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Update dependency numpy to v2 #1386

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Update dependency numpy to v2 #1386

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@renovate renovate bot commented Oct 20, 2024

This PR contains the following updates:

Package Change Age Adoption Passing Confidence
numpy (changelog) ^1.24.1 -> ^2.0.0 age adoption passing confidence
numpy (changelog) ==1.26.4 -> ==2.1.3 age adoption passing confidence

Release Notes

numpy/numpy (numpy)

v2.1.3

Compare Source

v2.1.2

Compare Source

v2.1.1: 2.1.1 (Sep 3, 2024)

Compare Source

NumPy 2.1.1 Release Notes

NumPy 2.1.1 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.0 release.

The Python versions supported by this release are 3.10-3.13.

Contributors

A total of 7 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Andrew Nelson
  • Charles Harris
  • Mateusz Sokół
  • Maximilian Weigand +
  • Nathan Goldbaum
  • Pieter Eendebak
  • Sebastian Berg
Pull requests merged

A total of 10 pull requests were merged for this release.

  • #​27236: REL: Prepare for the NumPy 2.1.0 release [wheel build]
  • #​27252: MAINT: prepare 2.1.x for further development
  • #​27259: BUG: revert unintended change in the return value of set_printoptions
  • #​27266: BUG: fix reference counting bug in __array_interface__ implementation...
  • #​27267: TST: Add regression test for missing descr in array-interface
  • #​27276: BUG: Fix #​27256 and #​27257
  • #​27278: BUG: Fix array_equal for numeric and non-numeric scalar types
  • #​27287: MAINT: Update maintenance/2.1.x after the 2.0.2 release
  • #​27303: BLD: cp311- macosx_arm64 wheels [wheel build]
  • #​27304: BUG: f2py: better handle filtering of public/private subroutines
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v2.1.0

Compare Source

v2.0.2: NumPy 2.0.2 release (Aug 26, 2024)

Compare Source

NumPy 2.0.2 Release Notes

NumPy 2.0.2 is a maintenance release that fixes bugs and regressions
discovered after the 2.0.1 release.

The Python versions supported by this release are 3.9-3.12.

Contributors

A total of 13 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Bruno Oliveira +
  • Charles Harris
  • Chris Sidebottom
  • Christian Heimes +
  • Christopher Sidebottom
  • Mateusz Sokół
  • Matti Picus
  • Nathan Goldbaum
  • Pieter Eendebak
  • Raghuveer Devulapalli
  • Ralf Gommers
  • Sebastian Berg
  • Yair Chuchem +
Pull requests merged

A total of 19 pull requests were merged for this release.

  • #​27000: REL: Prepare for the NumPy 2.0.1 release [wheel build]
  • #​27001: MAINT: prepare 2.0.x for further development
  • #​27021: BUG: cfuncs.py: fix crash when sys.stderr is not available
  • #​27022: DOC: Fix migration note for alltrue and sometrue
  • #​27061: BUG: use proper input and output descriptor in array_assign_subscript...
  • #​27073: BUG: Mirror VQSORT_ENABLED logic in Quicksort
  • #​27074: BUG: Bump Highway to latest master
  • #​27077: BUG: Off by one in memory overlap check
  • #​27122: BUG: Use the new npyv_loadable_stride_ functions for ldexp and...
  • #​27126: BUG: Bump Highway to latest
  • #​27128: BUG: add missing error handling in public_dtype_api.c
  • #​27129: BUG: fix another cast setup in array_assign_subscript
  • #​27130: BUG: Fix building NumPy in FIPS mode
  • #​27131: BLD: update vendored Meson for cross-compilation patches
  • #​27146: MAINT: Scipy openblas 0.3.27.44.4
  • #​27151: BUG: Do not accidentally store dtype metadata in np.save
  • #​27195: REV: Revert undef I and document it
  • #​27213: BUG: Fix NPY_RAVEL_AXIS on backwards compatible NumPy 2 builds
  • #​27279: BUG: Fix array_equal for numeric and non-numeric scalar types
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v2.0.1

Compare Source

NumPy 2.0.1 Release Notes

NumPy 2.0.1 is a maintenance release that fixes bugs and regressions
discovered after the 2.0.0 release. NumPy 2.0.1 is the last planned
release in the 2.0.x series, 2.1.0rc1 should be out shortly.

The Python versions supported by this release are 3.9-3.12.

