likelihoods module

Module with classes to define log likelihoods and log-likelihood ratios for given datasets and errors.

class pbarlike.likelihoods.LogLikeRatios(drn, chi_squares, sol_mod, verbose=False)

Bases: object

Class with methods defining log-likelihood ratios using correlated and uncorrelated errors.

Parameters:

• drn (object) – Object of class DRNet

• chi_squares (object) – Object of class LogLikes

• sol_mod (object) – Eg. Force field approximation

del_chi2_corr(phi_DMCR)

Calculates difference of marginalized chi-squared values between cases of with and without DM; using the total covariance matrix including correlated and uncorrelated errors.

del_chi2_uncorr(phi_DMCR)

Calculates difference of marginalized chi-squared values between cases of with and without DM; using the only uncorrelated errors.

class pbarlike.likelihoods.LogLikes(data, propagation_config, errors='correlated', verbose=False)

Bases: object

Class with methods defining chi-squared functions using correlated and uncorrelated errors.

Parameters:

• data (object) – Data object that contains data correlations and uncorrelated errors (Eg: AMS-02 Data)

• propagation_config (object) – Object of class Propagation

chi2_corr(phi_pred)

Chi-squared function including data covariance

chi2_uncorr(phi_pred)

Chi-squared function with only uncorrelated data errors; same as the one used to sample propagation parameters contained in the multinest sample.