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| Name: python311-scipy | Distribution: SUSE Linux Framework One |
| Version: 1.11.4 | Vendor: SUSE LLC <https://www.suse.com/> |
| Release: slfo.1.1.19 | Build date: Mon Jan 22 13:20:49 2024 |
| Group: Unspecified | Build host: reproducible |
| Size: 102876086 | Source RPM: python-scipy-1.11.4-slfo.1.1.19.src.rpm |
| Packager: https://www.suse.com/ | |
| Url: https://www.scipy.org | |
| Summary: Scientific Tools for Python | |
Scipy is open-source software for mathematics, science, and engineering. The core library is NumPy which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many numerical routines such as for numerical integration and optimization.
BSD-3-Clause AND LGPL-2.0-or-later AND BSL-1.0
* Mon Jan 22 2024 daniel.garcia@suse.com
- Disable broken tests in s390x, gh#scipy/scipy#18878, bsc#1218608
* Tue Nov 21 2023 steven.kowalik@suse.com
- 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@opensuse.org
- Let it build for Leap 15.6 also.
* Thu Jul 27 2023 mmachova@suse.com
- Add upstream intc.patch to fix gh#scipy/scipy#18603
* Tue Jul 25 2023 mmachova@suse.com
- 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 asn@cryptomilk.org
- Use sle15_python_module_pythons
- Require GCC >= 8
* Fri Mar 10 2023 mliska@suse.cz
- Fix i686 tests for GCC 13 due to:
https://gcc.gnu.org/gcc-13/porting_to.html#excess-precision
* Sun Feb 26 2023 code@bnavigator.de
- 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 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@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 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 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@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@suse.com
- Add fix-tests.patch gh#scipy/scipy#16926#issuecomment-1287507634
* Thu Oct 20 2022 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 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 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 code@bnavigator.de
- Keep lowercase egg-info despite setuptools 60+
* Sat May 21 2022 andythe_great@pm.me
- Update to version 1.8.1.
* Bug-fix release with no new features.
* Tue Apr 12 2022 mliska@suse.cz
- With the previously added -ffloat-store, some tests that fail on i586.
Disable them.
* Tue Apr 12 2022 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 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 code@bnavigator.de
- Provide empty debuginfo extraction for :test flavor
* Sun Jan 23 2022 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 schwab@suse.de
- Enable openblas on riscv64
* Mon May 03 2021 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@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@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 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 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 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 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 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 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 tchvatal@suse.com
- Fix pybind11 devel dependency to match real name
* Fri Dec 20 2019 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 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 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 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 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 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 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 mcepl@suse.com
- Use direct number in the Version tag
* Tue Feb 12 2019 eich@suse.com
bsc#1130564: Apply update from the openSUSE package
- Properly create and tear down default version links when the
HPC master packages are installed/uninstalled.
- Make use of %hpc_modules_init to make modules also known to
client.
- Module file:
* remove PATH element. Package has no binary,
* make cosmetic changes.
- Remove use of %%python_module in dependency.
* Mon Jan 21 2019 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,
* Sat Dec 22 2018 toddrme2178@gmail.com
- Update to version 1.2.0
* Many changes. Please see changelog at:
https://github.com/scipy/scipy/blob/v1.2.0/doc/release/1.2.0-notes.rst
* Fri May 11 2018 toddrme2178@gmail.com
- Fix build on SLE
* Mon May 07 2018 toddrme2178@gmail.com
- Update to version 1.1.0
* Many changes. Please see changelog at:
https://github.com/scipy/scipy/blob/v1.1.0/doc/release/1.1.0-notes.rst
* Sun Apr 01 2018 arun@gmx.de
- update to version 1.0.1:
* Issues closed for 1.0.1
+ #7493: ndimage.morphology functions are broken with numpy 1.13.0
+ #8118: minimize_cobyla broken if disp=True passed
+ #8142: scipy-v1.0.0 pdist with metric=`minkowski` raises
`ValueError:...
+ #8173: scipy.stats.ortho_group produces all negative
determinants...
+ #8207: gaussian_filter seg faults on float16 numpy arrays
+ #8234: scipy.optimize.linprog interior-point presolve bug with
trivial...
