ranking_HM.add_to_bg_and_fg_dicts#

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Summary#

Populates events in lists of pure background, zero-lag candidates, LSC events, and injected events

Signature#

def add_to_bg_and_fg_dicts(events, loc_id, bg_fg_dicts, extra_arrays = (), separate_lsc_events = True, separate_injections = True, inj_ends = INJECTION_ENDS, inj_starts = INJECTION_STARTS, eps = 4, output_mask_inj = False)

Input variables#
Name	Type	Default	Description
`events`			Array of shape n_events x (n_det=2) x row of processedclist
`loc_id`			Tuple with (chirp_mass_id, subbank ID)
`bg_fg_dicts`			List of dicts with pure background, zero-lag candidates, (and separate LSC events and injected events, if needed)
`extra_arrays`		()	If known, iterable with extra arrays for the events (timeseries, veto_metadata, coherent scores)
`separate_lsc_events`		True	Flag to collect lsc events separately
`separate_injections`		True	Flag to collect injections separately
`inj_ends`		INJECTION_ENDS	Array with end times of injections
`inj_starts`		INJECTION_STARTS	Array with start times of injections
`eps`		4	Tolerance for checking if an event is close to an injection
`output_mask_inj`		False	Flag to output the mask of injected events

Output variables#

Return annotation	Docstring type	Description
`None`		Adds an entry to each dict in bg_fg_dicts with key = loc_id, and item = events, or (events, timeseries) if we have timeseries

Docstring#

Populates events in lists of pure background, zero-lag candidates,
LSC events, and injected events
:param events: Array of shape n_events x (n_det=2) x row of processedclist
:param loc_id: Tuple with (chirp_mass_id, subbank ID)
:param bg_fg_dicts:
    List of dicts with pure background, zero-lag candidates,
     (and separate LSC events and injected events, if needed)
:param extra_arrays:
    If known, iterable with extra arrays for the events
    (timeseries, veto_metadata, coherent scores)
:param separate_lsc_events: Flag to collect lsc events separately
:param separate_injections: Flag to collect injections separately
:param inj_ends: Array with end times of injections
:param inj_starts: Array with start times of injections
:param eps: Tolerance for checking if an event is close to an injection
:param output_mask_inj: Flag to output the mask of injected events
:return:
    Adds an entry to each dict in bg_fg_dicts with key = loc_id, and
    item = events, or (events, timeseries) if we have timeseries