Merge branch 'master' into singularity-logging

Author: Shreyas-Ekanathan

.github/workflows/Downstream.yml

@@ -35,13 +35,13 @@ jobs:
           - {user: SKopecz, repo: PositiveIntegrators.jl, group: Downstream}
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v7
       - uses: julia-actions/setup-julia@v3
         with:
           version: ${{ matrix.julia-version }}
           arch: x64
       - name: Clone Downstream
-        uses: actions/checkout@v6
+        uses: actions/checkout@v7
         with:
           repository: ${{ matrix.package.user }}/${{ matrix.package.repo }}
           path: downstream

.typos.toml

@@ -22,6 +22,9 @@ vectorized = "vectorized"
 extrapolant = "extrapolant"
 # Person names in citations - these are correct spellings
 Sigal = "Sigal"  # Sigal Gottlieb is a real person/author
+lamba = "lamba"  # Lamba's adaptive Euler-Maruyama method (LambaEM, LambaEulerHeun)
+Lamba = "Lamba"
+Strang = "Strang"  # Strang splitting (Gilbert Strang)
 Steinebach = "Steinebach"
 Protopapa = "Protopapa"
 Hairer = "Hairer"
@@ -127,6 +130,7 @@ iif = "iif"
 currate = "currate"  # current rate variable in tau-leaping
 SIE = "SIE"  # SIEA/SIEB algorithm name prefix
 SME = "SME"  # SME algorithm name (Stochastic Modified Euler)
+MIS = "MIS"  # Multirate Infinitesimal Step methods (MIS2, MIS3a, ...)
 resetted = "resetted"  # variable name in stepsize control
 strat = "strat"  # Stratonovich abbreviation
 

NEWS.md

@@ -51,7 +51,7 @@ Most of the breaking changes fall into a small set of recurring themes. Keep the
   # v7 — a typed object
   Rosenbrock23(autodiff = AutoForwardDiff())
   solve(prob, alg;
-      verbose = ODEVerbosity(SciMLLogging.None()),
+      verbose = DEVerbosity(SciMLLogging.None()),
       alias = ODEAliasSpecifier(alias_u0 = true))
   ```
 
@@ -64,7 +64,7 @@ Most of the breaking changes fall into a small set of recurring themes. Keep the
 
 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.
+1. **Stay on SciMLBase v2 / OrdinaryDiffEq v6.** Update your code to the new names (`has_stats`, `sol.stats`, `AbstractDEAlgorithm`, `derivative_discontinuity!`, `ODEAliasSpecifier`, `DEVerbosity`, `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`).
 
@@ -310,11 +310,11 @@ Rosenbrock23(autodiff=AutoFiniteDiff())
 # v6
 solve(prob, alg, verbose=false)
 
-# v7 — must use ODEVerbosity
-solve(prob, alg, verbose=ODEVerbosity(SciMLLogging.None()))
+# v7 — must use DEVerbosity
+solve(prob, alg, verbose=DEVerbosity(SciMLLogging.None()))
 ```
 
-**Why:** same type-stability reason, plus `ODEVerbosity` exposes fine-grained control (separate levels for nonlinear solver, linear solver, initialization, etc.) that a single `Bool` can't express.
+**Why:** same type-stability reason, plus `DEVerbosity` exposes fine-grained control (separate levels for nonlinear solver, linear solver, initialization, etc.) that a single `Bool` can't express.
 
 ### alias: Bool no longer accepted
 

Project.toml

@@ -1,7 +1,7 @@
 name = "OrdinaryDiffEq"
 uuid = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 authors = ["Chris Rackauckas <accounts@chrisrackauckas.com>", "Yingbo Ma <mayingbo5@gmail.com>"]
-version = "7.0.0"
+version = "7.1.1"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -52,7 +52,7 @@ OrdinaryDiffEqStabilizedRK = {path = "lib/OrdinaryDiffEqStabilizedRK"}
 OrdinaryDiffEqSymplecticRK = {path = "lib/OrdinaryDiffEqSymplecticRK"}
 
 [compat]
-ADTypes = "1.16.0"
+ADTypes = "1.22.0"
 CommonSolve = "0.2.6"
 DocStringExtensions = "0.9.5"
 ForwardDiff = "1.3.3"
@@ -62,8 +62,10 @@ OrdinaryDiffEqDefault = "2"
 OrdinaryDiffEqRosenbrock = "2"
 OrdinaryDiffEqTsit5 = "2"
 OrdinaryDiffEqVerner = "2"
-SciMLBase = "3"
+RecursiveArrayTools = "4.2.0"
+SciMLBase = "3.30.0"
 SciMLLogging = "2.0.0"
+SciMLTesting = "1.7"
 julia = "1.10"
 
