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autora

Automated Research Assistant

https://github.com/autoresearch/autora

Science Score: 77.0%

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
  • ✓
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    Found 6 DOI reference(s) in README
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    Links to: joss.theoj.org
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    6 of 20 committers (30.0%) from academic institutions
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    Low similarity (17.2%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Automated Research Assistant

Basic Info
Statistics
  • Stars: 62
  • Watchers: 3
  • Forks: 9
  • Open Issues: 37
  • Releases: 35
Created almost 6 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

Automated Research Assistant

PyPI GitHub Workflow Status PyPI - Downloads Link to docs License: MIT GitHub Discussions DOI

BRAINSTORM Program     Schmidt Science Fellows

AutoRA (Automated Research Assistant) is an open-source framework for automating multiple stages of the empirical research process, including model discovery, experimental design, data collection, and documentation for open science.

AutoRA was initially intended for accelerating research in the behavioral and brain sciences. However, AutoRA is designed as a general framework that enables automation of the research processes in other empirical sciences, such as material science or physics.

Autonomous Empirical Research Paradigm

Installation

We recommend using a Python environment manager like virtualenv. You may refer to the Development Guide on how to set up a virtual environment.

Before installing the PyPI autora package, you may activate your environment. To install the PyPI autora package, run the following command:

shell pip install "autora"

Documentation

Check out tutorials and documentation at https://autoresearch.github.io/autora. If you run into any issues or questions regarding the use of AutoRA, please reach out to us at the AutoRA forum.

Example

The following basic example demonstrates how to use AutoRA to automate the process of model discovery, experimental design, and data collection.

The discovery problem is defined by a single independent variable $x \in [0, 2 \pi]$ and dependent variable $y$. The experiment amounts to a simple sine wave, $y = \sin(x)$, which is the model we are trying to discover.

Th discovery cycle iterates between the experimentalist, experiment runner, and theorist. Here, we us a "random" experimentalist, which samples novel experimental conditions for $x$ every cycle. The experiment runner then collects data for the corresponding $y$ values. Finally, the theorist uses a Bayesian Machine Scientist (BMS; Guimerà et al., in Science Advances) to identify a scientific model that explains the data.

