species.data package¶

Submodules¶

species.data.ames_cond module¶

Module for AMES-Cond atmospheric model spectra.

species.data.ames_cond.add_ames_cond(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: float = None) → None[source]¶

Function for adding the AMES-Cond atmospheric models to the database. The original spectra have been resampled to a spectral resolution of R = 2000 from 0.5 to 40 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The full wavelength range (0.5-40 um) is stored if set to `None`. Only used in combination with `spec_res`. teff_range (tuple(float, float), None) – Effective temperature range (K). All available temperatures are stored if set to `None`. spec_res (float, None) – Spectral resolution. The data is stored with the spectral resolution of the input spectra (R = 2000) if set to `None`. Only used in combination with `wavel_range`.
Returns:	None
Return type:	NoneType

species.data.ames_dusty module¶

Module for AMES-Dusty atmospheric model spectra.

species.data.ames_dusty.add_ames_dusty(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: float = None) → None[source]¶

Function for adding the AMES-Dusty atmospheric models to the database. The original spectra have been resampled to a spectral resolution of R = 2000 from 0.5 to 40 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The full wavelength range (0.5-40 um) is stored if set to `None`. Only used in combination with `spec_res`. teff_range (tuple(float, float), None) – Effective temperature range (K). All available temperatures are stored if set to `None`. spec_res (float, None) – Spectral resolution. The data is stored with the spectral resolution of the input spectra (R = 2000) if set to `None`. Only used in combination with `wavel_range`.
Returns:	None
Return type:	NoneType

species.data.atmo module¶

Module for ATMO 2020 atmospheric model spectra.

species.data.atmo.add_atmo(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the ATMO 2020 atmospheric models to the database. The spectra have been calculated with equilibrium chemistry and solar metallicity in the Teff range from 200 to 3000 K. The spectra have been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=atmo2020_ceq) and resampled to a spectral resolution of 5000 from 0.3 to 100 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.blackbody module¶

Module for blackbody model spectra.

species.data.blackbody.add_blackbody(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the blackbody atmospheric models to the database. The spectra have been calculated for Teff from 10 to 5000 K at spectral resolution of 1000 from 0.1 um to 5 mm.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.btcond module¶

Module for BT-Cond atmospheric model spectra.

species.data.btcond.add_btcond(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the BT-Cond atmospheric models (solar metallicity) to the database. The spectra have been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=bt-cond) and resampled to a spectral resolution of 5000 from 0.1 to 100 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.btcond_feh module¶

Module for BT-Cond atmospheric model spectra with Teff > 2500 K and [Fe/H] as free parameter.

species.data.btcond_feh.add_btcond_feh(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the BT-Cond atmospheric models with Teff > 2500 K to the database. The spectra have been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=bt-cond) and resampled to a spectral resolution of 5000 from 0.1 to 100 um. The metallicity is also a free parameter.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.btnextgen module¶

Module for BT-NextGen atmospheric model spectra.

species.data.btnextgen.add_btnextgen(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: float = None) → None[source]¶

Function for adding the BT-NextGen atmospheric models to the database. The original spectra have been resampled to a spectral resolution of R = 2000 from 0.1 to 50 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The full wavelength range (0.1-50 um) is stored if set to `None`. Only used in combination with `spec_res`. teff_range (tuple(float, float), None) – Effective temperature range (K). All available temperatures are stored if set to `None`. spec_res (float, None) – Spectral resolution. The data is stored with the spectral resolution of the input spectra (R = 2000) if set to `None`. Only used in combination with `wavel_range`.
Returns:	None
Return type:	NoneType

species.data.btsettl module¶

Module for BT-Settl atmospheric model spectra.

species.data.btsettl.add_btsettl(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the BT-Settl atmospheric models (solar metallicity) to the database. The spectra have been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=bt-settl) and resampled to a spectral resolution of 5000 from 0.1 to 100 um. For Teff > 2500 K, these are BT-NextGen spectra instead of BT-Settl.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.btsettl_cifist module¶

Module for BT-Settl atmospheric model spectra.

species.data.btsettl_cifist.add_btsettl(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the BT-Settl-CIFIST atmospheric models (solar metallicity) to the database. The spectra had been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=bt-settl-cifist) and resampled to a spectral resolution of 5000 from 0.1 to 100 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.companions module¶

Module for extracting data of directly imaged planets and brown dwarfs.

species.data.companions.companion_spectra(input_path: str, comp_name: str) → Optional[Dict[str, Tuple[str, Optional[str], float]]][source]¶

Function for getting available spectra of directly imaged planets and brown dwarfs.

