Update dependency numpy to v2 #1386
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This PR contains the following updates:
^1.24.1->^2.0.0==1.26.4->==2.1.3Release Notes
numpy/numpy (numpy)
v2.1.3Compare Source
v2.1.2Compare 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.
Pull requests merged
A total of 10 pull requests were merged for this release.
Checksums
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v2.1.0Compare 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.
Pull requests merged
A total of 19 pull requests were merged for this release.
alltrueandsometruenpyv_loadable_stride_functions for ldexp and...np.saveChecksums
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v2.0.1Compare 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.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)
Contributors
A total of 15 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
Pull requests merged
A total of 24 pull requests were merged for this release.
ma/extras.pyistubset_printoptionsloadtxtPyArray_FillWithScalarChecksums
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v2.0.0Compare 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:
numpy.dtypes.StringDTypeand a newnumpy.stringsnamespace with performant ufuncs for string operations,float32andlongdoublein allnumpy.fftfunctions,numpynamespace.
sort,argsort,partition,argpartitionhave beenaccelerated through the use of the Intel x86-simd-sort and
Google Highway libraries, and may see large (hardware-specific)
speedups,
significant performance improvements for linear algebra
operations on macOS, and wheels that are about 3 times smaller,
numpy.charfixed-length string operations havebeen accelerated by implementing ufuncs that also support
numpy.dtypes.StringDTypein addition to thefixed-length string dtypes,
numpy.lib.introspect.opt_func_info, to determinewhich hardware-specific kernels are available and will be
dispatched to.
numpy.savenow uses pickle protocol version 4 for savingarrays with object dtype, which allows for pickle objects larger
than 4GB and improves saving speed by about 5% for large arrays.
structure and each public function now available in a single place.
should make it easier to learn and use NumPy. The number of
objects in the main namespace decreased by ~10% and in
numpy.libby ~80%.Canonical dtype names and a newnumpy.isdtype` introspectionfunction,
internals hidden to ease future extensibility,
PyArray_ImportNumPyAPIand
PyUFunc_ImportUFuncAPI.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.
int64rather thanint32, matching the behavior on other platforms,there is now documentation on NumPy's
module structure,
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:
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
ruffmode to auto-fix many things in Pythoncode.
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
ImportErrorwith 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.seterrobjand the related ufunc keywordargument
extobj=have been removed. The preferred replacement forall of these is using the context manager
with np.errstate():.(gh-23922)
np.casthas been removed. The literal replacement fornp.cast[dtype](arg)isnp.asarray(arg, dtype=dtype).np.sourcehas been removed. The preferred replacement isinspect.getsource.np.lookforhas been removed.(gh-24144)
numpy.whohas been removed. As an alternative for the removedfunctionality, 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 nolonger 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.oldnumericandnp.set_numeric_ops.(gh-24316)
Replaced
from ... import *in thenumpy/__init__.pywithexplicit 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_docstringandnp.add_newdoc_ufunc.(gh-24357)
Alias
np.float_has been removed. Usenp.float64instead.Alias
np.complex_has been removed. Usenp.complex128instead.Alias
np.longfloathas been removed. Usenp.longdoubleinstead.Alias
np.singlecomplexhas been removed. Usenp.complex64instead.
Alias
np.cfloathas been removed. Usenp.complex128instead.Alias
np.longcomplexhas been removed. Usenp.clongdoubleinstead.
Alias
np.clongfloathas been removed. Usenp.clongdoubleinstead.
Alias
np.string_has been removed. Usenp.bytes_instead.Alias
np.unicode_has been removed. Usenp.str_instead.Alias
np.Infhas been removed. Usenp.infinstead.Alias
np.Infinityhas been removed. Usenp.infinstead.Alias
np.NaNhas been removed. Usenp.naninstead.Alias
np.inftyhas been removed. Usenp.infinstead.Alias
np.mathas been removed. Usenp.asmatrixinstead.np.issubclass_has been removed. Use theissubclassbuiltininstead.
np.asfarrayhas been removed. Usenp.asarraywith a proper dtypeinstead.
np.set_string_functionhas been removed. Usenp.set_printoptionsinstead with a formatter for custom printing of NumPy objects.
np.tracemalloc_domainis now only available fromnp.lib.np.recfromcsvandrecfromtxtare now only available fromnp.lib.npyio.np.issctype,np.maximum_sctype,np.obj2sctype,np.sctype2char,np.sctypes,np.issubsctypewere all removedfrom the main namespace without replacement, as they where niche
members.
