def update_status(id, **kwargs):
with SurveysDB() as sdb:
r = sdb.get_field(id)
for k in kwargs:
r[k] = kwargs[k]
sdb.set_field(r)
print('Now searching for results directories')
cwd = os.getcwd()
# find what we need to put in the mosaic
mosaicpointings, mosseps = find_pointings_to_mosaic(
pointingdict, mospointingname)
if ignorepointings != '':
ignorepointings = ignorepointings.split(',')
maxsep = np.max(mosseps)
# now find whether we have got these pointings somewhere!
mosaicdirs = []
missingpointing = False
scales = []
sdb = SurveysDB()
for p in mosaicpointings:
if p in ignorepointings:
continue
print('Wanting to put pointing %s in mosaic' % p)
for d in args.directories:
rd = d + '/' + p
print(rd)
if os.path.isfile(rd + '/' + fname):
mosaicdirs.append(rd)
try:
qualitydict = sdb.get_quality(p)
currentdict = sdb.get_field(p)
print(qualitydict)
#scale=qualitydict['scale']
scale = 1.0 / (qualitydict['nvss_scale'] / 5.9124)
if 'ddfp-' in jobname:
jobs[jobname[5:]]=status
return jobs
def plotcircle(name,ra,dec,color,pcolor='black'):
circle1=plt.Circle((ra,dec),csize,color=color,alpha=0.2)
plt.gcf().gca().add_artist(circle1)
plt.scatter(ra,dec,color=pcolor)
plt.text(ra,dec,name)
jobs=qstat()
print jobs
circles=[]
s_colours={'D/L failed':'black','List failed':'black','Downloading':'red','Downloaded':'orange','Unpacking':'orange','Unpacked':'orange','Ready':'yellow','Queued':'blue','Running':'cyan','Complete':'green','Archiving':'green','Archived':'olive','Stopped':'magenta','Failed':'magenta','DI_started':'white'}
sdb=SurveysDB(readonly=True)
sdb.cur.execute('select * from fields where status!="Not started"')
fields=sdb.cur.fetchall()
sdb.close()
for f in fields:
status=f['status']
shortname=f['id']
job_status = ''
d_colour='black'
if status=='Running' or status=='Ready' or status=='Failed':
if len(jobs)>0:
if shortname not in jobs:
job_status = 'not queued'
d_colour = 'red'
elif jobs[shortname] == 'Q':
#!/usr/bin/python
# Ingest the LOTSS file provided by Tim
import sys
from surveys_db import SurveysDB
import requests
root = 'https://lofar-webdav.grid.sara.nl/SKSP/L'
lines = [l.rstrip() for l in open(sys.argv[1]).readlines()]
sdb = SurveysDB()
sdb.cur.execute('delete from fields_new')
sdb.cur.execute('delete from observations')
for l in lines[1:]:
bits = l.split(',')
if bits[1] == 'WRONG':
continue
field = bits[0]
ra = float(bits[1])
dec = float(bits[2])
time = float(bits[3])
if bits[4] == 'None':
ids = []
else:
ids = bits[4].split(' ')
if ids[0] == '':
ids = ids[1:]
print time, field, ra, dec, ids
sdb.cur.execute(
'insert into fields_new values ( %s,"Not started",%s,%s,NULL,NULL,NULL,NULL,0)',
os.system(
'ssh lofar.herts.ac.uk "rm -rf /beegfs/lofar/lba/calibration_solutions/%s"'
% cal)
os.system(
'ssh lofar.herts.ac.uk "mkdir /beegfs/lofar/lba/calibration_solutions/%s"'
% cal)
os.system(
'scp -q cal-pa.h5 cal-amp.h5 cal-iono.h5 lofar.herts.ac.uk:/beegfs/lofar/lba/calibration_solutions/%s'
% cal)
os.system(
'scp -q -r plots* lofar.herts.ac.uk:/beegfs/lofar/lba/calibration_solutions/%s'
% cal)
# update the db
from surveys_db import SurveysDB
with SurveysDB(survey='lba', readonly=False) as sdb:
sdb.execute(
'INSERT INTO observations (id,calibratordata) VALUES (%i,"%s")' %
(obsid, cal))
w.done('upload')
### DONE
# a debug image
if imaging:
logger.info("Imaging section:")
if iono3rd:
MSs = lib_ms.AllMSs(sorted(
