A python package for semi-automated emulation
Project description
AutoEmulate 
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, Gaussian Processes and Conditional Neural Processes to find the best emulator for a simulation.
โ ๏ธ Warning: This is an early version of the package and is still under development. We are working on improving the documentation and adding more features. If you have any questions or suggestions, please open an issue or a pull request.
Documentation
You can find the project documentation here, including installation.
The AutoEmulate project
-
The AutoEmulate project is run out of the Alan Turing Institute.
-
Visit autoemulate.com to learn more.
-
We have also published a paper in The Journal of Open Source Software.
Please cite this paper if you use the package in your work:
@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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file autoemulate-0.3.2.tar.gz.
File metadata
- Download URL: autoemulate-0.3.2.tar.gz
- Upload date:
- Size: 15.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.3 CPython/3.10.17 Linux/6.11.0-1015-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ad33b111a188bb0d3dac9dae01e568988f11711c62142670393a1e92bcc5090f
|
|
| MD5 |
76b47f660fa5b53460eb762e04814ae9
|
|
| BLAKE2b-256 |
0494f81a127182d1b25800e89efe15a32be8324cced1e0b265a69a78493499a6
|
File details
Details for the file autoemulate-0.3.2-py3-none-any.whl.
File metadata
- Download URL: autoemulate-0.3.2-py3-none-any.whl
- Upload date:
- Size: 14.3 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.3 CPython/3.10.17 Linux/6.11.0-1015-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
cdd942a9d89feb8848e4d4046b16ed194df52886c30e8a7305c33d75586e556a
|
|
| MD5 |
206638524e3549c48e32e133fcedd1a8
|
|
| BLAKE2b-256 |
7b04e0d6859c782a3e3db70ff341485fa3b90b765c3906c0b3e6a30c03d9aa4a
|