Fix docs build for OrdinaryDiffEq v7 / DifferentialEquations v8 (+ #868 AlgebraicMultigrid bump)

.typos.toml

@@ -1,5 +1,6 @@
 [default.extend-words]
 quations = "quations"
+Lamba = "Lamba"
 IIF = "IIF"
 padd = "padd"
 thr = "thr"

docs/Project.toml

@@ -15,24 +15,53 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
 DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
+DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
 DiffEqDocs = "d91efeb5-c178-44a6-a2ee-51685df7c78e"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FiniteDiff = "6a86dc24-6348-571c-b903-95158fe2bd41"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+ImplicitDiscreteSolve = "3263718b-31ed-49cf-8a0f-35a466e8af96"
 IncompleteLU = "40713840-3770-5561-ab4c-a76e7d0d7895"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 LSODA = "7f56f5a3-f504-529b-bc02-0b1fe5e64312"
+LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 ODEInterfaceDiffEq = "09606e27-ecf5-54fc-bb29-004bd9f985bf"
 ODEProblemLibrary = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationNLopt = "4e6fcdb7-1186-4e1f-a706-475e75c168bb"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+OrdinaryDiffEqAMF = "08082164-f6a1-4363-b3df-3aa6fcf571ad"
+OrdinaryDiffEqAdamsBashforthMoulton = "89bda076-bce5-4f1c-845f-551c83cdda9a"
 OrdinaryDiffEqBDF = "6ad6398a-0878-4a85-9266-38940aa047c8"
 OrdinaryDiffEqCore = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
+OrdinaryDiffEqDefault = "50262376-6c5a-4cf5-baba-aaf4f84d72d7"
+OrdinaryDiffEqExplicitRK = "9286f039-9fbf-40e8-bf65-aa933bdc4db0"
+OrdinaryDiffEqExponentialRK = "e0540318-69ee-4070-8777-9e2de6de23de"
+OrdinaryDiffEqExtrapolation = "becaefa8-8ca2-5cf9-886d-c06f3d2bd2c4"
+OrdinaryDiffEqFIRK = "5960d6e9-dd7a-4743-88e7-cf307b64f125"
+OrdinaryDiffEqFeagin = "101fe9f7-ebb6-4678-b671-3a81e7194747"
+OrdinaryDiffEqHighOrderRK = "d28bc4f8-55e1-4f49-af69-84c1a99f0f58"
+OrdinaryDiffEqIMEXMultistep = "9f002381-b378-40b7-97a6-27a27c83f129"
+OrdinaryDiffEqLinear = "521117fe-8c41-49f8-b3b6-30780b3f0fb5"
+OrdinaryDiffEqLowOrderRK = "1344f307-1e59-4825-a18e-ace9aa3fa4c6"
+OrdinaryDiffEqLowStorageRK = "b0944070-b475-4768-8dec-fb6eb410534d"
+OrdinaryDiffEqNordsieck = "c9986a66-5c92-4813-8696-a7ec84c806c8"
+OrdinaryDiffEqPDIRK = "5dd0a6cf-3d4b-4314-aa06-06d4e299bc89"
+OrdinaryDiffEqPRK = "5b33eab2-c0f1-4480-b2c3-94bc1e80bda1"
+OrdinaryDiffEqQPRK = "04162be5-8125-4266-98ed-640baecc6514"
+OrdinaryDiffEqRKN = "af6ede74-add8-4cfd-b1df-9a4dbb109d7a"
+OrdinaryDiffEqRosenbrock = "43230ef6-c299-4910-a778-202eb28ce4ce"
+OrdinaryDiffEqSDIRK = "2d112036-d095-4a1e-ab9a-08536f3ecdbf"
+OrdinaryDiffEqSSPRK = "669c94d9-1f4b-4b64-b377-1aa079aa2388"
+OrdinaryDiffEqStabilizedIRK = "e3e12d00-db14-5390-b879-ac3dd2ef6296"
+OrdinaryDiffEqStabilizedRK = "358294b1-0aab-51c3-aafe-ad5ab194a2ad"
+OrdinaryDiffEqSymplecticRK = "fa646aed-7ef9-47eb-84c4-9443fc8cbfa8"
+OrdinaryDiffEqTsit5 = "b1df2697-797e-41e3-8120-5422d3b24e4a"
+OrdinaryDiffEqVerner = "79d7bb75-1356-48c1-b8c0-6832512096c2"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 SDEProblemLibrary = "c72e72a9-a271-4b2b-8966-303ed956772e"
@@ -43,6 +72,16 @@ SparseConnectivityTracer = "9f842d2f-2579-4b1d-911e-f412cf18a3f5"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 SteadyStateDiffEq = "9672c7b4-1e72-59bd-8a11-6ac3964bc41f"
 StochasticDiffEq = "789caeaf-c7a9-5a7d-9973-96adeb23e2a0"
+StochasticDiffEqCore = "19c5a474-6cd1-4a5f-be79-46dc34e54d7f"
+StochasticDiffEqHighOrder = "0520c28c-50fd-4d16-9c96-902fc80b3bab"
+StochasticDiffEqIIF = "ebf54054-c36b-4494-9aba-657e36df524f"
+StochasticDiffEqImplicit = "5080b986-4c76-4669-b5dc-373a41579d5b"
+StochasticDiffEqLeaping = "aefaaa88-39f2-4e89-b162-d61b7e8cc81b"
+StochasticDiffEqLowOrder = "d15fe365-ce7f-450a-828a-7985bd5b681b"
+StochasticDiffEqMilstein = "8c95a807-c8e7-4581-8419-890d001af53e"
+StochasticDiffEqROCK = "db241ea8-0e6b-4abc-8f2d-1adff2294fd9"
+StochasticDiffEqRODE = "49714585-0aa1-4f53-b1e6-a9b8c0d5e03f"
+StochasticDiffEqWeak = "af2a2fcd-1c36-4cbe-a6d0-5afda784a085"
 Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
@@ -51,7 +90,7 @@ DiffEqDocs = {path = ".."}
 