glob.glob('./*MS'))[int(len(glob.glob('./*MS')) / 2.):],
s,
t=Table.read('/home/mjh/pipeline-master/ddf-pipeline/misc/DR2-pointings.txt',format='ascii')
colnames=['Field','RA','Dec']
for i,c in enumerate(t.colnames):
t[c].name=colnames[i]
fields=['0h','8h','13h']
t0h=t[(t['RA']<50) | (t['RA']>300)]
t8h=t[(t['RA']<140) & (t['RA']>90)]
t13h=t[(t['RA']>140) & (t['RA']<250)]
ft=[t0h,t8h,t13h]
for field,t in zip(fields,ft):
print field,len(t)
with SurveysDB() as sdb:
sdb.cur.execute('select fields.id,fields.ra,fields.decl,fields.status,quality.* from fields left join quality on fields.id=quality.id order by fields.id')
results=sdb.cur.fetchall()
td={}
for r in results:
td[r['id']]=r
for field,t in zip(fields,ft):
print field,len(t)
complete=0
incomplete=0
incomplete_fields=[]
rmsmean=[]
for r in t:
name=r['Field']
args = parser.parse_args()
mospointingname = args.mospointingname
pointingdict = read_pointingfile()
print 'Now searching for results directories'
cwd = os.getcwd()
# find what we need to put in the mosaic
mosaicpointings, mosseps = find_pointings_to_mosaic(
pointingdict, mospointingname)
maxsep = np.max(mosseps)
# now find whether we have got these pointings somewhere!
mosaicdirs = []
missingpointing = False
sdb = SurveysDB()
for p in mosaicpointings:
print 'Wanting to put pointing %s in mosaic' % p
currentdict = sdb.get_field(p)
for d in args.directories:
rd = d + '/' + p
print rd
if os.path.isfile(
rd +
'/image_full_ampphase_di_m.NS_shift.int.facetRestored.fits'
):
mosaicdirs.append(rd)
break
else:
print 'Pointing', p, 'not found'
from astropy.table import Table
import glob
import os
import numpy as np
from surveys_db import SurveysDB
os.chdir('/data/lofar/DR2/fields')
g = glob.glob('*')
a1l = []
a2l = []
sdb = SurveysDB()
for d in g:
infile = d + '/image_full_ampphase_di_m.NS.cat.fits_NVSS_match.fits'
if os.path.isfile(infile):
t = Table.read(infile)
t = t[t['Total_flux'] > 0.01]
l1 = len(t)
#alpha1=np.median(np.log(t['Total_flux']/t['NVSS_Total_flux'])/np.log(1400/144.0))
alpha1 = np.median(t['Total_flux'] / t['NVSS_Total_flux'])
t = t[t['Total_flux'] > 0.03]
l2 = len(t)
#alpha2=np.median(np.log(t['Total_flux']/t['NVSS_Total_flux'])/np.log(1400/144.0))
alpha2 = np.median(t['Total_flux'] / t['NVSS_Total_flux'])
print d, alpha1, alpha2, l1, l2
a1l.append(alpha1)
a2l.append(alpha2)
r = sdb.get_quality(d)
r['nvss_scale'] = alpha2
RA = ravals
Dec = decvals
org = 180
x = np.remainder(RA + 360 - org, 360) # shift RA values
ind = x > 180
x[ind] -= 360 # scale conversion to [-180, 180]
x = -x # reverse the scale: East to the left
ax.scatter(np.radians(x),
np.radians(Dec),
s=10,
color='r',
zorder=1,
alpha=1.0) # convert degrees to radians
sdb = SurveysDB()
ravals = []
decvals = []
for i in range(0, len(identities)):
obsdict = sdb.get_observation(identities[i])
status = obsdict['status']
if status == 'DI_processed' or status == 'DI_Processed':
fielddict = sdb.get_field(identities_fields[i])
ravals.append(fielddict['ra'])
decvals.append(fielddict['decl'])
progressdict[identities_fields[i]][2] = 'partly processed'
sdb.close()
ravals = np.array(ravals)
decvals = np.array(decvals)
# ingest file from Francesco
from astropy.table import Table
from surveys_db import SurveysDB
t = Table.read('/beegfs/lofar/mjh/lba/allsky-grid.fits')
with SurveysDB(survey='lba') as sdb:
for r in t:
f = sdb.create_field(r['name'])
