Update dependency numpy to v2.1.0 #47
Loading…
Reference in a new issue
No description provided.
Delete branch "renovate/numpy-2.x"
Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?
This PR contains the following updates:
==2.0.1->==2.1.0Release Notes
numpy/numpy (numpy)
v2.1.0: 2.1.0 (Aug 18, 2024)Compare Source
NumPy 2.1.0 Release Notes
NumPy 2.1.0 provides support for the upcoming Python 3.13 release and
drops support for Python 3.9. In addition to the usual bug fixes and
updated Python support, it helps get us back into our usual release
cycle after the extended development of 2.0. The highlights for this
release are:
Python versions 3.10-3.13 are supported in this release.
New functions
New function
numpy.unstackA new function
np.unstack(array, axis=...)was added, which splits anarray into a tuple of arrays along an axis. It serves as the inverse of
[numpy.stack]{.title-ref}.
(gh-26579)
Deprecations
The
fix_importskeyword argument innumpy.saveis deprecated.Since NumPy 1.17,
numpy.saveuses a pickle protocol that no longersupports Python 2, and ignored
fix_importskeyword. This keywordis kept only for backward compatibility. It is now deprecated.
(gh-26452)
Passing non-integer inputs as the first argument of
[bincount]{.title-ref} is now deprecated, because such inputs are
silently cast to integers with no warning about loss of precision.
(gh-27076)
Expired deprecations
Scalars and 0D arrays are disallowed for
numpy.nonzeroandnumpy.ndarray.nonzero.(gh-26268)
set_string_functioninternal function was removed andPyArray_SetStringFunctionwas stubbed out.(gh-26611)
C API changes
API symbols now hidden but customizable
NumPy now defaults to hide the API symbols it adds to allow all NumPy
API usage. This means that by default you cannot dynamically fetch the
NumPy API from another library (this was never possible on windows).
If you are experiencing linking errors related to
PyArray_APIorPyArray_RUNTIME_VERSION, you can define theNPY_API_SYMBOL_ATTRIBUTEto opt-out of this change.
If you are experiencing problems due to an upstream header including
NumPy, the solution is to make sure you
#include "numpy/ndarrayobject.h"before their header and import NumPyyourself based on
including-the-c-api.(gh-26103)
Many shims removed from npy_3kcompat.h
Many of the old shims and helper functions were removed from
npy_3kcompat.h. If you find yourself in need of these, vendor theprevious version of the file into your codebase.
(gh-26842)
New
PyUFuncObjectfieldprocess_core_dims_funcThe field
process_core_dims_funcwas added to the structurePyUFuncObject. For generalized ufuncs, this field can be set to afunction of type
PyUFunc_ProcessCoreDimsFuncthat will be called whenthe ufunc is called. It allows the ufunc author to check that core
dimensions satisfy additional constraints, and to set output core
dimension sizes if they have not been provided.
(gh-26908)
New Features
Preliminary Support for Free-Threaded CPython 3.13
CPython 3.13 will be available as an experimental free-threaded build.
See https://py-free-threading.github.io, PEP 703 and the
CPython 3.13 release notes for more detail about free-threaded Python.
NumPy 2.1 has preliminary support for the free-threaded build of CPython
3.13. This support was enabled by fixing a number of C thread-safety
issues in NumPy. Before NumPy 2.1, NumPy used a large number of C global
static variables to store runtime caches and other state. We have either
refactored to avoid the need for global state, converted the global
state to thread-local state, or added locking.
Support for free-threaded Python does not mean that NumPy is thread
safe. Read-only shared access to ndarray should be safe. NumPy exposes
shared mutable state and we have not added any locking to the array
object itself to serialize access to shared state. Care must be taken in
user code to avoid races if you would like to mutate the same array in
multiple threads. It is certainly possible to crash NumPy by mutating an
array simultaneously in multiple threads, for example by calling a ufunc
and the
resizemethod simultaneously. For now our guidance is:"don't do that". In the future we would like to provide stronger
guarantees.
Object arrays in particular need special care, since the GIL previously
provided locking for object array access and no longer does. See
Issue #27199 for more information about object
arrays in the free-threaded build.
If you are interested in free-threaded Python, for example because you
have a multiprocessing-based workflow that you are interested in running
with Python threads, we encourage testing and experimentation.
If you run into problems that you suspect are because of NumPy, please
open an issue,
checking first if the bug also occurs in the "regular" non-free-threaded CPython 3.13
build. Many threading bugs can also occur in code that releases
the GIL; disabling the GIL only makes it easier to hit threading bugs.
(gh-26157)
f2pycan generate freethreading-compatible C extensionsPass
--freethreading-compatibleto the f2py CLI tool to produce a Cextension marked as compatible with the free threading CPython
interpreter. Doing so prevents the interpreter from re-enabling the GIL
at runtime when it imports the C extension. Note that
f2pydoes notanalyze fortran code for thread safety, so you must verify that the
wrapped fortran code is thread safe before marking the extension as
compatible.
(gh-26981)
numpy.reshapeandnumpy.ndarray.reshapenow supportshapeandcopyarguments.(gh-26292)
NumPy now supports DLPack v1, support for older versions will be
deprecated in the future.
(gh-26501)
numpy.asanyarraynow supportscopyanddevicearguments,matching
numpy.asarray.(gh-26580)
numpy.printoptions,numpy.get_printoptions, andnumpy.set_printoptionsnow support a new option,override_repr,for defining custom
repr(array)behavior.(gh-26611)
numpy.cumulative_sumandnumpy.cumulative_prodwere added asArray API compatible alternatives for
numpy.cumsumandnumpy.cumprod. The new functions can include a fixed initial(zeros for
sumand ones forprod) in the result.(gh-26724)
numpy.clipnow supportsmaxandminkeyword arguments whichare meant to replace
a_minanda_max. Also, fornp.clip(a)ornp.clip(a, None, None)a copy of the input array will be returnedinstead of raising an error.
