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jason-neal / companion_simulations

Simulating combined host+companion spectra, and fitting to observed crires spectra.
MIT License
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Scheduled monthly dependency update for October #111

Closed pyup-bot closed 1 year ago

pyup-bot commented 1 year ago

Update astropy from 5.0.4 to 5.1.

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

Links - PyPI: https://pypi.org/project/astropy - Changelog: https://pyup.io/changelogs/astropy/ - Homepage: http://astropy.org

Update matplotlib from 3.5.1 to 3.6.0.

Changelog ### 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 ```
Links - PyPI: https://pypi.org/project/matplotlib - Changelog: https://pyup.io/changelogs/matplotlib/ - Homepage: https://matplotlib.org

Update joblib from 1.1.0 to 1.2.0.

Changelog ### 1.2.0 ``` ------------- - Fix a security issue where ``eval(pre_dispatch)`` could potentially run arbitrary code. Now only basic numerics are supported. https://github.com/joblib/joblib/pull/1327 - Make sure that joblib works even when multiprocessing is not available, for instance with Pyodide https://github.com/joblib/joblib/pull/1256 - Avoid unnecessary warnings when workers and main process delete the temporary memmap folder contents concurrently. https://github.com/joblib/joblib/pull/1263 - Vendor loky 3.1.0 with several fixes to more robustly forcibly terminate worker processes in case of a crash. https://github.com/joblib/joblib/pull/1269 - Fix memory alignment bug for pickles containing numpy arrays. This is especially important when loading the pickle with ``mmap_mode != None`` as the resulting ``numpy.memmap`` object would not be able to correct the misalignment without performing a memory copy. This bug would cause invalid computation and segmentation faults with native code that would directly access the underlying data buffer of a numpy array, for instance C/C++/Cython code compiled with older GCC versions or some old OpenBLAS written in platform specific assembly. https://github.com/joblib/joblib/pull/1254 - Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+. - Vendor loky 3.3.0 which fixes a bug with leaking processes in case of nested loky parallel calls and more reliability spawn the correct number of reusable workers. ```
Links - PyPI: https://pypi.org/project/joblib - Changelog: https://pyup.io/changelogs/joblib/ - Docs: https://joblib.readthedocs.io

Update numba from 0.55.1 to 0.56.2.