 [compat]
 ADTypes = "1.7"
-AlgebraicMultigrid = "0.5, 0.6, 1"
+AlgebraicMultigrid = "0.5, 0.6, 1, 2"
 BSON = "0.3"
 BVProblemLibrary = "0.1.2"
 BenchmarkTools = "1"
@@ -66,23 +105,52 @@ DataFrames = "1.4"
 DelayDiffEq = "5.52, 6.0"
 DiffEqBase = "7"
 DiffEqCallbacks = "4"
+DiffEqDevTools = "3, 4.0"
 DifferentialEquations = "7.14, 8.0"
 Distributions = "0.25"
 Documenter = "1"
 FiniteDiff = "2"
 ForwardDiff = "0.10, 1"
+ImplicitDiscreteSolve = "2"
 IncompleteLU = "0.2"
 JLD2 = "0.4, 0.5.1, 0.6"
 LSODA = "0.7, 1.0"
+LinearSolve = "2, 3"
 ModelingToolkit = "9, 10, 11.0"
 NonlinearSolve = "3.15, 4"
 ODEInterfaceDiffEq = "3, 4.0, 5.0"
 ODEProblemLibrary = "0.1, 1"
 Optimization = "3, 4, 5"
 OptimizationNLopt = "0.2, 0.3"
 OrdinaryDiffEq = "7"
+OrdinaryDiffEqAMF = "2"
+OrdinaryDiffEqAdamsBashforthMoulton = "2"
 OrdinaryDiffEqBDF = "2"
 OrdinaryDiffEqCore = "4, 5.0"
+OrdinaryDiffEqDefault = "2"
+OrdinaryDiffEqExplicitRK = "2"
+OrdinaryDiffEqExponentialRK = "2"
+OrdinaryDiffEqExtrapolation = "2"
+OrdinaryDiffEqFIRK = "2"
+OrdinaryDiffEqFeagin = "2"
+OrdinaryDiffEqHighOrderRK = "2"
+OrdinaryDiffEqIMEXMultistep = "2"
+OrdinaryDiffEqLinear = "2"
+OrdinaryDiffEqLowOrderRK = "2"
+OrdinaryDiffEqLowStorageRK = "3"
+OrdinaryDiffEqNordsieck = "2"
+OrdinaryDiffEqPDIRK = "2"
+OrdinaryDiffEqPRK = "2"
+OrdinaryDiffEqQPRK = "2"
+OrdinaryDiffEqRKN = "2"
+OrdinaryDiffEqRosenbrock = "2"
+OrdinaryDiffEqSDIRK = "2"
+OrdinaryDiffEqSSPRK = "2"
+OrdinaryDiffEqStabilizedIRK = "2"
+OrdinaryDiffEqStabilizedRK = "2"
+OrdinaryDiffEqSymplecticRK = "2"
+OrdinaryDiffEqTsit5 = "2"
+OrdinaryDiffEqVerner = "2"
 Plots = "1"
 RecursiveArrayTools = "4"
 SDEProblemLibrary = "0.1, 1"
@@ -93,5 +161,15 @@ SparseConnectivityTracer = "0.6, 1"
 StaticArrays = "1"
 SteadyStateDiffEq = "2.4"
 StochasticDiffEq = "7"
+StochasticDiffEqCore = "2"
+StochasticDiffEqHighOrder = "2"
+StochasticDiffEqIIF = "2"
+StochasticDiffEqImplicit = "2"
+StochasticDiffEqLeaping = "2"
+StochasticDiffEqLowOrder = "2"
+StochasticDiffEqMilstein = "2"
+StochasticDiffEqROCK = "2"
+StochasticDiffEqRODE = "2"
+StochasticDiffEqWeak = "2"
 Sundials = "4.11.3, 5, 6.0"
 Unitful = "1"

