MAINT: Upgrade to anaconda=2024.02 and cuda=12.3.1

[mmcky]

This PR

• upgrades to anaconda=2024.02
• upgrades to CUDA=12.3.1

this PR is part of QuantEcon/meta#130

requires: #387

• this PR is waiting on interpolations to be updated for numba>=0.59

[mmcky]

• the broken link is to BK19 as a reference but that doesn't seem to be in our quant-con.bib file

You can read  about Dynamic Mode Decomposition here {cite}`DMD_book` and here [[BK19](https://python.quantecon.org/zreferences.html#id25)] (section 7.2).

@jstac or @thomassargent30 do you know what BK19 would refer to and I can add it as a proper reference using bibtex

[jstac]

@mmcky , it refers to this one:
https://www.databookuw.com/

[mmcky]

• this pr requires Use np.interp instead of interpolation.interp #387

[mmcky]

• this cannot be merged until interpolations is updated or there is a substitute for mlinterp that is suitable for the odu lecture (cc @kp992)

ImportError�[0m: cannot import name 'generated_jit' from 'numba' (/opt/conda/envs/quantecon/lib/python3.11/site-packages/numba/__init__.py)

[kp992]

I see, from numba 0.60, generated_jit will fail.

[mmcky]

I see, from numba 0.60, generated_jit will fail.

@kp992 I think from numba>=0.59 it will fail -- so that is why we will need to fix interpolation as we use it for minterp and some splines support. From my discussion with Pablo, the generated_jit will need to be replaced with an alternative (overload?) EconForge/interpolation.py#110

[kp992]

From my discussion with Pablo, the generated_jit will need to be replaced with an alternative (overload?)

I have tried fixing that locally but that's throwing some error. I followed the examples of moving from generated_jit to overload, but didn't work. Let's pin numba < 0.59 until we find and do robust a fix for this issue.

[mmcky]

• check status of Apply @njit to interp and mlinterp EconForge/interpolation.py#114

[github-actions]

🚀 Deployed on https://662db0ad52d90f4fc4907697--nostalgic-wright-5fa355.netlify.app

[mmcky]

@jstac this installs interpolation package in the odu lecture from the main branch of the repo as it isn't released to pypi yet. Are you happy to run with this until pypi is updated?

[mmcky]

• re-enable build cache
• open an issue to update pip install from main branch of interpolation repo to pypi once released

[mmcky]

• reverted to install interpolation from pypi which is currently 2.2.6