API
Fitting in the Graphical User Interface (GUI)
allesfitter.GUI()
Input:
- None
Returns:
- None
Outputs:
- Depends on what you do with it. Most likely you will create the settings file, the params file, and run the fit.
Fitting in Python
allesfitter.show_initial_guess(datadir, do_logprint=True, do_plot=True, return_figs=False)
Input:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
- do_logprint: bool (default: True)
If True, it will save a logfile.
- do_plot: bool (default: True)
If True, it will make and save the plots.
- return_figs: bool (default: True)
If True, it will it will return a list of the figure objects.
Returns:
- If return_figs is True, then it will return a list of figure objects that were plotted.
Outputs:
- Creates initial guess plots and a logfile in the given directory path
allesfitter.mcmc_fit(datadir)
Input:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
Returns:
- A German saying.
Outputs:
- Creates the file 'mcmc_save.h5' and a logfile in the given directory path
allesfitter.mcmc_output(datadir)
Input:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
Returns:
- A nerdy quote.
Outputs:
- Creates all output plots and a logfile in the given directory path
allesfitter.ns_fit(datadir)
Input:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
Returns:
- A German saying.
Outputs:
- Creates the file 'ns_save.pickle' and a logfile in the given directory path
allesfitter.ns_output(datadir)
Input:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
Returns:
- A nerdy quote.
Outputs:
- Creates all output plots and a logfile in the given directory path
Post-processing in Python
allesfitter.ns_plot_bayes_factors(datadirs, labels=None, return_logZ=False)
Input:
- datadirs: list of str
A list of all the directory paths to be compared, for example ['allesfit_circular', 'allesfit_eccentric']
- labels: list of str (default: None)
If given, this will set the plot labels accordingly. Otherwise, the datadir names will be used.
- return_logZ: bool (default: False)
If True, it will it will return a list of the Bayesian evidences, log Z, of all model fits
Returns:
- If return_figs is True, then it will return a list of figure objects that were plotted.
Outputs:
- Creates a histogram plot comparing all the Bayes factors between different model fits
allesclass
CLASS allesfitter.allesclass(datadir)
Inputs:
- datadir: str
The directory path, for example 'Users/JohnWayne/Science/allesfit'
Attributes:
- fulldata
A dictionary with the full data set that was loaded.
- data
A dictionary with the data set that was used for the fit. This means, if fast_fit was used and out-of-transit data was neglected, it will not show up here.
- settings
A dictionary of all settings.
- initial_guess_samples
A 2d numpy array with all initial guess parameters
- initial_guess_params_median
A dictionary with all initial guess parameters
- params_star
A dictionary with the stellar parameters (if any were given)
- external_priors
A dictionary with all external parameters (if any were given)
- posterior_samples
A 2d numpy array with all posterior parameters
- posterior_samples_at_maximum_likelihood
A 1d numpy array with all posterior parameters at the highest maximum likelihood step in the entire sampling
- posterior_params
A dictionary with all posterior parameters
- posterior_params_median
A dictionary with the medians of all posterior parameters
- posterior_params_ll
A dictionary with the lower errors of all posterior parameters
- posterior_params_ul
A dictionary with the upper errors of all posterior parameters
- posterior_params_at_maximum_likelihood
A dictionary with all posterior parameters at the highest maximum likelihood step in the entire sampling
- posterior_derived_params
A dictionary of all the derived parameters
Methods:
- plot(inst, companion, style, fig=None, ax=None, mode='posterior', Nsamples=20, samples=None, timelabel='Time', rasterized=True, marker='.', linestyle='none', color='b', markersize=8)
- get_initial_guess_model(inst, key, xx=None, phased=False)
- get_initial_guess_baseline(inst, key, xx=None, model=None, phased=False)
- get_initial_guess_stellar_var(self, inst, key, xx=None, phased=False)
- get_posterior_median_model(inst, key, xx=None, phased=False)
