popsynth
popsynth: A generic astrophysical population synthesis framework - Published in JOSS (2021)
Science Score: 95.0%
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Published in Journal of Open Source Software
Keywords
Repository
A generic flux/parameter population synthesis code
Basic Info
- Host: GitHub
- Owner: grburgess
- License: gpl-3.0
- Language: Python
- Default Branch: master
- Homepage: https://popsynth.readthedocs.io/en/latest/?badge=latest
- Size: 124 MB
Statistics
- Stars: 14
- Watchers: 2
- Forks: 5
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
popsynth
popsynth core function is to create observed surveys from latent population models.
First, let's define what a population of objects is in terms of a
generative model. The two main ingredients are the objects' spatial
distribution () and the distribution of
their inherent properties (
). Here,
are the latent population parameters,
are the
spatial locations of the objects, and
are the properties
of the individual objects (luminosity, spin, viewing angle, mass,
etc.). The spatial distribution is defined such that:
is the intensity of objects for a given set of population
parameters. With these definitions we can define the probability for
an object to have position and properties
as
popsynth allows you to specify these spatial and property
distributions in an object-oriented way to create surveys. The final
ingredient to creating a sample for a survey is knowing how many
objects to sample from the population (before any selection effects
are applied). Often, we see this number in simulation frameworks
presented as "we draw N objects to guarantee we have enough." This is
incorrect. A survey takes place over a given period of time () in which observed objects are counted. This is a description of a
Poisson process. Thus, the number of objects in a simulation of this
survey is a draw from a Poisson distribution:
Thus, popsynth first numerically integrates the spatial
distribution to determine the Poisson rate parameter for the given
$\vec{\psi}$, then makes a Poisson draw for the number of objects in
the population survey. For each object, positions and properties are
drawn with arbitrary dependencies between them. Finally, selection
functions are applied to either latent or observed (with or without
measurement error) properties.
Note: If instead we draw a preset number of objects, as is done in many astrophysical population simulation frameworks, it is equivalent to running a survey up until that specific number of objects is detected. This process is distributed as a negative binomial process, i.e, wait for a number of successes and requires a different statistical framework to compare models to data.
Installation
bash
pip install popsynth
Note: This is not synth pop! If you were looking for some hard driving beats out of a yamaha keyboard with bells... look elsewhere
Contributing
Contributions to popsynth are always welcome. They can come in the form of:
Bug reports
Please use the Github issue tracking system for any bugs, for questions, and or feature requests.
Code and more distributions
While it is easy to create custom distributions in your local setup, if you would like to add them to popsynth directly, go ahead. Please include tests to ensure that your contributions are compatible with the code and can be maintained in the long term.
Documentation
Additions or examples, tutorials, or better explanations are always welcome. To ensure that the documentation builds with the current version of the software, I am using jupytext to write the documentation in Markdown. These are automatically converted to and executed as jupyter notebooks when changes are pushed to Github.
Owner
- Name: J. Michael Burgess
- Login: grburgess
- Kind: user
- Location: München, Germany
- Company: Max-Planck-Institut für extraterrestrische Physik
- Website: jmichaelburgess.com
- Twitter: morethanpriors
- Repositories: 172
- Profile: https://github.com/grburgess
JOSS Publication
popsynth: A generic astrophysical population synthesis framework
Authors
Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, 85748 Garching, Germany
Technical University of Munich, Boltzmannstrasse 2, 85748 Garching, Germany
Editor
Juanjo Bazán
Tags
astronomy population synthesis cosmologyGitHub Events
Total
Last Year
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| grburgess | j****s@g****m | 710 |
| Francesca Capel | c****a@g****m | 62 |
| Elisa Schösser | e****e@m****e | 10 |
| The Codacy Badger | b****r@c****m | 2 |
| Juanjo Bazán | j****n@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 0
- Total pull requests: 50
- Average time to close issues: N/A
- Average time to close pull requests: about 15 hours
- Total issue authors: 0
- Total pull request authors: 5
- Average comments per issue: 0
- Average comments per pull request: 0.84
- Merged pull requests: 49
- Bot issues: 0
- Bot pull requests: 0
Past Year
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- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
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- grburgess (35)
- cescalara (11)
- codacy-badger (2)
- eschoesser (1)
- xuanxu (1)
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 254 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 27
- Total maintainers: 1
pypi.org: popsynth
A population synthesis code
- Homepage: https://github.com/grburgess/popsynth
- Documentation: https://popsynth.readthedocs.io/
- License: GPL-3+
-
Latest release: 1.1.1
published over 3 years ago
Rankings
Maintainers (1)
Dependencies
- astropy *
- betagen *
- better_apidoc *
- class-registry *
- cython *
- h5py *
- ipykernel *
- ipython *
- ipyvolume *
- jupyterthemes *
- matplotlib *
- nbsphinx *
- numba *
- numpy >=1.20
- pandas *
- recommonmark *
- scipy *
- sphinx >=1.4
- sphinx-gallery *
- tqdm *
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