How to use the bilby.core.likelihood.Likelihood.__init__ function in bilby

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github ColmTalbot / gwpopulation / gwpopulation / View on Github external
Maximum number of samples to use from each set.
        cupy: bool
            If True and a compatible CUDA environment is available,
            cupy will be used for performance.
            Note: this requires setting up your hyper_prior properly.
        if cupy and not CUPY_LOADED:
            logger.warning("Cannot import cupy, falling back to numpy.")

        self.samples_per_posterior = max_samples = self.resample_posteriors(posteriors, max_samples=max_samples)

        if not isinstance(hyper_prior, Model):
            hyper_prior = Model([hyper_prior])
        self.hyper_prior = hyper_prior
        Likelihood.__init__(self, hyper_prior.parameters)

        if sampling_prior is not None:
            raise ValueError(
                "Passing a sampling_prior is deprecated and will be removed "
                "in the next release. This should be passed as a 'prior' "
                "column in the posteriors."
        elif "prior" in
            self.sampling_prior ="prior")
  "No prior values provided, defaulting to 1.")
            self.sampling_prior = 1

        if ln_evidences is not None:
            self.total_noise_evidence = np.sum(ln_evidences)