Describe the issue:

I was working on Pynguin, an automated unit test generation tool for Python, and the tool found that Numpy creates a segmentation fault when doing a "Bitwise OR" on a np.longdouble with a None value.

Reproduce the code example:

import numpy

numpy.longdouble() | None

Error message:

Segmentation fault (core dumped)

Python and NumPy Versions:

2.0.0
3.10.14 (main, Mar 21 2024, 16:24:04) [GCC 11.2.0]

Runtime Environment:

[{'numpy_version': '2.0.0',
'python': '3.10.14 (main, Mar 21 2024, 16:24:04) [GCC 11.2.0]',
'uname': uname_result(system='Linux', node='lucas-hp', release='6.8.11-200.fc39.x86_64', version='#1 SMP PREEMPT_DYNAMIC Sun May 26 20:05:41 UTC 2024', machine='x86_64')},
{'simd_extensions': {'baseline': ['SSE', 'SSE2', 'SSE3'],
'found': ['SSSE3',
'SSE41',
'POPCNT',
'SSE42',
'AVX',
'F16C',
'FMA3',
'AVX2'],
'not_found': ['AVX512F',
'AVX512CD',
'AVX512_KNL',
'AVX512_KNM',
'AVX512_SKX',
'AVX512_CLX',
'AVX512_CNL',
'AVX512_ICL']}},
{'architecture': 'Zen',
'filepath': '/home/lucas/.conda/envs/pynguin-for-ML-libraries/lib/python3.10/site-packages/numpy.libs/libscipy_openblas64_-99b71e71.so',
'internal_api': 'openblas',
'num_threads': 12,
'prefix': 'libscipy_openblas',
'threading_layer': 'pthreads',
'user_api': 'blas',
'version': '0.3.27'}]

Context for the issue:

It's not a particularly serious bug, but an exception is thrown when the same code is run with a np.double, so fixing the bug might be a good idea to make it more user-friendly in the event of a user error and to make it more consistent with other Numpy types.