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Issues closed for 1.9.3
scipy.interpolate.UnivariateSpline segfault
BUG: multivariate_normal returns a pdf for values outside its...
BUG: stats: inconsistency in docs and behavior of gmean and hmean
running scipy.interpolate.tests.test_fitpack::test_bisplev_integer_overflow...
test_bisplev_integer_overflow: Segmentation fault (core dumped)
Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but...
\`scipy.stats.mood\` does not correct for ties
ks_2samp throws \`RuntimeWarning: overflow encountered in double_scalars\`
\`shgo\` error since scipy 1.8.0.dev0+1529.803e52d
Input data validation for RectSphereBivariateSpline
BUG: binom.pmf - RuntimeWarning: divide by zero
BUG: scipy.optimize.minimize: Powell's method function evaluated...
BUG: lombscargle fails if argument is a view
BUG: Possible bug when using winsorize on pandas data instead...
BUG: stats.ttest_ind returns wrong p-values with permutations
odr.Model default meta value fails with __getattr__
BUG: Error in error message for incorrect sample dimension in...
BUG: dimension of isuppz in syevr is mistranslated
BUG: \`KDTree\`'s optional argument \`eps\` seems to have no...
dtype not preserved with operations on sparse arrays
BUG: \`stats.fit\` on \`boltzmann\` expects \`bound\` for \`lambda\`,...
BUG: Small oversight in sparse.linalg.lsmr?
BUG: Build failure due to problems with shebang line in cythoner.py
BUG: stats.rayleigh.fit: returns \`loc\` that is inconsistent...
BUG? Incorrect branch in \`LAMV\` / \`_specfunc.lamv\`
DOC: keepdims in stats.mode is incorrectly documented
Pull requests for 1.9.3
BUG: multivariate_normal returns a pdf for values outside its...
Bug: setting iprint=0 hides all output from fmin_l_bfgs_b, but...
BUG: stats: Reformulate loggamma._rvs to handle c << 1.
BUG: fix out-of-bound evaluations in optimize.minimize, powell...
BUG: fix powell evaluated outside limits
BUG: fix stats.rv_histogram for non-uniform bins
stats.mood: correct for when ties are present
BUG: fix a crash in \`fpknot\`
MAINT: stats: fix _contains_nan on Pandas Series
Fix ttest permutations
MAINT: fix SHGO extra arguments
BUG: Fix error in error message for incorrect sample dimension...
MAINT: stats.ks_2samp: always emit warning when exact method...
BUG: fix syevr series segfault by explicitly specifying operator...
BUG: optimize: Fix differential_evolution error message.
FIX: \`odr.Model\` error with default \`meta\` value
FIX: stats: ignore divide-by-zero warnings from Boost binom impl
MAINT: stats.vonmises: wrap rvs to -pi, pi interval
BUG: eps param no effect fixed
MAINT: Ensure Pythran input for lombscargle are contiguous
Detect integer overflow in bivariate splines in fitpackmodule.c,...
BUG: sparse: Fix indexing sparse matrix with empty index arguments.
FIX: spurious divide error with \`gmean\`
BUG: fix mutable data types as default arguments in \`ord.{Data,RealData}\`
MAINT: stats.boltzmann: correct _shape_info typo
BUG: interpolate: sanity check x and y in make_interp_spline(x,...
MAINT: avoid \`func_data\`, it conflicts with system header on...
BUG: interpolate: work array sizes for RectSphereBivariateSpline
BUG: linalg: Fix the XSLOW test test_sgesdd_lwork_bug_workaround()
MAINT: fix small LSMR problem
MAINT: stats.rayleigh: enforce constraint on location
FIX: special: use intended branching for \`lamv\` implementation
MAINT: stats.rv_discrete.pmf: should be zero at non-integer argument
REL: Prep for SciPy 1.9.3
BUG: special: Fix two XSLOW test failures.
MAINT: update meson.build to make it work on IBM i system
BLD: fix issue with incomplete threads dependency handling
Keepdims incorrectly documneted fix
MAINT: Handle numpy's deprecation of accepting out-of-bound integers.
BLD: fix invalid shebang for build helper script
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Issues closed for 1.9.2
BUG: 1.9.0rc1: \`OptimizeResult\` not populated when \`optimize.milp\`...
BUG: \`sparse.hstack\` returns incorrect result when the stack...
BUG: optimize.minimize backwards compatability in scipy 1.9
BUG: using msvc + meson to build scipy --> cl cannot be used...
BUG: error from \`scipy.stats.mode\` with \`NaN\`s, \`axis !=...
BUG: scipy 1.7.3 wheels on PyPI require numpy<1.23 in contradiction...
BUG: ncf_gen::ppf(..) causes segfault
Pearson3 PPF does not function properly with negative skew.
BUG: OSX-64 Test failure test_ppf_against_tables getting NaN
Pull requests for 1.9.2
FIX: Updated dtype resolution in \`_stack_along_minor_axis\`
FIX: milp: return feasible solutions if available on time out
ENH: cibuildwheel infrastructure
MAINT: minimize, restore squeezed ((1.0)) addresses 16898
REL: prep for SciPy 1.9.2
DOC: update version switcher for 1.9.1 and pin theme to 0.9
MAINT: cast \`linear_sum_assignment\` to PyCFunction
BLD: use compiler flags in a more portable way
MAINT: stats.mode: fix bug with \`axis!=1\`, \`nan_policy='omit'\`,...
