pyLIMA.microlguess

Created on Mon May 23 16:00:51 2016

@author: ebachelet

Module Contents

Functions

initial_guess_PSPL(event)	Function to find initial PSPL guess for Levenberg-Marquardt solver (method==’LM’).
initial_guess_FSPL(event)	Function to find initial FSPL guess for Levenberg-Marquardt solver (method==’LM’).
initial_guess_DSPL(event)	Function to find initial DSPL guess for Levenberg-Marquardt solver (method==’LM’).
differential_evolution_parameters_boundaries(model)	This function define the parameters boundaries for a specific model.
MCMC_parameters_initialization(parameter_key, parameters_dictionnary, parameters)	Generate a random parameter for the MCMC initialization.

pyLIMA.microlguess.initial_guess_PSPL(event)

Function to find initial PSPL guess for Levenberg-Marquardt solver (method==’LM’).

This assumes no blending.

Parameters:event (object) – the event object on which you perform the fit on. More details on the event module. Returns:the PSPL guess for this event. A list of parameters associated to the PSPL model + the source flux of Returns:the PSPL guess for this event. A list of parameters associated to the PSPL model + the source flux of the survey telescope. Return type:list,float

pyLIMA.microlguess.initial_guess_FSPL(event)

Function to find initial FSPL guess for Levenberg-Marquardt solver (method==’LM’).

This assumes no blending.

Parameters:event (object) – the event object on which you perform the fit on. More details on the event module. Returns:the FSPL guess for this event. A list of parameters associated to the FSPL model + the source flux of the survey telescope. Return type:list,float

pyLIMA.microlguess.initial_guess_DSPL(event)

Function to find initial DSPL guess for Levenberg-Marquardt solver (method==’LM’). This assumes no blending.

Parameters:event (object) – the event object on which you perform the fit on. More details on the event module. Returns:the DSPL guess for this event. A list of parameters associated to the DSPL model + the source flux of the survey telescope. Return type:list,float

pyLIMA.microlguess.differential_evolution_parameters_boundaries(model)

This function define the parameters boundaries for a specific model.

Parameters:model (object) – a microlmodels object. Returns:parameters_boundaries, a list of tuple containing parameters limits Return type:list

pyLIMA.microlguess.MCMC_parameters_initialization(parameter_key, parameters_dictionnary, parameters)

Generate a random parameter for the MCMC initialization.

Parameters:

• parameter_key (str) – the parameter on which we apply the function
• parameters_dictionnary (dict) – the dictionnary of parameters keys associared to the parameters input
• parameters (list) – a list of float which indicate the model parameters

Returns:

a list containing the trial(s) associated to the parameter_key string

Return type:

list of float