+ #8243: Make csgraph importable again via from scipy.sparse
import*
+ #8320: scipy.root segfaults with optimizer 'lm'
* Pull requests for 1.0.1
+ #8068: BUG: fix numpy deprecation test failures
+ #8082: BUG: fix solve_lyapunov import
+ #8144: MRG: Fix for cobyla
+ #8150: MAINT: resolve UPDATEIFCOPY deprecation errors
+ #8156: BUG: missing check on minkowski w kwarg
+ #8187: BUG: Sign of elements in random orthogonal 2D matrices in
"ortho_group_gen"...
+ #8197: CI: uninstall oclint
+ #8215: Fixes Numpy datatype compatibility issues
+ #8237: BUG: optimize: fix bug when variables fixed by bounds are
inconsistent...
+ #8248: BUG: declare "gfk" variable before call of terminate() in
newton-cg
+ #8280: REV: reintroduce csgraph import in scipy.sparse
+ #8322: MAINT: prevent scipy.optimize.root segfault closes #8320
+ #8334: TST: stats: don't use exact equality check for hdmedian
test
+ #8477: BUG: signal/signaltools: fix wrong refcounting in
PyArray_OrderFilterND
+ #8530: BUG: linalg: Fixed typo in flapack.pyf.src.
+ #8566: CI: Temporarily pin Cython version to 0.27.3
+ #8573: Backports for 1.0.1
+ #8581: Fix Cython 0.28 build break of qhull.pyx
* Tue Feb 13 2018 schwab@suse.de
- Don't use openblas on m68k and riscv64
* Thu Oct 26 2017 toddrme2178@gmail.com
- Update to version 1.0.0
* Many changes. Please see changelog at:
https://github.com/scipy/scipy/blob/v1.0.0/doc/release/1.0.0-notes.rst#why-1-0-now
- Rebase no_implicit_decl.patch
* Tue Jul 11 2017 toddrme2178@gmail.com
- More rpmlint fixes.
* Mon Jul 10 2017 toddrme2178@gmail.com
- Update to version 0.19.1
* #7214: Memory use in integrate.quad in scipy-0.19.0
* #7258: linalg.matrix_balance gives wrong transformation matrix
* #7262: Segfault in daily testing
* #7273: scipy.interpolate._bspl.evaluate_spline gets wrong type
* #7335: scipy.signal.dlti(A,B,C,D).freqresp() fails
* #7211: BUG: convolve may yield inconsistent dtypes with method changed
* #7216: BUG: integrate: fix refcounting bug in quad()
* #7229: MAINT: special: Rewrite a test of wrightomega
* #7261: FIX: Corrected the transformation matrix permutation
* #7265: BUG: Fix broken axis handling in spectral functions
* #7266: FIX 7262: ckdtree crashes in query_knn.
* #7279: Upcast half- and single-precision floats to doubles in BSpline...
* #7336: BUG: Fix signal.dfreqresp for StateSpace systems
* #7419: Fix several issues in sparse.load_npz, save_npz
* #7420: BUG: stats: allow integers as kappa4 shape parameters
- Add no_implicit_decl.patch
Fixes implicit-pointer-decl warnings and implicit-fortify-decl error.
- Fix wrong-script-interpreter rpmlint error.
* Wed Apr 19 2017 toddrme2178@gmail.com
- Update to version 0.19.0
+ Highlights
* A unified foreign function interface layer, `scipy.LowLevelCallable`.
* Cython API for scalar, typed versions of the universal functions from
the `scipy.special` module, via `cimport scipy.special.cython_special`.
- Removed weave subpackage. It was removed upstream in this release.
* Fri Oct 21 2016 toddrme2178@gmail.com
- Switch to single-spec version
- update to version 0.18.1:
* #6357: scipy 0.17.1 piecewise cubic hermite interpolation does not
return...
* #6420: circmean() changed behaviour from 0.17 to 0.18
* #6421: scipy.linalg.solve_banded overwrites input 'b' when the
inversion...
* #6425: cKDTree INF bug
* #6435: scipy.stats.ks_2samp returns different values on different
computers
* #6458: Error in scipy.integrate.dblquad when using variable
integration...
* #6405: BUG: sparse: fix elementwise divide for CSR/CSC
* #6431: BUG: result for insufficient neighbours from cKDTree is
wrong.
* #6432: BUG Issue #6421: scipy.linalg.solve_banded overwrites input
'b'...