Changelog ### 0.56.1 ``` ---------------------------------- This is a bugfix release that supports NumPy 1.23 and fixes CUDA function caching. Pull-Requests: * PR `8239 <https://github.com/numba/numba/pull/8239>`_: Add decorator to run a test in a subprocess (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8276 <https://github.com/numba/numba/pull/8276>`_: Move Azure to use macos-11 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8310 <https://github.com/numba/numba/pull/8310>`_: CUDA: Fix Issue #8309 - atomics don't work on complex components (`Graham Markall <https://github.com/gmarkall>`_) * PR `8342 <https://github.com/numba/numba/pull/8342>`_: Upgrade to ubuntu-20.04 for azure pipeline CI (`jamesobutler <https://github.com/jamesobutler>`_) * PR `8356 <https://github.com/numba/numba/pull/8356>`_: Update setup.py, buildscripts, CI and docs to require setuptools<60 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8374 <https://github.com/numba/numba/pull/8374>`_: Don't pickle LLVM IR for CUDA code libraries (`Graham Markall <https://github.com/gmarkall>`_) * PR `8377 <https://github.com/numba/numba/pull/8377>`_: Add support for NumPy 1.23 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8384 <https://github.com/numba/numba/pull/8384>`_: Move strace() check into tests that actually need it (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8386 <https://github.com/numba/numba/pull/8386>`_: Fix the docs for numba.get_thread_id (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8407 <https://github.com/numba/numba/pull/8407>`_: Pin NumPy version to 1.18-1.24 (`Andre Masella <https://github.com/apmasell>`_) * PR `8411 <https://github.com/numba/numba/pull/8411>`_: update version support table for 0.56.1 (`esc <https://github.com/esc>`_) * PR `8412 <https://github.com/numba/numba/pull/8412>`_: Create changelog for 0.56.1 (`Andre Masella <https://github.com/apmasell>`_) * PR `8413 <https://github.com/numba/numba/pull/8413>`_: Fix Azure CI for NumPy 1.23 and use conda-forge scipy (`Siu Kwan Lam <https://github.com/sklam>`_) ``` ### 0.56.0 ``` ------------------------------ This release continues to add new features, bug fixes and stability improvements to Numba. Please note that this will be the last release that has support for Python 3.7 as the next release series (Numba 0.57) will support Python 3.11! Also note that, this will be the last release to support linux-32 packages produced by the Numba team. Python language support enhancements: * Previously missing support for large, in-line dictionaries and internal calls to functions with large numbers of keyword arguments in Python 3.10 has been added. * ``operator.mul`` now works for ``list`` s. * Literal slices, e.g. ``slice(1, 10, 2)`` can be returned from ``nopython`` mode functions. * The ``len`` function now works on ``dict_keys``, ``dict_values`` and ``dict_items`` . * Numba's ``set`` implementation now supports reference counted items e.g. strings. Numba specific feature enhancements: * The experimental ``jitclass`` feature gains support for a large number of ``builtin`` methods e.g. declaring ``__hash__`` or ``__getitem__`` for a ``jitclass`` type. * It's now possible to use ``vectorize`` on an already ``jit`` family decorated function. * Name mangling has been updated to emit compiled function names that exactly match the function name in Python. This means debuggers, like GDB, can be set to break directly on Python function names. * A GDB "pretty printing" support module has been added, when loaded into GDB Numba's internal representations of Python/NumPy types are rendered inside GDB as they would be in Python. * An experimental option is added to the ``jit`` family decorators to entirely turn off LLVM's optimisation passes for a given function (see ``_dbg_optnone`` kwarg in the ``jit`` decorator family). * A new environment variable is added ``NUMBA_EXTEND_VARIABLE_LIFETIMES``, which if set will extend the lifetime of variables to the end of their basic block, this to permit a debugging experience in GDB similar to that found in compiled C/C++/Fortran code. NumPy features/enhancements: * Initial support for passing, using and returning ``numpy.random.Generator`` instances has been added, this currently includes support for the ``random`` distribution. * The broadcasting functions ``np.broadcast_shapes`` and ``np.broadcast_arrays`` are now supported. * The ``min`` and ``max`` functions now work with ``np.timedelta64`` and ``np.datetime64`` types. * Sorting multi-dimensional arrays along the last axis is now supported in ``np.sort()``. * The ``np.clip`` function is updated to accept NumPy arrays for the ``a_min`` and ``a_max`` arguments. * The NumPy allocation routines (``np.empty`` , ``np.ones`` etc.) support shape arguments specified using members of ``enum.IntEnum`` s. * The function ``np.random.noncentral_chisquare`` is now supported. * The performance of functions ``np.full`` and ``np.ones`` has been improved. Parallel Accelerator enhancements: * The ``parallel=True`` functionality is enhanced through the addition of the functions ``numba.set_parallel_chunksize`` and ``numba.get_parallel_chunksize`` to permit a more fine grained scheduling of work defined in a parallel region. There is also support for adjusting the ``chunksize`` via a context manager. * The ``ID`` of a thread is now defined to be predictable and within a known range, it is available through calling the function ``numba.get_thread_id``. * The performance of ``stencil`` s has been improved in both serial and parallel execution. CUDA enhancements: * New functionality: * Self-recursive device functions. * Vector type support (``float4``, ``int2``, etc.). * Shared / local arrays of extension types can now be created. * Support for linking CUDA C / C++ device functions into Python kernels. * PTX generation for Compute Capabilities 8.6 and 8.7 - e.g. RTX A series, GTX 3000 series. * Comparison operations for ``float16`` types. * Performance improvements: * Context queries are no longer made during launch configuration. * Launch configurations are now LRU cached. * On-disk caching of CUDA kernels is now supported. * Documentation: many new examples added. Docs: * Numba now has an official "mission statement". * There's now a "version support table" in the documentation to act as an easy to use, single reference point, for looking up information about Numba releases and their required/supported dependencies. General Enhancements: * Numba imports more quickly in environments with large numbers of packages as it now uses ``importlib-metadata`` for querying other packages. * Emission of chrome tracing output is now supported for the internal compilation event handling system. * This release is tested and known to work when using the `Pyston <https://www.pyston.org/>`_ Python interpreter. Pull-Requests: * PR `5209 <https://github.com/numba/numba/pull/5209>`_: Use importlib to load numba extensions (`Stepan Rakitin <https://github.com/svrakitin>`_ `Graham Markall <https://github.com/gmarkall>`_ `stuartarchibald <https://github.com/stuartarchibald>`_) * PR `5877 <https://github.com/numba/numba/pull/5877>`_: Jitclass builtin methods (`Ethan Pronovost <https://github.com/EPronovost>`_ `Graham Markall <https://github.com/gmarkall>`_) * PR `6490 <https://github.com/numba/numba/pull/6490>`_: Stencil output allocated with np.empty now and new code to initialize the borders. (`Todd A. Anderson <https://github.com/DrTodd13>`_) * PR `7005 <https://github.com/numba/numba/pull/7005>`_: Make `numpy.searchsorted` match NumPy when first argument is unsorted (`Brandon T. Willard <https://github.com/brandonwillard>`_) * PR `7363 <https://github.com/numba/numba/pull/7363>`_: Update cuda.local.array to clarify "simple constant expression" (e.g. no NumPy ints) (`Sterling Baird <https://github.com/sgbaird>`_) * PR `7364 <https://github.com/numba/numba/pull/7364>`_: Removes an instance of signed integer overflow undefined behaviour. (`Tobias Sargeant <https://github.com/folded>`_) * PR `7537 <https://github.com/numba/numba/pull/7537>`_: Add chrome tracing (`Hadia Ahmed <https://github.com/hadia206>`_ `Siu Kwan Lam <https://github.com/sklam>`_) * PR `7556 <https://github.com/numba/numba/pull/7556>`_: Testhound/fp16 comparison (`Michael Collison <https://github.com/testhound>`_ `Graham Markall <https://github.com/gmarkall>`_) * PR `7586 <https://github.com/numba/numba/pull/7586>`_: Support for len on dict.keys, dict.values, and dict.items (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `7617 <https://github.com/numba/numba/pull/7617>`_: Numba gdb-python extension for printing (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7619 <https://github.com/numba/numba/pull/7619>`_: CUDA: Fix linking with PTX when compiling lazily (`Graham Markall <https://github.com/gmarkall>`_) * PR `7621 <https://github.com/numba/numba/pull/7621>`_: Add support for linking CUDA C / C++ with `cuda.jit` kernels (`Graham Markall <https://github.com/gmarkall>`_) * PR `7625 <https://github.com/numba/numba/pull/7625>`_: Combined parfor chunking and caching PRs. (`stuartarchibald <https://github.com/stuartarchibald>`_ `Todd A. Anderson <https://github.com/DrTodd13>`_ `Siu Kwan Lam <https://github.com/sklam>`_) * PR `7651 <https://github.com/numba/numba/pull/7651>`_: DOC: pypi and conda-forge badges (`Ray Bell <https://github.com/raybellwaves>`_) * PR `7660 <https://github.com/numba/numba/pull/7660>`_: Add support for np.broadcast_arrays (`Guilherme Leobas <https://github.com/guilhermeleobas>`_) * PR `7664 <https://github.com/numba/numba/pull/7664>`_: Flatten mangling dicts into a single dict (`Graham Markall <https://github.com/gmarkall>`_) * PR `7680 <https://github.com/numba/numba/pull/7680>`_: CUDA Docs: include example calling slow matmul (`Graham Markall <https://github.com/gmarkall>`_) * PR `7682 <https://github.com/numba/numba/pull/7682>`_: performance improvements to np.full and np.ones (`Rishi Kulkarni <https://github.com/rishi-kulkarni>`_) * PR `7684 <https://github.com/numba/numba/pull/7684>`_: DOC: remove incorrect warning in np.random reference (`Rishi Kulkarni <https://github.com/rishi-kulkarni>`_) * PR `7685 <https://github.com/numba/numba/pull/7685>`_: Don't convert setitems that have dimension mismatches to parfors. (`Todd A. Anderson <https://github.com/DrTodd13>`_) * PR `7690 <https://github.com/numba/numba/pull/7690>`_: Implemented np.random.noncentral_chisquare for all size arguments (`Rishi Kulkarni <https://github.com/rishi-kulkarni>`_) * PR `7695 <https://github.com/numba/numba/pull/7695>`_: `IntEnumMember` support for `np.empty`, `np.zeros`, and `np.ones` (`Benjamin Graham <https://github.com/benwilliamgraham>`_) * PR `7699 <https://github.com/numba/numba/pull/7699>`_: CUDA: Provide helpful error if the return type is missing for `declare_device` (`Graham Markall <https://github.com/gmarkall>`_) * PR `7700 <https://github.com/numba/numba/pull/7700>`_: Support for scalar arguments in Np.ascontiguousarray (`Dhruv Patel <https://github.com/DhruvPatel01>`_) * PR `7703 <https://github.com/numba/numba/pull/7703>`_: Ignore unsupported types in `ShapeEquivSet._getnames()` (`Benjamin Graham <https://github.com/benwilliamgraham>`_) * PR `7704 <https://github.com/numba/numba/pull/7704>`_: Move the type annotation pass to post legalization. