Merge pull request #8 from samuelbelko/remove-dep-and-fix-docs

Remove dependencies and improve docs

Project.toml

@@ -3,13 +3,7 @@ uuid = "89f642e6-4179-4274-8202-c11f4bd9a72c"
 authors = ["Samuel Belko <[email protected]> and contributors"]
 version = "1.0.0"
 
-[deps]
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
-
 [compat]
-Statistics = "1"
-StatsBase = "0.34"
 julia = "1.10"
 
 [extras]

docs/make.jl

@@ -1,5 +1,9 @@
 using Documenter, SurrogatesBase
 
+DocMeta.setdocmeta!(SurrogatesBase,
+    :DocTestSetup,
+    :(using SurrogatesBase))
+
 cp("./docs/Manifest.toml", "./docs/src/assets/Manifest.toml", force = true)
 cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true)
 
@@ -14,7 +18,7 @@ ENV["GKSwstype"] = "100"
 makedocs(modules = [SurrogatesBase],
     sitename = "SurrogatesBase.jl",
     clean = true,
-    doctest = false,
+    doctest = true,
     linkcheck = true,
     format = Documenter.HTML(assets = ["assets/favicon.ico"],
         canonical = "https://docs.sciml.ai/SurrogatesBase/stable/"),

docs/src/interface.md

@@ -75,8 +75,7 @@ The following methods might be supported:
 
 - `mean(finite_posterior(s,xs))` returns a `Vector` of posterior means at `xs`
 - `var(finite_posterior(s,xs))` returns a `Vector` of posterior variances at `xs`
-- `mean_and_var(finite_posterior(s,xs))` returns a `Tuple` consisting of a `Vector`
-of posterior means and a `Vector` of posterior variances at `xs`
+- `mean_and_var(finite_posterior(s,xs))` returns a `Tuple` consisting of a `Vector` of posterior means and a `Vector` of posterior variances at `xs`
 - `rand(finite_posterior(s,xs))` returns a `Vector`, which is a sample from the joint posterior at points `xs`
 
 ### Optional methods

src/SurrogatesBase.jl

@@ -18,18 +18,18 @@ Subtypes of `AbstractDeterministicSurrogate` are callable with a `Vector` of poi
 The result is a `Vector` of evaluations of the surrogate at points `xs`, corresponding to
 approximations of the underlying function at points `xs` respectively.
 
- # Examples
- ```jldoctest
- julia> struct ZeroSurrogate <: AbstractDeterministicSurrogate end
+# Examples
 
- julia> (::ZeroSurrogate)(xs) = 0
+```jldoctest
+julia> struct ZeroSurrogate <: AbstractDeterministicSurrogate end
 
- julia> s = ZeroSurrogate()
- ZeroSurrogate()
+julia> (::ZeroSurrogate)(xs) = 0
 
- julia> s([4]) == 0
- true
- ```
+julia> s = ZeroSurrogate();
+
+julia> s([4]) == 0
+true
+```
 """
 abstract type AbstractDeterministicSurrogate <: Function end
 
@@ -93,8 +93,7 @@ the returned object:
 
 - `mean(finite_posterior(s,xs))` returns a `Vector` of posterior means at `xs`
 - `var(finite_posterior(s,xs))` returns a `Vector` of posterior variances at `xs`
-- `mean_and_var(finite_posterior(s,xs))` returns a `Tuple` consisting of a `Vector`
-of posterior means and a `Vector` of posterior variances at `xs`
+- `mean_and_var(finite_posterior(s,xs))` returns a `Tuple` consisting of a `Vector` of posterior means and a `Vector` of posterior variances at `xs`
 - `rand(finite_posterior(s,xs))` returns a `Vector`, which is a sample from the joint
 posterior at points `xs`