def connectDb(dbfile):
version = db.testOpsimVersion(dbfile)
if version == "Unknown":
opsdb = db.Database(dbfile)
colmap = batches.ColMapDict('barebones')
elif version == "V3":
opsdb = db.OpsimDatabaseV3(dbfile)
colmap = batches.ColMapDict('OpsimV3')
elif version == "V4":
opsdb = db.OpsimDatabaseV4(dbfile)
colmap = batches.ColMapDict('OpsimV4')
return opsdb, colmap
def testColMap(self):
colmap = batches.ColMapDict('opsimv4')
self.assertEqual(colmap['raDecDeg'], True)
self.assertEqual(colmap['ra'], 'fieldRA')
opsdb = OpsTestDb()
colmap = batches.getColMap(opsdb)
self.assertEqual(colmap['raDecDeg'], True)
self.assertEqual(colmap['ra'], 'fieldRA')
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')
import lsst.sims.maf.db as db
import lsst.sims.maf.metricBundles as mb
if __name__ == "__main__":
"""
Run the glance batch on all .db files in a directory.
"""
db_files = glob.glob('*.db')
run_names = [name.replace('.db', '') for name in db_files]
if os.path.isfile('trackingDb_sqlite.db'):
os.remove('trackingDb_sqlite.db')
for name in run_names:
if os.path.isdir(name):
shutil.rmtree(name)
opsdb = db.OpsimDatabaseV4(name + '.db')
colmap = batches.ColMapDict('OpsimV4')
bdict = {}
bdict.update(batches.glanceBatch(colmap, name, slicer_camera='ComCam'))
bdict.update(batches.fOBatch(colmap, name))
resultsDb = db.ResultsDb(outDir=name)
group = mb.MetricBundleGroup(bdict,
opsdb,
outDir=name,
resultsDb=resultsDb)
group.runAll()
group.plotAll()
resultsDb.close()
opsdb.close()
db.addRunToDatabase(name, 'trackingDb_sqlite.db', None, name, '', '',
name + '.db')
slicer,
sqls[f],
metadata=metadata[f],
displayDict=displayDict,
plotFuncs=subsetPlots,
plotDict=plotDict,
summaryMetrics=standardStats)
bundleList.append(bundle)
# Set the runName for all bundles and return the bundleDict.
for b in bundleList:
b.setRunName(runName)
return mb.makeBundlesDictFromList(bundleList)
colmap = batches.ColMapDict('barebones')
colmap['ra'] = 'RA'
colmap['seeingEff'] = 'FWHMeff'
colmap['seeingGeom'] = 'FWHM_geometric'
colmap['note'] = 'note'
bd = batches.glanceBatch(colmap=colmap)
cadence_batch = interNight(colmap=colmap)
def run_glance(outDir, dbname):
conn = db.Database(dbname, defaultTable='observations')
resultsDb = db.ResultsDb(outDir=outDir)
mbg = MetricBundleGroup(bd, conn, outDir=outDir, resultsDb=resultsDb)
mbg.runAll()