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ChrisRackauckas-ClaudeChrisRackauckasclaude
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Fix docs build for OrdinaryDiffEq v7 / DifferentialEquations v8 (+ #868 AlgebraicMultigrid bump) (#869)
* Fix docs build for OrdinaryDiffEq v7: load solver subpackages explicitly OrdinaryDiffEq v7 dropped its blanket @reexport, so `OrdinaryDiffEq.OrdinaryDiffEqXXX` no longer resolves and `make.jl` died with `UndefVarError` at the makedocs `modules` list. Load each OrdinaryDiffEq *and* StochasticDiffEq solver subpackage by bare name and list them directly (mirroring OrdinaryDiffEq.jl's own docs build), rather than relying on the meta-packages to reexport them; add them as deps + compat. Also in this commit: - Bump AlgebraicMultigrid compat to allow v2 (PR #868). v2's SPQR coarse solver fixes the non-SPD preconditioner crash that v1's Pinv/SVD coarse solver hits. - Add LinearSolve as a docs dependency (used by advanced_ode_example.md, previously only available transitively). - Bring the OrdinaryDiffEqCore controller API symbols into Main so the unqualified @ref links in the copied controllers.md resolve. - Drop OrdinaryDiffEq's contributor-internal devtools pages from the user docs: their @eval blocks read paths relative to OrdinaryDiffEq's own build layout and cannot build when embedded in DiffEqDocs. - Guard the StochasticDiffEq API nav section, which is empty now that StochasticDiffEq ships no docs/ directory in the v7 monorepo. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Update executed doc examples for DifferentialEquations v8 + RecursiveArrayTools v4 With OrdinaryDiffEq v7 pinned, the resolver takes DifferentialEquations v8, which now only `@reexport`s SciMLBase + OrdinaryDiffEq (documented in index.md/getting_started.md). Executed @example blocks that reached for symbols no longer reexported through `DE.` therefore errored. Source each from the package it now lives in: - ensemble.md: `DE.SRIW1` -> `SDE.SRIW1` (StochasticDiffEq) - dde_example.md: `DE.RK4` -> `ODELow.RK4` (OrdinaryDiffEqLowOrderRK) - callback_functions.md, spiking_neural_systems.md: `DE.PresetTimeCallback` -> `CB.PresetTimeCallback` (DiffEqCallbacks) - callback_functions.md: `DE.resize!` -> `resize!` (Base, extended for integrators) Also: - advanced_ode_example.md: preconditioner `precs` functions returned `(Pl, nothing)`, but Krylov.jl now calls `ldiv!` on the right preconditioner; return `(Pl, I)` so the identity right-preconditioner has an `ldiv!` method. (LinearSolve `import` was already used here; LinearSolve is added as a docs dep in the previous commit.) - faq.md: `solve(...)[end]` returned a scalar under RecursiveArrayTools v4 (AbstractArray indexing), breaking the downstream ForwardDiff/FiniteDiff jacobian blocks; use `.u[end]` to get the final state vector. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Fix pre-existing spell-check failures blocking docs CI The Spell Check (typos) job has been failing on master and every PR. Fix the two real typos and allowlist the proper noun so the check passes: - classical_physics.md: ContiunousCallback -> ContinuousCallback - bvp_solve.md: prblem -> problem - .typos.toml: allowlist `Lamba` (the surname in the Lamba & Rackauckas methods LambaEM / LambaEulerHeun; typos mis-flags it as "Lambda") Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com> Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: ChrisRackauckas-Claude <accounts@chrisrackauckas.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
1 parent eb48837 commit d1f3dcc

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‎.typos.toml‎

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[default.extend-words]
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quations = "quations"
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Lamba = "Lamba"
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IIF = "IIF"
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padd = "padd"
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thr = "thr"

