def testOpSimFieldStacker(self):
"""
Test the OpSimFieldStacker
"""
rng = np.random.RandomState(812351)
s = stackers.OpSimFieldStacker(raCol='ra', decCol='dec', degrees=False)
# First sanity check. Make sure the center of the fields returns the right field id
opsim_fields_db = FieldsDatabase()
# Returned RA/Dec coordinates in degrees
field_id, ra, dec = opsim_fields_db.get_id_ra_dec_arrays(
"select * from Field;")
data = np.array(list(zip(np.radians(ra), np.radians(dec))),
dtype=list(zip(['ra', 'dec'], [float, float])))
new_data = s.run(data)
np.testing.assert_array_equal(field_id, new_data['opsimFieldId'])
# Cherry picked a set of coordinates that should belong to a certain list of fields.
# These coordinates are not exactly at the center of fields, but close enough that
# they should be classified as belonging to them.
ra_inside_2548 = (10. + 1. / 60 +
6.59 / 60. / 60.) * np.pi / 12. # 10:01:06.59
dec_inside_2548 = np.radians(
-1. * (2. + 8. / 60. + 27.6 / 60. / 60.)) # -02:08:27.6
ra_inside_8 = (8. + 49. / 60 +
19.83 / 60. / 60.) * np.pi / 12. # 08:49:19.83
dec_inside_8 = np.radians(
-1. * (85. + 19. / 60. + 04.7 / 60. / 60.)) # -85:19:04.7
ra_inside_1253 = (9. + 16. / 60 +
13.67 / 60. / 60.) * np.pi / 12. # 09:16:13.67
dec_inside_1253 = np.radians(
-1. * (30. + 23. / 60. + 41.4 / 60. / 60.)) # -30:23:41.4
data = np.zeros(3, dtype=list(zip(['ra', 'dec'], [float, float])))
field_id = np.array([2548, 8, 1253], dtype=int)
data['ra'] = np.array([ra_inside_2548, ra_inside_8, ra_inside_1253])
data['dec'] = np.array(
[dec_inside_2548, dec_inside_8, dec_inside_1253])
new_data = s.run(data)
np.testing.assert_array_equal(field_id, new_data['opsimFieldId'])
# Now let's generate a set of random coordinates and make sure they are all assigned a fieldID.
data = np.array(list(
zip(
rng.rand(600) * 2. * np.pi,
rng.rand(600) * np.pi - np.pi / 2.)),
dtype=list(zip(['ra', 'dec'], [float, float])))
new_data = s.run(data)
self.assertGreater(new_data['opsimFieldId'].max(), 0)
def __init__(self, raCol='fieldRA', decCol='fieldDec', degrees=True):
self.colsReq = [raCol, decCol]
self.units = ['#']
self.raCol = raCol
self.decCol = decCol
self.degrees = degrees
fields_db = FieldsDatabase()
# Returned RA/Dec coordinates in degrees
fieldid, ra, dec = fields_db.get_id_ra_dec_arrays("select * from Field;")
asort = np.argsort(fieldid)
self.tree = _buildTree(np.radians(ra[asort]),
np.radians(dec[asort]))
def testOpSimFieldStacker(self):
"""
Test the OpSimFieldStacker
"""
rng = np.random.RandomState(812351)
s = stackers.OpSimFieldStacker(raCol='ra', decCol='dec', degrees=False)
# First sanity check. Make sure the center of the fields returns the right field id
opsim_fields_db = FieldsDatabase()
# Returned RA/Dec coordinates in degrees
field_id, ra, dec = opsim_fields_db.get_id_ra_dec_arrays("select * from Field;")
data = np.array(list(zip(np.radians(ra),
np.radians(dec))),
dtype=list(zip(['ra', 'dec'], [float, float])))
new_data = s.run(data)
np.testing.assert_array_equal(field_id, new_data['opsimFieldId'])
