def testsched(self):
target_map = standard_goals()['r']
bfs = []
bfs.append(basis_functions.M5_diff_basis_function())
bfs.append(
basis_functions.Target_map_basis_function(target_map=target_map))
weights = np.array([1., 1])
survey = surveys.Greedy_survey(bfs, weights)
scheduler = Core_scheduler([survey])
observatory = Model_observatory()
# Check that we can update conditions
scheduler.update_conditions(observatory.return_conditions())
# Check that we can get an observation out
obs = scheduler.request_observation()
assert (obs is not None)
# Check that we can flush the Queue
scheduler.flush_queue()
assert (len(scheduler.queue) == 0)
# Check that we can add an observation
scheduler.add_observation(obs)
def testBlobs(self):
"""
Set up a blob selection survey
"""
nside = 32
survey_length = 2.0 # days
surveys = []
# Set up the DD
dd_surveys = generate_dd_surveys(nside=nside)
surveys.append(dd_surveys)
surveys.append(gen_blob_surveys(nside))
surveys.append(gen_greedy_surveys(nside))
scheduler = Core_scheduler(surveys, nside=nside)
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations = sim_runner(
observatory, scheduler, survey_length=survey_length, filename=None)
# Make sure some blobs executed
assert ('blob, gg, b' in observations['note'])
assert ('blob, gg, a' in observations['note'])
# assert('blob, u' in observations['note'])
# Make sure some greedy executed
assert ('' in observations['note'])
# Check that the a DD was observed
assert ('DD:ELAISS1' in observations['note'])
# Make sure a few different filters were observed
assert (len(np.unique(observations['filter'])) > 3)
# Make sure lots of observations executed
assert (observations.size > 1000)
# Make sure nothing tried to look through the earth
assert (np.min(observations['alt']) > 0)
def testGreedy(self):
"""
Set up a greedy survey and run for a few days. A crude way to touch lots of code.
"""
nside = 32
survey_length = 2.0 # days
surveys = gen_greedy_surveys(nside)
# Depricating Pairs_survey_scripted
#surveys.append(Pairs_survey_scripted(None, ignore_obs='DD'))
# Set up the DD
dd_surveys = generate_dd_surveys(nside=nside)
surveys.extend(dd_surveys)
scheduler = Core_scheduler(surveys, nside=nside)
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations = sim_runner(
observatory, scheduler, survey_length=survey_length, filename=None)
# Check that greedy observed some
assert ('' in observations['note'])
# Check that the a DD was observed
assert ('DD:ELAISS1' in observations['note'])
# Make sure a few different filters were observed
assert (len(np.unique(observations['filter'])) > 3)
# Make sure lots of observations executed
assert (observations.size > 1000)
# Make sure nothing tried to look through the earth
assert (np.min(observations['alt']) > 0)
def run_sched(surveys, survey_length=365.25, nside=32, fileroot='baseline_', verbose=False,
extra_info=None, cloud_limit=0.3, downtime=True):
years = np.round(survey_length/365.25)
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
observatory = Model_observatory(nside=nside, cloud_limit=cloud_limit)
# If we want to remove the downtime.
if not downtime:
down_starts=[-667]
down_ends=[-666]
observatory.downtimes = np.array(list(zip(down_starts, down_ends)), dtype=list(zip(['start', 'end'], [float, float])))
observatory, scheduler, observations = sim_runner(observatory, scheduler,
survey_length=survey_length,
filename=fileroot+'%iyrs.db' % years,
delete_past=True, n_visit_limit=n_visit_limit,
verbose=verbose, extra_info=extra_info)
def run_sched(surveys, survey_length=365.25, nside=32, fileroot='baseline_', verbose=False,
extra_info=None):
years = np.round(survey_length/365.25)
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations = sim_runner(observatory, scheduler,
survey_length=survey_length,
filename=fileroot+'%iyrs.db' % years,
delete_past=True, n_visit_limit=n_visit_limit,
verbose=verbose, extra_info=extra_info)
def run_sched(surveys,
survey_length=None,
nside=32,
fileroot='baseline_',
verbose=False,
extra_info=None,
illum_limit=40.,
survey_lengths=None,
pause_lengths=None,
delete_past=True):
years = np.round(np.sum(survey_lengths) / 365.25)
filename = fileroot + '%iyrs.db' % years
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
filter_sched = simple_filter_sched(illum_limit=illum_limit)
