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

To help you get started, we’ve selected a few bilby examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github ColmTalbot / gwpopulation / gwpopulation / View on Github external
import numpy as np
import pandas as pd
from tqdm import tqdm

from bilby.core.utils import logger
from bilby.core.likelihood import Likelihood
from bilby.hyper.model import Model

from .cupy_utils import CUPY_LOADED, to_numpy, xp

INF = xp.nan_to_num(xp.inf)

class HyperparameterLikelihood(Likelihood):
    A likelihood for inferring hyperparameter posterior distributions with
    including selection effects.

    See Eq. (34) of for a definition.

    posteriors: list
        An list of pandas data frames of samples sets of samples.
        Each set may have a different size.
    hyper_prior: `bilby.hyper.model.Model`
        The population model, this can alternatively be a function.
    sampling_prior: `bilby.hyper.model.Model`
        The sampling prior, this can alternatively be a function.
    log_evidences: list, optional