* #6455: DOC: add links to release notes
* #6462: BUG: interpolate: fix .roots method of PchipInterpolator
* #6492: BUG: Fix regression in dblquad: #6458
* #6543: fix the regression in circmean
* #6545: Revert gh-5938, restore ks_2samp
* #6557: Backports for 0.18.1
- update to version 0.18.0:
(see http://scipy.github.io/devdocs/release.0.18.0.html for full changelog)
* Highlights of this release include:
+ A new ODE solver for two-point boundary value problems,
scipy.optimize.solve_bvp.
+ A new class, CubicSpline, for cubic spline interpolation of
data.
+ N-dimensional tensor product polynomials,
scipy.interpolate.NdPPoly.
+ Spherical Voronoi diagrams, scipy.spatial.SphericalVoronoi.
+ Support for discrete-time linear systems, scipy.signal.dlti.
- update to version 0.17.1:
* #5817: BUG: skew, kurtosis return np.nan instead of "propagate"
* #5850: Test failed with sgelsy
* #5898: interpolate.interp1d crashes using float128
* #5953: Massive performance regression in cKDTree.query with L_inf
distance...
* #6062: mannwhitneyu breaks backward compatibility in 0.17.0
* #6134: T test does not handle nans
* #5902: BUG: interpolate: make interp1d handle np.float128 again
* #5957: BUG: slow down with p=np.inf in 0.17 cKDTree.query
* #5970: Actually propagate nans through stats functions with
nan_policy="propagate"
* #5971: BUG: linalg: fix lwork check in *gelsy
* #6074: BUG: special: fixed violation of strict aliasing rules.
* #6083: BUG: Fix dtype for sum of linear operators
* #6100: BUG: Fix mannwhitneyu to be backward compatible
* #6135: Don't pass null pointers to LAPACK, even during workspace
queries.
* #6148: stats: fix handling of nan values in T tests and kendalltau
- specfile:
* updated source url to files.pythonhosted.org
* require setuptools
* Add openBLAS support.
This can improve performance in many situations.
* Drop ATLAS support.
* Thu Jan 28 2016 toddrme2178@gmail.com
- specfile:
* update copyright year
- update to version 0.17.0:
(see http://scipy.github.io/devdocs/release.0.17.0.html for full changelog)
* Highlights
+ New functions for linear and nonlinear least squares
optimization with constraints: scipy.optimize.lsq_linear and
scipy.optimize.least_squares
+ Support for fitting with bounds in scipy.optimize.curve_fit.
+ Significant improvements to scipy.stats, providing many
functions with better handing of inputs which have NaNs or are
empty, improved documentation, and consistent behavior between
scipy.stats and scipy.stats.mstats.
+ Significant performance improvements and new functionality in
scipy.spatial.cKDTree.
* Fri Oct 30 2015 toddrme2178@gmail.com
- Update to 0.16.1
SciPy 0.16.1 is a bug-fix release with no new features compared
to 0.16.0.
* Mon Jul 27 2015 toddrme2178@gmail.com
- Remove Cython subpackage. The sources are not as cleanly
separated as the changelog implied.
* Mon Jul 27 2015 toddrme2178@gmail.com
- Update to 0.16.0
* Highlights of this release include:
- A Cython API for BLAS/LAPACK in scipy.linalg
- A new benchmark suite. It's now straightforward to add new benchmarks,
and they're routinely included with performance enhancement PRs.
- Support for the second order sections (SOS) format in scipy.signal.
* New features
- Benchmark suite
+ The benchmark suite has switched to using Airspeed Velocity
for benchmarking.
- scipy.linalg improvements
+ A full set of Cython wrappers for BLAS and LAPACK has been added in
the modules scipy.linalg.cython_blas and scipy.linalg.cython_lapack.
In Cython, these wrappers can now be cimported from their
corresponding modules and used without linking directly against BLAS
or LAPACK.
+ The functions scipy.linalg.qr_delete, scipy.linalg.qr_insert and
scipy.linalg.qr_update for updating QR decompositions were added.
+ The function scipy.linalg.solve_circulant solves a linear system with
a circulant coefficient matrix.
+ The function scipy.linalg.invpascal computes the inverse of a Pascal matrix.
+ The function scipy.linalg.solve_toeplitz, a Levinson-Durbin Toeplitz solver,
was added.
+ Added wrapper for potentially useful LAPACK function *lasd4. It computes
the square root of the i-th updated eigenvalue of a positive symmetric rank-one
modification to a positive diagonal matrix. See its LAPACK documentation and
unit tests for it to get more info.
