pipeline.src.flows.risk_factors

Functions

`extract_current_segments`()
`extract_recent_segments`()
`extract_usual_segments`()
`extract_vessels_with_current_vms_fishing_activity`(→ set)
`compute_profile_segments_risk_levels`(→ pandas.DataFrame)
`extract_control_anteriority`()
`merge`(→ pandas.DataFrame)
`compute_risk_factors`(merged_segments, ...)
`load_risk_factors`(risk_factors)	Load the output of `compute_risk_factors` task into `risk_factors` table.
`risk_factors_flow`()

pipeline.src.flows.risk_factors.extract_vessels_with_current_vms_fishing_activity() → set[source]

pipeline.src.flows.risk_factors.compute_profile_segments_risk_levels(profile_segments: pandas.DataFrame, segments: pandas.DataFrame, control_priorities_and_infringement_risk_levels: pandas.DataFrame, profile_type: src.entities.vessel_profiles.VesselProfileType) → pandas.DataFrame[source]

pipeline.src.flows.risk_factors.merge(current_segments: pandas.DataFrame, recent_segments: pandas.DataFrame, usual_segments: pandas.DataFrame) → pandas.DataFrame[source]

pipeline.src.flows.risk_factors.compute_risk_factors(merged_segments: pandas.DataFrame, control_anteriority: pandas.DataFrame, vessels_with_current_vms_fishing_activity: set)[source]

pipeline.src.flows.risk_factors.load_risk_factors(risk_factors: pandas.DataFrame)[source]

Load the output of compute_risk_factors task into risk_factors table.

Parameters:: risk_factors (pd.DataFrame) – output of compute_risk_factors task.