Bd J Prospector Versions Save

• 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

• Added LineSpecModel for fitting integrated emission line fluxes (h/t @kgarofali).
• Add AGNSpecModel with a scalable, empirical AGN emission line template.
• Fix floating point issue with Dirichlet SFH transforms (h/t TakumiSTanaka)
• 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 treatments.

• 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.

Release to accompany submitted paper. Includes a new plotting module, demonstrations of MPI usage with dynesty, and small bugfixes.

• 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
• 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)

New UI, based on argparse command line options and a high level fit_model function

• new prospector_parse module that generates a default argument parser

• importable default probability function as fitting.lnprobfn

• new high level fit_model method that can use emcee, dynesty, or optimization algorithms

• documentation and new notebook reflect UI changes

• model_setup methods raise a FutureWarning

• better usage of warnings

• non-object prior methods removed

• Bugfixes, including the polynomial optimization in PolySedModel

• New prior objects (SkewNorm, StudentT)

• New parameter templates (IGM, continuity SFH, spectral smoothing)

• Restart emcee chains

• Python3 compatibility improvements

• Sweet new animated figure for the documentation.

• Add modules for pre-packaged model parameter templates and transforms;

• Can now instantiate ProspectorParams objects with configuration dictionaries;

• Configuration dictionaries now public (ProspectorParams.config_dict)

• Add a nested sampling demo notebook

This is an initial release of the Prospector stellar population inference code.