bet
Python package for data-consistent stochastic inverse and forward problems.
Science Score: 33.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 11 DOI reference(s) in README -
✓Academic publication links
Links to: scholar.google, wiley.com, iop.org, zenodo.org -
✓Committers with academic emails
5 of 12 committers (41.7%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (15.0%) to scientific vocabulary
Repository
Python package for data-consistent stochastic inverse and forward problems.
Basic Info
- Host: GitHub
- Owner: UT-CHG
- License: other
- Language: Python
- Default Branch: master
- Homepage: http://ut-chg.github.io/BET
- Size: 20.1 MB
Statistics
- Stars: 11
- Watchers: 3
- Forks: 21
- Open Issues: 29
- Releases: 0
Metadata Files
README.md
BET
BET is a Python package for data-consistent stochastic forward and inverse problems. The package is very flexible and is applicable to a wide variety of problems.
BET is an initialism of Butler, Estep and Tavener, the primary authors of a series of papers that introduced the mathematical framework for measure-based data-consistent stochastic inversion, for which BET included a computational implementation. However, since its initial inception it has grown to include a broad range of data-consistent methods. It has been applied to a wide variety of application problems, many of which can be found here.
Installation
The current development branch of BET can be installed from GitHub, using pip:
pip install git+https://github.com/UT-CHG/BET
Another option is to clone the repository and install BET using
python setup.py install
Dependencies
BET is tested on Python 3.6, 3.7, and 3.8 (but should work on most recent Python 3 versions) and depends on NumPy, SciPy, matplotlib, pyDOE, pytest, and mpi4py (optional) (see requirements.txt for version information). For some optional features LUQ is also required. mpi4py is required to take advantage of parallel features and requires an mpi implementation. It can be installed by:
pip install mpi4py
License
GNU Lesser General Public License (LGPL)
Citing BET
Please include the citation:
Lindley Graham, Steven Mattis, Michael Pilosov, Scott Walsh, Troy Butler, Michael Pilosov, … Damon McDougall. (2020, July 9). UT-CHG/BET: BET v3.0.0 (Version v3.0.0). Zenodo. http://doi.org/10.5281/zenodo.3936258
or in BibTEX:
@software{BET,
author = {Lindley Graham and
Steven Mattis and
Michael Pilosov and
Scott Walsh and
Troy Butler and
Wenjuan Zhang and
Damon McDougall},
title = {UT-CHG/BET: BET v3.0.0},
month = jul,
year = 2020,
publisher = {Zenodo},
version = {v3.0.0},
doi = {10.5281/zenodo.3936258},
url = {https://doi.org/10.5281/zenodo.3936258}
}
Documentation
This code has been documented with sphinx. the documentation is available online at http://ut-chg.github.io/BET. To build documentation run
make html in the doc/ folder.
To build/update the documentation use the following commands:
sphinx-apidoc -f -o doc bet
cd doc/
make html
make html
This creates the relevant documentation at bet/gh-pages/html.
To change the build location of the documentation you will need to update doc/makefile.
You will need to run sphinx-apidoc and reinstall bet anytime a new module or method in the source code has been added.
If only the *.rst files have changed then you can simply run make html twice in the doc folder.
Building the docs requires Sphinx and the Read the Docs Sphinx theme, which can be installed with pip by:
pip install Sphinx sphinx_rtd_theme
Examples
Examples scripts are contained in here.
You can also try out BET in your browser using Binder.
Testing
To run the tests in the root directory with pytest in serial call:
pytest ./test/
Some features of BET (primarily those associated with the measure-based approach) have the ability to work in parallel. To run tests in parallel call:
mpirun -np NPROC pytest ./test/
Make sure to have a working MPI environment (we recommend mpich) if you want to use parallel features.
(Note: you may need to set ~/.config/matplotlib/matplotlibrc to include backend:agg if there is no DISPLAY port in your environment).
Contributors
See the GitHub contributors page.
Contact
BET is in active development. Hence, some features are still being added and you may find bugs we have overlooked. If you find something please report these problems to us through GitHub so that we can fix them. Thanks!
Please note that we are using continuous integration and issues for bug tracking.
Owner
- Name: UT Austin Computational Hydrualics Group
- Login: UT-CHG
- Kind: organization
- Website: http://chg.ices.utexas.edu/
- Repositories: 17
- Profile: https://github.com/UT-CHG
The Computational Hydraulics Group (CHG) at The University of Texas at Austin.
GitHub Events
Total
Last Year
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Steve Mattis | s****s@g****m | 317 |
| Lindley Graham | l****m@g****m | 290 |
| Michael Pilosov | c****s@g****m | 257 |
| Lindley Graham | l****m@i****u | 208 |
| Scott Walsh | s****3@g****m | 128 |
| Troy Butler | b****d@g****m | 89 |
| Steven Andrew Mattis | s****n@p****u | 24 |
| M. Pilosov | m****v@u****u | 9 |
| Michael Pilosov | 4****l | 7 |
| Wenjuan | w****g@u****u | 4 |
| Damon McDougall | d****l@g****m | 2 |
| Scott Walsh | w****h@s****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: over 2 years ago
All Time
- Total issues: 44
- Total pull requests: 56
- Average time to close issues: 7 months
- Average time to close pull requests: 24 days
- Total issue authors: 7
- Total pull request authors: 5
- Average comments per issue: 3.95
- Average comments per pull request: 2.41
- Merged pull requests: 46
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- mathematicalmichael (33)
- smattis (4)
- lcgraham (2)
- eecsu (2)
- User-zwj (1)
- mpilosov (1)
- yentyu (1)
Pull Request Authors
- mathematicalmichael (27)
- smattis (24)
- yentyu (3)
- User-zwj (1)
- lcgraham (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 64 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 2
- Total maintainers: 1
pypi.org: bet
A toolkit for data-consistent stochastic problems.
- Homepage: https://github.com/UT-CHG/BET
- Documentation: https://bet.readthedocs.io/
- License: GNU LGPL
-
Latest release: 3.0.0
published almost 6 years ago