doc_improv

.JuliaFormatter.toml

@@ -1 +1,2 @@
-style = "sciml"
+style = "sciml"
+format_markdown = true

LICENSE.md

@@ -1,42 +1,35 @@
 The PoissonRandom.jl package is licensed under the MIT "Expat" License:
 
 > Copyright (c) 2018: Christopher Rackauckas.
->
->
+> 
 > Permission is hereby granted, free of charge, to any person obtaining a copy
->
+> 
 > of this software and associated documentation files (the "Software"), to deal
->
+> 
 > in the Software without restriction, including without limitation the rights
->
+> 
 > to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
->
+> 
 > copies of the Software, and to permit persons to whom the Software is
->
+> 
 > furnished to do so, subject to the following conditions:
->
->
->
+> 
 > The above copyright notice and this permission notice shall be included in all
->
+> 
 > copies or substantial portions of the Software.
->
->
->
+> 
 > THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
->
+> 
 > IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
->
+> 
 > FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
->
+> 
 > AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
->
+> 
 > LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
->
+> 
 > OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
->
+> 
 > SOFTWARE.
->
->
 
 All of this code is derived from JuliaStats/Distributions.jl

README.md

@@ -6,7 +6,7 @@
 [![codecov](https://codecov.io/gh/SciML/PoissonRandom.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/SciML/PoissonRandom.jl)
 [![Build Status](https://github.com/SciML/PoissonRandom.jl/workflows/CI/badge.svg)](https://github.com/SciML/PoissonRandom.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)
+[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor%27s%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)
 
 ## Tutorials and Documentation
@@ -27,7 +27,7 @@ pois_rand(λ)
 # Using another RNG
 using RandomNumbers
 rng = Xorshifts.Xoroshiro128Plus()
-pois_rand(rng,λ)
+pois_rand(rng, λ)
 ```
 
 ## Implementation
@@ -38,52 +38,53 @@ See [this blog post for details](https://www.johndcook.com/blog/2010/06/14/gener
 ## Benchmark
 
 ```julia
-using RandomNumbers, Distributions, BenchmarkTools, StaticArrays,
-      RecursiveArrayTools, Plots, PoissonRandom
-labels = ["count_rand","ad_rand","pois_rand","Distributions.jl"]
+using RandomNumbers,
+    Distributions, BenchmarkTools, StaticArrays,
+    RecursiveArrayTools, Plots, PoissonRandom
+labels = ["count_rand", "ad_rand", "pois_rand", "Distributions.jl"]
 rng = Xorshifts.Xoroshiro128Plus()
 
-function n_count(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += PoissonRandom.count_rand(rng,λ)
-  end
+function n_count(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += PoissonRandom.count_rand(rng, λ)
+    end
 end
 
-function n_pois(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += pois_rand(rng,λ)
-  end
+function n_pois(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += pois_rand(rng, λ)
+    end
 end
 
-function n_ad(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += PoissonRandom.ad_rand(rng,λ)
-  end
+function n_ad(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += PoissonRandom.ad_rand(rng, λ)
+    end
 end
 
-function n_dist(λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += rand(Poisson(λ))
-  end
+function n_dist(λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += rand(Poisson(λ))
+    end
 end
 
-function time_λ(rng,λ,n)
-  t1 = @elapsed n_count(rng,λ,n)
-  t2 = @elapsed n_ad(rng,λ,n)
-  t3 = @elapsed n_pois(rng,λ,n)
-  t4 = @elapsed n_dist(λ,n)
-  @SArray [t1,t2,t3,t4]
+function time_λ(rng, λ, n)
+    t1 = @elapsed n_count(rng, λ, n)
+    t2 = @elapsed n_ad(rng, λ, n)
+    t3 = @elapsed n_pois(rng, λ, n)
+    t4 = @elapsed n_dist(λ, n)
+    @SArray [t1, t2, t3, t4]
 end
 
