Merge pull request #19670 from tylerjereddy/treddy_1_12_version_pins

WIP, MAINT: version bounds for 1.12.0rc1

.github/workflows/wheels.yml

@@ -128,24 +128,9 @@ jobs:
           CIBW_BUILD: ${{ matrix.python[0] }}-${{ matrix.buildplat[1] }}*
           CIBW_ARCHS: ${{ matrix.buildplat[2] }}
           CIBW_ENVIRONMENT_PASS_LINUX: RUNNER_OS
-          CIBW_PRERELEASE_PYTHONS: True
-
-          # TODO remove the CIBW_BEFORE_BUILD_* lines once there are
-          #  numpy2.0 wheels available on PyPI. Also remove/comment out the
-          # PIP_NO_BUILD_ISOLATION and PIP_EXTRA_INDEX_URL from CIBW_ENVIRONMENT
-          # (also for _MACOS and _WINDOWS below)
-          CIBW_BEFORE_BUILD_LINUX: "pip install numpy>=2.0.0.dev0 meson-python cython pythran pybind11 ninja; bash {project}/tools/wheels/cibw_before_build_linux.sh {project}"
-          CIBW_BEFORE_BUILD_WINDOWS: "pip install numpy>=2.0.0.dev0 meson-python cython pythran pybind11 ninja && bash {project}/tools/wheels/cibw_before_build_win.sh {project}"
-          CIBW_BEFORE_BUILD_MACOS: "pip install numpy>=2.0.0.dev0 meson-python cython pythran pybind11 ninja; bash {project}/tools/wheels/cibw_before_build_macos.sh {project}"
-          # Allow pip to find install nightly wheels if necessary
-          # Setting PIP_NO_BUILD_ISOLATION=false makes pip use build-isolation.
-          CIBW_ENVIRONMENT: "PIP_NO_BUILD_ISOLATION=false PIP_PRE=1 PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"
 
           CIBW_ENVIRONMENT_WINDOWS: >
             PKG_CONFIG_PATH=c:/opt/64/lib/pkgconfig
-            PIP_PRE=1
-            PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
-            PIP_NO_BUILD_ISOLATION=false
 
           # setting SDKROOT necessary when using the gfortran compiler
           # installed in cibw_before_build_macos.sh
@@ -159,9 +144,6 @@ jobs:
             MACOSX_DEPLOYMENT_TARGET=10.9
             MACOS_DEPLOYMENT_TARGET=10.9
             _PYTHON_HOST_PLATFORM=macosx-10.9-x86_64
-            PIP_PRE=1
-            PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
-            PIP_NO_BUILD_ISOLATION=false
 
           CIBW_REPAIR_WHEEL_COMMAND_MACOS: >
             DYLD_LIBRARY_PATH=/usr/local/lib delocate-listdeps {wheel} &&

ci/cirrus_wheels.yml

@@ -12,6 +12,7 @@ build_and_store_wheels: &BUILD_AND_STORE_WHEELS
 ######################################################################
 
 cirrus_wheels_linux_aarch64_task:
+  timeout_in: 75m
   compute_engine_instance:
     image_project: cirrus-images
     image: family/docker-builder-arm64
@@ -27,15 +28,6 @@ cirrus_wheels_linux_aarch64_task:
         CIBW_BUILD: cp39-manylinux* cp310-manylinux*
     - env:
         CIBW_BUILD: cp311-manylinux* cp312-manylinux*
-  env:
-    CIBW_PRERELEASE_PYTHONS: True
-    # TODO remove the CIBW_BEFORE_BUILD_LINUX line once there are numpy2.0 wheels available on PyPI.
-    # Also remove/comment out PIP_NO_BUILD_ISOLATION, PIP_EXTRA_INDEX_URL flags.
-    CIBW_BEFORE_BUILD_LINUX: "pip install numpy>=2.0.0.dev0 meson-python cython pythran pybind11 ninja;bash {project}/tools/wheels/cibw_before_build_linux.sh {project}"
-    CIBW_ENVIRONMENT: >
-      PIP_PRE=1
-      PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
-      PIP_NO_BUILD_ISOLATION=false
 