docs/make.jl

@@ -1,6 +1,26 @@
 using Documenter, DiffEqBase, SciMLBase, OrdinaryDiffEq, OrdinaryDiffEqBDF,
     OrdinaryDiffEqCore, StochasticDiffEq, DelayDiffEq, SteadyStateDiffEq, DiffEqCallbacks,
     BoundaryValueDiffEq
+# Load the OrdinaryDiffEq/StochasticDiffEq solver subpackages directly instead of relying
+# on the meta-packages to reexport them: OrdinaryDiffEq v7 already dropped its reexports,
+# so listing each subpackage explicitly is what keeps the API docs complete and robust.
+using OrdinaryDiffEqAdamsBashforthMoulton, OrdinaryDiffEqDefault, OrdinaryDiffEqExplicitRK,
+    OrdinaryDiffEqExponentialRK, OrdinaryDiffEqExtrapolation, OrdinaryDiffEqFeagin,
+    OrdinaryDiffEqFIRK, OrdinaryDiffEqHighOrderRK, OrdinaryDiffEqIMEXMultistep,
+    OrdinaryDiffEqLinear, OrdinaryDiffEqLowOrderRK, OrdinaryDiffEqLowStorageRK,
+    OrdinaryDiffEqNordsieck, OrdinaryDiffEqPDIRK, OrdinaryDiffEqPRK, OrdinaryDiffEqQPRK,
+    OrdinaryDiffEqRKN, OrdinaryDiffEqRosenbrock, OrdinaryDiffEqSDIRK, OrdinaryDiffEqSSPRK,
+    OrdinaryDiffEqStabilizedIRK, OrdinaryDiffEqStabilizedRK, OrdinaryDiffEqSymplecticRK,
+    OrdinaryDiffEqTsit5, OrdinaryDiffEqVerner, OrdinaryDiffEqAMF, ImplicitDiscreteSolve,
+    DiffEqDevTools
+using StochasticDiffEqCore, StochasticDiffEqHighOrder, StochasticDiffEqIIF,
+    StochasticDiffEqImplicit, StochasticDiffEqLeaping, StochasticDiffEqLowOrder,
+    StochasticDiffEqMilstein, StochasticDiffEqROCK, StochasticDiffEqRODE,
+    StochasticDiffEqWeak
+# Bring the OrdinaryDiffEqCore controller API symbols into Main so the unqualified
+# @ref links in the copied controllers.md resolve (mirrors OrdinaryDiffEq.jl's docs).
+using OrdinaryDiffEqCore: default_controller, resolve_basic, get_EEst, set_EEst!,
+    CompositeController
 import ODEProblemLibrary,
     SDEProblemLibrary, DDEProblemLibrary, DAEProblemLibrary, BVProblemLibrary
 using Sundials, DASKR, LSODA, DASSL, SimpleDiffEq, ODEInterfaceDiffEq
@@ -24,6 +44,11 @@ if isdir(ordinartdiffeq_docs_path)
     # Copy all the docs from OrdinaryDiffEq.jl
     cp(ordinartdiffeq_docs_path, ordinary_diffeq_dest, force = true)
 