f['ra'] = r['radeg']
f['decl'] = r['decdeg']
f['gal_l'] = r['GAL_LONG']
f['gal_b'] = r['GAL_LAT']
f['status'] = 'Not started'
f['lotss_field'] = 1
sdb.set_field(f)
if fieldname == 'LoTSS-DR2':
print lotssdr2['Mosaic_ID'][0]
else:
if nodatabase:
print 'Scaling factor being used for field catalogue', fieldfactor
lotssdr2['Peak_flux'] = lotssdr2[
'Peak_flux'] * fieldfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['Total_flux'] = lotssdr2[
'Total_flux'] * fieldfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['E_Peak_flux'] = lotssdr2[
'E_Peak_flux'] * fieldfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['E_Total_flux'] = lotssdr2[
'E_Total_flux'] * fieldfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
else:
from surveys_db import SurveysDB
sdb = SurveysDB()
qualitydict = sdb.get_quality(fieldname)
sdb.close()
nvssfactor = 1.0 / (qualitydict['nvss_scale'] / 5.9124)
tgssscale = qualitydict['tgss_scale']
print 'Scaling comparison catalogue by nvssfactor', nvssfactor
lotssdr2['Peak_flux'] = lotssdr2[
'Peak_flux'] * nvssfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['Total_flux'] = lotssdr2[
'Total_flux'] * nvssfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['E_Peak_flux'] = lotssdr2[
'E_Peak_flux'] * nvssfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
lotssdr2['E_Total_flux'] = lotssdr2[
'E_Total_flux'] * nvssfactor * 1000.0 #1000 scaling is to match mJy which is the units of LoTSS-DR2 cat
#lotssdr2=select_isolated_sources(lotssdr2,45)
#!/usr/bin/python
#insert a field and priority into the list for processing
import sys
from surveys_db import SurveysDB
name=sys.argv[1]
if name[0]=='L':
name=name[1:]
id=int(name)
priority=int(sys.argv[2])
sdb=SurveysDB()
idd=sdb.get_id(id)
if idd is not None:
print 'Field already exists in the database! (Status is %s)' % idd['status']
else:
idd=sdb.create_id(id)
idd['status']='Preprocessed'
idd['priority']=priority
sdb.set_id(idd)
sdb.close()
'List failed': 'black',
'Downloading': 'red',
'Downloaded': 'orange',
'Unpacking': 'orange',
'Unpacked': 'orange',
'Ready': 'yellow',
'Queued': 'blue',
'Running': 'cyan',
'Complete': 'green',
'Archiving': 'green',
'Archived': 'olive',
'Stopped': 'magenta',
'Failed': 'magenta',
'DI_started': 'white'
}
sdb = SurveysDB(readonly=True)
sdb.cur.execute('select * from fields where status!="Not started"')
fields = sdb.cur.fetchall()
sdb.close()
for f in fields:
status = f['status']
shortname = f['id']
job_status = ''
d_colour = 'black'
if status == 'Running' or status == 'Ready' or status == 'Failed':
if len(jobs) > 0:
if shortname not in jobs:
job_status = 'not queued'
d_colour = 'red'
elif jobs[shortname] == 'Q':
def __init__(self,
ListMSName,
ColName="DATA",
ModelName="PREDICT_KMS",
UVRange=[1., 1000.],
SolsName=None,
FileCoords=None,
Radius=3.,
NOff=-1,
Image=None,
SolsDir=None,
NCPU=1):
self.ListMSName = sorted(ListMSName) #[0:2]
self.nMS = len(self.ListMSName)
self.ColName = ColName
self.ModelName = ModelName
self.OutName = self.ListMSName[0].split("/")[-1].split("_")[0]
self.UVRange = UVRange
self.ReadMSInfos()
self.Radius = Radius
self.Image = Image
self.SolsDir = SolsDir
#self.PosArray=np.genfromtxt(FileCoords,dtype=[('Name','S200'),("ra",np.float64),("dec",np.float64),('Type','S200')],delimiter="\t")
# identify version in logs
print >> log, "DynSpecMS version %s starting up" % version()
