Update README.md for JuMP documentation (#260)

README.md

@@ -1,54 +1,67 @@
-![Logo](logo-full.svg)
----
+<img src="https://github.com/MadNLP/MadNLP.jl/blob/master/logo-full.svg?raw=true"/>
+
 | **Documentation** | **Build Status** | **Coverage** | **DOI** |
 |:-----------------:|:----------------:|:----------------:|:----------------:|
 | [![doc](https://img.shields.io/badge/docs-dev-blue.svg)](https://madnlp.github.io/MadNLP.jl/dev) | [![build](https://github.com/MadNLP/MadNLP.jl/workflows/build/badge.svg?branch=dev%2Fgithub_actions)](https://github.com/MadNLP/MadNLP.jl/actions?query=workflow%3Abuild) | [![codecov](https://codecov.io/gh/MadNLP/MadNLP.jl/branch/master/graph/badge.svg?token=MBxH2AAu8Z)](https://codecov.io/gh/MadNLP/MadNLP.jl) | [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5825776.svg)](https://doi.org/10.5281/zenodo.5825776) |
 
 MadNLP is a [nonlinear programming](https://en.wikipedia.org/wiki/Nonlinear_programming) (NLP) solver, purely implemented in [Julia](https://julialang.org/). MadNLP implements a filter line-search algorithm, as that used in [Ipopt](https://github.com/coin-or/Ipopt). MadNLP seeks to streamline the development of modeling and algorithmic paradigms in order to exploit structures and to make efficient use of high-performance computers.
 
+## License
+
+MadNLP is available under the [MIT license](https://github.com/MadNLP/MadNLP.jl/blob/master/LICENSE).
+
 ## Installation
+
 ```julia
 pkg> add MadNLP
 ```
+
 Optionally, various extension packages can be installed together:
 ```julia
 pkg> add MadNLPHSL, MadNLPPardiso, MadNLPMumps, MadNLPGPU, MadNLPGraph, MadNLPKrylov
 ```
-These packages are stored in the `lib` subdirectory within the main MadNLP repository. Some extension packages may require additional dependencies or specific hardware. For the instructions for the build procedure, see the following links: [MadNLPHSL](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPHSL), [MadNLPPardiso](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPHSL), [MadNLPGPU](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPGPU).
 
+These packages are stored in the `lib` subdirectory within the main MadNLP repository. Some extension packages may require additional dependencies or specific hardware. For the instructions for the build procedure, see the following links:
+
+ * [MadNLPHSL](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPHSL)
+ * [MadNLPPardiso](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPHSL)
+ * [MadNLPGPU](https://github.com/MadNLP/MadNLP.jl/tree/master/lib/MadNLPGPU)
 
 ## Usage
+
 ### Interfaces
+
 MadNLP is interfaced with modeling packages:
+
 - [JuMP](https://github.com/jump-dev/JuMP.jl)
 - [Plasmo](https://github.com/zavalab/Plasmo.jl)
 - [NLPModels](https://github.com/JuliaSmoothOptimizers/NLPModels.jl).
-Users can pass various options to MadNLP also through the modeling packages. The interface-specific syntaxes are shown below. To see the list of MadNLP solver options, check the [OPTIONS.md](https://github.com/MadNLP/MadNLP/blob/master/OPTIONS.md) file.
+
+Users can pass various options to MadNLP also through the modeling packages. The interface-specific syntax are shown below. To see the list of MadNLP solver options, check the [OPTIONS.md](https://github.com/MadNLP/MadNLP/blob/master/OPTIONS.md) file.
 
