from lsst.sims.catalogs.measures.instance import InstanceCatalog
galDB = CatalogDBObject.from_objid('galaxyTiled')
# Create a child of the InstanceCatalog Class
class galCopy(InstanceCatalog):
column_outputs = ['id', 'raJ2000', 'decJ2000', 'redshift']
override_formats = {'raJ2000': '%8e', 'decJ2000': '%8e'}
# Sizes to be used for querying
boundLens = np.arange(0.02, 0.1, 0.02)
# Instantiate a benchmark object
opsimDBHDF ='/Users/rbiswas/data/LSST/OpSimData/storage.h5'
gcb = QueryBenchMarks.fromOpSimDF(instanceCatChild=galCopy, dbObject=galDB,
opSimHDF=opsimDBHDF, boundLens=boundLens,
numSamps=1, name='new_test')
# Look at the size
print gcb.coords.size
print gcb.boundLens.size
# Now run results
gcb.aggregateResults()
# Obtain plots
fig = gcb.plots
gcb2 = QueryBenchMarks.fromOpSimDF(instanceCatChild=galCopy, dbObject=galDB,
opSimHDF=opsimDBHDF, boundLens=boundLens,
constraints='r_ab < 20',
numSamps=1, name='new_test')
gcb2.aggregateResults()
from benchmarkInstanceCatalogs import QueryBenchMarks
from lsst.sims.catalogs.generation.db import CatalogDBObject
import lsst.sims.catUtils.baseCatalogModels as bcm
from lsst.sims.catalogs.measures.instance import InstanceCatalog
galDB = CatalogDBObject.from_objid('galaxyTiled')
# Create a child of the InstanceCatalog Class
class galCopy(InstanceCatalog):
column_outputs = ['id', 'raJ2000', 'decJ2000', 'redshift']
override_formats = {'raJ2000': '%8e', 'decJ2000': '%8e'}
# Sizes to be used for querying
boundLens = np.arange(0.05, 1.8, 0.05)
# Instantiate a benchmark object
opsimDBHDF ='/astro/users/rbiswas/data/LSST/OpSimData/storage.h5'
gcb = QueryBenchMarks.fromOpSimDF(instanceCatChild=galCopy, dbObject=galDB,
opSimHDF=opsimDBHDF, boundLens=boundLens,
constraints='r_ab < 24.0',
numSamps=3, name='magneto_test_rless24')
# Look at the size
print gcb.coords.size
print gcb.boundLens.size
# Now run results
gcb.aggregateResults()
fig = gcb.plots
fig.savefig('magneto_test_rless24.pdf')
from benchmarkInstanceCatalogs import QueryBenchMarks
from lsst.sims.catalogs.generation.db import CatalogDBObject
import lsst.sims.catUtils.baseCatalogModels as bcm
from lsst.sims.catalogs.measures.instance import InstanceCatalog
galDB = CatalogDBObject.from_objid('galaxyTiled')
# Create a child of the InstanceCatalog Class
class galCopy(InstanceCatalog):
column_outputs = ['id', 'raJ2000', 'decJ2000', 'redshift']
override_formats = {'raJ2000': '%8e', 'decJ2000': '%8e'}
# Sizes to be used for querying
boundLens = np.arange(0.02, 0.1, 0.02)
# Instantiate a benchmark object
opsimDBHDF ='/Users/rbiswas/data/LSST/OpSimData/storage.h5'
gcb = QueryBenchMarks.fromOpSimDF(instanceCatChild=galCopy, dbObject=galDB,
opSimHDF=opsimDBHDF, boundLens=boundLens,
numSamps=3, name='small_test_run')
# Look at the size
print gcb.coords.size
print gcb.boundLens.size
# Now run results
gcb.aggregateResults()
# Obtain plots
fig = gcb.plots
# fig.savefig('catsim_new.pdf')
