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| Name: python38-scipy-gnu-hpc | Distribution: openSUSE Tumbleweed |
| Version: 1.10.0 | Vendor: openSUSE |
| Release: 1.1 | Build date: Sat Jan 28 20:03:16 2023 |
| Group: Productivity/Scientific/Other | Build host: obs-arm-11 |
| Size: 202 | Source RPM: python-scipy_1_10_0-gnu-hpc-1.10.0-1.1.src.rpm |
| Packager: http://bugs.opensuse.org | |
| Url: https://www.scipy.org | |
| Summary: Dependency package for python38-scipy_1_10_0-gnu-hpc | |
python38-scipy: Scientific Tools for Python The package python38-scipy-gnu-hpc provides the dependency to get binary package python38-scipy_1_10_0-gnu-hpc. When this package gets updated it installs the latest version of python38-scipy_1_10_0-gnu-hpc.
BSD-3-Clause AND LGPL-2.0-or-later AND BSL-1.0
* Mon Jan 16 2023 Ben Greiner <code@bnavigator.de>
- 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 <guillaume.gardet@opensuse.org>
- 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 <code@bnavigator.de>
- 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 <dimstar@opensuse.org>
- 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 <daniel.garcia@suse.com>
- Add fix-tests-pytest72.patch to fix the tests that fails with pytest 7
gh#scipy/scipy#17296
* Fri Dec 02 2022 Daniel Garcia <daniel.garcia@suse.com>
- Add fix-tests.patch gh#scipy/scipy#16926#issuecomment-1287507634
* Thu Oct 20 2022 Ben Greiner <code@bnavigator.de>
- 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 <code@bnavigator.de>
- 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 <code@bnavigator.de>
- 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 <code@bnavigator.de>
- Keep lowercase egg-info despite setuptools 60+
* Sat May 21 2022 andy great <andythe_great@pm.me>
- Update to version 1.8.1.
* Bug-fix release with no new features.
* Tue Apr 12 2022 Martin Liška <mliska@suse.cz>
- With the previously added -ffloat-store, some tests that fail on i586.
Disable them.
* Tue Apr 12 2022 Martin Liška <mliska@suse.cz>
- 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 <code@bnavigator.de>
- 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 <code@bnavigator.de>
- Provide empty debuginfo extraction for :test flavor
* Sun Jan 23 2022 Ben Greiner <code@bnavigator.de>
- 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 <schwab@suse.de>
- Enable openblas on riscv64
* Mon May 03 2021 Arun Persaud <arun@gmx.de>
- 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 <arun@gmx.de>
- 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 <arun@gmx.de>
- 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 <code@bnavigator.de>
- 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 <info@paolostivanin.com>
- 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 <andythe_great@pm.me>
- 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 <mcalabkova@suse.com>
- 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 <mliska@suse.cz>
- 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 <eich@suse.com>
- '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 <tchvatal@suse.com>
- Fix pybind11 devel dependency to match real name
* Fri Dec 20 2019 Todd R <toddrme2178@gmail.com>
- 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 <toddrme2178@gmail.com>
- 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 <toddrme2178@gmail.com>
- 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 <toddrme2178@gmail.com>
- 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 <toddrme2178@gmail.com>
- 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 <toddrme2178@gmail.com>
- 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 <https://docs.scipy.org/doc/scipy-1.1.0/reference/misc.html>`__
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 <toddrme2178@gmail.com>
- 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 <mcepl@suse.com>
- Use direct number in the Version tag
* Tue Feb 12 2019 Egbert Eich <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.
* Mon Jan 21 2019 Jan Engelhardt <jengelh@inai.de>
- Trim filler wording from description.
* 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,
/usr/share/doc/packages/python38-scipy-gnu-hpc /usr/share/doc/packages/python38-scipy-gnu-hpc/README.python38-scipy_1_10_0-gnu-hpc
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