Add support for numpy 2 #2421
Add support for numpy 2 #2421
Conversation
| @@ -108,7 +108,7 @@ def clebsch(j1, j2, j3, m1, m2, m3): | |||
| C = np.sqrt((2.0 * j3 + 1.0)*_to_long(c_factor)) | |||
|
|
|||
| s_factors = np.zeros(((vmax + 1 - vmin), (int(j1 + j2 + j3))), np.int32) | |||
| sign = (-1) ** (vmin + j2 + m2) | |||
| sign = int((-1) ** (vmin + j2 + m2)) | |||
There was a problem hiding this comment.
Why did this need to be wrapped with int?
There was a problem hiding this comment.
clebsch is computed using large integer over 32 and sometime 64 bits.
If the sign is a 0d numpy array it overflow.
There was a problem hiding this comment.
Ah. Perhaps add a comment above this line with that explanation?
|
Numpy is maintaining a list of project versions that support numpy 2 -- numpy/numpy#26191. They're waiting of downstream packages to be ready before release. We could add ourselves there if we liked. |
There was a problem hiding this comment.
Numpy 2.0 is scheduled to be released June 6th (see numpy/numpy#24300 (comment))
| os: ubuntu-latest | ||
| python-version: "3.12" | ||
| scipy-requirement: "" | ||
| numpy-requirement: "==2.0.0rc1" |
There was a problem hiding this comment.
| numpy-requirement: "==2.0.0rc1" | |
| numpy-requirement: "==2.0.0rc2" |
There is a new release candidate available
| os: ubuntu-latest | ||
| python-version: "3.10" | ||
| scipy-requirement: "" | ||
| numpy-requirement: "==2.0.0rc1" |
There was a problem hiding this comment.
| numpy-requirement: "==2.0.0rc1" | |
| numpy-requirement: "==2.0.0rc2" |
Description
Add support for the up comming numpy v2:
I did not update the requirement yet, it must be installed in
--no-build-isolation.When it's officially released, we will need to update
pyproject.tomlandsetup.cfg, and possibly add test for np2 on windows and mac.Here are the changes that affect us:
np.array(.., copy=False)no longer mean copy only if needed.copy=Nonewas added for that.np.trapzwas replaced bynp.trapezoid. Since there are no overlaps, I opted to usescipy.integrate.trapezoidinstead.np.array(1, np.int32) * 2**33will enforce the integer type and overflow.Py_intptr_tfrompython.his no longer available through numpy cython interface.