Parameters:	input_path (str) – Path of the data folder. comp_name (str) – Companion name for which the spectra will be returned.
Returns:	Dictionary with the spectra of `comp_name`. A `None` will be returned if there are not any spectra available.
Return type:	dict, None

species.data.companions.get_data() → Dict[str, Dict[str, Union[bool, Tuple[float, float], Dict[str, Union[Tuple[float, float], List[Tuple[float, float]]]]]]][source]¶

Function for extracting a dictionary with the distances (pc) and apparent magnitudes of directly imaged planets and brown dwarfs.

Returns:	Dictionary with the distances and apparent magnitudes of directly imaged companions. Distances are from GAIA DR2 unless indicated as comment.
Return type:	dict

species.data.companions.get_spec_data() → Dict[str, Dict[str, Tuple[str, Optional[str], float, str]]][source]¶

Function for extracting a dictionary with the spectra of directly imaged planets.

Returns:	Dictionary with the spectrum, optional covariances, spectral resolution, and filename.
Return type:	dict

species.data.database module¶

Module with functionalities for reading and writing of data.

class species.data.database.Database[source]¶

Bases: object

Class with reading and writing functionalities for the HDF5 database.

Returns:	None
Return type:	NoneType

add_calibration(tag: str, filename: Optional[str] = None, data: Optional[numpy.ndarray] = None, units: Optional[Dict[str, str]] = None, scaling: Optional[Tuple[float, float]] = None) → None[source]¶

Function for adding a calibration spectrum to the database.

Parameters:	tag (str) – Tag name in the database. filename (str, None) – Filename with the calibration spectrum. The first column should contain the wavelength (um), the second column the flux density (W m-2 um-1), and the third column the error (W m-2 um-1). The `data` argument is used if set to `None`. data (np.ndarray, None) – Spectrum stored as 3D array with shape `(n_wavelength, 3)`. The first column should contain the wavelength (um), the second column the flux density (W m-2 um-1), and the third column the error (W m-2 um-1). The `filename` argument is used if set to `None`. units (dict, None) – Dictionary with the wavelength and flux units, e.g. `{'wavelength': 'angstrom', 'flux': 'w m-2'}`. The default units (um and W m-2 um-1) are used if set to `None`. scaling (tuple(float, float), None) – Scaling for the wavelength and flux as `(scaling_wavelength, scaling_flux)`. Not used if set to `None`.
Returns:	None
Return type:	NoneType

add_companion(name: Union[str, None, List[str]] = None) → None[source]¶

Function for adding the magnitudes and spectra of directly imaged planets and brown dwarfs from get_data and :class:`~species.data.companions.get_comp_spec`to the database.

Parameters:	name (str, list(str), None) – Name or list with names of the directly imaged planets and brown dwarfs (e.g. `'HR 8799 b'` or `['HR 8799 b', '51 Eri b', 'PZ Tel B']`). All the available companion data are added if set to `None`.
Returns:	None
Return type:	NoneType

add_comparison(tag: str, goodness_of_fit: numpy.ndarray, flux_scaling: numpy.ndarray, model_param: List[str], coord_points: List[numpy.ndarray], object_name: str, spec_name: List[str], model: str) → None[source]¶

Parameters:	tag (str) – Database tag where the results will be stored. goodness_of_fit (np.ndarray) – Array with the goodness-of-fit values. flux_scaling (np.ndarray) – Array with the best-fit scaling values to match the model spectra with the data. model_param (list(str)) – List with the names of the model parameters. coord_points (list(np.ndarray)) – List with 1D arrays of the model grid points, in the same order as `model_param`. object_name (str) – Object name as stored in the database with `add_object()` or `add_companion()`. spec_name (list(str)) – List with spectrum names that are stored at the object data of `object_name`. model (str) – Atmospheric model grid that is used for the comparison.
Returns:	None
Return type:	NoneType

add_dust() → None[source]¶

Function for adding optical constants of MgSiO3 and Fe, and MgSiO3 cross sections for a log-normal and power-law size distribution to the database. The optical constants have been compiled by Mollière et al. (2019) for petitRADTRANS from the following sources:

