AArch64 | |

ppc64le | |

s390x | |

x86-64 |

python2-scipy-gnu-hpc

python2-scipy_1_2_0-gnu-hpc

python3-scipy-gnu-hpc

python3-scipy_1_2_0-gnu-hpc

- 'umpfack' is a runtime dependency of scipy. No build time dependency to suitesparse is required (jsc#SLE-11732, jsc#SLE-11776). - Get rid of site.cfg entirely as it is used nowhwere in scipy.

Version: 1.2.0-bp151.1.2
*** Tue Feb 12 2019 Egbert Eich <eich@suse.com> **
*** Fri Jan 18 2019 eich@suse.com **
*** Thu Jan 17 2019 jjolly@suse.com **
*** Sat Dec 22 2018 Todd R <toddrme2178@gmail.com> **
*** Fri May 11 2018 toddrme2178@gmail.com **
*** Mon May 07 2018 toddrme2178@gmail.com **
*** Sun Apr 01 2018 arun@gmx.de **
*** Tue Feb 13 2018 schwab@suse.de **
*** Thu Oct 26 2017 toddrme2178@gmail.com **
*** Tue Jul 11 2017 toddrme2178@gmail.com **
*** Mon Jul 10 2017 toddrme2178@gmail.com **
*** Wed Apr 19 2017 toddrme2178@gmail.com **
*** Fri Oct 21 2016 toddrme2178@gmail.com **
*** Thu Jan 28 2016 toddrme2178@gmail.com **
*** Fri Oct 30 2015 toddrme2178@gmail.com **
*** Mon Jul 27 2015 toddrme2178@gmail.com **
*** Mon Jul 27 2015 toddrme2178@gmail.com **
*** Mon Mar 02 2015 toddrme2178@gmail.com **
*** Mon Jan 12 2015 toddrme2178@gmail.com **
*** Mon Aug 11 2014 toddrme2178@gmail.com **

bsc#1130564: Apply update from the openSUSE package - Properly create and tear down default version links when the HPC master packages are installed/uninstalled. - Make use of %hpc_modules_init to make modules also known to client. - Module file: * remove PATH element. Package has no binary, * make cosmetic changes. - Remove use of %%python_module in dependency.

- Some futher changes: * Remove the use of fftw. The code doesn't link against it anywhere. For HPC we would have to build things separately for different MPI flavors as fftw3 exists only with HPC support there. * restructure the build process: since the environment for the right python version of Numpy needs to be loaded, wrap entire build (and install) in %%{python_expand: ..}.

- Add support for HPC builds: * Add _multibuild file * Add standard and gnu-hpc builds * Create initialization for both flavors to set the correct target directories in macros and replace install paths with these. * Restructure the build process. * Create 'master' packages for non-HPC builds. * Create environment module information,

- Update to version 1.2.0 * Many changes. Please see changelog at: https://github.com/scipy/scipy/blob/v1.2.0/doc/release/1.2.0-notes.rst

- Fix build on SLE

- Update to version 1.1.0 * Many changes. Please see changelog at: https://github.com/scipy/scipy/blob/v1.1.0/doc/release/1.1.0-notes.rst

- update to version 1.0.1: * Issues closed for 1.0.1 + #7493: ndimage.morphology functions are broken with numpy 1.13.0 + #8118: minimize_cobyla broken if disp=True passed + #8142: scipy-v1.0.0 pdist with metric=`minkowski` raises `ValueError:... + #8173: scipy.stats.ortho_group produces all negative determinants... + #8207: gaussian_filter seg faults on float16 numpy arrays + #8234: scipy.optimize.linprog interior-point presolve bug with trivial... + #8243: Make csgraph importable again via from scipy.sparse import* + #8320: scipy.root segfaults with optimizer 'lm' * Pull requests for 1.0.1 + #8068: BUG: fix numpy deprecation test failures + #8082: BUG: fix solve_lyapunov import + #8144: MRG: Fix for cobyla + #8150: MAINT: resolve UPDATEIFCOPY deprecation errors + #8156: BUG: missing check on minkowski w kwarg + #8187: BUG: Sign of elements in random orthogonal 2D matrices in "ortho_group_gen"... + #8197: CI: uninstall oclint + #8215: Fixes Numpy datatype compatibility issues + #8237: BUG: optimize: fix bug when variables fixed by bounds are inconsistent... + #8248: BUG: declare "gfk" variable before call of terminate() in newton-cg + #8280: REV: reintroduce csgraph import in scipy.sparse + #8322: MAINT: prevent scipy.optimize.root segfault closes #8320 + #8334: TST: stats: don't use exact equality check for hdmedian test + #8477: BUG: signal/signaltools: fix wrong refcounting in PyArray_OrderFilterND + #8530: BUG: linalg: Fixed typo in flapack.pyf.src. + #8566: CI: Temporarily pin Cython version to 0.27.3 + #8573: Backports for 1.0.1 + #8581: Fix Cython 0.28 build break of qhull.pyx