   build_script: |
     apt install -y python3-venv python-is-python3
@@ -63,12 +55,6 @@ cirrus_wheels_macos_arm64_task:
     CIBW_ENVIRONMENT: >
       MACOSX_DEPLOYMENT_TARGET=12.0
       _PYTHON_HOST_PLATFORM="macosx-12.0-arm64"             
-      PIP_PRE=1
-      PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple
-      PIP_NO_BUILD_ISOLATION=false
-    # TODO remove the following line once there are numpy2.0 wheels available on PyPI.
-    # Also remove PIP_NO_BUILD_ISOLATION, PIP_EXTRA_INDEX_URL flags.
-    CIBW_BEFORE_BUILD_MACOS: "pip install numpy>=2.0.0.dev0 meson-python cython pythran pybind11 ninja;bash {project}/tools/wheels/cibw_before_build_macos.sh {project}"
     PKG_CONFIG_PATH: /opt/arm64-builds/lib/pkgconfig
     # assumes that the cmake config is in /usr/local/lib/cmake
     CMAKE_PREFIX_PATH: /opt/arm64-builds/

doc/source/dev/api-dev/array_api.rst

@@ -1,13 +1,13 @@
-Support for Array API
-=====================
+Support for the array API standard
+==================================
 
-.. note:: Array API support is still experimental and hidden behind an
+.. note:: array API standard support is still experimental and hidden behind an
           environment variable. Only a small part of the public API is covered
           right now.
 
 This guide describes how to **use** and **add support for** the
-`Python Array API standard <https://data-apis.org/array-api/latest/index.html>`_.
-This standard allows users to use any Array API compatible array library
+`Python array API standard <https://data-apis.org/array-api/latest/index.html>`_.
+This standard allows users to use any array API compatible array library
 with SciPy out of the box.
 
 The `RFC`_ defines how SciPy implements support for the standard, with the main
@@ -16,13 +16,13 @@ implementation does more strict validation of allowed array-like inputs, e.g.
 rejecting numpy matrix and masked array instances, and arrays with object
 dtype.
 
-In the following, an Array API compatible namespace is noted as ``xp``.
+In the following, an array API compatible namespace is noted as ``xp``.
 
 
-Using Array API support
------------------------
+Using array API standard support
+--------------------------------
 
-To enable the Array API standard support, an environment variable must be set
+To enable the array API standard support, an environment variable must be set
 before importing SciPy:
 