MgSiO3, crystalline
- Scott & Duley (1996), ApJS, 105, 401
- Jäger et al. (1998), A&A, 339, 904
MgSiO3, amorphous
- Jäger et al. (2003), A&A, 408, 193
Fe, crystalline
- Henning & Stognienko (1996), A&A, 311, 291
Fe, amorphous
- Pollack et al. (1994), ApJ, 421, 615

Returns:	None
Return type:	NoneType

add_empirical(tag: str, names: List[str], sptypes: List[str], goodness_of_fit: List[float], flux_scaling: List[float], av_ext: List[float], rad_vel: List[float], object_name: str, spec_name: str, spec_library: str) → None[source]¶

Parameters:	tag (str) – Database tag where the results will be stored. names (list(str)) – Array with the names of the empirical spectra. sptypes (list(str)) – Array with the spectral types of `names`. goodness_of_fit (list(float)) – Array with the goodness-of-fit values. flux_scaling (list(float)) – Array with the best-fit scaling values to match the library spectra with the data. av_ext (list(float)) – Array with the visual extinction \(A_V\). rad_vel (list(float)) – Array with the radial velocities (km s-1). object_name (str) – Object name as stored in the database with `add_object()` or `add_companion()`. spec_name (str) – Name of the spectrum that is stored at the object data of `object_name`. spec_library (str) – Name of the spectral library that was used for the empirical comparison.
Returns:	None
Return type:	NoneType

add_filter(filter_name: str, filename: Optional[str] = None, detector_type: str = 'photon') → None[source]¶

Function for adding a filter profile to the database, either from the SVO Filter profile Service or from an input file. Additional filters that are automatically added are Magellan/VisAO.rp, Magellan/VisAO.ip, Magellan/VisAO.zp, Magellan/VisAO.Ys, ALMA/band6, and ALMA/band7.

Parameters:	filter_name (str) – Filter name from the SVO Filter Profile Service (e.g., ‘Paranal/NACO.Lp’) or a user-defined name if a `filename` is specified. filename (str) – Filename of the filter profile. The first column should contain the wavelength (um) and the second column the fractional transmission. The profile is downloaded from the SVO Filter Profile Service if the argument of `filename` is set to `None`. detector_type (str) – The detector type (‘photon’ or ‘energy’). The argument is only used if a `filename` is provided. Otherwise, for filters that are fetched from the SVO website, the detector type is read from the SVO data. The detector type determines if a wavelength factor is included in the integral for the synthetic photometry.
Returns:	None
Return type:	NoneType

add_isochrones(filename: str, tag: str, model: str = 'baraffe') → None[source]¶

Function for adding isochrone data to the database.

Parameters:	filename (str) – Filename with the isochrone data. tag (str) – Database tag name where the isochrone that will be stored. model (str) – Evolutionary model (‘baraffe’ or ‘marleau’). For ‘baraffe’ models, the isochrone data can be downloaded from https://phoenix.ens-lyon.fr/Grids/. For ‘marleau’ models, the data can be requested from Gabriel Marleau.
Returns:	None
Return type:	NoneType

add_model(model: str, wavel_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = None, teff_range: Optional[Tuple[float, float]] = None, data_folder: Optional[str] = None) → None[source]¶

Method for adding a grid of model spectra to the database. All spectra have been resampled to a lower, constant spectral resolution (typically \(R = 5000\)).

Parameters:	model (str) – Model name (‘ames-cond’, ‘ames-dusty’, ‘atmo’, ‘bt-settl’, ‘bt-settl-cifist’, ‘bt-nextgen’, ‘drift-phoenix’, ‘petitcode-cool-clear’, ‘petitcode-cool-cloudy’, ‘petitcode-hot-clear’, ‘petitcode-hot-cloudy’, ‘exo-rem’, ‘blackbody’, bt-cond’, ‘bt-cond-feh, ‘morley-2012’). wavel_range (tuple(float, float), None) – Wavelength range (um) for adding a subset of the spectra. The full wavelength range is used if the argument is set to `None`. spec_res (float, None) – Spectral resolution to which the spectra will be resampled. This parameter is optional since the spectra have already been resampled to a lower, constant resolution (typically \(R = 5000\)). The argument is only used if `wavel_range` is not `None`. teff_range (tuple(float, float), None) – Effective temperature range (K) for adding a subset of the model grid. The full parameter grid will be added if the argument is set to `None`. data_folder (str, None) – DEPRECATED: Folder where the input data is located. This parameter is no longer in use since all model spectra are publicly available. The parameter will be removed in a future release.
Returns:	None
Return type:	NoneType

add_object(object_name: str, distance: Optional[Tuple[float, float]] = None, app_mag: Optional[Dict[str, Union[Tuple[float, float], List[Tuple[float, float]]]]] = None, flux_density: Optional[Dict[str, Tuple[float, float]]] = None, spectrum: Optional[Dict[str, Tuple[str, Optional[str], Optional[float]]]] = None, deredden: Union[Dict[str, float], float] = None) → None[source]¶

Function for adding the photometric and/or spectroscopic data of an object to the database.

