JuliaIntervals · yashvardhan747 · Jun 4, 2019 · Jun 4, 2019 · Jun 4, 2019 · Jun 6, 2019
diff --git a/.DS_Store b/.DS_Store
diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,8 @@
 # NEWS for IntervalOptimisation.jl
 
+## v0.4
+- Drop support for Julia 0.7  
+
 ## v0.3
 - Drop support for Julia 0.6. The package is now fully compatible with Julia 1.0.
 

diff --git a/Project.toml b/Project.toml
@@ -0,0 +1,24 @@
+name = "IntervalOptimisation"
+uuid = "c7c68f13-a4a2-5b9a-b424-07d005f8d9d2"
+version = "0.4.0" 
+
+[compat]
+DataStructures = "≥ 0.9.0"
+ForwardDiff = "≥ 0.8.0"
+IntervalArithmetic = "≥ 0.15.0"
+IntervalConstraintProgramming = "≥ 0.9.0"
+IntervalRootFinding = "≥ 0.4.0"
+julia = "≥ 1.0.0"
+
+[deps]
+DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+IntervalArithmetic = "d1acc4aa-44c8-5952-acd4-ba5d80a2a253"
+IntervalConstraintProgramming = "138f1668-1576-5ad7-91b9-7425abbf3153"
+IntervalRootFinding = "d2bf35a9-74e0-55ec-b149-d360ff49b807"
+
+[extras]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["Test"]
diff --git a/README.md b/README.md
@@ -4,8 +4,6 @@
 [![appveyor badge][appveyor_badge]][appveyor_url]
 [![codecov badge][codecov_badge]][codecov_url]
 
-## Documentation [here][documenter_latest]
-
 [travis_badge]: https://travis-ci.org/JuliaIntervals/IntervalOptimisation.jl.svg?branch=master
 [travis_url]: https://travis-ci.org/JuliaIntervals/IntervalOptimisation.jl
 
@@ -16,7 +14,6 @@
 [codecov_url]: http://codecov.io/github/JuliaIntervals/IntervalOptimisation.jl?branch=master
 
 [documenter_stable]: https://JuliaIntervals.github.io/IntervalOptimisation.jl/stable
-[documenter_latest]: https://JuliaIntervals.github.io/IntervalOptimisation.jl/latest
 
 
 ## Rigorous global optimisation using Julia
@@ -25,59 +22,9 @@ This package provides rigorous global optimisation routines written in pure Juli
 
 Currently, the package uses an implementation of the Moore-Skelboe algorithm.
 
-## Usage  
-
-Functions `minimise` and `maximise` are provided to find the **global** minimum or maximum, respectively, of a standard Julia function `f` of one or several variables.
-
-They return an `Interval` that is guaranteed to contain the global minimum (maximum), and a `Vector` of `Interval`s or `IntervalBox`es whose union contains all the minimisers.
-
-### Examples
-
-
-#### 1D
-```
-using IntervalArithmetic, IntervalOptimisation
-
-julia> @time global_min, minimisers = minimise(x -> (x^2 - 2)^2, -10..11);
-  0.046620 seconds (36.07 k allocations: 1.586 MiB)
-
-julia> global_min
-[0, 1.50881e-09]
-
-julia> minimisers
-2-element Array{IntervalArithmetic.Interval{Float64},1}:
-  [1.41387, 1.41453]
- [-1.41428, -1.41363]
-```
-
-#### 2D
-
-```
-julia> @time global_min, minimisers = minimise(  X -> ( (x,y) = X; x^2 + y^2 ),
-                                                        (-10000..10001) × (-10000..10001) );
-  0.051122 seconds (46.80 k allocations: 2.027 MiB)
-
-julia> global_min
-[0, 2.33167e-08]
-
-julia> minimisers
-3-element Array{IntervalArithmetic.IntervalBox{2,Float64},1}:
- [-0.000107974, 0.000488103] × [-0.000107974, 0.000488103]
- [-0.000107974, 0.000488103] × [-0.000704051, -0.000107973]
- [-0.000704051, -0.000107973] × [-0.000107974, 0.000488103]
-```
-Note that the last two `IntervalBox`es do not actually contain the global minimum;
-decreasing the tolerance (maximum allowed box diameter) removes them:
-
-```
-julia> @time global_min, minimisers = minimise(  X -> ( (x,y) = X; x^2 + y^2 ),
-                                                               (-10000..10001) × (-10000..10001), 1e-5 );
-  0.047196 seconds (50.72 k allocations: 2.180 MiB)
+## Documentation
+Documentation of this package is available [here](https://JuliaIntervals.github.io/IntervalOptimisation.jl/latest/)
 
