revised exposure factor implementation for bright time#109
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changhoonhahn wants to merge 38 commits into
Open
revised exposure factor implementation for bright time#109changhoonhahn wants to merge 38 commits into
changhoonhahn wants to merge 38 commits into
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…exposure_factor; changes in etc.bright_exposure_factor to deal with moon and sun parameter inputs; setup.py adjusted to read in gp files; GP files are made using python2 and thus incompatible...
- regression models for bright sky exposure factor implemented in `desisurvey.etc` - `desisurvey.scheduler.Scheduler` now has a method `update_exposure_factor` to calculate exposure factor - if `use_brightsky == True` for `desisurvey.scheduler.Scheduler`, bright sky exposure factor is used in `next_tile`.
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I think these will be pretty orthogonal, fortunately! |
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- new polynomial regression model fit to exposure time factors measured from BOSS and DESI CMX data. - previous regression model, which is the one implemented in [desisurvey pull request #109](desihub/desisurvey#109) show significant discrepancies for high exposure time factors. - new model does significantly better, especially for DESI CMX exposures.
…xposure factor for bright time
… corrected CMX sky surface brightness
…OSS, CMX and SV1 data
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py/desisurvey/ephem.pypy/desisurvey/etc.pybright_exposure_factorfunction calculates the bright time exposure factor from airmass, moon illumination, moon separation, moon altitude, sun separation, and sun altitude as input._bright_exposure_factor_notwifunction calculates the bright time exposure factor without twilight contributions from airmass and moon parameters. The function uses a polynomial regression model fit to exposure factors calculated using an improved sky brightness model (see notebook). The model is based on re-fitting Krisciunas & Schaefer (1991) to BOSS sky fiber data plus twilight contribution from Parker Fagrelius's thesis work. See notebook for a comparison of the original KS1991 sky model to refit+twilight model._bright_exposure_factor_twifunction calculates the twilight contribution to the bright time exposure factor. The function uses a simple linear regression model that takes airmass, sun separation, and sun altitude as input.py/desisurvey/scheduler.pynext_tilemethod: Ifuse_brightsky==True, bright time exposure factor is included in next tile selectionupdate_exposure_factormethod implemented. This method is also called insurveysim.nightops.simulate_nightto correct the ETC on the fly.