canonize docs

README.md

@@ -1,20 +1,35 @@
 # LabelledArrays.jl
 
 [![Join the chat at https://julialang.zulipchat.com #sciml-bridged](https://img.shields.io/static/v1?label=Zulip&message=chat&color=9558b2&labelColor=389826)](https://julialang.zulipchat.com/#narrow/stream/279055-sciml-bridged)
-[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](http://labelledarrays.sciml.ai/stable/)
-[![Global Docs](https://img.shields.io/badge/docs-SciML-blue.svg)](https://docs.sciml.ai/dev/modules/LabelledArrays/)
+[![Global Docs](https://img.shields.io/badge/docs-SciML-blue.svg)](https://docs.sciml.ai/LabelledArrays/stable/)
 
 [![codecov](https://codecov.io/gh/SciML/LabelledArrays.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/SciML/LabelledArrays.jl)
 [![Build Status](https://github.com/SciML/LabelledArrays.jl/workflows/CI/badge.svg)](https://github.com/SciML/LabelledArrays.jl/actions?query=workflow%3ACI)
 
 [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
 [![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
 
+# About
+
 LabelledArrays.jl is a package which provides arrays with labels, i.e. they are
 arrays which `map`, `broadcast`, and all of that good stuff, but their components
 are labelled. Thus for instance you can set that the second component is named
 `:second` and retrieve it with `A.second`.
 
+## How to install
+
+The package can be installed from this repository by
+```julia
+> using Pkg
+> Pkg.add("LabelledArrays")
+```
+## Tutorials and Documentation
+
+For information on using the package,
+[see the stable documentation](https://docs.sciml.ai/LabelledArrays/stable/). Use the
+[in-development documentation](https://docs.sciml.ai/LabelledArrays/dev/) for the version of
+the documentation, which contains the unreleased features.
+
 ## SLArrays
 
 The `SLArray` and `SLVector` macros are for creating static LabelledArrays.
@@ -268,4 +283,4 @@ unlike a named tuple, is mutable.
 
 This functionality has been removed from LabelledArrays.jl, but can 
 replicated with the same compile-time performance and indexing syntax 
-using [DimensionalData.jl](https://github.com/rafaqz/DimensionalData.jl).
+using [DimensionalData.jl](https://rafaqz.github.io/DimensionalData.jl/stable/).

docs/make.jl

@@ -8,7 +8,7 @@ makedocs(sitename = "LabelledArrays.jl",
          clean = true, doctest = false,
          format = Documenter.HTML(analytics = "UA-90474609-3",
                                   assets = ["assets/favicon.ico"],
-                                  canonical = "https://labelledarrays.sciml.ai/stable/"),
+                                  canonical = "https://docs.sciml.ai/LabelledArrays/stable/"),
          pages = pages)
 
 deploydocs(repo = "github.com/SciML/LabelledArrays.jl.git";

docs/src/Example_dsl.md

@@ -45,7 +45,7 @@ sol[10].x
 In the example above, we used an `LArray` to define the
 intial state `u0` as well as the parameter vector `p`.
 The reminder of the ODE solution steps are are no different
-that the original `DifferentialEquations` [tutorials](https://diffeq.sciml.ai/stable/tutorials/ode_example/#Example-2:-Solving-Systems-of-Equations).
+that the original `DifferentialEquations` [tutorials](https://docs.sciml.ai/DiffEqDocs/stable/tutorials/ode_example/#Example-2:-Solving-Systems-of-Equations).
 
 Alternatively, we can use an immutable `SLVector` to 
 implement the same equation. In this case, we need to 

docs/src/LArrays.md

@@ -7,7 +7,7 @@ the given values:
 
 Users interested in using labelled elements in their arrays should also 
 consider `ComponentArrays` from the 
-[ComponentArrays.jl](https://github.com/jonniedie/ComponentArrays.jl)
+[ComponentArrays.jl](https://docs.sciml.ai/ComponentArrays/stable/)
 library. `ComponentArrays` are well integrated into the SciML ecosystem. 
 
 ## `@LArray` and `@LVector` macros

test/diffeq.jl

@@ -15,7 +15,7 @@ p = LorenzParameterVector(10.0, 28.0, 8 / 3)
 tspan = (0.0, 10.0)
 prob = ODEProblem(f, u0, tspan, p)
 sol = solve(prob, Rosenbrock23())
-@test sol.retcode === :Success
+@test sol.retcode == :Success
 sol = solve(prob, Tsit5())
 @test prob.u0 === sol.u[1] === u0
 @test prob.p === p