+    # OrdinaryDiffEq's developer docs are contributor-internal and their @eval blocks
+    # read paths relative to OrdinaryDiffEq's own build layout, so they cannot build
+    # inside DiffEqDocs; drop them from the user-facing site.
+    rm(joinpath(ordinary_diffeq_dest, "devtools"), recursive = true, force = true)
+
     # Copy the pages.jl file from OrdinaryDiffEq.jl
     ordinary_diffeq_pages_dest = joinpath(@__DIR__, "ordinarydiffeq_pages.jl")
     ordinary_diffeq_pages_file = joinpath(ordinartdiffeq_docs_root, "pages.jl")
@@ -69,33 +94,47 @@ makedocs(
         DAEProblemLibrary,
         BVProblemLibrary,
         OrdinaryDiffEq,
-        OrdinaryDiffEq.OrdinaryDiffEqAdamsBashforthMoulton,
-        OrdinaryDiffEq.OrdinaryDiffEqBDF,
-        OrdinaryDiffEq.OrdinaryDiffEqDefault,
-        OrdinaryDiffEq.OrdinaryDiffEqExplicitRK,
-        OrdinaryDiffEq.OrdinaryDiffEqExponentialRK,
-        OrdinaryDiffEq.OrdinaryDiffEqExtrapolation,
-        OrdinaryDiffEq.OrdinaryDiffEqFeagin,
-        OrdinaryDiffEq.OrdinaryDiffEqFIRK,
-        OrdinaryDiffEq.OrdinaryDiffEqHighOrderRK,
-        OrdinaryDiffEq.OrdinaryDiffEqIMEXMultistep,
-        OrdinaryDiffEq.OrdinaryDiffEqLinear,
-        OrdinaryDiffEq.OrdinaryDiffEqLowOrderRK,
-        OrdinaryDiffEq.OrdinaryDiffEqLowStorageRK,
-        OrdinaryDiffEq.OrdinaryDiffEqNordsieck,
-        OrdinaryDiffEq.OrdinaryDiffEqPDIRK,
-        OrdinaryDiffEq.OrdinaryDiffEqPRK,
-        OrdinaryDiffEq.OrdinaryDiffEqQPRK,
-        OrdinaryDiffEq.OrdinaryDiffEqRKN,
-        OrdinaryDiffEq.OrdinaryDiffEqRosenbrock,
-        OrdinaryDiffEq.OrdinaryDiffEqSDIRK,
-        OrdinaryDiffEq.OrdinaryDiffEqSSPRK,
-        OrdinaryDiffEq.OrdinaryDiffEqStabilizedIRK,
-        OrdinaryDiffEq.OrdinaryDiffEqStabilizedRK,
-        OrdinaryDiffEq.OrdinaryDiffEqSymplecticRK,
-        OrdinaryDiffEq.OrdinaryDiffEqTsit5,
-        OrdinaryDiffEq.OrdinaryDiffEqVerner,
+        OrdinaryDiffEqCore,
+        OrdinaryDiffEqAdamsBashforthMoulton,
+        OrdinaryDiffEqBDF,
+        OrdinaryDiffEqDefault,
+        OrdinaryDiffEqExplicitRK,
+        OrdinaryDiffEqExponentialRK,
+        OrdinaryDiffEqExtrapolation,
+        OrdinaryDiffEqFeagin,
+        OrdinaryDiffEqFIRK,
+        OrdinaryDiffEqHighOrderRK,
+        OrdinaryDiffEqIMEXMultistep,
+        OrdinaryDiffEqLinear,
+        OrdinaryDiffEqLowOrderRK,
+        OrdinaryDiffEqLowStorageRK,
+        OrdinaryDiffEqNordsieck,
+        OrdinaryDiffEqPDIRK,
+        OrdinaryDiffEqPRK,
+        OrdinaryDiffEqQPRK,
+        OrdinaryDiffEqRKN,
+        OrdinaryDiffEqRosenbrock,
+        OrdinaryDiffEqSDIRK,
+        OrdinaryDiffEqSSPRK,
+        OrdinaryDiffEqStabilizedIRK,
+        OrdinaryDiffEqStabilizedRK,
+        OrdinaryDiffEqSymplecticRK,
+        OrdinaryDiffEqTsit5,
+        OrdinaryDiffEqVerner,
+        OrdinaryDiffEqAMF,
+        ImplicitDiscreteSolve,
+        DiffEqDevTools,
         StochasticDiffEq,
+        StochasticDiffEqCore,
+        StochasticDiffEqHighOrder,
+        StochasticDiffEqIIF,
+        StochasticDiffEqImplicit,
+        StochasticDiffEqLeaping,
+        StochasticDiffEqLowOrder,
+        StochasticDiffEqMilstein,
+        StochasticDiffEqROCK,
+        StochasticDiffEqRODE,
+        StochasticDiffEqWeak,
         DelayDiffEq,
         SteadyStateDiffEq,
         DiffEqCallbacks,

