コード例 #1
0
class ObservatoryStateMock:
    def __init__(self):
        self.ptg = salobj.Controller("MTPtg")

        self.location = ObservatoryLocation()
        self.location.for_lsst()

        self.model = ObservatoryModel(self.location)
        self.model.configure_from_module()

        self.telemetry_sleep_time = 0.02
        self.run_current_target_status_loop = True
        self.current_target_status_task = None

        self._started = False
        self.start_task = asyncio.create_task(self.start())

    async def current_target_status(self):
        while self.run_current_target_status_loop:
            time = utils.current_tai()
            self.model.update_state(time)
            await self.ptg.tel_currentTargetStatus.set_write(
                timestamp=time,
                demandAz=self.model.current_state.telaz,
                demandEl=self.model.current_state.telalt,
                demandRot=self.model.current_state.telrot,
                demandRa=self.model.current_state.ra,
                demandDec=self.model.current_state.dec,
                parAngle=self.model.current_state.pa,
            )
            await asyncio.sleep(self.telemetry_sleep_time)

    async def start(self):
        if not self._started:
            self._started = True
            await self.ptg.start_task

            self.run_current_target_status_loop = True
            self.current_target_status_task = asyncio.create_task(
                self.current_target_status())

    async def close(self):
        self.run_current_target_status_loop = False
        try:
            await asyncio.wait_for(self.current_target_status_task,
                                   timeout=self.telemetry_sleep_time * 5)
        finally:
            await self.ptg.close()

    async def __aenter__(self):
        await self.start_task
        return self

    async def __aexit__(self, type, value, traceback):
        await self.close()
コード例 #2
0
class Driver(object):
    def __init__(self):

        self.log = logging.getLogger("schedulerDriver")

        self.params = DriverParameters()
        self.location = ObservatoryLocation()

        self.observatoryModel = ObservatoryModel(self.location, WORDY)
        self.observatoryModel2 = ObservatoryModel(self.location, WORDY)
        self.observatoryState = ObservatoryState()

        self.sky = AstronomicalSkyModel(self.location)

        self.db = FieldsDatabase()

        self.build_fields_dict()

        self.propid_counter = 0
        self.science_proposal_list = []

        self.start_time = 0.0
        self.time = 0.0
        self.targetid = 0
        self.survey_started = False
        self.isnight = False
        self.sunset_timestamp = 0.0
        self.sunrise_timestamp = 0.0
        self.survey_duration_DAYS = 0.0
        self.survey_duration_SECS = self.survey_duration_DAYS * 24 * 60 * 60.0
        self.darktime = False
        self.mounted_filter = ""
        self.unmounted_filter = ""
        self.midnight_moonphase = 0.0

        self.nulltarget = Target()
        self.nulltarget.targetid = -1
        self.nulltarget.num_exp = 1
        self.nulltarget.exp_times = [0.0]
        self.nulltarget.num_props = 1
        self.nulltarget.propid_list = [0]
        self.nulltarget.need_list = [0.0]
        self.nulltarget.bonus_list = [0.0]
        self.nulltarget.value_list = [0.0]
        self.nulltarget.propboost_list = [1.0]
        self.last_winner_target = self.nulltarget.get_copy()
        self.deep_drilling_target = None

        self.need_filter_swap = False
        self.filter_to_unmount = ""
        self.filter_to_mount = ""

        self.cloud = 0.0
        self.seeing = 0.0

    def configure_survey(self, survey_conf_file):

        prop_conf_path = os.path.dirname(survey_conf_file)
        confdict = read_conf_file(survey_conf_file)

        self.survey_duration_DAYS = confdict["survey"]["survey_duration"]
        self.survey_duration_SECS = self.survey_duration_DAYS * 24 * 60 * 60.0

        self.propid_counter = 0
        self.science_proposal_list = []

        if 'scripted_propconf' in confdict["proposals"]:
            scripted_propconflist = confdict["proposals"]["scripted_propconf"]
        else:
            scripted_propconflist = []
        if not isinstance(scripted_propconflist, list):
            # turn it into a list with one entry
            propconf = scripted_propconflist
            scripted_propconflist = []
            scripted_propconflist.append(propconf)
        self.log.info("configure_survey: scripted proposals %s" % (scripted_propconflist))
        for k in range(len(scripted_propconflist)):
            self.propid_counter += 1
            scripted_prop = ScriptedProposal(self.propid_counter,
                                             os.path.join(prop_conf_path,
                                                          "{}".format(scripted_propconflist[k])),
                                             self.sky)
            self.science_proposal_list.append(scripted_prop)

        if 'areadistribution_propconf' in confdict["proposals"]:
            areadistribution_propconflist = confdict["proposals"]["areadistribution_propconf"]
        else:
            areadistribution_propconflist = []
            self.log.info("areadistributionPropConf:%s default" % (areadistribution_propconflist))
        if not isinstance(areadistribution_propconflist, list):
            # turn it into a list with one entry
            propconf = areadistribution_propconflist
            areadistribution_propconflist = []
            areadistribution_propconflist.append(propconf)
        self.log.info("init: areadistribution proposals %s" % (areadistribution_propconflist))
        for k in range(len(areadistribution_propconflist)):
            self.propid_counter += 1
            configfilepath = os.path.join(prop_conf_path, "{}".format(areadistribution_propconflist[k]))
            (path, name_ext) = os.path.split(configfilepath)
            (name, ext) = os.path.splitext(name_ext)
            proposal_confdict = read_conf_file(configfilepath)
            self.create_area_proposal(self.propid_counter, name, proposal_confdict)

