Sourced from Catalyst's releases.

v16.1.1

Catalyst v16.1.1

Diff since v16.1.0

Merged pull requests:

• Bump julia-actions/cache from 2 to 3 (#1439) (@​dependabot[bot])
• Update SBMLImporter tutorial (#1441) (@​sebapersson)
• New Turing Doc (#1443) (@​TorkelE)
• [WIP] Add new parts to coupled equations docs (#1444) (@​TorkelE)
• build: unpin OrdinaryDiffEqCore and StochasticDiffEq (#1456) (@​AayushSabharwal)

Sourced from Catalyst's changelog.

Breaking updates and feature summaries across releases

Unreleased (on master)

Catalyst 16.1

• Added use_jump_ratelaws keyword argument to ode_model, sde_model, hybrid_model, ODEProblem, SDEProblem, and HybridProblem. When set to true, both drift and diffusion terms use the jump/stochastic rate law (binomial propensities) instead of the ODE rate law (power-based). This gives the mathematically correct CLE derived from the CME when species populations are integers. Defaults to false for backward compatibility.

Catalyst 16.0

Catalyst 16 is a major release that transitions from ModelingToolkit (MT) v9 to ModelingToolkitBase (the base for ModelingToolkit v11); introduces unified hybrid model support for mixed ODE/SDE/Jump systems; supports user-provided coupled ODEs, SDEs, jump processes, and jump-diffusions; and modernizes the conversion and problem-creation API.

Please also see the ModelingToolkit NEWS.md for all the changes that have occurred in ModelingToolkit as part of v10 and v11, and which are now relevant for Catalyst users.

BREAKING: ModelingToolkitBase replaces ModelingToolkit

• Catalyst now depends on and re-exports ModelingToolkitBase instead of ModelingToolkit. This ensures Catalyst remains fully MIT-licensed after the library split that occurred in ModelingToolkit v11. ModelingToolkitBase provides the core symbolic system infrastructure (types, accessors, problem construction) that Catalyst needs. With this update, Catalyst moves from ModelingToolkit v9 to ModelingToolkitBase 1.12+ (part of ModelingToolkit v11).

  Most commonly used functions (unknowns, parameters, equations, @mtkcompile, etc.) are available through ModelingToolkitBase. However, if you relied on structural_simplify, now part of mtkcompile, for reducing models with algebraic equations, you may need to explicitly load ModelingToolkit to obtain equivalent levels of model reduction and optimization:

  using Catalyst
  using ModelingToolkit  # only if you need MTK-specific features not in MTKBase

  The version of mtkcompile in ModelingToolkitBase is less feature filled than in ModelingToolkit, but please be aware that the latter version now loads AGPL-licensed libraries that may impose additional restrictions on your code.

BREAKING: Conversion functions renamed

... (truncated)

• 080e5cb Update project version to 16.1.1
• 2f67115 Merge pull request #1456 from SciML/as/unpin
• f534762 build: unpin OrdinaryDiffEqCore and StochasticDiffEq
• 64f3df6 Merge pull request #1441 from sebapersson/sbmlimporter
• 1315737 uncomment doc page in pages.jl
• affe366 update with codex feedback
• cc472e3 update for new syntax
• 4d1d324 Merge pull request #1443 from SciML/turing_doc_page
• da09456 Merge branch 'master' into sbmlimporter
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Sourced from DiffEqBase's changelog.

OrdinaryDiffEq.jl v7 Breaking Changes

This release bumps to SciMLBase v3, RecursiveArrayTools v4, and includes breaking changes across DiffEqBase, OrdinaryDiffEqCore, and all solver sublibraries.

