Summary: | Cached state of the next tile selector. |
---|---|
Naming Convention: | scheduler_YEAR-MM-DD.fits , where YEAR-MM-DD is
the date of the sunset (i.e. night) when the scheduler was run. |
Regex: | scheduler_[0-9]{4}-[0-9]{2}-[0-9]{2}\.fits |
File Type: | FITS, 130 KB |
Number | EXTNAME | Type | Contents |
---|---|---|---|
HDU0 | SCHED | IMAGE | 1D Array of Scheduler state |
EXTNAME = SCHED
Snapshot of the internal state of a Scheduler object.
KEY | Example Value | Type | Comment |
---|---|---|---|
NAXIS1 | 16071 | int | Length of dimension 1. |
NIGHT | 2020-03-15 | str | Last night the scheduler was initialized for. |
NDONE | 3 | int | Total number of completed tiles. |
Data: FITS image [float64, 16071]
The data is a 1D array of the integrated squared signal-to-noise ratio (SNR) accumulated on each tile so far, relative to the target value. Tile indexing matches desisurvey.tiles.Tiles.
A Scheduler object schedules observations during each night:
import desisurvey.scheduler scheduler = desisurvey.scheduler.Scheduler()
Its internal state after each afternoon can be saved using, for example:
scheduler.save('scheduler_snapshot.fits')
This state can then be later restored using:
scheduler = desisurvey.scheduler.Scheduler(restore='scheduler_snapshot.fits')