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cggh / scikit-allel

A Python package for exploring and analysing genetic variation data
MIT License
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Scheduled monthly dependency update for November #388

Closed pyup-bot closed 1 year ago

pyup-bot commented 1 year ago

Update cython from 0.29.24 to 0.29.32.

Changelog ### 0.29.32 ``` ==================== Bugs fixed ---------- * Revert "Using memoryview typed arguments in inner functions is now rejected as unsupported." Patch by David Woods. (Github issue :issue:`4798`) * ``from module import *`` failed in 0.29.31 when using memoryviews. Patch by David Woods. (Github issue :issue:`4927`) ``` ### 0.29.31 ``` ==================== Features added -------------- * A new argument ``--module-name`` was added to the ``cython`` command to provide the (one) exact target module name from the command line. Patch by Matthew Brett and h-vetinari. (Github issue :issue:`4906`) Bugs fixed ---------- * Use ``importlib.util.find_spec()`` instead of the deprecated ``importlib.find_loader()`` function when setting up the package path at import-time. Patch by Matti Picus. (Github issue :issue:`4764`) * Require the C compiler to support the two-arg form of ``va_start`` on Python 3.10 and higher. Patch by Thomas Caswell. (Github issue :issue:`4820`) * Make ``fused_type`` subscriptable in Shadow.py. Patch by Pfebrer. (Github issue :issue:`4842`) * Fix the incorrect code generation of the target type in ``bytearray`` loops. Patch by Kenrick Everett. (Github issue :issue:`4108`) * Atomic refcounts for memoryviews were not used on some GCC versions by accident. Patch by Sam Gross. (Github issue :issue:`4915`) * Silence some GCC ``-Wconversion`` warnings in C utility code. Patch by Lisandro Dalcin. (Github issue :issue:`4854`) * Tuple multiplication was ignored in expressions such as ``[*(1,) * 2]``. Patch by David Woods. (Github issue :issue:`4864`) * Calling ``append`` methods on extension types could fail to find the method in some cases. Patch by David Woods. (Github issue :issue:`4828`) * Ensure that object buffers (e.g. ``ndarray[object, ndim=1]``) containing ``NULL`` pointers are safe to use, returning ``None`` instead of the ``NULL`` pointer. Patch by Sebastian Berg. (Github issue :issue:`4859`) * Using memoryview typed arguments in inner functions is now rejected as unsupported. Patch by David Woods. (Github issue :issue:`4798`) * Compilation could fail on systems (e.g. FIPS) that block MD5 checksums at runtime. (Github issue :issue:`4909`) * Experimental adaptations for the CPython "nogil" fork was added. Note that there is no official support for this in Cython 0.x. Patch by Sam Gross. (Github issue :issue:`4912`) ``` ### 0.29.30 ``` ==================== Bugs fixed ---------- * The GIL handling changes in 0.29.29 introduced a regression where objects could be deallocated without holding the GIL. (Github issue :issue:`4796`) ``` ### 0.29.29 ``` ==================== Features added -------------- * Avoid acquiring the GIL at the end of nogil functions. This change was backported in order to avoid generating wrong C code that would trigger C compiler warnings with tracing support enabled. Backport by Oleksandr Pavlyk. (Github issue :issue:`4637`) Bugs fixed ---------- * Function definitions in ``finally:`` clauses were not correctly generated. Patch by David Woods. (Github issue :issue:`4651`) * A case where C-API functions could be called with a live exception set was fixed. Patch by Jakub Kulík. (Github issue :issue:`4722`) * Pickles can now be exchanged again with those generated from Cython 3.0 modules. (Github issue :issue:`4680`) * Cython now correctly generates Python methods for both the provided regular and reversed special numeric methods of extension types. Patch by David Woods. (Github issue :issue:`4750`) * Calling unbound extension type methods without arguments could raise an ``IndexError`` instead of a ``TypeError``. Patch by David Woods. (Github issue :issue:`4779`) * Calling unbound ``.__contains__()`` super class methods on some builtin base types could trigger an infinite recursion. Patch by David Woods. (Github issue :issue:`4785`) * The C union type in pure Python mode mishandled some field names. Patch by Jordan Brière. (Github issue :issue:`4727`) * Allow users to overwrite the C macro ``_USE_MATH_DEFINES``. Patch by Yuriy Chernyshov. (Github issue :issue:`4690`) * Improved compatibility with CPython 3.10/11. Patches by Thomas Caswell, David Woods. (Github issues :issue:`4609`, :issue:`4667`, :issue:`4721`, :issue:`4730`, :issue:`4777`) * Docstrings of descriptors are now provided in PyPy 7.3.9. Patch by Matti Picus. (Github issue :issue:`4701`) ``` ### 0.29.28 ``` ==================== Bugs fixed ---------- * Due to backwards incompatible changes in CPython 3.11a4, the feature flags ``CYTHON_FAST_THREAD_STATE`` and ``CYTHON_USE_EXC_INFO_STACK`` are now disabled in Python 3.11 and later. They are enabled again in Cython 3.0. Patch by David Woods. (Github issue :issue:`4610`) * A C compiler warning in older PyPy versions was resolved. Patch by Matti Picus. (Github issue :issue:`4236`) ``` ### 0.29.27 ``` ==================== Features added -------------- * The ``cythonize`` command has a new option ``-M`` to generate ``.dep`` dependency files for the compilation unit. This can be used by external build tools to track these dependencies. Patch by Evgeni Burovski. (Github issue :issue:`1214`) Bugs fixed ---------- * Compilation failures on PyPy were resolved. Patches by Matti Picus. (Github issues :issue:`4509`, :issue:`4517`) * Calls to ``range()`` with more than three arguments did not fail. Original patch by Max Bachmann. (Github issue :issue:`4550`) * Some C compiler warnings about missing type struct initialisers in Py3.10 were resolved. * Cython no longer warns about using OpenMP 3.0 features since they are now considered generally available. ``` ### 0.29.26 ``` ==================== Bugs fixed ---------- * An incompatibility with CPython 3.11.0a3 was resolved. (Github issue :issue:`4499`) * The ``in`` operator failed on literal lists with starred expressions. Patch by Arvind Natarajan. (Github issue :issue:`3938`) * A C compiler warning in PyPy about a missing struct field initialisation was resolved. ``` ### 0.29.25 ``` ==================== Bugs fixed ---------- * Several incompatibilities with CPython 3.11 were resolved. Patches by David Woods, Victor Stinner, Thomas Caswell. (Github issues :issue:`4411`, :issue:`4414`, :issue:`4415`, :issue:`4416`, :issue:`4420`, :issue:`4428`, :issue:`4473`, :issue:`4479`, :issue:`4480`) * Some C compiler warnings were resolved. Patches by Lisandro Dalcin and others. (Github issue :issue:`4439`) * C++ ``std::move()`` should only be used automatically in MSVC versions that support it. Patch by Max Bachmann. (Github issue :issue:`4191`) * The ``Py_hash_t`` type failed to accept arbitrary "index" values. (Github issue :issue:`2752`) * Avoid copying unaligned 16-bit values since some platforms require them to be aligned. Use memcpy() instead to let the C compiler decide how to do it. (Github issue :issue:`4343`) * Cython crashed on invalid truthiness tests on C++ types without ``operator bool``. Patch by David Woods. (Github issue :issue:`4348`) * The declaration of ``PyUnicode_CompareWithASCIIString()`` in ``cpython.unicode`` was incorrect. Patch by Max Bachmann. (Github issue :issue:`4344`) ```
Links - PyPI: https://pypi.org/project/cython - Changelog: https://pyup.io/changelogs/cython/ - Homepage: http://cython.org/

Update numpy from 1.21.2 to 1.23.4.

