2. Release Notes

This section reports notable changes and additions in SdePy releases.

Not all releases are covered. For further information, and a complete list of releases, please refer to the SdePy repository on GitHub.

2.1. SdePy 1.2.0

New in this release

SdePy was upgraded to the current NumPy pseudo-random numbers generation framework, based on the PCG-64 algorithm. The following additions were made:

  • SDEs and stochasticity source classes now accept upon instantiation a new optional parameter rng, to locally set the random number generator used by each instance. Such rng is expected to expose the interface used by numpy.random.Generator and numpy.random.RandomState instances.
  • In case no rng parameter is given, random number generation is delegated to a global numpy.random.default_rng() object, created upon import: absent any user intervention, unmodified pre-existing code will rely on PCG-64 random number generation after upgrading to current NumPy and SdePy releases.
  • To access the stably reproducible NumPy legacy random generation, it is recommended to instantiate sources and SDEs with the rng=numpy.random.RandomState(SEED) parameter. As a result, each object is served the random numbers stream formerly obtained from the global NumPy random state after a numpy.random.seed(SEED) call.
  • Compatibility with legacy NumPy versions was maintained, if now deprecated: in such case, SdePy silently falls back on the legacy global NumPy random state.

The present SdePy version safeguards functional compatibility with code written for previous versions, note however that, if such code is run with current NumPy and SdePy versions, it will break pseudo-random numbers reproducibility:

  • numpy.random.seed calls no longer affect SdePy objects.

  • To reproduce the default output of former SdePy versions, numpy.random.seed(SEED) statements may be replaced with the following assignment:

    sdepy.infrastructure.default_rng = numpy.random.RandomState(SEED)

    Any other use of such global variable should rather be avoided, in favor of the rng keyword.

Improvements

  • The testing suite was updated, and its interface sdepy.test() extended, for use beyond NumPy legacy random generation.
  • GitHub Actions were updated accordingly, to perform CI tests using both legacy and current NumPy random generation.

Changes

Python 3.5 is no longer supported.

2.2. SdePy 1.1.0

New in this release

  • The sdepy.process class acquired new methods vmin, vmax, vmean, vvar, vstd to perform summary operations across values, for each time point and path.
  • A piecewise constant process constructor was added as the piecewise function; it replaces, and improves upon, the private _piecewise_constant_process (undocumented, not part of the API), now deprecated.

Bug-fixes

  • An incompatibility issue of the sdepy.process class with NumPy versions >= 1.16.0 was solved.
  • A bug in the out parameter of process methods pmin, pmax, tmin, tmax was fixed. No backward incompatible changes were made against the stated API, note however that code relying on the out parameter of the mentioned process methods might need fixing as well.