Changelog for python311-scipy-1.13.0-lp156.4.4.x86_64.rpm :

* Sun May 12 2024 Sarah Kriesch - Enable python-scipy:gnu-hpc for s390x (together with python-numpy:gnu-hpc)
* Thu May 09 2024 Sarah Kriesch - Enable openblas for s390x
* Wed Apr 24 2024 Ben Greiner - Skip another test out of numeric precision for 32-bit- Fix HPC _version
* Fri Apr 19 2024 Ben Greiner - Update to 1.13.0 [#]# Highlights of this release
* Support for NumPy 2.0.0.
* Interactive examples have been added to the documentation, allowing users to run the examples locally on embedded Jupyterlite notebooks in their browser.
* Preliminary 1D array support for the COO and DOK sparse formats.
* Several scipy.stats functions have gained support for additional axis, nan_policy, and keepdims arguments. scipy.stats also has several performance and accuracy improvements. [#]# New features
* scipy.integrate improvements
* scipy.io improvements
* scipy.interpolate improvements
* scipy.signal improvements
* scipy.sparse improvements
* scipy.spatial improvements
* scipy.special improvements
* scipy.stats improvements [#]# Deprecated features
* Complex dtypes in PchipInterpolator and Akima1DInterpolator have been deprecated and will raise an error in SciPy 1.15.0. If you are trying to use the real components of the passed array, use np.real on y. [#]# Other changes
* The second argument of scipy.stats.moment has been renamed to order while maintaining backward compatibility.- Release 1.12.0 [#]# Highlights of this release
* Experimental support for the array API standard has been added to part of scipy.special, and to all of scipy.fft and scipy.cluster. There are likely to be bugs and early feedback for usage with CuPy arrays, PyTorch tensors, and other array API compatible libraries is appreciated. Use the SCIPY_ARRAY_API environment variable for testing.
* A new class, ShortTimeFFT, provides a more versatile implementation of the short-time Fourier transform (STFT), its inverse (ISTFT) as well as the (cross-) spectrogram. It utilizes an improved algorithm for calculating the ISTFT.
* Several new constructors have been added for sparse arrays, and many operations now additionally support sparse arrays, further facilitating the migration from sparse matrices.
* A large portion of the scipy.stats API now has improved support for handling NaN values, masked arrays, and more fine-grained shape-handling. The accuracy and performance of a number of stats methods have been improved, and a number of new statistical tests and distributions have been added. [#]# New features
* scipy.cluster improvements
* scipy.fft improvements
* scipy.integrate improvements
* scipy.interpolate improvements
* scipy.linalg improvements
* scipy.ndimage improvements
* scipy.optimize improvements
* scipy.signal improvements
* scipy.sparse improvements
* scipy.spatial improvements
* scipy.special improvements
* scipy.stats improvements [#]# Deprecated features
* Error messages have been made clearer for objects that don’t exist in the public namespace and warnings sharpened for private attributes that are not supposed to be imported at all.
* scipy.signal.cmplx_sort has been deprecated and will be removed in SciPy 1.15. A replacement you can use is provided in the deprecation message.
* Values the argument initial of scipy.integrate.cumulative_trapezoid other than 0 and None are now deprecated.
* scipy.stats.rvs_ratio_uniforms is deprecated in favour of scipy.stats.sampling.RatioUniforms
* scipy.integrate.quadrature and scipy.integrate.romberg have been deprecated due to accuracy issues and interface shortcomings. They will be removed in SciPy 1.15. Please use scipy.integrate.quad instead.
* Coinciding with upcoming changes to function signatures (e.g. removal of a deprecated keyword), we are deprecating positional use of keyword arguments for the affected functions, which will raise an error starting with SciPy 1.14. In some cases, this has delayed the originally announced removal date, to give time to respond to the second part of the deprecation. Affected functions are: - linalg.{eigh, eigvalsh, pinv} - integrate.simpson - signal.{firls, firwin, firwin2, remez} - sparse.linalg.{bicg, bicgstab, cg, cgs, gcrotmk, gmres, lgmres, minres, qmr, tfqmr} - special.comb - stats.kendalltau
* All wavelet functions have been deprecated, as PyWavelets provides suitable implementations; affected functions are: signal.{daub, qmf, cascade, morlet, morlet2, ricker, cwt}
* scipy.integrate.trapz, scipy.integrate.cumtrapz, and scipy.integrate.simps have been deprecated in favour of scipy.integrate.trapezoid, scipy.integrate.cumulative_trapezoid, and scipy.integrate.simpson respectively and will be removed in SciPy 1.14.
* The tol argument of scipy.sparse.linalg.{bcg,bicstab,cg,cgs,gcrotmk,gmres,lgmres, minres,qmr,tfqmr} is now deprecated in favour of rtol and will be removed in SciPy 1.14. Furthermore, the default value of atol for these functions is due to change to 0.0 in SciPy 1.14. [#]# Expired Deprecations
* There is an ongoing effort to follow through on long-standing deprecations. The following previously deprecated features are affected:
* The centered keyword of scipy.stats.qmc.LatinHypercube has been removed. Use scrambled=False instead of centered=True.
* scipy.stats.binom_test has been removed in favour of scipy.stats.binomtest.
* In scipy.stats.iqr, the use of scale=\'raw\' has been removed in favour of scale=1.
* Functions from NumPy’s main namespace which were exposed in SciPy’s main namespace, such as numpy.histogram exposed by scipy.histogram, have been removed from SciPy’s main namespace. Please use the functions directly from numpy. [#]# Other changes
* The arguments used to compile and link SciPy are now available via show_config.- Drop 8c96a1f742335bca283aae418763aaba62c03378.patch (merged upstream)- Add scipy-pr20530-f2py_error.patch gh#scipy/scipy#20530, used to find workaround for failing HPC build gh#scipy/scipy#20535
* Tue Feb 27 2024 Egbert Eich - Add 8c96a1f742335bca283aae418763aaba62c03378.patch to fix issues with OpenBLAS 0.3.26 and later (boo#1220163).