(gh-26724)
numpy.astypenow supportsdeviceargument.(gh-26724)
Improvements
histogramauto-binning now returns bin sizes >=1 for integer input dataFor integer input data, bin sizes smaller than 1 result in spurious
empty bins. This is now avoided when the number of bins is computed
using one of the algorithms provided by
histogram_bin_edges.(gh-12150)
ndarrayshape-type parameter is now covariant and bound totuple[int, ...]Static typing for
ndarrayis a long-term effort that continues withthis change. It is a generic type with type parameters for the shape and
the data type. Previously, the shape type parameter could be any value.
This change restricts it to a tuple of ints, as one would expect from
using
ndarray.shape. Further, the shape-type parameter has beenchanged from invariant to covariant. This change also applies to the
subtypes of
ndarray, e.g.numpy.ma.MaskedArray. See thetyping docs
for more information.
(gh-26081)
np.quantilewith methodclosest_observationchooses nearest even order statisticThis changes the definition of nearest for border cases from the nearest
odd order statistic to nearest even order statistic. The numpy
implementation now matches other reference implementations.
(gh-26656)
lapack_liteis now thread safeNumPy provides a minimal low-performance version of LAPACK named
lapack_litethat can be used if no BLAS/LAPACK system is detected atbuild time.
Until now,
lapack_litewas not thread safe. Single-threaded use casesdid not hit any issues, but running linear algebra operations in
multiple threads could lead to errors, incorrect results, or segfaults
due to data races.
We have added a global lock, serializing access to
lapack_liteinmultiple threads.
(gh-26750)
The
numpy.printoptionscontext manager is now thread and async-safeIn prior versions of NumPy, the printoptions were defined using a
combination of Python and C global variables. We have refactored so the
state is stored in a python
ContextVar, making the context managerthread and async-safe.
(gh-26846)
Type hinting
numpy.polynomialStarting from the 2.1 release, PEP 484 type annotations have been
included for the functions and convenience classes in
numpy.polynomialand its sub-packages.
(gh-26897)
Improved
numpy.dtypestype hintsThe type annotations for
numpy.dtypesare now a better reflection ofthe runtime: The
numpy.dtypetype-aliases have been replaced withspecialized
dtypesubtypes, and the previously missing annotationsfor
numpy.dtypes.StringDTypehave been added.(gh-27008)
Performance improvements and changes
numpy.savenow uses pickle protocol version 4 for saving arrayswith object dtype, which allows for pickle objects larger than 4GB
and improves saving speed by about 5% for large arrays.
(gh-26388)
OpenBLAS on x86_64 and i686 is built with fewer kernels. Based on
benchmarking, there are 5 clusters of performance around these
kernels:
PRESCOTT NEHALEM SANDYBRIDGE HASWELL SKYLAKEX.(gh-27147)
OpenBLAS on windows is linked without quadmath, simplifying
licensing
(gh-27147)
Due to a regression in OpenBLAS on windows, the performance
improvements when using multiple threads for OpenBLAS 0.3.26 were
reverted.
(gh-27147)
ma.covandma.corrcoefare now significantly fasterThe private function has been refactored along with
ma.covandma.corrcoef. They are now significantly faster, particularly on large,masked arrays.
(gh-26285)
Changes
As
numpy.vecdotis now a ufunc it has a less precise signature.This is due to the limitations of ufunc's typing stub.
(gh-26313)
numpy.floor,numpy.ceil, andnumpy.truncnow won't performcasting to a floating dtype for integer and boolean dtype input
arrays.
(gh-26766)
ma.corrcoefmay return a slightly different resultA pairwise observation approach is currently used in
ma.corrcoeftocalculate the standard deviations for each pair of variables. This has
been changed as it is being used to normalise the covariance, estimated
using
ma.cov, which does not consider the observations for eachvariable in a pairwise manner, rendering it unnecessary. The
normalisation has been replaced by the more appropriate standard
deviation for each variable, which significantly reduces the wall time,
but will return slightly different estimates of the correlation
coefficients in cases where the observations between a pair of variables
are not aligned. However, it will return the same estimates in all other
cases, including returning the same correlation matrix as
corrcoefwhen using a masked array with no masked values.
(gh-26285)
Cast-safety fixes in
copytoandfullcopytonow uses NEP 50 correctly and applies this to its cast safety.Python integer to NumPy integer casts and Python float to NumPy float
casts are now considered "safe" even if assignment may fail or
precision may be lost. This means the following examples change
slightly:
np.copyto(int8_arr, 1000)previously performed an unsafe/same-kind castof the Python integer. It will now always raise, to achieve an
unsafe cast you must pass an array or NumPy scalar.
np.copyto(uint8_arr, 1000, casting="safe")will raise anOverflowError rather than a TypeError due to same-kind casting.
np.copyto(float32_arr, 1e300, casting="safe")will overflow toinf(float32 cannot hold1e300) rather raising a TypeError.Further, only the dtype is used when assigning NumPy scalars (or 0-d
arrays), meaning that the following behaves differently:
np.copyto(float32_arr, np.float64(3.0), casting="safe")raises.np.coptyo(int8_arr, np.int64(100), casting="safe")raises.Previously, NumPy checked whether the 100 fits the
int8_arr.This aligns
copyto,full, andfull_likewith the correct NumPy 2behavior.
(gh-27091)
Checksums
MD5
SHA256
Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Enabled.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.
This PR has been generated by Renovate Bot.
ef39d0f970tod2a91aea0e