        for prop in self.science_proposal_list:
            prop.configure_constraints(self.params)

    def configure_duration(self, survey_duration):

        self.survey_duration_DAYS = survey_duration
        self.survey_duration_SECS = survey_duration * 24 * 60 * 60.0

    def configure(self, confdict):

        self.params.configure(confdict)
        self.log.log(WORDY,
                     "configure: coadd_values=%s" % (self.params.coadd_values))
        self.log.log(WORDY,
                     "configure: time_balancing=%s" % (self.params.time_balancing))
        self.log.log(WORDY,
                     "configure: timecost_dc=%.3f" % (self.params.timecost_dc))
        self.log.log(WORDY,
                     "configure: timecost_dt=%.3f" % (self.params.timecost_dt))
        self.log.log(WORDY,
                     "configure: timecost_k=%.3f" % (self.params.timecost_k))
        self.log.log(WORDY,
                     "configure: timecost_weight=%.3f" % (self.params.timecost_weight))
        self.log.log(WORDY,
                     "configure: night_boundary=%.1f" % (self.params.night_boundary))
        self.log.log(WORDY,
                     "configure: ignore_sky_brightness=%s" % (self.params.ignore_sky_brightness))
        self.log.log(WORDY,
                     "configure: ignore_airmass=%s" % (self.params.ignore_airmass))
        self.log.log(WORDY,
                     "configure: ignore_clouds=%s" % (self.params.ignore_clouds))
        self.log.log(WORDY,
                     "configure: ignore_seeing=%s" % (self.params.ignore_seeing))
        self.log.log(WORDY,
                     "configure: new_moon_phase_threshold=%.2f" % (self.params.new_moon_phase_threshold))

        for prop in self.science_proposal_list:
            prop.configure_constraints(self.params)

    def configure_location(self, confdict):

        self.location.configure(confdict)
        self.observatoryModel.location.configure(confdict)
        self.observatoryModel2.location.configure(confdict)
        self.sky.update_location(self.location)

    def configure_observatory(self, confdict):

        self.observatoryModel.configure(confdict)
        self.observatoryModel2.configure(confdict)

    def configure_telescope(self, confdict):

        self.observatoryModel.configure_telescope(confdict)
        self.observatoryModel2.configure_telescope(confdict)

    def configure_rotator(self, confdict):

        self.observatoryModel.configure_rotator(confdict)
        self.observatoryModel2.configure_rotator(confdict)

    def configure_dome(self, confdict):

        self.observatoryModel.configure_dome(confdict)
        self.observatoryModel2.configure_dome(confdict)

    def configure_optics(self, confdict):

        self.observatoryModel.configure_optics(confdict)
        self.observatoryModel2.configure_optics(confdict)

    def configure_camera(self, confdict):

        self.observatoryModel.configure_camera(confdict)
        self.observatoryModel2.configure_camera(confdict)

    def configure_slew(self, confdict):

        self.observatoryModel.configure_slew(confdict)
        self.observatoryModel2.configure_slew(confdict)

    def configure_park(self, confdict):

        self.observatoryModel.configure_park(confdict)
        self.observatoryModel2.configure_park(confdict)

    def create_area_proposal(self, propid, name, config_dict):

        self.propid_counter += 1
        area_prop = AreaDistributionProposal(propid, name, config_dict, self.sky)
        area_prop.configure_constraints(self.params)
        self.science_proposal_list.append(area_prop)

    def create_sequence_proposal(self, propid, name, config_dict):

        self.propid_counter += 1
        seq_prop = TimeDistributionProposal(propid, name, config_dict, self.sky)
        seq_prop.configure_constraints(self.params)
        self.science_proposal_list.append(seq_prop)

    def build_fields_dict(self):

        sql = "select * from Field"
        res = self.db.query(sql)

        self.fields_dict = {}
        for row in res:
            field = Field()
            fieldid = row[0]
            field.fieldid = fieldid
            field.fov_rad = math.radians(row[1])
            field.ra_rad = math.radians(row[2])
            field.dec_rad = math.radians(row[3])
            field.gl_rad = math.radians(row[4])
            field.gb_rad = math.radians(row[5])
            field.el_rad = math.radians(row[6])
            field.eb_rad = math.radians(row[7])
            self.fields_dict[fieldid] = field
            self.log.log(EXTENSIVE, "buildFieldsTable: %s" % (self.fields_dict[fieldid]))
        self.log.info("buildFieldsTable: %d fields" % (len(self.fields_dict)))

    def get_fields_dict(self):

        return self.fields_dict

    def start_survey(self, timestamp, night):

        self.start_time = timestamp
        self.log.info("start_survey t=%.6f" % timestamp)