 .. code:: bash
@@ -90,12 +90,19 @@ More strict array input validation will reject ``np.matrix`` and
 Currently supported functionality
 `````````````````````````````````
 
-The following modules provide Array API standard support when the environment
+The following modules provide array API standard support when the environment
 variable is set:
 
-- ``scipy.cluster.hierarchy``
-- ``scipy.cluster.vq``
-- ``scipy.fft``
+- `scipy.cluster.hierarchy`
+- `scipy.cluster.vq`
+- `scipy.fft`
+
+Support is provided in `scipy.special` for the following functions:
+`scipy.special.log_ndtr`, `scipy.special.ndtr`, `scipy.special.ndtri`,
+`scipy.special.erf`, `scipy.special.erfc`, `scipy.special.i0`,
+`scipy.special.i0e`, `scipy.special.i1`, `scipy.special.i1e`, 
+`scipy.special.gammaln`, `scipy.special.gammainc`, `scipy.special.gammaincc`,
+`scipy.special.logit`, and `scipy.special.expit`.
 
 
 Implementation notes
@@ -112,25 +119,25 @@ as ``xp.concat`` (which, for numpy, maps to ``np.concatenate``). This allows
 using a uniform API across NumPy, PyTorch and CuPy (as of right now; support
 for other libraries like JAX is expected to be added in the future).
 
-When the environment variable isn't set and hence Array API support in SciPy is
-disabled, we still use the "augmented" version of the NumPy namespace, which is
-``array_api_compat.numpy``. That should not change behavior of SciPy functions,
-it's effectively the existing ``numpy`` namespace with a number of aliases
-added and a handful of functions amended/added for array API standard support.
-When support is enabled, depending on the type of arrays, ``xp`` will return the
-standard-compatible namespace matching the input array type to a function (e.g.,
-if the input to ``cluster.vq.kmeans`` is a PyTorch array, then ``xp`` is
-``array_api_compat.torch``).
+When the environment variable isn't set and hence array API standard support in
+SciPy is disabled, we still use the "augmented" version of the NumPy namespace,
+which is ``array_api_compat.numpy``. That should not change behavior of SciPy
+functions, it's effectively the existing ``numpy`` namespace with a number of
+aliases added and a handful of functions amended/added for array API standard
+support. When support is enabled, depending on the type of arrays, ``xp`` will
+return the standard-compatible namespace matching the input array type to a
+function (e.g., if the input to `cluster.vq.kmeans` is a PyTorch array, then
+``xp`` is ``array_api_compat.torch``).
 
 
-Adding Array API support to a SciPy function
---------------------------------------------
+Adding array API standard support to a SciPy function
+-----------------------------------------------------
 
 As much as possible, new code added to SciPy should try to follow as closely as
-possible the Array API standard (these functions typically are best-practice
+possible the array API standard (these functions typically are best-practice
 idioms for NumPy usage as well). By following the standard, effectively adding
-support for Array API is typically straightforward, and we ideally don't need
-to maintain any customization.
+support for the array API standard is typically straightforward, and we ideally
+don't need to maintain any customization.
 
 Two helper functions are available:
 

doc/source/release/1.12.0-notes.rst

@@ -28,8 +28,9 @@ Highlights of this release
 - Experimental support for the array API standard has been added to part of
   `scipy.special`, and to all of `scipy.fft` and `scipy.cluster`. There are
   likely to be bugs and early feedback for usage with CuPy arrays, PyTorch
-  tensors, and other array API compatible libraries is appreciated.
-- A new class, ``ShortTimeFFT```, provides a more versatile implementation of the
+  tensors, and other array API compatible libraries is appreciated. Use the
+  ``SCIPY_ARRAY_API`` environment variable for testing.
+- A new class, ``ShortTimeFFT``, provides a more versatile implementation of the
   short-time Fourier transform (STFT), its inverse (ISTFT) as well as the (cross-)
   spectrogram. It utilizes an improved algorithm for calculating the ISTFT.