The workflow relies on the StandardState object, which stores the current state of the discovery process, such as conditions, experiment_data, or models. The state is passed between the experimentalist, experiment runner, and theorist.

```python

Import statements

import pandas as pd import numpy as np import sympy as sp

from autora.variable import Variable, ValueType, VariableCollection

from autora.experimentalist.random import randompool from autora.experimentrunner.synthetic.abstract.equation import equation_experiment from autora.theorist.bms import BMSRegressor

from autora.state import StandardState, onstate, estimatoron_state

Define initial data

Define variable data

iv = Variable(name="x", valuerange=(0, 2 * np.pi), allowedvalues=np.linspace(0, 2 * np.pi, 30)) dv = Variable(name="y", type=ValueType.REAL) variables = VariableCollection(independentvariables=[iv],dependentvariables=[dv])

Define seed condition data

conditions = randompool(variables, numsamples=10, random_state=0)

Define experimentalist

experimentalist = onstate(randompool, output=["conditions"])

Define experiment runner

sinexperiment = equationexperiment(sp.simplify('sin(x)'), variables.independentvariables, variables.dependentvariables[0]) sinrunner = sinexperiment.experiment_runner

experimentrunner = onstate(sinrunner, output=["experimentdata"])

Define theorist

theorist = estimatoronstate(BMSRegressor(epochs=100))

Define state

s = StandardState( variables = variables, conditions = conditions, experiment_data = pd.DataFrame(columns=["x","y"]) )

Cycle through the state

print('Pre-Defined State:') print(f"Number of datapoints collected: {len(s['experiment_data'])}") print(f"Derived models: {s['models']}") print('\n')

for i in range(5): s = experimentalist(s, numsamples=10, randomstate=42) s = experimentrunner(s, addednoise=1.0, randomstate=42) s = theorist(s) print(f"\nCycle {i+1} Results:") print(f"Number of datapoints collected: {len(s['experimentdata'])}") print(f"Derived models: {s['models']}") print('\n') ```

If you are curious about how to apply AutoRA to real-world discovery problems, you can find use case examples of AutoRA in the Use Case Tutorials section of the documentation.

Contributions

We welcome contributions to the AutoRA project. Please refer to the contributor guide for more information. Also, feel free to ask any questions or provide any feedback regarding core contributions on the AutoRA forum.

About

This project is in active development by the Autonomous Empirical Research Group.

The development of this package was supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University. The development of auxiliary packages for AutoRA, such as autodoc, is supported by Schmidt Sciences, LLC. and the Virtual Institute for Scientific Software (VISS). The AutoRA package was developed using computational resources and services at the Center for Computation and Visualization at Brown University.

Read More

Citation

If you would like to reference AutoRA, you can use the following BibTeX entry for the associated publication in JOSS:

bibtex @article{Musslick_AutoRA_Automated_Research_2024, author = {Musslick, Sebastian and Andrew, Benjamin and Williams, Chad C. and Hewson, Joshua T. S. and Li, Sida and Marinescu, Ioana and Dubova, Marina and Dang, George T. and Strittmatter, Younes and Holland, John G.}, doi = {10.21105/joss.06839}, journal = {Journal of Open Source Software}, month = dec, number = {104}, pages = {6839}, title = {{AutoRA: Automated Research Assistant for Closed-Loop Empirical Research}}, url = {https://joss.theoj.org/papers/10.21105/joss.06839}, volume = {9}, year = {2024} }

Owner

  • Name: Autonomous Empirical Research Initiative
  • Login: AutoResearch
  • Kind: organization

We strive to enhance and accelerate scientific discovery by automating steps in the empirical research process.

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Musslick
  given-names: Sebastian
  orcid: "https://orcid.org/0000-0002-8896-639X"
- family-names: Andrew
  given-names: Benjamin
- family-names: Williams
  given-names: Chad C.
  orcid: "https://orcid.org/0000-0003-2016-5614"
- family-names: Hewson
  given-names: Joshua T. S.
- family-names: Li
  given-names: Sida
  orcid: "https://orcid.org/0009-0009-7849-1923"
- family-names: Marinescu
  given-names: Ioana
- family-names: Dubova
  given-names: Marina
  orcid: "https://orcid.org/0000-0001-5264-0489"
- family-names: Dang
  given-names: George T.
  orcid: "https://orcid.org/0009-0008-1566-8245"
- family-names: Strittmatter
  given-names: Younes
  orcid: "https://orcid.org/0000-0002-3414-2838"
- family-names: Holland
  given-names: John G.
  orcid: "https://orcid.org/0000-0001-6845-8657"
contact:
- family-names: Musslick
  given-names: Sebastian
  orcid: "https://orcid.org/0000-0002-8896-639X"
doi: 10.5281/zenodo.14278950
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Musslick
    given-names: Sebastian
    orcid: "https://orcid.org/0000-0002-8896-639X"
  - family-names: Andrew
    given-names: Benjamin
  - family-names: Williams
    given-names: Chad C.
    orcid: "https://orcid.org/0000-0003-2016-5614"
  - family-names: Hewson
    given-names: Joshua T. S.
  - family-names: Li
    given-names: Sida
    orcid: "https://orcid.org/0009-0009-7849-1923"
  - family-names: Marinescu
    given-names: Ioana
