Fix shaper.vals/calibration_data.freqs length mismatch on some Kalico builds

[Hannott]

Summary

SHAPER_CALIBRATE graph generation can crash with a ValueError: x and y must have same first dimension, but have shapes (N,) and (M,) matplotlib error, reported on KalicoCrew/kalico:main when a lower max_freq is configured (reproduced here with max_freq < 150).

Root cause: ShaperComputation.compute() assumes that on Klipper/Kalico builds where CalibrationResult has no freq_bins field, shaper.vals is already truncated to exactly match calibration_data.freqs. That assumption only holds when the requested max_freq is >= the shaper search's own internal frequency ceiling (MAX_SHAPER_FREQ, 150Hz on KalicoCrew/kalico). Internally, fit_shaper computes max_freq = max(max_freq, test_freqs.max()) -- so a lower requested max_freq gets silently overridden, and shaper.vals ends up longer than calibration_data.freqs, which was truncated with the original (lower) value. That length mismatch reaches matplotlib as an opaque crash during graph generation.

Fix

Since freq_bins is sorted ascending, both truncations are prefixes of the same underlying array -- slicing shaper.vals down to len(calibration_data.freqs) recovers the correct values without needing to know the installed Kalico/Klipper version's internal behavior. Falls back to edge-padding with a console warning in the (currently unobserved) case where vals is shorter than expected, rather than crashing.

Also fixes traceback.print_exc() being used inside an f-string in the graph-generation error handler (shaketune_process.py) -- it prints to stderr and returns None, which is why that error message always had a trailing literal None instead of the actual traceback.

Testing

Added test_shaper_length_mismatch.py, which drives the real ShaperComputation against a real Kalico checkout (KalicoCrew/kalico:main) with a synthetic capture, across max_freq values from 80-300:

• Before this fix: fails for max_freq 80 and 100 (below MAX_SHAPER_FREQ) with the exact length-mismatch pattern; also reproduced the literal matplotlib crash end-to-end via shaketune.cli.
• After this fix: passes for all 8 tested max_freq values, no regressions at the values that already worked.

Also verified with ruff check / ruff format --check (both files clean).

Summary by Sourcery

Handle length mismatches between shaper.vals and calibration_data.freqs on older Klipper/Kalico builds to prevent graph-generation crashes.

Bug Fixes:

• Prevent matplotlib graph generation from crashing when shaper.vals has a different length than calibration_data.freqs by truncating or padding shaper values as needed.
• Fix graph-generation error reporting so the full traceback is printed instead of a trailing literal 'None'.

Tests:

• Add a regression test script that runs ShaperComputation against a real Kalico/Klipper checkout across multiple max_freq values to verify shaper.vals aligns with calibration_data.freqs.

[sourcery-ai]

Reviewer's Guide

Fixes a crash in SHAPER_CALIBRATE graph generation caused by a length mismatch between shaper.vals and calibration_data.freqs on older Klipper/Kalico builds with low max_freq, and improves error reporting plus adds a regression test that drives real Kalico firmware across multiple max_freq values.

File-Level Changes

Change	Details	Files
Guard ShaperComputation against shaper.vals/calibration_data.freqs length mismatches on older Klipper/Kalico builds.	Replace assumption that shaper.vals exactly matches calibration_data.freqs with logic that truncates shaper.vals to the expected length when longer. Add a defensive path that pads shaper.vals via np.pad with edge mode when it is shorter than calibration_data.freqs, emitting a ConsoleOutput warning instead of crashing. Document the internal fit_shaper/max_freq behavior and the previous matplotlib crash scenario in comments.	shaketune/graph_creators/computations/shaper_computation.py
Improve exception reporting when graph generation fails.	Replace traceback.print_exc() usage inside an f-string with traceback.format_exc() so the full traceback string is captured and printed without an extra literal 'None'.	shaketune/shaketune_process.py
Add a regression test that exercises ShaperComputation against a real Kalico/Klipper checkout across a range of max_freq values.	Introduce a synthetic accelerometer capture generator with resonance-like data extending beyond 300Hz. Load actual shaper_calibrate/shaper_defs modules from a provided Kalico/Klipper checkout to use real firmware code in the test. Drive ShaperComputation over a configurable list of max_freq values spanning below, at, and above MAX_SHAPER_FREQ, and assert that all shaper vals arrays match calibration_data.freqs length, failing with a clear summary if any mismatch is found.	test_shaper_length_mismatch.py

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[sourcery-ai]

Hey - I've found 1 issue

Prompt for AI Agents

Please address the comments from this code review:

## Individual Comments

### Comment 1
<location path="shaketune/graph_creators/computations/shaper_computation.py" line_range="120-127" />
<code_context>
+                # (a mismatch here used to reach matplotlib as an opaque "x and y must have the same
+                # first dimension" crash -- see issue with max_freq=300 on KalicoCrew/kalico).
+                n = len(calibration_data.freqs)
+                if len(shaper.vals) < n:
+                    ConsoleOutput.print(
+                        f'Warning: {shaper.name} returned fewer frequency bins than expected '
+                        f'({len(shaper.vals)} < {n}); padding with its last value. This may indicate '
+                        'an unsupported Klipper/Kalico version -- results near the high end of the '
+                        'graph may be inaccurate.'
+                    )
+                    vals_resampled = np.pad(shaper.vals, (0, n - len(shaper.vals)), mode='edge')
+                else:
+                    vals_resampled = shaper.vals[:n]
</code_context>
<issue_to_address>
**issue:** Guard against the case where `shaper.vals` is empty before using `np.pad(..., mode='edge')`.

If `shaper.vals` is ever empty, `np.pad(..., mode='edge')` will raise a `ValueError` because there is no edge element to replicate. Please add an explicit check for the empty case (e.g. `if not shaper.vals: ...`) or use `mode='constant'` for this branch so a Klipper/Kalico mismatch doesn’t become a hard crash.
</issue_to_address>

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