# Cherry picked a set of coordinates that should belong to a certain list of fields.
# These coordinates are not exactly at the center of fields, but close enough that
# they should be classified as belonging to them.
ra_inside_2548 = (10. + 1. / 60 + 6.59 / 60. / 60.) * np.pi / 12. # 10:01:06.59
dec_inside_2548 = np.radians(-1. * (2. + 8. / 60. + 27.6 / 60. / 60.)) # -02:08:27.6
ra_inside_8 = (8. + 49. / 60 + 19.83 / 60. / 60.) * np.pi / 12. # 08:49:19.83
dec_inside_8 = np.radians(-1. * (85. + 19. / 60. + 04.7 / 60. / 60.)) # -85:19:04.7
ra_inside_1253 = (9. + 16. / 60 + 13.67 / 60. / 60.) * np.pi / 12. # 09:16:13.67
dec_inside_1253 = np.radians(-1. * (30. + 23. / 60. + 41.4 / 60. / 60.)) # -30:23:41.4
data = np.zeros(3, dtype=list(zip(['ra', 'dec'], [float, float])))
field_id = np.array([2548, 8, 1253], dtype=int)
data['ra'] = np.array([ra_inside_2548, ra_inside_8, ra_inside_1253])
data['dec'] = np.array([dec_inside_2548, dec_inside_8, dec_inside_1253])
new_data = s.run(data)
np.testing.assert_array_equal(field_id, new_data['opsimFieldId'])
# Now let's generate a set of random coordinates and make sure they are all assigned a fieldID.
data = np.array(list(zip(rng.rand(600) * 2. * np.pi,
rng.rand(600) * np.pi - np.pi / 2.)),
dtype=list(zip(['ra', 'dec'], [float, float])))
new_data = s.run(data)
self.assertGreater(new_data['opsimFieldId'].max(), 0)
def test_proposal_fields(self):
fd = FieldsDatabase()
fs = FieldSelection()
gen = BasicProposal1()
ids = gen.proposal_fields(fd, fs)
self.assertEqual(len(ids), 139)
gen = BasicProposal4()
ids = gen.proposal_fields(fd, fs)
self.assertEqual(len(ids), 2285)
gen = BasicProposal7()
ids = gen.proposal_fields(fd, fs)
self.assertEqual(len(ids), 239)
def read_fields():
"""
Read in the Field coordinates
Returns
-------
numpy.array
With RA and dec in radians.
"""
query = 'select fieldId, fieldRA, fieldDEC from Field;'
fd = FieldsDatabase()
fields = np.array(list(fd.get_field_set(query)))
# order by field ID
fields = fields[fields[:,0].argsort()]
names = ['RA', 'dec']
types = [float, float]
result = np.zeros(np.size(fields[:, 1]), dtype=list(zip(names, types)))
result['RA'] = np.radians(fields[:, 1])
result['dec'] = np.radians(fields[:, 2])
return result
def __init__(self, options, configuration, database):
"""Initialize the class.
Parameters
----------
options : argparse.Namespace
The instance returned by ArgumentParser containing the command-line options.
configuration : :class:`.SimulationConfig`
The simulation configuration instance.
database : :class:`.SocsDatabase`
The simulation database instance.