‎docs/Project.toml‎

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@@ -15,24 +15,53 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
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DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
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DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
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DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
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DiffEqDocs = "d91efeb5-c178-44a6-a2ee-51685df7c78e"
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DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
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ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
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ImplicitDiscreteSolve = "3263718b-31ed-49cf-8a0f-35a466e8af96"
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IncompleteLU = "40713840-3770-5561-ab4c-a76e7d0d7895"
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JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
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LSODA = "7f56f5a3-f504-529b-bc02-0b1fe5e64312"
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LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
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ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
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NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
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ODEInterfaceDiffEq = "09606e27-ecf5-54fc-bb29-004bd9f985bf"
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ODEProblemLibrary = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
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Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
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OptimizationNLopt = "4e6fcdb7-1186-4e1f-a706-475e75c168bb"
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OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
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OrdinaryDiffEqAMF = "08082164-f6a1-4363-b3df-3aa6fcf571ad"
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OrdinaryDiffEqAdamsBashforthMoulton = "89bda076-bce5-4f1c-845f-551c83cdda9a"
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OrdinaryDiffEqBDF = "6ad6398a-0878-4a85-9266-38940aa047c8"
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OrdinaryDiffEqCore = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
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OrdinaryDiffEqDefault = "50262376-6c5a-4cf5-baba-aaf4f84d72d7"
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OrdinaryDiffEqExplicitRK = "9286f039-9fbf-40e8-bf65-aa933bdc4db0"
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OrdinaryDiffEqExponentialRK = "e0540318-69ee-4070-8777-9e2de6de23de"
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OrdinaryDiffEqExtrapolation = "becaefa8-8ca2-5cf9-886d-c06f3d2bd2c4"
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OrdinaryDiffEqFIRK = "5960d6e9-dd7a-4743-88e7-cf307b64f125"
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OrdinaryDiffEqFeagin = "101fe9f7-ebb6-4678-b671-3a81e7194747"
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OrdinaryDiffEqHighOrderRK = "d28bc4f8-55e1-4f49-af69-84c1a99f0f58"
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OrdinaryDiffEqIMEXMultistep = "9f002381-b378-40b7-97a6-27a27c83f129"
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OrdinaryDiffEqLinear = "521117fe-8c41-49f8-b3b6-30780b3f0fb5"
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OrdinaryDiffEqLowOrderRK = "1344f307-1e59-4825-a18e-ace9aa3fa4c6"
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OrdinaryDiffEqLowStorageRK = "b0944070-b475-4768-8dec-fb6eb410534d"
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OrdinaryDiffEqNordsieck = "c9986a66-5c92-4813-8696-a7ec84c806c8"
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OrdinaryDiffEqPDIRK = "5dd0a6cf-3d4b-4314-aa06-06d4e299bc89"
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OrdinaryDiffEqPRK = "5b33eab2-c0f1-4480-b2c3-94bc1e80bda1"
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OrdinaryDiffEqQPRK = "04162be5-8125-4266-98ed-640baecc6514"
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OrdinaryDiffEqRKN = "af6ede74-add8-4cfd-b1df-9a4dbb109d7a"
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OrdinaryDiffEqRosenbrock = "43230ef6-c299-4910-a778-202eb28ce4ce"
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OrdinaryDiffEqSDIRK = "2d112036-d095-4a1e-ab9a-08536f3ecdbf"
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OrdinaryDiffEqSSPRK = "669c94d9-1f4b-4b64-b377-1aa079aa2388"
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OrdinaryDiffEqStabilizedIRK = "e3e12d00-db14-5390-b879-ac3dd2ef6296"
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OrdinaryDiffEqStabilizedRK = "358294b1-0aab-51c3-aafe-ad5ab194a2ad"
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OrdinaryDiffEqSymplecticRK = "fa646aed-7ef9-47eb-84c4-9443fc8cbfa8"
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OrdinaryDiffEqTsit5 = "b1df2697-797e-41e3-8120-5422d3b24e4a"
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OrdinaryDiffEqVerner = "79d7bb75-1356-48c1-b8c0-6832512096c2"
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Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
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RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
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SDEProblemLibrary = "c72e72a9-a271-4b2b-8966-303ed956772e"
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StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
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SteadyStateDiffEq = "9672c7b4-1e72-59bd-8a11-6ac3964bc41f"
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StochasticDiffEq = "789caeaf-c7a9-5a7d-9973-96adeb23e2a0"
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StochasticDiffEqCore = "19c5a474-6cd1-4a5f-be79-46dc34e54d7f"
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StochasticDiffEqHighOrder = "0520c28c-50fd-4d16-9c96-902fc80b3bab"
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StochasticDiffEqIIF = "ebf54054-c36b-4494-9aba-657e36df524f"
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StochasticDiffEqImplicit = "5080b986-4c76-4669-b5dc-373a41579d5b"
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StochasticDiffEqLeaping = "aefaaa88-39f2-4e89-b162-d61b7e8cc81b"
