coherent_score_hm_search.compute_coherent_scores#

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Summary#

Signature#

def compute_coherent_scores(cs_instance, coincident_trig_list, trig1, trig2, minimal_time_slide_jump = 0.1, score_reduction_timeseries = 10, output_timeseries = False, output_coherent_score = True, coh_score_iterations = 1, return_inputs = False)

Input variables#
Name	Type	Default	Description
`cs_instance`			instance of SearchCoherentScoreHMAS
`coincident_trig_list`			list of coincident triggers
`trig1`			trigger object for detector 1
`trig2`			trigger object for detector 2
`minimal_time_slide_jump`		0.1	minimal time slide jump
`score_reduction_timeseries`		10
`output_timeseries`		False
`output_coherent_score`		True
`coh_score_iterations`		1	to improve convergence, one could average over multiple iterations of the coherent score calculation
`return_inputs`		False	for debugging purposes, return the inputs to the coherent score calculation (only for the first trigger in the list)

Output variables#

Return annotation	Docstring type	Description
`None`

Docstring#

:param cs_instance: instance of SearchCoherentScoreHMAS
:param coincident_trig_list: list of coincident triggers
:param trig1: trigger object for detector 1
:param trig2: trigger object for detector 2
:param minimal_time_slide_jump: minimal time slide jump
:param score_reduction_timeseries:
:param output_timeseries:
:param output_coherent_score:
:param coh_score_iterations: to improve convergence, one could average
        over multiple iterations of the coherent score calculation
:param return_inputs: for debugging purposes, return the inputs to the
        coherent score calculation (only for the first trigger in the list)