or msvc10 for 32 bit Windows now requires SSE2. This was the easiest fix for what looked to be some miscompiled code when SSE2 was not used. If you need to compile for 32 bit Windows systems without SSE2 support, mingw32 should still work. * Make compiling with VS2008 python2.7 SDK easier * Change Intel compiler options so that code will also be generated to support systems without SSE4.2. * Some _config test functions needed an explicit integer return in order to avoid the openSUSE rpmlinter erring out. * We ran into a problem with pipy not allowing reuse of filenames and a resulting proliferation of *.*.*.postN releases. Not only were the names getting out of hand, some packages were unable to work with the postN suffix. - Remove upstream-included numpy-1.10.0-remove_Wreturn_type_warnings.patch- Update to version 1.10.0 + Highlights * numpy.distutils now supports parallel compilation via the --parallel/-j argument passed to setup.py build * numpy.distutils now supports additional customization via site.cfg to control compilation parameters, i.e. runtime libraries, extra linking/compilation flags. * Addition of *np.linalg.multi_dot*: compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order. * The new function `np.stack` provides a general interface for joining a sequence of arrays along a new axis, complementing `np.concatenate` for joining along an existing axis. * Addition of `nanprod` to the set of nanfunctions. * Support for the '@' operator in Python 3.5. + Dropped Support: * The _dotblas module has been removed. CBLAS Support is now in Multiarray. * The testcalcs.py file has been removed. * The polytemplate.py file has been removed. * npy_PyFile_Dup and npy_PyFile_DupClose have been removed from npy_3kcompat.h. * splitcmdline has been removed from numpy/distutils/exec_command.py. * try_run and get_output have been removed from numpy/distutils/command/config.py * The a._format attribute is no longer supported for array printing. * Keywords ``skiprows`` and ``missing`` removed from np.genfromtxt. * Keyword ``old_behavior`` removed from np.correlate. + Future Changes: * In array comparisons like ``arr1 == arr2``, many corner cases involving strings or structured dtypes that used to return scalars now issue ``FutureWarning`` or ``DeprecationWarning``, and in the future will be change to either perform elementwise comparisons or raise an error. * The SafeEval class will be removed. * The alterdot and restoredot functions will be removed. - Rebase numpy-1.9.0-remove-__declspec.patch - Add numpy-1.10.0-remove_Wreturn_type_warnings.patch This patch is already merged upstream and should be present in numpy-1.10.1- update to version 1.9.3: * #5866: fix error finding Python headers when build_ext --include-dirs is set; * #6016: fix np.loadtxt error on Python 3.5 when reading from gzip files; * #5555: Replace deprecated options for ifort; * #6096: remove /GL for VS2015 in check_long_double_representation; * #6141: enable Visual Studio 2015 C99 features; * #6171: revert C99 complex for MSVC14.- Update to 1.9.2: Bugfix release * #5316: fix too large dtype alignment of strings and complex types * #5424: fix ma.median when used on ndarrays * #5481: Fix astype for structured array fields of different byte order * #5354: fix segfault when clipping complex arrays * #5524: allow np.argpartition on non ndarrays * #5612: Fixes ndarray.fill to accept full range of uint64 * #5155: Fix loadtxt with comments=None and a string None data * #4476: Masked array view fails if structured dtype has datetime component * #5388: Make RandomState.set_state and RandomState.get_state threadsafe * #5390: make seed, randint and shuffle threadsafe * #5374: Fixed incorrect assert_array_almost_equal_nulp documentation * #5393: Add support for ATLAS > 3.9.33. * #5313: PyArray_AsCArray caused segfault for 3d arrays * #5492: handle out of memory in rfftf * #4181: fix a few bugs in the random.pareto docstring * #5359: minor changes to linspace docstring * #4723: fix a compile issues on AIX- Update to 1.9.1: Bugfix release * gh-5184: restore linear edge behaviour of gradient to as it was in < 1.9. The second order behaviour is available via the `edge_order` keyword * gh-4007: workaround Accelerate sgemv crash on OSX 10.9 * gh-5100: restore object dtype inference from iterable objects without `len()` * gh-5163: avoid gcc-4.1.2 (red hat 5) miscompilation causing a crash * gh-5138: fix nanmedian on arrays containing inf * gh-5203: copy inherited masks in MaskedArray.__array_finalize__ * gh-2317: genfromtxt did not handle filling_values=0 correctly * gh-5067: restore api of npy_PyFile_DupClose in python2 * gh-5063: cannot convert invalid sequence index to tuple * gh-5082: Segmentation fault with argmin() on unicode arrays * gh-5095: don't propagate subtypes from np.where * gh-5104: np.inner segfaults with SciPy's sparse matrices * gh-5136: Import dummy_threading if importing threading fails * gh-5148: Make numpy import when run with Python flag '-OO' * gh-5147: Einsum double contraction in particular order causes ValueError * gh-479: Make f2py work with intent(in out) * gh-5170: 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