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StochasticDiffEqLowOrder = "d15fe365-ce7f-450a-828a-7985bd5b681b"
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StochasticDiffEqMilstein = "8c95a807-c8e7-4581-8419-890d001af53e"
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StochasticDiffEqROCK = "db241ea8-0e6b-4abc-8f2d-1adff2294fd9"
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StochasticDiffEqRODE = "49714585-0aa1-4f53-b1e6-a9b8c0d5e03f"
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StochasticDiffEqWeak = "af2a2fcd-1c36-4cbe-a6d0-5afda784a085"
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Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
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Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
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[compat]
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ADTypes = "1.7"
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AlgebraicMultigrid = "0.5, 0.6, 1"
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AlgebraicMultigrid = "0.5, 0.6, 1, 2"
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BSON = "0.3"
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BVProblemLibrary = "0.1.2"
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BenchmarkTools = "1"
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DelayDiffEq = "5.52, 6.0"
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DiffEqBase = "7"
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DiffEqCallbacks = "4"
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DiffEqDevTools = "3, 4.0"
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DifferentialEquations = "7.14, 8.0"
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Distributions = "0.25"
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Documenter = "1"
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FiniteDiff = "2"
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ForwardDiff = "0.10, 1"
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ImplicitDiscreteSolve = "2"
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IncompleteLU = "0.2"
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JLD2 = "0.4, 0.5.1, 0.6"
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LSODA = "0.7, 1.0"
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LinearSolve = "2, 3"
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ModelingToolkit = "9, 10, 11.0"
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NonlinearSolve = "3.15, 4"
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ODEInterfaceDiffEq = "3, 4.0, 5.0"
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ODEProblemLibrary = "0.1, 1"
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Optimization = "3, 4, 5"
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OptimizationNLopt = "0.2, 0.3"
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OrdinaryDiffEq = "7"
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OrdinaryDiffEqAMF = "2"
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OrdinaryDiffEqAdamsBashforthMoulton = "2"
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OrdinaryDiffEqBDF = "2"
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OrdinaryDiffEqCore = "4, 5.0"
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OrdinaryDiffEqDefault = "2"
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OrdinaryDiffEqExplicitRK = "2"
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OrdinaryDiffEqExponentialRK = "2"
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OrdinaryDiffEqExtrapolation = "2"
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OrdinaryDiffEqFIRK = "2"
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OrdinaryDiffEqFeagin = "2"
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OrdinaryDiffEqHighOrderRK = "2"
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OrdinaryDiffEqIMEXMultistep = "2"
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OrdinaryDiffEqLinear = "2"
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OrdinaryDiffEqLowOrderRK = "2"
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OrdinaryDiffEqLowStorageRK = "3"
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OrdinaryDiffEqNordsieck = "2"
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OrdinaryDiffEqPDIRK = "2"
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OrdinaryDiffEqPRK = "2"
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OrdinaryDiffEqQPRK = "2"
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OrdinaryDiffEqRKN = "2"
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OrdinaryDiffEqRosenbrock = "2"
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OrdinaryDiffEqSDIRK = "2"
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OrdinaryDiffEqSSPRK = "2"
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OrdinaryDiffEqStabilizedIRK = "2"
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OrdinaryDiffEqStabilizedRK = "2"
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OrdinaryDiffEqSymplecticRK = "2"
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OrdinaryDiffEqTsit5 = "2"
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OrdinaryDiffEqVerner = "2"
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Plots = "1"
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RecursiveArrayTools = "4"
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SDEProblemLibrary = "0.1, 1"
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StaticArrays = "1"
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SteadyStateDiffEq = "2.4"
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StochasticDiffEq = "7"
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StochasticDiffEqCore = "2"
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StochasticDiffEqHighOrder = "2"
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StochasticDiffEqIIF = "2"
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StochasticDiffEqImplicit = "2"
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StochasticDiffEqLeaping = "2"
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StochasticDiffEqLowOrder = "2"
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StochasticDiffEqMilstein = "2"
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StochasticDiffEqROCK = "2"
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StochasticDiffEqRODE = "2"
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StochasticDiffEqWeak = "2"
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Sundials = "4.11.3, 5, 6.0"
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Unitful = "1"