        self.survey_started = True
        for prop in self.science_proposal_list:
            prop.start_survey()

        self.sky.update(timestamp)
        (sunset, sunrise) = self.sky.get_night_boundaries(self.params.night_boundary)
        self.log.debug("start_survey sunset=%.6f sunrise=%.6f" % (sunset, sunrise))
        # if round(sunset) <= round(timestamp) < round(sunrise):
        if sunset <= timestamp < sunrise:
            self.start_night(timestamp, night)

        self.sunset_timestamp = sunset
        self.sunrise_timestamp = sunrise

    def end_survey(self):

        self.log.info("end_survey")

        for prop in self.science_proposal_list:
            prop.end_survey()

    def start_night(self, timestamp, night):

        timeprogress = (timestamp - self.start_time) / self.survey_duration_SECS
        self.log.info("start_night t=%.6f, night=%d timeprogress=%.2f%%" %
                      (timestamp, night, 100 * timeprogress))

        self.isnight = True

        for prop in self.science_proposal_list:
            prop.start_night(timestamp, self.observatoryModel.current_state.mountedfilters, night)

    def end_night(self, timestamp, night):

        timeprogress = (timestamp - self.start_time) / self.survey_duration_SECS
        self.log.info("end_night t=%.6f, night=%d timeprogress=%.2f%%" %
                      (timestamp, night, 100 * timeprogress))

        self.isnight = False

        self.last_winner_target = self.nulltarget
        self.deep_drilling_target = None

        total_filter_visits_dict = {}
        total_filter_goal_dict = {}
        total_filter_progress_dict = {}
        for prop in self.science_proposal_list:
            prop.end_night(timestamp)
            filter_visits_dict = {}
            filter_goal_dict = {}
            filter_progress_dict = {}
            for filter in self.observatoryModel.filters:
                if filter not in total_filter_visits_dict:
                    total_filter_visits_dict[filter] = 0
                    total_filter_goal_dict[filter] = 0
                filter_visits_dict[filter] = prop.get_filter_visits(filter)
                filter_goal_dict[filter] = prop.get_filter_goal(filter)
                filter_progress_dict[filter] = prop.get_filter_progress(filter)
                total_filter_visits_dict[filter] += filter_visits_dict[filter]
                total_filter_goal_dict[filter] += filter_goal_dict[filter]
                self.log.debug("end_night propid=%d name=%s filter=%s progress=%.2f%%" %
                               (prop.propid, prop.name, filter, 100 * filter_progress_dict[filter]))
        for filter in self.observatoryModel.filters:
            if total_filter_goal_dict[filter] > 0:
                total_filter_progress_dict[filter] = \
                    float(total_filter_visits_dict[filter]) / total_filter_goal_dict[filter]
            else:
                total_filter_progress_dict[filter] = 0.0
            self.log.info("end_night filter=%s progress=%.2f%%" %
                          (filter, 100 * total_filter_progress_dict[filter]))

        previous_midnight_moonphase = self.midnight_moonphase
        self.sky.update(timestamp)
        (sunset, sunrise) = self.sky.get_night_boundaries(self.params.night_boundary)
        self.log.debug("end_night sunset=%.6f sunrise=%.6f" % (sunset, sunrise))

        self.sunset_timestamp = sunset
        self.sunrise_timestamp = sunrise
        next_midnight = (sunset + sunrise) / 2
        self.sky.update(next_midnight)
        info = self.sky.get_moon_sun_info(numpy.array([0.0]), numpy.array([0.0]))
        self.midnight_moonphase = info["moonPhase"]
        self.log.info("end_night next moonphase=%.2f%%" % (self.midnight_moonphase))

        self.need_filter_swap = False
        self.filter_to_mount = ""
        self.filter_to_unmount = ""
        if self.darktime:
            if self.midnight_moonphase > previous_midnight_moonphase:
                self.log.info("end_night dark time waxing")
                if self.midnight_moonphase > self.params.new_moon_phase_threshold:
                    self.need_filter_swap = True
                    self.filter_to_mount = self.unmounted_filter
                    self.filter_to_unmount = self.mounted_filter
                    self.darktime = False
            else:
                self.log.info("end_night dark time waning")
        else:
            if self.midnight_moonphase < previous_midnight_moonphase:
                self.log.info("end_night bright time waning")
                if self.midnight_moonphase < self.params.new_moon_phase_threshold:
                    self.need_filter_swap = True
                    self.filter_to_mount = self.observatoryModel.params.filter_darktime
                    max_progress = -1.0
                    for filter in self.observatoryModel.params.filter_removable_list:
                        if total_filter_progress_dict[filter] > max_progress:
                            self.filter_to_unmount = filter
                            max_progress = total_filter_progress_dict[filter]
                    self.darktime = True
            else:
                self.log.info("end_night bright time waxing")

        if self.need_filter_swap:
            self.log.debug("end_night filter swap %s=>cam=>%s" %
                           (self.filter_to_mount, self.filter_to_unmount))

    def swap_filter(self, filter_to_unmount, filter_to_mount):

        self.log.info("swap_filter swap %s=>cam=>%s" % (filter_to_mount, filter_to_unmount))