"""
self.opts = options
self.conf = configuration
self.db = database
if self.opts.frac_duration == -1:
self.fractional_duration = self.conf.survey.duration
else:
self.fractional_duration = self.opts.frac_duration
self.conf.survey.duration = self.opts.frac_duration
self.time_handler = TimeHandler(self.conf.survey.start_date)
self.log = logging.getLogger("kernel.Simulator")
self.sal = SalManager()
self.seq = Sequencer(self.conf.observing_site,
self.conf.survey.idle_delay)
self.dh = DowntimeHandler()
self.conf_comm = ConfigurationCommunicator()
self.sun = Sun()
self.cloud_model = CloudModel(self.time_handler)
self.seeing_model = SeeingModel(self.time_handler)
self.field_database = FieldsDatabase()
self.field_selection = FieldSelection()
self.obs_site_info = (self.conf.observing_site.longitude,
self.conf.observing_site.latitude)
self.wait_for_scheduler = not self.opts.no_scheduler
self.observation_proposals_counted = 1
self.target_proposals_counted = 1
self.socs_timeout = 180.0 # seconds
if self.opts.scheduler_timeout > self.socs_timeout:
self.socs_timeout = self.opts.scheduler_timeout
class TestFieldDatabase(unittest.TestCase):
def setUp(self):
self.fields_db = FieldsDatabase()
self.query = "select * from Field limit 2;"
def test_basic_information_after_creation(self):
self.assertEqual(self.fields_db.db_name, "Fields.db")
self.assertIsNotNone(self.fields_db.connect)
def test_opsim3_userregions(self):
result = self.fields_db.get_opsim3_userregions(self.query)
truth_result = """userRegion = 0.00,-90.00,0.03
userRegion = 180.00,-87.57,0.03"""
self.assertEqual(result, truth_result)
def test_get_ra_dec_arrays(self):
ra, dec = self.fields_db.get_ra_dec_arrays(self.query)
self.assertEqual(ra.size, 2)
self.assertEqual(dec.size, 2)
self.assertEqual(ra[1], 180.0)
self.assertAlmostEqual(dec[1], -87.57, delta=1e-2)
def test_get_rows(self):
rows = self.fields_db.get_rows(self.query)
self.assertIsInstance(rows, list)
self.assertEqual(len(rows), 2)
self.assertEqual(len(rows[0]), 8)
def test_get_field_set(self):
field_set = self.fields_db.get_field_set(self.query)
truth_set = set()
truth_set.add((1, 3.5, 0.0, -90.0, -57.068082, -27.128251, -89.93121,
-66.561358))
truth_set.add((2, 3.5, 180.0, -87.568555, -57.663825, -24.756541,
-96.024547, -66.442665))
self.assertEqual(len(field_set), 2)
self.assertSetEqual(field_set, truth_set)
def test_proposal_fields(self):
fd = FieldsDatabase()
fs = FieldSelection()
ids = self.prop.proposal_fields(fd, fs)
self.assertEqual(len(ids), 233)
class Simulator(object):
"""Main class for the survey simulation.
This class is responsible for setting up, running and shutting down the LSST survey simulation.
Attributes
----------
opts : argparse.Namespace
The options returned by the ArgumentParser instance.
conf : :class:`.SimulationConfig`
The simulation configuration instance.
db : :class:`.SocsDatabase`
The simulation database instance.
fractional_duration : float
The length in years for the simulated survey.
time_handler : :class:`.TimeHandler`
The simulation time handling instance.
log : logging.Logger
The logging instance.
sal : :class:`.SalManager`
The instance that manages interactions with the SAL.
seq : :class:`.Sequencer`
The sequencer instance.
dh : :class:`.DowntimeHandler`
The downtime handler instance.
conf_comm : :class:`.ConfigurationCommunicator`
The configuration communicator instance.
cloud_model : :class:`.CloudModel`
The cloud model instance.
seeing_model : :class:`.SeeingModel`
The seeing model instance.
field_database : lsst.sims.survey.fields.FieldsDatabase
The instance of the fields database.
field_selection : lsst.sims.survey.fields.FieldSelection
The instance of the field selector.
"""
def __init__(self, options, configuration, database):
"""Initialize the class.
Parameters
----------
options : argparse.Namespace
The instance returned by ArgumentParser containing the command-line options.
configuration : :class:`.SimulationConfig`
The simulation configuration instance.
database : :class:`.SocsDatabase`
The simulation database instance.
"""
self.opts = options
self.conf = configuration
self.db = database
if self.opts.frac_duration == -1:
self.fractional_duration = self.conf.survey.duration
else:
self.fractional_duration = self.opts.frac_duration
self.conf.survey.duration = self.opts.frac_duration
self.time_handler = TimeHandler(self.conf.survey.start_date)
self.log = logging.getLogger("kernel.Simulator")
self.sal = SalManager()
self.seq = Sequencer(self.conf.observing_site,
self.conf.survey.idle_delay)
self.dh = DowntimeHandler()
self.conf_comm = ConfigurationCommunicator()
self.sun = Sun()
self.cloud_model = CloudModel(self.time_handler)
self.seeing_model = SeeingModel(self.time_handler)
self.field_database = FieldsDatabase()
self.field_selection = FieldSelection()
self.obs_site_info = (self.conf.observing_site.longitude,
self.conf.observing_site.latitude)
self.wait_for_scheduler = not self.opts.no_scheduler
self.observation_proposals_counted = 1
self.target_proposals_counted = 1
self.socs_timeout = 180.0 # seconds
if self.opts.scheduler_timeout > self.socs_timeout:
self.socs_timeout = self.opts.scheduler_timeout
@property
def duration(self):
"""int: The duration of the simulation in days.
