def _slice2obs(self, obs_row):
"""take a slice and return a full observation object
"""
observation = empty_observation()
for key in ['RA', 'dec', 'filter', 'exptime', 'nexp', 'note', 'field_id']:
observation[key] = obs_row[key]
return observation
def testVisit_repeat_basis_function(self):
bf = fs.Visit_repeat_basis_function()
indx = np.array([1000])
# 30 minute step
delta = 30. / 60. / 24.
# Add 1st observation, should still be zero
obs = fs.empty_observation()
obs['filter'] = 'r'
obs['mjd'] = 59000.
conditions = {'mjd': obs['mjd']}
bf.add_observation(obs, indx=indx)
bf.update_conditions(conditions)
self.assertEqual(np.max(bf()), 0.)
# Advance time so now we want a pair
conditions['mjd'] += delta
bf.update_conditions(conditions)
self.assertEqual(np.max(bf()), 1.)
# Now complete the pair and it should go back to zero
bf.add_observation(obs, indx=indx)
conditions['mjd'] += delta
bf.update_conditions(conditions)
self.assertEqual(np.max(bf()), 0.)
def teststubb(self):
so = speedo.Speed_observatory()
# Check that we can get a status
status = so.return_status()
# Check that we can get an observation
obs = empty_observation()
obs['dec'] = np.radians(-30.)
obs['filter'] = 'r'
obs['exptime'] = 30.
obs['nexp'] = 2.
result = so.attempt_observe(obs)
status2 = so.return_status()
assert (status2['mjd'] > status['mjd'])
obs['dec'] = np.radians(-35.)
result = so.attempt_observe(obs)
assert (result['airmass'] >= 1.)
def testPair_in_night(self):
pin = fs.Pair_in_night(gap_min=25., gap_max=45.)
self.assertEqual(np.max(pin.feature), 0.)
indx = np.array([1000])
delta = 30. / 60. / 24.
# Add 1st observation, feature should still be zero
obs = fs.empty_observation()
obs['filter'] = 'r'
obs['mjd'] = 59000.
pin.add_observation(obs, indx=indx)
self.assertEqual(np.max(pin.feature), 0.)
# Add 2nd observation
obs['mjd'] += delta
pin.add_observation(obs, indx=indx)
self.assertEqual(np.max(pin.feature), 1.)
obs['mjd'] += delta
pin.add_observation(obs, indx=indx)
self.assertEqual(np.max(pin.feature), 2.)
survey_length = 5.5 #365.25*10 # days nside = fs.set_default_nside(nside=32) # Define what we want the final visit ratio map to look like years = np.round(survey_length / 365.25) # get rid of silly northern strip. target_map = fs.standard_goals(nside=nside) norm_factor = fs.calc_norm_factor(target_map) # List to hold all the surveys (for easy plotting later) surveys = [] # Let's set up a scripted observation that will just interupt whenever mjd0 = 59583.060669 ssurvey = Scripted_survey(mjd0, 10.) for_type = fs.empty_observation() scripted_obs = np.zeros(20, dtype=for_type.dtype) scripted_obs['filter'] = 'r' # Take a strip of declination at constant RA. scripted_obs['RA'] = np.radians(53.) # radians scripted_obs['dec'] = np.radians(-np.arange(20) * 2. - 20.) # Assume about 37 seconds per visit scripted_obs['mjd'] = (np.arange(20) * 36.) / 3600. / 24. + mjd0 scripted_obs['exptime'] = 30. scripted_obs['nexp'] = 2 # Add a note so it's easy to see if they fire scripted_obs['note'] = 'scripted_tier1' ssurvey.set_script(scripted_obs) scripted_surveys = [ssurvey]
def __call__(self):
"""
Find a good block of observations.
"""
if not self.reward_checked:
# This should set self.best_fields
self.reward = self.calc_reward_function()
# Let's find the alt, az coords of the points (right now, hopefully doesn't change much in time block)
pointing_alt, pointing_az = stupidFast_RaDec2AltAz(
self.fields['RA'][self.best_fields],
self.fields['dec'][self.best_fields],
self.lat,
self.lon,
self.extra_features['mjd'].feature,
lmst=self.extra_features['lmst'].feature)
# Let's find a good spot to project the points to a plane
mid_alt = (np.max(pointing_alt) - np.min(pointing_alt)) / 2.
# Code snippet from MAF for computing mean of angle accounting for wrap around
# XXX-TODO: Maybe move this to sims_utils as a generally useful snippet.
x = np.cos(pointing_az)
y = np.sin(pointing_az)
meanx = np.mean(x)
meany = np.mean(y)
angle = np.arctan2(meany, meanx)
radius = np.sqrt(meanx**2 + meany**2)
mid_az = angle % (2. * np.pi)
if radius < 0.1:
mid_az = np.pi
# Project the alt,az coordinates to a plane. Could consider scaling things to represent
# time between points rather than angular distance.
pointing_x, pointing_y = gnomonic_project_toxy(pointing_az,
pointing_alt, mid_az,
mid_alt)
# Now I have a bunch of x,y pointings. Drop into TSP solver to get an effiencent route
towns = np.vstack((pointing_x, pointing_y)).T
# Leaving optimize=False for speed. The optimization step doesn't usually improve much.
better_order = tsp_convex(towns, optimize=False)
# XXX-TODO: Could try to roll better_order to start at the nearest/fastest slew from current position.
observations = []
counter2 = 0
for indx in better_order:
field = self.best_fields[indx]
if self.tag_fields:
tag = np.unique(
self.tag_map[np.where(self.hp2fields == field)])[0]
else:
tag = 1
if tag == 0:
continue
obs = empty_observation()
obs['RA'] = self.fields['RA'][field]
obs['dec'] = self.fields['dec'][field]
obs['rotSkyPos'] = 0.
obs['filter'] = self.filtername
obs['nexp'] = self.nexp
obs['exptime'] = self.exptimes_f1[indx]
obs['field_id'] = -1
if self.tag_fields:
obs['survey_id'] = np.unique(
self.tag_map[np.where(self.hp2fields == field)])[0]
else:
obs['survey_id'] = 1
obs['note'] = '%s' % (self.survey_note)
obs['block_id'] = self.counter
obs['note'] = '%s, a' % (self.survey_note)
observations.append(obs)
counter2 += 1
# If we only want one filter block
if self.filter2 is None:
result = observations
else:
# Double the list to get a pair.
observations_paired = []
for i, observation in enumerate(observations):
obs = copy.copy(observation)
obs['filter'] = self.filter2
obs['exptime'] = self.exptimes_f2[better_order[i]]
obs['note'] = '%s, b' % (self.survey_note)
observations_paired.append(obs)
# Check loaded filter here to decide which goes first
if self.extra_features['current_filter'].feature == self.filter2:
result = observations_paired + observations
else:
result = observations + observations_paired
# Keep track of which block we're on. Nice for debugging.
self.counter += 1
return result