FeatureScheduler

class lsst.ts.scheduler.driver.FeatureScheduler(models, raw_telemetry, observing_blocks, parameters=None, log=None)

Bases: Driver

Feature scheduler driver.

Attributes Summary

default_observation_database_name

Methods Summary

assert_survey_observing_script(survey_name)	Assert that the input survey name has a dedicated observing script.
cold_start(observations)	Rebuilds the internal state of the scheduler from a list of Targets.
configure_scheduler([config])	This method is responsible for running the scheduler configuration and returning the survey topology, which specifies the number, name and type of projects running by the scheduler.
convert_efd_observations_to_targets(...)	Convert EFD dataframe into list of driver targets.
fbs_observation_named_parameter_map()	Return the mapping between feature scheduler observation parameter keywords and the Observation parameter name keywords
get_state_as_file_object(targets_queue)	Get the current state of the scheduling algorithm as a file object.
get_stop_tracking_target()
get_survey_observing_block(survey_name)	Return the appropriate survey observing block.
get_survey_topology(config)	Get the survey topology.
load(config)	Load a new set of targets.
parse_observation_database(filename)	Parse an observation database into a list of observations.
register_observation(target)	Register observation.
register_observed_target(target)	Validates observation and returns a list of successfully completed observations.
reset_from_state(filename)	Load the state from a file.
save_state()	Save the current state of the scheduling algorithm to a file.
select_next_target()	Pick a target and return it as a target object.
select_next_targets()	Pick a target and return it as a list of target objects.
update_conditions()	Update conditions on the scheduler.

Attributes Documentation

default_observation_database_name = PosixPath('/home/saluser/fbs_observation_database.sql')

Methods Documentation

assert_survey_observing_script(survey_name: str) → None

Assert that the input survey name has a dedicated observing script.

Parameters:

survey_namestr

Name of the survey.

Raises:

AssertError:

If survey_name is not in the list of valid survey observing scripts.

cold_start(observations: List[DriverTarget]) → None

Rebuilds the internal state of the scheduler from a list of Targets.

Parameters:

observationslist of DriverTarget

configure_scheduler(config=None)

This method is responsible for running the scheduler configuration and returning the survey topology, which specifies the number, name and type of projects running by the scheduler.

By default it will just return a test survey topology.

Parameters:

configtypes.SimpleNamespace

Configuration, as described by schema/Scheduler.yaml

Returns:

survey_topology: lsst.ts.scheduler.kernel.SurveyTopology

Raises:

RuntimeError:

If config does not have a scheduler_config attribute or if it points to a non-existing file.

NoSchedulerError:

If scheduler configuration does not define scheduler attribute.

NoNsideError:

If scheduler configuration does not define nside attribute.

convert_efd_observations_to_targets(efd_observations: DataFrame) → List[DriverTarget]

Convert EFD dataframe into list of driver targets.

Parameters:

efd_observationspandas.DataFrame

Data frame returned from a query to the EFD for observations.

static fbs_observation_named_parameter_map() → Dict[str, str]

Return the mapping between feature scheduler observation parameter keywords and the Observation parameter name keywords

Returns:

dict

Mapping between fbs observations keywords and Observation keywords.

get_state_as_file_object(targets_queue: list[lsst.ts.scheduler.driver.feature_scheduler_target.FeatureSchedulerTarget])

Get the current state of the scheduling algorithm as a file object.

Parameters:

targets_queuelist`[`DriverTarget]

A List of targets in the queue to be observed.

Returns:

file_objectio.BytesIO

File object with the current.

get_stop_tracking_target() → DriverTarget

get_survey_observing_block(survey_name: str) → ObservingBlock

Return the appropriate survey observing block.

Parameters:

survey_namestr

Name of the survey.

Returns:

observing.ObservingBlock

Survey observing block.

get_survey_topology(config: SimpleNamespace) → SurveyTopology

Get the survey topology.

Parameters:

configtypes.SimpleNamespace

Configuration, as described by schema/Scheduler.yaml

Returns:

survey_topologySurveyTopology

Survey topology.

load(config)

Load a new set of targets.

parse_observation_database(filename: str) → None

Parse an observation database into a list of observations.

Parameters:

filenamestr

Returns:

observationslist of DriverTarget

register_observation(target: FeatureSchedulerTarget) → None

Register observation.

Write the target observation into the observation database.

Parameters:

targetFeatureSchedulerTarget

Target to register.

register_observed_target(target: DriverTarget) → Observation

Validates observation and returns a list of successfully completed observations.

Add target observation to the feature based scheduler.

Parameters:

observationlist of Target

Python list of Targets observed.

Returns:

Observation

reset_from_state(filename)

Load the state from a file.

Parameters:

filenamestr

Name of the file with the state.

save_state()

Save the current state of the scheduling algorithm to a file.

Returns:

filenamestr

Name of the file with the state.

select_next_target() → FeatureSchedulerTarget

Pick a target and return it as a target object.

Returns:

Target

select_next_targets() → list[lsst.ts.scheduler.driver.feature_scheduler_target.FeatureSchedulerTarget]

Pick a target and return it as a list of target objects.

Instead of requesting a single target like select_next_target, this method will inquire the scheduling algorithm for a list of potential next targets.

Returns:

desired_observations: list`[`FeatureSchedulerTarget]

List of desired observations.

update_conditions()

Update conditions on the scheduler.