Parameters:	object_name (str) – Object name that will be used as label in the database. distance (tuple(float, float), None) – Distance and uncertainty (pc). Not stored if set to None. app_mag (dict, None) – Dictionary with the filter names, apparent magnitudes, and uncertainties. For example, `{'Paranal/NACO.Lp': (15., 0.2), 'Paranal/NACO.Mp': (13., 0.3)}`. For the use of duplicate filter names, the magnitudes have to be provided in a list, for example `{'Paranal/NACO.Lp': [(15., 0.2), (14.5, 0.5)], 'Paranal/NACO.Mp': (13., 0.3)}`. No photometric data is stored if set to `None`. flux_density (dict, None) – Dictionary with filter names, flux densities (W m-2 um-1), and uncertainties (W m-1 um-1). For example, `{'Paranal/NACO.Lp': (1e-15, 1e-16)}`. Currently, the use of duplicate filters is not implemented. The use of `app_mag` is preferred over `flux_density` because with `flux_density` only fluxes are stored while with `app_mag` both magnitudes and fluxes. However, `flux_density` can be used in case the magnitudes and/or filter profiles are not available. In that case, the fluxes can still be selected with `inc_phot` in `FitModel`. The argument of `flux_density` is ignored if set to `None`. spectrum (dict, None) – Dictionary with the spectrum, optional covariance matrix, and spectral resolution for each instrument. The input data can either have a FITS or ASCII format. The spectra should have 3 columns with wavelength (um), flux (W m-2 um-1), and uncertainty (W m-2 um-1). The covariance matrix should be 2D with the same number of wavelength points as the spectrum. For example, `{'SPHERE': ('spectrum.dat', 'covariance.fits', 50.)}`. No covariance data is stored if set to None, for example, `{'SPHERE': ('spectrum.dat', None, 50.)}`. The `spectrum` parameter is ignored if set to None. For GRAVITY data, the same FITS file can be provided as spectrum and covariance matrix. deredden (dict, float, None) – Dictionary with `spectrum` and `app_mag` names that will de dereddened with the provided A_V. For example, `deredden={'SPHERE': 1.5, 'Keck/NIRC2.J': 1.5}` will deredden the provided spectrum named ‘SPHERE’ and the Keck/NIRC2 J-band photometry with a visual extinction of 1.5. For photometric fluxes, the filter-averaged extinction is used for the dereddening.
Returns:	None
Return type:	NoneType

add_photometry(phot_library: str) → None[source]¶

Parameters:	phot_library (str) – Photometric library (‘vlm-plx’ or ‘leggett’).
Returns:	None
Return type:	NoneType

add_samples(sampler: str, samples: numpy.ndarray, ln_prob: numpy.ndarray, ln_evidence: Optional[Tuple[float, float]], mean_accept: Optional[float], spectrum: Tuple[str, str], tag: str, modelpar: List[str], distance: Optional[float], spec_labels: Optional[List[str]])[source]¶

Parameters:	sampler (str) – Sampler (‘emcee’, ‘multinest’, or ‘ultranest’). samples (np.ndarray) – Samples of the posterior. ln_prob (np.ndarray) – Log posterior for each sample. ln_evidence (tuple(float, float)) – Log evidence and uncertainty. Set to `None` when `sampler` is ‘emcee’. mean_accept (float, None) – Mean acceptance fraction. Set to `None` when `sampler` is ‘multinest’ or ‘ultranest’. spectrum (tuple(str, str)) – Tuple with the spectrum type (‘model’ or ‘calibration’) and spectrum name (e.g. ‘drift-phoenix’). tag (str) – Database tag. modelpar (list(str)) – List with the model parameter names. distance (float, None) – Distance to the object (pc). Not used if set to `None`. spec_labels (list(str), None) – List with the spectrum labels that are used for fitting an additional scaling parameter. Not used if set to `None`.
Returns:	None
Return type:	NoneType

add_spectrum(spec_library: str, sptypes: Optional[List[str]] = None) → None[source]¶

Parameters:	spec_library (str) – Spectral library (‘irtf’, ‘spex’, ‘kesseli+2017’). sptypes (list(str)) – Spectral types (‘F’, ‘G’, ‘K’, ‘M’, ‘L’, ‘T’). Currently only implemented for ‘irtf’.
Returns:	None
Return type:	NoneType

delete_data(dataset: str) → None[source]¶

Function for deleting a dataset from the HDF5 database.

