gravelamps.likelihood.joint

Implementations of joint likelihoods for strongly lensed gravitational wave signals.

class gravelamps.likelihood.joint.JointGWTransientPair(first_image_interferometers: InterferometerList, second_image_interferometers: InterferometerList, first_image_generator: SingleImageGenerator, second_image_generator: SingleImageGenerator, priors: PriorDict = None)

Bases: Likelihood

Implementation of the model specific joint likelihood computation for a pair of strongly lensed gravitational wave events.

Attributes:

first_image_interferometers: Union[InterferometerList, Interferometer]

Interferometer data for the first image.

second_image_interferometers: Union[InterferometerList, Interferometer]

Interferometer data for the second image.

first_image_generator: SingleImageGenerator

Waveform generator for the first image type.

second_image_generator: SingleImageGenerator

Waveform generator for the second image type.

priors: PriorDict, optional, default=None

Priors for the pair.

Methods

calculate_snrs(waveform_polarisations, ...)	Calculate the SNR for a detector.
log_likelihood()	Compute the log likelihood for the event pair.
log_likelihood_per_image(...)	Calculate the contribution to the log likelihood from an individual image.
log_likelihood_ratio()	Compute the log likelihood ratio for the two lensed images.
noise_log_likelihood()	Compute the noise log likelihood for the two images at the same time.

calculate_snrs(waveform_polarisations: dict, interferometer: Interferometer, parameters: dict) → _CalculatedSNRs

Calculate the SNR for a detector.

Parameters:

waveform_polarisations: dict

Dictionary containing polarisation mode data for the waveform.

interferometer: Interferometer

Interferometer data for signal.

parameters: dict

Parameters of the signal.

log_likelihood() → float

Compute the log likelihood for the event pair.

log_likelihood_per_image(waveform_polarisations: dict, interferometers: InterferometerList, parameters: dict) → float

Calculate the contribution to the log likelihood from an individual image.

Parameters:

waveform_polarisations: dict

Dictionary containing polarisation mode data for the waveform.

interferometers: InterferometerList

Interferometer data for the signal.

parameters: dict

Parameter values.

log_likelihood_ratio() → float

Compute the log likelihood ratio for the two lensed images.

noise_log_likelihood() → float

Compute the noise log likelihood for the two images at the same time.

property priors: PriorDict

Priors on the parameters of the signal.