The MDAF (Multi-Disciplinary Analysis Framework) repository provides a collection of tools and functions for performing multi-disciplinary analysis, optimization, and surrogate modeling.

Installation

To install the MDAF package, use the following command:

pip install git+fullurl

Dependencies

The MDAF package depends on the following libraries:

rpy2
scikit-learn
numpy
matplotlib

Usage

The MDAF package provides several functions and tools for performing multi-disciplinary analysis, optimization, and surrogate modeling. Some examples include:

installFlacco: Installs the Flacco package and its dependencies.
representfunc: Represents test functions for analysis and optimization.
doe: Performs design of experiments (DOE) for surrogate modeling.

Test Functions

The MDAF package includes a collection of test functions for analysis and optimization, including:

Alpine.py
Bukin4.py
Bukin6.py
Keane.py
Leon.py
Miele_Cantrell.py
Rastriring.py
Step.py
Step2.py
Wayburn.py
Zettle.py
Zirilli.py

Notebooks

The repository includes several Jupyter notebooks that demonstrate the usage of the MDAF package, including:

Analyse_folders_and_description.ipynb
PSO.ipynb
Simulated_Annealing_General.ipynb

Tests

The repository includes a collection of unit tests and integration tests to ensure the correctness of the MDAF package.

Misc

reinstall the package for testing:

py -m pip install --upgrade --force-reinstall git+fullurl

use specific versions: python 37
dependencies: rpy2, scikitlearn,
Windows: install R first
- When using installFlacco please choose to create a new library on the first run