stellarmass_pca

This library fits stellar-continuum observations with a basis set of q spectral vectors (generated from a library of synthetic star formation histories). The fit in this low-dimensional space makes various spectral-fitting degeneracies more tractable. Much of this library is a reimplimentation of Chen et al. (2012), but for SDSS-IV/MaNGA IFS data.

We will release a SDSS-IV VAC (#0060) as part of DR16 in December 2019. This library contains some simple data-access scripting utilities for reading the data in the VAC.

Publication

If you use the stellar M/L maps (from the SDSS VAC) or a portion of this software, please cite Pace et al 2019a. If you use the resulting estimates of total galaxy stellar mass (also in the VAC), please cite Pace et al 2019b.

Related Libraries

• cspgen, which provides some code to help you generate synthetic stellar pops
• fsps, the "workhorse" of cspgen
• mangapca_read (released with SDSS DR16), a lighter-weight "data-reader"-only library intended for users who just want to read our analyzed prodducts

Most Important Contents (selected)

• read_results.py (1): parses results from SDSS-IV Value-Added Catalog (VAC #0060)
• find_pcs.py (2): generates a PC vector basis set, and uses it to fit MaNGA datacubes

(1) - for user of data from VAC #0060 (2) - if you want to run your own analysis, using the provided set of synthetic training spectra

Dependencies

• zpmanga, a set of handy MaNGA-related functions