Prospector#
Prospector is a package to conduct principled inference of stellar population properties from photometric and/or spectroscopic data using flexible models. Prospector allows you to:
Infer high-dimensional stellar population properties, including nebular emission, from rest UV through Far-IR data (with nested or ensemble MCMC sampling.)
Combine photometric and spectroscopic data rigorously using a flexible spectroscopic calibration model and forward modeling many aspects of spectroscopic data analysis.
Use spectra and/or photometry to constrain highly flexible star formation history treatments.
Changelog#
v1.3.0 (2024-03-27)#
Adds the prospector-beta SFH priors and documentation courtesy @wangbingjie
Bugfixes in emission line masking, polynomial regularization, sfr_ratio clipping (h/t @mjastro, @wangbingjie, @davidjsetton)
Documentation updates
v1.2.0 (2022-12-31)#
Document, improvements, and bugfixes in
LineSpecModel
(h/t @kgarofali)Add
AGNSpecModel
with a scalable, empirical AGN emission line template.Fix floating point issue with Dirichlet SFH transforms.
Implement
nested_target_n_effective
as dynesty stopping criterion.Fixes to the dynesty interface for dynesty >= 2.0 (h/t @mjastro)
Fix sign error in Powell minimization (h/t @blanton144)
Fix bugs in parameter template for emission line fitting.
numerous documentation updates including nebular emission details.
v1.1.0 (2022-02-20)#
Improved treatment of emission lines in
SpecModel
, including ability to ignore selected lines entirely.New
NoiseModelKDE
andKernel
classes to accommodate non-Gaussian and correlated uncertainties, courtesy of @wpb-astroNew flexible SFH parameterization courtesy @wrensuess
Support for
sedpy.observate.FilterSet
objects and computing rest-frame absolute magnitudes.Documentation updates, including a dedicated SFH page and a quickstart.
Several bugfixes including fixes to the “logm_sfh” parameter template, a fix for the nested sampling argument parsing, and bestfit spectrum saving.
v1.0 (2020-12-02)#
Release to accompany submitted paper. Includes
New plotting module
Demonstrations of MPI usage with dynesty
Numerous small bugfixes.
v0.4 (2020-07-08)#
New
models.SpecModel
class that handles much of the conversion from FSPS spectra to observed frame spectra (redshifting, smoothing, dimming, spectroscopic calibration, filter projections) internally instead of relying on source classes.The
SpecModel
class enables analytic marginalization of emission line amplitudes, with or without FSPS based priors.A new mixture model option in the likelihood to handle outlier points (for diagonal covariance matrices)
A noise model kernel for photometric calibration offsets.
Rename
mean_model()
topredict()
(old method kept for backwards compatibility)Some fixes to priors and optimization
Python3 compatibility improvements (now developed and tested with Python3)
v0.3 (2019-04-23)#
New UI, based on
argparse
command line options and a high level ``fit_model()` function that can use emcee, dynesty, or optimization algorithmsNew
prospector_parse
module that generates a default argument parser.Importable default probability function as
fitting.lnprobfn()
Non-object prior methods removed
Documentation and new notebook reflect UI changes
model_setup
methods are deprecated, better usage of warnings