 - Several new constructors have been added for sparse arrays, and many operations
@@ -81,7 +82,7 @@ New features
   and knot vectors. This way it generalizes ``BSpline`` for 1D data to N-D, and
   parallels ``NdPPoly`` (which represents N-D tensor product polynomials).
   Evaluations exploit the localized nature of b-splines.
-- ``NeastNDInterpolator.__call__`` accepts ``**query_options``, which are
+- ``NearestNDInterpolator.__call__`` accepts ``**query_options``, which are
   passed through to the ``KDTree.query`` call to find nearest neighbors. This
   allows, for instance, to limit the neighbor search distance and parallelize
   the query using the ``workers`` keyword.
@@ -317,17 +318,19 @@ Authors
 * Ben Beasley (3) +
 * Doron Behar (1)
 * Peter Bell (1)
+* Sebastian Berg (1)
 * Ben Boeckel (1) +
-* Jake Bowhay (100)
+* David Boetius (1) +
+* Jake Bowhay (102)
 * Larry Bradley (1) +
 * Dietrich Brunn (5)
 * Evgeni Burovski (101)
 * Matthias Bussonnier (18)
-* CJ Carey (4)
+* CJ Carey (6)
 * Colin Carroll (1) +
 * Aadya Chinubhai (1) +
 * Luca Citi (1)
-* Lucas Colley (136) +
+* Lucas Colley (140) +
 * com3dian (1) +
 * Anirudh Dagar (4)
 * Danni (1) +
@@ -337,26 +340,28 @@ Authors
 * drestebon (1) +
 * Thomas Duvernay (1)
 * elbarso (1) +
+* emilfrost (2) +
 * Paul Estano (8) +
 * Evandro (2)
 * Franz Király (1) +
 * Nikita Furin (1) +
 * gabrielthomsen (1) +
-* Lukas Geiger (8) +
+* Lukas Geiger (9) +
 * Artem Glebov (22) +
 * Caden Gobat (1)
-* Ralf Gommers (120)
+* Ralf Gommers (125)
 * Alexander Goscinski (2) +
 * Rohit Goswami (2) +
 * Olivier Grisel (1)
-* Matt Haberland (238)
+* Matt Haberland (243)
 * Charles Harris (1)
 * harshilkamdar (1) +
 * Alon Hovav (2) +
 * Gert-Ludwig Ingold (1)
 * Romain Jacob (1) +
 * jcwhitehead (1) +
 * Julien Jerphanion (13)
+* He Jia (1)
 * JohnWT (1) +
 * jokasimr (1) +
 * Evan W Jones (1)
@@ -398,12 +403,12 @@ Authors
 * Roberto Pastor Muela (3) +
 * Bijay Nayak (1) +
 * Andrew Nelson (105)
-* Praveer Nidamaluri (1) +
+* Praveer Nidamaluri (2) +
 * Lysandros Nikolaou (2)
 * Dimitri Papadopoulos Orfanos (7)
 * Pablo Rodríguez Pérez (1) +
 * Dimitri Papadopoulos (2)
-* Tirth Patel (13)
+* Tirth Patel (14)
 * Kyle Paterson (1) +
 * Paul (4) +
 * Yann Pellegrini (2) +
@@ -413,7 +418,7 @@ Authors
 * Bharat Raghunathan (1)
 * Chris Rapson (1) +
 * Matteo Raso (4)
-* Tyler Reddy (161)
+* Tyler Reddy (165)
 * Martin Reinecke (1)
 * Tilo Reneau-Cardoso (1) +
 * resting-dove (2) +
@@ -425,8 +430,8 @@ Authors
 * Masahiro Sakai (2) +
 * Omar Salman (14)
 * Andrej Savikin (1) +
-* Daniel Schmitz (50)
-* Dan Schult (18)
+* Daniel Schmitz (52)
+* Dan Schult (19)
 * Scott Shambaugh (9)
 * Sheila-nk (2) +
 * Mauro Silberberg (3) +
@@ -453,14 +458,14 @@ Authors
 * Warren Weckesser (7)
 * Bernhard M. Wiedemann (4)
 * Levi John Wolf (1)
-* Xuefeng Xu (3) +
+* Xuefeng Xu (4) +
 * Rory Yorke (2)
 * YoussefAli1 (1) +
 * Irwin Zaid (4) +
 * Jinzhe Zeng (1) +
 * JIMMY ZHAO (1) +
 
-A total of 157 people contributed to this release.
+A total of 161 people contributed to this release.
 People with a "+" by their names contributed a patch for the first time.
 This list of names is automatically generated, and may not be fully complete.
 
@@ -488,6 +493,7 @@ Issues closed for 1.12.0
 * `#14480 <https://github.com/scipy/scipy/issues/14480>`__: LSODA implementation of dense output yields incorrect result
 * `#15533 <https://github.com/scipy/scipy/issues/15533>`__: BUG: test failure with MKL in presence of AVX512-capable processor
 * `#15676 <https://github.com/scipy/scipy/issues/15676>`__: ENH: Implement \`multivariate_normal.fit\`
+* `#15738 <https://github.com/scipy/scipy/issues/15738>`__: DEP: change default of atol in \`scipy.sparse.linalg.\*\`
 * `#16729 <https://github.com/scipy/scipy/issues/16729>`__: _fitpack / dfitpack duplication
 * `#16880 <https://github.com/scipy/scipy/issues/16880>`__: ENH: Add Rotation.align_vector
 * `#17290 <https://github.com/scipy/scipy/issues/17290>`__: ENH: multi dimensional wasserstein/earth mover distance in Scipy
@@ -1037,6 +1043,7 @@ Pull requests for 1.12.0
