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.
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| Filename, size | File type | Python version | Upload date | Hashes |
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| Filename, size odetoolbox-2.2-py2-none-any.whl (41.4 kB) | File type Wheel | Python version py2 | Upload date | Hashes View |
| Filename, size odetoolbox-2.2.tar.gz (24.9 kB) | File type Source | Python version None | Upload date | Hashes View |
