heyoka.py 1.0.0

[bluescarni]

Version 1.0.0 of heyoka.py is here, and it brings several new features and important changes.

Semantic versioning

Starting from this release, heyoka.py adopts the semantic versioning numbering scheme. In particular:

• the MAJOR version will be increased in case of backwards-incompatible changes in the public API,
• the MINOR version will be increased in case of backwards-compatible additions to the public API,
• the PATCH version will be increased in case of backwards-compatible bugfixes.

Note that, due to the lack of API docs at the present time, heyoka.py's public API is somewhat fuzzily defined by the C++ and Python tutorials.

Overhaul of the expression system

The biggest user-facing change in this release is a comprehensive internal overhaul of the expression system, including:

• the removal of several ad-hoc primitives with somewhat redundant functionality (e.g., square(), sqrt(), sum_sq(), etc.);
• the implementation of several automated simplifications/normalisations, mostly inspired by the behaviour of SymPy;
• the re-implementation of sums and products as multivariate functions.

Users are encouraged to read this tutorial in order to understand how to best take advantage of the revamped expression system.

New API to compute high-order derivatives

A new function called diff_tensors() is available to compute efficiently high-order derivative tensors. Please see this tutorial for an introduction to this new feature.

Improvements to step callbacks

Step callbacks can now optionally implement a pre_hook() method that will be invoked once before the first step in a time-limited propagation is performed. This feature can be useful to implement an init/setup phase in the callback before the numerical integration starts. The tutorial has been updated to include this new feature.

Additionally, in multi-threaded ensemble propagations the step callback is now copied for each iteration of the ensemble, rather than being shared among all the iterations. This behaviour should reduce the risk of data races.

New model submodule

A new model submodule has been introduced, which includes functions to generate the dynamics for several commonly-used dynamical models (e.g., pendulum, N-body, etc.). The make_nbody_sys() helper has been replaced by an equivalent function in the model submodule. More models are planned to be added in the near future.

Miscellanea

• Substitution of generic subexpressions has been implemented;
• the screen output of expressions is now truncated for very large expressions;
• several other quality-of-life improvements.

As usual, the full changelog is available here:

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

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This discussion was created from the release heyoka.py 1.0.0.