- get_posterior_median_baseline(inst, key, xx=None, model=None, phased=False)
- get_posterior_median_stellar_var(inst, key, xx=None, phased=False)
- get_posterior_median_residuals(inst, key)
- get_posterior_median_yerr(inst, key)
- get_one_posterior_curve_set(inst, key, xx=None, sample_id=None, phased=False)
- get_one_posterior_model(inst, key, xx=None, sample_id=None, phased=False)
- get_one_posterior_baseline(inst, key, xx=None, sample_id=None, phased=False)
- get_one_posterior_stellar_var(inst, key, xx=None, sample_id=None, phased=False)
Injection recovery tests
from allesfitter.transit_search.injection_recovery_test import inject_and_tls_search
inject_and_tls_search(time, flux, flux_err,
periods, rplanets, logfname,
SNR_threshold=5.,
known_transits=None,
R_star=0.13, R_star_min=1., R_star_max=3.5,
M_star=0.1, M_star_min=1., M_star_max=1.,
show_plot=False, save_plot=False)
Summary:
- Injects a planet signal via ellc, for a given period and radius (at random epoch)
- Runs TLS on these injected data and infos
Input:
- time : array of float
time stamps of observations
- flux : array of float
normalized flux
- flux_err : array of float
error of normalized flux
- periods : float or array of float
a period or list of periods for injections
- rplanets : float or array of float
a planet radius or list of planet radii for injections
- logfname : str
file path and name for the log file
- SNR_threshold : float
the SNR threshold at which to stop the TLS search
- known_transits : None or dict
if dict and one transit is already known:
known_transits = {'period':[1.3], 'duration':[2.1], 'epoch':[245800.0]}
if dict and multiple transits are already known:
known_transits = {'period':[1.3, 21.0], 'duration':[2.1, 4.1], 'epoch':[245800.0, 245801.0]}
'period' is the period of the transit
'duration' must be the total duration, i.e. from first ingress point to last egrees point, in days
'epoch' is the epoch of the transit
- R_star : float
radius of the star (e.g. median)
default 1 R_sun (from TLS)
- R_star_min : float
minimum radius of the star (e.g. 1st percentile)
default 0.13 R_sun (from TLS)
- R_star_max : float
maximum radius of the star (e.g. 99th percentile)
default 3.5 R_sun (from TLS)
- M_star : float
mass of the star (e.g. median)
default 1. M_sun (from TLS)
- M_star_min : float
minimum mass of the star (e.g. 1st percentile)
default 0.1 M_sun (from TLS)
- M_star_max : float
maximum mass of the star (e.g. 99th percentile)
default 1. M_sun (from TLS)
- show_plot : bool
show a plot in the terminal or not
- save_plot : bool
save a plot or not
Returns:
- None
Outputs:
- A list of all TLS results will get saved to a log file
Internal nomenclature: time series
On the observation time grid:
- time
- flux
- flux_err
- rv
- rv_err
- model_flux
- model_rv
On a phase-folded grid:
- phi
On a phase-folded and binned time grid:
- phase
- phaseflux
- phaseflux_err
- phaserv
- phaserv_err
- model_phaseflux
- model_phaserv
On a finely interpolated observation time grid (for plots):
- time_grid
- model_flux_grid
- model_rv_grid
On a finely interpolated phase-folded grid (for plots):
- phase_grid
- model_phaseflux_grid
- model_phaserv_grid
Internal nomenclature: parameters
Model parameter abbreviations:
- rr: radius of the companion divided by radius of the host [unit-less]
- rsuma: radius of the companion plus radius of the host divided by the semi-major axis [unit-less]
- epoch: transit/eclipse epoch [in days]
- period: orbital period [in days]
- cosi: cosine of the inclination [unit-less]
- K: RV semi-amplitude [in km/s]
- f_c: sqrt(ecc) * cos(omega) [unit-less]
- f_s: sqrt(ecc) * sin(omega) [unit-less]
- sbratio: surface brightness ratio [unit-less]
- dil: dilution, defined as D_0 = 1 - (F_target / (F_target + F_blend)) [unit-less]
Other abbreviations:
- incl: inclination in degree
- ecc: eccentricity
- omega: argument of periastron in degree
- a: semi-major axis in AU
- ldc: list of the limb darkening parameters in u-space
- ld: limb darkening law
Dictionary keywords:
- R_companion/a: radius of the companion divided by the semi-major axis [unit-less]
- R_host/a: radius of the host divided by the semi-major axis [unit-less]
- R_companion: radius of the companion [in R_earth or R_jupiter]
- R_host: radius of the host [in R_sun]