Themes of the v7 release

Most of the breaking changes fall into a small set of recurring themes. Keep these in mind while reading the migration table — they explain why an individual change exists and often suggest the right migration direction:

• Time to first solve (TTFS) reduction. Direct deps on Static.jl, StaticArrayInterface.jl, Polyester.jl, and StaticArrays.jl were dropped; using OrdinaryDiffEq now loads only the default solver set; ODEFunction switched to AutoSpecialize. All of this means less code loaded and more precompilation caching on first solve.
• Type stability everywhere. All Bool solver/solve keyword arguments (autodiff, verbose, alias, lazy, …) were replaced by typed objects. Passing a Bool no longer changes dispatch in ways the compiler cannot specialize on, and the reverse is no longer allowed to silently fall back through slow generic paths.
• Generality beyond ForwardDiff. chunk_size, diff_type, standardtag, etc. encoded ForwardDiff-specific or FiniteDiff-specific knobs on every solver. They are replaced by the ADTypes interface (AutoForwardDiff, AutoFiniteDiff, AutoEnzyme, AutoZygote, …) so every solver automatically generalizes to any AD backend.
• Controller is now an object, not a pile of solve kwargs. gamma, beta1, beta2, qmin, qmax, qsteady_min, qsteady_max, qoldinit were moved onto concrete PIController / PIDController / IController / PredictiveController structs, and EEst moved to the controller cache. This is prep work for pluggable controllers and removes a large amount of dead state from the integrator struct.
• Cleanup of old re-exports / deprecations. Functions like has_destats (now has_stats), sol.destats (now sol.stats), DEAlgorithm/DEProblem/DESolution abstract types, tuples()/intervals(), QuadratureProblem, fastpow, concrete_solve, etc. were on a deprecation path for one or more minor releases. v7 removes them.

Recommended upgrade path

The cleanest path is not to jump straight from an old environment onto v7. Most renamed APIs (e.g. DEAlgorithm → AbstractDEAlgorithm, u_modified! → derivative_discontinuity!, has_destats → has_stats, sol.destats → sol.stats, the construct* tableau functions, alias_u0/alias_du0, beta1/beta2, PID kwargs) already exist under their new names in SciMLBase v2 / OrdinaryDiffEq v6 with deprecation warnings. The recommended sequence is:

1. Stay on SciMLBase v2 / OrdinaryDiffEq v6. Update your code to the new names (has_stats, sol.stats, AbstractDEAlgorithm, derivative_discontinuity!, ODEAliasSpecifier, ODEVerbosity, ADTypes-based autodiff, explicit controller = … objects, new tableau names) while the deprecation shims still exist.
2. Verify your tests pass on v6 with no deprecation warnings.
3. Then bump to v7. At this point your code should compile and run against v7 without further changes aside from the genuinely new breakage (RAT v4 array semantics, ensemble prob_func/output_func signature, struct type parameter removals, kwargs that truly no longer exist, default changes like CheckInit and williamson_condition=false).

Doing it in two steps keeps the diff small per step and lets the deprecation warnings on v6 point you at the exact call sites that will break on v7.

Fallback for RAT v4 indexing

If you cannot update sol[i] / length(sol) / eachindex(sol) call sites yet (see the RAT v4 table below), you can opt back into v3 semantics on a per-solution basis by converting the container type to the ragged variant:

using RecursiveArrayToolsRaggedArrays
sol_old = RaggedVectorOfArray(sol)   # indexes like v3: sol_old[i] is the i-th timestep

RecursiveArrayToolsRaggedArrays.jl preserves the previous AbstractVectorOfArray indexing behavior (timestep-first, not element-first). This is the escape hatch for code that assumes sol[i] returns the i-th timestep. It is, however, recommended that you update to the sol.u[i] / sol[:, i] style — the ragged wrapper is a compatibility layer, not the canonical API going forward.

---

RecursiveArrayTools v4

ODESolution is now an AbstractArray

AbstractVectorOfArray (the parent type of ODESolution, RODESolution, DAESolution, etc.) now subtypes AbstractArray. This changes the semantics of several common operations:

Operation	v3 (old)	v4 (new)	Migration
sol[i]	Returns i-th timestep (Vector)	Returns i-th scalar element (column-major)	Use sol.u[i] or sol[:, i]
length(sol)	Number of timesteps	prod(size(sol)) (total elements)	Use length(sol.t) or length(sol.u)
eachindex(sol)	1:nsteps	CartesianIndices(size(sol))	Use eachindex(sol.u)
iterate(sol)	Iterates over timesteps	Iterates over scalar elements	Use for u in sol.u
first(sol) / last(sol)	First/last timestep	First/last scalar element	Use first(sol.u) / last(sol.u)

... (truncated)

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