Test doc generation

.github/codecov.yml

@@ -0,0 +1,8 @@
+coverage:
+  status:
+    project:
+      default:
+        threshold: 0.5%
+    patch:
+      default:
+        target: 80%

.github/workflows/SpellCheck.yml

@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v4
+      - name: Check spelling
+        uses: crate-ci/typos@master

Project.toml

@@ -5,14 +5,18 @@ version = "0.1.0"
 
 [deps]
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
 julia = "1.6"
 
 [extras]
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
+Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["SparseArrays", "Test"]
+test = ["DataFrames", "LinearAlgebra", "MLUtils", "Serialization", "SparseArrays", "Tables", "Test"]

docs/Project.toml

@@ -1,8 +1,9 @@
 [deps]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 ScientificTypesBase = "30f210dd-8aff-4c5f-94ba-8e64358c1161"
 Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
 
 [compat]
-Documenter = "^0.27"
-julia = "1"
+Documenter = "1"
+julia = "1.6"

docs/make.jl

@@ -2,30 +2,32 @@ using Documenter
 using LearnAPI
 using ScientificTypesBase
 
-const REPO="github.com/JuliaAI/LearnAPI.jl"
+const  REPO = Remotes.GitHub("JuliaAI", "LearnAPI.jl")
 
-makedocs(;
+makedocs(
     modules=[LearnAPI,],
     format=Documenter.HTML(prettyurls = get(ENV, "CI", nothing) == "true"),
     pages=[
-        "Overview" => "index.md",
-        "Goals and Approach" => "goals_and_approach.md",
+        "Home" => "index.md",
         "Anatomy of an Implementation" => "anatomy_of_an_implementation.md",
         "Reference" => "reference.md",
-        "Fit, update and ingest" => "fit_update_and_ingest.md",
-        "Predict and other operations" => "operations.md",
+        "Kinds of Target Proxy" => "kinds_of_target_proxy.md",
+        "fit" => "fit.md",
+        "predict, transform, and relatives" => "predict_transform.md",
+        "minimize" => "minimize.md",
+        "obs" => "obs.md",
         "Accessor Functions" => "accessor_functions.md",
-        "Optional Data Interface" => "optional_data_interface.md",
-        "Algorithm Traits" => "algorithm_traits.md",
+        "Algorithm Traits" => "traits.md",
         "Common Implementation Patterns" => "common_implementation_patterns.md",
         "Testing an Implementation" => "testing_an_implementation.md",
     ],
-    repo="https://$REPO/blob/{commit}{path}#L{line}",
-    sitename="LearnAPI.jl"
+    sitename="LearnAPI.jl",
+    warnonly = [:cross_references, :missing_docs],
+    repo = Remotes.GitHub("JuliaAI", "LearnAPI.jl"),
 )
 
 deploydocs(
-    ; repo=REPO,
     devbranch="dev",
     push_preview=false,
+    repo="github.com/JuliaAI/LearnAPI.jl.git",
 )

docs/src/accessor_functions.md

@@ -1,16 +1,39 @@
-# Accessor Functions 
+# [Accessor Functions](@id accessor_functions)
 
-> **Summary.** While byproducts of training are ordinarily recorded in the `report`
-> component of the output of `fit`/`update!`/`ingest!`, some families of algorithms report an
-> item that is likely shared by multiple algorithm types, and it is useful to have common
-> interface for accessing these directly. Training losses and feature importances are two
-> examples.
+The sole argument of an accessor function is the output, `model`, of [`fit`](@ref) or
+[`obsfit`](@ref).
+
+- [`LearnAPI.algorithm(model)`](@ref)
+- [`LearnAPI.extras(model)`](@ref)
+- [`LearnAPI.coefficients(model)`](@ref)
+- [`LearnAPI.intercept(model)`](@ref)
+- [`LearnAPI.tree(model)`](@ref)
+- [`LearnAPI.trees(model)`](@ref)
+- [`LearnAPI.feature_importances(model)`](@ref)
+- [`LearnAPI.training_labels(model)`](@ref)
+- [`LearnAPI.training_losses(model)`](@ref)
+- [`LearnAPI.training_scores(model)`](@ref)
+- [`LearnAPI.components(model)`](@ref)
+
+## Implementation guide
+
+All new implementations must implement [`LearnAPI.algorithm`](@ref). All others are
+optional.
+
+## Reference
 
 ```@docs
+LearnAPI.algorithm
+LearnAPI.extras
+LearnAPI.coefficients
+LearnAPI.intercept
+LearnAPI.tree
+LearnAPI.trees
 LearnAPI.feature_importances
 LearnAPI.training_losses
 LearnAPI.training_scores
 LearnAPI.training_labels
+LearnAPI.components
 ```