Deprecated
np.deprecateandnp.deprecate_with_dochas beenremoved from the main namespace. Use
DeprecationWarninginstead.Deprecated
np.safe_evalhas been removed from the main namespace.Use
ast.literal_evalinstead.(gh-24376)
np.find_common_typehas been removed. Usenumpy.promote_typesornumpy.result_typeinstead. To achieve semantics for thescalar_typesargument, usenumpy.result_typeand pass0,0.0, or0jas a Python scalar instead.np.round_has been removed. Usenp.roundinstead.np.nbyteshas been removed. Usenp.dtype(<dtype>).itemsizeinstead.
(gh-24477)
np.compare_chararrayshas been removed from the main namespace.Use
np.char.compare_chararraysinstead.The
charrarrayin the main namespace has been deprecated. It canbe imported without a deprecation warning from
np.char.chararrayfor now, but we are planning to fully deprecate and remove
chararrayin the future.np.format_parserhas been removed from the main namespace. Usenp.rec.format_parserinstead.(gh-24587)
Support for seven data type string aliases has been removed from
np.dtype:int0,uint0,void0,object0,str0,bytes0and
bool8.(gh-24807)
The experimental
numpy.array_apisubmodule has been removed. Usethe main
numpynamespace for regular usage instead, or theseparate
array-api-strictpackage for the compliance testing usecase for which
numpy.array_apiwas mostly used.(gh-25911)
__array_prepare__is removedUFuncs called
__array_prepare__before running computations for normalufunc calls (not generalized ufuncs, reductions, etc.). The function was
also called instead of
__array_wrap__on the results of some linearalgebra functions.
It is now removed. If you use it, migrate to
__array_ufunc__or relyon
__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 subclassarray.
(gh-25105)
Deprecations
np.compathas been deprecated, as Python 2 is no longer supported.numpy.int8and similar classes will no longer support conversionof 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_evalhas been deprecated.ast.literal_evalshould beused instead.
(gh-23830)
np.recfromcsv,np.recfromtxt,np.disp,np.get_array_wrap,np.maximum_sctype,np.deprecateandnp.deprecate_with_dochavebeen deprecated.
(gh-24154)
np.trapzhas been deprecated. Usenp.trapezoidor ascipy.integratefunction instead.np.in1dhas been deprecated. Usenp.isininstead.Alias
np.row_stackhas been deprecated. Usenp.vstackdirectly.(gh-24445)
__array_wrap__is now passedarr, context, return_scalarandsupport 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.crosshave been deprecated.Use arrays of 3-dimensional vectors instead.
(gh-24818)
np.dtype("a")alias fornp.dtype(np.bytes_)was deprecated. Usenp.dtype("S")alias instead.(gh-24854)
Use of keyword arguments
xandywith functionsassert_array_equalandassert_array_almost_equalhas beendeprecated. Pass the first two arguments as positional arguments
instead.
(gh-24978)
numpy.fftdeprecations for n-D transforms with None values in argumentsUsing
fftn,ifftn,rfftn,irfftn,fft2,ifft2,rfft2orirfft2with thesparameter set to a value that is notNoneandthe
axesparameter set toNonehas been deprecated, in line with thearray API standard. To retain current behaviour, pass a sequence [0,
..., k-1] to
axesfor an array of dimension k.Furthermore, passing an array to
swhich containsNonevalues isdeprecated 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
nparameter. To use the default behaviourfor every axis, the
sargument can be omitted.(gh-25495)
np.linalg.lstsqnow defaults to a newrcondvaluenumpy.linalg.lstsqnow uses the new rcond value of themachine precision times
max(M, N). Previously, the machine precisionwas 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_testssubmodule has been removed from the publicAPI. (Deprecated in NumPy 1.15)
(gh-23809)
The
PyDataMem_SetEventHookdeprecation has expired and it isremoved. Use
tracemallocand thenp.lib.tracemalloc_domaindomain. (Deprecated in NumPy 1.23)
(gh-23921)
The deprecation of
set_numeric_opsand the C functionsPyArray_SetNumericOpsandPyArray_GetNumericOpshas been expiredand the functions removed. (Deprecated in NumPy 1.16)
(gh-23998)
The
fasttake,fastclip, andfastputmaskArrFuncsdeprecationis now finalized.
The deprecated function
fastCopyAndTransposeand its C counterpartare now removed.
The deprecation of
PyArray_ScalarFromObjectis now finalized.(gh-24312)
np.msorthas 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 ratherthan a non-subarray one.
(gh-25761)
Assigning to the
.dataattribute of an ndarray is disallowed andwill raise.
np.binary_repr(a, width)will raise if width is too small.Using
NPY_CHARinPyArray_DescrFromType()will raise, useNPY_STRINGNPY_UNICODE, orNPY_VSTRINGinstead.(gh-25794)
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