 * `#19623 <https://github.com/scipy/scipy/pull/19623>`__: MAINT: lint: enable \`stacklevel\` warnings check
 * `#19624 <https://github.com/scipy/scipy/pull/19624>`__: MAINT/TST: _lib: use value instead of deprecated s
 * `#19626 <https://github.com/scipy/scipy/pull/19626>`__: MAINT: more SciPy windows int shims
+* `#19628 <https://github.com/scipy/scipy/pull/19628>`__: DOC: 1.12.0 release notes
 * `#19635 <https://github.com/scipy/scipy/pull/19635>`__: MAINT: simplify Nakagami mean calculation
 * `#19637 <https://github.com/scipy/scipy/pull/19637>`__: DOC: Clarify integration error bound in \`integrate\` tutorial
 * `#19648 <https://github.com/scipy/scipy/pull/19648>`__: MAINT: simplify chi distribution mean calculation
@@ -1045,3 +1052,9 @@ Pull requests for 1.12.0
 * `#19658 <https://github.com/scipy/scipy/pull/19658>`__: MAINT: git blame ignores for lint clean-ups
 * `#19660 <https://github.com/scipy/scipy/pull/19660>`__: STY: special: use indent width of 4 in clang-format
 * `#19661 <https://github.com/scipy/scipy/pull/19661>`__: CI: fix pre-release job by correct version pin for scipy-openblas32
+* `#19677 <https://github.com/scipy/scipy/pull/19677>`__: DOC: array types: mention partial support in \`special\`
+* `#19686 <https://github.com/scipy/scipy/pull/19686>`__: TST: fix incorrect signal.sosfilt tests
+* `#19690 <https://github.com/scipy/scipy/pull/19690>`__: BLD: avoid fast-math for oneAPI compilers, fix up handling of...
+* `#19691 <https://github.com/scipy/scipy/pull/19691>`__: BUG: fix negative overflow in stats.boxcox_normmax
+* `#19693 <https://github.com/scipy/scipy/pull/19693>`__: BUG: Prevent mutation of \`w\` parameter in \`spatial.distance.\*\`
+* `#19702 <https://github.com/scipy/scipy/pull/19702>`__: DEP: Adopt \`\*tol\` deprecations also for \`gcrotmk/lgmres/minres/tfqmr\`

pyproject.toml

@@ -10,10 +10,10 @@
 [build-system]
 build-backend = 'mesonpy'
 requires = [
-    "meson-python>=0.15.0",
-    "Cython>=0.29.35,!=3.0.3",  # when updating version, also update check in meson.build
-    "pybind11>=2.10.4",
-    "pythran>=0.14.0",
+    "meson-python>=0.15.0,<0.16.0", # working with 0.15.x series at branch time
+    "Cython>=0.29.35,!=3.0.3,<3.1.0",  # when updating version, also update check in meson.build
+    "pybind11>=2.10.4,<2.12.0", # working with 2.11.x series at branch time
+    "pythran@git+https://github.com/serge-sans-paille/pythran", # TODO: pin back to stable release when ready
 
     # When numpy 2.0.0rc1 comes out, we should update this to build against 2.0,
     # and then runtime depend on the range 1.22.X to <2.3. No need to switch to
@@ -50,11 +50,11 @@ maintainers = [
 # Note: Python and NumPy upper version bounds should be set correctly in
 # release branches, see:
 #     https://scipy.github.io/devdocs/dev/core-dev/index.html#version-ranges-for-numpy-and-other-dependencies
-requires-python = ">=3.9"
+requires-python = ">=3.9" # newest supported Python version: 3.12
 dependencies = [
     # TODO: update to "pin-compatible" once possible, see
     # https://github.com/mesonbuild/meson-python/issues/29
-    "numpy>=1.22.4",
+    "numpy>=1.22.4,<1.29.0", # NOTE: at time of writing, NumPy is unlikely to go beyond 1.26.x as 2.0.0 looms
 ]
 readme = "README.rst"
 classifiers = [

scipy/__init__.py

@@ -67,7 +67,7 @@
 from scipy._lib import _pep440
 # In maintenance branch, change to np_maxversion N+3 if numpy is at N
 np_minversion = '1.22.4'
-np_maxversion = '9.9.99'
+np_maxversion = '1.29.0'
 if (_pep440.parse(__numpy_version__) < _pep440.Version(np_minversion) or
         _pep440.parse(__numpy_version__) >= _pep440.Version(np_maxversion)):
     import warnings

scipy/optimize/_nonlin.py

@@ -1477,10 +1477,10 @@ def matvec(self, v):
         return r
 
     def solve(self, rhs, tol=0):
-        if 'tol' in self.method_kw:
+        if 'rtol' in self.method_kw:
             sol, info = self.method(self.op, rhs, **self.method_kw)
         else:
-            sol, info = self.method(self.op, rhs, tol=tol, **self.method_kw)
+            sol, info = self.method(self.op, rhs, rtol=tol, **self.method_kw)
         return sol
 
     def update(self, x, f):