Purpose
Conduct principled inference of stellar population properties from photometric and/or spectroscopic data. Prospector allows you to:
-
Infer high-dimensional stellar population properties using parametric or highly flexible SFHs (with nested or ensemble Monte Carlo sampling)
-
Combine photometric and spectroscopic data from the UV to Far-IR rigorously using a flexible spectroscopic calibration model and forward modeling many aspects of spectroscopic data analysis.
Read the documentation and the code paper.
Installation
See installation for requirements and dependencies. The documentation includes a tutorial and demos.
To install to a conda environment with dependencies, see conda_install.sh.
To install just Prospector (stable release):
python -m pip install astro-prospector
To install the latest development version:
cd <install_dir>
git clone https://github.com/bd-j/prospector
cd prospector
python -m pip install .
Then, in Python
import prospect
Citation
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}
}
and make sure to cite the dependencies as listed in installation
Example
Inference with mock broadband data, showing the change in posteriors as the
number of photometric bands is increased.
Metadata
Release files for astro-prospector 1.4.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| astro_prospector-1.4.1.tar.gz | 14.4 MB | Without provenance | Details for astro_prospector-1.4.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| astro_prospector-1.4.1-py3-none-any.whl | Python 3 | none | any | Details for astro_prospector-1.4.1-py3-none-any.whl |
Total release size: 14.6 MB
Release files / astro_prospector-1.4.1.tar.gz
| Download URL | astro_prospector-1.4.1.tar.gz |
|---|---|
| Size | 14.4 MB |
| Tags | Source |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.10.13
|
Release files / astro_prospector-1.4.1-py3-none-any.whl
| Download URL | astro_prospector-1.4.1-py3-none-any.whl |
|---|---|
| Size | 205.0 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.13
|
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