NOTE: Do not use the GitHub generated "Source code" files listed in the "Assets", they are garbage.

Improvements

np.quantile with method closest_observation chooses nearest even order statistic

This 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)

Contributors

A total of 15 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • @​vahidmech +
  • Alex Herbert +
  • Charles Harris
  • Giovanni Del Monte +
  • Leo Singer
  • Lysandros Nikolaou
  • Matti Picus
  • Nathan Goldbaum
  • Patrick J. Roddy +
  • Raghuveer Devulapalli
  • Ralf Gommers
  • Rostan Tabet +
  • Sebastian Berg
  • Tyler Reddy
  • Yannik Wicke +

Pull requests merged

A total of 24 pull requests were merged for this release.

  • #​26711: MAINT: prepare 2.0.x for further development
  • #​26792: TYP: fix incorrect import in ma/extras.pyi stub
  • #​26793: DOC: Mention '1.25' legacy printing mode in set_printoptions
  • #​26794: DOC: Remove mention of NaN and NAN aliases from constants
  • #​26821: BLD: Fix x86-simd-sort build failure on openBSD
  • #​26822: BUG: Ensure output order follows input in numpy.fft
  • #​26823: TYP: fix missing sys import in numeric.pyi
  • #​26832: DOC: remove hack to override _add_newdocs_scalars
  • #​26835: BUG: avoid side-effect of 'include complex.h'
  • #​26836: BUG: fix max_rows and chunked string/datetime reading in loadtxt
  • #​26837: BUG: fix PyArray_ImportNumPyAPI under -Werror=strict-prototypes
  • #​26856: DOC: Update some documentation
  • #​26868: BUG: fancy indexing copy
  • #​26869: BUG: Mismatched allocation domains in PyArray_FillWithScalar
  • #​26870: BUG: Handle --f77flags and --f90flags for meson [wheel build]
  • #​26887: BUG: Fix new DTypes and new string promotion when signature is...
  • #​26888: BUG: remove numpy.f2py from excludedimports
  • #​26959: BUG: Quantile closest_observation to round to nearest even order
  • #​26960: BUG: Fix off-by-one error in amount of characters in strip
  • #​26961: API: Partially revert unique with return_inverse
  • #​26962: BUG,MAINT: Fix utf-8 character stripping memory access
  • #​26963: BUG: Fix out-of-bound minimum offset for in1d table method
  • #​26971: BUG: fix f2py tests to work with v2 API
  • #​26995: BUG: Add object cast to avoid warning with limited API

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v2.0.0

Compare Source

NumPy 2.0.0 Release Notes

NumPy 2.0.0 is the first major release since 2006. It is the result of
11 months of development since the last feature release and is the work
of 212 contributors spread over 1078 pull requests. It contains a large
number of exciting new features as well as changes to both the Python
and C APIs.

This major release includes breaking changes that could not happen in a
regular minor (feature) release - including an ABI break, changes to
type promotion rules, and API changes which may not have been emitting
deprecation warnings in 1.26.x. Key documents related to how to adapt to
changes in NumPy 2.0, in addition to these release notes, include:

Highlights

Highlights of this release include:

  • New features:
    • A new variable-length string dtype, numpy.dtypes.StringDType and a new
      numpy.strings namespace with performant ufuncs for string operations,
    • Support for float32 and longdouble in all
      numpy.fft functions,
    • Support for the array API standard in the main numpy
      namespace.
  • Performance improvements:
    • Sorting functions sort, argsort,
      partition, argpartition have been
      accelerated through the use of the Intel x86-simd-sort and
      Google Highway libraries, and may see large (hardware-specific)
      speedups,
    • macOS Accelerate support and binary wheels for macOS >=14, with
      significant performance improvements for linear algebra
      operations on macOS, and wheels that are about 3 times smaller,
    • numpy.char fixed-length string operations have
      been accelerated by implementing ufuncs that also support
      numpy.dtypes.StringDType in addition to the
      fixed-length string dtypes,
    • A new tracing and introspection API,
      numpy.lib.introspect.opt_func_info, to determine
      which hardware-specific kernels are available and will be
      dispatched to.
    • numpy.save now uses pickle protocol version 4 for saving
      arrays with object dtype, which allows for pickle objects larger
      than 4GB and improves saving speed by about 5% for large arrays.
  • Python API improvements:
    • A clear split between public and private API, with a new module
      structure and each public function now available in a single place.
    • Many removals of non-recommended functions and aliases. This
      should make it easier to learn and use NumPy. The number of
      objects in the main namespace decreased by ~10% and in
      numpy.lib by ~80%.
    • Canonical dtype names and a new numpy.isdtype` introspection
      function,
  • C API improvements:
    • A new public C API for creating custom dtypes,
    • Many outdated functions and macros removed, and private
      internals hidden to ease future extensibility,
    • New, easier to use, initialization functions: PyArray_ImportNumPyAPI
      and PyUFunc_ImportUFuncAPI.
  • Improved behavior:
    • Improvements to type promotion behavior was changed by adopting NEP 50.
      This fixes many user surprises about promotions which previously often
      depended on data values of input arrays rather than only their dtypes.
      Please see the NEP and the numpy-2-migration-guide for details as this
      change can lead to changes in output dtypes and lower precision results
      for mixed-dtype operations.
    • The default integer type on Windows is now int64 rather than
      int32, matching the behavior on other platforms,
    • The maximum number of array dimensions is changed from 32 to 64
  • Documentation:
    • The reference guide navigation was significantly improved, and
      there is now documentation on NumPy's
      module structure,
    • The building from source documentation was completely rewritten,

Furthermore there are many changes to NumPy internals, including
continuing to migrate code from C to C++, that will make it easier to
improve and maintain NumPy in the future.

The "no free lunch" theorem dictates that there is a price to pay for
all these API and behavior improvements and better future extensibility.
This price is:

  1. Backwards compatibility. There are a significant number of breaking
    changes to both the Python and C APIs. In the majority of cases,
    there are clear error messages that will inform the user how to
    adapt their code. However, there are also changes in behavior for
    which it was not possible to give such an error message - these
    cases are all covered in the Deprecation and Compatibility sections
    below, and in the numpy-2-migration-guide.

    Note that there is a ruff mode to auto-fix many things in Python
    code.

  2. Breaking changes to the NumPy ABI. As a result, binaries of packages
    that use the NumPy C API and were built against a NumPy 1.xx release
    will not work with NumPy 2.0. On import, such packages will see an
    ImportError with a message about binary incompatibility.

    It is possible to build binaries against NumPy 2.0 that will work at
    runtime with both NumPy 2.0 and 1.x. See numpy-2-abi-handling for more
    details.

    All downstream packages that depend on the NumPy ABI are advised
    to do a new release built against NumPy 2.0 and verify that that
    release works with both 2.0 and 1.26 - ideally in the period between
    2.0.0rc1 (which will be ABI-stable) and the final 2.0.0 release to
    avoid problems for their users.

The Python versions supported by this release are 3.9-3.12.

NumPy 2.0 Python API removals

  • np.geterrobj, np.seterrobj and the related ufunc keyword
    argument extobj= have been removed. The preferred replacement for
    all of these is using the context manager with np.errstate():.

    (gh-23922)

  • np.cast has been removed. The literal replacement for
    np.cast[dtype](arg) is np.asarray(arg, dtype=dtype).

  • np.source has been removed. The preferred replacement is
    inspect.getsource.

  • np.lookfor has been removed.

    (gh-24144)

  • numpy.who has been removed. As an alternative for the removed
    functionality, one can use a variable explorer that is available in
    IDEs such as Spyder or Jupyter Notebook.

    (gh-24321)

  • Warnings and exceptions present in numpy.exceptions,
    e.g, numpy.exceptions.ComplexWarning,
    numpy.exceptions.VisibleDeprecationWarning, are no
    longer exposed in the main namespace.

  • Multiple niche enums, expired members and functions have been
    removed from the main namespace, such as: ERR_*, SHIFT_*,
    np.fastCopyAndTranspose, np.kernel_version, np.numarray,
    np.oldnumeric and np.set_numeric_ops.

    (gh-24316)

  • Replaced from ... import * in the numpy/__init__.py with
    explicit imports. As a result, these main namespace members got
    removed: np.FLOATING_POINT_SUPPORT, np.FPE_*, np.NINF,
    np.PINF, np.NZERO, np.PZERO, np.CLIP, np.WRAP, np.WRAP,
    np.RAISE, np.BUFSIZE, np.UFUNC_BUFSIZE_DEFAULT,
    np.UFUNC_PYVALS_NAME, np.ALLOW_THREADS, np.MAXDIMS,
    np.MAY_SHARE_EXACT, np.MAY_SHARE_BOUNDS, add_newdoc,
    np.add_docstring and np.add_newdoc_ufunc.