"""
return round(self.fractional_duration * DAYS_IN_YEAR)
def end_night(self):
"""Perform actions at the end of the night.
"""
self.db.write()
self.seq.end_night()
def finalize(self):
"""Perform finalization steps.
This function handles finalization of the :class:`.SalManager` and :class:`.Sequencer` instances.
"""
self.seq.finalize()
self.sal.finalize()
self.log.info("Ending simulation")
def gather_proposal_history(self, phtype, topic):
"""Gather the proposal history from the current target.
Parameters
----------
phtype : str
The type of the proposal history (target or observation).
topic : :class:`scheduler_targetC` or :class:`scheduler_interestedProposalC`
The topic instance to gather the observation proposal information from.
"""
if phtype == "observation":
for i in range(topic.num_proposals):
self.db.append_data(
"observation_proposal_history",
ObsProposalHistory(
self.observation_proposals_counted,
topic.proposal_Ids[i], topic.proposal_values[i],
topic.proposal_needs[i], topic.proposal_bonuses[i],
topic.proposal_boosts[i], topic.observationId))
self.observation_proposals_counted += 1
if phtype == "target":
for i in range(topic.num_proposals):
self.db.append_data(
"target_proposal_history",
TargetProposalHistory(
self.target_proposals_counted, topic.proposal_Ids[i],
topic.proposal_values[i], topic.proposal_needs[i],
topic.proposal_bonuses[i], topic.proposal_boosts[i],
topic.targetId))
self.target_proposals_counted += 1
def get_target_from_scheduler(self):
"""Get target from scheduler.
This function provides the mechanism for getting the target from the
Scheduler. Currently, a while loop is required to do this.
"""
lasttime = time.time()
while self.wait_for_scheduler:
rcode = self.sal.manager.getNextSample_target(self.target)
if rcode == 0 and self.target.num_exposures != 0:
break
else:
tf = time.time()
if (tf - lasttime) > self.socs_timeout:
raise SchedulerTimeoutError(
"The Scheduler is not serving targets!")
def initialize(self):
"""Perform initialization steps.
This function handles initialization of the :class:`.SalManager` and :class:`.Sequencer` instances and
gathering the necessary telemetry topics.
"""
self.log.info("Initializing simulation")
self.log.info("Simulation Session Id = {}".format(self.db.session_id))
self.sal.initialize()
self.seq.initialize(self.sal, self.conf.observatory)
self.dh.initialize(self.conf.downtime)
self.dh.write_downtime_to_db(self.db)
self.cloud_model.initialize(self.conf.environment.cloud_db)
self.seeing_model.initialize(self.conf.environment,
self.conf.observatory.filters)
self.conf_comm.initialize(self.sal, self.conf)
self.comm_time = self.sal.set_publish_topic("timeHandler")
self.target = self.sal.set_subscribe_topic("target")
self.cloud = self.sal.set_publish_topic("cloud")
self.seeing = self.sal.set_publish_topic("seeing")
self.filter_swap = self.sal.set_subscribe_topic("filterSwap")
self.interested_proposal = self.sal.set_subscribe_topic(
"interestedProposal")
self.log.info("Finishing simulation initialization")
def run(self):
"""Run the simulation.
