def _update_rotSkyPos(self, observation):
"""If we have an undefined rotSkyPos, try to fill it out.
"""
alt, az = _approx_RaDec2AltAz(observation['RA'], observation['dec'],
self.site.latitude_rad,
self.site.longitude_rad, self.mjd)
obs_pa = approx_altaz2pa(alt, az, self.site.latitude_rad)
observation['rotSkyPos'] = (obs_pa +
observation['rotTelPos']) % (2 * np.pi)
observation['rotTelPos'] = 0.
return observation
def __call__(self, observation_list, conditions):
# XXX--should I convert the list into an array and get rid of this loop?
for obs in observation_list:
alt, az = _approx_RaDec2AltAz(obs['RA'], obs['dec'],
conditions.site.latitude_rad,
conditions.site.longitude_rad,
conditions.mjd)
obs_pa = approx_altaz2pa(alt, az, conditions.site.latitude_rad)
obs['rotSkyPos'] = obs_pa
return observation_list
def request_observation(self, mjd=None):
"""
Ask the scheduler what it wants to observe next
Paramters
---------
mjd : float (None)
The Modified Julian Date. If None, it uses the MJD from the conditions from the last conditions update.
Returns
-------
observation object (ra,dec,filter,rotangle)
Returns None if the queue fails to fill
"""
if mjd is None:
mjd = self.conditions.mjd
if len(self.queue) == 0:
self._fill_queue()
if len(self.queue) == 0:
return None
else:
# If the queue has gone stale, flush and refill. Zero means no flush_by was set.
if (int_rounded(mjd) > int_rounded(self.queue[0]['flush_by_mjd'])
) & (self.queue[0]['flush_by_mjd'] != 0):
self.flushed += len(self.queue)
self.flush_queue()
self._fill_queue()
if len(self.queue) == 0:
return None
observation = self.queue.pop(0)
# If we are limiting the camera rotator
if self.rotator_limits is not None:
alt, az = _approx_RaDec2AltAz(
observation['RA'], observation['dec'],
self.conditions.site.latitude_rad,
self.conditions.site.longitude_rad, mjd)
obs_pa = approx_altaz2pa(alt, az,
self.conditions.site.latitude_rad)
rotTelPos_expected = (obs_pa -
observation['rotSkyPos']) % (2. * np.pi)
if (int_rounded(rotTelPos_expected) > int_rounded(
self.rotator_limits[0])) & (
int_rounded(rotTelPos_expected) < int_rounded(
self.rotator_limits[1])):
diff = np.abs(self.rotator_limits - rotTelPos_expected)
limit_indx = np.min(np.where(diff == np.min(diff))[0])
observation['rotSkyPos'] = (
obs_pa - self.rotator_limits[limit_indx]) % (2. *
np.pi)
return observation
def __call__(self, observation_list, conditions):
# Generate offsets in RA and Dec
offsets = self._generate_offsets(len(observation_list),
conditions.night)
for i, obs in enumerate(observation_list):
alt, az = _approx_RaDec2AltAz(obs['RA'], obs['dec'],
conditions.site.latitude_rad,
conditions.site.longitude_rad,
conditions.mjd)
obs_pa = approx_altaz2pa(alt, az, conditions.site.latitude_rad)
obs['rotSkyPos'] = (obs_pa + offsets[i]) % (2. * np.pi)
return observation_list
def __call__(self, observation_list, conditions):
favored_rotSkyPos = np.radians([0., 90., 180., 270.,
360.]).reshape(5, 1)
obs_array = np.concatenate(observation_list)
alt, az = _approx_RaDec2AltAz(obs_array['RA'], obs_array['dec'],
conditions.site.latitude_rad,
conditions.site.longitude_rad,
conditions.mjd)
parallactic_angle = approx_altaz2pa(alt, az,
conditions.site.latitude_rad)
# If we set rotSkyPos to parallactic angle, rotTelPos will be zero. So, find the
# favored rotSkyPos that is closest to PA to keep rotTelPos as close as possible to zero.
ang_diff = np.abs(parallactic_angle - favored_rotSkyPos)
min_indxs = np.argmin(ang_diff, axis=0)
# can swap 360 and zero if needed?
final_rotSkyPos = favored_rotSkyPos[min_indxs]
# Set all the observations to the proper rotSkyPos
for rsp, obs in zip(final_rotSkyPos, observation_list):
obs['rotSkyPos'] = rsp
return observation_list
def calc_pa(self):
self._pa = approx_altaz2pa(self.alt, self.az, self.site.latitude_rad)