Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org, acs.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 (4.7%) to scientific vocabulary
Repository
A library of discrete objectives
Basic Info
Statistics
- Stars: 21
- Watchers: 4
- Forks: 1
- Open Issues: 60
- Releases: 8
Metadata Files
README.MD
poli 🧪, a library for discrete objective functions
poli is a library of discrete objective functions for benchmarking optimization algorithms.
Black boxes
| Black box | References | Tests
|----------|----------|----------|
| Toy continuous functions (e.g. Ackley, Hartmann...) | (Al-Roomi 2015), (Surjanovic & Bingham 2013) | |
| Ehrlich functions | (Stanton et al. 2024) |
| PMO/GuacaMol benchmark | (Brown et al. 2019), (Gao et al. 2022), (Huang et al. 2021) | 
| Dockstring | (García-Ortegón et al. 2022) | 
| Rosetta Energy | (Chaudhury et al. 2010) | 
| RaSP | (Blaabjerg et al. 2023) | 
| FoldX stability and SASA | (Schymkowitz et al. 2005) | - |
Features
- 🔲 isolation of black box function calls inside conda environments. Don't worry about clashes w. black box requirements, poli will create the relevant conda environments for you.
- 🗒️ logging each black box call using observers.
- A numpy interface. Inputs are
np.arrays of strings, outputs arenp.arrays of floats. SMILESandSELFIESsupport for small molecule manipulation.
Getting started
To install poli, we recommend creating a fresh conda environment
bash
conda create -n poli-base python=3.9
conda activate poli-base
pip install git+https://github.com/MachineLearningLifeScience/poli.git@dev
To check if everything went well, you can run
bash
$ python -c "from poli import create"
An example: dockstring
In this next example, we estimate the docking score of the example provided in dockstring:
```python
import numpy as np
from poli import objective_factory
problem = objectivefactory.create( name="dockstring", targetname="drd2" ) f, x0 = problem.black_box, problem.x0 y0 = f(x0)
x0: ['C' 'C' '1' '=' 'C' '(' 'C', ...]
y0: 11.9
print(x0, y0) ```
Cite us and other relevant work
If you use certain black boxes, we expect you to cite the relevant work. Check inside the documentation of each black box for the relevant references.
Where can I find the documentation?
The main documentation site is hosted as a GitHub page here: https://machinelearninglifescience.github.io/poli-docs/
Building the documentation locally
If you install the requirements-dev.txt via
bash
pip install -r requirements-dev.txt
then you will have access to sphinx. You should be able to build the documentation by going to the docs folder and building it:
bash
cd docs/
make html
Afterwards, you can enter the build folder and open index.html.
Owner
- Name: Machine Learning in Life Science
- Login: MachineLearningLifeScience
- Kind: organization
- Repositories: 1
- Profile: https://github.com/MachineLearningLifeScience
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below. Make sure you also cite the relevant software used in the black-boxes." authors: - family-names: "González-Duque" given-names: "Miguel" - family-names: "Bartels" given-names: "Simon" - family-names: "Michael" given-names: "Richard" title: "poli: a libary of discrete sequence objectives" version: 1.2.0 date-released: 2024-01-23 url: "https://github.com/MachineLearningLifeScience/poli"
GitHub Events
Total
- Create event: 21
- Release event: 3
- Issues event: 22
- Watch event: 6
- Delete event: 13
- Issue comment event: 13
- Push event: 90
- Pull request review event: 14
- Pull request review comment event: 11
- Pull request event: 37
Last Year
- Create event: 21
- Release event: 3
- Issues event: 22
- Watch event: 6
- Delete event: 13
- Issue comment event: 13
- Push event: 90
- Pull request review event: 14
- Pull request review comment event: 11
- Pull request event: 37
Issues and Pull Requests
Last synced: 10 months ago
All Time
- Total issues: 9
- Total pull requests: 8
- Average time to close issues: about 1 month
- Average time to close pull requests: about 16 hours
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.56
- Average comments per pull request: 0.38
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 9
- Pull requests: 8
- Average time to close issues: about 1 month
- Average time to close pull requests: about 16 hours
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 0.56
- Average comments per pull request: 0.38
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- miguelgondu (51)
- RMichae1 (24)
- SimonBartels (2)
Pull Request Authors
- miguelgondu (87)
- RMichae1 (14)
- SimonBartels (6)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
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Total downloads:
- pypi 38 last-month
-
Total dependent packages: 0
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 5
- Total maintainers: 2
pypi.org: poli-core
poli, a library of discrete objective functions
- Homepage: https://github.com/MachineLearningLifeScience/poli
- Documentation: https://poli-core.readthedocs.io/
- License: MIT LICENSE Copyright 2023 MLLS 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: 1.2.0
published over 1 year ago
Rankings
Maintainers (2)
pypi.org: poli-base
poli, a library of discrete objective functions
- Homepage: https://github.com/MachineLearningLifeScience/poli
- Documentation: https://poli-base.readthedocs.io/
- License: MIT LICENSE Copyright 2023 MLLS 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: 1.0.1
published over 1 year ago