* Mon Jan 22 2024 Daniel Garcia - Disable broken tests in s390x, gh#scipy/scipy#18878, bsc#1218608
* Tue Nov 21 2023 Steve Kowalik - Update to 1.11.4:
* MAINT: ensure cobyla objective returns scalar
* MAINT: fixup dep warning
* BUG: interpolate: fix spalde with len(c) < len(t)
* BUG: pass unused xrtol in fmin_bfgs to _minimize_bfgs
* BUG: Regression test for lsq trf boundary error
* BUG: lsq trf gives x=1e-10 if x0 is near a bound
* BUG: make Bessel-roots function not hang and not skip roots
* io/matlab: Fix loading of mat files containing fn handles when simplify_cells=True
* BUG: make L-BFGS-B work with single precision gradient
* MAINT: stats: fix NumPy DeprecationWarnings
* BUG: sparse.linalg: Cast to intc before SuperLU
* MAINT: Use deb_system scheme to match meson\'s path inference & fix aarch64
* BUG: Fix python3.12 distutils dev.py build
* BUG: stats: remove use of `BOOST_MATH_DECLARE_SPECIAL_FUNCTIONS`
* MAINT: fix libquadmath licence
* MAINT: newton, make sure x0 is an inexact type
* MAINT: stats.CovViaEigendecomposition: fix _colorize for singular covariance
* TST: fix `TestODR.test_implicit` test failure with tolerance bump
* BUG: signal: freqz rfft grid fix
* BUG: Support sparse arrays in scipy.sparse.csgraph.laplacian
* MAINT: signal: Remove the cval parameter from the private function _pad_test.
* BLD: Avoid absolute pathnames in .pyx files
* BUG: Add back make_strictly_feasible to lsq trf.
* MAINT: should not be using np.float64() on arrays
* BUG: trust-constr Bounds exclusive
* BUG: sparse.csgraph: Support int64 indices in traversal.pyx
* BUG: add infeasibility checks to min_weight_full_bipartite_matching
* DOC, MAINT: workaround for py311 docs
* BUG: Fix typecasting problem in scipy.sparse.lil_matrix truediv
* BUG: In least_squares make initial guess sufficiently feasible w.r.t. to bounds for method \'trf\'
* BUG: fix pow method for sparrays with power zero
* BUG: set idx_dtype in sparse dia_array.tocoo- Drop patch intc.patch, included.
* Mon Oct 09 2023 ecsos - Let it build for Leap 15.6 also.
* Thu Jul 27 2023 Markéta Machová - Add upstream intc.patch to fix gh#scipy/scipy#18603
* Tue Jul 25 2023 Markéta Machová - Update to 1.11.1
* Several scipy.sparse array API improvements, including sparse.sparray, a new public base class distinct from the older sparse.spmatrix class, proper 64-bit index support, and numerous deprecations paving the way to a modern sparse array experience.
* scipy.stats added tools for survival analysis, multiple hypothesis testing, sensitivity analysis, and working with censored data.
* A new function was added for quasi-Monte Carlo integration, and linear algebra functions det and lu now accept nD-arrays.
* An axes argument was added broadly to ndimage functions, facilitating analysis of stacked image data.
* Thu Jun 29 2023 Andreas Schneider - Use sle15_python_module_pythons- Require GCC >= 8
* Fri Mar 10 2023 Martin Liška - Fix i686 tests for GCC 13 due to: https://gcc.gnu.org/gcc-13/porting_to.html#excess-precision
* Sun Feb 26 2023 Ben Greiner - Update to 1.10.1
* bug-fix release with no new features compared to 1.10.0- Drop scipy-pr17717-ro-interpn.patch
* Mon Jan 16 2023 Ben Greiner - Highlights of the 1.10.0 release
* A new dedicated datasets submodule (scipy.datasets) has been added, and is now preferred over usage of scipy.misc for dataset retrieval.
* A new scipy.interpolate.make_smoothing_spline function was added. This function constructs a smoothing cubic spline from noisy data, using the generalized cross-validation (GCV) criterion to find the tradeoff between smoothness and proximity to data points.
* scipy.stats has three new distributions, two new hypothesis tests, three new sample statistics, a class for greater control over calculations involving covariance matrices, and many other enhancements.- Add scipy-pr17717-ro-interpn.patch gh#scipy/scipy#17717
* Fixes gh#spacetelescope/gwcs#433- Provide scipy-datasets.tar.gz for pooch cache and tests without needing to download during test time.
* Wed Jan 11 2023 Guillaume GARDET - Update to version 1.10.0- Drop upstream pacthes:
* fix-tests.patch
* fix-tests-pytest72.patch
* scipy-pr17467-no-np.int0.patch
* Fri Dec 23 2022 Ben Greiner - Add scipy-pr17467-no-np.int0.patch gh#scipy/scipy#17467- Move the flavored packaganame definition so that quilt does not fail
* Thu Dec 08 2022 Dominique Leuenberger - Ensure the test flavor has a different source name than the main flavor: OBS uses the source names to create the dep-chain. With the test package having the same name as the mani flavor, all builds behind python-scipy are blocked until the test suite passed.
* Wed Dec 07 2022 Daniel Garcia - Add fix-tests-pytest72.patch to fix the tests that fails with pytest 7 gh#scipy/scipy#17296
* Fri Dec 02 2022 Daniel Garcia - Add fix-tests.patch gh#scipy/scipy#16926#issuecomment-1287507634
* Thu Oct 20 2022 Ben Greiner - Update to version 1.9.3
* SciPy 1.9.3 is a bug-fix release with no new features compared to 1.9.2.
* #3691: scipy.interpolate.UnivariateSpline segfault
* #5286: BUG: multivariate_normal returns a pdf for values outside its…
* #6551: BUG: stats: inconsistency in docs and behavior of gmean and hmean
* #9245: running scipy.interpolate.tests.test_fitpack::test_bisplev_integer_overflow…
* #12471: test_bisplev_integer_overflow: Segmentation fault (core dumped)
* #13321: Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but…
* #13730: `scipy.stats.mood` does not correct for ties
* #14019: ks_2samp throws `RuntimeWarning: overflow encountered in double_scalars`
* #14589: `shgo` error since scipy 1.8.0.dev0+1529.803e52d
* #14591: Input data validation for RectSphereBivariateSpline
* #15101: BUG: binom.pmf - RuntimeWarning: divide by zero
* #15342: BUG: scipy.optimize.minimize: Powell’s method function evaluated…
* #15964: BUG: lombscargle fails if argument is a view
* #16211: BUG: Possible bug when using winsorize on pandas data instead…
* #16459: BUG: stats.ttest_ind returns wrong p-values with permutations
* #16500: odr.Model default meta value fails with __getattr__
* #16519: BUG: Error in error message for incorrect sample dimension in…
* #16527: BUG: dimension of isuppz in syevr is mistranslated
* #16600: BUG: `KDTree`’s optional argument `eps` seems to have no…
* #16656: dtype not preserved with operations on sparse arrays
* #16751: BUG: `stats.fit` on `boltzmann` expects `bound` for `lambda`,…
* #17012: BUG: Small oversight in sparse.linalg.lsmr?
