The algorithm is already equipped with a handful of checks for
problem infeasibility, but the tests added here show two different
examples that were not caught by any of those checks. It is likely
possible to dive in and determine infeasibility in `_lapjvsp` itself, as
in both examples, the symptom is the algorithm hitting an infinite loop
(but a different infinite loop for each case), but here we simply add
the catch-all fix of checking that the problem is feasible before even
trying to solve it. This does come with a performance hit, but at least
the implementation of Hopcroft--Karp that we're using is fast.

Co-authored-by: Jake Bowhay <60778417+j-bowhay@users.noreply.github.com>

)

Closes scipygh-18716

Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>

Closes scipy#15093
The scipy docs define Bounds as inclusive but trust-constr treats
bounds as exclusive. According to Nocedal, Jorge, and Stephen J.
Wright. "Numerical optimization" Second Edition (2006), p. 393,
interior point methods necessarily treat bounds as exclusive. To work
around this limitation of interior point methods and create consistent
behavior for Bounds, this PR modifies trust-constr so that Bounds
passed to trust-constr are expanded by epsilon.

Switched from using assert_ to using assert.

PR scipy#18896 removed make_strictly_feasible because it makes solutions
worse if they are close to the boundary.
However, the downstream algorithm that eventually solves the
optimization problem has some trouble with starting points that
are on the boundaries of a bounded optimization problem.
This either results in division by zero warnings, see scipy#19102,
or in failure of finding the correct solution at all,
which is added as a regression test in this commit.
This PR brings back make_strictly_feasible but with the
smallest possible step from the boundary a floating point allows
by setting rstep=0 on the function make_strictly_feasible,
which uses np.nextafter to find such a point, hereby respecting
the strictly feasible point condition and minimizing boundary effects.
See strictly feasible points in interior-point methods for more context
https://nmayorov.wordpress.com/2015/06/19/trust-region-reflective-algorithm/

to allow for reproducible builds
even when (unneeded) .pyx files are installed and shipped in OS packages

Fixes: scipy#19101

This patch was done while working on reproducible builds for openSUSE.

…ad_test.

The parameter `cval` in the private helper function `_pad_test` is not
used, so remove it.  This change is inspired by a bug in Cython 3.0.1
(see SciPy issue scipygh-19132), and this change is a work-around for that bug,
but since the parameter is unused and in a private function, there is no
need to revert this change.

* BLD: revert to using published wheels [wheel build]

…9156)

* BUG: Support sparse arrays in scipy.sparse.csgraph.laplacian

* TST: Added unit test for laplacian

* TST: for issues scipy#17289 scipy#15273

* BUG/ENH: fix scipy#17289 scipy#15273

* TST: use correct assert

* BENCH: Added a benchmark for signal.freqz

* TST/BENCH: improved coverage scipy#17289 scipy#15273

* BENCH: removed vectorized input scipy#17289 scipy#15273

* STY: add missing whitespace

[skip ci]

---------

Co-authored-by: Jake Bowhay <60778417+j-bowhay@users.noreply.github.com>

* update the SciPy 1.11.3 release notes

* update our wheel build config per feedback
in scipygh-19274

[skip cirrus]

* fix a doc build failure related to `numpy.ma.row_stack`; should
use `vstack` now re: NumPy namespace changes that are happening

Fixes scipy#18782 18782

* `node_list` was already made private on `main` in `_traversal.pyx`,
so just apply that fix here as well, to fix the linter error

* pin `pythran` in gcc-8 GHA job, was causing problem in build
with isolation disabled because `0.14.0` is now available

…ipy#19200)

This was failing on macOS x86-64 in CI with:
```
 E   Arrays are not almost equal to 6 decimals
E
E   Mismatched elements: 1 / 25 (4%)
E   Max absolute difference: 1.52291797e-06
E   Max relative difference: 8.81522156e-07
E    x: array([[ 2.108927e+00, -1.943767e+00,  7.026353e-02, -4.717525e-02,
E            5.251554e-02],
E          [-1.943767e+00,  2.048149e+00, -6.160049e-02,  4.626880e-02,...
E    y: array([[ 2.108927e+00, -1.943769e+00,  7.026355e-02, -4.717527e-02,
E            5.251558e-02],
E          [-1.943769e+00,  2.048151e+00, -6.160052e-02,  4.626883e-02,...
```

So it's a very small atol violation (1.52e-6, where decimal=6 implies
1.5e-6). Rather than bump to `decimal=5`, I decided to change the test
to `assert_allclose` so the bump could be smaller.

[skip ci]

* update SciPy `1.11.3` release notes after more changes/backports

[skip cirrus]

* pin `meson-python` version in gcc-8 GHA job, because it has
build isolation disabled

[skip cirrus]

…ariance (scipy#19199)

* update SciPy `1.11.3` release notes following
more backports

* `test_int_x0_gh19280()` required a small shim to
deal with module import differences vs. `main`

[skip cirrus]

* MAINT: linux amendments

* MAINT: osx amendments

* MAINT: win licence amendments

* MAINT: licence typo

This macro must not be used in the global scope, but rather in
a separate namespace (see, e.g., `boost_math/example/policy_eg_9.cpp`).
It caused compilation errors with Clang on Windows in
PR 246 on the conda-forge scipy feedback.

This bit of code also did not seem necessary, given that these
compile flags in `stats/_boost/meson.build` should already achieve
the same effect:
```
  '-DBOOST_MATH_EVALUATION_ERROR_POLICY=user_error',
  '-DBOOST_MATH_OVERFLOW_ERROR_POLICY=user_error',
```

That the custom error handling in `func_defs.hpp` is still used can
be verified by running for example after modifying the
`user_evaluation_error` handler:
```
python dev.py test -t scipy.stats.tests.test_distributions -- -k test_boost_eval_issue_14606
```

Follow-up to scipygh-8918; the linked CPython code in the discussion
on the issue that that PR closes has the same `<float.h>` include.

This upstreams a patch from PR 246 to
https://github.com/conda-forge/scipy-feedstock

Co-authored-by: Uwe L. Korn <uwe.korn@quantco.com>

Fix scipygh-18689 scipygh-18922

python3.12 removes distutils and scipy dev.py uses
distutils for the meson based build in debian python.
With python3.12 debian has patched sysconfig and no
longer requires dependence on distutils.

…rch64

* update the SciPy 1.11.3 release notes following
another series of backports

[skip cirrus]

* empty commit to test wheel builds for
the SciPy `1.11.3` release process before
the backport PR is merged

[wheel build]