        self.observatoryModel.swap_filter(filter_to_unmount)

        self.unmounted_filter = filter_to_unmount
        self.mounted_filter = filter_to_mount

        return

    def update_time(self, timestamp, night):

        self.time = timestamp
        self.observatoryModel.update_state(self.time)
        if not self.survey_started:
            self.start_survey(timestamp, night)

        if self.isnight:
            # if round(timestamp) >= round(self.sunrise_timestamp):
            if timestamp >= self.sunrise_timestamp:
                self.end_night(timestamp, night)
        else:
            # if round(timestamp) >= round(self.sunset_timestamp):
            if timestamp >= self.sunset_timestamp:
                self.start_night(timestamp, night)

        return self.isnight

    def get_need_filter_swap(self):

        return (self.need_filter_swap, self.filter_to_unmount, self.filter_to_mount)

    def update_internal_conditions(self, observatory_state, night):

        if observatory_state.unmountedfilters != self.observatoryModel.current_state.unmountedfilters:
            unmount = observatory_state.unmountedfilters[0]
            mount = self.observatoryModel.current_state.unmountedfilters[0]
            self.swap_filter(unmount, mount)
            for prop in self.science_proposal_list:
                prop.start_night(observatory_state.time, observatory_state.mountedfilters, night)

        self.time = observatory_state.time
        self.observatoryModel.set_state(observatory_state)
        self.observatoryState.set(observatory_state)

    def update_external_conditions(self, cloud, seeing):

        self.cloud = cloud
        self.seeing = seeing

        return

    def select_next_target(self):

        if not self.isnight:
            return self.nulltarget

        targets_dict = {}
        ranked_targets_list = []
        propboost_dict = {}
        sumboost = 0.0

        timeprogress = (self.time - self.start_time) / self.survey_duration_SECS
        for prop in self.science_proposal_list:

            progress = prop.get_progress()
            if self.params.time_balancing:
                if progress > 0.0:
                    if timeprogress < 1.0:
                        needindex = (1.0 - progress) / (1.0 - timeprogress)
                    else:
                        needindex = 0.0
                    if timeprogress > 0.0:
                        progressindex = progress / timeprogress
                    else:
                        progressindex = 1.0
                    propboost_dict[prop.propid] = needindex / progressindex
                else:
                    propboost_dict[prop.propid] = 1.0
            else:
                propboost_dict[prop.propid] = 1.0
            sumboost += propboost_dict[prop.propid]

        if self.deep_drilling_target is not None:
            self.log.debug("select_next_target: in deep drilling %s" % str(self.deep_drilling_target))

        if self.observatoryModel.is_filter_change_allowed():
            constrained_filter = None
        else:
            constrained_filter = self.observatoryModel.current_state.filter
        num_filter_changes = self.observatoryModel.get_number_filter_changes()
        delta_burst = self.observatoryModel.get_delta_filter_burst()
        delta_avg = self.observatoryModel.get_delta_filter_avg()
        self.log.debug("select_next_target: filter changes num=%i tburst=%.1f tavg=%.1f constrained=%s" %
                       (num_filter_changes, delta_burst, delta_avg, constrained_filter))

        for prop in self.science_proposal_list:
            propboost_dict[prop.propid] = \
                (propboost_dict[prop.propid] * len(self.science_proposal_list) / sumboost) ** self.params.propboost_weight

            proptarget_list = prop.suggest_targets(self.time,
                                                   self.deep_drilling_target, constrained_filter,
                                                   self.cloud, self.seeing)
            self.log.log(EXTENSIVE, "select_next_target propid=%d name=%s "
                         "targets=%d progress=%.2f%% propboost=%.3f" %
                         (prop.propid, prop.name,
                          len(proptarget_list), 100 * progress, propboost_dict[prop.propid]))

            for target in proptarget_list:
                target.num_props = 1
                target.propboost = propboost_dict[prop.propid]
                target.propid_list = [prop.propid]
                target.need_list = [target.need]
                target.bonus_list = [target.bonus]
                target.value_list = [target.value]
                target.propboost_list = [target.propboost]
                target.sequenceid_list = [target.sequenceid]
                target.subsequencename_list = [target.subsequencename]
                target.groupid_list = [target.groupid]
                target.groupix_list = [target.groupix]
                target.is_deep_drilling_list = [target.is_deep_drilling]
                target.is_dd_firstvisit_list = [target.is_dd_firstvisit]
                target.remaining_dd_visits_list = [target.remaining_dd_visits]
                target.dd_exposures_list = [target.dd_exposures]
                target.dd_filterchanges_list = [target.dd_filterchanges]
                target.dd_exptime_list = [target.dd_exptime]