docs/pages.jl

@@ -25,6 +25,9 @@ function transform_ordinarydiffeq_pages(pages_array)
 end
 
 ordinary_diffeq_pages = transform_ordinarydiffeq_pages(pages)
+# The Developer Documentation section maps to OrdinaryDiffEq's contributor-internal
+# devtools pages, which are excluded from the DiffEqDocs build (see docs/make.jl).
+filter!(p -> !(p isa Pair && first(p) == "Developer Documentation"), ordinary_diffeq_pages)
 
 # Load StochasticDiffEq pages - if available
 stochastic_diffeq_pages_file = joinpath(@__DIR__, "stochasticdiffeq_pages.jl")
@@ -159,3 +162,9 @@ pages = Any[
         "migration/ordinarydiffeq_v7.md",
     ],
 ]
+
+# StochasticDiffEq ships no docs in the OrdinaryDiffEq v7 monorepo, so drop the API
+# section entirely rather than leaving an empty navigation entry.
+if isempty(stochastic_diffeq_pages)
+    filter!(p -> !(p isa Pair && first(p) == "StochasticDiffEq.jl API"), pages)
+end

docs/src/basics/faq.md

@@ -480,7 +480,7 @@ end
 function f(p)
     prob = DE.ODEProblem(func, eltype(p).([1.0, 1.0]), (0.0, 10.0), p)
     # Lower tolerances to show the methods converge to the same value
-    DE.solve(prob, DE.Tsit5(), save_everystep = false, abstol = 1e-12, reltol = 1e-12)[end]
+    DE.solve(prob, DE.Tsit5(), save_everystep = false, abstol = 1e-12, reltol = 1e-12).u[end]
 end
 ```
 

docs/src/examples/classical_physics.md

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

docs/src/examples/spiking_neural_systems.md

@@ -20,6 +20,7 @@ The LIF model has five parameters, `gL, EL, C, Vth, I` and we define it in the `
 
