CONAN._classes.fit_setup

CONAN._classes.fit_setup#

class CONAN._classes.fit_setup(R_st=None, M_st=None, par_input='Rrho', apply_LCjitter='y', apply_RVjitter='y', apply_LC_GPndim_jitter='y', apply_RV_GPndim_jitter='y', apply_LC_GPndim_offset='y', apply_RV_GPndim_offset='y', LCjitter_loglims='auto', RVjitter_lims='auto', LCbasecoeff_lims='auto', RVbasecoeff_lims='auto', leastsq_for_basepar='n', LTT_corr='n', verbose=True)#

class to configure mcmc run

Parameters:

  • R_st (tuple of length 2 ;) – stellar radius and mass (in solar units) to use for calculating absolute dimensions. R_st is also used in calculating light travel time correction. Only one of these is needed, preferrably R_st. First tuple element is the value and the second is the uncertainty

  • M_st (tuple of length 2 ;) – stellar radius and mass (in solar units) to use for calculating absolute dimensions. R_st is also used in calculating light travel time correction. Only one of these is needed, preferrably R_st. First tuple element is the value and the second is the uncertainty

  • par_input (str;) – input method of stellar parameters. It can be one of [“Rrho”,”Mrho”], to use the fitted stellar density and one stellar parameter (M_st or R_st) to compute the other stellar parameter (R_st or M_st). Default is ‘Rrho’ to use the fitted stellar density and stellar radius to compute the stellar mass.

  • leastsq_for_basepar ("y" or "n";) – whether to use least-squares fit within the mcmc to fit for the baseline. This reduces the computation time especially in cases with several input files. Default is “n”.

  • apply_RVjitter ("y" or "n";) – whether to apply a jitter term for the fit of RV data. Default is “y”. A List can be given to specify y/n for each RV.

  • apply_LCjitter ("y" or "n";) – whether to apply a jitter term for the fit of LC data. Default is “y”. A List can be given to specify y/n for each LC.

  • LCjitter_loglims ("auto" or list of length 2: [lo_lim,hi_lim];) – log limits of uniform prior for the LC jitter term. Default is “auto” which automatically determines the limits for each lcfile as [-15,log(10*mean(LCerr))].

  • RVjitter_lims ("auto" or list of length 2:[lo_lim,hi_lim];) – limits of uniform prior for the RV jitter term. Default is “auto” which automatically determines the limits for each rvfile as [0,10*mean(RVerr)].

  • LCbasecoeff_lims ("auto" or list of length 2: [lo_lim,hi_lim];) – limits of uniform prior for the LC baseline coefficients default. Default is “auto” which automatically determines the limits from data properties.

  • RVbasecoeff_lims ("auto" or list of length 2: [lo_lim,hi_lim];) – limits of uniform prior for the RV baseline coefficients. Dafault is “auto” which automatically determines the limits from data properties.

  • LTT_corr ("y" or "n";) – whether to apply light travel time correction to the LC data. Default is “n”.

  • apply_LC_GPndim_jitter ("y" or "n";) – whether to apply a jitter term for each of the timeseries in the spleaf multi-dim GP fit. Default is “y”. A List can be given to specify y/n for each LC.

  • apply_RV_GPndim_jitter ("y" or "n";) – whether to apply a jitter term for each of the timeseries in the spleaf multi-dim GP fit. Default is “y”. A List can be given to specify y/n for each timeseries.

  • apply_LC_GP_ndim_offset ("y" or "n";) – whether to apply an offset for each of the LC timeseries in the spleaf multi-dim GP

  • apply_RV_GP_ndim_offset ("y" or "n";) – whether to apply an offset for each of the RV timeseries in the spleaf multi-dim GP

  • verbose (bool;) – print output. Default is True.

  • or (Other keyword arguments to the emcee or dynesty sampler functions (run_mcmc())

  • CONAN.run_fit(). (run_nested()) can be given in the call to)

_obj_type#

type of object. Default is “fit_obj”

Type:

str;

_lcobj#

light curve object. Default is None.

Type:

lc_obj;

_rvobj#

RV object. Default is None.

Type:

rv_obj;

_stellar_parameters#

method to compute stellar parameters.

Type:

method;

_fit_dict#

dictionary of fit configuration

Type:

dict;

Returns:

fit_obj

Return type:

fit object

Examples

>>> fit_obj = CONAN.fit_setup(  R_st            = (1,0.01),
>>>                             M_st            = (1,0.01),
>>>                             par_input       = "Rrho",
>>>                             apply_LCjitter  = "y",
>>>                             apply_RVjitter  = "y")
>>> fit_obj.sampling(   sampler = "emcee",
>>>                     ncpus   = 2,
>>>                     n_chains= 64,
>>>                     n_steps = 2000,
>>>                     n_burn  = 500)
_fit_dict#
_fitobj#
_lcobj#
_obj_type = 'fit_obj'#
_rvobj#

Methods#

_stellar_parameters([R_st, M_st, par_input, verbose])

input parameters of the star

print([section])

sampling([sampler, n_cpus, n_chains, n_steps, n_burn, ...])

configure sampling
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