- Don't use openblas on m68k and riscv64

- Update to version 1.0.0 * Many changes. Please see changelog at: https://github.com/scipy/scipy/blob/v1.0.0/doc/release/1.0.0-notes.rst#why-1-0-now - Rebase no_implicit_decl.patch

- More rpmlint fixes.

- Update to version 0.19.1 * #7214: Memory use in integrate.quad in scipy-0.19.0 * #7258: linalg.matrix_balance gives wrong transformation matrix * #7262: Segfault in daily testing * #7273: scipy.interpolate._bspl.evaluate_spline gets wrong type * #7335: scipy.signal.dlti(A,B,C,D).freqresp() fails * #7211: BUG: convolve may yield inconsistent dtypes with method changed * #7216: BUG: integrate: fix refcounting bug in quad() * #7229: MAINT: special: Rewrite a test of wrightomega * #7261: FIX: Corrected the transformation matrix permutation * #7265: BUG: Fix broken axis handling in spectral functions * #7266: FIX 7262: ckdtree crashes in query_knn. * #7279: Upcast half- and single-precision floats to doubles in BSpline... * #7336: BUG: Fix signal.dfreqresp for StateSpace systems * #7419: Fix several issues in sparse.load_npz, save_npz * #7420: BUG: stats: allow integers as kappa4 shape parameters - Add no_implicit_decl.patch Fixes implicit-pointer-decl warnings and implicit-fortify-decl error. - Fix wrong-script-interpreter rpmlint error.

- Update to version 0.19.0 + Highlights * A unified foreign function interface layer, `scipy.LowLevelCallable`. * Cython API for scalar, typed versions of the universal functions from the `scipy.special` module, via `cimport scipy.special.cython_special`. - Removed weave subpackage. It was removed upstream in this release.

- Switch to single-spec version - update to version 0.18.1: * #6357: scipy 0.17.1 piecewise cubic hermite interpolation does not return... * #6420: circmean() changed behaviour from 0.17 to 0.18 * #6421: scipy.linalg.solve_banded overwrites input 'b' when the inversion... * #6425: cKDTree INF bug * #6435: scipy.stats.ks_2samp returns different values on different computers * #6458: Error in scipy.integrate.dblquad when using variable integration... * #6405: BUG: sparse: fix elementwise divide for CSR/CSC * #6431: BUG: result for insufficient neighbours from cKDTree is wrong. * #6432: BUG Issue #6421: scipy.linalg.solve_banded overwrites input 'b'... * #6455: DOC: add links to release notes * #6462: BUG: interpolate: fix .roots method of PchipInterpolator * #6492: BUG: Fix regression in dblquad: #6458 * #6543: fix the regression in circmean * #6545: Revert gh-5938, restore ks_2samp * #6557: Backports for 0.18.1 - update to version 0.18.0: (see http://scipy.github.io/devdocs/release.0.18.0.html for full changelog) * Highlights of this release include: + A new ODE solver for two-point boundary value problems, scipy.optimize.solve_bvp. + A new class, CubicSpline, for cubic spline interpolation of data. + N-dimensional tensor product polynomials, scipy.interpolate.NdPPoly. + Spherical Voronoi diagrams, scipy.spatial.SphericalVoronoi. + Support for discrete-time linear systems, scipy.signal.dlti. - update to version 0.17.1: * #5817: BUG: skew, kurtosis return np.nan instead of "propagate" * #5850: Test failed with sgelsy * #5898: interpolate.interp1d crashes using float128 * #5953: Massive performance regression in cKDTree.query with L_inf distance... * #6062: mannwhitneyu breaks backward compatibility in 0.17.0 * #6134: T test does not handle nans * #5902: BUG: interpolate: make interp1d handle np.float128 again * #5957: BUG: slow down with p=np.inf in 0.17 cKDTree.query * #5970: Actually propagate nans through stats functions with nan_policy="propagate" * #5971: BUG: linalg: fix lwork check in *gelsy * #6074: BUG: special: fixed violation of strict aliasing rules. * #6083: BUG: Fix dtype for sum of linear operators * #6100: BUG: Fix mannwhitneyu to be backward compatible * #6135: Don't pass null pointers to LAPACK, even during workspace queries. * #6148: stats: fix handling of nan values in T tests and kendalltau - specfile: * updated source url to files.pythonhosted.org * require setuptools * Add openBLAS support. This can improve performance in many situations. * Drop ATLAS support.

