AutoEmulate

AutoEmulate: A Python package for semi-automated emulation - Published in JOSS (2025)

https://github.com/alan-turing-institute/autoemulate

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 5 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org
  • Committers with academic emails
    4 of 16 committers (25.0%) from academic institutions
  • Institutional organization owner
    Organization alan-turing-institute has institutional domain (turing.ac.uk)
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

active-learning calibration emulation ensemble gaussian-processes history-matching hut23 hut23-1468 mcmc neural-networks pytorch sensitivity-analysis uncertainty-quantification

Keywords from Contributors

article digital-humanities hut23-96 spatial-data

Scientific Fields

Mathematics Computer Science - 37% confidence
Last synced: 4 months ago · JSON representation

Repository

Emulate simulations easily

Basic Info
  • Host: GitHub
  • Owner: alan-turing-institute
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage: https://www.autoemulate.com
  • Size: 278 MB
Statistics
  • Stars: 88
  • Watchers: 6
  • Forks: 14
  • Open Issues: 99
  • Releases: 10
Topics
active-learning calibration emulation ensemble gaussian-processes history-matching hut23 hut23-1468 mcmc neural-networks pytorch sensitivity-analysis uncertainty-quantification
Created over 2 years ago · Last pushed 5 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

AutoEmulate

CI codecov Code style: black All Contributors Documentation

Simulations of physical systems are often slow and need lots of compute, which makes them unpractical for real-world applications like digital twins, or when they have to run thousands of times for sensitivity analyses. The goal of AutoEmulate is to make it easy to replace simulations with fast, accurate emulators. To do this, AutoEmulate automatically fits and compares various emulators, ranging from simple models like Radial Basis Functions and Second Order Polynomials to more complex models like Support Vector Machines and Gaussian Processes to find the best emulator for a simulation.

[!WARNING] Although AutoEmulate is currently on version 1.x, we are not following semantic versioning at the moment. The convention for V1 is that breaking and major changes will be made between minor version (1.1 -> 1.2). Bug fixes will be made in patch versions (1.1.1 -> 1.1.2). We plan to implement true semantic versioning in v2 of the package. We recommend pinning the minor version of AutoEmulate if using downstream and carefully reading release notes.

Documentation

You can find the project documentation here, including installation.

The AutoEmulate project

Please cite this paper if you use the package in your work:

bibtex @article{Stoffel2025, doi = {10.21105/joss.07626}, url = {https://doi.org/10.21105/joss.07626}, year = {2025}, publisher = {The Open Journal}, volume = {10}, number = {107}, pages = {7626}, author = {Martin A. Stoffel and Bryan M. Li and Kalle Westerling and Sophie Arana and Max Balmus and Eric Daub and Steve Niederer}, title = {AutoEmulate: A Python package for semi-automated emulation}, journal = {Journal of Open Source Software} }

Contributors

Kalle Westerling
Kalle Westerling

📖 💻 🖋
Bryan M. Li
Bryan M. Li

💻
martin
martin

💻 🤔 📖 🚧 🔬 👀
Eric Daub
Eric Daub

🤔 📆 👀 💻
steven niederer
steven niederer

🤔 🖋 📆
Maximilian Balmus
Maximilian Balmus

💻 🐛
Sophie Arana
Sophie Arana

🖋 📖 📆
Andrew Duncan
Andrew Duncan

🤔 📆
Marjan Famili
Marjan Famili

💻 🤔 📖 👀
Radka Jersakova
Radka Jersakova

💻 📆 🚧 🤔 👀
Christopher Iliffe Sprague
Christopher Iliffe Sprague

💻 🎨 🤔 👀 📖
Will Usher
Will Usher

💻
Sam Greenbury
Sam Greenbury

💻 🤔 👀 📆
Ed Chalstrey
Ed Chalstrey

💻 🎨 👀 📖
Edwin
Edwin

💻 🤔 👀 📖
Paolo Conti
Paolo Conti

💻 🤔 👀 📖
Camila Rangel Smith
Camila Rangel Smith

💻 🖋
Nayara Fonseca
Nayara Fonseca

📖
Jason McEwen
Jason McEwen

🤔 📆
Amir Ali
Amir Ali

🤔
Harry Saxton
Harry Saxton

🤔
Josh Williams
Josh Williams

🐛 🤔
Levan Bokeria
Levan Bokeria

🐛
Ritkaar Singh
Ritkaar Singh

📖

Owner

  • Name: The Alan Turing Institute
  • Login: alan-turing-institute
  • Kind: organization
  • Email: info@turing.ac.uk

The UK's national institute for data science and artificial intelligence.