 [extras]
@@ -84,7 +86,6 @@ JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
-NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 ODEProblemLibrary = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
 OrdinaryDiffEqAdamsBashforthMoulton = "89bda076-bce5-4f1c-845f-551c83cdda9a"
@@ -117,6 +118,7 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 RecursiveFactorization = "f2c3362d-daeb-58d1-803e-2bc74f2840b4"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SparseConnectivityTracer = "9f842d2f-2579-4b1d-911e-f412cf18a3f5"
@@ -129,4 +131,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["ADTypes", "ArrayInterface", "ComponentArrays", "AlgebraicMultigrid", "DiffEqBase", "DiffEqCallbacks", "DifferentiationInterface", "DiffEqDevTools", "ExplicitImports",  "ForwardDiff", "IncompleteLU", "InteractiveUtils", "LinearAlgebra", "LinearSolve", "ODEProblemLibrary", "OrdinaryDiffEqAdamsBashforthMoulton", "OrdinaryDiffEqDifferentiation", "OrdinaryDiffEqExplicitRK", "OrdinaryDiffEqExplicitTableaus", "OrdinaryDiffEqExponentialRK", "OrdinaryDiffEqExtrapolation", "OrdinaryDiffEqFIRK", "OrdinaryDiffEqFeagin", "OrdinaryDiffEqFunctionMap", "OrdinaryDiffEqHighOrderRK", "OrdinaryDiffEqIMEXMultistep", "OrdinaryDiffEqLinear", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqLowStorageRK", "NLsolve", "NonlinearSolve", "OrdinaryDiffEqNonlinearSolve", "OrdinaryDiffEqNordsieck", "OrdinaryDiffEqPDIRK", "OrdinaryDiffEqPRK", "OrdinaryDiffEqQPRK", "OrdinaryDiffEqRKN", "OrdinaryDiffEqSDIRK", "OrdinaryDiffEqSSPRK", "OrdinaryDiffEqStabilizedIRK", "OrdinaryDiffEqStabilizedRK", "OrdinaryDiffEqSymplecticRK", "ElasticArrays", "JLArrays", "Random", "SafeTestsets", "StableRNGs", "StructArrays", "Test", "Unitful", "Pkg", "RecursiveArrayTools", "RecursiveFactorization", "SparseArrays", "SparseConnectivityTracer", "SparseMatrixColorings", "StaticArrays", "Statistics"]
+test = ["ADTypes", "ArrayInterface", "ComponentArrays", "AlgebraicMultigrid", "DiffEqBase", "DiffEqCallbacks", "DifferentiationInterface", "DiffEqDevTools", "ExplicitImports",  "ForwardDiff", "IncompleteLU", "InteractiveUtils", "LinearAlgebra", "LinearSolve", "ODEProblemLibrary", "OrdinaryDiffEqAdamsBashforthMoulton", "OrdinaryDiffEqDifferentiation", "OrdinaryDiffEqExplicitRK", "OrdinaryDiffEqExplicitTableaus", "OrdinaryDiffEqExponentialRK", "OrdinaryDiffEqExtrapolation", "OrdinaryDiffEqFIRK", "OrdinaryDiffEqFeagin", "OrdinaryDiffEqFunctionMap", "OrdinaryDiffEqHighOrderRK", "OrdinaryDiffEqIMEXMultistep", "OrdinaryDiffEqLinear", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqLowStorageRK", "NonlinearSolve", "OrdinaryDiffEqNonlinearSolve", "OrdinaryDiffEqNordsieck", "OrdinaryDiffEqPDIRK", "OrdinaryDiffEqPRK", "OrdinaryDiffEqQPRK", "OrdinaryDiffEqRKN", "OrdinaryDiffEqSDIRK", "OrdinaryDiffEqSSPRK", "OrdinaryDiffEqStabilizedIRK", "OrdinaryDiffEqStabilizedRK", "OrdinaryDiffEqSymplecticRK", "ElasticArrays", "JLArrays", "Random", "SafeTestsets", "SciMLTesting", "StableRNGs", "StructArrays", "Test", "Unitful", "Pkg", "RecursiveArrayTools", "RecursiveFactorization", "SparseArrays", "SparseConnectivityTracer", "SparseMatrixColorings", "StaticArrays", "Statistics"]

docs/src/devtools/alg_dev/benchmarks.md

@@ -54,7 +54,7 @@ on each of these values.
 
