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()