Driver¶

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

Bases: object

The Scheduler Driver is the module that normalizes the interface between any scheduling algorithm to the LSST Scheduler CSC. The interface implements three main behaviours; configure an underlying algorithm, request targets and register successful observations.

If the Scheduler algorithm requires a specific set of parameters the user must subclass DriverParameters, in the same module as the Driver, and add the appropriate parameters using the LSST pexConfig module.

Access to the telemetry stream and models are also interfaced by Driver. The full list of default available telemetry data is shown in the scheduler_csc module. Nevertheless, the full list of telemetry may vary depending on the models used. The user has control over this while configuring the Scheduler CSC.

Parameters:

models (dict) – A dictionary with models available for the scheduling algorithm.
raw_telemetry (dict) – A dictionary with available raw telemetry.
observing_blocks (dict[str, observing.ObservingBlock]) – Observing blocks.
parameters (DriverParameters, optional) – Input functional parameters for the scheduling algorithm.
log (Logger) – Parent logger class.

log¶

Logger class.

Type:: Logger

parameters¶

Store functional driver parameters.

Type:: DriverParameters

models¶

Dictionary with models.

Type:: dict

raw_telemetry¶

Dictionary with raw telemetry data.

Type:: dict

target_id¶

Counter of the number of targets generated by the scheduler since it was last instantiated.

Type:: int

observing_blocks¶

Observing blocks.

Type:: dict[str, observing.ObservingBlock]

stop_tracking_script_name¶

Name of a SAL Script that can be used to stop the observatory. This is, in general, queued by the Driver when it fails to select an observation.

Type:: str

stop_tracking_script_is_standard¶

Specify if the stop tracking script is standard.

Type:: bool

is_night¶

Track if it is night time.

Type:: bool

night¶

Count the number of nights from the start of the survey.

Type:: int

current_sunset¶

Timestamp for the current sunset.

Type:: float

current_sunrise¶

Timestamp for the current sunrise.

Type:: float

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 observations.
`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.
`get_state_as_file_object`()	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 modifying configuration.
`parse_observation_database`(filename)	Parse an observation database into a list of observations.
`register_observation`(target)	Register observations.
`register_observed_target`(target)	Validates observed target and returns an observation.
`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`()	Picks a target and returns it as a target object.
`select_next_targets`()	Select a list of targets.
`update_conditions`()	Update driver internal conditions.

Methods Documentation

assert_survey_observing_script(survey_name)¶

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

Parameters:: survey_name (str) – Name of the survey.
Raises:: AssertError: – If survey_name is not in the list of valid survey observing scripts.
Return type:: None

cold_start(observations)¶

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

Parameters:: observations (list`[`Observation]) – List of observations.
Return type:: None

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.

By default it will just return a test survey topology.

Parameters:: config (types.SimpleNamespace) – Configuration, as described by schema/Scheduler.yaml
Returns:: survey_topology – Survey topology.
Return type:: SurveyTopology

convert_efd_observations_to_targets(efd_observations)¶

Convert EFD dataframe into list of driver targets.

Parameters:: efd_observations (pandas.DataFrame) – Data frame returned from a query to the EFD for observations.
Return type:: List[DriverTarget]

get_state_as_file_object()¶

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

Returns:: file_object – File object with the current.
Return type:: io.BytesIO

get_stop_tracking_target()¶

Return type:: DriverTarget

get_survey_observing_block(survey_name)¶

Return the appropriate survey observing block.

Parameters:: survey_name (str) – Name of the survey.
Returns:: Survey observing block.
Return type:: observing.ObservingBlock

get_survey_topology(config)¶

Get the survey topology.

Parameters:: config (types.SimpleNamespace) – Configuration, as described by schema/Scheduler.yaml
Returns:: survey_topology – Survey topology.
Return type:: SurveyTopology

load(config)¶

Load a modifying configuration.

The input is a file that the Driver must be able to parse. It should contain that the driver can parse to reconfigure the current scheduler algorithm. For instance, it could contain new targets to add to a queue or project.

Each Driver must implement its own load method. This method just checks that the file exists.

Parameters:: config (str) – Configuration to load
Raises:: RuntimeError: – If input configuration file does not exists.
Return type:: None

parse_observation_database(filename)¶

Parse an observation database into a list of observations.

Parameters:: filename (str)
Returns:: observations
Return type:: list of DriverTarget

register_observation(target)¶

Register observations.

This method should store the observation in a way that can be retrieved afterwards by the driver.

The default implementation is not implemented.

Parameters:: target (DriverTarget) – Observation to register.
Return type:: None

register_observed_target(target)¶

Validates observed target and returns an observation.

Parameters:: target (DriverTarget) – Observed target to register.
Returns:: Registered observation.
Return type:: Observation

reset_from_state(filename)¶

Load the state from a file.

Parameters:: filename (str)
Return type:: None

save_state()¶

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

Returns:: filename – The name of the file with the state.
Return type:: str

select_next_target()¶

Picks a target and returns it as a target object.

By default it will just return a dummy test target.

Return type:: DriverTarget

select_next_targets()¶

Select a list of targets.

By default it will just return a dummy test target.

Return type:: list [DriverTarget]

update_conditions()¶

Update driver internal conditions.

When subclassing this method, make sure to call it at the start of the method, as it performs operations like running the observatory through the current targets on the queue.

Return type:: None