Parameters:	dataset (str) – Dataset path in the HDF5 database.
Returns:	None
Return type:	NoneType

get_compare_sample(tag: str, spec_fix: Optional[str] = None) → Dict[str, float][source]¶

Function for extracting the sample parameters with the highest posterior probability.

Parameters:	tag (str) – Database tag where the results from `compare_model()` are stored. spec_fix (str, None) – After comparing multiple spectra with a model grid, one of the flux scalings need to be used to calculate the planet radius (i.e. scaling = (radius/distance)^2). The name of this spectrum is specified as argument of `spec_fix`. For the other spectra, the same radius will be used and an additional scaling parameter will be included in the returned dictionary. When passing the returned dictionary to `update_spectra()`, the spectra can be updated with the derived scaling corrections. The argument can be set to `None` if a single spectrum was used for the comparison.
Returns:	Dictionary with the best-fit parameters.
Return type:	dict

get_mcmc_photometry(tag: str, filter_name: str, burnin: Optional[int] = None, phot_type: str = 'magnitude') → numpy.ndarray[source]¶

Function for calculating synthetic magnitudes or fluxes from the posterior samples.

Parameters:	tag (str) – Database tag with the posterior samples. filter_name (str) – Filter name for which the synthetic photometry will be computed. burnin (int, None) – Number of burnin steps. No burnin is removed if set to `None`. Not required when using nested sampling. phot_type (str) – Photometry type (‘magnitude’ or ‘flux’).
Returns:	Synthetic magnitudes or fluxes (W m-2 um-1).
Return type:	np.ndarray

get_mcmc_spectra(tag: str, random: int, burnin: Optional[int] = None, wavel_range: Union[Tuple[float, float], str, None] = None, spec_res: Optional[float] = None, wavel_resample: Optional[numpy.ndarray] = None) → Union[List[species.core.box.ModelBox], List[species.core.box.SpectrumBox]][source]¶

Function for drawing random spectra from the sampled posterior distributions.

Parameters:	tag (str) – Database tag with the posterior samples. random (int) – Number of random samples. burnin (int, None) – Number of burnin steps. No burnin is removed if set to `None`. Not required when using nested sampling. wavel_range (tuple(float, float), str, None) – Wavelength range (um) or filter name. Full spectrum is used if set to `None`. spec_res (float) – Spectral resolution that is used for the smoothing with a Gaussian kernel. No smoothing is applied if the argument set to `None`. wavel_resample (np.ndarray, None) – Wavelength points (um) to which the model spectrum will be resampled. The resampling is applied after the optional smoothing to the resolution of `spec_res`.
Returns:	List with `ModelBox` objects.
Return type:	list(species.core.box.ModelBox)

get_median_sample(tag: str, burnin: Optional[int] = None) → Dict[str, float][source]¶

Function for extracting the median parameter values from the posterior samples.

Parameters:	tag (str) – Database tag with the posterior results. burnin (int, None) – Number of burnin steps. No burnin is removed if set to `None`.
Returns:	Parameters and values for the sample with the maximum posterior probability.
Return type:	dict

get_object(object_name: str, inc_phot: Union[bool, List[str]] = True, inc_spec: Union[bool, List[str]] = True) → species.core.box.ObjectBox[source]¶

Function for extracting the photometric and/or spectroscopic data of an object from the database. The spectroscopic data contains optionally the covariance matrix and its inverse.

Parameters:	object_name (str) – Object name in the database. inc_phot (bool, list(str)) – Include photometric data. If a boolean, either all (`True`) or none (`False`) of the data are selected. If a list, a subset of filter names (as stored in the database) can be provided. inc_spec (bool, list(str)) – Include spectroscopic data. If a boolean, either all (`True`) or none (`False`) of the data are selected. If a list, a subset of spectrum names (as stored in the database with `add_object()`) can be provided.
Returns:	Box with the object’s data.
Return type:	species.core.box.ObjectBox

get_probable_sample(tag: str, burnin: Optional[int] = None) → Dict[str, float][source]¶

Function for extracting the sample parameters with the highest posterior probability.

