template_bank_generator_HM.TemplateBank.marginalized_HM_scores

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Summary

The scores obtained from triggering can sometimes be unphysical ,e.g., \|Z_33\|>>\|Z_22\| (here Z=complex rho timeseries) This function marginalizes or maximizes over inclination and mass ratio for HMs

Signature

def marginalized_HM_scores(self, triggers, input_Z = False, marginalized = True, Rij_samples = None, single_det = True, calpha = None, N_det_effective = 2, **kwargs)

Input variables

Name	Type	Default	Description
triggers			if input_Z: array with ntriggers x [Z22, Z33, Z44] else: if single_det: array with ntriggers x processedclist else: array with n_det x processedclist (only implemented for n_triggers=1)
input_Z		False
marginalized		True	marginalizing instead of maximizing
Rij_samples		None
single_det		True	Boolean flag for multi-detector case
calpha		None	[c0,c1,…] array (in case Norm Flow is implemented in the future)
N_det_effective		2	if single_det=True, how many times to multiply the likelihood in single det case by corresponding to the likelihood expected from other detectors in an optimistic scenario.
\*\*kwargs

Output variables

Return annotation	Docstring type	Description
None		if marginalized: return Z^2_marginalized (size: ntriggers) else: ntriggers x [Z22, Z33, Z44] array where Z are complex overlaps corresponding to max lnL physical sample

Docstring

The scores obtained from triggering can sometimes be unphysical
,e.g., |Z_33|>>|Z_22| (here Z=complex rho timeseries)
This function marginalizes or maximizes over inclination and mass ratio for HMs
:param triggers:
    if input_Z:
            array with ntriggers x [Z22, Z33, Z44]
    else:
        if single_det:
            array with ntriggers x processedclist
        else:
            array with n_det x processedclist (only implemented for n_triggers=1)
:param marginalized: marginalizing instead of maximizing
:param single_det: Boolean flag for multi-detector case
:param calpha: [c0,c1,...] array (in case Norm Flow is implemented in the future)
:param N_det_effective: if single_det=True, how many times to multiply the
        likelihood in single det case by  corresponding to the likelihood
        expected from other detectors in an optimistic scenario.
:return: if marginalized: return Z^2_marginalized (size: ntriggers)
         else: ntriggers x [Z22, Z33, Z44] array
                 where Z are complex overlaps corresponding
                 to max lnL physical sample