  - family-names: Dubova
    given-names: Marina
    orcid: "https://orcid.org/0000-0001-5264-0489"
  - family-names: Dang
    given-names: George T.
    orcid: "https://orcid.org/0009-0008-1566-8245"
  - family-names: Strittmatter
    given-names: Younes
    orcid: "https://orcid.org/0000-0002-3414-2838"
  - family-names: Holland
    given-names: John G.
    orcid: "https://orcid.org/0000-0001-6845-8657"
  date-published: 2024-12-05
  doi: 10.21105/joss.06839
  issn: 2475-9066
  issue: 104
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6839
  title: "AutoRA: Automated Research Assistant for Closed-Loop Empirical
    Research"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06839"
  volume: 9
title: "AutoRA: Automated Research Assistant for Closed-Loop Empirical
  Research"

GitHub Events

Total
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  • Issues event: 35
  • Watch event: 22
  • Delete event: 31
  • Member event: 1
  • Issue comment event: 10
  • Push event: 361
  • Pull request review event: 20
  • Pull request event: 40
  • Fork event: 3
Last Year
  • Create event: 37
  • Release event: 1
  • Issues event: 35
  • Watch event: 22
  • Delete event: 31
  • Member event: 1
  • Issue comment event: 10
  • Push event: 361
  • Pull request review event: 20
  • Pull request event: 40
  • Fork event: 3

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 1,686
  • Total Committers: 20
  • Avg Commits per committer: 84.3
  • Development Distribution Score (DDS): 0.53
Top Committers
Name Email Commits
John Gerrard Holland j****1@b****u 793
Roger Guimera r****a@g****m 183
Sebastian Musslick s****n@m****e 145
benwandrew b****w@g****m 143
TheLemonPig 4****g@u****m 110
George Dang 5****g@u****m 96
TheLemonPig j****n@b****u 86
listar2000 3****0@u****m 44
dependabot[bot] 4****]@u****m 36
John Gerrard Holland o****e@j****e 22
seeslab s****b@g****m 7
listar2000 l****5@o****m 6
Admin i****m@p****u 4
Hannah Even h****n@g****m 3
Roger Guimera r****a@c****u 2
George Dang g****g@b****u 2
hollandjg h****g@u****m 1
Admin A****n@d****u 1
kphan20 8****0@u****m 1
ioanam25 7****5@u****m 1
Committer Domains (Top 20 + Academic)
brown.edu: 3 dynamic-oit-vapornet100-10-8-28-247.princeton.edu: 1 chem-eng.northwestern.edu: 1 princeton.edu: 1 jgholland.de: 1 musslick.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 122
  • Total pull requests: 164
  • Average time to close issues: 3 months
  • Average time to close pull requests: 7 days
  • Total issue authors: 8
  • Total pull request authors: 11
  • Average comments per issue: 0.61
  • Average comments per pull request: 0.57
  • Merged pull requests: 130
  • Bot issues: 0
  • Bot pull requests: 46
Past Year
  • Issues: 26
  • Pull requests: 24
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 9 days
  • Issue authors: 4
  • Pull request authors: 3
  • Average comments per issue: 0.23
  • Average comments per pull request: 0.25
  • Merged pull requests: 18
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • musslick (69)
  • hollandjg (20)
  • younesStrittmatter (16)
  • benwandrew (10)
  • chadcwilliams (3)
  • gtdang (3)
  • TheLemonPig (1)
  • LJKS (1)
Pull Request Authors
  • musslick (54)
  • dependabot[bot] (45)
  • hollandjg (34)
  • younesStrittmatter (32)
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  • chadcwilliams (6)
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Top Labels
Issue Labels
documentation (65) priority 1 - needed (32) enhancement (25) priority 2 - wanted (12) good first issue (9) priority 3 - optional (6) priority 0 - emergency (5) bug (4) theorist (3) refactor (3) duplicate (3) full cycle (2) test (2) PI priority (2)
Pull Request Labels
documentation (47) dependencies (45) enhancement (9) bug (7) priority 1 - needed (6) help wanted (1) experiment runner (1) theorist (1)

Packages

  • Total packages: 36
  • Total downloads:
    • pypi 9,547 last-month
  • Total dependent packages: 67
    (may contain duplicates)
  • Total dependent repositories: 6
    (may contain duplicates)
  • Total versions: 286
  • Total maintainers: 8
pypi.org: autora-core

Autonomous Research Assistant (AutoRA) is a framework for automating steps of the empirical research process.

  • Documentation: https://autora-core.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.
  • Latest release: 5.0.3
    published over 1 year ago
  • Versions: 24
  • Dependent Packages: 43
  • Dependent Repositories: 5
  • Downloads: 3,909 Last month
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Average: 4.5%
Dependent repos count: 6.6%
Downloads: 6.6%
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younesStrittmatter musslick
Last synced: 6 months ago
pypi.org: equation-tree

Describe your contribution

  • Documentation: https://equation-tree.readthedocs.io/
  • License: Copyright (c) 2023 Younes Strittmatter 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.
  • Latest release: 0.0.33
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  • Versions: 32
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  • Downloads: 46 Last month
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Average: 15.1%
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younesStrittmatter
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pypi.org: autora

Autonomous Research Assistant (AutoRA) is a framework for automating steps of the empirical research process.