 ### WorkPrecision
 
-A WorkPrecision calculates the necessary componnets of a work-precision plot. This
+A WorkPrecision calculates the necessary components of a work-precision plot. This
 shows how time scales with the user chosen tolerances on a given problem. To make
 a WorkPrecision, you give it a vector of absolute and relative tolerances:
 

docs/src/implicit/FIRK.md

@@ -35,7 +35,7 @@ These methods are recommended for:
 
 RadauIIA methods are based on Gaussian collocation and achieve order 2s-1 for s stages, making them among the highest-order implicit methods available. They represent the ODE analog of Gaussian quadrature with a fixed right node (Gauss-Radau). They are L-stable, meaning they are stiffly accurate and handle large negative eigenvalues/stiffness ratios. For more details on recent advances in FIRK methods, see our paper: [High-Order Adaptive Time Stepping for the Incompressible Navier-Stokes Equations](https://arxiv.org/abs/2412.14362).
 
-Gauss–Legendre methods use the roots of the Legendre polynomial directly as collocation points and achieve an order of 2s, the highest order IRK available. They are also A-stable, symmetric, and can be symplectic in certain usages. They conserve energy within the system but are not L-Stable like Radau, which means they preserve oscilations instead of damping. 
+Gauss–Legendre methods use the roots of the Legendre polynomial directly as collocation points and achieve an order of 2s, the highest order IRK available. They are also A-stable, symmetric, and can be symplectic in certain usages. They conserve energy within the system but are not L-Stable like Radau, which means they preserve oscillations instead of damping. 
 
 ## Computational Considerations
 

docs/src/semiimplicit/StabilizedRK.md

@@ -53,6 +53,7 @@ If not provided, the methods include automatic estimation procedures.
 
   - **`RKC`**: Second-order one-step stabilized method for low accuracy requirements
   - **`TSRKC3`**: Third-order two-step stabilized method for moderate accuracy requirements
+  - **`ROCK4`**: Fourth-order stabilized method for higher accuracy requirements
   - **`RKL2`**: Second-order, monotone stable, super-time-stepping method for parabolic PDEs
 
 ## Performance Guidelines
@@ -97,6 +98,7 @@ ROCK2
 ROCK4 
 RKC
 RKMC2
+TSRKC2
 TSRKC3
 SERK2
 ESERK4

lib/DelayDiffEq/Project.toml

@@ -1,7 +1,7 @@
 name = "DelayDiffEq"
 uuid = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 authors = ["Chris Rackauckas <accounts@chrisrackauckas.com>"]
-version = "6.0.3"
+version = "6.0.6"
 
 [deps]
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
@@ -57,21 +57,20 @@ DiffEqBase = {path = "../DiffEqBase"}
 DiffEqDevTools = {path = "../DiffEqDevTools"}
 