    (gh-24357)

  • Alias np.float_ has been removed. Use np.float64 instead.

  • Alias np.complex_ has been removed. Use np.complex128 instead.

  • Alias np.longfloat has been removed. Use np.longdouble instead.

  • Alias np.singlecomplex has been removed. Use np.complex64
    instead.

  • Alias np.cfloat has been removed. Use np.complex128 instead.

  • Alias np.longcomplex has been removed. Use np.clongdouble
    instead.

  • Alias np.clongfloat has been removed. Use np.clongdouble
    instead.

  • Alias np.string_ has been removed. Use np.bytes_ instead.

  • Alias np.unicode_ has been removed. Use np.str_ instead.

  • Alias np.Inf has been removed. Use np.inf instead.

  • Alias np.Infinity has been removed. Use np.inf instead.

  • Alias np.NaN has been removed. Use np.nan instead.

  • Alias np.infty has been removed. Use np.inf instead.

  • Alias np.mat has been removed. Use np.asmatrix instead.

  • np.issubclass_ has been removed. Use the issubclass builtin
    instead.

  • np.asfarray has been removed. Use np.asarray with a proper dtype
    instead.

  • np.set_string_function has been removed. Use np.set_printoptions
    instead with a formatter for custom printing of NumPy objects.

  • np.tracemalloc_domain is now only available from np.lib.

  • np.recfromcsv and recfromtxt are now only available from
    np.lib.npyio.

  • np.issctype, np.maximum_sctype, np.obj2sctype,
    np.sctype2char, np.sctypes, np.issubsctype were all removed
    from the main namespace without replacement, as they where niche
    members.

  • Deprecated np.deprecate and np.deprecate_with_doc has been
    removed from the main namespace. Use DeprecationWarning instead.

  • Deprecated np.safe_eval has been removed from the main namespace.
    Use ast.literal_eval instead.

    (gh-24376)

  • np.find_common_type has been removed. Use numpy.promote_types or
    numpy.result_type instead. To achieve semantics for the
    scalar_types argument, use numpy.result_type and pass 0,
    0.0, or 0j as a Python scalar instead.

  • np.round_ has been removed. Use np.round instead.

  • np.nbytes has been removed. Use np.dtype(<dtype>).itemsize
    instead.

    (gh-24477)

  • np.compare_chararrays has been removed from the main namespace.
    Use np.char.compare_chararrays instead.

  • The charrarray in the main namespace has been deprecated. It can
    be imported without a deprecation warning from np.char.chararray
    for now, but we are planning to fully deprecate and remove
    chararray in the future.

  • np.format_parser has been removed from the main namespace. Use
    np.rec.format_parser instead.

    (gh-24587)

  • Support for seven data type string aliases has been removed from
    np.dtype: int0, uint0, void0, object0, str0, bytes0
    and bool8.

    (gh-24807)

  • The experimental numpy.array_api submodule has been removed. Use
    the main numpy namespace for regular usage instead, or the
    separate array-api-strict package for the compliance testing use
    case for which numpy.array_api was mostly used.

    (gh-25911)

__array_prepare__ is removed

UFuncs called __array_prepare__ before running computations for normal
ufunc calls (not generalized ufuncs, reductions, etc.). The function was
also called instead of __array_wrap__ on the results of some linear
algebra functions.

It is now removed. If you use it, migrate to __array_ufunc__ or rely
on __array_wrap__ which is called with a context in all cases,
although only after the result array is filled. In those code paths,
__array_wrap__ will now be passed a base class, rather than a subclass
array.

(gh-25105)

Deprecations

  • np.compat has been deprecated, as Python 2 is no longer supported.

  • numpy.int8 and similar classes will no longer support conversion
    of out of bounds python integers to integer arrays. For example,
    conversion of 255 to int8 will not return -1. numpy.iinfo(dtype)
    can be used to check the machine limits for data types. For example,
    np.iinfo(np.uint16) returns min = 0 and max = 65535.

    np.array(value).astype(dtype) will give the desired result.

  • np.safe_eval has been deprecated. ast.literal_eval should be
    used instead.