+ Added two extra wrappers for LAPACK least-square solvers. Namely, they are
* gelsd and *gelsy.
+ Wrappers for the LAPACK *lange functions, which calculate various matrix
norms, were added.
+ Wrappers for *gtsv and *ptsv, which solve A*X = B for tri-diagonal
matrix A, were added.
- scipy.signal improvements
+ Support for second order sections (SOS) as a format for IIR filters
was added. The new functions are:
* scipy.signal.sosfilt
* scipy.signal.sosfilt_zi,
* scipy.signal.sos2tf
* scipy.signal.sos2zpk
* scipy.signal.tf2sos
* scipy.signal.zpk2sos.
+ Additionally, the filter design functions iirdesign, iirfilter, butter,
cheby1, cheby2, ellip, and bessel can return the filter in the SOS
format.
+ The function scipy.signal.place_poles, which provides two methods to place
poles for linear systems, was added.
+ The option to use Gustafsson's method for choosing the initial conditions
of the forward and backward passes was added to scipy.signal.filtfilt.
+ New classes TransferFunction, StateSpace and ZerosPolesGain were
added. These classes are now returned when instantiating scipy.signal.lti.
Conversion between those classes can be done explicitly now.
+ An exponential (Poisson) window was added as scipy.signal.exponential, and a
Tukey window was added as scipy.signal.tukey.
+ The function for computing digital filter group delay was added as
scipy.signal.group_delay.
+ The functionality for spectral analysis and spectral density estimation has
been significantly improved: scipy.signal.welch became ~8x faster and the
functions scipy.signal.spectrogram, scipy.signal.coherence and
scipy.signal.csd (cross-spectral density) were added.
+ scipy.signal.lsim was rewritten - all known issues are fixed, so this
function can now be used instead of lsim2; lsim is orders of magnitude
faster than lsim2 in most cases.
- scipy.sparse improvements
+ The function scipy.sparse.norm, which computes sparse matrix norms, was
added.
+ The function scipy.sparse.random, which allows to draw random variates from
an arbitrary distribution, was added.
- scipy.spatial improvements
+ scipy.spatial.cKDTree has seen a major rewrite, which improved the
performance of the query method significantly, added support for parallel
queries, pickling, and options that affect the tree layout. See pull request
4374 for more details.
+ The function scipy.spatial.procrustes for Procrustes analysis (statistical
shape analysis) was added.
- scipy.stats improvements
+ The Wishart distribution and its inverse have been added, as
scipy.stats.wishart and scipy.stats.invwishart.
+ The Exponentially Modified Normal distribution has been
added as scipy.stats.exponnorm.
+ The Generalized Normal distribution has been added as scipy.stats.gennorm.
+ All distributions now contain a random_state property and allow specifying a
specific numpy.random.RandomState random number generator when generating
random variates.
+ Many statistical tests and other scipy.stats functions that have multiple
return values now return namedtuples. See pull request 4709 for details.
- scipy.optimize improvements
+ A new derivative-free method DF-SANE has been added to the nonlinear equation
system solving function scipy.optimize.root.
* Deprecated features
- scipy.stats.pdf_fromgamma is deprecated. This function was undocumented,
untested and rarely used. Statsmodels provides equivalent functionality
with statsmodels.distributions.ExpandedNormal.
- scipy.stats.fastsort is deprecated. This function is unnecessary,
numpy.argsort can be used instead.
- scipy.stats.signaltonoise and scipy.stats.mstats.signaltonoise are
deprecated. These functions did not belong in scipy.stats and are rarely
used. See issue #609 for details.
- scipy.stats.histogram2 is deprecated. This function is unnecessary,
numpy.histogram2d can be used instead.
* Backwards incompatible changes
- The deprecated global optimizer scipy.optimize.anneal was removed.
- The following deprecated modules have been removed. They had been deprecated
since Scipy 0.12.0, the functionality should be accessed as scipy.linalg.blas
and scipy.linalg.lapack.
+ scipy.lib.blas
+ scipy.lib.lapack
+ scipy.linalg.cblas
+ scipy.linalg.fblas
+ scipy.linalg.clapack
+ scipy.linalg.flapack.
- The deprecated function scipy.special.all_mat has been removed.
- These deprecated functions have been removed from scipy.stats:
+ scipy.stats.fprob
+ scipy.stats.ksprob
+ scipy.stats.zprob
+ scipy.stats.randwcdf
+ scipy.stats.randwppf
* Other changes
- The version numbering for development builds has been updated to comply with PEP 440.
