Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org, zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Keywords
Repository
Bayesian reconstruction of cosmic density fields
Basic Info
- Host: GitHub
- Owner: egpbos
- License: mit
- Language: C++
- Default Branch: master
- Size: 415 KB
Statistics
- Stars: 1
- Watchers: 5
- Forks: 1
- Open Issues: 1
- Releases: 2
Topics
Metadata Files
README.md
Barcode
Bayesian Reconstruction of COsmic DEnsity fields
This repository contains both Barcode and a set of supplementary analysis tools.
Citing
If you use this software, please cite it as:
Bos E. G. P., Kitaura F.-S., van de Weygaert R., 2019, MNRAS, 488, 2573
In bibtex format:
bibtex
@ARTICLE{2019MNRAS.488.2573B,
author = {{Bos}, E.~G. Patrick and {Kitaura}, Francisco-Shu and
{van de Weygaert}, Rien},
title = "{Bayesian cosmic density field inference from redshift space dark matter maps}",
journal = {MNRAS},
keywords = {methods: analytical, methods: statistical, galaxies: distances and redshifts, cosmology: observations, large-scale structure of Universe, Astrophysics - Cosmology and Nongalactic Astrophysics, Statistics - Applications, Statistics - Computation},
year = "2019",
month = "Sep",
volume = {488},
number = {2},
pages = {2573-2604},
doi = {10.1093/mnras/stz1864},
archivePrefix = {arXiv},
eprint = {1810.05189},
primaryClass = {astro-ph.CO},
adsurl = {https://ui.adsabs.harvard.edu/abs/2019MNRAS.488.2573B},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
Unique identifiers for citing the software itself (preferably in addition to citing the paper above) are provided through Zenodo (a unique DOI for each Barcode release) and the Astrophysics Source Code Library (all Barcode versions).
This code was previously described and applied in conference proceedings and in Patrick's PhD thesis.
Build
Install dependencies
Before compiling, make sure you have the required dependencies:
- CMake
- A compiler supporting at least C++11 (e.g. gcc 7 or clang 5)
- FFTW 3
- GNU Scientific Library
- ncurses
If you install these using a Linux package manager, make sure you get the development versions of the packages, i.e. the ones ending in -dev (libfftw3-dev, etcetera).
For instance, with apt-get in Debian or Ubuntu, you can install the requirements with:
sh
sudo apt-get install cmake g++ fftw3-dev libgsl-dev libncurses-dev
Using MacPorts on macOS, you can install the necessary packages with:
sh
sudo port install cmake fftw-3 fftw-3-single gsl ncurses
You can also use conda to install everything in a virtual environment:
sh
conda create -n barcode cmake cxx-compiler fftw gsl ncurses -c conda-forge
When using the conda environment, make sure you activate it before compiling and using barcode:
sh
conda activate barcode
Compile the code
Clone the repository and cd into the cloned directory:
sh
git clone https://github.com/egpbos/barcode.git
cd barcode
Then run cmake and make to configure and build:
sh
mkdir cmake-build
cd cmake-build
cmake ..
make
This will create binaries for barcode and the supplementary tools in the cmake-build directory.
Run
Barcode must be run in the same directory as the input.par file.
Edit this file to change input parameters.
Then simply run with:
cmake-build/barcode [restart_iteration]
Optionally add the restart_iteration number when doing a restart run from existing output files.
Development and contributing
This is an early release. Unit tests and other test codes will be added later (as mentioned in some of the code comments). Documentation as well.
Contributions are very welcome! Please don't hesitate to propose ideas for improvements in the GitHub issues or in a PR.
License
The original contributions made as part of this code are distributed under the MIT license (see LICENSE file).
When compiled, this code must link to FFTW 3 and the GNU Scientific Library (GSL). FFTW is distributed under the GNU Public License v2 or a later version, GSL under GPL v3. This means that any redistribution of Barcode in binary form is subject to GPL v3 terms.
Owner
- Name: Patrick Bos
- Login: egpbos
- Kind: user
- Location: Amsterdam
- Company: Netherlands eScience Center
- Website: http://egpbos.nl
- Repositories: 66
- Profile: https://github.com/egpbos
Technology Lead (software quality), freelance data scientist, cosmologist / scientific computing, HPC, data science, Bayesian inference
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 1
- Total pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: 6 minutes
- Total issue authors: 1
- Total pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- egpbos (1)
Pull Request Authors
- gitter-badger (1)