‎docs/make.jl‎

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using Documenter, DiffEqBase, SciMLBase, OrdinaryDiffEq, OrdinaryDiffEqBDF,
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OrdinaryDiffEqCore, StochasticDiffEq, DelayDiffEq, SteadyStateDiffEq, DiffEqCallbacks,
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BoundaryValueDiffEq
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# Load the OrdinaryDiffEq/StochasticDiffEq solver subpackages directly instead of relying
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# on the meta-packages to reexport them: OrdinaryDiffEq v7 already dropped its reexports,
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# so listing each subpackage explicitly is what keeps the API docs complete and robust.
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using OrdinaryDiffEqAdamsBashforthMoulton, OrdinaryDiffEqDefault, OrdinaryDiffEqExplicitRK,
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OrdinaryDiffEqExponentialRK, OrdinaryDiffEqExtrapolation, OrdinaryDiffEqFeagin,
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OrdinaryDiffEqFIRK, OrdinaryDiffEqHighOrderRK, OrdinaryDiffEqIMEXMultistep,
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OrdinaryDiffEqLinear, OrdinaryDiffEqLowOrderRK, OrdinaryDiffEqLowStorageRK,
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OrdinaryDiffEqNordsieck, OrdinaryDiffEqPDIRK, OrdinaryDiffEqPRK, OrdinaryDiffEqQPRK,
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OrdinaryDiffEqRKN, OrdinaryDiffEqRosenbrock, OrdinaryDiffEqSDIRK, OrdinaryDiffEqSSPRK,
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OrdinaryDiffEqStabilizedIRK, OrdinaryDiffEqStabilizedRK, OrdinaryDiffEqSymplecticRK,
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OrdinaryDiffEqTsit5, OrdinaryDiffEqVerner, OrdinaryDiffEqAMF, ImplicitDiscreteSolve,
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DiffEqDevTools
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using StochasticDiffEqCore, StochasticDiffEqHighOrder, StochasticDiffEqIIF,
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StochasticDiffEqImplicit, StochasticDiffEqLeaping, StochasticDiffEqLowOrder,
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StochasticDiffEqMilstein, StochasticDiffEqROCK, StochasticDiffEqRODE,
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StochasticDiffEqWeak
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# Bring the OrdinaryDiffEqCore controller API symbols into Main so the unqualified
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# @ref links in the copied controllers.md resolve (mirrors OrdinaryDiffEq.jl's docs).
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using OrdinaryDiffEqCore: default_controller, resolve_basic, get_EEst, set_EEst!,
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CompositeController
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import ODEProblemLibrary,
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SDEProblemLibrary, DDEProblemLibrary, DAEProblemLibrary, BVProblemLibrary
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using Sundials, DASKR, LSODA, DASSL, SimpleDiffEq, ODEInterfaceDiffEq
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# Copy all the docs from OrdinaryDiffEq.jl
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cp(ordinartdiffeq_docs_path, ordinary_diffeq_dest, force = true)
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# OrdinaryDiffEq's developer docs are contributor-internal and their @eval blocks
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# read paths relative to OrdinaryDiffEq's own build layout, so they cannot build
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# inside DiffEqDocs; drop them from the user-facing site.
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rm(joinpath(ordinary_diffeq_dest, "devtools"), recursive = true, force = true)
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ordinary_diffeq_pages_dest = joinpath(@__DIR__, "ordinarydiffeq_pages.jl")
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ordinary_diffeq_pages_file = joinpath(ordinartdiffeq_docs_root, "pages.jl")
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DAEProblemLibrary,
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BVProblemLibrary,
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OrdinaryDiffEq,
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OrdinaryDiffEq.OrdinaryDiffEqAdamsBashforthMoulton,
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OrdinaryDiffEq.OrdinaryDiffEqBDF,
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OrdinaryDiffEq.OrdinaryDiffEqDefault,
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OrdinaryDiffEq.OrdinaryDiffEqExplicitRK,
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OrdinaryDiffEq.OrdinaryDiffEqExponentialRK,
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OrdinaryDiffEq.OrdinaryDiffEqExtrapolation,
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OrdinaryDiffEq.OrdinaryDiffEqFeagin,
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OrdinaryDiffEq.OrdinaryDiffEqFIRK,
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OrdinaryDiffEq.OrdinaryDiffEqHighOrderRK,
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OrdinaryDiffEq.OrdinaryDiffEqIMEXMultistep,
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OrdinaryDiffEq.OrdinaryDiffEqLinear,
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OrdinaryDiffEq.OrdinaryDiffEqLowOrderRK,
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OrdinaryDiffEq.OrdinaryDiffEqLowStorageRK,
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OrdinaryDiffEq.OrdinaryDiffEqNordsieck,
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OrdinaryDiffEq.OrdinaryDiffEqPDIRK,
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OrdinaryDiffEq.OrdinaryDiffEqPRK,
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OrdinaryDiffEq.OrdinaryDiffEqQPRK,
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OrdinaryDiffEq.OrdinaryDiffEqRKN,
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OrdinaryDiffEq.OrdinaryDiffEqRosenbrock,
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OrdinaryDiffEq.OrdinaryDiffEqSDIRK,
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OrdinaryDiffEq.OrdinaryDiffEqSSPRK,
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OrdinaryDiffEq.OrdinaryDiffEqStabilizedIRK,
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OrdinaryDiffEq.OrdinaryDiffEqStabilizedRK,
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OrdinaryDiffEq.OrdinaryDiffEqSymplecticRK,
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OrdinaryDiffEq.OrdinaryDiffEqTsit5,
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OrdinaryDiffEq.OrdinaryDiffEqVerner,
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OrdinaryDiffEqCore,
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OrdinaryDiffEqAdamsBashforthMoulton,
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OrdinaryDiffEqBDF,
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OrdinaryDiffEqDefault,
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OrdinaryDiffEqExplicitRK,
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OrdinaryDiffEqExponentialRK,
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OrdinaryDiffEqExtrapolation,
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OrdinaryDiffEqFeagin,
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OrdinaryDiffEqFIRK,
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OrdinaryDiffEqHighOrderRK,
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OrdinaryDiffEqIMEXMultistep,
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OrdinaryDiffEqLinear,
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OrdinaryDiffEqLowOrderRK,
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OrdinaryDiffEqLowStorageRK,
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OrdinaryDiffEqNordsieck,
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OrdinaryDiffEqPDIRK,
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OrdinaryDiffEqPRK,
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OrdinaryDiffEqQPRK,
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OrdinaryDiffEqRKN,
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OrdinaryDiffEqRosenbrock,
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OrdinaryDiffEqSDIRK,
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OrdinaryDiffEqSSPRK,
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OrdinaryDiffEqStabilizedIRK,
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OrdinaryDiffEqStabilizedRK,
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OrdinaryDiffEqSymplecticRK,
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OrdinaryDiffEqTsit5,
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OrdinaryDiffEqVerner,
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OrdinaryDiffEqAMF,
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ImplicitDiscreteSolve,
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DiffEqDevTools,
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StochasticDiffEq,
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StochasticDiffEqCore,
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StochasticDiffEqHighOrder,
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StochasticDiffEqIIF,
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StochasticDiffEqImplicit,
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StochasticDiffEqLeaping,
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StochasticDiffEqLowOrder,
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StochasticDiffEqMilstein,
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StochasticDiffEqROCK,
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StochasticDiffEqRODE,
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StochasticDiffEqWeak,
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‎docs/pages.jl‎