* #17020: BUG: Build failure due to problems with shebang line in cythoner.py
* #17088: BUG: stats.rayleigh.fit: returns `loc` that is inconsistent…
* #17104: BUG? Incorrect branch in `LAMV` / `_specfunc.lamv`
* #17196: DOC: keepdims in stats.mode is incorrectly documented- Move multibuild flavor \":standard\" to unflavored build- Test in parallel (pytest-xdist)
* Tue Oct 11 2022 Ben Greiner - Update to version 1.9.2
* SciPy 1.9.2 is a bug-fix release with no new features compared to 1.9.1.
* Sat Sep 10 2022 Ben Greiner - Update to version 1.9.1
* SciPy 1.9.1 is a bug-fix release with no new features compared to 1.9.0. Notably, some important meson build fixes are included.- Release 1.9.0
* Full changelog at https://docs.scipy.org/doc/scipy/release.1.9.0.html- Highlights of the 1.9.0 release:
* We have modernized our build system to use meson, substantially improving our build performance, and providing better build-time configuration and cross-compilation support,
* Added scipy.optimize.milp, new function for mixed-integer linear programming,
* Added scipy.stats.fit for fitting discrete and continuous distributions to data,
* Tensor-product spline interpolation modes were added to scipy.interpolate.RegularGridInterpolator,
* A new global optimizer (DIviding RECTangles algorithm) scipy.optimize.direct.- Switch to meson-python PEP517 build
* Mon Jul 18 2022 Ben Greiner - Keep lowercase egg-info despite setuptools 60+
* Sat May 21 2022 andy great - Update to version 1.8.1.
* Bug-fix release with no new features.
* Tue Apr 12 2022 Martin Liška - With the previously added -ffloat-store, some tests that fail on i586. Disable them.
* Tue Apr 12 2022 Martin Liška - Limit double floating point precision for x87, triggered by GCC 12. Fixes test_kolmogorov.py Fatal Python error: Floating point exception which is a double floating-point test.
* Mon Mar 28 2022 Ben Greiner - Update to version 1.8.0
* https://scipy.github.io/devdocs/release.1.8.0.html
* SciPy 1.8.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for `DeprecationWarning`s).
* A sparse array API has been added for early testing and feedback; this work is ongoing, and users should expect minor API refinements over the next few releases.
* The sparse SVD library PROPACK is now vendored with SciPy, and an interface is exposed via scipy.sparse.svds with solver=\'PROPACK\'. It is currently default-off due to potential issues on Windows that we aim to resolve in the next release, but can be optionally enabled at runtime for friendly testing with an environment variable setting of USE_PROPACK=1.
* A new scipy.stats.sampling submodule that leverages the UNU.RAN C library to sample from arbitrary univariate non-uniform continuous and discrete distributions
* All namespaces that were private but happened to miss underscores in their names have been deprecated.
* Backwards incompatible changes - SciPy has raised the minimum compiler versions to GCC 6.3 on linux and VS2019 on windows. In particular, this means that SciPy may now use C99 and C++14 features. For more details see here. - The result for empty bins for scipy.stats.binned_statistic with the builtin \'std\' metric is now nan, for consistency with np.std. - The function scipy.spatial.distance.wminkowski has been removed. To achieve the same results as before, please use the minkowski distance function with the (optional) w= keyword-argument for the given weight.
* Sat Jan 29 2022 Ben Greiner - Provide empty debuginfo extraction for :test flavor
* Sun Jan 23 2022 Ben Greiner - Update to version 1.7.3
* 3rd bugfix release since 1.7.0- Highlights from the 1.7.0 release
* A new submodule for quasi-Monte Carlo, scipy.stats.qmc, was added
* The documentation design was updated to use the same PyData-Sphinx theme as NumPy and other ecosystem libraries.
* We now vendor and leverage the Boost C++ library to enable numerous improvements for long-standing weaknesses in scipy.stats
* scipy.stats has six new distributions, eight new (or overhauled) hypothesis tests, a new function for bootstrapping, a class that enables fast random variate sampling and percentile point function evaluation, and many other enhancements.
