python-scipy_1_2_0-gnu-hpc-1.2.0-bp151.1.2

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