                fieldfilter = (target.fieldid, target.filter)
                if fieldfilter in targets_dict:
                    if self.params.coadd_values:
                        targets_dict[fieldfilter][0] = targets_dict[fieldfilter][0].get_copy()
                        targets_dict[fieldfilter][0].need += target.need
                        targets_dict[fieldfilter][0].bonus += target.bonus
                        targets_dict[fieldfilter][0].value += target.value
                        targets_dict[fieldfilter][0].propboost += target.propboost
                        if target.is_deep_drilling:
                            # overrides to make the coadded target a consistent deep drilling
                            targets_dict[fieldfilter][0].is_deep_drilling = target.is_deep_drilling
                            targets_dict[fieldfilter][0].is_dd_firstvisit = target.is_dd_firstvisit
                            targets_dict[fieldfilter][0].remaining_dd_visits = target.remaining_dd_visits
                            targets_dict[fieldfilter][0].dd_exposures = target.dd_exposures
                            targets_dict[fieldfilter][0].dd_filterchanges = target.dd_filterchanges
                            targets_dict[fieldfilter][0].dd_exptime = target.dd_exptime
                            targets_dict[fieldfilter][0].sequenceid = target.sequenceid
                            targets_dict[fieldfilter][0].subsequencename = target.subsequencename
                            targets_dict[fieldfilter][0].groupid = target.groupid
                            targets_dict[fieldfilter][0].groupix = target.groupix
                        else:
                            # new target to coadd is not deep drilling
                            if not targets_dict[fieldfilter][0].is_deep_drilling:
                                # coadded target is not deep drilling
                                # overrides with new sequence information
                                targets_dict[fieldfilter][0].sequenceid = target.sequenceid
                                targets_dict[fieldfilter][0].subsequencename = target.subsequencename
                                targets_dict[fieldfilter][0].groupid = target.groupid
                                targets_dict[fieldfilter][0].groupix = target.groupix
                            # if coadded target is already deep drilling, don't override
                        targets_dict[fieldfilter][0].num_props += 1
                        targets_dict[fieldfilter][0].propid_list.append(prop.propid)
                        targets_dict[fieldfilter][0].need_list.append(target.need)
                        targets_dict[fieldfilter][0].bonus_list.append(target.bonus)
                        targets_dict[fieldfilter][0].value_list.append(target.value)
                        targets_dict[fieldfilter][0].propboost_list.append(target.propboost)
                        targets_dict[fieldfilter][0].sequenceid_list.append(target.sequenceid)
                        targets_dict[fieldfilter][0].subsequencename_list.append(target.subsequencename)
                        targets_dict[fieldfilter][0].groupid_list.append(target.groupid)
                        targets_dict[fieldfilter][0].groupix_list.append(target.groupix)
                        targets_dict[fieldfilter][0].is_deep_drilling_list.append(target.is_deep_drilling)
                        targets_dict[fieldfilter][0].is_dd_firstvisit_list.append(target.is_dd_firstvisit)
                        targets_dict[fieldfilter][0].remaining_dd_visits_list.append(
                            target.remaining_dd_visits)
                        targets_dict[fieldfilter][0].dd_exposures_list.append(target.dd_exposures)
                        targets_dict[fieldfilter][0].dd_filterchanges_list.append(target.dd_filterchanges)
                        targets_dict[fieldfilter][0].dd_exptime_list.append(target.dd_exptime)
                    else:
                        targets_dict[fieldfilter].append(target)
                else:
                    targets_dict[fieldfilter] = [target]

        filtercost = self.compute_filterchange_cost() * self.params.filtercost_weight
        for fieldfilter in targets_dict:
            slewtime = self.observatoryModel.get_slew_delay(targets_dict[fieldfilter][0])
            if slewtime >= 0:
                timecost = self.compute_slewtime_cost(slewtime) * self.params.timecost_weight
                for target in targets_dict[fieldfilter]:
                    target.slewtime = slewtime
                    if target.filter != self.observatoryModel.current_state.filter:
                        target.cost = timecost + filtercost
                    else:
                        target.cost = timecost
                    target.rank = (target.value * target.propboost) - target.cost
                    ranked_targets_list.append((-target.rank, target))

        sorted_list = sorted(ranked_targets_list, key=itemgetter(0))

        winner_found = False
        while len(sorted_list) > 0 and not winner_found:
            winner_target = sorted_list.pop(0)[1]

            self.observatoryModel2.set_state(self.observatoryState)
            self.observatoryModel2.observe(winner_target)
            if winner_target.is_dd_firstvisit:
                ttime = self.observatoryModel2.get_deep_drilling_time(winner_target)
            else:
                ttime = 0.0
            ntime = self.observatoryModel2.current_state.time + ttime + 30.0
            if ntime < self.sunrise_timestamp:
                self.observatoryModel2.update_state(ntime)
                if self.observatoryModel2.current_state.tracking:
                    self.targetid += 1
                    winner_target.targetid = self.targetid
                    winner_target.time = self.time
                    winner_found = True
                else:
                    self.log.debug("select_next_target: target rejected ttime=%.1f %s" %
                                   (ttime, str(winner_target)))
                    self.log.debug("select_next_target: state rejected %s" %
                                   str(self.observatoryModel2.current_state))
            else:
                self.log.debug("select_next_target: target rejected ttime=%.1f %s" %
                               (ttime, str(winner_target)))
                self.log.debug("select_next_target: rejected due to end of night")
                if ttime == 0.0:
                    # ttime == 0 means it is a regular visit (not DD)
                    # if there is no time left for a single visit then quit
                    break