The bot wasn't able to find a changelog for this release. Got an idea?

Links - PyPI: https://pypi.org/project/numpy - Homepage: https://www.numpy.org

Update dask[array] from 2021.9.1 to 2022.10.2.

The bot wasn't able to find a changelog for this release. Got an idea?

Links - PyPI: https://pypi.org/project/dask - Repo: https://github.com/dask/dask/

Update scipy from 1.7.1 to 1.9.3.

Changelog ### 1.9.2 ``` compared to `1.9.1`. It also provides wheels for Python `3.11` on several platforms. Authors ======= * Hood Chatham (1) * Thomas J. Fan (1) * Ralf Gommers (22) * Matt Haberland (5) * Julien Jerphanion (1) * Loïc Estève (1) * Nicholas McKibben (2) * Naoto Mizuno (1) * Andrew Nelson (3) * Tyler Reddy (28) * Pamphile Roy (1) * Ewout ter Hoeven (2) * Warren Weckesser (1) * Meekail Zain (1) + A total of 14 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.9.1 ``` compared to `1.9.0`. Notably, some important meson build fixes are included. Authors ======= * Anirudh Dagar (1) * Ralf Gommers (12) * Matt Haberland (2) * Andrew Nelson (1) * Tyler Reddy (14) * Atsushi Sakai (1) * Eli Schwartz (1) * Warren Weckesser (2) A total of 8 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.9.0 ``` 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+` and NumPy `1.18.5` or greater. For running on PyPy, PyPy3 `6.0+` is required. Highlights of this release =================== - We have modernized our build system to use ``meson``, substantially reducing our source build times - 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` New features =========== `scipy.interpolate` improvements ================================ - Speed up the ``RBFInterpolator`` evaluation with high dimensional interpolants. - Added new spline based interpolation methods for `scipy.interpolate.RegularGridInterpolator` and its tutorial. - `scipy.interpolate.RegularGridInterpolator` and `scipy.interpolate.interpn` now accept descending ordered points. - ``RegularGridInterpolator`` now handles length-1 grid axes. - The ``BivariateSpline`` subclasses have a new method ``partial_derivative`` which constructs a new spline object representing a derivative of an original spline. This mirrors the corresponding functionality for univariate splines, ``splder`` and ``BSpline.derivative``, and can substantially speed up repeated evaluation of derivatives. `scipy.linalg` improvements =========================== - `scipy.linalg.expm` now accepts nD arrays. Its speed is also improved. - Minimum required LAPACK version is bumped to ``3.7.1``. `scipy.fft` improvements ======================== - Added ``uarray`` multimethods for `scipy.fft.fht` and `scipy.fft.ifht` to allow provision of third party backend implementations such as those recently added to CuPy. `scipy.optimize` improvements ============================= - A new global optimizer, `scipy.optimize.direct` (DIviding RECTangles algorithm) was added. For problems with inexpensive function evaluations, like the ones in the SciPy benchmark suite, ``direct`` is competitive with the best other solvers in SciPy (``dual_annealing`` and ``differential_evolution``) in terms of execution time. See `gh-14300 <https://github.com/scipy/scipy/pull/14300>`__ for more details. - Add a ``full_output`` parameter to `scipy.optimize.curve_fit` to output additional solution information. - Add a ``integrality`` parameter to `scipy.optimize.differential_evolution`, enabling integer constraints on parameters. - Add a ``vectorized`` parameter to call a vectorized objective function only once per iteration. This can improve minimization speed by reducing interpreter overhead from the multiple objective function calls. - The default method of `scipy.optimize.linprog` is now ``'highs'``. - Added `scipy.optimize.milp`, new function for mixed-integer linear programming. - Added Newton-TFQMR method to ``newton_krylov``. - Added support for the ``Bounds`` class in ``shgo`` and ``dual_annealing`` for a more uniform API across `scipy.optimize`. - Added the ``vectorized`` keyword to ``differential_evolution``. - ``approx_fprime`` now works with vector-valued functions. `scipy.signal` improvements =========================== - The new window function `scipy.signal.windows.kaiser_bessel_derived` was added to compute the Kaiser-Bessel derived window. - Single-precision ``hilbert`` operations are now faster as a result of more consistent ``dtype`` handling. `scipy.sparse` improvements =========================== - Add a ``copy`` parameter to `scipy.sparce.csgraph.laplacian`. Using inplace computation with ``copy=False`` reduces the memory footprint. - Add a ``dtype`` parameter to `scipy.sparce.csgraph.laplacian` for type casting. - Add a ``symmetrized`` parameter to `scipy.sparce.csgraph.laplacian` to produce symmetric Laplacian for directed graphs. - Add a ``form`` parameter to `scipy.sparce.csgraph.laplacian` taking one of the three values: ``array``, or ``function``, or ``lo`` determining the format of the output Laplacian: * ``array`` is a numpy array (backward compatible default); * ``function`` is a pointer to a lambda-function evaluating the Laplacian-vector or Laplacian-matrix product; * ``lo`` results in the format of the ``LinearOperator``. `scipy.sparse.linalg` improvements ================================== - ``lobpcg`` performance improvements for small input cases. `scipy.spatial` improvements ============================ - Add an ``order`` parameter to `scipy.spatial.transform.Rotation.from_quat` and `scipy.spatial.transform.Rotation.as_quat` to specify quaternion format. `scipy.stats` improvements ========================== - `scipy.stats.monte_carlo_test` performs one-sample Monte Carlo hypothesis tests to assess whether a sample was drawn from a given distribution. Besides reproducing the results of hypothesis tests like `scipy.stats.ks_1samp`, `scipy.stats.normaltest`, and `scipy.stats.cramervonmises` without small sample size limitations, it makes it possible to perform similar tests using arbitrary statistics and distributions. - Several `scipy.stats` functions support new ``axis`` (integer or tuple of integers) and ``nan_policy`` ('raise', 'omit', or 'propagate'), and ``keepdims`` arguments. These functions also support masked arrays as inputs, even if they do not have a `scipy.stats.mstats` counterpart. Edge cases for multidimensional arrays, such as when axis-slices have no unmasked elements or entire inputs are of size zero, are handled consistently. - Add a ``weight`` parameter to `scipy.stats.hmean`. - Several improvements have been made to `scipy.stats.levy_stable`. Substantial improvement has been made for numerical evaluation of the pdf and cdf, resolving [12658](https://github.com/scipy/scipy/issues/12658) and [14944](https://github.com/scipy/scipy/issues/14994). The improvement is particularly dramatic for stability parameter ``alpha`` close to or equal to 1 and for ``alpha`` below but approaching its maximum value of 2. The alternative fast Fourier transform based method for pdf calculation has also been updated to use the approach of Wang and Zhang from their 2008 conference paper *Simpson’s rule based FFT method to compute densities of stable distribution*, making this method more competitive with the default method. In addition, users now have the option to change the parametrization of the Levy Stable