Added util to correct over-estimation of AOS residual #4
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jbkalmbach
approved these changes
Apr 28, 2025
| """Correct the AOS residual for over-estimation. | ||
| This correction is empirically fit in | ||
| https://gist.github.com/jfcrenshaw/24056516cfa3ce0237e39507674a43e1 |
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Do you want to maybe move this to ts_aos_analysis?
| Parameters | ||
| ---------- | ||
| zernikes : np.ndarray |
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I'm assuming when using sparse Zernikes you should fill in with 0s the unused indices? I think it would be good to mention that here.
| # Finally check converting array of 1's returns the coefficients | ||
| coeffs = convertZernikesToPsfWidth(np.ones(19)) | ||
| self.assertTrue(np.allclose(coeffs, getPsfGradPerZernike())) | ||
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I know it's trivial but for completeness can you add a convertAOSResid test?
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