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# The Developer Documentation section maps to OrdinaryDiffEq's contributor-internal
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# devtools pages, which are excluded from the DiffEqDocs build (see docs/make.jl).
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filter!(p -> !(p isa Pair && first(p) == "Developer Documentation"), ordinary_diffeq_pages)
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stochastic_diffeq_pages_file = joinpath(@__DIR__, "stochasticdiffeq_pages.jl")
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"migration/ordinarydiffeq_v7.md",
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# StochasticDiffEq ships no docs in the OrdinaryDiffEq v7 monorepo, so drop the API
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# section entirely rather than leaving an empty navigation entry.
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if isempty(stochastic_diffeq_pages)
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filter!(p -> !(p isa Pair && first(p) == "StochasticDiffEq.jl API"), pages)
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end

‎docs/src/basics/faq.md‎

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function f(p)
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# Lower tolerances to show the methods converge to the same value
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DE.solve(prob, DE.Tsit5(), save_everystep = false, abstol = 1e-12, reltol = 1e-12)[end]
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DE.solve(prob, DE.Tsit5(), save_everystep = false, abstol = 1e-12, reltol = 1e-12).u[end]
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```
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‎docs/src/examples/classical_physics.md‎

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Original file line numberDiff line numberDiff line change
@@ -265,7 +265,7 @@ function double_pendulum_hamiltonian(udot, u, p, t)
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2sin(2β) * ((lα^2 - 2(1 + cos(β))lα * lβ + (3 + 2cos(β))lβ^2) / (3 - cos(2β))^2)]
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end
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# Construct a ContiunousCallback
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# Construct a ContinuousCallback
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condition(u, t, integrator) = u[1]
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affect!(integrator) = nothing
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cb = ODE.ContinuousCallback(condition, affect!, nothing,

