gw.noise.synthetic.asd_sampling.KDE

gw.noise.synthetic.asd_sampling.KDE(parameter_dict, sampling_settings)

Kernel Density Estimation (KDE) class for sampling ASDs.

Parameters

Name	Type	Description	Default
parameter_dict	dict	Dictionary containing the parameters of the ASDs used for fitting the synthetic distribution.	required
sampling_settings	dict	Dictionary containing the settings for the sampling.	required

Attributes

Name	Description
broadband_kde
parameter_dicts
settings
spectral_kde

Methods

Name	Description
fit	Fit the KDEs to the parameters saved in ‘self.parameter_dict’.
sample

fit

gw.noise.synthetic.asd_sampling.KDE.fit(weights=None)

Fit the KDEs to the parameters saved in ‘self.parameter_dict’.

Parameters

Name	Type	Description	Default
weights	array_like	Weights for the KDEs. If None, all weights are set to 1.	None

sample

gw.noise.synthetic.asd_sampling.KDE.sample(num_samples, rescaling_ys=None)

Sample a synthetic ASD dataset from the fitted KDEs

Parameters: num_samples (int): Number of samples to draw. rescaling_ys (dict): Optional dictionary of spline y-values used for rescaling the base noise.