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Diffrax v0.4.0
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@github-actions github-actions released this 22 May 15:33
· 149 commits to main since this release
v0.4.0
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Features

  • Highlight: added IMEX solvers! These solve the "easy" part of the diffeq using an explicit solver, and the "hard" part using an implicit solver. We now have:
    • diffrax.KenCarp3
    • diffrax.KenCarp4
    • diffrax.KenCarp5
    • diffrax.Sil3
      Each of these should be called with e.g. diffeqsolve(terms=MultiTerm(explicit_term, implicit_term), solver=diffrax.KenCarp4(), ...)
  • diffrax.ImplicitEuler now supports adaptive time stepping, by using an embedded Heun method. (#251)

Backward incompatibilities

  • scan_stages, e.g. Tsit5(scan_stages=True), no longer exists. All Runge--Kutta solvers now scan-over-stages by default.
    • If you were using scan_stages, then you should simply delete this argument.
    • If you were using the interactive API together with forward-mode autodiff then you should pass scan_kind="bounded" to the solver, e.g. Tsit5(scan_kind="bounded").

Bugfixes

  • Fixed AbstractTerm.vf_prod being ignored, so that naive prod(vf(...), control) calls were being used instead of optimised vf-prod routines, where available. (#239)
  • Implicit solvers now use the correct stage value predictors. This should help the implicit solvers converge faster, so that overall runtime is decreased. This should mean that they occasionally take a different number of steps than before -- usually fewer.

Performance

  • Overall compilation should be faster. (Due to patrick-kidger/equinox#353)
  • Initial step size selection should now compile faster. (#257)
  • Fixed dense output consuming far too much memory. (#252)
  • Backsolve adjoint should now be much more efficient (due to the vf_prod bugfix).

Full Changelog: v0.3.1...v0.4.0

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