‎docs/src/examples/spiking_neural_systems.md‎

Lines changed: 9 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -20,6 +20,7 @@ The LIF model has five parameters, `gL, EL, C, Vth, I` and we define it in the `
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```@example spikingneural
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import DifferentialEquations as DE
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import DiffEqCallbacks as CB # PresetTimeCallback is no longer reexported by DifferentialEquations v8
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import ComponentArrays
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import Plots
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Plots.gr()
@@ -65,7 +66,7 @@ function reset!(integrator)
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end
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threshold = DE.ContinuousCallback(thr, reset!, nothing)
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current_step = DE.PresetTimeCallback([2, 15], integrator -> integrator.p.I += 150.0)
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current_step = CB.PresetTimeCallback([2, 15], integrator -> integrator.p.I += 150.0)
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cb = DE.CallbackSet(current_step, threshold)
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```
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@@ -100,6 +101,7 @@ We see that the model is resting at `-75` while there is no input. At `t=2` the
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```@example spikingneural
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#Izhikevichch Model
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import DifferentialEquations as DE
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import DiffEqCallbacks as CB
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import Plots
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function izh!(du, u, p, t)
@@ -123,7 +125,7 @@ function reset!(integrator)
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end
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threshold = DE.DiscreteCallback(thr, reset!)
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current_step = DE.PresetTimeCallback(50, integrator -> integrator.p[5] += 10)
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current_step = CB.PresetTimeCallback(50, integrator -> integrator.p[5] += 10)
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cb = DE.CallbackSet(current_step, threshold)
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```
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@@ -168,6 +170,7 @@ The Hodgkin-Huxley (HH) model is our first biophysically realistic model. This m
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```@example spikingneural
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import DifferentialEquations as DE
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import DiffEqCallbacks as CB
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import Plots
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# Potassium ion-channel rate functions
@@ -198,7 +201,7 @@ We have three different types of ionic conductances. Potassium, sodium and the l
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The sodium current is not very different, but it has two gating variables, `m, h` instead of one. The leak conductance gL has no gating variables because it is not voltage gated. Let's move on to the parameters. If you want all the details on the HH model, you can find a great description [here](https://neuronaldynamics.epfl.ch/online/Ch2.S2.html).
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```@example spikingneural
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current_step = DE.PresetTimeCallback(100, integrator -> integrator.p[8] += 1)
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current_step = CB.PresetTimeCallback(100, integrator -> integrator.p[8] += 1)
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# n, m & h steady-states
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n_inf(v) = alpha_n(v) / (alpha_n(v) + beta_n(v))
@@ -308,7 +311,7 @@ function epsp!(integrator)
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integrator.u[6] -= integrator.u[5] * integrator.u[6]
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end
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epsp_ts = DE.PresetTimeCallback(100:100:500, epsp!)
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epsp_ts = CB.PresetTimeCallback(100:100:500, epsp!)
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p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 1000, 50, 0.5, 0.005, 0]
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u0 = [-60, n_inf(-60), m_inf(-60), h_inf(-60), 0.0, 1.0, 0.0]
@@ -331,7 +334,7 @@ Plots.plot(sol, vars = [5, 6])
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Because of the time courses at play here, this facilitation is frequency-dependent. If we increase the period between these events, facilitation does not occur.
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```@example spikingneural
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epsp_ts = DE.PresetTimeCallback(100:1000:5100, epsp!)
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epsp_ts = CB.PresetTimeCallback(100:1000:5100, epsp!)
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p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 500, 50, 0.5, 0.005, 0]
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u0 = [-60, n_inf(-60), m_inf(-60), h_inf(-60), 0.0, 1.0, 0.0]
@@ -348,7 +351,7 @@ Plots.plot(sol, vars = [5, 6])
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We can also change these time constants such that the dynamics show short-term depression instead of facilitation.
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```@example spikingneural
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epsp_ts = DE.PresetTimeCallback(100:100:500, epsp!)
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epsp_ts = CB.PresetTimeCallback(100:100:500, epsp!)
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p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 100, 1000, 0.5, 0.005, 0]
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u0 = [-60, n_inf(-60), m_inf(-60), h_inf(-60), 0.0, 1.0, 0.0]

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