distribution to Nolan's "S0" parametrization which is used internally by SciPy's pdf and cdf implementations. The "S0" parametrization is described in Nolan's paper [*Numerical calculation of stable densities and distribution functions*](https://doi.org/10.1080/15326349708807450) upon which SciPy's implementation is based. "S0" has the advantage that ``delta`` and ``gamma`` are proper location and scale parameters. With ``delta`` and ``gamma`` fixed, the location and scale of the resulting distribution remain unchanged as ``alpha`` and ``beta`` change. This is not the case for the default "S1" parametrization. Finally, more options have been exposed to allow users to trade off between runtime and accuracy for both the default and FFT methods of pdf and cdf calculation. More information can be found in the documentation here (to be linked). - Added `scipy.stats.fit` for fitting discrete and continuous distributions to data. - The methods ``"pearson"`` and ``"tippet"`` from `scipy.stats.combine_pvalues` have been fixed to return the correct p-values, resolving [15373](https://github.com/scipy/scipy/issues/15373). In addition, the documentation for `scipy.stats.combine_pvalues` has been expanded and improved. - Unlike other reduction functions, ``stats.mode`` didn't consume the axis being operated on and failed for negative axis inputs. Both the bugs have been fixed. Note that ``stats.mode`` will now consume the input axis and return an ndarray with the ``axis`` dimension removed. - Replaced implementation of `scipy.stats.ncf` with the implementation from Boost for improved reliability. - Add a `bits` parameter to `scipy.stats.qmc.Sobol`. It allows to use from 0 to 64 bits to compute the sequence. Default is ``None`` which corresponds to 30 for backward compatibility. Using a higher value allow to sample more points. Note: ``bits`` does not affect the output dtype. - Add a `integers` method to `scipy.stats.qmc.QMCEngine`. It allows sampling integers using any QMC sampler. - Improved the fit speed and accuracy of ``stats.pareto``. - Added ``qrvs`` method to ``NumericalInversePolynomial`` to match the situation for ``NumericalInverseHermite``. - Faster random variate generation for ``gennorm`` and ``nakagami``. - ``lloyd_centroidal_voronoi_tessellation`` has been added to allow improved sample distributions via iterative application of Voronoi diagrams and centering operations - Add `scipy.stats.qmc.PoissonDisk` to sample using the Poisson disk sampling method. It guarantees that samples are separated from each other by a given ``radius``. - Add `scipy.stats.pmean` to calculate the weighted power mean also called generalized mean. Deprecated features ================ - Due to collision with the shape parameter ``n`` of several distributions, use of the distribution ``moment`` method with keyword argument ``n`` is deprecated. Keyword ``n`` is replaced with keyword ``order``. - Similarly, use of the distribution ``interval`` method with keyword arguments ``alpha`` is deprecated. Keyword ``alpha`` is replaced with keyword ``confidence``. - The ``'simplex'``, ``'revised simplex'``, and ``'interior-point'`` methods of `scipy.optimize.linprog` are deprecated. Methods ``highs``, ``highs-ds``, or ``highs-ipm`` should be used in new code. - Support for non-numeric arrays has been deprecated from ``stats.mode``. ``pandas.DataFrame.mode`` can be used instead. - The function `spatial.distance.kulsinski` has been deprecated in favor of `spatial.distance.kulczynski1`. - The ``maxiter`` keyword of the truncated Newton (TNC) algorithm has been deprecated in favour of ``maxfun``. - The ``vertices`` keyword of ``Delauney.qhull`` now raises a DeprecationWarning, after having been deprecated in documentation only for a long time. - The ``extradoc`` keyword of ``rv_continuous``, ``rv_discrete`` and ``rv_sample`` now raises a DeprecationWarning, after having been deprecated in documentation only for a long time. Expired Deprecations ================= There is an ongoing effort to follow through on long-standing deprecations. The following previously deprecated features are affected: - Object arrays in sparse matrices now raise an error. - Inexact indices into sparse matrices now raise an error. - Passing ``radius=None`` to `scipy.spatial.SphericalVoronoi` now raises an error (not adding ``radius`` defaults to 1, as before). - Several BSpline methods now raise an error if inputs have ``ndim > 1``. - The ``_rvs`` method of statistical distributions now requires a ``size`` parameter. - Passing a ``fillvalue`` that cannot be cast to the output type in `scipy.signal.convolve2d` now raises an error. - `scipy.spatial.distance` now enforces that the input vectors are one-dimensional. - Removed ``stats.itemfreq``. - Removed ``stats.median_absolute_deviation``. - Removed ``n_jobs`` keyword argument and use of ``k=None`` from ``kdtree.query``. - Removed ``right`` keyword from ``interpolate.PPoly.extend``. - Removed ``debug`` keyword from ``scipy.linalg.solve_*``. - Removed class ``_ppform`` ``scipy.interpolate``. - Removed BSR methods ``matvec`` and ``matmat``. - Removed ``mlab`` truncation mode from ``cluster.dendrogram``. - Removed ``cluster.vq.py_vq2``. - Removed keyword arguments ``ftol`` and ``xtol`` from ``optimize.minimize(method='Nelder-Mead')``. - Removed ``signal.windows.hanning``. - Removed LAPACK ``gegv`` functions from ``linalg``; this raises the minimally required LAPACK version to 3.7.1. - Removed ``spatial.distance.matching``. - Removed the alias ``scipy.random`` for ``numpy.random``. - Removed docstring related functions from ``scipy.misc`` (``docformat``, ``inherit_docstring_from``, ``extend_notes_in_docstring``, ``replace_notes_in_docstring``, ``indentcount_lines``, ``filldoc``, ``unindent_dict``, ``unindent_string``). - Removed ``linalg.pinv2``. Backwards incompatible changes ========================== - Several `scipy.stats` functions now convert ``np.matrix`` to ``np.ndarray``s before the calculation is performed. In this case, the output will be a scalar or ``np.ndarray`` of appropriate shape rather than a 2D ``np.matrix``. Similarly, while masked elements of masked arrays are still ignored, the output will be a scalar or ``np.ndarray`` rather than a masked array with ``mask=False``. - The default method of `scipy.optimize.linprog` is now ``'highs'``, not ``'interior-point'`` (which is now deprecated), so callback functions and some options are no longer supported with the default method. - For `scipy.stats.combine_pvalues`, the sign of the test statistic returned for the method ``"pearson"`` has been flipped so that higher values of the statistic now correspond to lower p-values, making the statistic more consistent with those of the other methods and with the majority of the literature. - `scipy.linalg.expm` due to historical reasons was using the sparse implementation and thus was accepting sparse arrays. Now it only works with nDarrays. For sparse usage, `scipy.sparse.linalg.expm` needs to be used explicitly. - The definition of `scipy.stats.circvar` has reverted to the one that is standard in the literature; note that this is not the same as the square of `scipy.stats.circstd`. - Remove inheritance to `QMCEngine` in `MultinomialQMC` and `MultivariateNormalQMC`. It removes the methods `fast_forward` and `reset`. - Init of `MultinomialQMC` now require the number of trials with `n_trials`. Hence, `MultinomialQMC.random` output has now the correct shape ``(n, pvals)``. - Several function-specific warnings (``F_onewayConstantInputWarning``, ``F_onewayBadInputSizesWarning``, ``PearsonRConstantInputWarning``, ``PearsonRNearConstantInputWarning``, ``SpearmanRConstantInputWarning``, and ``BootstrapDegenerateDistributionWarning``) have been replaced with more general warnings. Other changes ============ - A draft developer CLI is available for SciPy, leveraging the ``doit``, ``click`` and ``rich-click`` tools. For more details, see [gh-15959](https://github.com/scipy/scipy/pull/15959). - The SciPy contributor guide has been reorganized and updated (see [15947](https://github.com/scipy/scipy/pull/15947) for details). - QUADPACK Fortran routines in `scipy.integrate`, which power `scipy.integrate.quad`, have been marked as `recursive`. This should fix rare issues in multivariate integration (`nquad` and friends) and obviate the need for compiler-specific compile flags (`/recursive` for ifort etc). Please file an issue if this change turns out problematic for you. This is also true for ``FITPACK`` routines in `scipy.interpolate`, which power ``splrep``, ``splev`` etc., and ``*UnivariateSpline`` and ``*BivariateSpline`` classes. - the ``USE_PROPACK`` environment variable has been renamed to ``SCIPY_USE_PROPACK``; setting to a non-zero value will enable the usage of the ``PROPACK`` library as before Lazy access to subpackages ====================== Before this release, all subpackages of SciPy (`cluster`, `fft`, `ndimage`, etc.) had to be explicitly imported. Now, these subpackages are lazily loaded as soon as they are accessed, so that the following is possible (if desired for interactive use, it's not actually recommended for code, see :ref:`scipy-api`): ``import scipy as sp; sp.fft.dct([1, 2, 3])``. Advantages include: making it easier to navigate SciPy in interactive terminals, reducing subpackage import conflicts (which before required ``import networkx.linalg as nla; import scipy.linalg as sla``), and avoiding repeatedly having to update imports during teaching & experimentation. Also see [the related community specification document](https://scientific-python.org/specs/spec-0001/). SciPy switched to Meson as its build system =========================================== This is the first release that ships with [Meson](https://mesonbuild.com) as the build system. When installing with ``pip`` or ``pypa/build``, Meson will be used (invoked via the ``meson-python`` build hook). This change brings significant benefits - most importantly much faster build times, but also better support for cross-compilation and cleaner build logs. *Note*: This release still ships with support for ``numpy.distutils``-based builds as well. Those can be invoked through the ``setup.py`` command-line interface (e.g., ``python setup.py install``). It is planned to remove ``numpy.distutils`` support before the 1.10.0 release. When building from source, a number of things have changed compared to building with ``numpy.distutils``: - New build dependencies: ``meson``, ``ninja``, and ``pkg-config``. ``setuptools`` and ``wheel`` are no longer needed. - BLAS and LAPACK libraries that are supported haven't changed, however the discovery mechanism has: that is now using ``pkg-config`` instead of hardcoded paths or a ``site.cfg`` file. - The build defaults to using OpenBLAS. See :ref:`blas-lapack-selection` for details. The two CLIs that can be used to build wheels are ``pip`` and ``build``. In addition, the SciPy repo contains a ``python dev.py`` CLI for any kind of development task (see its ``--help`` for details). For a comparison between old (``distutils``) and new (``meson``) build commands, see :ref:`meson-faq`. For more information on the introduction of Meson support in SciPy, see `gh-13615 <https://github.com/scipy/scipy/issues/13615>`__ and `this blog post <https://labs.quansight.org/blog/2021/07/moving-scipy-to-meson/>`__. Authors ======= * endolith (12) * Caio Agiani (2) + * Emmy Albert (1) + * Joseph Albert (1) * Tania Allard (3) * Carsten Allefeld (1) + * Kartik Anand (1) + * Virgile Andreani (2) + * Weh Andreas (1) + * Francesco Andreuzzi (5) + * Kian-Meng Ang (2) + * Gerrit Ansmann (1) * Ar-Kareem (1) + * Shehan Atukorala (1) + * avishai231 (1) + * Blair Azzopardi (1) * Sayantika Banik (2) + * Ross Barnowski (8) * Christoph Baumgarten (3) * Nickolai Belakovski (1) * Peter Bell (9) * Sebastian Berg (2) * Bharath (1) + * bobcatCA (2) + * boussoffara (2) + * Islem BOUZENIA (1) + * Jake Bowhay (41) + * Matthew Brett (11) * Dietrich Brunn (2) + * Michael Burkhart (2) + * Evgeni Burovski (96) * Matthias Bussonnier (20) * Dominic C (1) * Cameron (1) + * CJ Carey (3) * Thomas A Caswell (2) * Ali Cetin (2) + * Hood Chatham (5) + * Klesk Chonkin (1) * Craig Citro (1) + * Dan Cogswell (1) + * Luigi Cruz (1) + * Anirudh Dagar (5) * Brandon David (1) * deepakdinesh1123 (1) + * Denton DeLoss (1) + * derbuihan (2) + * Sameer Deshmukh (13) + * Niels Doucet (1) + * DWesl (8) * eytanadler (30) + * Thomas J. Fan (5) * Isuru Fernando (3) * Joseph Fox-Rabinovitz (1) * Ryan Gibson (4) + * Ralf Gommers (308) * Srinivas Gorur-Shandilya (1) + * Alex Griffing (2) * h-vetinari (3) * Matt Haberland (442) * Tristan Hearn (1) + * Jonathan Helgert (1) + * Samuel Hinton (1) + * Jake (1) + * Stewart Jamieson (1) + * Jan-Hendrik Müller (1) * Yikun Jiang (1) + * JuliaMelle01 (1) + * jyuv (12) + * Chris Keefe (1) + * Robert Kern (4) * Andrew Knyazev (11) * Matthias Koeppe (4) + * Sergey Koposov (1) * Volodymyr Kozachynskyi (1) + * Yotaro Kubo (2) + * Jacob Lapenna (1) + * Peter Mahler Larsen (8) * Eric Larson (4) * Laurynas Mikšys (1) + * Antony Lee (1) * Gregory R. Lee (2) * lerichi (1) + * Tim Leslie (2) * P. L. Lim (1) * Smit Lunagariya (43) * lutefiskhotdish (1) + * Cong Ma (12) * Syrtis Major (1) * Nicholas McKibben (17) * Melissa Weber Mendonça (10) * Mark Mikofski (1) * Jarrod Millman (13) * Harsh Mishra (6) * ML-Nielsen (3) + * Matthew Murray (1) + * Andrew Nelson (50) * Dimitri Papadopoulos Orfanos (1) + * Evgueni Ovtchinnikov (2) + * Sambit Panda (1) * Nick Papior (2) * Tirth Patel (43) * Petar Mlinarić (1) * petroselo (1) + * Ilhan Polat (64) * Anthony Polloreno (1) * Amit Portnoy (1) + * Quentin Barthélemy (9) * Patrick N. Raanes (1) + * Tyler Reddy (121) * Pamphile Roy (196) * Vivek Roy (2) + * Niyas Sait (2) + * Atsushi Sakai (25) * Mazen Sayed (1) + * Eduardo Schettino (5) + * Daniel Schmitz (6) + * Eli Schwartz (3) + * SELEE (2) + * Namami Shanker (4) * siddhantwahal (1) + * Gagandeep Singh (8) * Soph (1) + * Shivnaren Srinivasan (1) + * Scott Staniewicz (1) + * Leo C. Stein (4) * Albert Steppi (7) * Christopher Strickland (1) + * Kai Striega (4) * Søren Fuglede Jørgensen (1) * Aleksandr Tagilov (1) + * Masayuki Takagi (1) + * Sai Teja (1) + * Ewout ter Hoeven (2) + * Will Tirone (2) * Bas van Beek (7) * Dhruv Vats (1) * H. Vetinari (4) * Arthur Volant (1) * Samuel Wallan (5) * Stefan van der Walt (8) * Warren Weckesser (83) * Anreas Weh (1) * Nils Werner (1) * Aviv Yaish (1) + * Dowon Yi (1) * Rory Yorke (1) * Yosshi999 (1) + * yuanx749 (2) + * Gang Zhao (23) * ZhihuiChen0903 (1) * Pavel Zun (1) + * David Zwicker (1) + A total of 153 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.8.1 ``` compared to `1.8.0`. Notably, usage of Pythran has been restored for Windows builds/binaries. Authors ======= * Henry Schreiner * Maximilian Nöthe * Sebastian Berg (1) * Sameer Deshmukh (1) + * Niels Doucet (1) + * DWesl (4) * Isuru Fernando (1) * Ralf Gommers (4) * Matt Haberland (1) * Andrew Nelson (1) * Dimitri Papadopoulos Orfanos (1) + * Tirth Patel (3) * Tyler Reddy (46) * Pamphile Roy (7) * Niyas Sait (1) + * H. Vetinari (2) * Warren Weckesser (1) A total of 17 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.8.0 ``` 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'``. - 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. New features ------------- `scipy.fft` improvements ======================== Added an ``orthogonalize=None`` parameter to the real transforms in `scipy.fft` which controls whether the modified definition of DCT/DST is used without changing the overall scaling. `scipy.fft` backend registration is now smoother, operating with a single registration call and no longer requiring a context manager. `scipy.integrate` improvements ============================== `scipy.integrate.quad_vec` introduces a new optional keyword-only argument, ``args``. ``args`` takes in a tuple of extra arguments if any (default is ``args=()``), which is then internally used to pass into the callable function (needing these extra arguments) which we wish to integrate. `scipy.interpolate` improvements ================================ `scipy.interpolate.BSpline` has a new method, ``design_matrix``, which constructs a design matrix of b-splines in the sparse CSR format. A new method ``from_cubic`` in ``BSpline`` class allows to convert a ``CubicSpline`` object to ``BSpline`` object. `scipy.linalg` improvements =========================== `scipy.linalg` gained three new public array structure investigation functions. `scipy.linalg.bandwidth` returns information about the bandedness of an array and can be used to test for triangular structure discovery, while `scipy.linalg.issymmetric` and `scipy.linalg.ishermitian` test the array for exact and approximate symmetric/Hermitian structure. `scipy.optimize` improvements ============================= `scipy.optimize.check_grad` introduces two new optional keyword only arguments, ``direction`` and ``seed``. ``direction`` can take values, ``'all'`` (default), in which case all the one hot direction vectors will be used for verifying the input analytical gradient function and ``'random'``, in which case a random direction vector will be used for the same purpose. ``seed`` (default is ``None``) can be used for reproducing the return value of ``check_grad`` function. It will be used only when ``direction='random'``. The `scipy.optimize.minimize` ``TNC`` method has been rewritten to use Cython bindings. This also fixes an issue with the callback altering the state of the optimization. Added optional parameters ``target_accept_rate`` and ``stepwise_factor`` for adapative step size adjustment in ``basinhopping``. The ``epsilon`` argument to ``approx_fprime`` is now optional so that it may have a default value consistent with most other functions in `scipy.optimize`. `scipy.signal` improvements =========================== Add ``analog`` argument, default ``False``, to ``zpk2sos``, and add new pairing option ``'minimal'`` to construct analog and minimal discrete SOS arrays. ``tf2sos`` uses zpk2sos; add ``analog`` argument here as well, and pass it on to ``zpk2sos``. ``savgol_coeffs`` and ``savgol_filter`` now work for even window lengths. Added the Chirp Z-transform and Zoom FFT available as `scipy.signal.CZT` and `scipy.signal.ZoomFFT`. `scipy.sparse` improvements =========================== An 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. Please refer to the `scipy.sparse` docstring for more information. ``maximum_flow`` introduces optional keyword only argument, ``method`` which accepts either, ``'edmonds-karp'`` (Edmonds Karp algorithm) or ``'dinic'`` (Dinic's algorithm). Moreover, ``'dinic'`` is used as default value for ``method`` which means that Dinic's algorithm is used for computing maximum flow unless specified. See, the comparison between the supported algorithms in `this comment <https://github.com/scipy/scipy/pull/14358#issue-684212523>`_. Parameters ``atol``, ``btol`` now default to 1e-6 in `scipy.sparse.linalg.lsmr` to match with default values in `scipy.sparse.linalg.lsqr`. Add the Transpose-Free Quasi-Minimal Residual algorithm (TFQMR) for general nonsingular non-Hermitian linear systems in `scipy.sparse.linalg.tfqmr`. The sparse SVD library PROPACK is now vendored with SciPy, and an interface is exposed via `scipy.sparse.svds` with ``solver='PROPACK'``. For some problems, this may be faster and/or more accurate than the default, ARPACK. ``sparse.linalg`` iterative solvers now have a nonzero initial guess option, which may be specified as ``x0 = 'Mb'``. The ``trace`` method has been added for sparse matrices. `scipy.spatial` improvements ============================ `scipy.spatial.transform.Rotation` now supports item assignment and has a new ``concatenate`` method. Add `scipy.spatial.distance.kulczynski1` in favour of `scipy.spatial.distance.kulsinski` which will be deprecated in the next release. `scipy.spatial.distance.minkowski` now also supports ``0<p<1``. `scipy.special` improvements ============================ The new function `scipy.special.log_expit` computes the logarithm of the logistic sigmoid function. The function is formulated to provide accurate results for large positive and negative inputs, so it avoids the problems that would occur in the naive implementation ``log(expit(x))``. A suite of five new functions for elliptic integrals: ``scipy.special.ellipr{c,d,f,g,j}``. These are the `Carlson symmetric elliptic integrals <https://dlmf.nist.gov/19.16>`_, which have computational advantages over the classical Legendre integrals. Previous versions included some elliptic integrals from the Cephes library (``scipy.special.ellip{k,km1,kinc,e,einc}``) but was missing the integral of third kind (Legendre's Pi), which can be evaluated using the new Carlson functions. The new Carlson elliptic integral functions can be evaluated in the complex plane, whereas the Cephes library's functions are only defined for real inputs. Several defects in `scipy.special.hyp2f1` have been corrected. Approximately correct values are now returned for ``z`` near ``exp(+-i*pi/3)``, fixing `8054 <https://github.com/scipy/scipy/issues/8054>`_. Evaluation for such ``z`` is now calculated through a series derived by `López and Temme (2013) <https://arxiv.org/abs/1306.2046>`_ that converges in these regions. In addition, degenerate cases with one or more of ``a``, ``b``, and/or ``c`` a non-positive integer are now handled in a manner consistent with `mpmath's hyp2f1 implementation <https://mpmath.org/doc/current/functions/hypergeometric.html>`_, which fixes `7340 <https://github.com/scipy/scipy/issues/7340>`_. These fixes were made as part of an effort to rewrite the Fortran 77 implementation of hyp2f1 in Cython piece by piece. This rewriting is now roughly 50% complete. `scipy.stats` improvements ========================== `scipy.stats.qmc.LatinHypercube` introduces two new optional keyword-only arguments, ``optimization`` and ``strength``. ``optimization`` is either ``None`` or ``random-cd``. In the latter, random permutations are performed to improve the centered discrepancy. ``strength`` is either 1 or 2. 