-julia> minimisers
-1-element Array{IntervalArithmetic.IntervalBox{2,Float64},1}:
- [-5.52321e-06, 3.79049e-06] × [-5.52321e-06, 3.79049e-06]
- ```
 
 ## Author
 

diff --git a/REQUIRE b/REQUIRE
diff --git a/docs/.DS_Store b/docs/.DS_Store
diff --git a/docs/.gitignore b/docs/.gitignore
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -0,0 +1,6 @@
+name = "docs"
+uuid = "6854bdac-4683-567a-be4f-b22094e82ce7"
+
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+IntervalOptimisation = "c7c68f13-a4a2-5b9a-b424-07d005f8d9d2"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,20 +1,16 @@
-import Documenter
+using Documenter, IntervalOptimisation
 
-Documenter.makedocs(
+makedocs(
     modules = [IntervalOptimisation],
-    format = :html,
+    format = Documenter.HTML(),
     sitename = "IntervalOptimisation.jl",
-    root = joinpath(dirname(dirname(@__FILE__)), "docs"),
-    pages = Any["Home" => "index.md"],
-    strict = true,
-    linkcheck = true,
-    checkdocs = :exports,
+    pages = ["Home" => "index.md"],
     authors = "David Sanders"
 )
 
 
 Documenter.deploydocs(
-    repo = "github.com/dpsanders/IntervalOptimisation.jl.git",
+    repo = "github.com/JuliaIntervals/IntervalOptimisation.jl.git",
     target = "build",
     deps = nothing,
     make = nothing

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -1,8 +1,80 @@
-# IntervalOptimisation.jl
+# `IntervalOptimisation.jl`
 
-```@index
+## Rigorous global optimisation using Julia
+
+This package provides rigorous global optimisation routines written in pure Julia, using interval arithmetic provided by the author's [IntervalArithmetic.jl](https://github.com/JuliaIntervals/IntervalArithmetic.jl) package.
+
+Currently, the package uses an implementation of the Moore-Skelboe algorithm.
+
+## Usage  
+
+Functions `minimise` and `maximise` are provided to find the **global** minimum or maximum, respectively, of a standard Julia function `f` of one or several variables.
+
+They return an `Interval` that is guaranteed to contain the global minimum (maximum), and a `Vector` of `Interval`s or `IntervalBox`es whose union contains all the minimisers.
+
+### Examples
+
+
+#### 1D
+```
+using IntervalArithmetic, IntervalOptimisation
+
+julia> @time global_min, minimisers = minimise(x -> (x^2 - 2)^2, -10..11);
+  0.046620 seconds (36.07 k allocations: 1.586 MiB)
+
+julia> global_min
+[0, 1.50881e-09]
+
+julia> minimisers
+2-element Array{IntervalArithmetic.Interval{Float64},1}:
+  [1.41387, 1.41453]
+ [-1.41428, -1.41363]
+```
+
+#### 2D
+
+```
+julia> @time global_min, minimisers = minimise(  X -> ( (x,y) = X; x^2 + y^2 ),
+                                                        (-10000..10001) × (-10000..10001) );
+  0.051122 seconds (46.80 k allocations: 2.027 MiB)
+
+julia> global_min
+[0, 2.33167e-08]
+
+julia> minimisers
+3-element Array{IntervalArithmetic.IntervalBox{2,Float64},1}:
+ [-0.000107974, 0.000488103] × [-0.000107974, 0.000488103]
+ [-0.000107974, 0.000488103] × [-0.000704051, -0.000107973]
+ [-0.000704051, -0.000107973] × [-0.000107974, 0.000488103]
 ```
+Note that the last two `IntervalBox`es do not actually contain the global minimum;
+decreasing the tolerance (maximum allowed box diameter) removes them:
 
-```@autodocs
-Modules = [IntervalOptimisation]
 ```
+julia> @time global_min, minimisers = minimise(  X -> ( (x,y) = X; x^2 + y^2 ),
+                                                               (-10000..10001) × (-10000..10001), 1e-5 );
+  0.047196 seconds (50.72 k allocations: 2.180 MiB)
+
+julia> minimisers
+1-element Array{IntervalArithmetic.IntervalBox{2,Float64},1}:
+ [-5.52321e-06, 3.79049e-06] × [-5.52321e-06, 3.79049e-06]
+ ```
+
+## Author
+
+- [David P. Sanders](http://sistemas.fciencias.unam.mx/~dsanders),
+Departamento de Física, Facultad de Ciencias, Universidad Nacional Autónoma de México (UNAM)
+
+
+## References:
+
+- *Validated Numerics: A Short Introduction to Rigorous Computations*, W. Tucker, Princeton University Press (2010)
+
+- *Applied Interval Analysis*, Luc Jaulin, Michel Kieffer, Olivier Didrit, Eric Walter (2001)
+
+- van Emden M.H., Moa B. (2004). Termination Criteria in the Moore-Skelboe Algorithm for Global Optimization by Interval Arithmetic. In: Floudas C.A., Pardalos P. (eds), *Frontiers in Global Optimization. Nonconvex Optimization and Its Applications*, vol. 74. Springer, Boston, MA. [Preprint](http://webhome.cs.uvic.ca/~vanemden/Publications/mooreSkelb.pdf)
+
+- H. Ratschek and J. Rokne, [*New Computer Methods for Global Optimization*](http://pages.cpsc.ucalgary.ca/~rokne/global_book.pdf)
+
+## Acknowledements
+Financial support is acknowledged from DGAPA-UNAM PAPIIT grant IN-117117.