* cdist and pdist distance calculations are faster for several metrics, especially weighted cases, thanks to a rewrite to a new C++ backend framework
* A new class for radial basis function interpolation, RBFInterpolator, was added to address issues with the Rbf class.- Enable fast part of the test suite
* Mon Jul 26 2021 Andreas Schwab - Enable openblas on riscv64
* Mon May 03 2021 Arun Persaud - update to version 1.6.3:
* Issues closed + #13772: Divide by zero in distance.yule + #13796: CI: prerelease_deps failures + #13890: TST: spatial rotation failure in (1.6.3) wheels repo (ARM64)
* Pull requests + #13755: CI: fix the matplotlib warning emitted during builing docs + #13773: BUG: Divide by zero in yule dissimilarity of constant vectors + #13799: CI/MAINT: deprecated np.typeDict + #13819: substitute np.math.factorial with math.factorial + #13895: TST: add random seeds in Rotation module
* Sun Apr 04 2021 Arun Persaud - update to version 1.6.2:
* Issues closed for 1.6.2 + #13512: `stats.gaussian_kde.evaluate` broken on S390X + #13584: rotation._compute_euler_from_matrix() creates an array with negative... + #13585: Behavior change in coo_matrix when dtype=None + #13686: delta0 argument of scipy.odr.ODR() ignored
* Pull requests for 1.6.2 + #12862: REL: put upper bounds on versions of dependencies + #13575: BUG: fix `gaussian_kernel_estimate` on S390X + #13586: BUG: sparse: Create a utility function `getdata` + #13598: MAINT, BUG: enforce contiguous layout for output array in Rotation.as_euler + #13687: BUG: fix scipy.odr to consider given delta0 argument
* Wed Mar 03 2021 Arun Persaud - update to version 1.6.1:
* Issues closed + #13072: BLD: Quadpack undefined references + #13241: Not enough values to unpack when passing tuple to `blocksize`... + #13329: Large sparse matrices of big integers lose information + #13342: fftn crashes if shape arguments are supplied as ndarrays + #13356: LSQBivariateSpline segmentation fault when quitting the Python... + #13358: scipy.spatial.transform.Rotation object can not be deepcopied... + #13408: Type of `has_sorted_indices` property + #13412: Sorting spherical Voronoi vertices leads to crash in area calculation + #13421: linear_sum_assignment - support for matrices with more than 2^31... + #13428: `stats.exponnorm.cdf` returns `nan` for small values of `K`... + #13465: KDTree.count_neighbors : 0xC0000005 error for tuple of different... + #13468: directed_hausdorff issue with shuffle + #13472: Failures on FutureWarnings with numpy 1.20.0 for lfilter, sosfilt... + #13565: BUG: 32-bit wheels repo test failure in optimize
* Pull requests + #13318: REL: prepare for SciPy 1.6.1 + #13344: BUG: fftpack doesn\'t work with ndarray shape argument + #13345: MAINT: Replace scipy.take with numpy.take in FFT function docstrings. + #13354: BUG: optimize: rename private functions to include leading underscore + #13387: BUG: Support big-endian platforms and big-endian WAVs + #13394: BUG: Fix Python crash by allocating larger array in LSQBivariateSpline + #13400: BUG: sparse: Better validation for BSR ctor + #13403: BUG: sparse: Propagate dtype through CSR/CSC constructors + #13414: BUG: maintain dtype of SphericalVoronoi regions + #13422: FIX: optimize: use npy_intp to store array dims for lsap + #13425: BUG: spatial: make Rotation picklable + #13426: BUG: `has_sorted_indices` and `has_canonical_format` should... + #13430: BUG: stats: Fix exponnorm.cdf and exponnorm.sf for small K + #13470: MAINT: silence warning generated by `spatial.directed_hausdorff` + #13473: TST: fix failures due to new FutureWarnings in NumPy 1.21.dev0 + #13479: MAINT: update directed_hausdorff Cython code + #13485: BUG: KDTree weighted count_neighbors doesn\'t work between two... + #13503: TST: fix `test_fortranfile_read_mixed_record` on big-endian... + #13518: DOC: document that pip >= 20.3.3 is needed for macOS 11 + #13520: BLD: update reqs based on oldest-supported-numpy in pyproject.toml + #13567: TST, BUG: adjust tol on test_equivalence
* Sat Jan 16 2021 Benjamin Greiner - NEP 29: Last minorversion bump deprecated Python 3.6 https://numpy.org/neps/nep-0029-deprecation_policy.html- Fix hpc setup for coinstallable python3 flavors, needs gh#openSUSE/hpc#3
* Tue Jan 05 2021 Paolo Stivanin - Update to 1.6.0:
* scipy.ndimage improvements: Fixes and ehancements to boundary extension modes for interpolation functions. Support for complex-valued inputs in many filtering and interpolation functions. New grid_mode option for scipy.ndimage.zoom to enable results consistent with scikit-image’s rescale.
* scipy.optimize.linprog has fast, new methods for large, sparse problems from the HiGHS library.
* scipy.stats improvements including new distributions, a new test, and enhancements to existing distributions and tests
* scipy.special now has improved support for 64-bit LAPACK backend
* scipy.odr now has support for 64-bit integer BLAS
* scipy.odr.ODR has gained an optional overwrite argument so that existing files may be overwritten.
* scipy.cluster.hierarchy.DisjointSet has been added for incremental connectivity queries.
* scipy.cluster.hierarchy.dendrogram return value now also includes leaf color information in leaves_color_list.
* scipy.interpolate.interp1d has a new method nearest-up, similar to the existing method nearest but rounds half-integers up instead of down.
* scipy.ndimage.convolve, scipy.ndimage.correlate and their 1d counterparts now accept both complex-valued images and/or complex-valued filter kernels. All convolution-based filters also now accept complex-valued inputs
* scipy.optimize.linprog has fast, new methods for large, sparse problems from the HiGHS C++ library
* scipy.optimize.quadratic_assignment has been added for approximate solution of the quadratic assignment problem.
* scipy.optimize.linear_sum_assignment now has a substantially reduced overhead for small cost matrix sizes
* scipy.optimize.least_squares has improved performance when the user provides the jacobian as a sparse jacobian already in csr_matrix format
* scipy.signal.gammatone has been added to design FIR or IIR filters that model the human auditory system.
* scipy.signal.iircomb has been added to design IIR peaking/notching comb filters that can boost/attenuate a frequency from a signal.
* scipy.signal.sosfilt performance has been improved to avoid some previously- observed slowdowns
* scipy.signal.windows.taylor has been added–the Taylor window function is commonly used in radar digital signal processing
* scipy.signal.gauss_spline now supports list type input for consistency with other related SciPy functions
* scipy.signal.correlation_lags has been added to allow calculation of the lag/ displacement indices array for 1D cross-correlation.
* Fri Dec 18 2020 andy great - Update to version 1.5.4.
* Bug fix release with no new feature.- Updates for 1.5.3.
* Bug fix release with no new feature.
* Thu Aug 13 2020 Marketa Calabkova - Update to 1.5.2
* wrappers for more than a dozen new LAPACK routines are now available in scipy.linalg.lapack
* Improved support for leveraging 64-bit integer size from linear algebra backends
* addition of the probability distribution for two-sided one-sample Kolmogorov-Smirnov tests
* see upstream changelog for more detailed info- Drop breaking patch no_implicit_decl.patch
* the problem is with lapacke
* Thu Mar 19 2020 Martin Liška - Add -std=legacy in order to build with GCC10: https://gcc.gnu.org/gcc-10/porting_to.html#argument-mismatch
* Mon Mar 16 2020 Egbert Eich - \'umpfack\' is a runtime dependency of scipy. No build time dependency to suitesparse is required (jsc#SLE-11732).- Get rid of site.cfg entirely as it is used nowhwere in scipy.
* Wed Jan 15 2020 Tomáš Chvátal - Fix pybind11 devel dependency to match real name
* Fri Dec 20 2019 Todd R - Update to 1.4.1
* SciPy 1.4.1 is a bug-fix release with no new features compared to 1.4.0. Importantly, it aims to fix a problem where an older version of pybind11 may cause a segmentation fault when imported alongside incompatible libraries.