        if winner_found:
            if not self.params.coadd_values:
                first_target = targets_dict[(winner_target.fieldid, winner_target.filter)][0]
                if first_target.propid != winner_target.propid:
                    winner_target.copy_driver_state(first_target)
            self.last_winner_target = winner_target.get_copy()
        else:
            self.last_winner_target = self.nulltarget

        return self.last_winner_target

    def register_observation(self, observation):

        target_list = []
        if observation.targetid > 0:
            if self.observation_fulfills_target(observation, self.last_winner_target):
                observation = self.last_winner_target
            else:
                self.log.info("register_observation: unexpected observation %s" % str(observation))

            for prop in self.science_proposal_list:
                target = prop.register_observation(observation)
                if target is not None:
                    target_list.append(target)

        self.last_observation = observation.get_copy()
        if self.last_observation.is_deep_drilling and (self.last_observation.remaining_dd_visits > 1):
            self.deep_drilling_target = self.last_observation
        else:
            self.deep_drilling_target = None

        return target_list

    def compute_slewtime_cost(self, slewtime):

        cost = (self.params.timecost_k / (slewtime + self.params.timecost_dt) -
                self.params.timecost_dc - self.params.timecost_cref) / (1.0 - self.params.timecost_cref)
        #cost = self.params.timecost_k / (slewtime + self.params.timecost_dt) - self.params.timecost_dc

        return cost

    def compute_filterchange_cost(self):

        t = self.observatoryModel.get_delta_last_filterchange()
        T = self.observatoryModel.params.filter_max_changes_avg_interval
        if t < T:
            cost = 1.0 - t / T
        else:
            cost = 0.0

        return cost

    def observation_fulfills_target(self, observ, target):

        return (observ.fieldid == target.fieldid) and (observ.filter == target.filter)
コード例 #3
0
class TestFeatureSchedulerTarget(unittest.TestCase):
    def setUp(self) -> None:

        self.observatory_model = ObservatoryModel()
        self.observatory_model.configure_from_module()

        start_time = Time(59853.983, format="mjd", scale="tai")

        self.observatory_model.update_state(start_time.unix)

        return super().setUp()

    def test_constructor(self):

        observation = self.make_fbs_observation(note="std")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
        )

        slew_time, error = self.observatory_model.get_slew_delay(target)

        self.assertEqual(error, 0)
        self.assertGreater(slew_time, 0.0)

    def test_get_script_config(self):

        observation = self.make_fbs_observation(note="std")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
        )

        script_config_expected = {
            "targetid":
            target.targetid,
            "band_filter":
            target.filter,
            "ra":
            Angle(float(observation["RA"][0]),
                  unit=units.rad).to_string(unit=units.hourangle, sep=":"),
            "dec":
            Angle(float(observation["dec"][0]),
                  unit=units.rad).to_string(unit=units.degree, sep=":"),
            "name":
            observation["note"][0],
            "program":
            observation["note"][0].rsplit("_", maxsplit=1)[0],
            "rot_sky":
            target.ang,
            "obs_time":
            target.obs_time,
            "num_exp":
            target.num_exp,
            "exp_times":
            target.exp_times,
            "estimated_slew_time":
            target.slewtime,
        }

        script_config_yaml = target.get_script_config()

        script_config_unpacked = yaml.safe_load(script_config_yaml)

        self.assertEqual(script_config_expected, script_config_unpacked)

    def test_get_script_config_cwfs(self):

        observation = self.make_fbs_observation(note="cwfs")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
        )

        script_config_expected = dict(find_target=dict(
            az=math.degrees(float(observation["az"][0])),
            el=math.degrees(float(observation["alt"][0])),
        ))

        script_config_yaml = target.get_script_config()

        script_config_unpacked = yaml.safe_load(script_config_yaml)

        self.assertEqual(script_config_expected, script_config_unpacked)

    def test_get_script_config_cwfs_with_additional_config(self):

        observation = self.make_fbs_observation(note="cwfs")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
            script_configuration_cwfs=dict(filter="SDSSg", grating="empty_1"),
        )

        script_config_expected = dict(
            find_target=dict(
                az=math.degrees(float(observation["az"][0])),
                el=math.degrees(float(observation["alt"][0])),
            ),
            filter="SDSSg",
            grating="empty_1",
        )

        script_config_yaml = target.get_script_config()

        script_config_unpacked = yaml.safe_load(script_config_yaml)

        self.assertEqual(script_config_expected, script_config_unpacked)

    def test_get_script_config_spec(self):

        observation = self.make_fbs_observation(note="spec:HD12345")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
        )

        script_config_expected = {
            "object_name":
            observation["note"][0],
            "object_dec":
            Angle(float(observation["dec"][0]),
                  unit=units.rad).to_string(unit=units.degree, sep=":"),
            "object_ra":
            Angle(float(observation["RA"][0]),
                  unit=units.rad).to_string(unit=units.hourangle, sep=":"),
        }

        script_config_yaml = target.get_script_config()

        script_config_unpacked = yaml.safe_load(script_config_yaml)

        self.assertEqual(script_config_expected, script_config_unpacked)

    def test_get_script_config_spec_with_additional_config(self):

        observation = self.make_fbs_observation(note="spec:HD12345")

