punchbowl.auto.flows.level2

Attributes

SCIENCE_POLARIZED_LEVEL1_TYPES
SCIENCE_CLEAR_LEVEL1_TYPES

Functions

level2_query_ready_files(session, pipeline_config[, ...])
level2_query_ready_clear_files(session, pipeline_config)
_level2_query_ready_files(session, polarized, ...[, max_n])
group_l2_inputs(...)	Group up L1 inputs into MZP clusters that match in time (i.e. occur sequentially in one image cluster).
group_l2_inputs_single_observatory(...)	For a single observatory, groups up L1 inputs into MZP clusters that match in time (i.e. occur sequentially in one
level2_construct_flow_info(level1_files, level2_file, ...)
level2_construct_file_info(...)
level2_scheduler_flow([pipeline_config_path, session, ...])
level2_clear_scheduler_flow([pipeline_config_path, ...])
level2_call_data_processor(→ dict)
level2_process_flow(flow_id[, pipeline_config_path, ...])
level2_clear_process_flow(flow_id[, ...])

Module Contents

punchbowl.auto.flows.level2.SCIENCE_POLARIZED_LEVEL1_TYPES = ['PM', 'PZ', 'PP']

punchbowl.auto.flows.level2.SCIENCE_CLEAR_LEVEL1_TYPES = ['CR']

punchbowl.auto.flows.level2.level2_query_ready_files(session, pipeline_config: dict, reference_time=None, max_n=9e+99)

punchbowl.auto.flows.level2.level2_query_ready_clear_files(session, pipeline_config: dict, reference_time=None, max_n=9e+99)

punchbowl.auto.flows.level2._level2_query_ready_files(session, polarized: bool, pipeline_config: dict, max_n=9e+99)

punchbowl.auto.flows.level2.group_l2_inputs(files: list[punchbowl.auto.control.db.File]) → list[tuple[punchbowl.auto.control.db.File]]

Group up L1 inputs into MZP clusters that match in time (i.e. occur sequentially in one image cluster).

Handles any combination of missing files, and for each observatory returns only complete MZP triplets

punchbowl.auto.flows.level2.group_l2_inputs_single_observatory(files: list[punchbowl.auto.control.db.File], expected_sequence: list[str] | str, max_separation: float = 80, only_complete=False) → list[tuple[punchbowl.auto.control.db.File]]

For a single observatory, groups up L1 inputs into MZP clusters that match in time (i.e. occur sequentially in one image cluster).

Accepts as input the order of P, Z and M, and handles any combination of missing files

punchbowl.auto.flows.level2.level2_construct_flow_info(level1_files: list[punchbowl.auto.control.db.File], level2_file: punchbowl.auto.control.db.File, pipeline_config: dict, session=None, reference_time=None)

punchbowl.auto.flows.level2.level2_construct_file_info(level1_files: list[punchbowl.auto.control.db.File], pipeline_config: dict, reference_time=None) → list[punchbowl.auto.control.db.File]

punchbowl.auto.flows.level2.level2_scheduler_flow(pipeline_config_path=None, session=None, reference_time=None)

punchbowl.auto.flows.level2.level2_clear_scheduler_flow(pipeline_config_path=None, session=None, reference_time=None)

punchbowl.auto.flows.level2.level2_call_data_processor(call_data: dict, pipeline_config, session=None) → dict

punchbowl.auto.flows.level2.level2_process_flow(flow_id: int | list[int], pipeline_config_path=None, session=None)

punchbowl.auto.flows.level2.level2_clear_process_flow(flow_id: int | list[int], pipeline_config_path=None, session=None)