1 corresponds to the classical LHS while 2 has better sub-projection properties. This construction is referred to as an orthogonal array based LHS of strength 2. In both cases, the output is still a LHS. `scipy.stats.qmc.Halton` is faster as the underlying Van der Corput sequence was ported to Cython. The ``alternative`` parameter was added to the ``kendalltau`` and ``somersd`` functions to allow one-sided hypothesis testing. Similarly, the masked versions of ``skewtest``, ``kurtosistest``, ``ttest_1samp``, ``ttest_ind``, and ``ttest_rel`` now also have an ``alternative`` parameter. Add `scipy.stats.gzscore` to calculate the geometrical z score. Random variate generators to sample from arbitrary univariate non-uniform continuous and discrete distributions have been added to the new `scipy.stats.sampling` submodule. Implementations of a C library `UNU.RAN <http://statmath.wu.ac.at/software/unuran/>`_ are used for performance. The generators added are: - TransformedDensityRejection - DiscreteAliasUrn - NumericalInversePolynomial - DiscreteGuideTable - SimpleRatioUniforms The ``binned_statistic`` set of functions now have improved performance for the ``std``, ``min``, ``max``, and ``median`` statistic calculations. ``somersd`` and ``_tau_b`` now have faster Pythran-based implementations. Some general efficiency improvements to handling of ``nan`` values in several ``stats`` functions. Added the Tukey-Kramer test as `scipy.stats.tukey_hsd`. Improved performance of `scipy.stats.argus` ``rvs`` method. Added the parameter ``keepdims`` to `scipy.stats.variation` and prevent the undesirable return of a masked array from the function in some cases. ``permutation_test`` performs an exact or randomized permutation test of a given statistic on provided data. Deprecated features --------------------- Clear split between public and private API ========================================== SciPy has always documented what its public API consisted of in :ref:`its API reference docs <scipy-api>`, however there never was a clear split between public and private namespaces in the code base. In this release, all namespaces that were private but happened to miss underscores in their names have been deprecated. These include (as examples, there are many more): - ``scipy.signal.spline`` - ``scipy.ndimage.filters`` - ``scipy.ndimage.fourier`` - ``scipy.ndimage.measurements`` - ``scipy.ndimage.morphology`` - ``scipy.ndimage.interpolation`` - ``scipy.sparse.linalg.solve`` - ``scipy.sparse.linalg.eigen`` - ``scipy.sparse.linalg.isolve`` All functions and other objects in these namespaces that were meant to be public are accessible from their respective public namespace (e.g. `scipy.signal`). The design principle is that any public object must be accessible from a single namespace only; there are a few exceptions, mostly for historical reasons (e.g., ``stats`` and ``stats.distributions`` overlap). For other libraries aiming to provide a SciPy-compatible API, it is now unambiguous what namespace structure to follow. See `gh-14360 <https://github.com/scipy/scipy/issues/14360>`_ for more details. Other deprecations -------------------- ``NumericalInverseHermite`` has been deprecated from `scipy.stats` and moved to the `scipy.stats.sampling` submodule. It now uses the C implementation of the UNU.RAN library so the result of methods like ``ppf`` may vary slightly. Parameter ``tol`` has been deprecated and renamed to ``u_resolution``. The parameter ``max_intervals`` has also been deprecated and will be removed in a future release of SciPy. 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 <https://docs.scipy.org/doc/scipy/reference/dev/toolchain.html>`_. - 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. Other changes --------------- Some Fortran 77 code was modernized to be compatible with NAG's nagfor Fortran compiler (see, e.g., `PR 13229 <https://github.com/scipy/scipy/pull/13229>`_). ``threadpoolctl`` may now be used by our test suite to substantially improve the efficiency of parallel test suite runs. Authors --------- * endolith * adamadanandy + * akeemlh + * Anton Akhmerov * Marvin Albert + * alegresor + * Andrew Annex + * Pantelis Antonoudiou + * Ross Barnowski + * Christoph Baumgarten * Stephen Becker + * Nickolai Belakovski * Peter Bell * berberto + * Georgii Bocharov + * Evgeni Burovski * Matthias Bussonnier * CJ Carey * Justin Charlong + * Dennis Collaris + * David Cottrell + * cruyffturn + * da-woods + * Anirudh Dagar * Tiger Du + * Thomas Duvernay * Dani El-Ayyass + * Castedo Ellerman + * Donnie Erb + * Andreas Esders-Kopecky + * Livio F + * Isuru Fernando * Evelyn Fitzgerald + * Sara Fridovich-Keil + * Mark E Fuller + * Ralf Gommers * Kevin Richard Green + * guiweber + * Nitish Gupta + * h-vetinari * Matt Haberland * J. Hariharan + * Charles Harris * Trever Hines * Ian Hunt-Isaak + * ich + * Itrimel + * Jan-Hendrik Müller + * Jebby993 + * Evan W Jones + * Nathaniel Jones + * Jeffrey Kelling + * Malik Idrees Hasan Khan + * Sergey B Kirpichev * Kadatatlu Kishore + * Andrew Knyazev * Ravin Kumar + * Peter Mahler Larsen * Eric Larson * Antony Lee * Gregory R. Lee * Tim Leslie * lezcano + * Xingyu Liu * Christian Lorentzen * Lorenzo + * Smit Lunagariya + * Lv101Magikarp + * Yair M + * Cong Ma * Lorenzo Maffioli + * majiang + * Brian McFee + * Nicholas McKibben * John Speed Meyers + * millivolt9 + * Jarrod Millman * Harsh Mishra + * Boaz Mohar + * naelsondouglas + * Andrew Nelson * Nico Schlömer * Thomas Nowotny + * nullptr + * Teddy Ort + * Nick Papior * ParticularMiner + * Dima Pasechnik * Tirth Patel * Matti Picus * Ilhan Polat * Adrian Price-Whelan + * Quentin Barthélemy + * Sundar R + * Judah Rand + * Tyler Reddy * Renal-Of-Loon + * Frederic Renner + * Pamphile Roy * Bharath Saiguhan + * Atsushi Sakai * Eric Schanet + * Sebastian Wallkötter * serge-sans-paille * Reshama Shaikh + * Namami Shanker * Walter Simson + * Gagandeep Singh + * Leo C. Stein + * Albert Steppi * Kai Striega * Diana Sukhoverkhova * Søren Fuglede Jørgensen * Mike Taves * Ben Thompson + * Bas van Beek * Jacob Vanderplas * Dhruv Vats + * H. Vetinari + * Thomas Viehmann + * Pauli Virtanen * Vlad + * Arthur Volant * Samuel Wallan * Stefan van der Walt * Warren Weckesser * Josh Wilson * Haoyin Xu + * Rory Yorke * Egor Zemlyanoy * Gang Zhao + * 赵丰 (Zhao Feng) + A total of 132 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.7.3 ``` 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](https://github.com/scipy/scipy/issues/14688). Authors ======= * Anirudh Dagar * Ralf Gommers * Tyler Reddy * Pamphile Roy * Olivier Grisel * Isuru Fernando A total of 6 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ``` ### 1.7.2 ``` 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. Authors ======= * Peter Bell * da-woods + * Isuru Fernando * Ralf Gommers * Matt Haberland * Nicholas McKibben * Ilhan Polat * Judah Rand + * Tyler Reddy * Pamphile Roy * Charles Harris * Matti Picus * Hugo van Kemenade * Jacob Vanderplas A total of 14 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. ```
Links - PyPI: https://pypi.org/project/scipy - Changelog: https://pyup.io/changelogs/scipy/ - Homepage: https://scipy.org/