Parameters:	tag (str) – Database tag with the posterior results. burnin (int, None) – Number of burnin steps. No burnin is removed if set to `None`.
Returns:	Parameters and values for the sample with the maximum posterior probability.
Return type:	dict

get_samples(tag: str, burnin: Optional[int] = None, random: Optional[int] = None, json_file: Optional[str] = None) → species.core.box.SamplesBox[source]¶

Parameters:	tag (str) – Database tag with the samples. burnin (int, None) – Number of burnin samples to exclude. All samples are selected if set to `None`. The parameter is only required for samples obtained with `emcee` and is therefore not used for samples obtained with `MultiNest` or `UltraNest`. random (int, None) – Number of random samples to select. All samples (with the burnin excluded) are selected if set to `None`. json_file (str, None) – JSON file to store the posterior samples. The data will not be written if the argument is set to `None`.
Returns:	Box with the posterior samples.
Return type:	species.core.box.SamplesBox

static list_companions() → None[source]¶

Returns:	None
Return type:	NoneType

list_content() → None[source]¶

Returns:	None
Return type:	NoneType

species.data.drift_phoenix module¶

Module for DRIFT-PHOENIX atmospheric model spectra.

species.data.drift_phoenix.add_drift_phoenix(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: float = None) → None[source]¶

Function for adding the DRIFT-PHOENIX atmospheric models to the database. The original spectra were downloaded from http://svo2.cab.inta-csic.es/theory/newov2/index.php?models=drift and have been resampled to a spectral resolution of R = 2000 from 0.1 to 50 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The full wavelength range (0.1-50 um) is stored if set to `None`. Only used in combination with `spec_res`. teff_range (tuple(float, float), None) – Effective temperature range (K). All available temperatures are stored if set to `None`. spec_res (float, None) – Spectral resolution. The data is stored with the spectral resolution of the input spectra (R = 2000) if set to `None`. Only used in combination with `wavel_range`.
Returns:	None
Return type:	NoneType

species.data.dust module¶

Module for optical constants of dust grains.

species.data.dust.add_cross_sections(input_path: str, database: h5py._hl.files.File) → None[source]¶

Function for adding the extinction cross section of crystalline MgSiO3 for a log-normal and power-law size distribution to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database.
Returns:	NoneType
Return type:	None

species.data.dust.add_optical_constants(input_path: str, database: h5py._hl.files.File) → None[source]¶

Function for adding the optical constants of crystalline and amorphous MgSiO3 and Fe to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database.
Returns:	NoneType
Return type:	None

species.data.exo_rem module¶

Module for Exo-REM atmospheric model spectra.

species.data.exo_rem.add_exo_rem(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = None) → None[source]¶

Function for adding the Exo-REM atmospheric models to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points with a spectral resolution of 5000 are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.filters module¶

Module for downloading filter data from the website of the SVO Filter Profile Service.

species.data.filters.download_filter(filter_id: str) → Tuple[Optional[numpy.ndarray], Optional[numpy.ndarray], Optional[str]][source]¶

Function for downloading filter profile data from the SVO Filter Profile Service.

Parameters:	filter_id (str) – Filter name as listed on the website of the SVO Filter Profile Service (see http://svo2.cab.inta-csic.es/svo/theory/fps/).
Returns:	np.ndarray – Wavelength (um). np.ndarray – Fractional transmission. str – Detector type (‘energy’ or ‘photon’).

species.data.irtf module¶

Module for adding the IRTF Spectral Library to the database.

species.data.irtf.add_irtf(input_path: str, database: h5py._hl.files.File, sptypes: Optional[List[str]] = None) → None[source]¶

Function for adding the IRTF Spectral Library to the database.

Parameters:	input_path (str) – Path of the data folder. database (h5py._hl.files.File) – Database. sptypes (list(str), None) – List with the spectral types (‘F’, ‘G’, ‘K’, ‘M’, ‘L’, ‘T’). All spectral types are included if set to `None`.
Returns:	None
Return type:	NoneType

species.data.isochrones module¶

Module for isochrone data of evolutionary models.

species.data.isochrones.add_baraffe(database, tag, filename)[source]¶

Function for adding the Baraffe et al. (2003) isochrone data to the database. Any of the isochrones from https://phoenix.ens-lyon.fr/Grids/ can be used as input.