"""
self.log.info("Starting simulation")
self.conf_comm.run()
self.save_configuration()
self.save_proposal_information()
self.save_field_information()
self.log.debug("Duration = {}".format(self.duration))
for night in range(1, int(self.duration) + 1):
self.start_night(night)
while self.time_handler.current_timestamp < self.end_of_night:
self.comm_time.timestamp = self.time_handler.current_timestamp
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Timestamp sent: {:.6f}".format(
self.time_handler.current_timestamp))
self.sal.put(self.comm_time)
observatory_state = self.seq.get_observatory_state(
self.time_handler.current_timestamp)
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Observatory State: {}".format(
topic_strdict(observatory_state)))
self.sal.put(observatory_state)
self.cloud_model.set_topic(self.time_handler, self.cloud)
self.sal.put(self.cloud)
self.seeing_model.set_topic(self.time_handler, self.seeing)
self.sal.put(self.seeing)
self.get_target_from_scheduler()
observation, slew_info, exposure_info = self.seq.observe_target(
self.target, self.time_handler)
# Add a few more things to the observation
observation.night = night
elapsed_time = self.time_handler.time_since_given(
observation.observation_start_time)
observation.cloud = self.cloud_model.get_cloud(elapsed_time)
seeing_values = self.seeing_model.calculate_seeing(
elapsed_time, observation.filter, observation.airmass)
observation.seeing_fwhm_500 = seeing_values[0]
observation.seeing_fwhm_geom = seeing_values[1]
observation.seeing_fwhm_eff = seeing_values[2]
visit_exposure_time = sum([
observation.exposure_times[i]
for i in range(observation.num_exposures)
])
observation.five_sigma_depth = m5_flat_sed(
observation.filter, observation.sky_brightness,
observation.seeing_fwhm_eff, visit_exposure_time,
observation.airmass)
# Pass observation back to scheduler
self.log.log(LoggingLevel.EXTENSIVE.value, "tx: observation")
self.sal.put(observation)
# Wait for interested proposal information
lastconfigtime = time.time()
while self.wait_for_scheduler:
rcode = self.sal.manager.getNextSample_interestedProposal(
self.interested_proposal)
if rcode == 0 and self.interested_proposal.num_proposals >= 0:
self.log.log(LoggingLevel.EXTENSIVE.value,
"Received interested proposal.")
break
else:
tf = time.time()
if (tf - lastconfigtime) > 5.0:
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Failed to receive interested proposal due to timeout."
)
break
if self.wait_for_scheduler and observation.targetId != -1:
self.db.append_data("target_history", self.target)
self.db.append_data("observation_history", observation)
self.gather_proposal_history("target", self.target)
self.gather_proposal_history("observation",
self.interested_proposal)
for slew_type, slew_data in slew_info.items():
self.log.log(
LoggingLevel.TRACE.value,
"{}, {}".format(slew_type, type(slew_data)))
if isinstance(slew_data, list):
for data in slew_data:
self.db.append_data(slew_type, data)
else:
self.db.append_data(slew_type, slew_data)
for exposure_type in exposure_info:
self.log.log(LoggingLevel.TRACE.value,
"Adding {} to DB".format(exposure_type))
self.log.log(
LoggingLevel.TRACE.value,
"Number of exposures being added: "
"{}".format(len(exposure_info[exposure_type])))
for exposure in exposure_info[exposure_type]:
self.db.append_data(exposure_type, exposure)
self.end_night()
self.start_day()
def save_configuration(self):
"""Save the configuration information to the DB.
"""
c = self.conf.config_list()
c.extend(self.seq.sky_brightness_config())
c.append(("scheduler/version", self.opts.scheduler_version))
c.append(("dateloc/version", dateloc_version.__version__))
c.append(("astrosky_model/version", astrosky_version.__version__))
c.append(("observatory_model/version", obs_mod_version.__version__))
config_list = [
write_config((i + 1, x[0], x[1]), self.db.session_id)
for i, x in enumerate(c)
]
self.db.write_table("config", config_list)
def save_field_information(self):
"""Save the field information to the DB.
"""
query = self.field_selection.get_all_fields()
fields = self.field_database.get_field_set(query)
field_list = [
write_field(field, self.db.session_id) for field in sorted(fields)
]
self.db.write_table("field", field_list)
def save_proposal_information(self):
"""Save the active proposal information to the DB.