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observation,
            script_configuration_spec=dict(
                filter_sequence=["SDSSg", "SDSSg"],
                grating_sequence=["empty_1", "empty_1"],
            ),
        )

        script_config_expected = {
            "object_name":
            observation["note"][0],
            "object_dec":
            Angle(float(observation["dec"][0]),
                  unit=units.rad).to_string(unit=units.degree, sep=":"),
            "object_ra":
            Angle(float(observation["RA"][0]),
                  unit=units.rad).to_string(unit=units.hourangle, sep=":"),
            "filter_sequence": ["SDSSg", "SDSSg"],
            "grating_sequence": ["empty_1", "empty_1"],
        }

        script_config_yaml = target.get_script_config()

        script_config_unpacked = yaml.safe_load(script_config_yaml)

        self.assertEqual(script_config_expected, script_config_unpacked)

    def test_get_script_config_multiple_observations(self):

        filter_obs = "gri"
        observations = self.make_fbs_observation("std", filter_obs=filter_obs)

        target = FeatureSchedulerTarget(
            observing_script_name="observing_script",
            observing_script_is_standard=True,
            observation=observations,
        )

        slew_time, error = self.observatory_model.get_slew_delay(target)

        script_config = yaml.safe_load(target.get_script_config())

        self.assertEqual(len(script_config["exp_times"]), len(filter_obs) * 2)
        for filter_name in filter_obs:
            self.assertIn(filter_name, script_config["band_filter"])

        self.assertEqual(error, 0)
        self.assertGreater(slew_time, 0.0)

    def make_fbs_observation(self, note, filter_obs="r"):

        observations = np.concatenate(
            [empty_observation() for _ in range(len(filter_obs))])

        ra, dec, _ = self.observatory_model.altaz2radecpa(
            self.observatory_model.dateprofile, 65.0, 180.0)
        for obs_filter, observation in zip(filter_obs, observations):
            observation["RA"] = ra
            observation["dec"] = dec
            observation["mjd"] = self.observatory_model.dateprofile.mjd
            observation["filter"] = obs_filter
            observation["exptime"] = 30.0
            observation["nexp"] = 2
            observation["note"] = note

        return observations
コード例 #4
0
ファイル: driver.py プロジェクト: lsst-ts/ts_scheduler
class Driver(object):
    def __init__(self):
        self.log = logging.getLogger("schedulerDriver")

        self.params = DriverParameters()
        self.location = ObservatoryLocation()

        self.observatoryModel = ObservatoryModel(self.location, WORDY)
        self.observatoryModel2 = ObservatoryModel(self.location, WORDY)
        self.observatoryState = ObservatoryState()

        self.sky = AstronomicalSkyModel(self.location)

        self.propid_counter = 0
        self.night = 0
        self.start_time = 0.0
        self.time = 0.0
        self.targetid = 0
        self.survey_started = False
        self.isnight = False
        self.sunset_timestamp = 0.0
        self.sunrise_timestamp = 0.0
        self.survey_duration_DAYS = 0.0
        self.survey_duration_SECS = self.survey_duration_DAYS * 24 * 60 * 60.0
        self.darktime = False
        self.mounted_filter = ""
        self.unmounted_filter = ""
        self.midnight_moonphase = 0.0

        self.nulltarget = Target()
        self.nulltarget.targetid = -1
        self.nulltarget.num_exp = 1
        self.nulltarget.exp_times = [0.0]
        self.nulltarget.num_props = 1
        self.nulltarget.propid_list = [0]
        self.nulltarget.need_list = [0.0]
        self.nulltarget.bonus_list = [0.0]
        self.nulltarget.value_list = [0.0]
        self.nulltarget.propboost_list = [1.0]

        self.last_winner_target = self.nulltarget.get_copy()
        self.deep_drilling_target = None

        self.need_filter_swap = False
        self.filter_to_unmount = ""
        self.filter_to_mount = ""

        self.cloud = 0.0
        self.seeing = 0.0

    def configure_scheduler(self, **kwargs):
        raise NotImplemented

    def configure_duration(self, survey_duration):

        self.survey_duration_DAYS = survey_duration
        self.survey_duration_SECS = survey_duration * 24 * 60 * 60.0

    def configure(self, confdict):
        self.params.configure(confdict)
        self.log.log(WORDY,
                     "configure: night_boundary=%.1f" % (self.params.night_boundary))

    def configure_location(self, confdict):

        self.location.configure(confdict)
        self.observatoryModel.location.configure(confdict)
        self.observatoryModel2.location.configure(confdict)
        self.sky.update_location(self.location)

    def configure_observatory(self, confdict):
        """This method calls the configure()method in ObservatoryModel class,
        which configures all its submodules. When initializing one can issue
        a call to this method with a complete set of parameters on confdict.