  • Documentation: https://autora.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.
  • Latest release: 4.2.0
    published about 1 year ago
  • Versions: 45
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1,079 Last month
Rankings
Dependent packages count: 6.6%
Downloads: 12.2%
Average: 17.9%
Forks count: 19.6%
Stargazers count: 20.5%
Dependent repos count: 30.6%
Maintainers (5)
younesStrittmatter musslick benwandrew chadcwilliams gdang_brown
Last synced: 6 months ago
pypi.org: autora-theorist-bsr

Bayesian Symbolic Regression theorist for AutoRA

  • Versions: 11
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 180 Last month
Rankings
Dependent packages count: 7.2%
Average: 20.3%
Dependent repos count: 33.4%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-theorist-darts

Differentiable Architecture Search theorist for AutoRA

  • Documentation: https://autora-theorist-darts.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.
  • Latest release: 1.1.0
    published over 1 year ago
  • Versions: 8
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 264 Last month
Rankings
Dependent packages count: 7.2%
Average: 20.3%
Dependent repos count: 33.4%
Maintainers (2)
younesStrittmatter musslick
Last synced: 6 months ago
pypi.org: autora-theorist-bms

Bayesian Machine Scientist theorist for AutoRA

  • Documentation: https://autora-theorist-bms.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.
  • Latest release: 1.0.6
    published over 2 years ago
  • Versions: 9
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 440 Last month
Rankings
Dependent packages count: 7.2%
Average: 21.4%
Dependent repos count: 35.5%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: mixture-experimentalist

The goal of this project is to examine the performance of a mixture experimentalist–a hybrid of different experimental sampling strategies–in terms of its ability to recover a ground-truth model from synthetic data.

  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 163 Last month
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Dependent repos count: 41.5%
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blinodelka
Last synced: 6 months ago
pypi.org: autora-experiment-runner-firebase-prolific

AutoRA Firebase Prolific Experiment Runner provides experiment runners to run experiments with prolific and firebase

  • Documentation: https://autora-experiment-runner-firebase-prolific.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.
  • Latest release: 1.0.1
    published over 1 year ago
  • Versions: 10
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 138 Last month
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Dependent packages count: 7.2%
Average: 22.1%
Dependent repos count: 37.0%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experimentalist-sampler-uncertainty

Sampler based on where the model is least certain.

  • Versions: 3
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 25 Last month
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younesStrittmatter
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pypi.org: autora-experimentalist-sampler-model-disagreement

Compares weaknesses in multiple models

  • Versions: 4
  • Dependent Packages: 2
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younesStrittmatter hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-sampler-nearest-value

A sampler which returns the nearest values between the input samples and the allowed values, without replacement.

  • Versions: 2
  • Dependent Packages: 1
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  • Downloads: 31 Last month
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younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experimentalist-sampler-inequality

AutoRA Inequality Sampler

  • Versions: 2
  • Dependent Packages: 1
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  • Downloads: 26 Last month
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younesStrittmatter
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pypi.org: autora-experimentalist-sampler-novelty

AutoRA Novelty Experimentalist

  • Versions: 3
  • Dependent Packages: 1
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  • Downloads: 27 Last month
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younesStrittmatter
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pypi.org: autora-experimentalist-falsification

AutoRA Falsification Experimentalist

  • Documentation: https://autora-experimentalist-falsification.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.
  • Latest release: 2.2.0
    published over 1 year ago
  • Versions: 12
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 359 Last month
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Dependent packages count: 7.3%
Average: 24.5%
Downloads: 24.9%
Dependent repos count: 41.4%
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younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-theorist-toolkit

Toolkit to build algorithms for model recovery

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 88 Last month
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JoshuaTSHewson
Last synced: 6 months ago
pypi.org: autora-theorist-rnn-sindy-rl

