perf(zernike): build z**m iteratively in _zernike_scores#92
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The azimuthal power table used `z**m` (m up to the zernike order) on the complex foreground-pixel array; `**` is ~20x slower than repeated multiply for m>=3. Accumulating the powers by multiplication is bit-identical and cuts ~9% off _zernike_scores across image sizes — both get_zernike and the intensity-weighted radial Zernikes go through it. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Benchmark —
|
| size \ objects | 16 | 64 | 256 |
|---|---|---|---|
| 256 | 1.01× | 1.01× | 0.99× |
| 512 | 1.06× | 1.01× | 0.93× |
| 1024 | 0.98× | 1.00× | 1.02× |
manders_fold
| size \ objects | 16 | 64 | 256 |
|---|---|---|---|
| 256 | 0.99× | 0.98× | 0.97× |
| 512 | 0.96× | 0.97× | 0.92× |
| 1024 | 0.97× | 0.97× | 0.98× |
radial_zernikes
| size \ objects | 16 | 64 | 256 |
|---|---|---|---|
| 256 | 1.13× | 1.15× | 1.11× |
| 512 | 1.08× | 1.15× | 1.09× |
| 1024 | 1.12× | 1.12× | 1.11× |
zernike
| size \ objects | 16 | 64 | 256 |
|---|---|---|---|
| 256 | 1.14× | 1.15× | 1.11× |
| 512 | 1.09× | 1.11× | 1.11× |
| 1024 | 1.10× | 1.13× | 1.12× |
afermg
approved these changes
Jul 3, 2026
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Kind of crazy the difference, but might as well add the change.
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_zernike_scoresbuilt its azimuthal power table withz**m(m up to the zernike order) on the complex foreground-pixel array. For m ≥ 3, numpy's**is ~20× slower than repeated multiplication. Accumulating the powers by multiplication (z, z·z, …) is bit-identical and cuts ~9% off_zernike_scoresacross image sizes — bothget_zernikeand the intensity-weighted radial Zernikes go through it.Verified bit-identical to the previous output; existing
test_zernike.py/test_radial_zernike.pycover it.