 [compat]
-ADTypes = "1.16"
+ADTypes = "1.22.0"
 Aqua = "0.8.11"
 ArrayInterface = "7.19.0"
 DDEProblemLibrary = "0.1"
 BinaryHeaps = "1"
 DiffEqBase = "7"
 DiffEqCallbacks = "4.17.0"
 DiffEqDevTools = "3"
-DiffEqNoiseProcess = "5"
-ExplicitImports = "1.13.1"
+DiffEqNoiseProcess = "5.30.0"
 FastBroadcast = "1.3"
 FiniteDiff = "2.27"
 ForwardDiff = "1.3.3"
 LinearAlgebra = "1"
-LinearSolve = "3.75.0"
+LinearSolve = "3.75.0, 4"
 Logging = "1"
 OrdinaryDiffEqBDF = "2"
 OrdinaryDiffEqCore = "4"
@@ -89,10 +88,11 @@ OrdinaryDiffEqSSPRK = "2"
 OrdinaryDiffEqTsit5 = "2"
 OrdinaryDiffEqVerner = "2"
 Random = "<0.0.1, 1"
-RecursiveArrayTools = "4"
+RecursiveArrayTools = "4.2.0"
 Reexport = "1.2.2"
 SafeTestsets = "0.1.0"
-SciMLBase = "3.1.0"
+SciMLBase = "3.30.0"
+SciMLTesting = "1.7"
 SparseArrays = "<0.0.1, 1, 2"
 StochasticDiffEqCore = "2"
 StochasticDiffEqHighOrder = "2"
@@ -119,7 +119,6 @@ Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 DDEProblemLibrary = "f42792ee-6ffc-4e2a-ae83-8ee2f22de800"
 DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
 DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
-ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
 FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 OrdinaryDiffEqBDF = "6ad6398a-0878-4a85-9266-38940aa047c8"
@@ -134,8 +133,9 @@ OrdinaryDiffEqVerner = "79d7bb75-1356-48c1-b8c0-6832512096c2"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+SciMLTesting = "09d9d899-5365-40a9-917a-5f67fddea283"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [targets]
-test = ["ADTypes", "Aqua", "DDEProblemLibrary", "DiffEqCallbacks", "DiffEqDevTools", "ExplicitImports", "FiniteDiff", "LinearSolve", "OrdinaryDiffEqBDF", "OrdinaryDiffEqFeagin", "OrdinaryDiffEqHighOrderRK", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqLowStorageRK", "OrdinaryDiffEqSDIRK", "OrdinaryDiffEqSSPRK", "OrdinaryDiffEqTsit5", "OrdinaryDiffEqVerner", "Random", "RecursiveArrayTools", "SafeTestsets", "SparseArrays", "StochasticDiffEqCore", "StochasticDiffEqHighOrder", "StochasticDiffEqImplicit", "StochasticDiffEqLowOrder", "StochasticDiffEqROCK", "Test", "Unitful"]
+test = ["ADTypes", "Aqua", "DDEProblemLibrary", "DiffEqCallbacks", "DiffEqDevTools", "FiniteDiff", "LinearSolve", "OrdinaryDiffEqBDF", "OrdinaryDiffEqFeagin", "OrdinaryDiffEqHighOrderRK", "OrdinaryDiffEqLowOrderRK", "OrdinaryDiffEqLowStorageRK", "OrdinaryDiffEqSDIRK", "OrdinaryDiffEqSSPRK", "OrdinaryDiffEqTsit5", "OrdinaryDiffEqVerner", "Random", "RecursiveArrayTools", "SafeTestsets", "SciMLTesting", "SparseArrays", "StochasticDiffEqCore", "StochasticDiffEqHighOrder", "StochasticDiffEqImplicit", "StochasticDiffEqLowOrder", "StochasticDiffEqROCK", "Test", "Unitful"]

lib/DelayDiffEq/src/DelayDiffEq.jl

@@ -30,14 +30,15 @@ import FastBroadcast: @..
 
 using OrdinaryDiffEqNonlinearSolve: NLAnderson, NLFunctional
 using OrdinaryDiffEqCore: AbstractNLSolverCache, SlowConvergence,
-    alg_extrapolates, alg_maximum_order, initialize!
+    alg_extrapolates, alg_maximum_order
 using OrdinaryDiffEqCore: StochasticDiffEqAlgorithm,
     StochasticDiffEqRODEAlgorithm
 using OrdinaryDiffEqRosenbrock: RosenbrockMutableCache
 using OrdinaryDiffEqFunctionMap: FunctionMap
 # using OrdinaryDiffEqDifferentiation: resize_grad_config!, resize_jac_config!
 
-using DiffEqBase: is_diagonal_noise, DEVerbosity
+using SciMLBase: is_diagonal_noise
+using DiffEqBase: DEVerbosity
 
 # Explicit imports for functions
 using OrdinaryDiffEqCore: AutoSwitch, CompositeAlgorithm

lib/DelayDiffEq/src/integrators/interface.jl

@@ -206,7 +206,16 @@ function DiffEqBase.initialize!(integrator::DDEIntegrator)
 end
 
 # signal the integrator of a derivative discontinuity
+"""
+    derivative_discontinuity!(integrator::DDEIntegrator, bool::Bool)
+
+Flag whether the current callback introduced a derivative discontinuity. Behaves
+identically to the `ODEIntegrator` method, including the order-independent,
+any-`true`-wins merge across simultaneous callbacks; see that method for details.
+"""
 function SciMLBase.derivative_discontinuity!(integrator::DDEIntegrator, bool::Bool)
+    # See ODEIntegrator counterpart: plain assignment; the order-independent merge
+    # lives in apply_callback! / apply_discrete_callback!.
     return integrator.derivative_discontinuity = bool
 end