Priors

pyLIMA.priors.guess.initial_guess_DSPL(event)

Function to find initial DSPL guess

Parameters:

event (object, an event object)

Returns:

• guess_model (list, [t0,u0,delta_t0,delta_u0,tE,q_flux] the DSPL guess)

• fs_guess (float, the source flux guess)

pyLIMA.priors.guess.initial_guess_FSPL(event)

Function to find initial FSPL guess, i.e. PSPL guess + rho = 0.05

Parameters:

event (object, an event object)

Returns:

• guess_model (list, [t0,u0,tE,rho] the FSPL guess)

• fs_guess (float, the source flux guess)

pyLIMA.priors.guess.initial_guess_FSPLarge(event)

Function to find initial FSPL guess, i.e. PSPL guess + rho = 0.05

Parameters:

event (object, an event object)

Returns:

• guess_model (list, [t0,u0,tE,rho] the FSPL guess)

• fs_guess (float, the source flux guess)

pyLIMA.priors.guess.initial_guess_PSPL(event)

Function to find initial PSPL guess. This assumes no blending.

Parameters:

event (object, an event object)

Returns:

• guess_model (list, [t0,u0,tE] the PSPL guess)

• fs_guess (float, the source flux guess)

pyLIMA.priors.parameters_boundaries.parameters_boundaries(event, model_dictionnary)

Function to find initial DSPL guess

Parameters:

• event (object, an event object)

• model_dictionnary (dict, a dictionnary containing the parameetrs)

Returns:

bounds

Return type:

list, [[bound_min,bound_max]_i] for all i parameters

pyLIMA.priors.parameters_priors.default_parameters_priors(fit_parameters)

Function to return default priors on parameters (i.e. uniform)

Parameters:

fit_parameters (dict, a dictionnary containing the parameters bounds)

Returns:

priors

Return type:

dict, {‘i’:prior_i} for all i parameters