* Tue Dec 17 2019 Todd R - Update to 1.4.0 + Highlights of this release
* a new submodule, `scipy.fft`, now supersedes `scipy.fftpack`; this means support for ``long double`` transforms, faster multi-dimensional transforms, improved algorithm time complexity, release of the global intepreter lock, and control over threading behavior
* support for ``pydata/sparse`` arrays in `scipy.sparse.linalg`
* substantial improvement to the documentation and functionality of several `scipy.special` functions, and some new additions
* the generalized inverse Gaussian distribution has been added to `scipy.stats`
* an implementation of the Edmonds-Karp algorithm in `scipy.sparse.csgraph.maximum_flow`
* `scipy.spatial.SphericalVoronoi` now supports n-dimensional input, has linear memory complexity, improved performance, and supports single-hemisphere generators + New features > Infrastructure
* Documentation can now be built with ``runtests.py --doc``
* A ``Dockerfile`` is now available in the ``scipy/scipy-dev`` repository to acilitate getting started with SciPy development. > `scipy.constants` improvements
* `scipy.constants` has been updated with the CODATA 2018 constants. > `scipy.fft` added
* `scipy.fft` is a new submodule that supersedes the `scipy.fftpack` submodule. or the most part, this is a drop-in replacement for ``numpy.fft`` and scipy.fftpack` alike. With some important differences, `scipy.fft`:
* uses NumPy\'s conventions for real transforms (``rfft``). This means the eturn value is a complex array, half the size of the full ``fft`` output. his is different from the output of ``fftpack`` which returned a real array epresenting complex components packed together.
* the inverse real to real transforms (``idct`` and ``idst``) are normalized or ``norm=None`` in thesame way as ``ifft``. This means the identity `idct(dct(x)) == x`` is now ``True`` for all norm modes.
* does not include the convolutions or pseudo-differential operators rom ``fftpack``.
* This submodule is based on the ``pypocketfft`` library, developed by the uthor of ``pocketfft`` which was recently adopted by NumPy as well. `pypocketfft`` offers a number of advantages over fortran ``FFTPACK``:
* support for long double (``np.longfloat``) precision transforms.
* faster multi-dimensional transforms using vectorisation
* Bluestein’s algorithm removes the worst-case ``O(n^2)`` complexity of `FFTPACK``
* the global interpreter lock (``GIL``) is released during transforms
* optional multithreading of multi-dimensional transforms via the ``workers`` rgument
* Note that `scipy.fftpack` has not been deprecated and will continue to be aintained but is now considered legacy. New code is recommended to use scipy.fft` instead, where possible. > `scipy.fftpack` improvements
* `scipy.fftpack` now uses pypocketfft to perform its FFTs, offering the same peed and accuracy benefits listed for scipy.fft above but without the mproved API. > `scipy.integrate` improvements
* The function `scipy.integrate.solve_ivp` now has an ``args`` argument. his allows the user-defined functions passed to the function to have dditional parameters without having to create wrapper functions or ambda expressions for them.
* `scipy.integrate.solve_ivp` can now return a ``y_events`` attribute epresenting the solution of the ODE at event times
* New ``OdeSolver`` is implemented --- ``DOP853``. This is a high-order explicit unge-Kutta method originally implemented in Fortran. Now we provide a pure ython implementation usable through ``solve_ivp`` with all its features.
* `scipy.integrate.quad` provides better user feedback when break points are pecified with a weighted integrand.
* `scipy.integrate.quad_vec` is now available for general purpose integration f vector-valued functions > `scipy.interpolate` improvements
* `scipy.interpolate.pade` now handles complex input data gracefully
* `scipy.interpolate.Rbf` can now interpolate multi-dimensional functions > `scipy.io` improvements
* `scipy.io.wavfile.read` can now read data from a `WAV` file that has a alformed header, similar to other modern `WAV` file parsers
* `scipy.io.FortranFile` now has an expanded set of available ``Exception`` lasses for handling poorly-formatted files > `scipy.linalg` improvements
* The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct esults for complex-valued matrices. Before this, the function only returned orrect values for real-valued matrices.
* New boolean keyword argument ``check_finite`` for `scipy.linalg.norm`; whether o check that the input matrix contains only finite numbers. Disabling may ive a performance gain, but may result in problems (crashes, non-termination) f the inputs do contain infinities or NaNs.
* `scipy.linalg.solve_triangular` has improved performance for a C-ordered riangular matrix
* ``LAPACK`` wrappers have been added for ``?geequ``, ``?geequb``, ``?syequb``, nd ``?heequb``
* Some performance improvements may be observed due to an internal optimization n operations involving LAPACK routines via ``_compute_lwork``. This is articularly true for operations on small arrays.
* Block ``QR`` wrappers are now available in `scipy.linalg.lapack` > `scipy.optimize` improvements
* It is now possible to use linear and non-linear constraints with scipy.optimize.differential_evolution`.
* `scipy.optimize.linear_sum_assignment` has been re-written in C++ to improve erformance, and now allows input costs to be infinite.
* A ``ScalarFunction.fun_and_grad`` method was added for convenient simultaneous etrieval of a function and gradient evaluation
* `scipy.optimize.minimize` ``BFGS`` method has improved performance by avoiding uplicate evaluations in some cases
* Better user feedback is provided when an objective function returns an array nstead of a scalar. > `scipy.signal` improvements
* Added a new function to calculate convolution using the overlap-add method, amed `scipy.signal.oaconvolve`. Like `scipy.signal.fftconvolve`, this unction supports specifying dimensions along which to do the convolution.
* `scipy.signal.cwt` now supports complex wavelets.
* The implementation of ``choose_conv_method`` has been updated to reflect the ew FFT implementation. In addition, the performance has been significantly mproved (with rather drastic improvements in edge cases).
* The function ``upfirdn`` now has a ``mode`` keyword argument that can be used o select the signal extension mode used at the signal boundaries. These modes re also available for use in ``resample_poly`` via a newly added ``padtype`` rgument.
* `scipy.signal.sosfilt` now benefits from Cython code for improved performance
* `scipy.signal.resample` should be more efficient by leveraging ``rfft`` when ossible > `scipy.sparse` improvements
* It is now possible to use the LOBPCG method in `scipy.sparse.linalg.svds`.
* `scipy.sparse.linalg.LinearOperator` now supports the operation ``rmatmat`` or adjoint matrix-matrix multiplication, in addition to ``rmatvec``.
