Science Score: 23.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
9 of 16 committers (56.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.5%) to scientific vocabulary
Keywords
Repository
Ultra-faint galaxy likelihood toolkit
Basic Info
- Host: GitHub
- Owner: DarkEnergySurvey
- License: mit
- Language: Python
- Default Branch: main
- Size: 1.57 MB
Statistics
- Stars: 15
- Watchers: 8
- Forks: 15
- Open Issues: 27
- Releases: 5
Topics
Metadata Files
README.md
Overview
The ultra-faint galaxy likelihood (ugali) toolkit provides a set of python modules developed for maximum-likelihood-based studies of resolved satellite galaxies. The primary inputs are stellar object catalogs derived from optical photometric surveys and the coverage masks of those surveys. In addition, ugali ships with a set of synthetic isochrone libraries and catalogs of known resolved stellar systems.
Authors: Keith Bechtol & Alex Drlica-Wagner
Installation
There are several ways to install ugali.
The most robust way is to follow the installation procedure for the automated GitHub Actions build documented in python-package.yml. This installation creates a conda environment with the necessary dependencies and installs ugali.
```bash
Create and activate conda environment
conda create -n ugali-env numpy scipy matplotlib astropy healpy pyyaml emcee nose fitsio corner -c conda-forge -c kadrlica source activate ugali-env
Clone source code from the parent repository
git clone https://github.com/DarkEnergySurvey/ugali.git && cd ugali
Install just the python source code
python setup.py install
Install source code with a minimal set of isochrone and catalog libraries
python setup.py install --isochrones --catalogs ```
In theory, the easiest way to get a stable release of ugali is through PyPi using pip:
```bash
Install just the source code
pip install ugali
Install source code with a minimal set of isochrone and catalog libraries
pip install ugali --install-option "--isochrones" --install-option "--catalogs" ```
By default, the minimal isochrone and catalog libraries are installed into the directory specified by the $UGALIDIR environment variable (default: $HOME/.ugali). The download and unpacking of the isochrone and catalog files might make it appear that your pip installation has stalled. Unfortunately, pip may not display a progress bar during this delay.
Auxiliary Libraries
The ugali source code is distributed with several auxiliary libraries for isochrone generation and catalog matching. These libraries can be downloaded directly from the releases page, and unpacked in your $UGALIDIR. For example, to install the Bressan et al. 2012 isochrones for the DES survey:
cd $UGALIDIR
wget https://github.com/DarkEnergySurvey/ugali/releases/download/v1.8.0/ugali-des-bressan2012.tar.gz
tar -xzf ugali-des-bressan2012.tar.gz
The UGALIDIR environment variable is used to point to the isochrone and catalog libraries. If you install the isochrones in a non-standard location be sure to set UGALIDIR so ugali can find them:
export UGALIDIR=<PATH>
An experimental interface for downloading the isochrone and catalog libraries also exists through setup.py:
```
To install the Bressan+ 2012 isochrones for the DES survey
python setup.py isochrones --survey des --model bressan2012
If you have isochrones already installed, you may need to force
python setup.py isochrones --survey des --model bressan2012 --force
To install all available DES isochrones
python setup.py isochrones --survey des
To install all available Bressan+ 2012 isochrones
python setup.py isochrones --model bressan2012
To install the catalog libraries
python setup.py catalogs ```
Usage Examples
Several examples can be found as jupyter notebooks in the notebooks directory.
Additional Information
Dependencies
These should mostly be taken care of by PyPi with a pip install.
* numpy
* scipy
* matplotlib
* astropy
* healpy
* emcee
* pyyaml
* fitsio
Isochrones
The isochrones used by ugali come dominantly from:
* PARSEC isochrones from the Padova group (http://stev.oapd.inaf.it/cgi-bin/cmd)
* Dartmouth isochrones (http://stellar.dartmouth.edu/models/isolfnew.html)
* MESA isochrones (http://waps.cfa.harvard.edu/MIST/interpisos.html)
More information can be found in the isochrone module.
Abbreviations
- CMD: color-magnitude diagram
- ROI: region of interest
- PDF: probability distribution function
- LKHD: likelihood
- IMF: initial mass function
- LUT: look-up table
Owner
- Name: Dark Energy Survey
- Login: DarkEnergySurvey
- Kind: organization
- Location: NCSA, University of Illinois, Urbana IL
- Website: http://www.darkenergysurvey.org
- Repositories: 48
- Profile: https://github.com/DarkEnergySurvey
Data Management
GitHub Events
Total
- Issues event: 2
- Watch event: 1
- Issue comment event: 6
- Push event: 2
- Pull request event: 3
- Fork event: 1
Last Year
- Issues event: 2
- Watch event: 1
- Issue comment event: 6
- Push event: 2
- Pull request event: 3
- Fork event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 668
- Total Committers: 16
- Avg Commits per committer: 41.75
- Development Distribution Score (DDS): 0.163
Top Committers
| Name | Commits | |
|---|---|---|
| Alex Drlica-Wagner | k****a@f****v | 559 |
| Keith Bechtol | b****l@d****v | 39 |
| Keith Bechtol | k****l@l****g | 18 |
| Sidney Mau | s****u@g****m | 12 |
| Mitch McNanna | m****a@w****u | 9 |
| KeithBechtol | k****l@e****u | 8 |
| Keith Bechtol | b****l@m****l | 6 |
| KeithBechtol | k****l@d****u | 4 |
| Keith Bechtol | b****l@m****l | 4 |
| Keith Bechtol | b****l@d****v | 3 |
| Johann Cohen-Tanugi | j****i@g****m | 1 |
| Ethan O. Nadler | e****r@s****u | 1 |
| scantu | s****3@t****u | 1 |
| Alex Drlica-Wagner | k****a@k****u | 1 |
| William Cerny | W****y@g****m | 1 |
| Mitch McNanna | m****a@c****v | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: over 2 years ago
All Time
- Total issues: 54
- Total pull requests: 44
- Average time to close issues: 10 months
- Average time to close pull requests: 8 days
- Total issue authors: 6
- Total pull request authors: 9
- Average comments per issue: 1.39
- Average comments per pull request: 0.5
- Merged pull requests: 38
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- kadrlica (46)
- sidneymau (3)
- psferguson (2)
- willcerny (2)
- apace7 (1)
- mcnanna (1)
Pull Request Authors
- kadrlica (36)
- willcerny (4)
- sidneymau (3)
- mcnanna (1)
- bechtol (1)
- scantu (1)
- eonadler (1)
- TrellixVulnTeam (1)
- AlexKurek (1)
- johannct (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 24 last-month
- Total dependent packages: 0
- Total dependent repositories: 2
- Total versions: 8
- Total maintainers: 1
pypi.org: ugali
Ultra-faint galaxy likelihood toolkit.
- Homepage: https://github.com/DarkEnergySurvey/ugali
- Documentation: https://ugali.readthedocs.io/
- License: MIT License
-
Latest release: 1.8.0
published over 4 years ago
Rankings
Maintainers (1)
Dependencies
- astropy *
- corner *
- emcee *
- fitsio *
- healpy *
- matplotlib *
- numpy *
- pyyaml *
- scipy *
- actions/checkout v2 composite
- actions/setup-python v2 composite