 # Compile
-time_λ(rng,5,5000000)
+time_λ(rng, 5, 5000000)
 # Run with a bunch of λ
-times = VectorOfArray([time_λ(rng,n,5000000) for n in 1:20])'
-plot(times,labels = labels, lw = 3)
+times = VectorOfArray([time_λ(rng, n, 5000000) for n in 1:20])'
+plot(times, labels = labels, lw = 3)
 ```
 
 ![benchmark result](https://user-images.githubusercontent.com/1814174/40387004-1e377776-5dc0-11e8-88a2-2d9cb12db984.png)

docs/make.jl

@@ -6,13 +6,22 @@ cp("./docs/Project.toml", "./docs/src/assets/Project.toml", force = true)
 include("pages.jl")
 
 makedocs(sitename = "PoissonRandom.jl",
-         authors = "Chris Rackauckas",
-         modules = [PoissonRandom],
-         clean = true, doctest = false,
-         format = Documenter.HTML(analytics = "UA-90474609-3",
-                                  assets = ["assets/favicon.ico"],
-                                  canonical = "https://docs.sciml.ai/PoissonRandom/stable/"),
-         pages = pages)
+    authors = "Chris Rackauckas",
+    modules = [PoissonRandom],
+    clean = true, doctest = false, linkcheck = true,
+    strict = [
+        :doctest,
+        :linkcheck,
+        :parse_error,
+        :example_block,
+        :cross_references,
+        # Other available options are
+        # :autodocs_block, :cross_references, :docs_block, :eval_block, :example_block, :footnote, :meta_block, :missing_docs, :setup_block
+    ],
+    format = Documenter.HTML(analytics = "UA-90474609-3",
+        assets = ["assets/favicon.ico"],
+        canonical = "https://docs.sciml.ai/PoissonRandom/stable/"),
+    pages = pages)
 
 deploydocs(repo = "github.com/SciML/PoissonRandom.jl.git";
-           push_preview = true)
+    push_preview = true)

docs/src/index.md

@@ -21,7 +21,7 @@ pois_rand(λ)
 # Using another RNG
 using RandomNumbers
 rng = Xorshifts.Xoroshiro128Plus()
-pois_rand(rng,λ)
+pois_rand(rng, λ)
 ```
 
 ## Implementation
@@ -32,121 +32,143 @@ See [this blog post for details](https://www.johndcook.com/blog/2010/06/14/gener
 ## Benchmark
 
 ```julia
-using RandomNumbers, Distributions, BenchmarkTools, StaticArrays,
-      RecursiveArrayTools, Plots, PoissonRandom
-labels = ["count_rand","ad_rand","pois_rand","Distributions.jl"]
+using RandomNumbers,
+    Distributions, BenchmarkTools, StaticArrays,
+    RecursiveArrayTools, Plots, PoissonRandom
+labels = ["count_rand", "ad_rand", "pois_rand", "Distributions.jl"]
 rng = Xorshifts.Xoroshiro128Plus()
 
-function n_count(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += PoissonRandom.count_rand(rng,λ)
-  end
+function n_count(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += PoissonRandom.count_rand(rng, λ)
+    end
 end
 
-function n_pois(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += pois_rand(rng,λ)
-  end
+function n_pois(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += pois_rand(rng, λ)
+    end
 end
 
-function n_ad(rng,λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += PoissonRandom.ad_rand(rng,λ)
-  end
+function n_ad(rng, λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += PoissonRandom.ad_rand(rng, λ)
+    end
 end
 
-function n_dist(λ,n)
-  tmp = 0
-  for i in 1:n
-    tmp += rand(Poisson(λ))
-  end
+function n_dist(λ, n)
+    tmp = 0
+    for i in 1:n
+        tmp += rand(Poisson(λ))
+    end
 end
 
-function time_λ(rng,λ,n)
-  t1 = @elapsed n_count(rng,λ,n)
-  t2 = @elapsed n_ad(rng,λ,n)
-  t3 = @elapsed n_pois(rng,λ,n)
-  t4 = @elapsed n_dist(λ,n)
-  @SArray [t1,t2,t3,t4]
+function time_λ(rng, λ, n)
+    t1 = @elapsed n_count(rng, λ, n)
+    t2 = @elapsed n_ad(rng, λ, n)
+    t3 = @elapsed n_pois(rng, λ, n)
+    t4 = @elapsed n_dist(λ, n)
+    @SArray [t1, t2, t3, t4]
 end
 
 # Compile
-time_λ(rng,5,5000000)
+time_λ(rng, 5, 5000000)
 # Run with a bunch of λ
-times = VectorOfArray([time_λ(rng,n,5000000) for n in 1:20])'
-plot(times,labels = labels, lw = 3)
+times = VectorOfArray([time_λ(rng, n, 5000000) for n in 1:20])'
+plot(times, labels = labels, lw = 3)
 ```
 
 ![benchmark result](https://user-images.githubusercontent.com/1814174/40387004-1e377776-5dc0-11e8-88a2-2d9cb12db984.png)
 
 So this package ends up about 30% or so faster than Distributions.jl (the method
-at the far edge is λ-independent so that goes on forever).
+at the far edge is λ-independent, so that goes on forever).
 