- specfile: * update copyright year - update to version 0.17.0: (see http://scipy.github.io/devdocs/release.0.17.0.html for full changelog) * Highlights + New functions for linear and nonlinear least squares optimization with constraints: scipy.optimize.lsq_linear and scipy.optimize.least_squares + Support for fitting with bounds in scipy.optimize.curve_fit. + Significant improvements to scipy.stats, providing many functions with better handing of inputs which have NaNs or are empty, improved documentation, and consistent behavior between scipy.stats and scipy.stats.mstats. + Significant performance improvements and new functionality in scipy.spatial.cKDTree.

- Update to 0.16.1 SciPy 0.16.1 is a bug-fix release with no new features compared to 0.16.0.

- Remove Cython subpackage. The sources are not as cleanly separated as the changelog implied.

- Update to 0.16.0 * Highlights of this release include: - A Cython API for BLAS/LAPACK in scipy.linalg - A new benchmark suite. It's now straightforward to add new benchmarks, and they're routinely included with performance enhancement PRs. - Support for the second order sections (SOS) format in scipy.signal. * New features - Benchmark suite + The benchmark suite has switched to using Airspeed Velocity for benchmarking. - scipy.linalg improvements + A full set of Cython wrappers for BLAS and LAPACK has been added in the modules scipy.linalg.cython_blas and scipy.linalg.cython_lapack. In Cython, these wrappers can now be cimported from their corresponding modules and used without linking directly against BLAS or LAPACK. + The functions scipy.linalg.qr_delete, scipy.linalg.qr_insert and scipy.linalg.qr_update for updating QR decompositions were added. + The function scipy.linalg.solve_circulant solves a linear system with a circulant coefficient matrix. + The function scipy.linalg.invpascal computes the inverse of a Pascal matrix. + The function scipy.linalg.solve_toeplitz, a Levinson-Durbin Toeplitz solver, was added. + Added wrapper for potentially useful LAPACK function *lasd4. It computes the square root of the i-th updated eigenvalue of a positive symmetric rank-one modification to a positive diagonal matrix. See its LAPACK documentation and unit tests for it to get more info. + Added two extra wrappers for LAPACK least-square solvers. Namely, they are * gelsd and *gelsy. + Wrappers for the LAPACK *lange functions, which calculate various matrix norms, were added. + Wrappers for *gtsv and *ptsv, which solve A*X = B for tri-diagonal matrix A, were added. - scipy.signal improvements + Support for second order sections (SOS) as a format for IIR filters was added. The new functions are: * scipy.signal.sosfilt * scipy.signal.sosfilt_zi, * scipy.signal.sos2tf * scipy.signal.sos2zpk * scipy.signal.tf2sos * scipy.signal.zpk2sos. + Additionally, the filter design functions iirdesign, iirfilter, butter, cheby1, cheby2, ellip, and bessel can return the filter in the SOS format. + The function scipy.signal.place_poles, which provides two methods to place poles for linear systems, was added. + The option to use Gustafsson's method for choosing the initial conditions of the forward and backward passes was added to scipy.signal.filtfilt. + New classes TransferFunction, StateSpace and ZerosPolesGain were added. These classes are now returned when instantiating scipy.signal.lti. Conversion between those classes can be done explicitly now. + An exponential (Poisson) window was added as scipy.signal.exponential, and a Tukey window was added as scipy.signal.tukey. + The function for computing digital filter group delay was added as scipy.signal.group_delay. + The functionality for spectral analysis and spectral density estimation has been significantly improved: scipy.signal.welch became ~8x faster and the functions scipy.signal.spectrogram, scipy.signal.coherence and scipy.signal.csd (cross-spectral density) were added. + scipy.signal.lsim was rewritten - all known issues are fixed, so this function can now be used instead of lsim2; lsim is orders of magnitude faster than lsim2 in most cases. - scipy.sparse improvements + The function scipy.sparse.norm, which computes sparse matrix norms, was added. + The function scipy.sparse.random, which allows to draw random variates from an arbitrary distribution, was added. - scipy.spatial improvements + scipy.spatial.cKDTree has seen a major rewrite, which improved the performance of the query method significantly, added support for parallel queries, pickling, and options that affect the tree layout. See pull request 4374 for more details. + The function scipy.spatial.procrustes for Procrustes analysis (statistical shape analysis) was added. - scipy.stats improvements + The Wishart distribution and its inverse have been added, as scipy.stats.wishart and scipy.stats.invwishart. + The Exponentially Modified Normal distribution has been added as scipy.stats.exponnorm. + The Generalized Normal distribution has been added as scipy.stats.gennorm. + All distributions now contain a random_state property and allow specifying a specific numpy.random.RandomState random number generator when generating random variates. + Many statistical tests and other scipy.stats functions that have multiple return values now return namedtuples. See pull request 4709 for details. - scipy.optimize improvements + A new derivative-free method DF-SANE has been added to the nonlinear equation system solving function scipy.optimize.root. * Deprecated features - scipy.stats.pdf_fromgamma is deprecated. This function was undocumented, untested and rarely used. Statsmodels provides equivalent functionality with statsmodels.distributions.ExpandedNormal. - scipy.stats.fastsort is deprecated. This function is unnecessary, numpy.argsort can be used instead. - scipy.stats.signaltonoise and scipy.stats.mstats.signaltonoise are deprecated. These functions did not belong in scipy.stats and are rarely used. See issue #609 for details. - scipy.stats.histogram2 is deprecated. This function is unnecessary, numpy.histogram2d can be used instead. * Backwards incompatible changes - The deprecated global optimizer scipy.optimize.anneal was removed. - The following deprecated modules have been removed. They had been deprecated since Scipy 0.12.0, the functionality should be accessed as scipy.linalg.blas and scipy.linalg.lapack. + scipy.lib.blas + scipy.lib.lapack + scipy.linalg.cblas + scipy.linalg.fblas + scipy.linalg.clapack + scipy.linalg.flapack. - The deprecated function scipy.special.all_mat has been removed. - These deprecated functions have been removed from scipy.stats: + scipy.stats.fprob + scipy.stats.ksprob + scipy.stats.zprob + scipy.stats.randwcdf + scipy.stats.randwppf * Other changes - The version numbering for development builds has been updated to comply with PEP 440. - Building with python setup.py develop is now supported. - Move Cython imports to another package

