The TesseRACt package is designed to compute concentrations of simulated dark
matter halos from volume info for particles generated using Voronoi tesselation.
This technique is advantageous as it is non-parametric, does not assume
spherical symmetry, and allows for the presence of substructure. For a more
complete description of this technique including a comparison to other
techniques for calculating concentration, please see the accompanying paper
`Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_.
This package includes:
* **vorovol**: C program for computing the Voronoi diagram of particle data in a number of formats including Gadget-2, Gasoline, binary, and ASCII as well as BGC2 halo catalogues.
* routines for compiling, running, and parsing **vorovol** output
* routines for computing concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry.
* routines and test halos for running many of the performance tests presented in `Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_.
Below are some useful links associated with TesseRACt:
* `PyPI <https://pypi.python.org/pypi/tesseract>`_ - The most recent stable release.
* `Docs <http://pytesseract.readthedocs.org/en/latest/>`_ - Tutorials and descriptions of the package modules and functions.
* `Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_ - The accompanying scientific paper.
If you would like more information about TesseRACt, please contact `Meagan Lang <mailto:cfh5058@gmail.com>`_.
Raw data
{
"_id": null,
"home_page": "http://vpac00.phy.vanderbilt.edu/~langmm/index.html",
"name": "tesseract",
"maintainer": "",
"docs_url": null,
"requires_python": null,
"maintainer_email": "",
"keywords": "",
"author": "Meagan Lang",
"author_email": "meagan.lang@vanderbilt.edu",
"download_url": "https://files.pythonhosted.org/packages/8d/b7/c4fae9af5842f69d9c45bf1195a94aec090628535c102894552a7a7dbe6c/tesseract-0.1.3.tar.gz",
"platform": "UNKNOWN",
"description": "The TesseRACt package is designed to compute concentrations of simulated dark\r\nmatter halos from volume info for particles generated using Voronoi tesselation.\r\nThis technique is advantageous as it is non-parametric, does not assume \r\nspherical symmetry, and allows for the presence of substructure. For a more\r\ncomplete description of this technique including a comparison to other \r\ntechniques for calculating concentration, please see the accompanying paper \r\n`Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_.\r\n\r\nThis package includes:\r\n * **vorovol**: C program for computing the Voronoi diagram of particle data in a number of formats including Gadget-2, Gasoline, binary, and ASCII as well as BGC2 halo catalogues.\r\n * routines for compiling, running, and parsing **vorovol** output\r\n * routines for computing concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry.\r\n * routines and test halos for running many of the performance tests presented in `Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_.\r\n\r\nBelow are some useful links associated with TesseRACt:\r\n * `PyPI <https://pypi.python.org/pypi/tesseract>`_ - The most recent stable release.\r\n * `Docs <http://pytesseract.readthedocs.org/en/latest/>`_ - Tutorials and descriptions of the package modules and functions.\r\n * `Lang et al. (2015) <http://arxiv.org/abs/1504.04307>`_ - The accompanying scientific paper.\r\n\r\nIf you would like more information about TesseRACt, please contact `Meagan Lang <mailto:cfh5058@gmail.com>`_.",
"bugtrack_url": null,
"license": "UNKNOWN",
"summary": "Tesselation based Recovery of Amorphous halo Concentrations",
"version": "0.1.3",
"project_urls": {
"Download": "UNKNOWN",
"Homepage": "http://vpac00.phy.vanderbilt.edu/~langmm/index.html"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "8db7c4fae9af5842f69d9c45bf1195a94aec090628535c102894552a7a7dbe6c",
"md5": "960d52b63ed99e2665c007633904ebac",
"sha256": "4ab908f06ff15b60959ed0f200bddf8309ed02e6435ddc29445961cf8e3f5365"
},
"downloads": -1,
"filename": "tesseract-0.1.3.tar.gz",
"has_sig": false,
"md5_digest": "960d52b63ed99e2665c007633904ebac",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 45555135,
"upload_time": "2015-07-13T21:21:24",
"upload_time_iso_8601": "2015-07-13T21:21:24.512781Z",
"url": "https://files.pythonhosted.org/packages/8d/b7/c4fae9af5842f69d9c45bf1195a94aec090628535c102894552a7a7dbe6c/tesseract-0.1.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2015-07-13 21:21:24",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "tesseract"
}