# should we use the surveys DB?
if 'DDF_PIPELINE_DATABASE' in os.environ:
print >> log, "Using the surveys database"
from surveys_db import SurveysDB
with SurveysDB() as sdb:
sdb.cur.execute('select * from transients')
result = sdb.cur.fetchall()
# convert to a list, then to ndarray, then to recarray
l = []
for r in result:
l.append((r['id'], r['ra'], r['decl'], r['type']))
self.PosArray = np.asarray(l,
dtype=[('Name', 'S200'),
("ra", np.float64),
("dec", np.float64),
('Type', 'S200')])
print >> log, "Created an array with %i records" % len(result)
else:
if FileCoords is None:
FileCoords = "Transient_LOTTS.csv"
if not os.path.isfile(FileCoords):
ssExec = "wget -q --user=anonymous ftp://ftp.strw.leidenuniv.nl/pub/tasse/%s -O %s" % (
FileCoords, FileCoords)
print >> log, "Downloading %s" % FileCoords
print >> log, " Executing: %s" % ssExec
os.system(ssExec)
self.PosArray = np.genfromtxt(FileCoords,
dtype=[('Name', 'S200'),
("ra", np.float64),
("dec", np.float64),
('Type', 'S200')],
delimiter=",")[()]
self.PosArray = self.PosArray.view(np.recarray)
self.PosArray.ra *= np.pi / 180.
self.PosArray.dec *= np.pi / 180.
NOrig = self.PosArray.shape[0]
Dist = AngDist(self.ra0, self.PosArray.ra, self.dec0,
self.PosArray.dec)
ind = np.where(Dist < Radius * np.pi / 180)[0]
self.PosArray = self.PosArray[ind]
self.NDirSelected = self.PosArray.shape[0]
print >> log, "Selected %i target [out of the %i in the original list]" % (
self.NDirSelected, NOrig)
if self.NDirSelected == 0:
print >> log, ModColor.Str(" Have found no sources - returning")
self.killWorkers()
return
if NOff == -1:
NOff = self.PosArray.shape[0] * 2
if NOff is not None:
print >> log, "Including %i off targets" % (NOff)
self.PosArray = np.concatenate(
[self.PosArray, self.GiveOffPosArray(NOff)])
self.PosArray = self.PosArray.view(np.recarray)
self.NDir = self.PosArray.shape[0]
print >> log, "For a total of %i targets" % (self.NDir)
self.DicoDATA = shared_dict.create("DATA")
self.DicoGrids = shared_dict.create("Grids")
self.DicoGrids["GridLinPol"] = np.zeros(
(self.NDir, self.NChan, self.NTimes, 4), np.complex128)
self.DicoGrids["GridWeight"] = np.zeros(
(self.NDir, self.NChan, self.NTimes, 4), np.complex128)
self.SolsName = SolsName
self.DoJonesCorr = False
if self.SolsName:
self.DoJonesCorr = True
self.DicoJones = shared_dict.create("DicoJones")
APP.registerJobHandlers(self)
AsyncProcessPool.init(ncpu=NCPU, affinity=0)
APP.startWorkers()
r_in=[]
r_out=[]
for f in r:
if sf(f):
ra.append(f['ra'])
dec.append(f['decl'])
r_in.append(f)
else:
r_out.append(f)
ra_r,dec_r=cc(ra,dec)
plt.scatter(ra_r,dec_r,label=label,**kwargs)
print "%-20s : %i" % (label,len(r_in))
return r_in,r_out
with SurveysDB(readonly=True) as sdb:
sdb.cur.execute('select fields.id as id,gal_l as ra,gal_b as decl,fields.status as status,observations.status as ostatus,observations.location as location,sum(nsb*integration/232) as s,count(observations.id) as c,fields.priority from fields left join observations on (observations.field=fields.id) group by fields.id having ostatus is not null')
#sdb.cur.execute('select * from fields where status!="Not started"')
results=sdb.cur.fetchall()
print len(results),'fields have some observations'
fig = plt.figure(figsize=(16, 8))
fig.add_subplot(111, projection='aitoff')
# GP
for b in [-10,0,10]:
lon=np.linspace(-180,180,1000)
lat=b*np.ones_like(lon)
#!/usr/bin/env python
#insert a field and priority into the list for processing
from __future__ import print_function
import sys
from surveys_db import SurveysDB
name = sys.argv[1]
if name[0] == 'L':
name = name[1:]
id = int(name)