        Parameters
        ----------
        confdict : dict()

        Returns
        -------
        None
        """
        self.observatoryModel.configure(confdict)
        self.observatoryModel2.configure(confdict)

    def configure_telescope(self, confdict):

        self.observatoryModel.configure_telescope(confdict)
        self.observatoryModel2.configure_telescope(confdict)

    def configure_rotator(self, confdict):

        self.observatoryModel.configure_rotator(confdict)
        self.observatoryModel2.configure_rotator(confdict)

    def configure_dome(self, confdict):

        self.observatoryModel.configure_dome(confdict)
        self.observatoryModel2.configure_dome(confdict)

    def configure_optics(self, confdict):

        self.observatoryModel.configure_optics(confdict)
        self.observatoryModel2.configure_optics(confdict)

    def configure_camera(self, confdict):

        self.observatoryModel.configure_camera(confdict)
        self.observatoryModel2.configure_camera(confdict)

    def configure_slew(self, confdict):

        self.observatoryModel.configure_slew(confdict)
        self.observatoryModel2.configure_slew(confdict)

    def configure_park(self, confdict):

        self.observatoryModel.configure_park(confdict)
        self.observatoryModel2.configure_park(confdict)

    def start_survey(self, timestamp, night):
        """This method begins the survey.

        Parameters
        ----------
        timestamp : float
        night : int

        Returns
        -------
        None
        """
        self.start_time = timestamp

        self.log.info("start_survey t=%.6f" % timestamp)

        self.survey_started = True
        self.sky.update(timestamp)
        (sunset, sunrise) = self.sky.get_night_boundaries(self.params.night_boundary)
        self.log.debug("start_survey sunset=%.6f sunrise=%.6f" % (sunset, sunrise))
        # if round(sunset) <= round(timestamp) < round(sunrise):
        if sunset <= timestamp < sunrise:
            self.start_night(timestamp, night)

        self.sunset_timestamp = sunset
        self.sunrise_timestamp = sunrise

    def end_survey(self):
        """This method ends the survey.

        Parameters
        ----------
        None

        Returns
        -------
        None
        """
        self.log.info("end_survey")

    def start_night(self, timestamp, night):
        """This method is called once per night before observations begin.
        It is not called if the observatory is undergoing downtime.
        Parameters
        ----------
        timestamp : float
        night : int

        Returns
        -------
        None
        """
        timeprogress = (timestamp - self.start_time) / self.survey_duration_SECS
        self.log.info("start_night t=%.6f, night=%d timeprogress=%.2f%%" %
                      (timestamp, night, 100 * timeprogress))

        self.isnight = True

    def end_night(self, timestamp, night):
        """This method is called once per night after observing completes.

        Parameters
        ----------
        timestamp : float
        night : int

        Returns
        -------
        None
        """
        pass

    def swap_filter(self, filter_to_unmount, filter_to_mount):

        self.log.info("swap_filter swap %s=>cam=>%s" % (filter_to_mount, filter_to_unmount))

        self.observatoryModel.swap_filter(filter_to_unmount)

        self.unmounted_filter = filter_to_unmount
        self.mounted_filter = filter_to_mount

        return

    def update_time(self, timestamp, night):
            self.time = timestamp
            self.observatoryModel.update_state(self.time)
            if not self.survey_started:
                self.start_survey(timestamp, night)

            if self.isnight:
                # if round(timestamp) >= round(self.sunrise_timestamp):
                if timestamp >= self.sunrise_timestamp:
                    self.end_night(timestamp, night)
            else:
                # if round(timestamp) >= round(self.sunset_timestamp):
                if timestamp >= self.sunset_timestamp:
                    self.start_night(timestamp, night)
            return self.isnight

    def get_need_filter_swap(self):
        """When scheduler determines that a filter swap is needed,
        this shall return a tuple where the first element is a TRUE value,
        and the second and third elements are single-character strings identifying
        which filter to remove from the carousel, and which filter to add, respectively.

        Parameters
        ----------
        None

        Returns
        -------
        Tuple (bool, str, str)
        """
        return (self.need_filter_swap, self.filter_to_unmount, self.filter_to_mount)

    def update_internal_conditions(self, observatory_state, night):

        if observatory_state.unmountedfilters != self.observatoryModel.current_state.unmountedfilters:
            unmount = observatory_state.unmountedfilters[0]
            mount = self.observatoryModel.current_state.unmountedfilters[0]
            self.swap_filter(unmount, mount)
        self.time = observatory_state.time
        self.observatoryModel.set_state(observatory_state)
        self.observatoryState.set(observatory_state)

    def update_external_conditions(self, cloud, seeing):

        self.cloud = cloud
        self.seeing = seeing

        return

    def cold_start(self, observations):
        """Rebuilds the internal state of the scheduler from a list of observations.

        Parameters
        ----------
        observations : list of Observation objects

        Returns
        -------
        None
        """
        raise NotImplemented

    def select_next_target(self):
        """Picks a target and returns it as a target object.

        Parameters
        ----------
        None

        Returns
        -------
        Target
        """

        raise NotImplemented

    def register_observation(self, observation):
        """Validates observation and returns a list of successfully completed observations.

        Parameters
        ----------
        observation : Observation or a python list of Observations

        Returns
        -------
        Python list of one or more Observations
        """

        raise NotImplemented