Galsampler algorithms used for generating synthetic cosmological data
Project description
GalSampler
Tools for generating synthetic cosmological data.
Installation
The latest release of galsampler, v0.1.0, can be installed with conda-forge:
$ conda install lsstdesc-galsampler
To install galsampler into your environment from the source code:
$ cd /path/to/root/galsampler $ pip install .
However you install the code, to use it from a python interpreter:
>>> import galsampler
Documentation
See https://galsampler.readthedocs.io/en/latest for complete documentation and usage tutorials.
Citation information
The galsampler paper has been published in MNRAS. Citation information for the paper can be found at [this ADS link](https://ui.adsabs.harvard.edu/abs/2020MNRAS.495.5040H/exportcitation), copied below for convenience:
@ARTICLE{2020MNRAS.495.5040H, author = {{Hearin}, Andrew and {Korytov}, Danila and {Kovacs}, Eve and {Benson}, Andrew and {Aung}, Han and {Bradshaw}, Christopher and {Campbell}, Duncan and {LSST Dark Energy Science Collaboration}}, title = "{Generating synthetic cosmological data with GalSampler}", journal = {\mnras}, keywords = {large-scale structure of Universe, Astrophysics - Cosmology and Nongalactic Astrophysics}, year = 2020, month = jul, volume = {495}, number = {4}, pages = {5040-5051}, doi = {10.1093/mnras/staa1495}, archivePrefix = {arXiv}, eprint = {1909.07340}, primaryClass = {astro-ph.CO}, adsurl = {https://ui.adsabs.harvard.edu/abs/2020MNRAS.495.5040H}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }
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