on MPIA computers, and then link this to pythoning... (E. Schlafly --> HWR)
As of July 2013 the PS1 stuff is migrating to aida41233; so: ssh -Y aida41233
then:
> source /disk/LSD/LSD/lsd_environment_a41233_2
> ipython --pylab
within python
plot(arange(10)) % test whether plotting windows
from lsd import bounds %
import util_efs_pub
ob=util_efs_pub.query_lsd('select * from ucal_magsqw',bounds=bounds.beam(150.,50.,1.))
% the syntax of that query should be like sql; in essence get "everything" within 1 degree of (150,50)
len(ob)
ob.dtype %take a look at what's in the table
m = numpy.sum(ob['namg_ok']>0,axis=1) >=3
m = numpy.sum(ob['nmag_ok']>0,axis=1) >=3 % pick out those object with good detection in 3 bands
clf(); plot(ob['ra'][m], ab['dec'][m], ',') % make a plot
clf(); plot(ob['ra'][m], ob['dec'][m], ',')
clf() ; plot(ob['mean'][:,0]-ob['mean'][:,1],ob['mean'][:,0], ',') % make a CMD
ob.dtype
%save first_lsd_steps 1-18 % that saves the session
ob=util_efs_pub.query_lsd('select * from ucal_magsqw , sdss(matchedto=ucal_magsqw)',bounds=bounds.beam(150.,50.,1.)) % cross-matched catalog
ob_stack=util_efs_pub.query_lsd('select * from stack , sdss(matchedto=stack)',bounds=bounds.beam(150.,50.,1.)) % query stacked catalog
ob_stack=util_efs_pub.query_lsd('select * from ps1_det , sdss(matchedto=ps1_det)',bounds=bounds.beam(150.,50.,1.))
ob_stack.dtype
ob_ps1_det=util_efs_pub.query_lsd('select * from ps1_det , sdss(matchedto=ps1_det)',bounds=bounds.beam(150.,50.,1.))
Issues: there is no single data base that has everything; e.g. to get proper motions,
one has to talk to Bertrand where this information is....
subsequent e-mail from Eddie
The database that Bertrand has made with Gene's proper motions is in: /a41217d5/LSD/PS1/tpifeb13 That means if your LSD_DB includes /a41217d5/LSD/PS1 then you can get at the proper motions via select * from tpifeb13 or select * from ucal_magsqw, tpifeb13(matchedto=tpifeb13) ... and things should work.