 #### JuMP interface
+
 ```julia
 using MadNLP, JuMP
-
 model = Model(()->MadNLP.Optimizer(print_level=MadNLP.INFO, max_iter=100))
 @variable(model, x, start = 0.0)
 @variable(model, y, start = 0.0)
 @NLobjective(model, Min, (1 - x)^2 + 100 * (y - x^2)^2)
-
 optimize!(model)
-
 ```
 
 #### NLPModels interface
+
 ```julia
 using MadNLP, CUTEst
 model = CUTEstModel("PRIMALC1")
 madnlp(model, print_level=MadNLP.WARN, max_wall_time=3600)
 ```
 
 #### Plasmo interface (requires extension `MadNLPGraph`)
+
 ```julia
 using MadNLP, MadNLPGraph, Plasmo
-
 graph = OptiGraph()
 @optinode(graph,n1)
 @optinode(graph,n2)
@@ -59,12 +72,11 @@ graph = OptiGraph()
 @variable(n2,x)
 @NLnodeconstraint(n2,exp(x) >= 2)
 @linkconstraint(graph,n1[:x] == n2[:x])
-
 MadNLP.optimize!(graph; print_level=MadNLP.DEBUG, max_iter=100)
-
 ```
 
 ### Linear Solvers
+
 MadNLP is interfaced with non-Julia sparse/dense linear solvers:
 - [Umfpack](https://people.engr.tamu.edu/davis/suitesparse.html)
 - [MKL-Pardiso](https://software.intel.com/content/www/us/en/develop/documentation/mkl-developer-reference-fortran/top/sparse-solver-routines/intel-mkl-pardiso-parallel-direct-sparse-solver-interface.html)
@@ -77,6 +89,7 @@ MadNLP is interfaced with non-Julia sparse/dense linear solvers:
 Each linear solver in MadNLP is a Julia type, and the `linear_solver` option should be specified by the actual type. Note that the linear solvers are always exported to `Main`.
 
 #### Built-in Solvers: Umfpack, PardisoMKL, LapackCPU
+
 ```julia
 using MadNLP, JuMP
 # ...
@@ -85,6 +98,7 @@ model = Model(()->MadNLP.Optimizer(linear_solver=LapackCPUSolver))
 ```
 
 #### HSL (requires extension `MadNLPHSL`)
+
 ```julia
 using MadNLP, MadNLPHSL, JuMP
 # ...
@@ -96,13 +110,15 @@ model = Model(()->MadNLP.Optimizer(linear_solver=Ma97Solver))
 ```
 
 #### Mumps (requires extension `MadNLPMumps`)
+
 ```julia
 using MadNLP, MadNLPMumps, JuMP
 # ...
 model = Model(()->MadNLP.Optimizer(linear_solver=MumpsSolver))
 ```
 
 #### Pardiso (requires extension `MadNLPPardiso`)
+
 ```julia
 using MadNLP, MadNLPPardiso, JuMP
 # ...
@@ -111,14 +127,15 @@ model = Model(()->MadNLP.Optimizer(linear_solver=PardisoMKLSolver))
 ```
 
 #### LapackGPU (requires extension `MadNLPGPU`)
+
 ```julia
 using MadNLP, MadNLPGPU, JuMP
 # ...
 model = Model(()->MadNLP.Optimizer(linear_solver=LapackGPUSolver))
 ```
 
-
 #### Schur and Schwarz (requires extension `MadNLPGraph`)
+
 ```julia
 using MadNLP, MadNLPGraph, JuMP
 # ...
@@ -131,7 +148,9 @@ julia -t 16 # to use 16 threads
 ```
 
 ## Citing MadNLP.jl
+
 If you use MadNLP.jl in your research, we would greatly appreciate your citing it.
+
 ```bibtex
 @article{shin2020graph,
   title={Graph-Based Modeling and Decomposition of Energy Infrastructures},
@@ -142,4 +161,5 @@ If you use MadNLP.jl in your research, we would greatly appreciate your citing i
 ```
 
 ## Bug reports and support
-Please report issues and feature requests via the [Github issue tracker](https://github.com/MadNLP/MadNLP.jl/issues).
+
+Please report issues and feature requests via the [GitHub issue tracker](https://github.com/MadNLP/MadNLP.jl/issues).