This post will tell you how to install CUTEst using a different tool that makes it much easier. Also, I’ll install CUTEst.jl, the CUTEst interface for Julia.
Edit: Now, CUTEst.jl install CUTEst by itself. Check this post. Also, for Linux, I’ve created this CUTEst installer, which should be easier to use. February, 11, 2017.
Edit: Some corrections were made on February, 15, 2016.
Edit: Some corrections were made on November, 11, 2015.
By now you probably know CUTEst, the repository for testing and comparing nonlinear programming algorithms. It’s widely used in the community for some time (considering CUTE and CUTEr, the previous versions). If not, this is a good change to test it, using Julia to play around. This is a not a post to convince you to use Julia, but I have to say that it is much easier to use CUTEst on Julia than on MatLab. So, if you are starting on it, I suggest you take a look.
We will use Homebrew to install CUTEst, for two reasons:
- It’s much easier (when you learn it)
- Julia requires shared libraries, that the original installation did not provide.
Homebrew is a kind of package manager (such as apt-get, pip, etc.). For linux, there are many things that we don’t need from Homebrew, because you normally already have a package manager. However, Homebrew is widely used by OSX users, so it has a lot of packages. The linux version is Linuxbrew.
The installation is quite simple:
- Install brew
- Install CUTEst
- Install CUTEst.jl
I just made these steps and record my terminal, so you can check Asciinema, or the embedded version on the bottom of the page. Be warned, though, that I was “cold running” them, so some parts are very slow.
To install brew, I recommend you check the page. For the impatient,
ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/linuxbrew/go/install)"
echo 'export PATH="$HOME/.linuxbrew/bin:$PATH"' >> $HOME/.bashrc
source $HOME/.bashrc
sudo apt-get install build-essential subversion
brew doctor
To install CUTEst, read the tap cutest. Again, for the impatient
brew tap optimizers/cutest
brew install cutest
brew install mastsif
for f in archdefs mastsif sifdecode cutest; do \
echo "source $(brew --prefix $f)/$f.bashrc" >> \
$HOME/.bashrc; \
done
echo 'export LD_LIBRARY_PATH="$HOME/.linuxbrew/lib:$LD_LIBRARY_PATH"' >> $HOME/.bashrc
source $HOME/.bashrc
This should get CUTEst installed.
Notice the LD_LIBRARY_PATH variable, which points to where the CUTEst library
will be.
Test it with
brew test sifdecode
brew test cutest
That’s it. You have CUTEst installed to use with Fortran or C. A can’t provide a simple example, because they aren’t simple (enough). I’ll now go to Julia, and I recommend you try it.
To install Julia, go to their page, then downloads, then download the static version of the stable release (or do what you want, I’m not your boss). Then, in julia, to install CUTEst.jl, issue the commands
Pkg.clone("https://github.com/abelsiqueira/CUTEst.jl")
Pkg.checkout("CUTEst", "fix/issue4")
If nothing goes wrong, then you can play around. For instance, to open problem HS32 and get the objective function value at point (2,3), we do
using CUTEst
nlp = CUTEstModel("HS32")
f = obj(nlp, [2.0;3.0])
If you’re familiar with CUTEst, you can use the classic functions cfn and
ufn too, in the default way (as called from C) or a more Julian way.
This would become too long to explain now, so I’ll make a post in a few days (or
months).
If you need it, please contact me.
This concludes the new installation of CUTEst.
Warning: Due to current limitations we cannot open two problems at the same time in CUTEst without the possibility of a segmentation fault. So, if you need to run cutest for a list of problems, I suggest you use a bash script to loop over each problem and call your Julia code passing the problem as an input argument.
Ths embedded Asciinema video is below.