- Building with python setup.py develop is now supported.
- Move Cython imports to another package
* Mon Mar 02 2015 toddrme2178@gmail.com
- update to version 0.15.1:
* #4413: BUG: Tests too strict, f2py doesn't have to overwrite this array
* #4417: BLD: avoid using NPY_API_VERSION to check not using deprecated...
* #4418: Restore and deprecate scipy.linalg.calc_work
* Mon Jan 12 2015 toddrme2178@gmail.com
- Update to 0.15.0
* New features
* scipy.optimize improvements
* scipy.optimize.linprog now provides a generic
linear programming similar to the way scipy.optimize.minimize
provides a generic interface to nonlinear programming optimizers.
Currently the only method supported is simplex which provides
a two-phase, dense-matrix-based simplex algorithm. Callbacks
functions are supported,allowing the user to monitor the progress
of the algorithm.
* The differential_evolution function is available from the scipy.optimize
module. Differential Evolution is an algorithm used for finding the global
minimum of multivariate functions. It is stochastic in nature (does not use
gradient methods), and can search large areas of candidate space, but often
requires larger numbers of function evaluations than conventional gradient
based techniques.
* scipy.signal improvements
* The function max_len_seq was added, which computes a Maximum
Length Sequence (MLS) signal.
* scipy.integrate improvements
* The interface between the scipy.integrate module and the QUADPACK library was
redesigned. It is now possible to use scipy.integrate to integrate
multivariate ctypes functions, thus avoiding callbacks to Python and providing
better performance, especially for complex integrand functions.
* scipy.sparse improvements
* scipy.sparse.linalg.svds now takes a LinearOperator as its main input.
* scipy.stats improvements
* Added a Dirichlet distribution as multivariate distribution.
* The new function `scipy.stats.median_test` computes Mood's median test.
* `scipy.stats.describe` returns a namedtuple rather than a tuple, allowing
users to access results by index or by name.
* Deprecated features
* The scipy.weave module is deprecated. It was the only module never ported
to Python 3.x, and is not recommended to be used for new code - use Cython
instead. In order to support existing code, scipy.weave has been packaged
separately: https://github.com/scipy/weave. It is a pure Python package, so
can easily be installed with pip install weave.
* scipy.special.bessel_diff_formula is deprecated. It is a private function,
and therefore will be removed from the public API in a following release.
* Backwards incompatible changes
* scipy.ndimage
* The functions scipy.ndimage.minimum_positions,
scipy.ndimage.maximum_positions and scipy.ndimage.extrema return
positions as ints instead of floats.
* Other changes
* scipy.integrate
* The OPTPACK and QUADPACK code has been changed to use the LAPACK matrix
solvers rather than the bundled LINPACK code. This means that there is no
longer any need for the bundled LINPACK routines, so they have been removed.
- Update copyright year
* Mon Aug 11 2014 toddrme2178@gmail.com
- Switch to pypi download location
- Minor spec file cleanups
* Fri May 30 2014 toddrme2178@gmail.com
- Mark python-scipy-weave as deprecated.
Please use python-weave package instead.
* Thu May 08 2014 toddrme2178@gmail.com
- Update to version 0.14.0
* New features
* scipy.interpolate improvements
* A new wrapper function `scipy.interpolate.interpn` for
interpolation onregular grids has been added. `interpn`
supports linear and nearest-neighbor interpolation in
arbitrary dimensions and spline interpolation in two
dimensions.
* Faster implementations of piecewise polynomials in power
and Bernstein polynomial bases have been added as
`scipy.interpolate.PPoly` and `scipy.interpolate.BPoly`.
New users should use these in favor of
`scipy.interpolate.PiecewisePolynomial`.
* `scipy.interpolate.interp1d` now accepts non-monotonic
inputs and sorts them. If performance is critical, sorting
can be turned off by using the new ``assume_sorted``
keyword.
* Functionality for evaluation of bivariate spline
derivatives in ``scipy.interpolate`` has been added.
* The new class `scipy.interpolate.Akima1DInterpolator`
implements the piecewise cubic polynomial interpolation
scheme devised by H. Akima.
* Functionality for fast interpolation on regular, unevenly
spaced grids in arbitrary dimensions has been added as
`scipy.interpolate.RegularGridInterpolator` .