An AutoRA theorist for discovering reinforcement learning models from behavioral experiments.

  • Documentation: https://autora-theorist-rnn-sindy-rl.readthedocs.io/
  • License: Copyright (c) 2024 Sebastian Musslick 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.
  • Latest release: 0.0.3
    published over 1 year ago
  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 40 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.3%
Dependent repos count: 60.0%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: rnn-sindy-rl

An AutoRA theorist for discovering reinforcement learning models from behavioral experiments.

  • Documentation: https://rnn-sindy-rl.readthedocs.io/
  • License: Copyright (c) 2024 Sebastian Musslick 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.
  • Latest release: 0.0.1a0
    published over 1 year ago
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 13 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.3%
Dependent repos count: 60.0%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-bandit-random

Create a sequence of bandit task rewards using initial reward probabilties and drift

  • Documentation: https://autora-experimentalist-bandit-random.readthedocs.io/
  • License: Copyright (c) 2024 Younes Strittmatter 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.
  • Latest release: 1.0.0
    published over 1 year ago
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 166 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.4%
Dependent repos count: 60.0%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: bandit-random

Create a sequence of bandit task rewards using iniitial reward probabilty and drift

  • Documentation: https://bandit-random.readthedocs.io/
  • License: Copyright (c) 2024 Younes Strittmatter 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.
  • Latest release: 0.0.1
    published over 1 year ago
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 15 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.4%
Dependent repos count: 60.0%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-prediction-filter

Filters condition based on model predictions.

  • Documentation: https://autora-experimentalist-prediction-filter.readthedocs.io/
  • License: Copyright (c) 2024 Younes Strittmatter 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.
  • Latest release: 1.1.0
    published over 1 year ago
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 167 Last month
Rankings
Dependent packages count: 10.8%
Average: 36.0%
Dependent repos count: 61.1%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-extrapolation

AutoRA Extrapolation Experimentalist

  • Documentation: https://autora-experimentalist-extrapolation.readthedocs.io/
  • License: Copyright (c) 2024 Younes Strittmatter 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.
  • Latest release: 1.0.1
    published over 1 year ago
  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 35 Last month
Rankings
Dependent packages count: 9.5%
Average: 36.2%
Dependent repos count: 62.9%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-divergence

sampling based on divergence

  • Documentation: https://autora-experimentalist-divergence.readthedocs.io/
  • License: Copyright (c) 2024 Younes Strittmatter 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.
  • Latest release: 0.0.2
    published almost 2 years ago
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 25 Last month
Rankings
Dependent packages count: 9.6%
Average: 36.5%
Dependent repos count: 63.4%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-sampler-leverage

Experimentalist that uses statistical leverage to determine the next data to sample.

  • Documentation: https://autora-experimentalist-sampler-leverage.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.
  • Latest release: 0.0.1a0
    published over 2 years ago
  • Versions: 1
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 27 Last month
Rankings
Dependent packages count: 7.6%
Average: 38.5%
Dependent repos count: 69.4%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: equation-sampler

Tool to sample equations

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 20 Last month
Rankings
Dependent packages count: 7.6%
Average: 38.5%
Dependent repos count: 69.4%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experimentalist-model-disagreement

Compares weaknesses in multiple models

  • Documentation: https://autora-experimentalist-model-disagreement.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.
  • Latest release: 2.2.0
    published over 1 year ago
  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 266 Last month
Rankings
Dependent packages count: 7.5%
Average: 38.6%
Dependent repos count: 69.6%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experimentalist-novelty

AutoRA Novelty Experimentalist

  • Documentation: https://autora-experimentalist-novelty.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.
  • Latest release: 2.2.0
    published over 1 year ago
  • Versions: 6
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 245 Last month
Rankings
Dependent packages count: 7.5%
Average: 38.6%
Dependent repos count: 69.6%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-synthetic-abstract-equation

An experiment runner from arbitrary equations

  • Versions: 8
