The ultra-faint galaxy likelihood (UGaLi) toolkit provides a set of python classes and functions developed for maximum-likelihood-based studies of Milky Way satellite galaxies. The primary inputs are stellar object catalogs derived from optical photometric surveys and the coverage masks of those surveys.
Keith Bechtol & Alex Drlica-Wagner
There are several ways to install ugali and it's complimentary isochrone library.
The easiest way to install ugali is through PyPi using pip:
# To install just the source code
pip install ugali
# To install source code and isochrone library
pip install ugali --install-option "--isochrones"
# To specify a path for the isochrone library
pip install ugali --install-option "--isochrones" --install-option "--isochrones-path <PATH>"
The isochrone library is a ~100 MB tarball. The default isochrone installation location is set by the UGALIDIR environment variable and defaults to $HOME/.ugali. The download and unpacking of the isochrone files might make it appear that your pip installation has stalled. Unfortunately, pip will not display a progress bar during this delay.
To get the most up-to-date version of ugali, you can download the source code from github and install it using setup.py:
# Clone source code from the parent repository
git clone https://github.com/DarkEnergySurvey/ugali.git
cd ugali
# Install the python source code
python setup.py install
# Also install the isochrone library
python setup.py install --isochrones
# Specify the isochrone install path
python setup.py install --isochrones --isochrones-path=<PATH>
The code uses the UGALIDIR environment variable to find the isochrones (defaults to $HOME/.ugali). If you install the isochrones in a non-standard location be sure to set UGALIDIR so ugali can find them:
export UGALIDIR=<PATH>
If all else fails, check out the automated build installation procedure using conda in .travis.yml.
Examples go here...
These should mostly be taken care of by PyPi with a pip install.
Not a strict dependency. Used to interface with masks produced by the Dark Energy Survey Data Mangement group. Download and documentation available at http://space.mit.edu/~molly/mangle/
The ugali uses a library of stellar isochrones packaged with ugali releases. These isochrones come dominantly from two different groups:
- Padova isochrones (http://stev.oapd.inaf.it/cgi-bin/cmd)
- Dartmouth isochrones (http://stellar.dartmouth.edu/models/isolf_new.html)
array[index_z][index_y][index_x]
- package_name
- module_name.py
- ClassName
- functionName
- variable_name
- IMF: initial mass function
- CMD: color-magnitude diagram
- ROI: region of interest
- PDF: probability distribution function
- LUT: look-up table
- LKHD: likelihood