DM-54482: Integrate PSF-shapelet subtask into calibrateImage as a donut-detector#1302
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laurenam
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TallJimbo
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| afwTable.CoordKey.addErrorFields(self.psf_schema) | ||
| # This is to ensure the shapelets metrics make it into the exposure | ||
| # summary stats even if all calibrations fail. | ||
| self.initial_summary = None |
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Please pass this around as a local variable and method argument/return value instead of a task instance attribute. That might require changing some signatures of (hopefully) private methods, but it makes it a lot easier to read how information and logic flows through the task.
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Yeah, that’s what I tried to do initially, but because of the exception handling in _compute_psf, I couldn’t get it returned when the PSF modelling fails. I’ll try factoring out the shapelets measurement into its own method (but will have to think through passing catalogs around).
| background : `lsst.afw.math.BackgroundList` | ||
| summary : `lsst.afw.image.ExposureSummary`, optional | ||
| Summary object to be appended to if not `None`. If `None` a new | ||
| summary opject will be created. |
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| summary opject will be created. | |
| summary object will be created. |
laurenam
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These shapeletes will help in assessing the focus (IQ) of the image. Thresholds on the coefficient distributions will hopefully allow for decisions to be made on the value of further processing the image (particularly important for prompt processing such that we don't alert on donuts) and/or inclusion in coadds in general and/or for specific science use cases.
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TallJimbo
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