[Comm2011] code to get the 32 intersting raws when imaging some standard stars on all the cjips

[John P. McFarland]

Hi Jeffrey,

The 33 pointings of the 32 CCDs observations are in the following order:

1. center of field in center of mosaic
2. center of field on ESO_CCD_#65 (RawScienceFrame.extension == 1)
3. center of field on ESO_CCD_#66 (RawScienceFrame.extension == 2)
4. center of field on ESO_CCD_#67 (RawScienceFrame.extension == 3)
.
.
.
33. center of field on ESO_CCD_#96 (RawScienceFrame.extension == 32)

The first exposure is at the center of the full field, and all subsequent 
exposures set the center of the field on a CCD in the order of the extension 
number as illustrated above.

Sorry for not spelling this out before.

Cheers,


-=John


On Fri, 10 Jun 2011, Jeffrey Bout wrote:

> Hi all,
> Here some code to determine for a bunch of rawscience frames for
> 'putting some standard stars on all the 32 chips', which of the
> rawscience frames are the ones that image the standard stars:
>
> 1) get some raws...
>
> awe> context.set_project('COMM2011')
> awe> raws = (RawScienceFrame.OBJECT=='SA110')&(RawScienceFrame.is_valid<>0)&(RawScienceFrame.DATE_OBS>datetime.datetime(2011,5,9))&(RawScienceFrame.filter.name=='OCAM_g_SDSS')&(RawScienceFrame.astrom.CRVAL1<>280.458333)
> # not 280.458333 which is not part of the 32 pointings
>
> 2) separate the different exposures
>
> awe> from astro.experimental import jtools
> awe> rg = jtools.group_list(raws, 'DATE_OBS')
>
> 3) simulate the the boundingbox of each corr. coadd.
>
> awe> coadds = [jtools.BoundingBox({'method':'union',
> 'objects':frames}) for frames in rg.values()]
>
> 4) get the overlap of all these coadds, this is the interesting area
>
> awe> overlap = jtools.BoundingBox({'method':'intersection', 'objects':coadds})
>
> 5) optional: a nice plot?
>
> awe> import pylab as pl
> awe> pl.clf()
> awe> for c in coadds: c.plot()
> awe> overlap.plot('g', cross=True)
>
> 6) get the raws that overlap more than 90% with the 'coadds-overlap'
>
> awe> overlapping_raws = dict([(key, jtools.get_value(filter(lambda
> frame: jtools.BoundingBox(frame).get_overlap(overlap, fraction=True) >
> 0.9, frames))) for key, frames in rg.items()])
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