    (gh-23830)

  • np.recfromcsv, np.recfromtxt, np.disp, np.get_array_wrap,
    np.maximum_sctype, np.deprecate and np.deprecate_with_doc have
    been deprecated.

    (gh-24154)

  • np.trapz has been deprecated. Use np.trapezoid or a
    scipy.integrate function instead.

  • np.in1d has been deprecated. Use np.isin instead.

  • Alias np.row_stack has been deprecated. Use np.vstack directly.

    (gh-24445)

  • __array_wrap__ is now passed arr, context, return_scalar and
    support for implementations not accepting all three are deprecated.
    Its signature should be
    __array_wrap__(self, arr, context=None, return_scalar=False)

    (gh-25409)

  • Arrays of 2-dimensional vectors for np.cross have been deprecated.
    Use arrays of 3-dimensional vectors instead.

    (gh-24818)

  • np.dtype("a") alias for np.dtype(np.bytes_) was deprecated. Use
    np.dtype("S") alias instead.

    (gh-24854)

  • Use of keyword arguments x and y with functions
    assert_array_equal and assert_array_almost_equal has been
    deprecated. Pass the first two arguments as positional arguments
    instead.

    (gh-24978)

numpy.fft deprecations for n-D transforms with None values in arguments

Using fftn, ifftn, rfftn, irfftn, fft2, ifft2, rfft2 or
irfft2 with the s parameter set to a value that is not None and
the axes parameter set to None has been deprecated, in line with the
array API standard. To retain current behaviour, pass a sequence [0,
..., k-1] to axes for an array of dimension k.

Furthermore, passing an array to s which contains None values is
deprecated as the parameter is documented to accept a sequence of
integers in both the NumPy docs and the array API specification. To use
the default behaviour of the corresponding 1-D transform, pass the value
matching the default for its n parameter. To use the default behaviour
for every axis, the s argument can be omitted.

(gh-25495)

np.linalg.lstsq now defaults to a new rcond value

numpy.linalg.lstsq now uses the new rcond value of the
machine precision times max(M, N). Previously, the machine precision
was used but a FutureWarning was given to notify that this change will
happen eventually. That old behavior can still be achieved by passing
rcond=-1.

(gh-25721)

Expired deprecations

  • The np.core.umath_tests submodule has been removed from the public
    API. (Deprecated in NumPy 1.15)

    (gh-23809)

  • The PyDataMem_SetEventHook deprecation has expired and it is
    removed. Use tracemalloc and the np.lib.tracemalloc_domain
    domain. (Deprecated in NumPy 1.23)

    (gh-23921)

  • The deprecation of set_numeric_ops and the C functions
    PyArray_SetNumericOps and PyArray_GetNumericOps has been expired
    and the functions removed. (Deprecated in NumPy 1.16)

    (gh-23998)

  • The fasttake, fastclip, and fastputmask ArrFuncs deprecation
    is now finalized.

  • The deprecated function fastCopyAndTranspose and its C counterpart
    are now removed.

  • The deprecation of PyArray_ScalarFromObject is now finalized.

    (gh-24312)

  • np.msort has been removed. For a replacement, np.sort(a, axis=0)
    should be used instead.

    (gh-24494)

  • np.dtype(("f8", 1) will now return a shape 1 subarray dtype rather
    than a non-subarray one.

    (gh-25761)

  • Assigning to the .data attribute of an ndarray is disallowed and
    will raise.

  • np.binary_repr(a, width) will raise if width is too small.

  • Using NPY_CHAR in PyArray_DescrFromType() will raise, use
    NPY_STRING NPY_UNICODE, or NPY_VSTRING instead.

    (gh-25794)


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This PR was generated by Mend Renovate. View the repository job log.

@renovate renovate bot force-pushed the renovate/numpy-2.x branch 3 times, most recently from 831b6db to 62f803d Compare October 20, 2024 05:39
@OasisAkari OasisAkari marked this pull request as draft October 21, 2024 07:05
@renovate renovate bot force-pushed the renovate/numpy-2.x branch 2 times, most recently from 668a61f to 457cf98 Compare October 28, 2024 16:48
@renovate renovate bot force-pushed the renovate/numpy-2.x branch 3 times, most recently from 960ba12 to 2e943d3 Compare November 5, 2024 17:53
@renovate renovate bot force-pushed the renovate/numpy-2.x branch 2 times, most recently from 712002c to afdf712 Compare November 29, 2024 06:41
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