- update to version 0.15.1: * #4413: BUG: Tests too strict, f2py doesn't have to overwrite this array * #4417: BLD: avoid using NPY_API_VERSION to check not using deprecated... * #4418: Restore and deprecate scipy.linalg.calc_work

- Update to 0.15.0 * New features * scipy.optimize improvements * scipy.optimize.linprog now provides a generic linear programming similar to the way scipy.optimize.minimize provides a generic interface to nonlinear programming optimizers. Currently the only method supported is simplex which provides a two-phase, dense-matrix-based simplex algorithm. Callbacks functions are supported,allowing the user to monitor the progress of the algorithm. * The differential_evolution function is available from the scipy.optimize module. Differential Evolution is an algorithm used for finding the global minimum of multivariate functions. It is stochastic in nature (does not use gradient methods), and can search large areas of candidate space, but often requires larger numbers of function evaluations than conventional gradient based techniques. * scipy.signal improvements * The function max_len_seq was added, which computes a Maximum Length Sequence (MLS) signal. * scipy.integrate improvements * The interface between the scipy.integrate module and the QUADPACK library was redesigned. It is now possible to use scipy.integrate to integrate multivariate ctypes functions, thus avoiding callbacks to Python and providing better performance, especially for complex integrand functions. * scipy.sparse improvements * scipy.sparse.linalg.svds now takes a LinearOperator as its main input. * scipy.stats improvements * Added a Dirichlet distribution as multivariate distribution. * The new function `scipy.stats.median_test` computes Mood's median test. * `scipy.stats.describe` returns a namedtuple rather than a tuple, allowing users to access results by index or by name. * Deprecated features * The scipy.weave module is deprecated. It was the only module never ported to Python 3.x, and is not recommended to be used for new code - use Cython instead. In order to support existing code, scipy.weave has been packaged separately: https://github.com/scipy/weave. It is a pure Python package, so can easily be installed with pip install weave. * scipy.special.bessel_diff_formula is deprecated. It is a private function, and therefore will be removed from the public API in a following release. * Backwards incompatible changes * scipy.ndimage * The functions scipy.ndimage.minimum_positions, scipy.ndimage.maximum_positions and scipy.ndimage.extrema return positions as ints instead of floats. * Other changes * scipy.integrate * The OPTPACK and QUADPACK code has been changed to use the LAPACK matrix solvers rather than the bundled LINPACK code. This means that there is no longer any need for the bundled LINPACK routines, so they have been removed. - Update copyright year

- Switch to pypi download location - Minor spec file cleanups