* Multiple stability updates enable float32 support in the LOBPCG eigenvalue olver for symmetric and Hermitian eigenvalues problems in `scipy.sparse.linalg.lobpcg``.
* A solver for the maximum flow problem has been added as scipy.sparse.csgraph.maximum_flow`.
* `scipy.sparse.csgraph.maximum_bipartite_matching` now allows non-square inputs, o longer requires a perfect matching to exist, and has improved performance.
* `scipy.sparse.lil_matrix` conversions now perform better in some scenarios
* Basic support is available for ``pydata/sparse`` arrays in scipy.sparse.linalg`
* `scipy.sparse.linalg.spsolve_triangular` now supports the ``unit_diagonal`` rgument to improve call signature similarity with its dense counterpart, scipy.linalg.solve_triangular`
* ``assertAlmostEqual`` may now be used with sparse matrices, which have added upport for ``__round__`` > `scipy.spatial` improvements
* The bundled Qhull library was upgraded to version 2019.1, fixing several ssues. Scipy-specific patches are no longer applied to it.
* `scipy.spatial.SphericalVoronoi` now has linear memory complexity, improved erformance, and supports single-hemisphere generators. Support has also been dded for handling generators that lie on a great circle arc (geodesic input) nd for generators in n-dimensions.
* `scipy.spatial.transform.Rotation` now includes functions for calculation of a ean rotation, generation of the 3D rotation groups, and reduction of rotations ith rotational symmetries.
* `scipy.spatial.transform.Slerp` is now callable with a scalar argument
* `scipy.spatial.voronoi_plot_2d` now supports furthest site Voronoi diagrams
* `scipy.spatial.Delaunay` and `scipy.spatial.Voronoi` now have attributes or tracking whether they are furthest site diagrams > `scipy.special` improvements
* The Voigt profile has been added as `scipy.special.voigt_profile`.
* A real dispatch has been added for the Wright Omega function `scipy.special.wrightomega`).
* The analytic continuation of the Riemann zeta function has been added. (The iemann zeta function is the one-argument variant of `scipy.special.zeta`.)
* The complete elliptic integral of the first kind (`scipy.special.ellipk`) is ow available in `scipy.special.cython_special`.
* The accuracy of `scipy.special.hyp1f1` for real arguments has been improved.
* The documentation of many functions has been improved. > `scipy.stats` improvements
* `scipy.stats.multiscale_graphcorr` added as an independence test that perates on high dimensional and nonlinear data sets. It has higher statistical ower than other `scipy.stats` tests while being the only one that operates on ultivariate data.
* The generalized inverse Gaussian distribution (`scipy.stats.geninvgauss`) has een added.
* It is now possible to efficiently reuse `scipy.stats.binned_statistic_dd` ith new values by providing the result of a previous call to the function.
* `scipy.stats.hmean` now handles input with zeros more gracefully.
* The beta-binomial distribution is now available in `scipy.stats.betabinom`.
* `scipy.stats.zscore`, `scipy.stats.circmean`, `scipy.stats.circstd`, and scipy.stats.circvar` now support the ``nan_policy`` argument for enhanced andling of ``NaN`` values
* `scipy.stats.entropy` now accepts an ``axis`` argument
* `scipy.stats.gaussian_kde.resample` now accepts a ``seed`` argument to empower eproducibility
* `scipy.stats.kendalltau` performance has improved, especially for large inputs, ue to improved cache usage
* `scipy.stats.truncnorm` distribution has been rewritten to support much wider ails + Deprecated features > `scipy` deprecations
* Support for NumPy functions exposed via the root SciPy namespace is deprecated nd will be removed in 2.0.0. For example, if you use ``scipy.rand`` or `scipy.diag``, you should change your code to directly use `numpy.random.default_rng`` or ``numpy.diag``, respectively. hey remain available in the currently continuing Scipy 1.x release series.
* The exception to this rule is using ``scipy.fft`` as a function -- mod:`scipy.fft` is now meant to be used only as a module, so the ability to all ``scipy.fft(...)`` will be removed in SciPy 1.5.0.
* In `scipy.spatial.Rotation` methods ``from_dcm``, ``as_dcm`` were renamed to `from_matrix``, ``as_matrix`` respectively. The old names will be removed in ciPy 1.6.0.
* Method ``Rotation.match_vectors`` was deprecated in favor of `Rotation.align_vectors``, which provides a more logical and eneral API to the same functionality. The old method ill be removed in SciPy 1.6.0. + Backwards incompatible changes > `scipy.special` changes
* The deprecated functions ``hyp2f0``, ``hyp1f2``, and ``hyp3f0`` have been emoved.
* The deprecated function ``bessel_diff_formula`` has been removed.
* The function ``i0`` is no longer registered with ``numpy.dual``, so that `numpy.dual.i0`` will unconditionally refer to the NumPy version regardless f whether `scipy.special` is imported.
* The function ``expn`` has been changed to return ``nan`` outside of its omain of definition (``x, n < 0``) instead of ``inf``. > `scipy.sparse` changes
* Sparse matrix reshape now raises an error if shape is not two-dimensional, rather than guessing what was meant. The behavior is now the same as before ciPy 1.1.0.
* ``CSR`` and ``CSC`` sparse matrix classes should now return empty matrices f the same type when indexed out of bounds. Previously, for some versions f SciPy, this would raise an ``IndexError``. The change is largely motivated y greater consistency with ``ndarray`` and ``numpy.matrix`` semantics. > `scipy.signal` changes
* `scipy.signal.resample` behavior for length-1 signal inputs has been ixed to output a constant (DC) value rather than an impulse, consistent with he assumption of signal periodicity in the FFT method.
* `scipy.signal.cwt` now performs complex conjugation and time-reversal of avelet data, which is a backwards-incompatible bugfix for ime-asymmetric wavelets. > `scipy.stats` changes
* `scipy.stats.loguniform` added with better documentation as (an alias for `scipy.stats.reciprocal``). ``loguniform`` generates random variables hat are equally likely in the log space; e.g., ``1``, ``10`` and ``100`` re all equally likely if ``loguniform(10
*
* 0, 10
*
* 2).rvs()`` is used. + Other changes
* The ``LSODA`` method of `scipy.integrate.solve_ivp` now correctly detects stiff roblems.
* `scipy.spatial.cKDTree` now accepts and correctly handles empty input data
* `scipy.stats.binned_statistic_dd` now calculates the standard deviation tatistic in a numerically stable way.
