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github.com/ACCarnall/bagpipes
/ types & classes
Types & classes
19 in github.com/ACCarnall/bagpipes
⨍
Functions
181
◇
Types & classes
19
↓ 6 callers
Class
star_formation_history
Generate a star formation history. Parameters ---------- model_components : dict A dictionary containing information about the
bagpipes/models/star_formation_history.py:35
↓ 5 callers
Class
model_galaxy
Builds model galaxy spectra and calculates predictions for spectroscopic and photometric observables. Parameters ---------- model_c
bagpipes/models/model_galaxy.py:26
↓ 2 callers
Class
dust_attenuation
Allows access to and maniuplation of dust attenuation models. This class calculates the absolute attenuation curve (A_lam/A_V) for the specif
bagpipes/models/dust_attenuation_model.py:8
↓ 2 callers
Class
fitted_model
Contains a model which is to be fitted to observational data. Parameters ---------- galaxy : bagpipes.galaxy A galaxy object co
bagpipes/fitting/fitted_model.py:14
↓ 2 callers
Class
noise_model
A class for modelling the noise properties of spectroscopic data, including correlated noise. Parameters ---------- noise_dict : di
bagpipes/fitting/noise.py:17
↓ 2 callers
Class
posterior
Provides access to the outputs from fitting models to data and calculating posterior predictions for derived parameters (e.g. for star-format
bagpipes/fitting/posterior.py:20
↓ 2 callers
Class
prior
A class which allows for samples to be drawn from a joint prior distribution in several parameters and for transformations from the unit cube
bagpipes/fitting/prior.py:35
↓ 1 callers
Class
agn
A basic rest-optical AGN continuum + broad line model. Parameters ---------- wavelengths : np.ndarray 1D array of wavelength va
bagpipes/models/agn_model.py:6
↓ 1 callers
Class
calib_model
A class for modelling spectrophotometric calibration. Parameters ---------- calib_dict : dictionary Contains the desired parame
bagpipes/fitting/calibration.py:6
↓ 1 callers
Class
chemical_enrichment_history
bagpipes/models/chemical_enrichment_history.py:8
↓ 1 callers
Class
dust_emission
Allows access to and maniuplation of the dust emission models of Draine + Li (2007). Currently very simple, possibly could be sped up in some
bagpipes/models/dust_emission_model.py:8
↓ 1 callers
Class
fit
Top-level class for fitting models to observational data. Interfaces with MultiNest or nautilus to sample from the posterior distributio
bagpipes/fitting/fit.py:81
↓ 1 callers
Class
galaxy
A container for observational data loaded into Bagpipes. Parameters ---------- ID : str string denoting the ID of the object to
bagpipes/input/galaxy.py:12
↓ 1 callers
Class
igm
Allows access to and maniuplation of the IGM attenuation models of Inoue (2014). Parameters ---------- wavelengths : np.ndarray
bagpipes/models/igm_model.py:18
↓ 1 callers
Class
nebular
Allows access to and maniuplation of nebular emission models. These must be pre-computed using Cloudy and the relevant set of stellar emissio
bagpipes/models/nebular_model.py:8
↓ 1 callers
Class
stellar
Allows access to and maniuplation of stellar emission models. Parameters ---------- wavelengths : np.ndarray 1D array of wavele
bagpipes/models/stellar_model.py:9
Class
check_priors
bagpipes/fitting/check_priors.py:13
Class
filter_set
Class for loading and manipulating sets of filter curves. This is where integration over filter curves to get photometry happens. Parameters
bagpipes/filters/filter_set.py:8
Class
fit_catalogue
Fit a model to a catalogue of galaxies. Parameters ---------- IDs : list A list of ID numbers for galaxies in the catalogue
bagpipes/catalogue/fit_catalogue.py:27