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new bright time exposure factor #126
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will be calculated based on observing conditions
exposure factor calculation for available tiles.
Thanks Chang. Some comments:
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Great, yeah, I imagine the dark / gray time is the easier part of the model. Let's get that in this PR if it sounds feasible? I agree that the read noise comes in only there. My comment was more to say that that same bright_exposure_factor could be used outside of bright time without doing damage. And then it would be great to see the results from a surveysim run with these changes; i.e., when the dark / gray / bright surveys get finished. |
… times; etc.sky_exposure_factor modified to take nominal exposure time as an input
…t_weather in surveysim.nightops
accurately accounts for read noise. I've also added some documentation on sky_level
@schlafly Could you check over this pull request again? Below are the latest changes:
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I've updated the bright time exposure factor calculation based on SV1 observations. The new exposure factor
etc.bright_exposure_factor
is calculated using a regression sky brightness model fit to SV1, CMX, and BOSS sky brightness observations. The exposure factor accounts for read noise and assumes a new reference BGS sky (nominal dark sky scaled to r=21.07 + moon/solar spectrum scaled to r=20.07). Below are specific changes to the modulespy/desisurvey/ephem.py
py/desisurvey/etc.py
bright_exposure_factor
function calculates the bright time exposure factor based on airmass, moon illumination, moon separation, moon altitude, sun separation, and sun altitude. The exposure factor is how much the bright time exposure has to be scaled to match the SNR of the reference BGS sky (see notebook for new ref. sky). The calculation includes read noise contributions.bright_Isky5000_notwilight_regression
function calculates the sky surface brightness without twilight contributions at 5000A using a regression model. This sky model was fit using SV1, CMX, and BOSS observationsbright_Isky5000_twilight_regression
function calculates the twilight sky contribution at 5000A using a regression model. The twilight contribution was fit using BOSS twilight observations with sun alt > -18.py/desisurvey/scheduler.py
Scheduler.init_night
: now initializes moon Alt, Az, sun RA, Dec, Alt, Az in addition moon RA and Dec.Scheduler.next_tile
: for BRIGHT programetc.bright_exposure_factor
in included in the exposure factor calculation.py/desisurvey/util.py
import astropy._erfa.core
since it wasn't used and caused import errors.