* `scipy.stats.binned_statistic_dd` now throws an error if the input data ontains either ``np.nan`` or ``np.inf``. Similarly, in `scipy.stats` now all ontinuous distributions\' ``.fit()`` methods throw an error if the input data ontain any instance of either ``np.nan`` or ``np.inf``.- Rebase no_implicit_decl.patch
* Tue Dec 10 2019 Todd R - Update to 1.3.3
* Fix deadlock on osx for python 3.8
* MAINT: TST: Skip tests with multiprocessing that use \"spawn\" start method
* Tue Nov 19 2019 Todd R - Update to 1.3.2
* Bug in unique_roots in scipy.signal.signaltools.py for roots...
* Optimizers reporting success when the minimum is NaN
* ValueError raised if scipy.sparse.linalg.expm recieves array...
* linprog(method=\'revised simplex\') doctest bug
* Graph shortest path with Floyd-Warshall removes explicit zeros.
* BUG: stats: Formula for the variance of the noncentral F distribution...
* BUG: Assignation issues in csr_matrix with fancy indexing
* root_scalar fails when passed a function wrapped with functools.lru_cache
* CI: travis osx build failure
* macOS build failure in SuperLU on maintenance/1.3.x
* Typo in sp.stats.wilcoxon docstring
* Fri Aug 16 2019 Todd R - Update to 1.3.1
* BUG: Empty data handling of (c)KDTrees
* lsoda fails to detect stiff problem when called from solve_ivp
* sparse matrices indexing with scipy 1.3
* Exception in loadarff with quoted nominal attributes in scipy...
* DOC/REL: Some sections of the release notes are not nested correctly.
* BUG: optimize: `linprog` failing TestLinprogSimplexBland::test_unbounded_below_no_presolve_corrected
* TST: Travis CI fails (with pytest 5.0 ?)
* CircleCI doc build failing on new warnings
* Scipy 1.3.0 build broken in AIX
* BUG: scipy.spatial.HalfspaceIntersection works incorrectly
* BUG: cKDTree GIL handling is incorrect
* TST: master branch CI failures
* BUG: ckdtree query_ball_point errors on discontiguous input
* BUG: No warning on PchipInterpolator changing from bernstein base to local power base
* Sun May 19 2019 Todd R - Update to 1.3.0 + Highlights of this release
* Three new ``stats`` functions, a rewrite of ``pearsonr``, and an exact computation of the Kolmogorov-Smirnov two-sample test
* A new Cython API for bounded scalar-function root-finders in `scipy.optimize`
* Substantial ``CSR`` and ``CSC`` sparse matrix indexing performance improvements
* Added support for interpolation of rotations with continuous angular rate and acceleration in ``RotationSpline`` + New features > `scipy.interpolate` improvements
* A new class ``CubicHermiteSpline`` is introduced. It is a piecewise-cubic interpolator which matches observed values and first derivatives. Existing cubic interpolators ``CubicSpline``, ``PchipInterpolator`` and ``Akima1DInterpolator`` were made subclasses of ``CubicHermiteSpline``. > `scipy.io` improvements
* For the Attribute-Relation File Format (ARFF) `scipy.io.arff.loadarff` now supports relational attributes.
* `scipy.io.mmread` can now parse Matrix Market format files with empty lines. > `scipy.linalg` improvements
* Added wrappers for ``?syconv`` routines, which convert a symmetric matrix given by a triangular matrix factorization into two matrices and vice versa.
* `scipy.linalg.clarkson_woodruff_transform` now uses an algorithm that leverages sparsity. This may provide a 60-90 percent speedup for dense input matrices. Truly sparse input matrices should also benefit from the improved sketch algorithm, which now correctly runs in ``O(nnz(A))`` time.
* Added new functions to calculate symmetric Fiedler matrices and Fiedler companion matrices, named `scipy.linalg.fiedler` and `scipy.linalg.fiedler_companion`, respectively. These may be used for root finding. > `scipy.ndimage` improvements
* Gaussian filter performances may improve by an order of magnitude in some cases, thanks to removal of a dependence on ``np.polynomial``. This may impact `scipy.ndimage.gaussian_filter` for example. > `scipy.optimize` improvements
* The `scipy.optimize.brute` minimizer obtained a new keyword ``workers``, which can be used to parallelize computation.
* A Cython API for bounded scalar-function root-finders in `scipy.optimize` is available in a new module `scipy.optimize.cython_optimize` via ``cimport``. This API may be used with ``nogil`` and ``prange`` to loop over an array of function arguments to solve for an array of roots more quickly than with pure Python.
* ``\'interior-point\'`` is now the default method for ``linprog``, and ``\'interior-point\'`` now uses SuiteSparse for sparse problems when the required scikits (scikit-umfpack and scikit-sparse) are available. On benchmark problems (gh-10026), execution time reductions by factors of 2-3 were typical. Also, a new ``method=\'revised simplex\'`` has been added. It is not as fast or robust as ``method=\'interior-point\'``, but it is a faster, more robust, and equally accurate substitute for the legacy ``method=\'simplex\'``.
* ``differential_evolution`` can now use a ``Bounds`` class to specify the bounds for the optimizing argument of a function.
* `scipy.optimize.dual_annealing` performance improvements related to vectorisation of some internal code. > `scipy.signal` improvements
* Two additional methods of discretization are now supported by `scipy.signal.cont2discrete`: ``impulse`` and ``foh``.
* `scipy.signal.firls` now uses faster solvers
* `scipy.signal.detrend` now has a lower physical memory footprint in some cases, which may be leveraged using the new ``overwrite_data`` keyword argument
* `scipy.signal.firwin` ``pass_zero`` argument now accepts new string arguments that allow specification of the desired filter type: ``\'bandpass\'``, ``\'lowpass\'``, ``\'highpass\'``, and ``\'bandstop\'``
* `scipy.signal.sosfilt` may have improved performance due to lower retention of the global interpreter lock (GIL) in algorithm > `scipy.sparse` improvements
* A new keyword was added to ``csgraph.dijsktra`` that allows users to query the shortest path to ANY of the passed in indices, as opposed to the shortest path to EVERY passed index.
