def setBatches(opsdb, colmap, args):
propids, proptags, sqls, metadata = setSQL(
opsdb, sqlConstraint=args.sqlConstraint, extraMeta=None)
bdict = {}
for tag in ['All', 'WFD']:
fO = batches.fOBatch(colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(fO)
astrometry = batches.astrometryBatch(colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(astrometry)
rapidrevisit = batches.rapidRevisitBatch(
colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(rapidrevisit)
return bdict
def runGlance(dbfile, outDir='Glance', runName='runname', camera='LSST'):
conn = db.Database(dbfile, defaultTable='observations')
colmap = {
'ra': 'RA',
'dec': 'dec',
'mjd': 'mjd',
'exptime': 'exptime',
'visittime': 'exptime',
'alt': 'alt',
'az': 'az',
'filter': 'filter',
'fiveSigmaDepth': 'fivesigmadepth',
'night': 'night',
'slewtime': 'slewtime',
'seeingGeom': 'FWHM_geometric',
'rotSkyPos': 'rotSkyPos',
'raDecDeg': True,
'slewdist': None,
'note': 'note'
}
#del colmap['note']
gb = glanceBatch(colmap=colmap, slicer_camera=camera, runName=runName)
resultsDb = db.ResultsDb(outDir=outDir)
group = metricBundles.MetricBundleGroup(gb,
conn,
outDir=outDir,
resultsDb=resultsDb)
group.runAll()
group.plotAll()
fb = fOBatch(colmap=colmap, runName=runName)
group = metricBundles.MetricBundleGroup(fb,
conn,
outDir=outDir,
resultsDb=resultsDb)
group.runAll()
group.plotAll()
def setBatches(opsdb, colmap, args):
propids, proptags, sqls, metadata = setSQL(opsdb, sqlConstraint=args.sqlConstraint,
extraMeta=None)
bdict = {}
for tag in ['All', 'WFD']:
fO = batches.fOBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(fO)
astrometry = batches.astrometryBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(astrometry)
rapidrevisit = batches.rapidRevisitBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(rapidrevisit)
return bdict
def setBatches(opsdb, colmap, args):
propids, proptags, sqltags = setSQL(opsdb,
sqlConstraint=args.sqlConstraint)
bdict = {}
for md, sql in zip([None, 'WFD'], [None, sqltags['WFD']]):
fO = batches.fOBatch(colmap=colmap,
runName=args.runName,
extraSql=sql,
extraMetadata=md)
bdict.update(fO)
astrometry = batches.astrometryBatch(colmap=colmap,
runName=args.runName,
extraSql=sql,
extraMetadata=md)
bdict.update(astrometry)
rapidrevisit = batches.rapidRevisitBatch(colmap=colmap,
runName=args.runName,
extraSql=sql,
extraMetadata=md)
bdict.update(rapidrevisit)
return bdict
if args.db is None:
if os.path.isfile('trackingDb_sqlite.db'):
os.remove('trackingDb_sqlite.db')
db_files = glob.glob('*.db')
else:
db_files = [args.db]
run_names = [
os.path.basename(name).replace('.db', '') for name in db_files
]
for filename, name in zip(db_files, run_names):
if os.path.isdir(name + '_glance'):
shutil.rmtree(name + '_glance')
opsdb = db.OpsimDatabaseV4(filename)
colmap = batches.ColMapDict()
bdict = {}
bdict.update(batches.glanceBatch(colmap, name))
bdict.update(batches.fOBatch(colmap, name))
resultsDb = db.ResultsDb(outDir=name + '_glance')
group = mb.MetricBundleGroup(bdict,
opsdb,
outDir=name + '_glance',
resultsDb=resultsDb,
saveEarly=False)
group.runAll(clearMemory=True, plotNow=True)
resultsDb.close()
opsdb.close()
db.addRunToDatabase(name + '_glance', 'trackingDb_sqlite.db', None,
name, '', '', name + '.db')
def setBatches(opsdb, colmap, args):
# Set up WFD sql constraint
propids, proptags, sqls, metadata = setSQL(opsdb, sqlConstraint=args.sqlConstraint)
# Set up appropriate metadata - need to combine args.sqlConstraint
# Some of these metrics are reproduced in other scripts - srd and cadence
bdict = {}
plotbundles = []
for tag in ['All', 'WFD']:
fO = batches.fOBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(fO)
astrometry = batches.astrometryBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(astrometry)
rapidrevisit = batches.rapidRevisitBatch(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(rapidrevisit)
# Intranight (pairs/time)
intranight_all, plots = batches.intraNight(colmap, args.runName, extraSql=args.sqlConstraint,
ditherStacker=args.ditherStacker)
bdict.update(intranight_all)
plotbundles.append(plots)
sql = '(%s) or (%s)' % (sqls['WFD'], sqls['NES'])
md = 'WFD+' + metadata['NES']
intranight_wfdnes, plots = batches.intraNight(colmap, args.runName, extraSql=sql,
extraMetadata=md, ditherStacker=args.ditherStacker)
bdict.update(intranight_wfdnes)
plotbundles.append(plots)
# Internight (nights between visits)
for tag in ['All', 'WFD']:
internight, plots = batches.interNight(colmap, args.runName, extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(internight)
plotbundles.append(plots)
# Intraseason (length of season)
for tag in ['All', 'WFD']:
season, plots = batches.seasons(colmap=colmap, runName=args.runName,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(season)
plotbundles.append(plots)