 ## Contributing
 
-- Please refer to the
-  [SciML ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://github.com/SciML/ColPrac/blob/master/README.md)
-  for guidance on PRs, issues, and other matters relating to contributing to SciML.
-- There are a few community forums:
-    - the #diffeq-bridged channel in the [Julia Slack](https://julialang.org/slack/)
-    - [JuliaDiffEq](https://gitter.im/JuliaDiffEq/Lobby) on Gitter
-    - on the [Julia Discourse forums](https://discourse.julialang.org)
-    - see also [SciML Community page](https://sciml.ai/community/)
+  - Please refer to the
+    [SciML ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://github.com/SciML/ColPrac/blob/master/README.md)
+    for guidance on PRs, issues, and other matters relating to contributing to SciML.
+
+  - See the [SciML Style Guide](https://github.com/SciML/SciMLStyle) for common coding practices and other style decisions.
+  - There are a few community forums:
+
+      + The #diffeq-bridged and #sciml-bridged channels in the
+        [Julia Slack](https://julialang.org/slack/)
+      + The #diffeq-bridged and #sciml-bridged channels in the
+        [Julia Zulip](https://julialang.zulipchat.com/#narrow/stream/279055-sciml-bridged)
+      + On the [Julia Discourse forums](https://discourse.julialang.org)
+      + See also [SciML Community page](https://sciml.ai/community/)
 
 ## Reproducibility
+
 ```@raw html
 <details><summary>The documentation of this SciML package was built using these direct dependencies,</summary>
 ```
+
 ```@example
 using Pkg # hide
 Pkg.status() # hide
 ```
+
 ```@raw html
 </details>
 ```
+
 ```@raw html
 <details><summary>and using this machine and Julia version.</summary>
 ```
+
 ```@example
 using InteractiveUtils # hide
 versioninfo() # hide
 ```
+
 ```@raw html
 </details>
 ```
+
 ```@raw html
 <details><summary>A more complete overview of all dependencies and their versions is also provided.</summary>
 ```
+
 ```@example
 using Pkg # hide
-Pkg.status(;mode = PKGMODE_MANIFEST) # hide
+Pkg.status(; mode = PKGMODE_MANIFEST) # hide
 ```
+
 ```@raw html
 </details>
 ```
+
 ```@raw html
 You can also download the 
 <a href="
 ```
+
 ```@eval
 using TOML
-version = TOML.parse(read("../../Project.toml",String))["version"]
-name = TOML.parse(read("../../Project.toml",String))["name"]
-link = "https://github.com/SciML/"*name*".jl/tree/gh-pages/v"*version*"/assets/Manifest.toml"
+version = TOML.parse(read("../../Project.toml", String))["version"]
+name = TOML.parse(read("../../Project.toml", String))["name"]
+link = "https://github.com/SciML/" * name * ".jl/tree/gh-pages/v" * version *
+       "/assets/Manifest.toml"
 ```
+
 ```@raw html
 ">manifest</a> file and the
 <a href="
 ```
+
 ```@eval
 using TOML
-version = TOML.parse(read("../../Project.toml",String))["version"]
-name = TOML.parse(read("../../Project.toml",String))["name"]
-link = "https://github.com/SciML/"*name*".jl/tree/gh-pages/v"*version*"/assets/Project.toml"
+version = TOML.parse(read("../../Project.toml", String))["version"]
+name = TOML.parse(read("../../Project.toml", String))["name"]
+link = "https://github.com/SciML/" * name * ".jl/tree/gh-pages/v" * version *
+       "/assets/Project.toml"
 ```
+
 ```@raw html
 ">project</a> file.
 ```