* ``scipy.linalg`` improvements
* The new function `scipy.linalg.dft` computes the matrix of
the discrete Fourier transform.
* A condition number estimation function for matrix
exponential, `scipy.linalg.expm_cond`, has been added.
* ``scipy.optimize`` improvements
* A set of benchmarks for optimize, which can be run with
``optimize.bench()``, has been added.
* `scipy.optimize.curve_fit` now has more controllable error
estimation via the ``absolute_sigma`` keyword.
* Support for passing custom minimization methods to
``optimize.minimize()`` and ``optimize.minimize_scalar()``
has been added, currently useful especially for combining
``optimize.basinhopping()`` with custom local optimizer
routines.
* ``scipy.stats`` improvements
* A new class `scipy.stats.multivariate_normal` with
functionality for multivariate normal random variables
has been added.
* A lot of work on the ``scipy.stats`` distribution framework
has been done. Moment calculations (skew and kurtosis
mainly) are fixed and verified, all examples are now
runnable, and many small accuracy and performance
improvements for individual distributions were merged.
* The new function `scipy.stats.anderson_ksamp` computes the
k-sample Anderson-Darling test for the null hypothesis that
k samples come from the same parent population.
* ``scipy.signal`` improvements
* ``scipy.signal.iirfilter`` and related functions to design
Butterworth, Chebyshev, elliptical and Bessel IIR filters
now all use pole-zero ("zpk") format internally instead of
using transformations to numerator/denominator format.
The accuracy of the produced filters, especially high-order
ones, is improved significantly as a result.
* The new function `scipy.signal.vectorstrength` computes the
vector strength, a measure of phase synchrony, of a set of
events.
* ``scipy.special`` improvements
* The functions `scipy.special.boxcox` and
`scipy.special.boxcox1p`, which compute the
Box-Cox transformation, have been added.
* ``scipy.sparse`` improvements
* Significant performance improvement in CSR, CSC, and DOK
indexing speed.
* When using Numpy >= 1.9 (to be released in MM 2014), sparse
matrices function correctly when given to arguments of
``np.dot``, ``np.multiply`` and other ufuncs.
With earlier Numpy and Scipy versions, the results of such
operations are undefined and usually unexpected.
* Sparse matrices are no longer limited to ``2^31`` nonzero
elements. They automatically switch to using 64-bit index
data type for matrices containing more elements. User code
written assuming the sparse matrices use int32 as the index
data type will continue to work, except for such large
matrices. Code dealing with larger matrices needs to accept
either int32 or int64 indices.
* Deprecated features
* ``anneal``
* The global minimization function `scipy.optimize.anneal` is
deprecated. All users should use the
`scipy.optimize.basinhopping` function instead.
* ``scipy.stats``
* ``randwcdf`` and ``randwppf`` functions are deprecated.
All users should use distribution-specific ``rvs`` methods
instead.
* Probability calculation aliases ``zprob``, ``fprob`` and
``ksprob`` are deprecated. Use instead the ``sf`` methods
of the corresponding distributions or the ``special``
functions directly.
* ``scipy.interpolate``
* ``PiecewisePolynomial`` class is deprecated.
* Backwards incompatible changes
* scipy.special.lpmn
* ``lpmn`` no longer accepts complex-valued arguments. A new
function ``clpmn`` with uniform complex analytic behavior
has been added, and it should be used instead.
* scipy.sparse.linalg
* Eigenvectors in the case of generalized eigenvalue problem
are normalized to unit vectors in 2-norm, rather than
following the LAPACK normalization convention.
* The deprecated UMFPACK wrapper in ``scipy.sparse.linalg``
has been removed due to license and install issues. If
available, ``scikits.umfpack`` is still used transparently
in the ``spsolve`` and ``factorized`` functions.
Otherwise, SuperLU is used instead in these functions.
* scipy.stats
* The deprecated functions ``glm``, ``oneway`` and
``cmedian`` have been removed from ``scipy.stats``.
* ``stats.scoreatpercentile`` now returns an array instead of
a list of percentiles.
* scipy.interpolate
* The API for computing derivatives of a monotone piecewise
interpolation has changed: if `p` is a
``PchipInterpolator`` object, `p.derivative(der)`
returns a callable object representing the derivative of
`p`. For in-place derivatives use the second argument of
the `__call__` method: `p(0.1, der=2)` evaluates the
second derivative of `p` at `x=0.1`.