Update matplotlib from 3.4.3 to 3.6.1.

Changelog ### 3.6.1 ``` This is the first bugfix release of the 3.6.x series. This release contains several bug-fixes and adjustments: * A warning is no longer raised when constrained layout explicitly disabled and tight layout is applied * Add missing `get_cmap` method to `ColormapRegistry` * Adding a colorbar on a `ScalarMappable` that is not attached to an `Axes` is now deprecated instead of raising a hard error * Fix `barplot` being empty when first element is NaN * Fix `FigureManager.resize` on GTK4 * Fix `fill_between` compatibility with NumPy 1.24 development version * Fix `hexbin` with empty arrays and log scaling * Fix `resize_event` deprecation warnings when creating figure on macOS * Fix build in mingw * Fix compatibility with PyCharm's interagg backend * Fix crash on empty `Text` in PostScript backend * Fix generic font families in SVG exports * Fix horizontal colorbars with hatches * Fix misplaced mathtext using `eqnarray` * `stackplot` no longer changes the Axes cycler ``` ### 3.5.3 ``` This is the third bugfix release of the 3.5.x series. This release contains several bug-fixes and adjustments: * Fix alignment of over/under symbols * Fix bugs in colorbars: * alpha of extensions * `drawedges=True` with extensions * handling of `panchor=False` * Fix builds on Cygwin and IBM i * Fix contour labels in `SubFigure`s * Fix cursor output: * for `imshow` with all negative values * when using `BoundaryNorm` * Fix interactivity in IPython/Jupyter * Fix NaN handling in `errorbar` * Fix NumPy conversion from AstroPy unit arrays * Fix positional *markerfmt* passed to `stem` * Fix unpickling: * crash loading in a separate process * incorrect DPI when HiDPI screens ``` ### 3.5.2 ``` This is the second bugfix release of the 3.5.x series. This release contains several bug-fixes and adjustments: * Add support for Windows on ARM (source-only; no wheels provided yet) * Add year to concise date formatter when displaying less than 12 months * Disable `QuadMesh` mouse cursor to avoid severe performance regression in `pcolormesh` * Delay backend selection to allow choosing one in more cases * Fix automatic layout bugs in EPS output * Fix autoscaling of `scatter` plots * Fix clearing of subfigures * Fix colorbar exponents, inversion of extensions, and use on inset axes * Fix compatibility with various NumPy-like classes (e.g., Pandas, xarray, etc.) * Fix constrained layout bugs with mixed subgrids * Fix `errorbar` with dashes * Fix errors in conversion to GTK4 and Qt6 * Fix figure options accidentally re-ordering data * Fix keyboard focus of TkAgg backend * Fix manual selection of contour labels * Fix path effects on text with whitespace * Fix `quiver` in subfigures * Fix `RangeSlider.set_val` displaying incorrectly * Fix regressions in collection data limits * Fix `stairs` with no edgecolor * Fix some leaks in Tk backends * Fix tight layout DPI confusion * Fix tool button customizability and some tool manager bugs * Only set Tk HiDPI scaling-on-map for Windows systems * Partially allow TTC font collection files by selecting the first font ``` ### 3.5.1 ``` This is the first bugfix release of the 3.5.x series. This release contains several critical bug-fixes: * fix installation issues when setting a default backend * fix `add_lines` on horizontal colorbars * fix `streamplot` with start points on right or top edge * fix colorbars with boundaries or `NoNorm` * fix colorbars with negative contours * fix colorbars with tight layout * fix setting Axis label alignment to center * fix subfigure tight bounding box * fix subplot parameter window on macosx backend * fix unit handling in `Collections.set_offsets` * fix unyt integration in `errorbar` * re-display date offset in `ConciseDataFormatter` after zoom * reduce `do_3d_projection` deprecation warnings in external artists ```
Links - PyPI: https://pypi.org/project/matplotlib - Changelog: https://pyup.io/changelogs/matplotlib/ - Homepage: https://matplotlib.org