priority = int(sys.argv[2])
sdb = SurveysDB()
idd = sdb.get_id(id)
if idd is not None:
print('Field already exists in the database! (Status is %s)' %
idd['status'])
else:
idd = sdb.create_id(id)
idd['status'] = 'Preprocessed'
idd['priority'] = priority
sdb.set_id(idd)
sdb.close()
def make_custom_config(name, workdir, do_field, averaged=False):
if do_field:
with SurveysDB() as sdb:
idd = sdb.get_field(name)
if idd['gal_b'] is None:
print('Missing Galactic co-ordinates, adding them')
add_galcoords(sdb, [idd])
idd = sdb.get_field(name)
no_wenss = ((idd['decl'] < 32) | (idd['decl'] > 72))
no_tgss = (idd['no_tgss'] == 1)
if idd['lotss_field'] > 0:
lotss_field = True
do_polcubes = True
do_dynspec = True
do_stokesv = True
do_spectral_restored = True
else:
lotss_field = False
do_polcubes = (idd['do_polcubes'] > 0)
do_dynspec = (idd['do_dynspec'] > 0)
do_stokesv = (idd['do_stokesv'] > 0)
do_spectral_restored = (idd['do_spectral_restored'] > 0)
else:
# assume LOTSS defaults
no_wenss = False
no_tgss = False
lotss_field = True
if np.abs(idd['gal_b']) < 10.0:
template = os.environ[
'DDF_DIR'] + '/ddf-pipeline/examples/tier1-jul2018-MW.cfg'
else:
if no_wenss:
if idd['decl'] < 10.0:
template = os.environ[
'DDF_DIR'] + '/ddf-pipeline/examples/tier1-jul2018-lowdec.cfg'
else:
template = os.environ[
'DDF_DIR'] + '/ddf-pipeline/examples/tier1-jul2018-NVSS.cfg'
else:
template = os.environ[
'DDF_DIR'] + '/ddf-pipeline/examples/tier1-jul2018.cfg'
lines = open(template).readlines()
outfile = open(workdir + '/tier1-config.cfg', 'w')
for l in lines:
if 'colname' in l and averaged:
outfile.write('colname=DATA\n')
elif '[control]' in l and no_tgss:
outfile.write(l + 'redo_DI=True\n')
elif 'do_dynspec' in l and not do_dynspec:
outfile.write('do_dynspec=False\n')
elif 'spectral_restored' in l and not do_spectral_restored:
outfile.write('spectral_restored=False\n')
elif 'polcubes' in l and 'compress' not in l and not do_polcubes:
outfile.write('polcubes=False\n')
elif 'stokesv' in l and not do_stokesv:
outfile.write('stokesv=False\n')
else:
outfile.write(l)
def InitFromCatalog(self):
FileCoords = self.FileCoords
dtype = [('Name', 'S200'), ("ra", np.float64), ("dec", np.float64),
('Type', 'S200')]
# should we use the surveys DB?
if 'DDF_PIPELINE_DATABASE' in os.environ:
print("Using the surveys database", file=log)
from surveys_db import SurveysDB
with SurveysDB() as sdb:
sdb.cur.execute('select * from transients')
result = sdb.cur.fetchall()
# convert to a list, then to ndarray, then to recarray
l = []
for r in result:
l.append((r['id'], r['ra'], r['decl'], r['type']))
if FileCoords is not None:
print('Adding data from file ' + FileCoords, file=log)
additional = np.genfromtxt(FileCoords,
dtype=dtype,
delimiter=",")[()]
if not additional.shape:
# deal with a one-line input file
additional = np.array([additional], dtype=dtype)
for r in additional:
l.append(tuple(r))
self.PosArray = np.asarray(l, dtype=dtype)
print("Created an array with %i records" % len(result), file=log)
else:
#FileCoords="Transient_LOTTS.csv"
if FileCoords is None:
if not os.path.isfile(FileCoords):
ssExec = "wget -q --user=anonymous ftp://ftp.strw.leidenuniv.nl/pub/tasse/%s -O %s" % (
FileCoords, FileCoords)
print("Downloading %s" % FileCoords, file=log)
print(" Executing: %s" % ssExec, file=log)
os.system(ssExec)
log.print("Reading cvs file: %s" % FileCoords)
#self.PosArray=np.genfromtxt(FileCoords,dtype=dtype,delimiter=",")[()]
self.PosArray = np.genfromtxt(FileCoords,
dtype=dtype,
delimiter=",")
self.PosArray = self.PosArray.view(np.recarray)
self.PosArray.ra *= np.pi / 180.