observatory = Model_observatory(nside=nside)
observations = []
for survey_length, pause_length in zip(survey_lengths, pause_lengths):
observatory, scheduler, observations1 = sim_runner(
observatory,
scheduler,
survey_length=survey_length,
filename=None,
delete_past=True,
n_visit_limit=n_visit_limit,
verbose=verbose,
extra_info=extra_info,
filter_scheduler=filter_sched)
observatory.mjd += pause_length
observations.append(observations1)
# Now for the last set of observations
survey_length = survey_lengths[-1]
observatory, scheduler, observations1 = sim_runner(
observatory,
scheduler,
survey_length=survey_length,
filename=None,
delete_past=True,
n_visit_limit=n_visit_limit,
verbose=verbose,
extra_info=extra_info,
filter_scheduler=filter_sched)
observations.append(observations1)
observations = np.concatenate(observations)
info = run_info_table(observatory, extra_info=extra_info)
converter = schema_converter()
print("Writing combined results to %s" % filename)
converter.obs2opsim(observations,
filename=filename,
info=info,
delete_past=delete_past)
def run_sched(surveys, survey_length=365.25, nside=32, fileroot='greedy_'):
years = np.round(survey_length / 365.25)
scheduler = fs.schedulers.Core_scheduler(surveys, nside=nside)
n_visit_limit = None
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations = fs.sim_runner(
observatory,
scheduler,
survey_length=survey_length,
filename=fileroot + '%iyrs.db' % years,
delete_past=True,
n_visit_limit=n_visit_limit)
def run_sched(surveys,
survey_length=365.25,
nside=32,
fileroot='baseline_',
verbose=False,
extra_info=None,
illum_limit=40.):
years = np.round(survey_length / 365.25)
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
filter_sched = simple_filter_sched(illum_limit=illum_limit)
observatory = Model_observatory(nside=nside)
conditions_init = copy.deepcopy(observatory.return_conditions())
scheduler.update_conditions(observatory.return_conditions())
desired_obs = scheduler.request_observation(mjd=observatory.mjd)
print(desired_obs)
completed_obs, new_night = observatory.observe(desired_obs)
print(completed_obs)
# Check if there's any difference between where we wanted to point, and where it pointed
for key in ['RA', 'dec', 'rotSkyPos']:
print(key, desired_obs[key] - completed_obs[key], desired_obs[key][0])
conditions_final = observatory.return_conditions()
print(scheduler.survey_lists[2][-2].fields['dec'][3410])
import pdb
pdb.set_trace()
def run_sched(surveys, survey_length=365.25, nside=32, fileroot='baseline_cloud11_', verbose=False,
extra_info=None, illum_limit=40.):
years = np.round(survey_length/365.25)
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
filter_sched = simple_filter_sched(illum_limit=illum_limit)
observatory = Model_observatory(nside=nside,
cloud_db="./cloud_58967.db",
cloud_offset_year=-11)
observatory, scheduler, observations = sim_runner(observatory, scheduler,
survey_length=survey_length,
filename=fileroot+'%iyrs.db' % years,
delete_past=True, n_visit_limit=n_visit_limit,
verbose=verbose, extra_info=extra_info,
filter_scheduler=filter_sched)
def run_sched(surveys,
survey_length=None,
nside=32,
fileroot='baseline_',
verbose=False,
extra_info=None,
illum_limit=40.,
sl1=730,
sl2=2922,
pause_length=183,
delete_past=True):
years = np.round((sl1 + sl2 + pause_length) / 365.25)
filename = fileroot + '%iyrs.db' % years
scheduler = Core_scheduler(surveys, nside=nside)
n_visit_limit = None
filter_sched = simple_filter_sched(illum_limit=illum_limit)
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations1 = sim_runner(
observatory,
scheduler,
survey_length=sl1,
filename=None,
delete_past=True,
n_visit_limit=n_visit_limit,
verbose=verbose,
extra_info=extra_info,
filter_scheduler=filter_sched)
observatory.mjd += pause_length
observatory, scheduler, observations2 = sim_runner(
observatory,
scheduler,
survey_length=sl2,
filename=None,
delete_past=True,
n_visit_limit=n_visit_limit,
verbose=verbose,
extra_info=extra_info,
filter_scheduler=filter_sched)
observations = np.concatenate([observations1, observations2])
info = run_info_table(observatory, extra_info=extra_info)
converter = schema_converter()
converter.obs2opsim(observations,
filename=filename,
info=info,
delete_past=delete_past)
