Python based automated model reduction tools for SBML models
Project description
Automated Model Reduction Tool for SBML models
Python toolbox to automatically obtain reduced model expressions using time-scale separation, conservation laws, and other assumptions.
Refer to the bioRxiv paper for more details. To run - Go through tutorial files inside tutorials folder then check out some common examples in the examples folder. To check if different tools are working properly, run tests. Contact : Ayush Pandey (apandet at caltech dot edu) for any feedback or suggestions.
- Website: https://github.com/ayush9pandey/AutoReduce
- Paper: Journal of Robust and Nonlinear Control
- Source: https://github.com/ayush9pandey/autoreduce
- Bug reports: https://github.com/ayush9pandey/autoreduce/issues
- Documentation: Coming Soon on: autoreduce.readthedocs.io
Installation
Install the latest version of AutoReduce::
$ pip install autoreduce
Install with all optional dependencies::
$ pip install autoreduce[all]
Bugs
Report any bugs that you find here.
You can also fork the repository on GitHub,
and the create a pull request (PR) with any changes. We welcome all changes, big or small, and we
will help you make the PR if you are new to git
(just create a new issue)
Versions
AutoReduce versions:
- 0.2.0 (alpha release): To install run
pip install autoreduce=0.2.0
- 0.1.0 (alpha release): To install run
pip install autoreduce==0.1.0
License
Released under the BSD 3-Clause License (see LICENSE
)
Copyright (c) 2022, Ayush Pandey. All rights reserved.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
File details
Details for the file AutoReduce-0.2.0.tar.gz
.
File metadata
- Download URL: AutoReduce-0.2.0.tar.gz
- Upload date:
- Size: 27.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c7a83a7c63bf05bfb3fe12724c9b2e5273ab3d5ad28e62738bec5f91317687e1 |
|
MD5 | 073d48d633843479fd7c2ec1bcc25c63 |
|
BLAKE2b-256 | 78d2b7aa8e259512118d571cd4cde2fefe269091b7c394f26a4b2b8ab435b985 |
File details
Details for the file AutoReduce-0.2.0-py3.9.egg
.
File metadata
- Download URL: AutoReduce-0.2.0-py3.9.egg
- Upload date:
- Size: 55.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4db153a3f65c7b8e424b0345670f02fa70a8e3ee30978cda6dae07e26256038a |
|
MD5 | bdb9e0b714ca75790eac8bff4ad98b9d |
|
BLAKE2b-256 | dddcb4667de9350785344159933e656fed9cc9843e55403d47d4d9e9788f3507 |
File details
Details for the file AutoReduce-0.2.0-py2.py3-none-any.whl
.
File metadata
- Download URL: AutoReduce-0.2.0-py2.py3-none-any.whl
- Upload date:
- Size: 26.9 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1fe0fdab77d2ea8a10113c61117800afe12216315b04178176905d4e60ae7e55 |
|
MD5 | 80c1574f0edfb9eaceb8d1038fb5971c |
|
BLAKE2b-256 | 5390457a5af469d55f043149565f036e012b42b8fbd165fdf0224d5923893605 |