ODE-toolbox: Automatic selection and generation of integration schemes for systems of ordinary differential equations
Project description
Choosing the optimal solver for systems of ordinary differential equations (ODEs) is a critical step in dynamical systems simulation. ODE-toolbox is a Python package that assists in solver benchmarking, and recommends solvers on the basis of a set of user-configurable heuristics. For all dynamical equations that admit an analytic solution, ODE-toolbox generates propagator matrices that allow the solution to be calculated at machine precision. For all others, first-order update expressions are returned based on the Jacobian matrix.
In addition to continuous dynamics, discrete events can be used to model instantaneous changes in system state, such as a neuronal action potential. These can be generated by the system under test as well as applied as external stimuli, making ODE-toolbox particularly well-suited for applications in computational neuroscience.
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 Distributions
Built Distribution
Hashes for odetoolbox-2.5.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a75aad8bc1eadfa5a7cddfb4b8a0f453eeeff30e3e3d74893b6c5182bfb9cde9 |
|
MD5 | 3fb3503ccc3da4d3a1117a4d937cc465 |
|
BLAKE2b-256 | f33d545c5e11290e7a5a167f6311f66e80441040c01276c2268e9f8c6240b9a7 |