JOSS Publication

AutoEmulate: A Python package for semi-automated emulation
Published
March 24, 2025
Volume 10, Issue 107, Page 7626
Authors
Martin A. Stoffel ORCID
The Alan Turing Institute, London, United Kingdom
Bryan M. Li ORCID
The Alan Turing Institute, London, United Kingdom, University of Edinburgh, Edinburgh, United Kingdom
Kalle Westerling ORCID
The Alan Turing Institute, London, United Kingdom
Sophie Arana ORCID
The Alan Turing Institute, London, United Kingdom
Max Balmus ORCID
The Alan Turing Institute, London, United Kingdom, Imperial College London, London, United Kingdom
Eric Daub ORCID
The Alan Turing Institute, London, United Kingdom
Steve Niederer ORCID
The Alan Turing Institute, London, United Kingdom, Imperial College London, London, United Kingdom
Editor
Chris Vernon ORCID
Tags
Surrogate modelling Emulation Simulation Machine Learning Gaussian Processes Neural Processes

GitHub Events

Total
  • Create event: 178
  • Release event: 10
  • Issues event: 344
  • Watch event: 51
  • Delete event: 161
  • Member event: 8
  • Issue comment event: 753
  • Push event: 1,399
  • Pull request review comment event: 464
  • Pull request review event: 496
  • Pull request event: 302
  • Fork event: 9
Last Year
  • Create event: 180
  • Release event: 11
  • Issues event: 345
  • Watch event: 51
  • Delete event: 163
  • Member event: 8
  • Issue comment event: 761
  • Push event: 1,408
  • Pull request review comment event: 469
  • Pull request review event: 504
  • Pull request event: 305
  • Fork event: 9

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 2,300
  • Total Committers: 16
  • Avg Commits per committer: 143.75
  • Development Distribution Score (DDS): 0.78
Past Year
  • Commits: 1,917
  • Committers: 13
  • Avg Commits per committer: 147.462
  • Development Distribution Score (DDS): 0.736
Top Committers
Name Email Commits
Ed Chalstrey e****y@g****m 507
mastoffel m****l@g****m 502
Sam Greenbury s****y@t****k 464
radka-j r****a@g****m 463
marjanfamili m****i@g****m 128
allcontributors[bot] 4****] 51
Kalle Westerling k****g@g****m 38
cisprague c****e@g****m 34
Paolo Conti p****i@t****k 32
edwin w****n@s****k 29
Bryan M. Li b****y@g****m 19
Maximilian Balmus b****n@g****m 14
Kalle Westerling k****g@b****k 8
Sophie Arana a****e@g****m 5
Will Usher w****r@k****e 5
Nayara Fonseca 8****s 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 384
  • Total pull requests: 509
  • Average time to close issues: 2 months
  • Average time to close pull requests: 5 days
  • Total issue authors: 18
  • Total pull request authors: 15
  • Average comments per issue: 0.83
  • Average comments per pull request: 2.35
  • Merged pull requests: 390
  • Bot issues: 0
  • Bot pull requests: 41
Past Year
  • Issues: 268
  • Pull requests: 355
  • Average time to close issues: 22 days
  • Average time to close pull requests: 5 days
  • Issue authors: 16
  • Pull request authors: 13
  • Average comments per issue: 0.75
  • Average comments per pull request: 2.41
  • Merged pull requests: 256
  • Bot issues: 0
  • Bot pull requests: 27
Top Authors
Issue Authors
  • mastoffel (98)
  • sgreenbury (84)
  • radka-j (78)
  • kallewesterling (24)
  • edwardchalstrey1 (19)
  • marjanfamili (18)
  • EdwinB12 (16)
  • cisprague (11)
  • ContiPaolo (9)
  • aranas (7)
  • willu47 (6)
  • bryanlimy (3)
  • alighato (3)
  • MaxBalmus (2)
  • crangelsmith (2)
Pull Request Authors
  • mastoffel (156)
  • sgreenbury (83)
  • radka-j (78)
  • allcontributors[bot] (41)
  • edwardchalstrey1 (40)
  • marjanfamili (27)
  • kallewesterling (24)
  • EdwinB12 (24)
  • bryanlimy (11)
  • cisprague (9)
  • ContiPaolo (5)
  • MaxBalmus (4)
  • aranas (4)
  • willu47 (2)
  • nayara-focs (1)
Top Labels
Issue Labels
refactor (82) enhancement (59) ai-uk (39) bug (30) documentation (30) epic (10) research (7) good first issue (7) improve-code-quality (6) question (5) mvp (5) simulator (4) management (3) temporal (3) tutorial (2) strategy (1) FI (1)
Pull Request Labels
refactor (5) simulator (2)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 154 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 10
  • Total maintainers: 1
pypi.org: autoemulate

A python package for semi-automated emulation

  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 154 Last month
Rankings
Dependent packages count: 9.6%
Stargazers count: 18.5%
Forks count: 25.5%
Average: 29.3%
Dependent repos count: 63.4%
Maintainers (1)
Last synced: 4 months ago

Dependencies

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  • mogp-emulator 0.7.2
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pyproject.toml pypi
  • furo ^2023.9.10
  • matplotlib ^3.7.2
  • mogp-emulator ^0.7.2
  • myst-parser ^2.0.0
  • pytest ^7.4.0
  • python ^3.10
  • scikit-learn ^1.3.0
  • sphinx ^7.2.6
  • sphinx-autodoc-typehints ^1.24.0
  • sphinx-copybutton ^0.5.2
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