# Run all metadata metrics, All and just WFD.
for tag in ['All', 'WFD']:
bdict.update(batches.allMetadata(colmap, args.runName, extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
# Nvisits + m5 maps + Teff maps, All and just WFD.
for tag in ['All', 'WFD']:
bdict.update(batches.nvisitsM5Maps(colmap, args.runName, runLength=args.nyears,
extraSql=sqls[tag], extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
bdict.update(batches.tEffMetrics(colmap, args.runName, extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
# Nvisits per proposal and per night.
bdict.update(batches.nvisitsPerProp(opsdb, colmap, args.runName,
extraSql=args.sqlConstraint))
# NVisits alt/az LambertSkyMap (all filters, per filter)
bdict.update(batches.altazLambert(colmap, args.runName, extraSql=args.sqlConstraint))
# Slew metrics.
bdict.update(batches.slewBasics(colmap, args.runName, sqlConstraint=args.sqlConstraint))
# Open shutter metrics.
bdict.update(batches.openshutterFractions(colmap, args.runName, extraSql=args.sqlConstraint))
# Per night and whole survey filter changes.
bdict.update(batches.filtersPerNight(colmap, args.runName, nights=1, extraSql=args.sqlConstraint))
bdict.update(batches.filtersWholeSurvey(colmap, args.runName, extraSql=args.sqlConstraint))
# Hourglass plots.
bdict.update(batches.hourglassPlots(colmap, args.runName,
nyears=args.nyears, extraSql=args.sqlConstraint))
return bdict
def setBatches(opsdb, colmap, args):
bdict = {}
bdict.update(batches.glanceBatch(colmap, args.runName, sqlConstraint=args.sqlConstraint))
bdict.update(batches.fOBatch(colmap, args.runName, extraSql=args.sqlConstraint))
return bdict
def setBatches(opsdb, colmap, args):
# Set up WFD sql constraint, if possible.
propids, proptags, sqls, metadata = setSQL(
opsdb, sqlConstraint=args.sqlConstraint)
if 'WFD' in sqls:
tags = ['All', 'WFD']
else:
tags = ['All']
# Set up appropriate metadata - need to combine args.sqlConstraint
# Some of these metrics are reproduced in other scripts - srd and cadence
bdict = {}
plotbundles = []
for tag in tags:
fO = batches.fOBatch(colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(fO)
astrometry = batches.astrometryBatch(colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(astrometry)
rapidrevisit = batches.rapidRevisitBatch(
colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(rapidrevisit)
# Intranight (pairs/time)
intranight_all, plots = batches.intraNight(
colmap,
args.runName,
extraSql=args.sqlConstraint,
ditherStacker=args.ditherStacker)
bdict.update(intranight_all)
plotbundles.append(plots)
if ('WFD' in sqls) and ('NES' in sqls):
sql = '(%s) or (%s)' % (sqls['WFD'], sqls['NES'])
md = 'WFD+' + metadata['NES']
intranight_wfdnes, plots = batches.intraNight(
colmap,
args.runName,
extraSql=sql,
extraMetadata=md,
ditherStacker=args.ditherStacker)
bdict.update(intranight_wfdnes)
plotbundles.append(plots)
# Internight (nights between visits)
for tag in tags:
internight, plots = batches.interNight(
colmap,
args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(internight)
plotbundles.append(plots)
# Intraseason (length of season)
for tag in tags:
season, plots = batches.seasons(colmap=colmap,
runName=args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker)
bdict.update(season)
plotbundles.append(plots)
# Run all metadata metrics, All and just WFD.
for tag in tags:
bdict.update(
batches.allMetadata(colmap,
args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
# Nvisits + m5 maps + Teff maps, All and just WFD.
for tag in tags:
bdict.update(
batches.nvisitsM5Maps(colmap,
args.runName,
runLength=args.nyears,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
bdict.update(
batches.tEffMetrics(colmap,
args.runName,
extraSql=sqls[tag],
extraMetadata=metadata[tag],
ditherStacker=args.ditherStacker))
# Nvisits per proposal and per night.
bdict.update(
batches.nvisitsPerProp(opsdb,
colmap,
args.runName,
extraSql=args.sqlConstraint))
# NVisits alt/az LambertSkyMap (all filters, per filter)
bdict.update(
batches.altazLambert(colmap, args.runName,
extraSql=args.sqlConstraint))
# Slew metrics.
bdict.update(
batches.slewBasics(colmap,
args.runName,
sqlConstraint=args.sqlConstraint))
# Open shutter metrics.
bdict.update(
batches.openshutterFractions(colmap,
args.runName,
extraSql=args.sqlConstraint))
# Per night and whole survey filter changes.
bdict.update(
batches.filtersPerNight(colmap,
args.runName,
nights=1,
extraSql=args.sqlConstraint))
bdict.update(
batches.filtersWholeSurvey(colmap,
args.runName,
extraSql=args.sqlConstraint))
# Hourglass plots.
bdict.update(
batches.hourglassPlots(colmap,
args.runName,
nyears=args.nyears,
extraSql=args.sqlConstraint))
return bdict