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docs CI: re-clone StochasticDiffEq fresh in env setup (complete #870 fix) #872

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Merged
ChrisRackauckas merged 2 commits into from
Jun 16, 2026
Merged

docs CI: re-clone StochasticDiffEq fresh in env setup (complete #870 fix) #872

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14fc13e
docs: build against released (registry) OrdinaryDiffEq/StochasticDiffEq
ChrisRackauckas Jun 16, 2026
3de0840
docs: source EnsembleProblem from SciMLBase in the low_dep example
ChrisRackauckas Jun 16, 2026
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8 changes: 0 additions & 8 deletions .github/workflows/Documentation.yml
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Expand Up @@ -31,14 +31,6 @@ jobs:
using Pkg
Pkg.develop(PackageSpec(path=pwd()))
Pkg.instantiate()
println("--- Adding OrdinaryDiffEq from master")
# Drop any stale dev checkout a previous run left in ~/.julia/dev so the
# current master is cloned fresh; a stale checkout can pin an old version
# that conflicts with the docs [compat] (e.g. OrdinaryDiffEq 6.x vs "7").
let p = joinpath(Pkg.devdir(), "OrdinaryDiffEq")
isdir(p) && rm(p; recursive = true, force = true)
end
Pkg.develop("OrdinaryDiffEq")
env:
DATADEPS_ALWAYS_ACCEPT: true
JULIA_PKG_PRECOMPILE_AUTO: 0
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9 changes: 5 additions & 4 deletions docs/make.jl
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Expand Up @@ -25,10 +25,11 @@ import ODEProblemLibrary,
SDEProblemLibrary, DDEProblemLibrary, DAEProblemLibrary, BVProblemLibrary
using Sundials, DASKR, LSODA, DASSL, SimpleDiffEq, ODEInterfaceDiffEq

# Use development versions for API documentation
import Pkg
Pkg.develop("OrdinaryDiffEq")
Pkg.develop("StochasticDiffEq")
# OrdinaryDiffEq, StochasticDiffEq and the solver subpackages are resolved from the
# registry at their released versions — their docs/ ship in the released packages,
# so the API docs below are copied from the installed (stable) packages with no
# Pkg.develop of master (which would pin the docs to unreleased code and risk
# monorepo version skew against the registered subpackages).

cp("./docs/Manifest.toml", "./docs/src/assets/Manifest.toml", force = true)
cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true)
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3 changes: 2 additions & 1 deletion docs/src/features/low_dep.md
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Expand Up @@ -121,6 +121,7 @@ the old `using DifferentialEquations` shape:
import OrdinaryDiffEq as ODE
import OrdinaryDiffEqLowOrderRK as ODELow # Euler
import DiffEqCallbacks as CB # ProbIntsUncertainty
import SciMLBase # EnsembleProblem
function fitz(du, u, p, t)
V, R = u
a, b, c = p
Expand All @@ -132,7 +133,7 @@ tspan = (0.0, 20.0)
p = (0.2, 0.2, 3.0)
prob = ODE.ODEProblem(fitz, u0, tspan, p)
cb = CB.ProbIntsUncertainty(0.2, 1)
ensemble_prob = ODE.EnsembleProblem(prob)
ensemble_prob = SciMLBase.EnsembleProblem(prob)
sim = ODE.solve(ensemble_prob, ODELow.Euler(), trajectories = 100, callback = cb, dt = 1 / 10)
```

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