Vitepress based documentation

.gitignore

@@ -5,4 +5,8 @@
 Manifest.toml
 /docs/build/
 test/Manifest.toml
-test/gpu/Manifest.toml
+test/gpu/Manifest.toml
+node_modules
+package-lock.json
+docs/src/assets/Manifest.toml
+docs/src/assets/Project.toml

docs/Project.toml

@@ -8,6 +8,7 @@ DiffEqCallbacks = "459566f4-90b8-5000-8ac3-15dfb0a30def"
 DiffEqNoiseProcess = "77a26b50-5914-5dd7-bc55-306e6241c503"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+DocumenterVitepress = "4710194d-e776-4893-9690-8d956a29c365"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"

docs/make.jl

@@ -1,4 +1,5 @@
 using Documenter, SciMLSensitivity
+using DocumenterVitepress
 
 cp("./docs/Manifest.toml", "./docs/src/assets/Manifest.toml", force = true)
 cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true)
@@ -9,14 +10,24 @@ using Plots
 
 include("pages.jl")
 
+deploy_config = Documenter.auto_detect_deploy_system()
+deploy_decision = Documenter.deploy_folder(deploy_config; repo="github.com/SciML/SciMLSensitivity.jl",
+    devbranch="master", devurl="dev", push_preview=true)
+
 makedocs(sitename = "SciMLSensitivity.jl",
     authors = "Chris Rackauckas et al.",
     modules = [SciMLSensitivity],
     clean = true, doctest = false, linkcheck = true,
-    warnonly = [:missing_docs],
-    format = Documenter.HTML(assets = ["assets/favicon.ico"],
-        canonical = "https://docs.sciml.ai/SciMLSensitivity/stable/"),
+    warnonly = true,
+    format = DocumenterVitepress.MarkdownVitepress(
+            repo="https://github.com/SciML/SciMLSensitivity.jl",
+            devbranch="master", devurl="dev",
+            deploy_url="https://docs.sciml.ai/SciMLSensitivity/", deploy_decision
+        ),
     pages = pages)
 
 deploydocs(repo = "github.com/SciML/SciMLSensitivity.jl.git";
+    target="build", # this is where Vitepress stores its output
+    branch = "gh-pages",
+    devbranch="master",
     push_preview = true)

docs/package.json

@@ -0,0 +1,17 @@
+{
+    "devDependencies": {
+      "markdown-it": "^14.1.0",
+      "markdown-it-mathjax3": "^4.3.2",
+      "vitepress": "^1.1.4",
+      "vitepress-plugin-tabs": "^0.5.0"
+    },
+    "scripts": {
+      "docs:dev": "vitepress dev build/.documenter",
+      "docs:build": "vitepress build build/.documenter",
+      "docs:preview": "vitepress preview build/.documenter"
+    },
+    "dependencies": {
+      "@shikijs/transformers": "^1.1.7",
+      "markdown-it-footnote": "^4.0.0"
+    }
+  }