self.PosArray.dec *= np.pi / 180.
Radius = self.Radius
NOrig = self.PosArray.Name.shape[0]
Dist = AngDist(self.ra0, self.PosArray.ra, self.dec0,
self.PosArray.dec)
ind = np.where(Dist < (Radius * np.pi / 180))[0]
self.PosArray = self.PosArray[ind]
self.NDirSelected = self.PosArray.shape[0]
print("Selected %i target [out of the %i in the original list]" %
(self.NDirSelected, NOrig),
file=log)
if self.NDirSelected == 0:
print(ModColor.Str(" Have found no sources - returning"),
file=log)
self.killWorkers()
return
NOff = self.NOff
if NOff == -1:
NOff = self.PosArray.shape[0] * 2
if NOff is not None:
print("Including %i off targets" % (NOff), file=log)
self.PosArray = np.concatenate(
[self.PosArray, self.GiveOffPosArray(NOff)])
self.PosArray = self.PosArray.view(np.recarray)
self.NDir = self.PosArray.shape[0]
print("For a total of %i targets" % (self.NDir), file=log)
self.DicoDATA = shared_dict.create("DATA")
self.DicoGrids = shared_dict.create("Grids")
self.DicoGrids["GridLinPol"] = np.zeros(
(self.NDir, self.NChan, self.NTimes, 4), np.complex128)
self.DicoGrids["GridWeight"] = np.zeros(
(self.NDir, self.NChan, self.NTimes, 4), np.complex128)
self.DoJonesCorr_kMS = False
self.DicoJones = None
if self.SolsName:
self.DoJonesCorr_kMS = True
self.DicoJones_kMS = shared_dict.create("DicoJones_kMS")
self.DoJonesCorr_Beam = False
if self.BeamModel:
self.DoJonesCorr_Beam = True
self.DicoJones_Beam = shared_dict.create("DicoJones_Beam")
APP.registerJobHandlers(self)
AsyncProcessPool.init(ncpu=self.NCPU, affinity=0)
APP.startWorkers()
args = parser.parse_args()
mospointingname = args.mospointingname
pointingdict = read_pointingfile()
print 'Now searching for results directories'
cwd=os.getcwd()
# find what we need to put in the mosaic
mosaicpointings,mosseps = find_pointings_to_mosaic(pointingdict,mospointingname)
maxsep=np.max(mosseps)
# now find whether we have got these pointings somewhere!
mosaicdirs=[]
missingpointing = False
sdb = SurveysDB()
for p in mosaicpointings:
print 'Wanting to put pointing %s in mosaic'%p
currentdict = sdb.get_field(p)
for d in args.directories:
rd=d+'/'+p
print rd
if os.path.isfile(rd+'/image_full_ampphase_di_m.NS_shift.int.facetRestored.fits'):
mosaicdirs.append(rd)
break
else:
print 'Pointing',p,'not found'
missingpointing = True
if not missingpointing and (currentdict['status'] != 'Archived' or currentdict['archive_version'] != 4):
print 'Pointing',p,'not archived with archive_version 4'
def __init__(self):
with SurveysDB(readonly=True) as sdb:
sdb.cur.execute('select * from fields left join quality on fields.id=quality.id order by fields.id')
results=sdb.cur.fetchall()
self.t=table_from_dict_list(results)
self.t['sc']=SkyCoord(self.t['ra'],self.t['decl'],unit=u.deg)
