heyoka.py 0.16.0

[bluescarni]

This is another big release for heyoka.py, featuring 2 major new features and substantial performance improvements.

Event detection support in batch mode ⏩

Event detection is now available in the batch mode Taylor integrator. As a result, the batch mode integrator has now feature parity with the scalar mode integrator.

The batch mode event detection API is very similar to scalar mode. A tutorial describing the new feature is available here:

https://bluescarni.github.io/heyoka.py/notebooks/Batch%20mode%20overview.html#event-detection

Continuous output 📈

Debuting in this release is support for continuous output for the propagate_for/until() methods of the scalar and batch integrators.

Continuous output allows to compute the value of the solution of the ODE system at any time within the integration time interval covered by propagate_for/until(). Tutorials are available here:

https://bluescarni.github.io/heyoka.py/notebooks/Dense%20output.html#continuous-output

https://bluescarni.github.io/heyoka.py/notebooks/Batch%20mode%20overview.html#continuous-output

This feature has been inspired by a similar feature available in the DifferentialEquations.jl package.

Performance improvements 🚀

As a result of various micro-optimisations, performance for large ODE systems in compact mode has improved by up to 15%.

Additionally, fast event exclusion checking is now implemented as a JIT-compiled function, which leads to a ~30% reduction in the event detection overhead.

Miscellanea ☑️

• Fix potential issue with data aliasing in corner cases.
• Fix wrong counting of integration steps in case of interruption by a terminal event.

The full changelog, as usual, is available here:

https://bluescarni.github.io/heyoka.py/changelog.html

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This discussion was created from the release heyoka.py 0.16.0.