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python3-scipy_1_2_0-gnu-hpc-1.2.0-4.3.1 RPM for ppc64le

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Name: python3-scipy_1_2_0-gnu-hpc Distribution: SUSE Linux Enterprise 15
Version: 1.2.0 Vendor: SUSE LLC <https://www.suse.com/>
Release: 4.3.1 Build date: Tue May 12 12:59:45 2020
Group: Development/Libraries/Python Build host: sangiovese
Size: 53145407 Source RPM: python-scipy_1_2_0-gnu-hpc-1.2.0-4.3.1.src.rpm
Packager: https://www.suse.com/
Url: http://www.scipy.org
Summary: Scientific Tools for Python
Scipy is open-source software for mathematics, science, and
engineering. The core library is NumPy which provides convenient and
fast N-dimensional array manipulation. The SciPy library is built to
work with NumPy arrays, and provides many user-friendly and efficient
numerical routines such as routines for numerical integration and
optimization. Together, they run on all popular operating systems, are
quick to install, and are free of charge. NumPy and SciPy are easy to
use, but powerful enough to be depended upon by some of the world\'s
leading scientists and engineers.

Provides

Requires

License

BSD-3-Clause AND LGPL-2.0-or-later

Changelog

* Mon Mar 16 2020 eich@suse.com
  - '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.
* Tue Feb 12 2019 eich@suse.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.
* Fri Jan 18 2019 eich@suse.com
  - 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: ..}.
* Thu Jan 17 2019 jjolly@suse.com
  - 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,
* Sat Dec 22 2018 toddrme2178@gmail.com
  - 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
* Fri May 11 2018 toddrme2178@gmail.com
  - Fix build on SLE
* Mon May 07 2018 toddrme2178@gmail.com
  - 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
* Sun Apr 01 2018 arun@gmx.de
  - 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
* Tue Feb 13 2018 schwab@suse.de
  - Don't use openblas on m68k and riscv64
* Thu Oct 26 2017 toddrme2178@gmail.com
  - 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
* Tue Jul 11 2017 toddrme2178@gmail.com
  - More rpmlint fixes.
* Mon Jul 10 2017 toddrme2178@gmail.com
  - 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.
* Wed Apr 19 2017 toddrme2178@gmail.com
  - 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.
* Fri Oct 21 2016 toddrme2178@gmail.com
  - 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.
* Thu Jan 28 2016 toddrme2178@gmail.com
  - 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.
* Fri Oct 30 2015 toddrme2178@gmail.com
  - Update to 0.16.1
    SciPy 0.16.1 is a bug-fix release with no new features compared
    to 0.16.0.
* Mon Jul 27 2015 toddrme2178@gmail.com
  - Remove Cython subpackage.  The sources are not as cleanly
    separated as the changelog implied.
* Mon Jul 27 2015 toddrme2178@gmail.com
  - 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
* Mon Mar 02 2015 toddrme2178@gmail.com
  - 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
* Mon Jan 12 2015 toddrme2178@gmail.com
  - 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

Files

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Fabrice Bellet, Tue Jul 9 13:44:15 2024