* `scipy.sparse.linalg.lsmr` performance has been improved by roughly 10 percent on large problems
* Improved performance and reduced physical memory footprint of the algorithm used by `scipy.sparse.linalg.lobpcg`
* ``CSR`` and ``CSC`` sparse matrix fancy indexing performance has been improved substantially > `scipy.spatial` improvements
* `scipy.spatial.ConvexHull` now has a ``good`` attribute that can be used alongsize the ``QGn`` Qhull options to determine which external facets of a convex hull are visible from an external query point.
* `scipy.spatial.cKDTree.query_ball_point` has been modernized to use some newer Cython features, including GIL handling and exception translation. An issue with ``return_sorted=True`` and scalar queries was fixed, and a new mode named ``return_length`` was added. ``return_length`` only computes the length of the returned indices list instead of allocating the array every time.
* `scipy.spatial.transform.RotationSpline` has been added to enable interpolation of rotations with continuous angular rates and acceleration > `scipy.stats` improvements
* Added a new function to compute the Epps-Singleton test statistic, `scipy.stats.epps_singleton_2samp`, which can be applied to continuous and discrete distributions.
* New functions `scipy.stats.median_absolute_deviation` and `scipy.stats.gstd` (geometric standard deviation) were added. The `scipy.stats.combine_pvalues` method now supports ``pearson``, ``tippett`` and ``mudholkar_george`` pvalue combination methods.
* The `scipy.stats.ortho_group` and `scipy.stats.special_ortho_group` ``rvs(dim)`` functions\' algorithms were updated from a ``O(dim^4)`` implementation to a ``O(dim^3)`` which gives large speed improvements for ``dim>100``.
* A rewrite of `scipy.stats.pearsonr` to use a more robust algorithm, provide meaningful exceptions and warnings on potentially pathological input, and fix at least five separate reported issues in the original implementation.
* Improved the precision of ``hypergeom.logcdf`` and ``hypergeom.logsf``.
* Added exact computation for Kolmogorov-Smirnov (KS) two-sample test, replacing the previously approximate computation for the two-sided test `stats.ks_2samp`. Also added a one-sided, two-sample KS test, and a keyword ``alternative`` to `stats.ks_2samp`. + Backwards incompatible changes > `scipy.interpolate` changes
* Functions from ``scipy.interpolate`` (``spleval``, ``spline``, ``splmake``, and ``spltopp``) and functions from ``scipy.misc`` (``bytescale``, ``fromimage``, ``imfilter``, ``imread``, ``imresize``, ``imrotate``, ``imsave``, ``imshow``, ``toimage``) have been removed. The former set has been deprecated since v0.19.0 and the latter has been deprecated since v1.0.0. Similarly, aliases from ``scipy.misc`` (``comb``, ``factorial``, ``factorial2``, ``factorialk``, ``logsumexp``, ``pade``, ``info``, ``source``, ``who``) which have been deprecated since v1.0.0 are removed. `SciPy documentation for v1.1.0 `__ can be used to track the new import locations for the relocated functions. > `scipy.linalg` changes
* For ``pinv``, ``pinv2``, and ``pinvh``, the default cutoff values are changed for consistency (see the docs for the actual values). > `scipy.optimize` changes
* The default method for ``linprog`` is now ``\'interior-point\'``. The method\'s robustness and speed come at a cost: solutions may not be accurate to machine precision or correspond with a vertex of the polytope defined by the constraints. To revert to the original simplex method, include the argument ``method=\'simplex\'``. > `scipy.stats` changes
* Previously, ``ks_2samp(data1, data2)`` would run a two-sided test and return the approximated p-value. The new signature, ``ks_2samp(data1, data2, alternative=\"two-sided\", method=\"auto\")``, still runs the two-sided test by default but returns the exact p-value for small samples and the approximated value for large samples. ``method=\"asymp\"`` would be equivalent to the old version but ``auto`` is the better choice. + Other changes
* Our tutorial has been expanded with a new section on global optimizers
* There has been a rework of the ``stats.distributions`` tutorials.
* `scipy.optimize` now correctly sets the convergence flag of the result to ``CONVERR``, a convergence error, for bounded scalar-function root-finders if the maximum iterations has been exceeded, ``disp`` is false, and ``full_output`` is true.
* `scipy.optimize.curve_fit` no longer fails if ``xdata`` and ``ydata`` dtypes differ; they are both now automatically cast to ``float64``.
* `scipy.ndimage` functions including ``binary_erosion``, ``binary_closing``, and ``binary_dilation`` now require an integer value for the number of iterations, which alleviates a number of reported issues.
* Fixed normal approximation in case ``zero_method == \"pratt\"`` in `scipy.stats.wilcoxon`.
* Fixes for incorrect probabilities, broadcasting issues and thread-safety related to stats distributions setting member variables inside ``_argcheck()``.
* `scipy.optimize.newton` now correctly raises a ``RuntimeError``, when default arguments are used, in the case that a derivative of value zero is obtained, which is a special case of failing to converge.
* A draft toolchain roadmap is now available, laying out a compatibility plan including Python versions, C standards, and NumPy versions.- Python 2 is no longer supported
* Tue Mar 19 2019 Todd R - Update to 1.2.1
* SyntaxError: Non-ASCII character \'xe2\' in file scipy/stats/_continuous_distns.py on line 3346, but no encoding declared
* Version 1.2.0 introduces `too many indices for array` error in `optimize.newton()`
* scipy.stats.gaussian_kde normalizes the weights keyword argument externally.
* scipy.linalg.qr_update gives NaN result
* CI: Is scipy.scipy Windows Python36-32bit-full working?
* Fri Mar 01 2019 Matej Cepl - Use direct number in the Version tag
* Tue Feb 12 2019 Egbert Eich 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.
* Mon Jan 21 2019 Jan Engelhardt - Trim filler wording from description.
* Fri Jan 18 2019 eichAATTsuse.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 jjollyAATTsuse.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 Todd R - 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 toddrme2178AATTgmail.com- Fix build on SLE
* Mon May 07 2018 toddrme2178AATTgmail.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 arunAATTgmx.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 schwabAATTsuse.de- Don\'t use openblas on m68k and riscv64
* Thu Oct 26 2017 toddrme2178AATTgmail.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 toddrme2178AATTgmail.com- More rpmlint fixes.
* Mon Jul 10 2017 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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 toddrme2178AATTgmail.com- Remove Cython subpackage. The sources are not as cleanly separated as the changelog implied.
* Mon Jul 27 2015 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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 toddrme2178AATTgmail.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