delta/python-packages/numpy.git/tools/swig/numpy.i, branch dependabot/pip/gitpython-3.1.14 github.com: numpy/numpy.git removed extraneous ARGOUTVIEWM dim. 4 typemaps 2021-03-01T21:52:56+00:00 Patrick T. Komiske III pkomiske@mit.edu 2021-03-01T21:52:56+00:00 10b540ad0d82d7c1d0124c7cf9a8370490dcb8a4 https://github.com/numpy/numpy/issues/18521 
https://github.com/numpy/numpy/issues/18521
 MAINT: Cleanup swig for Python 3. 2020-10-18T21:05:25+00:00 Charles Harris charlesr.harris@gmail.com 2020-10-18T20:18:10+00:00 cf06cd41ba8bd49b3ada8aa333df8e562829247b Replaces ``PyInt_Check`` and ``PyInt_AsLong`` in a few places. 
Replaces ``PyInt_Check`` and ``PyInt_AsLong`` in a few places.
BLD: Fixed ARGOUTVIEWM memory deallocation. 2020-09-29T17:43:46+00:00 leakec leakec57@gmail.com 2020-09-29T17:43:46+00:00 4c74f375936c5271d48ec101676de1b3ab0b743c Closes #17398 
Closes #17398
MAINT: Replace PyString_Check with PyBytes_Check in numpy.i. 2020-09-11T00:03:58+00:00 Charles Harris charlesr.harris@gmail.com 2020-09-11T00:03:58+00:00 fcca6e7950e43a5d8ff88ec4bb22bb436bcc833e Replace the npy_3kcompat PyString_Check with its definition. This is done separately for the tools/swig/numpy.i file as it might be problematic. 
Replace the npy_3kcompat PyString_Check with its definition.  This is
done separately for the tools/swig/numpy.i file as it might be
problematic.
Cleaning up PY_MAJOR_VERSION/PY_VERSION_HEX 2020-01-03T21:44:22+00:00 Seth Troisi sethtroisi@google.com 2020-01-03T21:44:22+00:00 24189be60ec4d823f4068be727b5d28f7eacc823 






White spaces
2018-02-08T22:59:59+00:00

Mathieu Lamarre
mlamarre@ea.com

2018-02-08T22:59:59+00:00

50329041147190643a815ed0006920400048d0c5












Swig tool: Clear CARRAY flag when buffer is not C_CONTIGUOUS
2018-02-08T19:10:58+00:00

Mathieu Lamarre
mlamarre@ea.com

2018-02-08T19:10:58+00:00

a119f03a846e76dcc9aff64ea760b9f128110ea6

Leave the flag if there's only one non unit dim





Leave the flag if there's only one non unit dim







Swig tool: Clear CARRAY flag when setting FARRAY
2018-02-08T16:00:21+00:00

Mathieu Lamarre
mlamarre@ea.com

2018-02-08T16:00:06+00:00

6c4a77bf87b8a6fcadd7a128f73b8f2954642bec

Otherwise the returned array has both flags, which creates all sorts of confusing runtime behaviors.
C_CONTIGUOUS : True
F_CONTIGUOUS : True
Doesn't cause a crash, but some functions like copy() works in F_CONTIGUOUS others like element wise operators assume C_CONTIGUOUS, obviously this becomes a nightmare to debug.





Otherwise the returned array has both flags, which creates all sorts of confusing runtime behaviors.
C_CONTIGUOUS : True
F_CONTIGUOUS : True
Doesn't cause a crash, but some functions like copy() works in F_CONTIGUOUS others like element wise operators assume C_CONTIGUOUS, obviously this becomes a nightmare to debug.







Added types for int and uint with an explicit size.
2018-01-12T17:48:56+00:00

Mark Harfouche
mark.harfouche@gmail.com

2018-01-12T17:48:56+00:00

5dc1f717844723dd2524d318ae7a3ff9da7fe3e7












Avoid NPY_ARRAY_F_CONTIGUOUS for numpy < 1.7
2016-06-18T11:50:56+00:00

Jan David Mol
mol@astron.nl

2016-06-18T11:50:56+00:00

de97bb2ccaa4293632fdd28f6370d63a55d5d538

numpy API < 1.7 does not support NPY_ARRAY_F_CONTIGUOUS.or PyArray_IS_F_CONTIGUOUS. Supporting old APIs is useful as users tend to ship modern numpy.i files to compile against possibly older numpy installations.




numpy API < 1.7 does not support NPY_ARRAY_F_CONTIGUOUS.or PyArray_IS_F_CONTIGUOUS. Supporting old APIs is useful as users tend to ship modern numpy.i files to compile against possibly older numpy installations.