docs/pages.jl

@@ -1,37 +1,51 @@
-pages = ["index.md",
-    "getting_started.md",
-    "Tutorials" => Any["tutorials/parameter_estimation_ode.md",
-        "tutorials/direct_sensitivity.md",
-        "tutorials/adjoint_continuous_functional.md",
-        "tutorials/data_parallel.md",
-        "tutorials/chaotic_ode.md",
-        "Training Techniques and Tips" => Any["tutorials/training_tips/local_minima.md",
-            "tutorials/training_tips/divergence.md",
-            "tutorials/training_tips/multiple_nn.md"]],
-    "Examples" => Any[
-        "Ordinary Differential Equations (ODEs)" => Any["examples/ode/exogenous_input.md",
-            "examples/ode/prediction_error_method.md",
-            "examples/ode/second_order_adjoints.md",
-            "examples/ode/second_order_neural.md"],
-        "Neural Ordinary Differential Equations (Neural ODE)" => Any[
-            "examples/neural_ode/neural_ode_flux.md",
-            "examples/neural_ode/simplechains.md",
-            "examples/neural_ode/minibatch.md"],
-        "Stochastic Differential Equations (SDEs)" => Any[
-            "examples/sde/optimization_sde.md",
-            "examples/sde/SDE_control.md"],
-        "Delay Differential Equations (DDEs)" => Any["examples/dde/delay_diffeq.md"],
-        "Partial Differential Equations (PDEs)" => Any["examples/pde/pde_constrained.md"],
-        "Hybrid and Jump Equations" => Any["examples/hybrid_jump/hybrid_diffeq.md",
-            "examples/hybrid_jump/bouncing_ball.md"],
-        "Bayesian Estimation" => Any["examples/bayesian/turing_bayesian.md"],
-        "Optimal and Model Predictive Control" => Any[
-            "examples/optimal_control/optimal_control.md",
-            "examples/optimal_control/feedback_control.md"]],
-    "Manual and APIs" => Any["manual/differential_equation_sensitivities.md",
-        "manual/nonlinear_solve_sensitivities.md",
-        "manual/direct_forward_sensitivity.md",
-        "manual/direct_adjoint_sensitivities.md"],
+pages = ["Home" => "index.md",
+    "Get Started" => "getting_started.md",
+    "Tutorials" => [
+        "Parameter estimation ode" => "tutorials/parameter_estimation_ode.md",
+        "Training Techniques and Tips" => [
+            "Local minima" => "tutorials/training_tips/local_minima.md",
+            ]
+        ],
+    "Examples" => [
+        "Ordinary Differential Equations (ODEs)" => [
+            "Exogenous input"=>"examples/ode/exogenous_input.md",
+            "Prediction error method" => "examples/ode/prediction_error_method.md",
+            "Second order adjoints" => "examples/ode/second_order_adjoints.md",
+            "second_order_neural" => "examples/ode/second_order_neural.md"
+            ],
+        "Neural Ordinary Differential Equations (Neural ODE)" => [
+            "neural ode flux"=>"examples/neural_ode/neural_ode_flux.md",
+            "Simple chains" => "examples/neural_ode/simplechains.md",
+            "Minibatch" => "examples/neural_ode/minibatch.md"
+            ],
+        "Stochastic Differential Equations (SDEs)" => [
+            "optimization sde"=>"examples/sde/optimization_sde.md",
+            "SDE_control" => "examples/sde/SDE_control.md"
+            ],
+        "Delay Differential Equations (DDEs)" => [
+            "delay diffeq"=>"examples/dde/delay_diffeq.md"
+            ],
+        "Partial Differential Equations (PDEs)" => [
+            "pde constrained"=>"examples/pde/pde_constrained.md"
+            ],
+        "Hybrid and Jump Equations" => [
+            "Hybrid diffeq"=>"examples/hybrid_jump/hybrid_diffeq.md",
+            "Bouncing ball" => "examples/hybrid_jump/bouncing_ball.md"
+            ],
+        "Bayesian Estimation" => [
+            "Turing Bayesian"=>"examples/bayesian/turing_bayesian.md"
+            ],
+        "Optimal and Model Predictive Control" => [
+            "Optimal control"=>"examples/optimal_control/optimal_control.md",
+            "Feedback control" => "examples/optimal_control/feedback_control.md"
+            ]
+        ],
+    "Manual and APIs" => [
+        "Differential equation sensitivities" => "manual/differential_equation_sensitivities.md",
+        "Nonlinear solve sensitivities" => "manual/nonlinear_solve_sensitivities.md",
+        "Direct forward sensitivity" => "manual/direct_forward_sensitivity.md",
+        "Direct adjoint sensitivities" => "manual/direct_adjoint_sensitivities.md"
+        ],
     "Benchmarks" => "Benchmark.md",
     "Sensitivity Math Details" => "sensitivity_math.md"
-]
+]