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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}
}

Project details


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galsampler-0.1.1.tar.gz (19.4 kB view hashes)

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