Update seaborn from 0.11.2 to 0.12.1.

Changelog ### 0.12.1 ``` This is an incremental release that is a recommended upgrade for all users. It addresses a handful of bugs / regressions in v0.12.0 and adds several features and enhancements to the new [objects interface](http://seaborn.pydata.org/tutorial/objects_interface). - Added the `objects.Text` mark (3051). - Added the `objects.Dash` mark (3074). - Added the `objects.Perc` stat (3063). - Added the `objects.Count` stat (3086). - The `objects.Band` and `objects.Range` marks will now cover the full extent of the data if `min` / `max` variables are not explicitly assigned or added in a transform (3056). - The `objects.Jitter` move now applies a small amount of jitter by default (3066). - Axes with a `objects.Nominal` scale now appear like categorical axes in classic seaborn, with fixed margins, no grid, and an inverted y axis (3069). - The `objects.Continuous.label` method now accepts `base=None` to override the default formatter with a log transform (3087). - Marks that sort along the orient axis (e.g. `objects.Line`) now use a stable algorithm (3064). - Added a `label` parameter to `pointplot`, which addresses a regression in 0.12.0 when `pointplot` is passed to `FacetGrid` (3016). - Fixed a bug that caused an exception when more than two layers with the same mappings were added to `objects.Plot` (3055). - Made `objects.PolyFit` robust to missing data (3010). - Fixed a bug in `objects.Plot` that occurred when data assigned to the orient coordinate had zero variance (3084). - Fixed a regression in `kdeplot` where passing `cmap` for an unfilled bivariate plot would raise an exception (3065). - Addressed a performance regression in `lineplot` with a large number of unique x values (3081). - Seaborn no longer contains doctest-style examples, simplifying the testing infrastructure (3034). ``` ### 0.12.0 ``` Introduction of the objects interface This release debuts the <span class="title-ref">seaborn.objects</span> interface, an entirely new approach to making plots with seaborn. It is the product of several years of design and 16 months of implementation work. The interface aims to provide a more declarative, composable, and extensible API for making statistical graphics. It is inspired by Wilkinson's grammar of graphics, offering a Pythonic API that is informed by the design of libraries such as <span class="title-ref">ggplot2</span> and <span class="title-ref">vega-lite</span> along with lessons from the past 10 years of seaborn's development. For more information and numerous examples, see the [tutorial chapter](http://seaborn.pydata.org//tutorial/objects_interface) and [API reference](http://seaborn.pydata.org/api.html#objects-interface). This initial release should be considered "experimental". While it is stable enough for serious use, there are definitely some rough edges, and some key features remain to be implemented. It is possible that breaking changes may occur over the next few minor releases. Please be patient with any limitations that you encounter and help the development by reporting issues when you find behavior surprising. Keyword-only arguments Seaborn's plotting functions now require explicit keywords for most arguments, following the deprecation of positional arguments in v0.11.0. With this enforcement, most functions have also had their parameter lists rearranged so that <span class="title-ref">data</span> is the first and only positional argument. This adds consistency across the various functions in the library. It also means that calling <span class="title-ref">func(data)</span> will do something for nearly all functions (those that support wide-form data) and that `pandas.DataFrame` can be piped directly into a plot. It is possible that the signatures will be loosened a bit in future releases so that <span class="title-ref">x</span> and <span class="title-ref">y</span> can be positional, but minimal support for positional arguments after this change will reduce the chance of inadvertent mis-specification (`2804`). Modernization of categorical scatterplots This release begins the process of modernizing the categorical plots, beginning with `stripplot` and `swarmplot`. These functions are sporting some enhancements that alleviate a few long-running frustrations (`2413`, `2447`): - The new `native_scale` parameter allows numeric or datetime categories to be plotted with their original scale rather than converted to strings and plotted at fixed intervals. - The new `formatter` parameter allows more control over the string representation of values on the categorical axis. There should also be improved defaults for some types, such as dates. - It is now possible to assign `hue` when using only one coordinate variable (i.e. only `x` or `y`). - It is now possible to disable the legend. The updates also harmonize behavior with functions that have been more recently introduced. This should be relatively non-disruptive, although a few defaults will change: - The functions now hook into matplotlib's unit system for plotting categorical data. (Seaborn's categorical functions actually predate support for categorical data in matplotlib.) This should mostly be transparent to the user, but it may resolve a few edge cases. For example, matplotlib interactivity should work better (e.g., for showing the data value under the cursor). - A color palette is no longer applied to levels of the categorical variable by default. It is now necessary to explicitly assign <span class="title-ref">hue</span> to see multiple colors (i.e., assign the same variable to <span class="title-ref">x</span>/<span class="title-ref">y</span> and <span class="title-ref">hue</span>). Passing <span class="title-ref">palette</span> without <span class="title-ref">hue</span> will continue to be honored for one release cycle. - Numeric <span class="title-ref">hue</span> variables now receive a continuous mapping by default, using the same rules as `scatterplot`. Pass <span class="title-ref">palette="deep"</span> to reproduce previous defaults. - The plots now follow the default property cycle; i.e. calling an axes-level function multiple times with the same active axes will produce different-colored artists. - Currently, assigning <span class="title-ref">hue</span> and then passing a <span class="title-ref">color</span> will produce a gradient palette. This is now deprecated, as it is easy to request a gradient with, e.g. <span class="title-ref">palette="light:blue"</span>. Similar enhancements / updates should be expected to roll out to other categorical plotting functions in future releases. There are also several function-specific enhancements: - In `stripplot`, a "strip" with a single observation will be plotted without jitter (`2413`) - In `swarmplot`, the points are now swarmed at draw time, meaning that the plot will adapt to further changes in axis scaling or tweaks to the plot layout (`2443`). - In `swarmplot`, the proportion of points that must overlap before issuing a warning can now be controlled with the <span class="title-ref">warn_thresh</span> parameter (`2447`). - In `swarmplot`, the order of the points in each swarm now matches the order in the original dataset; previously they were sorted. This affects only the underlying data stored in the matplotlib artist, not the visual representation (`2443`). More flexible errorbars Increased the flexibility of what can be shown by the internally-calculated errorbars for `lineplot`, `barplot`, and `pointplot`. With the new <span class="title-ref">errorbar</span> parameter, it is now possible to select bootstrap confidence intervals, percentile / predictive intervals, or intervals formed by scaled standard deviations or standard errors. The parameter also accepts an arbitrary function that maps from a vector to an interval. There is a new [user guide chapter](https://seaborn.pydata.org/tutorial/error_bars) demonstrating these options and explaining when you might want to use each one. As a consequence of this change, the <span class="title-ref">ci</span> parameter has been deprecated. Note that `regplot` retains the previous API, but it will likely be updated in a future release (`2407`, `2866`). Other updates - It is now possible to aggregate / sort a `lineplot` along the y axis using <span class="title-ref">orient="y"</span> (`2854`). - Made it easier to customize `FacetGrid` / `PairGrid` / `JointGrid` with a fluent (method-chained) style by adding <span class="title-ref">apply</span>/ <span class="title-ref">pipe</span> methods. Additionally, fixed the <span class="title-ref">tight_layout</span> and <span class="title-ref">refline</span> methods so that they return <span class="title-ref">self</span> (`2926`). - Added `FacetGrid.tick_params` and `PairGrid.tick_params` to customize the appearance of the ticks, tick labels, and gridlines of all subplots at once (`2944`). - Added a <span class="title-ref">width</span> parameter to `barplot` (`2860`). - It is now possible to specify <span class="title-ref">estimator</span> as a string in `barplot` and `pointplot`, in addition to a callable (`2866`). - Error bars in `regplot` now inherit the alpha value of the points they correspond to (`2540`). - When using `pairplot` with <span class="title-ref">corner=True</span> and <span class="title-ref">diag_kind=None</span>, the top left y axis label is no longer hidden (`2850`). - It is now possible to plot a discrete `histplot` as a step function or polygon (`2859`). - It is now possible to customize the appearance of elements in a `boxenplot` with <span class="title-ref">box_kws</span>/<span class="title-ref">line_kws</span>/<sp
pyup-bot commented 1 year ago

Closing this in favor of #389