fix: clean up type handling

[beckermr]

This PR cleans up the type handling.

The goal is to have objects do one of three things:

1. If it is a python numeric type (i.e., int or float) or a numpy scalar type (i.e., isinstance(x, np.number), isinstance(x, np.integer), etc.; see https://numpy.org/doc/stable/reference/arrays.scalars.html#built-in-scalar-types), convert it to a python type of the appropriate kind.
2. Otherwise, cast to the correct type via jax.numpy.astype(x, ...).
3. For outputs in FITS headers, we allow conversions of numpy/jax arrays to python numeric types as long as there is one element in the array (i.e., it is a numpy scalar type, an array scalar, or a 1D array with one element).

This set of rules is simple to understand, consistently handles array scalars (i.e., arrays with zero dimensions) in that any numpy array scalar is converted to a jax array scalar, and transparently handles JAX tracing.

The diff on the PR results in fewer lines of code, which is a nice side effect!

TODO:

• instead of duck-typing via try...except blocks, explicitly test for types
• eliminate the has_tracers function in favor of transparent handling
• eliminate use of cast_to_python_float / cast_to_python_int outside of FITS handling
• document the ideas above in docs

closes #246

[codspeed-hq]

Merging this PR will not alter performance

⚠️ Unknown Walltime execution environment detected

Using the Walltime instrument on standard Hosted Runners will lead to inconsistent data.

For the most accurate results, we recommend using CodSpeed Macro Runners: bare-metal machines fine-tuned for performance measurement consistency.

⚠️ Different runtime environments detected

Some benchmarks with significant performance changes were compared across different runtime environments,
which may affect the accuracy of the results.

Open the report in CodSpeed to investigate

⚡ 4 improved benchmarks
❌ 3 regressed benchmarks
✅ 29 untouched benchmarks

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Mode	Benchmark	BASE	HEAD	Efficiency
⚡	WallTime	test_benchmarks_lanczos_interp[xval-conserve_dc-run]	126.5 µs	95.8 µs	+32.01%
⚡	WallTime	test_benchmarks_lanczos_interp[xval-no_conserve_dc-run]	123.7 µs	92.6 µs	+33.52%
⚡	WallTime	test_benchmarks_lanczos_interp[kval-no_conserve_dc-run]	57.9 µs	43.7 µs	+32.7%
❌	WallTime	test_benchmarks_metacal[run]	20.2 ms	34.8 ms	-41.84%
❌	WallTime	test_benchmark_spergel_conv[run]	169.2 ms	242.8 ms	-30.3%
⚡	WallTime	test_benchmark_moffat_init[run]	103 µs	58.9 µs	+75.04%
❌	WallTime	test_benchmark_moffat_conv[run]	195.3 ms	285.9 ms	-31.7%

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.

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_{Comparing typing-inits-cleanup (1aeb448) with main (6ebfcb8)}

[beckermr]

@ismael-mendoza This PR is based on top of #243. I plan to merge it after #243. Comments welcome!

[ismael-mendoza]

Thanks Matt! I just have a few minor comments/questions and perhaps one small bug in _cast_to_static_numeric_scalar?

[ismael-mendoza]

Could you explain why this is the check here? I guess more specifically, why not ensure that other is scalar instead?

[beckermr]

So the goal in this PR is to let arrays and tracers pass through without trying to detect which is which. We can do that for the most part (except for a few cases like BoundsI). So the goal of the check here is guard against common errors of handling Angles and AngleUnits.

[ismael-mendoza]

so if I understand correctly, if someone tries to have non static deltax or deltay they will now get a ConcretizationTypeError, with no error raised from JAX Galsim explicitly. Is that the intention since we warn the user in the LAX docs and we want to avoid using has_tracers?

[beckermr]

Yes that is the intention. I am further cleaning this up in #250.

[beckermr]

pre-commit.ci autofix

[beckermr]

OK @ismael-mendoza this one is ready for another look!

[ismael-mendoza]

Looks great!