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 83 Last month
Rankings
Dependent packages count: 7.5%
Average: 38.6%
Dependent repos count: 69.7%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-synthetic-abstract-sympy-equation

An experiment runner that uses an arbitrary sympy function

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 22 Last month
Rankings
Dependent packages count: 7.5%
Average: 38.6%
Dependent repos count: 69.7%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experiment-runner-synthetic-psychology-ssm

Run synthetic experiments with hierarchical sequential sampling models

  • Documentation: https://autora-experiment-runner-synthetic-psychology-ssm.readthedocs.io/
  • License: Copyright (c) 2023 Enter your full name 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.
  • Latest release: 0.0.2
    published about 2 years ago
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 21 Last month
Rankings
Dependent packages count: 10.1%
Average: 38.6%
Dependent repos count: 67.1%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-uncertainty

Experimentalist based on where the model is least certain.

  • Documentation: https://autora-experimentalist-uncertainty.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.
  • Latest release: 2.1.0
    published over 1 year ago
  • Versions: 2
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 167 Last month
Rankings
Dependent packages count: 9.8%
Average: 38.8%
Dependent repos count: 67.8%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-inequality

AutoRA Inequality Experimentalist

  • Documentation: https://autora-experimentalist-inequality.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.
  • Latest release: 2.2.0
    published over 1 year ago
  • Versions: 3
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 182 Last month
Rankings
Dependent packages count: 9.8%
Average: 38.8%
Dependent repos count: 67.8%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-assumption

Describe your contribution

  • Documentation: https://autora-experimentalist-assumption.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.
  • Latest release: 1.0.0
    published over 2 years ago
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 22 Last month
Rankings
Dependent packages count: 9.8%
Average: 38.8%
Dependent repos count: 67.8%
Maintainers (1)
musslick
Last synced: 6 months ago
pypi.org: autora-experimentalist-nearest-value

A experimentalist which returns the nearest values between the input samples and the allowed values, without replacement.

  • Documentation: https://autora-experimentalist-nearest-value.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.
  • Latest release: 2.2.0
    published over 1 year ago
  • Versions: 3
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 166 Last month
Rankings
Dependent packages count: 9.8%
Average: 38.8%
Dependent repos count: 67.8%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experimentalist-leverage

Experimentalist that uses statistical leverage to determine the next data to sample.

  • Documentation: https://autora-experimentalist-leverage.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.
  • Latest release: 1.0.0
    published over 2 years ago
  • Versions: 2
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 178 Last month
Rankings
Dependent packages count: 9.8%
Average: 38.8%
Dependent repos count: 67.8%
Maintainers (1)
hollandjg
Last synced: 6 months ago
pypi.org: autora-experiment-runner-experimentation-manager-firebase

AutoRA Experimentation Manager Firebase provides functionality to manage communication of conditions and observations between AutoRA and an experiment on Firebase.

  • Documentation: https://autora-experiment-runner-experimentation-manager-firebase.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.
  • Latest release: 1.1.5
    published 7 months ago
  • Versions: 14
  • Dependent Packages: 2
  • Dependent Repositories: 0
  • Downloads: 226 Last month
Rankings
Dependent packages count: 7.5%
Average: 40.7%
Downloads: 44.8%
Dependent repos count: 69.8%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago
pypi.org: autora-experiment-runner-recruitment-manager-prolific

AutoRA Prolific Recruitment Manager provides functionality to recruit participants via Prolific to set up an experiment runner for AutoRA

  • Documentation: https://autora-experiment-runner-recruitment-manager-prolific.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.
  • Latest release: 1.0.1
    published over 1 year ago
  • Versions: 21
  • Dependent Packages: 2
  • Dependent Repositories: 0
  • Downloads: 200 Last month
Rankings
Dependent packages count: 7.5%
Average: 41.8%
Downloads: 48.2%
Dependent repos count: 69.8%
Maintainers (1)
younesStrittmatter
Last synced: 6 months ago

Dependencies

pyproject.toml pypi
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  • mkdocs-literate-nav ^0.4.1 develop
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  • mkdocs-section-index ^0.3.4 develop
  • mkdocstrings-python ^0.7.1 develop
  • pytest ^7.1.2 develop
  • graphviz ^0.14.1
  • imageio ^2.9.0
  • matplotlib ^3.2.1
  • numpy ^1.18
  • pandas ^1.4.2
  • python ^3.8
  • scikit-learn ^1.1.1
  • scipy ^1.7.1
  • seaborn ^0.11.1
  • tinkerforge ^2.1.25
  • torch ^1.11.0
  • tqdm ^4.64.0
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