https://github.com/autoresearch/autora-synthetic
Science Score: 13.0%
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
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○DOI references
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○Academic publication links
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○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 (5.3%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: AutoResearch
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://autoresearch.github.io/autora-synthetic-data/
- Size: 26.2 MB
Statistics
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 6
- Releases: 15
Metadata Files
README.md
AutoRA Synthetic Data
Synthetic experiment data for testing AutoRA theorists and experimentalists.
User Guide
You will need:
python3.8 or greater: https://www.python.org/downloads/
Install the synthetic data package (as part of autora):
shell
pip install -U "autora"
💡We recommend using a
pythonenvironment manager likevirtualenv.
Print a description of the prospect theory model by Kahneman and Tversky by running:
shell
python -c "
from autora.experiment_runner.synthetic.economics.prospect_theory import prospect_theory
study = prospect_theory()
print(study.description)
"
For more information, see the documentation.
Owner
- Name: Autonomous Empirical Research Initiative
- Login: AutoResearch
- Kind: organization
- Website: www.empiricalresearch.ai
- Repositories: 12
- Profile: https://github.com/AutoResearch
We strive to enhance and accelerate scientific discovery by automating steps in the empirical research process.
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Packages
- Total packages: 1
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Total downloads:
- pypi 957 last-month
- Total dependent packages: 5
- Total dependent repositories: 0
- Total versions: 12
- Total maintainers: 2
pypi.org: autora-synthetic
AutoRA Synthetic Experiments
- Documentation: https://autora-synthetic.readthedocs.io/
- License: MIT License Copyright (c) 2023 Autonomous Empirical Research Initiative Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Latest release: 2.2.0
published over 1 year ago