Chart performance: lift loop throttle and de-pandas render path

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Summary

Three changes that together take the chart from the user-reported ~5 fps on a Pi to an estimated ~30 fps, plus a related 2× win on the main-menu screens. The PR is intentionally three commits so each piece can be reverted independently.

1. b501a62d — Use sleep_for_framerate in the main loop

main.py:560 was time.sleep(0.1) in the queue.Empty fallback, pinning every UI module at ~10 Hz max. Replaced with state_utils.sleep_for_framerate(shared_state) (the same throttle other UI modules already use directly): ~30 Hz when awake, ~2 Hz when asleep.

Also dropped the redundant time.sleep(0.2) from PowerManager.update() — the new throttle already sleeps longer when asleep, so the explicit sleep was unnecessary and slightly less power-saving than the new behavior.

2. 9c9ec779 — Remove redundant per-module framerate sleeps

Now that the main loop throttles, the per-module sleep_for_framerate / time.sleep(1/30) calls at the top of various UI update() methods are a second 33 ms sleep per iteration — capping those screens at ~13–15 Hz instead of 30 Hz.

Removed from equipment.py, gpsstatus.py, sqm.py, software.py, status.py. Other time.sleep(...) calls in ui/ (camera settling in calibration, marking-menu flash, exposure-sweep delays, etc.) are intentional state-waits and left in place.

3. 229fa49e — De-pandas the chart hot path

plot.py:plot_starfield / plot_markers / radec_to_xy were doing several DataFrame.assign() chains per frame over the star catalog and the constellation edges. Each .assign() builds a brand-new DataFrame and each column access dispatches through pandas — cProfile showed ~138 pandas.Series.__init__ calls per frame, dominating the per-frame cost.

Per-frame projection / rotation / screen-space / visibility math now runs on numpy arrays cached on the Starfield instance. Pandas DataFrames are kept only at the boundaries where they buy us something:

• Star.from_dataframe() is the documented skyfield API for building Stars in bulk; plot_markers and radec_to_xy still build a tiny DataFrame just for that call.
• render_starfield_pil still returns visible_stars as a DataFrame (sliced from self.stars once at the end) because ui/align.py treats it as a pandas object (.iloc, .sort_values, .assign, plus ra_degrees / dec_degrees column access).

Measured effect (Mac, 128×128 chart at FOV 10.2°)

Path	Before (release)	After commits 1–2	After all 3	Speedup
Main-loop iteration cap (no work)	10 Hz	30 Hz	30 Hz	3×
Menu-screen rate (trivial render)	~13 Hz	~27 Hz	~27 Hz	2×
Chart plot_starfield total	3,870 µs	3,870 µs	541 µs	~7.2×
Chart plot_markers (3)	1,625 µs	1,625 µs	355 µs	~4.6×
Chart full per-frame	5,750 µs	5,750 µs	1,084 µs	~5.3×

cProfile after this PR: per-frame pandas writes drop from 138 → 2 (the two visible_stars["x_pos"/"y_pos"] = ... assigns at the end of render_starfield_pil). The remaining dominant per-frame costs are skyfield.projections.project() and PIL's ImageChops — both C code, at the floor for pure-Python optimization.

Pi extrapolation

The user observed ~5 fps chart on the Pi before any of this work, implying ~167 ms/frame on Pi vs ~5.7 ms on Mac (~30× scaling). Applying that factor to the new 1,084 µs Mac figure suggests ~30 ms/frame on Pi, which fits within the 33 ms sleep_for_framerate budget — chart should now sustain close to 30 Hz instead of 5 Hz.

Behavioral diffs to be aware of

	Awake	Asleep
Before	~10 Hz (0.1 s sleep)	~3.3 Hz (0.1 + 0.2 s sleeps)
After	~30 Hz (1/30 s sleep)	2 Hz (0.5 s sleep)

Wake-from-sleep latency goes from ~300 ms to ~500 ms (one asleep-loop iteration). If that ever feels too slow in practice, the lever is state_utils.sleep_for_framerate's asleep value — but it affects all UI modules, so I left it alone.

Test plan

• nox -s lint clean
• nox -s format clean
• nox -s smoke_tests 2/2 pass
• nox -s unit_tests 98/98 pass
• Loop-rate harness confirms the expected 10→22 Hz chart and 13→27 Hz menu rates on the dev machine
• Smoke test on a Pi to confirm the predicted ~6× chart improvement and that the new ~30 Hz awake cadence is comfortable from a CPU/power standpoint

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