Parameters:	database (h5py._hl.files.File) – Database. tag (str) – Tag name in the database. filename (str) – Filename with the isochrones data.
Returns:	None
Return type:	NoneType

species.data.isochrones.add_marleau(database, tag, filename)[source]¶

Function for adding the Marleau et al. isochrone data to the database. The isochrone data can be requested from Gabriel Marleau.

https://ui.adsabs.harvard.edu/abs/2019A%26A…624A..20M/abstract

Parameters:	database (h5py._hl.files.File) – Database. tag (str) – Tag name in the database. filename (str) – Filename with the isochrones data.
Returns:	None
Return type:	NoneType

species.data.kesseli2017 module¶

Module for adding O5 through L3 SDSS stellar spectra from Kesseli et al. (2017) to the database.

species.data.kesseli2017.add_kesseli2017(input_path: str, database: h5py._hl.files.File) → None[source]¶

Function for adding the SDSS stellar spectra from Kesseli et al. (2017) to the database.

Parameters:	input_path (str) – Path of the data folder. database (h5py._hl.files.File) – The HDF5 database.
Returns:	None
Return type:	NoneType

species.data.leggett module¶

Text

species.data.leggett.add_leggett(input_path, database)[source]¶

Function for adding the Database of Ultracool Parallaxes to the database.

Parameters:	input_path (str) – Path of the data folder. database (h5py._hl.files.File) – Database.
Returns:	None
Return type:	NoneType

species.data.morley2012 module¶

Module for T/Y dwarf model spectra from Morley et al. (2012).

species.data.morley2012.add_morley2012(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]], teff_range: Optional[Tuple[float, float]], spec_res: Optional[float]) → None[source]¶

Function for adding the T/Y dwarf model spectra from Morley et al. (2012) to the database. The spectra have been at solar metallicity in the Teff range from 500 to 1300 K. The spectra have been downloaded from the Theoretical spectra web server (http://svo2.cab.inta-csic.es/svo/theory/newov2/index.php?models=morley12) and resampled to a spectral resolution of 5000 from 0.6 to 30 um.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to `None`. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to `None`. spec_res (float, None) – Spectral resolution for resampling. Not used if `wavel_range` is set to `None`.
Returns:	None
Return type:	NoneType

species.data.petitcode module¶

Module for petitCODE atmospheric model spectra.

species.data.petitcode.add_petitcode_cool_clear(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = 1000.0) → None[source]¶

Function for adding the petitCODE cool clear atmospheric models to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to None. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to None. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to None.
Returns:	None
Return type:	NoneType

species.data.petitcode.add_petitcode_cool_cloudy(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = 1000.0) → None[source]¶

Function for adding the petitCODE cool cloudy atmospheric models to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to None. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to None. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to None.
Returns:	None
Return type:	NoneType

species.data.petitcode.add_petitcode_hot_clear(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = 1000.0) → None[source]¶

Function for adding the petitCODE hot clear atmospheric models to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to None. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to None. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to None.
Returns:	None
Return type:	NoneType

species.data.petitcode.add_petitcode_hot_cloudy(input_path: str, database: h5py._hl.files.File, wavel_range: Optional[Tuple[float, float]] = None, teff_range: Optional[Tuple[float, float]] = None, spec_res: Optional[float] = 1000.0) → None[source]¶

Function for adding the petitCODE hot cloudy atmospheric models to the database.

Parameters:	input_path (str) – Folder where the data is located. database (h5py._hl.files.File) – Database. wavel_range (tuple(float, float), None) – Wavelength range (um). The original wavelength points are used if set to None. teff_range (tuple(float, float), None) – Effective temperature range (K). All temperatures are selected if set to None. spec_res (float, None) – Spectral resolution. Not used if `wavel_range` is set to None.
Returns:	None
Return type:	NoneType

species.data.spex module¶

Module for adding the SpeX Prism Spectral Libraries to the database.

species.data.spex.add_spex(input_path: str, database: h5py._hl.files.File) → None[source]¶

Function for adding the SpeX Prism Spectral Library to the database.

Parameters:	input_path (str) – Path of the data folder. database (h5py._hl.files.File) – The HDF5 database.
Returns:	None
Return type:	NoneType

species.data.vega module¶