[optgrowth_fast/ogm.py] Update np.random → Generator API

[Chihiro2000GitHub]

Summary

This PR migrates legacy NumPy random API usage in _static/lecture_specific/optgrowth_fast/ogm.py as part of QuantEcon/meta#299. The legacy global random-state calls are replaced with an explicit np.random.default_rng() generator.

Details

• The random draw sits inside the @jitclass OptimalGrowthModel.__init__. Following the QuantEcon jitclass convention, rng is passed in as an argument (not stored as a class attribute), and np.random.seed(seed) / np.random.randn(shock_size) are replaced with rng.standard_normal(shock_size).
• The seed parameter is dropped from the constructor; reproducibility now comes from the caller creating rng = np.random.default_rng(seed) and passing it in. This changes the __init__ signature (rng added, seed removed), so call sites must construct with OptimalGrowthModel(rng).
• Within this repository, no lecture appears to :load:/reference optgrowth_fast/ogm.py, so there are no in-repo call sites to update here. Any external call sites (e.g. in other lecture repos) will need to construct rng and pass it in.
• Verified locally that the sized rng.standard_normal(shock_size) call and passing a Generator into the @jitclass compile, run, and remain reproducible under Numba 0.62.1.

Hi @mmcky and @HumphreyYang, I'd be grateful if you could take a look when you have time.

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