"""
proposals = []
num_proposals = 1
proposal_fields = {}
if self.conf.science.general_props.active is not None:
for general_config in self.conf.science.general_props.active:
proposals.append(
write_proposal(
ProposalInfo(num_proposals, general_config.name,
"General"), self.db.session_id))
proposal_fields[
num_proposals] = general_config.proposal_fields(
self.field_database, self.field_selection)
num_proposals += 1
if self.conf.science.sequence_props.active is not None:
for sequence_config in self.conf.science.sequence_props.active:
proposals.append(
write_proposal(
ProposalInfo(num_proposals, sequence_config.name,
"Sequence"), self.db.session_id))
proposal_fields[
num_proposals] = sequence_config.proposal_fields()
num_proposals += 1
self.db.write_table("proposal", proposals)
self.write_proposal_fields(proposal_fields)
def start_day(self):
"""Perform actions at the start of day.
This function performs all actions at the start of day. This involves:
* Sending a timestamp to the Scheduler
* Checking if the Scheduler requests a filter swap
* Peforming the filter swap if requested
"""
self.comm_time.timestamp = self.time_handler.current_timestamp
self.log.debug("Start of day {} at {}".format(
self.comm_time.night, self.time_handler.current_timestring))
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Daytime Timestamp sent: {:.6f}".format(
self.time_handler.current_timestamp))
self.sal.put(self.comm_time)
self.filter_swap = self.sal.get_topic("filterSwap")
lastconfigtime = time.time()
while self.wait_for_scheduler:
rcode = self.sal.manager.getNextSample_filterSwap(self.filter_swap)
if rcode == 0 and self.filter_swap.filter_to_unmount != '':
break
else:
tf = time.time()
if (tf - lastconfigtime) > 5.0:
break
self.seq.start_day(self.filter_swap)
def start_night(self, night):
"""Perform actions at the start of the night.
Parameters
----------
night : int
The current night.
"""
self.log.info("Night {}".format(night))
self.seq.start_night(night, self.duration)
self.comm_time.night = night
self.seq.sky_model.update(self.time_handler.current_timestamp)
(set_timestamp,
rise_timestamp) = self.seq.sky_model.get_night_boundaries(
self.conf.sched_driver.night_boundary)
delta = math.fabs(self.time_handler.current_timestamp - set_timestamp)
self.time_handler.update_time(delta, "seconds")
self.log.debug("Start of night {} at {}".format(
night, self.time_handler.current_timestring))
self.end_of_night = rise_timestamp
end_of_night_str = self.time_handler.future_timestring(
0, "seconds", timestamp=self.end_of_night)
self.log.debug("End of night {} at {}".format(night, end_of_night_str))
self.db.clear_data()
down_days = self.dh.get_downtime(night)
if down_days:
self.log.info("Observatory is down: {} days.".format(down_days))
self.comm_time.is_down = True
self.comm_time.down_duration = down_days
self.comm_time.timestamp = self.time_handler.current_timestamp
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Downtime Start Night Timestamp sent: {:.6f}".format(
self.time_handler.current_timestamp))
self.sal.put(self.comm_time)
observatory_state = self.seq.get_observatory_state(
self.time_handler.current_timestamp)
self.log.log(
LoggingLevel.EXTENSIVE.value,
"Downtime Observatory State: {}".format(
topic_strdict(observatory_state)))
self.sal.put(observatory_state)
delta = math.fabs(self.time_handler.current_timestamp -
self.end_of_night) + SECONDS_IN_MINUTE
self.time_handler.update_time(delta, "seconds")
else:
self.comm_time.is_down = False
self.comm_time.down_duration = down_days
def write_proposal_fields(self, prop_fields):
"""Transform the proposal field information and write to the survey database.
Parameters
----------
prop_fields : dict
The set of proposal fields information.
"""
num_proposal_fields = 1
data = []
for prop_id, field_ids in prop_fields.items():
for field_id in field_ids:
data.append(
write_proposal_field(
ProposalFieldInfo(num_proposal_fields, prop_id,
field_id), self.db.session_id))
num_proposal_fields += 1
self.db.write_table("proposal_field", data)
def setUp(self):
self.fields_db = FieldsDatabase()
self.query = "select * from Field limit 2;"
