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Interface for NOMAD 4.4.0 blackbox optimization software.

Project description

NOMADLAD provides Python interface to the blackbox optimization software 
NOMAD (version 4) available from https://github.com/bbopt/nomad repository.

Installation

Starting with the release 1.0.0, the latest version of the package is
available from PyPi repository.

pip install nomadlad

Acknowledgements

This package is an alternative to the PyNomadBBO package interfacing the
blackbox optimization software NOMAD.


Building (Prerequisites)

- Python 3 (tested with version 3.12.4)
- Compiled NOMAD with static libraries (tested with version 4.4.0)
- GCC release that supports at least C++17 (tested with version 14.1.1)
- Exported the NOMAD_PATH environment variable

Building (A minimal build of NOMAD)

This is a considerably condensed version of the official installation guide
adapted to the purpose of manually building this module.

(Step 1) Download and extract the v4.4.0 release of NOMAD somewhere.

wget https://github.com/bbopt/nomad/archive/refs/tags/v.4.4.0.tar.gz
tar -zxf v.4.4.0.tar.gz

(Step 2) Enter the nomad-v.4.4.0 directory

cd nomad-v.4.4.0

(Step 3) Export path to the current directory (needed for the final step)

export NOMAD_PATH=$(pwd)

(Step 3) Prepare and build the core NOMAD library.

cmake -S . -B build \
-DBUILD_INTERFACE_PYTHON=ON \
-DBUILD_EXAMPLES=OFF \
-DTEST_OPENMP=OFF

cmake --build build --config Release --clean-first --target nomadStatic --parallel

Please note that you can set --parallel to the number of cores available.

(Step 5) Compile nomadlad module.

Please note that NOMAD_PATH must be exported for this to work.

(Option A) Install directly from a tagged commit

pip install --user --upgrade \
git+https://github.com/jan-provaznik/nomadlad.git@v1.0.0

(Option B) Build from a locally cloned repository. Enter the repository first.

python -m pip wheel -w dist -- .

(Step 6) Profit.

Documentation

The documentation is left as an exercise to the reader. See help(nomadlad).

The package exports the nomadlad.minimize procedure.
The examples provided with the package are intended to serve as a tutorial.

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