platon package

Submodules

platon.abundance_getter module

class platon.abundance_getter.AbundanceGetter(include_condensates=True)
static from_file()

Reads abundances file in the ExoTransmit format (called “EOS” files in ExoTransmit), returning a dictionary mapping species name to an abundance array of dimension

get(logZ, CO_ratio=0.53)
is_in_bounds(logZ, CO_ratio, T)

platon.constants module

platon.fit_info module

class platon.fit_info.FitInfo(guesses_dict)
add_fit_param(name, low_guess, high_guess, low_lim=None, high_lim=None, value=None)
freeze_fit_param(name, value=None)
generate_rand_param_arrays(num_arrays)
get(name)
get_guess_bounds(index)
get_num_fit_params()
get_param_array()
interpret_param_array(array)
within_limits(array)
class platon.fit_info.FitParam(value, low_guess=None, high_guess=None, low_lim=None, high_lim=None)
within_limits(value)

platon.retriever module

class platon.retriever.Retriever
static get_default_fit_info(g, Rp, T, logZ=0, CO_ratio=0.53, cloudtop_P=1000.0, log_scatt_factor=0, scatt_slope=4, error_multiple=1, add_fit_params=False)
run_emcee(wavelength_bins, depths, errors, fit_info, nwalkers=50, nsteps=10000, include_condensates=True, plot_best=False)

Runs affine-invariant MCMC to retrieve atmospheric parameters.

Parameters:
  • wavelength_bins (array_like, shape (N,2)) – Wavelength bins, where wavelength_bins[i][0] is the start wavelength and wavelength_bins[i][1] is the end wavelength for bin i.
  • depths (array_like, length N) – Measured transit depths for the specified wavelength bins
  • errors (array_like, length N) – Errors on the aforementioned transit depths
  • fit_info (FitInfo object) – Tells the method what parameters to freely vary, and in what range those parameters can vary. Also sets default values for the fixed parameters.
  • nwalkers (int, optional) – Number of walkers to use
  • nsteps (int, optional) – Number of steps that the walkers should walk for
  • include_condensates (bool, optional) – When determining atmospheric abundances, whether to include condensation.
  • plot_best (bool, optional) – If True, plots the best fit model with the data
Returns:

result – This returns emcee’s EnsembleSampler object. The most useful attributes in this item are result.chain, which is a (W x S X P) array where W is the number of walkers, S is the number of steps, and P is the number of parameters; and result.lnprobability, a (W x S) array of log probabilities. For your convenience, this object also contains result.flatchain, which is a (WS x P) array where WS = W x S is the number of samples; and result.flatlnprobability, an array of length WS
Return type:

EnsembleSampler object
run_multinest(wavelength_bins, depths, errors, fit_info, maxiter=None, include_condensates=True, plot_best=False)

Runs nested sampling to retrieve atmospheric parameters.

Parameters:
  • wavelength_bins (array_like, shape (N,2)) – Wavelength bins, where wavelength_bins[i][0] is the start wavelength and wavelength_bins[i][1] is the end wavelength for bin i.
  • depths (array_like, length N) – Measured transit depths for the specified wavelength bins
  • errors (array_like, length N) – Errors on the aforementioned transit depths
  • fit_info (FitInfo object) – Tells us what parameters to freely vary, and in what range those parameters can vary. Also sets default values for the fixed parameters.
  • maxiter (bool, optional) – If not None, run at most this many iterations of nestled sampling
  • include_condensates (bool, optional) – When determining atmospheric abundances, whether to include condensation.
  • plot_best (bool, optional) – If True, plots the best fit model with the data
Returns:

result – This returns the object returned by nestle.sample The object is dictionary-like and has many useful items. For example, result.samples (or alternatively, result[“samples”]) are the parameter values of each sample, result.weights contains the weights, and result.logl contains the log likelihoods. result.logz is the natural logarithm of the evidence.
Return type:

Result object

platon.transit_depth_calculator module

class platon.transit_depth_calculator.TransitDepthCalculator(star_radius, g, include_condensates=True, min_P_profile=0.1, max_P_profile=100000.0, num_profile_heights=400)
__init__(star_radius, g, include_condensates=True, min_P_profile=0.1, max_P_profile=100000.0, num_profile_heights=400)

All physical parameters are in SI.