MAINT: fix NumPy upper bound
BLD: fix usage of \`get_install_data\`, which defaults to purelib
DOC: Update numpy supported versions for 1.9.2
BLD: fixes for building with MSVC and Intel Fortran
Rudimentary test for manylinux_aarch64 with cibuildwheel
BLD: make MKL detection a little more robust, add notes on TODOs
CI: Update cibuildwheel to 2.10.1
MAINT: stats.pearson3: fix ppf for negative skew
BUG: Fix numerical precision error of \`truncnorm.logcdf\` when...
FIX: ensure a hold on GIL before raising warnings/errors
TST: stats.studentized_range: fix incorrect test
MAINT: pyproject.toml: Update build system requirements
MAINT: 1.9.2 backports
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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.
SciPy 1.9.0 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, which are documented below. 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).
Our development attention will now shift to bug-fix releases on the
1.9.x branch, and on adding new features on the main branch.
This release requires Python 3.8-3.11 and NumPy 1.18.5 or greater.
For running on PyPy, PyPy3 6.0+ is required.
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In the unuran part, omit defining _ISOC99_SOURCE. I am told that
the ieeefp.h header should not be used with _ISOC99_SOURCE. (Its
use comes from pyport.h.) Lately I've seen this package fail to
build also for aarch64, have not verified that this fixes it, though
it's not entirely impossible.
Fixes what triggered PR#56892.
Bump PKGREVISION.
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It failed with GCC too. There is some bad interaction with py-numpy,
probably related to patch-numpy_core_include_numpy_npy__common.h.
Unbreak the build until I have time to investigate this.
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SciPy 1.8.1 is a bug-fix release with no new features
compared to 1.8.0. Notably, usage of Pythran has been
restored for Windows builds/binaries.
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Previous workaround could fail to compile when double and long double are
effectively the same type.
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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, which are documented below. 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).
Our development attention will now shift to bug-fix releases on the
1.8.x branch, and on adding new features on the master branch.
This release requires Python 3.8+ and NumPy 1.17.3 or greater.
For running on PyPy, PyPy3 6.0+ is required.
**************************
Highlights of this release
**************************
- 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.
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They now have a tool dependency on py-setuptools instead of a DEPENDS
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it was added in 1.7.1 but there is no checksum, so patch is skipped.
Package apparently builds fine without it.
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SciPy 1.7.3 is a bug-fix release that provides binary wheels
for MacOS arm64 with Python 3.8, 3.9, and 3.10. The MacOS arm64 wheels
are only available for MacOS version 12.0 and greater, as explained
in Issue 14688, linked below.
Issues closed for 1.7.3
-----------------------
* Segmentation fault on import of scipy.integrate on Apple M1 ARM...
* BUG: ARPACK's eigsh & OpenBLAS from Apple Silicon M1 (arm64)...
* four CI failures on pre-release job
* Remaining test failures for macOS arm64 wheel
* BUG: Segmentation fault caused by scipy.stats.qmc.qmc.update_discrepancy
Pull requests for 1.7.3
-----------------------
* BLD: update pyproject.toml for Python 3.10 changes
* BUG: out of bounds indexing in stats.qmc.update_discrepancy
* MAINT: skip a few failing tests in \`1.7.x\` for macOS arm64
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SciPy 1.7.2 is a bug-fix release with no new features
compared to 1.7.1. Notably, the release includes wheels
for Python 3.10, and wheels are now built with a newer
version of OpenBLAS, 0.3.17. Python 3.10 wheels are provided
for MacOS x86_64 (thin, not universal2 or arm64 at this time),
and Windows/Linux 64-bit. Many wheels are now built with newer
versions of manylinux, which may require newer versions of pip.
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SciPy 1.7.1 is a bug-fix release with no new features compared to 1.7.0.
1.7.0:
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.
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All checksums have been double-checked against existing RMD160 and
SHA512 hashes
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Issues closed for 1.6.3
-----------------------
* Divide by zero in distance.yule
* prerelease_deps failures
* spatial rotation failure in (1.6.3) wheels repo (ARM64)
Pull requests for 1.6.3
-----------------------
* fix the matplotlib warning emitted during builing docs
* Divide by zero in yule dissimilarity of constant vectors
* deprecated np.typeDict
* substitute np.math.factorial with math.factorial
* add random seeds in Rotation module
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if you mark a package incompatible with python version X, you also
need to mark any dependent packages incompatible with version X
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Highlights of this release
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
Deprecated features
scipy.spatial changes
Calling KDTree.query with k=None to find all neighbours is deprecated.
Use KDTree.query_ball_point instead.
distance.wminkowski was deprecated; use distance.minkowski and supply
weights with the w keyword instead.