* The method `p.derivatives` has been removed.
* Sun Mar 02 2014 arun@gmx.de
- updated to version 0.13.3
Issues fixed:
* 3148: fix a memory leak in ``ndimage.label``.
* 3216: fix weave issue with too long file names for MSVC.
Other changes:
* Update Sphinx theme used for html docs so ``>>>`` in examples can be toggled.
* Wed Dec 11 2013 toddrme2178@gmail.com
- Update to version 0.13.2
+ require Cython 0.19, earlier versions have memory leaks in
fused types
+ ndimage.label fix swapped 64-bitness test
+ optimize.fmin_slsqp constraint violation
- Require python-Cython >= 0.19
* Tue Nov 19 2013 p.drouand@gmail.com
- Update to version 0.13.1
+ ``ndimage.label`` returns incorrect results in scipy 0.13.0
+ ``ndimage.label`` return type changed from int32 to uint32
+ `ndimage.find_objects`` doesn't work with int32 input in some cases
* Fri Oct 25 2013 toddrme2178@gmail.com
- Update to 0.13.0
* Highlights
* support for fancy indexing and boolean comparisons with
sparse matrices
* interpolative decompositions and matrix functions in the
linalg module
* two new trust-region solvers for unconstrained minimization
* scipy.integrate improvements
* N-dimensional numerical integration
* dopri* improvements
* scipy.linalg improvements
* Interpolative decompositions
* Polar decomposition
* BLAS level 3 functions
* Matrix functions
* scipy.optimize improvements
* Trust-region unconstrained minimization algorithms
* scipy.sparse improvements
* Boolean comparisons and sparse matrices
* CSR and CSC fancy indexing
* scipy.io improvements
* Unformatted Fortran file reader
* scipy.io.wavfile enhancements
* scipy.interpolate improvements
* B-spline derivatives and antiderivatives
* Deprecated features
* expm2 and expm3
* scipy.stats functions
* Backwards incompatible changes
* LIL matrix assignment
* Deprecated radon function removed
* Removed deprecated keywords xa and xb from
stats.distributions
* Changes to MATLAB file readers / writers
- Add a new flag to easily enable/disable atlas support for if it
ever gets fixed in the future
- Added numpy version number to requires and buildrequires
- Updated rpmlint fixes
* Sun Apr 14 2013 termim@gmail.com
- Update to version 0.12.0
Some of the highlights of this release are:
* Completed QHull wrappers in scipy.spatial.
* cKDTree now a drop-in replacement for KDTree.
* A new global optimizer, basinhopping.
* Support for Python 2 and Python 3 from the same code base (no more 2to3).
* Mon Oct 01 2012 toddrme2178@gmail.com
- Update to version 0.11.0:
* Sparse Graph Submodule
* scipy.optimize improvements
* A unified interface to minimizers of univariate and
multivariate functions has been added.
* A unified interface to root finding algorithms for
multivariate functions has been added.
* The L-BFGS-B algorithm has been updated to version 3.0.
* scipy.linalg improvements
* New matrix equation solvers
* QZ and QR Decomposition
* Pascal matrices
* Sparse matrix construction and operations
* LSMR iterative solver
* Discrete Sine Transform
* scipy.interpolate improvements
* Interpolation in spherical coordinates
* scipy.stats improvements
* Binned statistics
- Remove upstreamed patches
* Mon Aug 27 2012 toddrme2178@gmail.com
- Disable broken libatlas3
* Mon Jun 04 2012 toddrme2178@gmail.com
- Add suitesparse buildrequires
- Remove blas/lapack tests since these build successfully on all
targets now
* Tue May 29 2012 cfarrell@suse.com
- license update: BSD-3-Clause
No LGPL licenses found in the package
* Tue May 29 2012 toddrme2178@gmail.com
- Don't build against libatlas on factory since libatlas doesn't
work there
* Fri May 18 2012 toddrme2178@gmail.com
- Fix rmplint warnings
- Clean up spec file formatting
* Mon Apr 30 2012 toddrme2178@gmail.com
- Removed tests for unsupported openSUSE versions
* Tue Apr 24 2012 toddrme2178@gmail.com
- Add python 3 package
* Sat Apr 14 2012 badshah400@gmail.com
- Modify BuildRequires to match recent name changes of lapack and
blas in project.