Parameters:
  • star_radius (float) – Radius of the star
  • g (float) – Acceleration due to gravity of the planet at a pressure of max_P_profile
  • include_condensates (bool) – Whether to use equilibrium abundances that take condensation into account.
  • min_P_profile (float) – For the radiative transfer calculation, the atmosphere is divided into zones. This is the pressure at the topmost zone.
  • max_P_profile (float) – The pressure at the bottommost zone of the atmosphere
  • num_profile_heights (int) – The number of zones the atmosphere is divided into
change_wavelength_bins(bins)

Specify wavelength bins, instead of using the full wavelength grid in self.lambda_grid. This makes the code much faster, as compute_depths will only compute depths at wavelengths that fall within a bin.

Parameters:bins (array_like, shape (N,2)) – Wavelength bins, where bins[i][0] is the start wavelength and bins[i][1] is the end wavelength for bin i.
Raises:NotImplementedError – Raised when change_wavelength_bins is called more than once, which is not supported.
compute_depths(planet_radius, temperature, logZ=0, CO_ratio=0.53, add_scattering=True, scattering_factor=1, scattering_slope=4, scattering_ref_wavelength=1e-06, add_collisional_absorption=True, cloudtop_pressure=inf, custom_abundances=None)

Computes transit depths at a range of wavelengths, assuming an isothermal atmosphere. To choose bins, call change_wavelength_bins().

Parameters:
  • planet_radius (float) – radius of the planet at self.max_P_profile (by default, 100,000 Pa). Must be in metres.
  • temperature (float) – Temperature of the isothermal atmosphere, in Kelvin
  • logZ (float) – Base-10 logarithm of the metallicity, in solar units
  • CO_ratio (float, optional) – C/O atomic ratio in the atmosphere. The solar value is 0.53.
  • add_scattering (bool, optional) – whether Rayleigh scattering is taken into account
  • scattering_factor (float, optional) – if add_scattering is True, make scattering this many times as strong. If scattering_slope is 4, corresponding to Rayleigh scattering, the absorption coefficients are simply multiplied by scattering_factor. If slope is not 4, scattering_factor is defined such that the absorption coefficient is that many times as strong as Rayleigh scattering at scattering_ref_wavelength.
  • scattering_slope (float, optional) – Wavelength dependence of scattering, with 4 being Rayleigh.
  • scattering_ref_wavelength (float, optional) – Scattering is scattering_factor as strong as Rayleigh at this wavelength, expressed in metres.
  • add_collisional_absorption (float, optional) – Whether collisionally induced absorption is taken into account
  • cloudtop_pressure (float, optional) – Pressure level (in Pa) below which light cannot penetrate. Use np.inf for a cloudless atmosphere.
  • custom_abundances (str or dict of np.ndarray, optional) – If specified, overrides logZ and CO_ratio. Can specify a filename, in which case the abundances are read from a file in the format of the EOS/ files. These are identical to ExoTransmit’s EOS files. It is also possible, though highly discouraged, to specify a dictionary mapping species names to numpy arrays, so that custom_abundances[‘Na’][3,4] would mean the fractional number abundance of Na at a pressure of self.P_grid[3] and temperature of self.T_grid[4].
Returns:

  • wavelengths (array of float) – Central wavelengths, in metres
  • transit_depths (array of float) – Transit depths at wavelengths
is_in_bounds(logZ, CO_ratio, T, cloudtop_P)

Tests whether a certain combination of parameters is within the bounds of the data files. The arguments are the same as those in compute_depths.

Module contents