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.

Demos & Tutorials

API Reference

License and Attribution#

This code is available under the MIT License.

If you use this code, please reference this paper:

@ARTICLE{2021ApJS..254...22J,
    author = {{Johnson}, Benjamin D. and {Leja}, Joel and {Conroy}, Charlie and {Speagle}, Joshua S.},
        title = "{Stellar Population Inference with Prospector}",
    journal = {\apjs},
    keywords = {Galaxy evolution, Spectral energy distribution, Astronomy data modeling, 594, 2129, 1859, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
        year = 2021,
        month = jun,
    volume = {254},
    number = {2},
        eid = {22},
        pages = {22},
        doi = {10.3847/1538-4365/abef67},
archivePrefix = {arXiv},
    eprint = {2012.01426},
primaryClass = {astro-ph.GA},
    adsurl = {https://ui.adsabs.harvard.edu/abs/2021ApJS..254...22J},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Changelog#

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.
numeropus 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 and Kernel classes to accommodate non-Gaussian and correlated uncertainties, courtesy of @wpb-astro
New 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 (2021-12-02)#

Release to accompany submitted paper. Includes

New plotting module
Demonstrations of MPI usage with dynesty
Numerous small bugfixes.

v0.4 (2021-07-08)#

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() to predict() (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 algorithms
New 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

Prospector

Contents