Backwards incompatible changes
Using scipy.fft as a function aliasing numpy.fft.fft was removed after
being deprecated in SciPy 1.4.0. As a result, the scipy.fft submodule
must be explicitly imported now, in line with other SciPy subpackages.
scipy.signal changes
The output of decimate, lfilter_zi, lfiltic, sos2tf, and
sosfilt_zi have been changed to match numpy.result_type of their inputs.
The window function slepian was removed.
The frechet_l and frechet_r distributions were removed.
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Install the new interchangeable BLAS system created by Thomas Orgis,
currently supporting Netlib BLAS/LAPACK, OpenBLAS, cblas, lapacke, and
Apple's Accelerate.framework. This system allows the user to select any
BLAS implementation without modifying packages or using package options, by
setting PKGSRC_BLAS_TYPES in mk.conf. See mk/blas.buildlink3.mk for details.
This commit should not alter behavior of existing packages as the system
defaults to Netlib BLAS/LAPACK, which until now has been the only supported
implementation.
Details:
Add new mk/blas.buildlink3.mk for inclusion in dependent packages
Install compatible Netlib math/blas and math/lapack packages
Update math/blas and math/lapack MAINTAINER approved by adam@
OpenBLAS, cblas, and lapacke will follow in separate commits
Update direct dependents to use mk/blas.buildlink3.mk
Perform recursive revbump
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Done to fix build w/ gfortran 10. "make test" was mostly OK except for
three tests that returned nan where inf was expected ...
Highlights of this release:
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
New features:
Too many; see release notes at github.
Backwards incompatible changes:
The output signatures of ?syevr, ?heevr have been changed from
w, v, info to w, v, m, isuppz, info
The order of output arguments w, v of <sy/he>{gv, gvd, gvx} is
swapped.
The output length of scipy.signal.upfirdn has been corrected, resulting
outputs may now be shorter for some combinations of up/down ratios and
input signal and filter lengths.
scipy.signal.resample now supports a domain keyword argument for
specification of time or frequency domain input.
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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.
SciPy 1.4.0 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, which are documented below. 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).
Our development attention will now shift to bug-fix releases on the
1.4.x branch, and on adding new features on the master branch.
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Packages defined the variable BROKEN inconsistently. Some added quotes,
like they are required in PKG_FAIL_REASON, some omitted them.
Now all packages behave the same, and pkglint will flag future mistakes.
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pkglint -Wall -F --only aligned -r
Manual correction in R/Makefile.extension for the MASTER_SITES
continuation line.
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SciPy 1.3.0 Release Notes
SciPy 1.3.0 is the culmination of 5 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been some API changes
in this release, which are documented below. 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).
Our development attention will now shift to bug-fix releases on the
1.3.x branch, and on adding new features on the master branch.
This release requires Python 3.5+ and NumPy 1.13.3 or greater.
For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.
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
SciPy 1.2.0 Release Notes
SciPy 1.2.0 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, which are documented below. 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).
Our development attention will now shift to bug-fix releases on the
1.2.x branch, and on adding new features on the master branch.
This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater.
This will be the last SciPy release to support Python 2.7.
Consequently, the 1.2.x series will be a long term support (LTS)
release; we will backport bug fixes until 1 Jan 2020.
For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.
Highlights of this release
- 1-D root finding improvements with a new solver, toms748, and a new
unified interface, root_scalar
- New dual_annealing optimization method that combines stochastic and
local deterministic searching
- A new optimization algorithm, shgo (simplicial homology
global optimization) for derivative free optimization problems
- A new category of quaternion-based transformations are available in
scipy.spatial.transform
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Update comment about upstream bug reports about test failures.
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Without the link option, install_name_tool may cause an error.
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SciPy 1.1.0 is the culmination of 7 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, which are documented below. 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). Our development attention will now shift to bug-fix releases on the
1.1.x branch, and on adding new features on the master branch.
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Fixes bulk builds.
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SciPy 1.0.1 is a bug-fix release with no new features compared to 1.0.0.
Probably the most important change is a fix for an incompatibility between
SciPy 1.0.0 and numpy.f2py in the NumPy master branch.
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Some of the highlights of this release are:
* Major build improvements. Windows wheels are available on PyPI for the
first time, and continuous integration has been set up on Windows and OS X
in addition to Linux.
* A set of new ODE solvers and a unified interface to them
(scipy.integrate.solve_ivp).
* Two new trust region optimizers and a new linear programming method, with
improved performance compared to what scipy.optimize offered previously.
Many new BLAS and LAPACK functions were wrapped. The BLAS wrappers are now
complete.
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in our case, __STDC_VERSION__ isn't defined when built as C++.
The fix isn't completeely right, it insists on <fenv.h> if built as C++.
Not entirely unreasonable, and makes this build on NetBSD/powerpc as well,
which doesn't like the redefinition of fegetround() and fesetround().
Bump PKGREVISION.
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The most important change is a fix for a severe memory leak in integrate.quad.
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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, which are documented below. All users
are encouraged to upgrade to this release, as there are a large number
of bug-fixes and optimizations. Moreover, our development attention
will now shift to bug-fix releases on the 0.19.x branch, and on adding
new features on the master branch.
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