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exposures-jura contains some NaN values #2333
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thanks for initiating that. in short: in details: about the expids:
about the columns: desispec/bin/desi_tsnr_afterburner Lines 1115 to 1154 in 9101ccc
the EFFTIME_* columns come from some computation based on those columns, hence getting NaN's:https://github.com/desihub/desispec/blob/0.63.0/py/desispec/efftime.py#L13 for completeness, reading the gfa_table with the same routine, and looking for those columns for those expids:
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and about the I did the following check:
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IIUC all NaN values come from the GFA pipeline when its outputs are merged into to the exposures table. I don't think any of these are coming from the spectro pipeline itself. Options:
In practice these GFA quantities are mostly informative and used for operations debugging since the GFAs are used for the exposure time calculator. i.e. if we're got a quick and solid fix, ok, but I don't think this should delay Kibo. Also, if we confirm that all the NaNs are coming from GFA pipeline inputs being merged into the exposures table, that could be fixed and rerun while Kibo is running, since the exposures table isn't generated until after all of the tile-based processing is done. |
Thank you for contributing to this discussion. This is getting interesting. Here are some preliminary findings:
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Follow up results:
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thanks for the investigation.
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OK, I should have said "many early" SV1 exposures rather than "all" SV1 exposures, but the important thing here is that two GFA summary files must be read for completeness, and one of them will continue to contain the label "SV1". |
We also now know the reason for the difference between When
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While working on #2251, we discovered that the top-level
exposures-jura
files, specifically the exposure tables in those files contained some NaN values.This list of exposures should be all of those that contain NaN. You can see that some of the columns are masked.
This is the list of columns in
exposures-jura
that contain NaN values:The origin of these invalid values should be investigated at high priority in preparation for kibo. As part of the investigation, we need to look into the
tsnr_afterburner
to see where these columns come from.We also need to check the
FRAMES
table for invalid values (part ofexposures-jura.fits
).Attn: @sbailey, @araichoor, @akremin et al..
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