Skip to main content

kinetics

Documentation Status

kinetics is a package for modelling reactions using ordinary differential equations. It's primarily aimed at modelling enzyme reactions, although can be used for other purposes.

See the Documentation for more information.

kinetics uses scipy.integrate.odeint to solve ordinary differential equations, but extends upon this to allow the use of parameter distributions rather than single parameter values. This allows error to be incorporated into the modelling.

kinetics uses scipy's probability distributions, with a large number of distributions to choose from. Typically uniform, normal, log-uniform or log-normal distributions are used.

Documentation: ReadTheDocs

Github: kinetics

Requirements: NumPy, SciPy, matplotlib, tqdm, pandas, SALib, seaborn, and deap.

Installation: pip install kinetics

Citation: Finnigan, W., Cutlan, R., Snajdrova, R., Adams, J., Littlechild, J. and Harmer, N. (2019), Engineering a seven enzyme biotransformation using mathematical modelling and characterized enzyme parts. ChemCatChem.

Graphical Abstract

Features

  • Construct systems of ODEs simply by selecting suitable rate equations and naming parameters and species
  • Use either simple parameter values or probability distributions
  • Run sensitivity analysis using SALib
  • Easily plot model runs using predefined plotting functions
  • Optimisation using genetic algorithm using DEAP (coming soon)

Metadata

Release files for kinetics 1.4.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for kinetics 1.4.5
File Size Uploaded Provenance
kinetics-1.4.5.tar.gz 26.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for kinetics 1.4.5
File Interpreter ABI Platform
kinetics-1.4.5-py3-none-any.whl Python 3 none any Details

Total release size: 57.3 kB

Release files / kinetics-1.4.5.tar.gz

Download URL kinetics-1.4.5.tar.gz
Size 26.3 kB
Tags Source
SHA-256 checksum
How to use checksums
e68be0c385cb7e0794fca6831eb5e31d27d17dae19553a0760476ff137e92451
BLAKE2b-256 checksum
How to use checksums
6f4916871ab2e10e31f948c0ecbccef9a3e79bf40043e3eae2b187d5e864e68b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.8

Release files / kinetics-1.4.5-py3-none-any.whl

Download URL kinetics-1.4.5-py3-none-any.whl
Size 31.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a2ff5b1c279d2bcae8e1f6fe7407684bbdd453d866af6912fb78d504fd4604f0
BLAKE2b-256 checksum
How to use checksums
ed692eb691109332a8e1a0f90e517b1ab9fddb9c7e39e0865e7fb42a24b58083
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.8

Security for kinetics 1.4.5

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page