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7709 <https://github.com/numba/numba/pull/7709>`_: CUDA: Fixes missing type annotation pass following #7704 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7712 <https://github.com/numba/numba/pull/7712>`_: Fixing issue 7693 (`stuartarchibald <https://github.com/stuartarchibald>`_ `Graham Markall <https://github.com/gmarkall>`_ `luk-f-a <https://github.com/luk-f-a>`_) * PR `7714 <https://github.com/numba/numba/pull/7714>`_: Support for boxing SliceLiteral type (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `7718 <https://github.com/numba/numba/pull/7718>`_: Bump llvmlite dependency to 0.39.0dev0 for Numba 0.56.0dev0 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7724 <https://github.com/numba/numba/pull/7724>`_: Update URLs in error messages to refer to RTD docs. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7728 <https://github.com/numba/numba/pull/7728>`_: Document that AOT-compiled functions do not check arg types (`Graham Markall <https://github.com/gmarkall>`_) * PR `7729 <https://github.com/numba/numba/pull/7729>`_: Handle Omitted/OmittedArgDataModel in DI generation. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7732 <https://github.com/numba/numba/pull/7732>`_: update release checklist following 0.55.0 RC1 (`esc <https://github.com/esc>`_) * PR `7736 <https://github.com/numba/numba/pull/7736>`_: Update CHANGE_LOG for 0.55.0 final. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7740 <https://github.com/numba/numba/pull/7740>`_: CUDA Python 11.6 support (`Graham Markall <https://github.com/gmarkall>`_) * PR `7744 <https://github.com/numba/numba/pull/7744>`_: Fix issues with locating/parsing source during DebugInfo emission. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7745 <https://github.com/numba/numba/pull/7745>`_: Fix the release year for Numba 0.55 change log entry. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7748 <https://github.com/numba/numba/pull/7748>`_: Fix #7713: Ensure _prng_random_hash return has correct bitwidth (`Graham Markall <https://github.com/gmarkall>`_) * PR `7749 <https://github.com/numba/numba/pull/7749>`_: Refactor threading layer priority tests to not use stdout/stderr (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7752 <https://github.com/numba/numba/pull/7752>`_: Fix #7751: Use original filename for array exprs (`Graham Markall <https://github.com/gmarkall>`_) * PR `7755 <https://github.com/numba/numba/pull/7755>`_: CUDA: Deprecate support for CC < 5.3 and CTK < 10.2 (`Graham Markall <https://github.com/gmarkall>`_) * PR `7763 <https://github.com/numba/numba/pull/7763>`_: Update Read the Docs configuration (automatic) (`readthedocs-assistant <https://github.com/readthedocs-assistant>`_) * PR `7764 <https://github.com/numba/numba/pull/7764>`_: Add dbg_optnone and dbg_extend_lifetimes flags (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `7771 <https://github.com/numba/numba/pull/7771>`_: Move function unique ID to abi-tags (`stuartarchibald <https://github.com/stuartarchibald>`_ `Siu Kwan Lam <https://github.com/sklam>`_) * PR `7772 <https://github.com/numba/numba/pull/7772>`_: CUDA: Add Support to Creating `StructModel` Array (`Michael Wang <https://github.com/isVoid>`_) * PR `7776 <https://github.com/numba/numba/pull/7776>`_: Updates coverage.py config (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7777 <https://github.com/numba/numba/pull/7777>`_: Remove reference existing issue from GH template. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7778 <https://github.com/numba/numba/pull/7778>`_: Remove long deprecated flags from the CLI. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7780 <https://github.com/numba/numba/pull/7780>`_: Fix sets with reference counted items (`Benjamin Graham <https://github.com/benwilliamgraham>`_) * PR `7782 <https://github.com/numba/numba/pull/7782>`_: adding reminder to check on deprecations (`esc <https://github.com/esc>`_) * PR `7783 <https://github.com/numba/numba/pull/7783>`_: remove upper limit on Python version (`esc <https://github.com/esc>`_) * PR `7786 <https://github.com/numba/numba/pull/7786>`_: Remove dependency on intel-openmp for OSX (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7788 <https://github.com/numba/numba/pull/7788>`_: Avoid issue with DI gen for arrayexprs. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7796 <https://github.com/numba/numba/pull/7796>`_: update change-log for 0.55.1 (`esc <https://github.com/esc>`_) * PR `7797 <https://github.com/numba/numba/pull/7797>`_: prune README (`esc <https://github.com/esc>`_) * PR `7799 <https://github.com/numba/numba/pull/7799>`_: update the release checklist post 0.55.1 (`esc <https://github.com/esc>`_) * PR `7801 <https://github.com/numba/numba/pull/7801>`_: add sdist command and umask reminder (`esc <https://github.com/esc>`_) * PR `7804 <https://github.com/numba/numba/pull/7804>`_: update local references from master -> main (`esc <https://github.com/esc>`_) * PR `7805 <https://github.com/numba/numba/pull/7805>`_: Enhance source line finding logic for debuginfo (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `7809 <https://github.com/numba/numba/pull/7809>`_: Updates the gdb configuration to accept a binary name or a path. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7813 <https://github.com/numba/numba/pull/7813>`_: Extend parfors test timeout for aarch64. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7814 <https://github.com/numba/numba/pull/7814>`_: CUDA Dispatcher refactor (`Graham Markall <https://github.com/gmarkall>`_) * PR `7815 <https://github.com/numba/numba/pull/7815>`_: CUDA Dispatcher refactor 2: inherit from `dispatcher.Dispatcher` (`Graham Markall <https://github.com/gmarkall>`_) * PR `7817 <https://github.com/numba/numba/pull/7817>`_: Update intersphinx URLs for NumPy and llvmlite. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7823 <https://github.com/numba/numba/pull/7823>`_: Add renamed vars to callee scope such that it is self consistent. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7829 <https://github.com/numba/numba/pull/7829>`_: CUDA: Support `Enum/IntEnum` in Kernel (`Michael Wang <https://github.com/isVoid>`_) * PR `7833 <https://github.com/numba/numba/pull/7833>`_: Add version support information table to docs. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7835 <https://github.com/numba/numba/pull/7835>`_: Fix pickling error when module cannot be imported (`idorrington <https://github.com/idorrington>`_) * PR `7836 <https://github.com/numba/numba/pull/7836>`_: min() and max() support for np.datetime and np.timedelta (`Benjamin Graham <https://github.com/benwilliamgraham>`_) * PR `7837 <https://github.com/numba/numba/pull/7837>`_: Initial refactoring of parfor reduction lowering (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `7845 <https://github.com/numba/numba/pull/7845>`_: change time.time() to time.perf_counter() in docs (`Nopileos2 <https://github.com/Nopileos2>`_) * PR `7846 <https://github.com/numba/numba/pull/7846>`_: Fix CUDA enum vectorize test on Windows (`Graham Markall <https://github.com/gmarkall>`_) * PR `7848 <https://github.com/numba/numba/pull/7848>`_: Support for int * list (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `7850 <https://github.com/numba/numba/pull/7850>`_: CUDA: Pass `fastmath` compiler flag down to `compile_ptx` and `compile_device`; Improve `fastmath` tests (`Michael Wang <https://github.com/isVoid>`_) * PR `7855 <https://github.com/numba/numba/pull/7855>`_: Ensure np.argmin/no.argmax return type is intp (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7858 <https://github.com/numba/numba/pull/7858>`_: CUDA: Deprecate `ptx` Attribute and Update Tests (`Graham Markall <https://github.com/gmarkall>`_ `Michael Wang <https://github.com/isVoid>`_) * PR `7861 <https://github.com/numba/numba/pull/7861>`_: Fix a spelling mistake in README (`Zizheng Guo <https://github.com/gzz2000>`_) * PR `7864 <https://github.com/numba/numba/pull/7864>`_: Fix cross_iter_dep check. (`Todd A. Anderson <https://github.com/DrTodd13>`_) * PR `7865 <https://github.com/numba/numba/pull/7865>`_: Remove add_user_function (`Graham Markall <https://github.com/gmarkall>`_) * PR `7866 <https://github.com/numba/numba/pull/7866>`_: Support for large numbers of args/kws with Python 3.10 (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `7878 <https://github.com/numba/numba/pull/7878>`_: CUDA: Remove some deprecated support, add CC 8.6 and 8.7 (`Graham Markall <https://github.com/gmarkall>`_) * PR `7893 <https://github.com/numba/numba/pull/7893>`_: Use uuid.uuid4() as the key in serialization. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7895 <https://github.com/numba/numba/pull/7895>`_: Remove use of `llvmlite.llvmpy` (`Andre Masella <https://github.com/apmasell>`_) * PR `7898 <https://github.com/numba/numba/pull/7898>`_: Skip test_ptds under cuda-memcheck (`Graham Markall <https://github.com/gmarkall>`_) * PR `7901 <https://github.com/numba/numba/pull/7901>`_: Pyston compatibility for the test suite (`Kevin Modzelewski <https://github.com/kmod>`_) * PR `7904 <https://github.com/numba/numba/pull/7904>`_: Support m1 (`esc <https://github.com/esc>`_) * PR `7911 <https://github.com/numba/numba/pull/7911>`_: added sys import (`Nightfurex <https://github.com/Nightfurex>`_) * PR `7915 <https://github.com/numba/numba/pull/7915>`_: CUDA: Fix test checking debug info rendering. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7918 <https://github.com/numba/numba/pull/7918>`_: Add JIT examples to CUDA docs (`brandon-b-miller <https://github.com/brandon-b-miller>`_ `Graham Markall <https://github.com/gmarkall>`_) * PR `7919 <https://github.com/numba/numba/pull/7919>`_: Disallow //= reductions in pranges. (`Todd A. Anderson <https://github.com/DrTodd13>`_) * PR `7924 <https://github.com/numba/numba/pull/7924>`_: Retain non-modified index tuple components. (`Todd A. Anderson <https://github.com/DrTodd13>`_) * PR `7939 <https://github.com/numba/numba/pull/7939>`_: Fix rendering in feature request template. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7940 <https://github.com/numba/numba/pull/7940>`_: Implemented `np.allclose` in `numba/np/arraymath.py` (`Gagandeep Singh <https://github.com/czgdp1807>`_) * PR `7941 <https://github.com/numba/numba/pull/7941>`_: Remove debug dump output from closure inlining pass. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7946 <https://github.com/numba/numba/pull/7946>`_: instructions for creating a build environment were outdated (`esc <https://github.com/esc>`_) * PR `7949 <https://github.com/numba/numba/pull/7949>`_: Add Cuda Vector Types (`Michael Wang <https://github.com/isVoid>`_) * PR `7950 <https://github.com/numba/numba/pull/7950>`_: mission statement (`esc <https://github.com/esc>`_) * PR `7956 <https://github.com/numba/numba/pull/7956>`_: Stop using pip for 3.10 on public ci (Revert "start testing Python 3.10 on public CI") (`esc <https://github.com/esc>`_) * PR `7957 <https://github.com/numba/numba/pull/7957>`_: Use cloudpickle for disk caches (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `7958 <https://github.com/numba/numba/pull/7958>`_: `numpy.clip` accept `numpy.array` for `a_min`, `a_max` (`Gagandeep Singh <https://github.com/czgdp1807>`_) * PR `7959 <https://github.com/numba/numba/pull/7959>`_: Permit a new array model to have a super set of array model fields. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7961 <https://github.com/numba/numba/pull/7961>`_: `numba.typed.typeddict.Dict.get` uses `castedkey` to avoid returning default value even if the key is present (`Gagandeep Singh <https://github.com/czgdp1807>`_) * PR `7963 <https://github.com/numba/numba/pull/7963>`_: remove the roadmap from the sphinx based docs (`esc <https://github.com/esc>`_) * PR `7964 <https://github.com/numba/numba/pull/7964>`_: Support for large constant dictionaries in Python 3.10 (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `7965 <https://github.com/numba/numba/pull/7965>`_: Use uuid4 instead of PID in cache temp name to prevent collisions. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7971 <https://github.com/numba/numba/pull/7971>`_: lru cache for configure call (`Tingkai Liu <https://github.com/TK-21st>`_) * PR `7972 <https://github.com/numba/numba/pull/7972>`_: Fix fp16 support for cuda shared array (`Michael Collison <https://github.com/testhound>`_ `Graham Markall <https://github.com/gmarkall>`_) * PR `7986 <https://github.com/numba/numba/pull/7986>`_: Small caching refactor to support target cache implementations (`Graham Markall <https://github.com/gmarkall>`_) * PR `7994 <https://github.com/numba/numba/pull/7994>`_: Supporting multidimensional arrays in quick sort (`Gagandeep Singh <https://github.com/czgdp1807>`_ `Siu Kwan Lam <https://github.com/sklam>`_) * PR `7996 <https://github.com/numba/numba/pull/7996>`_: Fix binding logic in `overload_glue`. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `7999 <https://github.com/numba/numba/pull/7999>`_: Remove `overload_glue` for NumPy allocators. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8003 <https://github.com/numba/numba/pull/8003>`_: Add np.broadcast_shapes (`Guilherme Leobas <https://github.com/guilhermeleobas>`_) * PR `8004 <https://github.com/numba/numba/pull/8004>`_: CUDA fixes for Windows (`Graham Markall <https://github.com/gmarkall>`_) * PR `8014 <https://github.com/numba/numba/pull/8014>`_: Fix support for {real,imag} array attrs in Parfors. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8016 <https://github.com/numba/numba/pull/8016>`_: [Docs] [Very Minor] Make `numba.jit` boundscheck doc line consistent (`Kyle Martin <https://github.com/martinky24>`_) * PR `8017 <https://github.com/numba/numba/pull/8017>`_: Update FAQ to include details about using debug-only option (`Guilherme Leobas <https://github.com/guilhermeleobas>`_) * PR `8027 <https://github.com/numba/numba/pull/8027>`_: Support for NumPy 1.22 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8031 <https://github.com/numba/numba/pull/8031>`_: Support for Numpy BitGenerators PR#1 - Core Generator Support (`Kaustubh <https://github.com/kc611>`_) * PR `8035 <https://github.com/numba/numba/pull/8035>`_: Fix a couple of typos RE implementation (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8037 <https://github.com/numba/numba/pull/8037>`_: CUDA self-recursion tests (`Graham Markall <https://github.com/gmarkall>`_) * PR `8044 <https://github.com/numba/numba/pull/8044>`_: Make Python 3.10 kwarg peephole less restrictive (`Nick Riasanovsky <https://github.com/njriasan>`_) * PR `8046 <https://github.com/numba/numba/pull/8046>`_: Fix caching test failures (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8049 <https://github.com/numba/numba/pull/8049>`_: support str(bool) syntax (`LI Da <https://github.com/dlee992>`_) * PR `8052 <https://github.com/numba/numba/pull/8052>`_: Ensure pthread is linked in when building for ppc64le. (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8056 <https://github.com/numba/numba/pull/8056>`_: Move caching tests from test_dispatcher to test_caching (`Graham Markall <https://github.com/gmarkall>`_) * PR `8057 <https://github.com/numba/numba/pull/8057>`_: Fix coverage checking (`Graham Markall <https://github.com/gmarkall>`_) * PR `8064 <https://github.com/numba/numba/pull/8064>`_: Rename "nb:run_pass" to "numba:run_pass" and document it. (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8065 <https://github.com/numba/numba/pull/8065>`_: Fix PyLowering mishandling starargs (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8068 <https://github.com/numba/numba/pull/8068>`_: update changelog for 0.55.2 (`esc <https://github.com/esc>`_) * PR `8077 <https://github.com/numba/numba/pull/8077>`_: change return type of np.broadcast_shapes to a tuple (`Guilherme Leobas <https://github.com/guilhermeleobas>`_) * PR `8080 <https://github.com/numba/numba/pull/8080>`_: Fix windows test failure due to timeout when the machine is slow poss… (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8081 <https://github.com/numba/numba/pull/8081>`_: Fix erroneous array count in parallel gufunc kernel generation. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8089 <https://github.com/numba/numba/pull/8089>`_: Support on-disk caching in the CUDA target (`Graham Markall <https://github.com/gmarkall>`_) * PR `8097 <https://github.com/numba/numba/pull/8097>`_: Exclude libopenblas 0.3.20 on osx-arm64 (`esc <https://github.com/esc>`_) * PR `8099 <https://github.com/numba/numba/pull/8099>`_: Fix Py_DECREF use in case of error state (for devicearray). (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8102 <https://github.com/numba/numba/pull/8102>`_: Combine numpy run_constrained in meta.yaml to the run requirements (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8109 <https://github.com/numba/numba/pull/8109>`_: Pin TBB support with respect to incompatible 2021.6 API. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8118 <https://github.com/numba/numba/pull/8118>`_: Update release checklists post 0.55.2 (`esc <https://github.com/esc>`_) * PR `8123 <https://github.com/numba/numba/pull/8123>`_: Fix CUDA print tests on Windows (`Graham Markall <https://github.com/gmarkall>`_) * PR `8124 <https://github.com/numba/numba/pull/8124>`_: Add explicit checks to all allocators in the NRT. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8126 <https://github.com/numba/numba/pull/8126>`_: Mark gufuncs as having mutable outputs (`Andre Masella <https://github.com/apmasell>`_) * PR `8133 <https://github.com/numba/numba/pull/8133>`_: Fix #8132. Regression in Record.make_c_struct for handling nestedarray (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8137 <https://github.com/numba/numba/pull/8137>`_: CUDA: Fix #7806, Division by zero stops the kernel (`Graham Markall <https://github.com/gmarkall>`_) * PR `8142 <https://github.com/numba/numba/pull/8142>`_: CUDA: Fix some missed changes from dropping 9.2 (`Graham Markall <https://github.com/gmarkall>`_) * PR `8144 <https://github.com/numba/numba/pull/8144>`_: Fix NumPy capitalisation in docs. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8145 <https://github.com/numba/numba/pull/8145>`_: Allow ufunc builder to use previously JITed function (`Andre Masella <https://github.com/apmasell>`_) * PR `8151 <https://github.com/numba/numba/pull/8151>`_: pin NumPy to build 0 of 1.19.2 on public CI (`esc <https://github.com/esc>`_) * PR `8163 <https://github.com/numba/numba/pull/8163>`_: CUDA: Remove context query in launch config (`Graham Markall <https://github.com/gmarkall>`_) * PR `8165 <https://github.com/numba/numba/pull/8165>`_: Restrict strace based tests to be linux only via support feature. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8170 <https://github.com/numba/numba/pull/8170>`_: CUDA: Fix missing space in low occupancy warning (`Graham Markall <https://github.com/gmarkall>`_) * PR `8175 <https://github.com/numba/numba/pull/8175>`_: make build and upload order consistent (`esc <https://github.com/esc>`_) * PR `8181 <https://github.com/numba/numba/pull/8181>`_: Fix various typos (`luzpaz <https://github.com/luzpaz>`_) * PR `8187 <https://github.com/numba/numba/pull/8187>`_: Update CHANGE_LOG for 0.55.2 (`stuartarchibald <https://github.com/stuartarchibald>`_ `esc <https://github.com/esc>`_) * PR `8189 <https://github.com/numba/numba/pull/8189>`_: updated version support information for 0.55.2/0.57 (`esc <https://github.com/esc>`_) * PR `8191 <https://github.com/numba/numba/pull/8191>`_: CUDA: Update deprecation notes for 0.56. (`Graham Markall <https://github.com/gmarkall>`_) * PR `8192 <https://github.com/numba/numba/pull/8192>`_: Update CHANGE_LOG for 0.56.0 (`stuartarchibald <https://github.com/stuartarchibald>`_ `esc <https://github.com/esc>`_ `Siu Kwan Lam <https://github.com/sklam>`_) * PR `8195 <https://github.com/numba/numba/pull/8195>`_: Make the workqueue threading backend once again fork safe. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8196 <https://github.com/numba/numba/pull/8196>`_: Fix numerical tolerance in parfors caching test. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8197 <https://github.com/numba/numba/pull/8197>`_: Fix `isinstance` warning check test. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8203 <https://github.com/numba/numba/pull/8203>`_: pin llvmlite 0.39 for public CI builds (`esc <https://github.com/esc>`_) * PR `8255 <https://github.com/numba/numba/pull/8255>`_: CUDA: Make numba.cuda.tests.doc_examples.ffi a module to fix #8252 (`Graham Markall <https://github.com/gmarkall>`_) * PR `8274 <https://github.com/numba/numba/pull/8274>`_: Update version support table doc for 0.56. (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8275 <https://github.com/numba/numba/pull/8275>`_: Update CHANGE_LOG for 0.56.0 final (`stuartarchibald <https://github.com/stuartarchibald>`_) Authors: * `Andre Masella <https://github.com/apmasell>`_ * `Benjamin Graham <https://github.com/benwilliamgraham>`_ * `brandon-b-miller <https://github.com/brandon-b-miller>`_ * `Brandon T. Willard <https://github.com/brandonwillard>`_ * `Gagandeep Singh <https://github.com/czgdp1807>`_ * `Dhruv Patel <https://github.com/DhruvPatel01>`_ * `LI Da <https://github.com/dlee992>`_ * `Todd A. Anderson <https://github.com/DrTodd13>`_ * `Ethan Pronovost <https://github.com/EPronovost>`_ * `esc <https://github.com/esc>`_ * `Tobias Sargeant <https://github.com/folded>`_ * `Graham Markall <https://github.com/gmarkall>`_ * `Guilherme Leobas <https://github.com/guilhermeleobas>`_ * `Zizheng Guo <https://github.com/gzz2000>`_ * `Hadia Ahmed <https://github.com/hadia206>`_ * `idorrington <https://github.com/idorrington>`_ * `Michael Wang <https://github.com/isVoid>`_ * `Kaustubh <https://github.com/kc611>`_ * `Kevin Modzelewski <https://github.com/kmod>`_ * `luk-f-a <https://github.com/luk-f-a>`_ * `luzpaz <https://github.com/luzpaz>`_ * `Kyle Martin <https://github.com/martinky24>`_ * `Nightfurex <https://github.com/Nightfurex>`_ * `Nick Riasanovsky <https://github.com/njriasan>`_ * `Nopileos2 <https://github.com/Nopileos2>`_ * `Ray Bell <https://github.com/raybellwaves>`_ * `readthedocs-assistant <https://github.com/readthedocs-assistant>`_ * `Rishi Kulkarni <https://github.com/rishi-kulkarni>`_ * `Sterling Baird <https://github.com/sgbaird>`_ * `Siu Kwan Lam <https://github.com/sklam>`_ * `stuartarchibald <https://github.com/stuartarchibald>`_ * `Stepan Rakitin <https://github.com/svrakitin>`_ * `Michael Collison <https://github.com/testhound>`_ * `Tingkai Liu <https://github.com/TK-21st>`_ ``` ### 0.55.2 ``` ----------------------------- This is a maintenance release to support NumPy 1.22 and Apple M1. Pull-Requests: * PR `8067 <https://github.com/numba/numba/pull/8067>`_: Backport #8027: Support for NumPy 1.22 (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8069 <https://github.com/numba/numba/pull/8069>`_: Install llvmlite 0.38 for Numba 0.55.* (`esc <https://github.com/esc>`_) * PR `8075 <https://github.com/numba/numba/pull/8075>`_: update max NumPy for 0.55.2 (`esc <https://github.com/esc>`_) * PR `8078 <https://github.com/numba/numba/pull/8078>`_: Backport #7804: update local references from master -> main (`esc <https://github.com/esc>`_) * PR `8082 <https://github.com/numba/numba/pull/8082>`_: Backport #8080: fix windows failure due to timeout (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8084 <https://github.com/numba/numba/pull/8084>`_: Pin meta.yaml to llvmlite 0.38 series (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8093 <https://github.com/numba/numba/pull/8093>`_: Backport #7904: Support m1 (`esc <https://github.com/esc>`_) * PR `8094 <https://github.com/numba/numba/pull/8094>`_: Backport #8052 Ensure pthread is linked in when building for ppc64le. (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8098 <https://github.com/numba/numba/pull/8098>`_: Backport #8097: Exclude libopenblas 0.3.20 on osx-arm64 (`esc <https://github.com/esc>`_) * PR `8100 <https://github.com/numba/numba/pull/8100>`_: Backport #7786 for 0.55.2: Remove dependency on intel-openmp for OSX (`stuartarchibald <https://github.com/stuartarchibald>`_) * PR `8103 <https://github.com/numba/numba/pull/8103>`_: Backport #8102 to fix numpy requirements (`Siu Kwan Lam <https://github.com/sklam>`_) * PR `8114 <https://github.com/numba/numba/pull/8114>`_: Backport #8109 Pin TBB support with respect to incompatible 2021.6 API. (`stuartarchibald <https://github.com/stuartarchibald>`_) Total PRs: 12 Authors: * `esc <https://github.com/esc>`_ * `Siu Kwan Lam <https://github.com/sklam>`_ * `stuartarchibald <https://github.com/stuartarchibald>`_ Total authors: 3 ```
Links - PyPI: https://pypi.org/project/numba - Changelog: https://pyup.io/changelogs/numba/ - Homepage: https://numba.pydata.org

Update numpy from 1.22.3 to 1.23.3.

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 multiprocess from 0.70.12.2 to 0.70.13.

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

Links - PyPI: https://pypi.org/project/multiprocess - Changelog: https://pyup.io/changelogs/multiprocess/ - Repo: https://github.com/uqfoundation/multiprocess

Update pandas from 1.4.1 to 1.5.0.

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

Links - PyPI: https://pypi.org/project/pandas - Homepage: https://pandas.pydata.org

Update scipy from 1.8.0 to 1.9.1.

Changelog ### 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) *
pyup-bot commented 1 year ago

Closing this in favor of #112