 ```@example spikingneural
 import DifferentialEquations as DE
+import DiffEqCallbacks as CB # PresetTimeCallback is no longer reexported by DifferentialEquations v8
 import ComponentArrays
 import Plots
 Plots.gr()
@@ -65,7 +66,7 @@ function reset!(integrator)
 end
 
 threshold = DE.ContinuousCallback(thr, reset!, nothing)
-current_step = DE.PresetTimeCallback([2, 15], integrator -> integrator.p.I += 150.0)
+current_step = CB.PresetTimeCallback([2, 15], integrator -> integrator.p.I += 150.0)
 cb = DE.CallbackSet(current_step, threshold)
 ```
 
@@ -100,6 +101,7 @@ We see that the model is resting at `-75` while there is no input. At `t=2` the
 ```@example spikingneural
 #Izhikevichch Model
 import DifferentialEquations as DE
+import DiffEqCallbacks as CB
 import Plots
 
 function izh!(du, u, p, t)
@@ -123,7 +125,7 @@ function reset!(integrator)
 end
 
 threshold = DE.DiscreteCallback(thr, reset!)
-current_step = DE.PresetTimeCallback(50, integrator -> integrator.p[5] += 10)
+current_step = CB.PresetTimeCallback(50, integrator -> integrator.p[5] += 10)
 cb = DE.CallbackSet(current_step, threshold)
 ```
 
@@ -168,6 +170,7 @@ The Hodgkin-Huxley (HH) model is our first biophysically realistic model. This m
 
 ```@example spikingneural
 import DifferentialEquations as DE
+import DiffEqCallbacks as CB
 import Plots
 
 # Potassium ion-channel rate functions
@@ -198,7 +201,7 @@ We have three different types of ionic conductances. Potassium, sodium and the l
 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).
 
 ```@example spikingneural
-current_step = DE.PresetTimeCallback(100, integrator -> integrator.p[8] += 1)
+current_step = CB.PresetTimeCallback(100, integrator -> integrator.p[8] += 1)
 
 # n, m & h steady-states
 n_inf(v) = alpha_n(v) / (alpha_n(v) + beta_n(v))
@@ -308,7 +311,7 @@ function epsp!(integrator)
     integrator.u[6] -= integrator.u[5] * integrator.u[6]
 end
 
-epsp_ts = DE.PresetTimeCallback(100:100:500, epsp!)
+epsp_ts = CB.PresetTimeCallback(100:100:500, epsp!)
 
 p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 1000, 50, 0.5, 0.005, 0]
 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])
 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.
 
 ```@example spikingneural
-epsp_ts = DE.PresetTimeCallback(100:1000:5100, epsp!)
+epsp_ts = CB.PresetTimeCallback(100:1000:5100, epsp!)
 
 p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 500, 50, 0.5, 0.005, 0]
 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])
 We can also change these time constants such that the dynamics show short-term depression instead of facilitation.
 
 ```@example spikingneural
-epsp_ts = DE.PresetTimeCallback(100:100:500, epsp!)
+epsp_ts = CB.PresetTimeCallback(100:100:500, epsp!)
 
 p = [35.0, 40.0, 0.3, -77.0, 55.0, -65.0, 1, 0, 30, 100, 1000, 0.5, 0.005, 0]
 u0 = [-60, n_inf(-60), m_inf(-60), h_inf(-60), 0.0, 1.0, 0.0]