* Tue Mar 27 2012 saschpe@suse.de
- Update to version 0.10.1:
* AFAICS, upstream provides no changelog
- Spec file cleanup:
* New sub-package weave provides the devel package (only headers in
a 'devel' package won't work)
* Don't ship testsuite and package weave examples as documentation
* Set license to SDPX style
* Sun Oct 02 2011 behrisch@users.sf.net
- update to 0.10.0b2
- added patch for fortran functions returning random data
- prepared addition of ufsparse
* Mon Sep 13 2010 coolo@novell.com
- update to 0.8.0:
* Python 3 compat
* Major documentation improvements
* Deprecated features
o Swapping inputs for correlation functions (scipy.signal)
o Obsolete code deprecated (scipy.misc)
* New features
o DCT support (scipy.fftpack)
o Single precision support for fft functions (scipy.fftpack)
o Correlation functions now implement the usual definition (scipy.signal)
o Additions and modification to LTI functions (scipy.signal)
... many more, see 0.8.0-notes.rst
* Tue Jul 14 2009 lars@linux-schulserver.de
- update to 0.7.1:
+ Several fixes in Matlab file IO
+ Work around a failure with Python 2.6
+ Memory leak in lfilter have been fixed
+ Several bugs of varying severity were fixed in the special
functions
- adapted patches to latest version
- also package release notes
* Sun Jun 21 2009 lars@linux-schulserver.de
- update to 0.7.0.3 (0.7.1rc3):
+ bugfix release
- adapted patches:
+ scipy-0.7.1rc3-implicit-fortify-decl.patch (xerbla.c)
+ scipy-0.7.1rc3-undefined_operation.patch (zutil.c; cutil.c)
- new patches:
+ scipy-0.7.1rc3-umfpack-include.patch (fix to find umfpack)
+ scipy-0.7.1rc3-atlas-include.patch (fix to find atlas)
+ scipy-0.7.1rc3-superlu.patch (correct use of fprintf)
- enable umfpack, atlas and amd support
- drop devel subpackage
- enable mandriva build
* Mon Mar 09 2009 lars@linux-schulserver.de
- update to 0.7.0:
SciPy 0.7.0 is the culmination of 16 months of hard work. It
contains many new features, numerous bug-fixes, improved test
coverage and better documentation.
+ Python 2.6 support (NOT Python 3.0)
+ Major documentation improvements
+ Support for NumScons has been added
+ Sandbox Removed
+ Sparse matrices have seen extensive improvements
+ Statistical functions for masked arrays have been added
+ The IO code in both NumPy and SciPy is being extensively
reworked
+ New Hierarchical Clustering module
+ New Spatial package
+ Reworked fftpack package
+ New Constants package
+ New Radial Basis Function module
+ New complex ODE integrator
+ New generalized symmetric and hermitian eigenvalue problem solver
+ Bug fixes in the interpolation package
+ Weave clean up
- adapted patches to new source
* Fri Dec 19 2008 lars@linux-schulserver.de
- fix compile errors on 11.1 and Factory (should go upstream):
+ scipy-0.6.0-implicit-fortify-decl.patch
+ scipy-0.6.0-undefined_operation.patch
+ scipy-0.6.0-no-return-in-nonvoid-function.patch
* Thu Oct 30 2008 lars@linux-schulserver.de
- temporary fix _Py_c_abs compile error on new python
* Thu Sep 25 2008 lars@linux-schulserver.de
- moved to Education base repository
* Tue Jul 01 2008 andrea@opensuse-org
- fixed spec file
- libblas-devel is now libblas3 and blas to avoid version conflicts
- devel package splitted out to make rpmlint happy
* Sun May 11 2008 lars@linux-schulserver.de
- build for openSUSE-Education
- Require python-numpy-devel for build
- blas-devel is now libblas-devel
- beautify specfile
* Mon Nov 05 2007 felix.richter2@uni-rostock.de
- version bump to 0.6.0
* Thu Oct 18 2007 werner.ho@gmx.de
- removed blas/lapack-devel packages for newer distributions
* Fri Sep 07 2007 werner.ho@gmx.de
- new version 0.5.2.1
* Thu Jan 18 2007 werner.ho@gmx.de
- version upgraded to 0.5.2
* Mon Dec 04 2006 werner.ho@gmx.de
- added blas-devel and lapack-devel to BuildRequires
* Wed Sep 27 2006 werner.ho@gmx.de
- Initial build.
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