['git', 'rev-parse', 'HEAD'])
except subprocess.CalledProcessError:
extra_info['git hash'] = 'Not in git repo'
extra_info['file executed'] = os.path.realpath(__file__)
fileroot = 'weather_%.1f_' % cloud_limit
file_end = 'v1.6_'
if scale_down:
footprints_hp = nes_light_footprints(nside=nside)
fileroot = fileroot + 'scaleddown_'
else:
footprints_hp = standard_goals(nside=nside)
observatory = Model_observatory(nside=nside)
conditions = observatory.return_conditions()
footprints = Footprint(conditions.mjd_start,
sun_RA_start=conditions.sun_RA_start,
nside=nside)
for i, key in enumerate(footprints_hp):
footprints.footprints[i, :] = footprints_hp[key]
# Set up the DDF surveys to dither
dither_detailer = detailers.Dither_detailer(per_night=per_night,
max_dither=max_dither)
details = [
detailers.Camera_rot_detailer(min_rot=-camera_ddf_rot_limit,
max_rot=camera_ddf_rot_limit),
dither_detailer
]
filtername2=filtername2,
ideal_pair_time=pair_time,
nside=nside,
survey_note=survey_name,
ignore_obs='DD',
dither=True))
return surveys
if __name__ == "__main__":
nside = 32
survey_length = 365.25 * 10 # Days
years = int(survey_length / 365.25)
greedy = gen_greedy_surveys(nside)
ddfs = generate_dd_surveys(nside=nside)
blobs = generate_blobs(nside)
surveys = [ddfs, blobs, greedy]
n_visit_limit = None
scheduler = Core_scheduler(surveys, nside=nside)
observatory = Model_observatory(nside=nside)
observatory, scheduler, observations = sim_runner(
observatory,
scheduler,
survey_length=survey_length,
filename='blob_no_slew_%i.db' % years,
n_visit_limit=n_visit_limit)
max_dither=max_dither)
details = [
detailers.Camera_rot_detailer(min_rot=-87., max_rot=87.),
dither_detailer
]
ddfs = generate_dd_surveys(nside=nside, nexp=nexp, detailers=details)
greedy = gen_greedy_surveys(nside, nexp=nexp)
blobs = generate_blobs(nside, nexp=nexp, mixed_pairs=True)
surveys = [ddfs, blobs, greedy]
scheduler = Core_scheduler(surveys, nside=nside)
for obs in observations[0:max_indx]:
scheduler.add_observation(obs)
observatory = Model_observatory(nside=nside)
observatory.mjd = obs['mjd']
_ = observatory.observe(obs)
observatory.mjd = obs['mjd']
_ = observatory.observe(obs)
conditions = observatory.return_conditions()
scheduler.update_conditions(conditions)
rewards = []
reward_sizes = []
for survey_list in scheduler.survey_lists:
rw = []
rws = []
for survey in survey_list:
reward = survey.calc_reward_function(conditions)
exec_command += ' ' + arg
extra_info['exec command'] = exec_command
extra_info['git hash'] = subprocess.check_output(
['git', 'rev-parse', 'HEAD'])
extra_info['file executed'] = os.path.realpath(__file__)
# Generate some simulated ToOs
simple_too = False
if simple_too:
sim_ToOs = generate_events_simple(nside=nside)
event_table = None
else:
sim_ToOs, event_table = generate_events(nside=nside,
survey_length=survey_length,
rate=too_rate)
observatory = Model_observatory(nside=nside, sim_ToO=sim_ToOs)
if Pairs:
if mixedPairs:
# mixed pairs.
toos = gen_too_surveys(nside=nside, nexp=nexp, nvis=nvis)
greedy = gen_greedy_surveys(nside, nexp=nexp)
ddfs = generate_dd_surveys(nside=nside, nexp=nexp)
blobs = generate_blobs(nside, nexp=nexp, mixed_pairs=True)
surveys = [toos, ddfs, blobs, greedy]
run_sched(surveys,
observatory,
survey_length=survey_length,
verbose=verbose,
fileroot=os.path.join(outDir,
'too_pairsmix_rate%i_' % too_rate),
scheduler,
survey_length=survey_length,
filename=fileroot + '%iyrs.db' % years,
delete_past=True,
n_visit_limit=n_visit_limit,
verbose=verbose,
extra_info=extra_info,
filter_scheduler=filter_sched)
if __name__ == "__main__":
nside = 32
scheduler = make_scheduler()
observatory = Model_observatory(nside=nside)
sco = schema_converter()
observations = sco.opsim2obs('baseline_nexp1_v1.6_1yrs.db')
indx = 64840 - 1
for obs in observations[0:indx]:
scheduler.add_observation(obs)
observatory.mjd = obs['mjd']
# Observatory starts parked, so need to send an expose command to slew to the correct position
temp = observatory.observe(obs)
# It took some time to make that slew, so reset the time again
observatory.mjd = observations[indx]['mjd']
should_match_obs, new_night = observatory.observe(obs)
conditions = observatory.return_conditions()
scheduler.update_conditions(conditions)
for survey in scheduler.survey_lists[-1]:
