Warren Weckesser

Will this affect the repr of a structured data type? E.g. ``` In [66]: dt = np.dtype([('x', np.float32), ('code', 'S4'), ('flag', np.bool_)]) In [67]: a = np.array((1.25, 'ABC', False), dtype=dt)[()]...

Is there any way the name `void` can be changed to something more descriptive? Maybe `struct`, or `record` (at least for the case where the type actually is a structured...

The [docs for `np.double`](https://numpy.org/doc/stable/reference/arrays.scalars.html?highlight=float64#numpy.double) show the signature to be `numpy.double(x=0, /)`. But the keyword `x` is ignored. Combine that with the default value of 0, and we have the following...

I don't think fixing the signature reported in the docs is a trivial fix. My understanding is that `numpy.cdouble`/`numpy.complex128` inherits from Python `complex`, and I think that is where the...

FYI: https://github.com/scipy/scipy/pull/16168 fixes another failure that occurs when SCIPY_XSLOW is defined. That test requires mpmath and sympy to be installed. (The problem was not numerical; it was just a bug...

I created https://github.com/scipy/scipy/issues/16655 to explain the failure indicated by FAILED scipy/stats/tests/test_continuous_basic.py::test_moments[vonmises-arg103-True-True-True] The test `test_moments` calls `check_normalization` in `common_tests.py`, and `check_normalization` computes normalization_expect = distfn.expect(lambda x: 1, args=args) which should be...

https://github.com/scipy/scipy/pull/16965 fixed the XSLOW test `test_sgesdd_lwork_bug_workaround()` in `scipy/linalg/tests/test_lapack.py`.

> For `scipy/spatial/tests/test_hausdorff.py::test_massive_arr_overflow` you need more RAM. How much RAM is required for that test? My computer has 64gig, and the test fails (actually, the test runner gets killed by...

FWIW, on my Linux machine, with Python 3.10.1 and a development version of NumPy (`'1.24.0.dev0+837.g9c5a2b41c'`), I get the following failures in `stats` when the `xslow` tests are included: ``` ======================================================...

https://github.com/scipy/scipy/pull/17190 should fix two of the `xslow` failures in `scipy.special`.