Welcome to the documentation of pflacco#

Feature-based landscape analysis of continuous and constrained optimization problems is now available in Python as well. This package provides a Python interface to the R package flacco by Pascal Kerschke in version v0.4.0. And now also a native Python implementation with additional features such as:

The conventional features are identical or equivalent to the implementation of the R-package flacco. To directly quote the documentation of flacco: .. epigraph:

flacco is a collection of features for Explorative Landscape Analysis (ELA) of single-objective, continuous (Black-Box-)Optimization Problems.
It allows the user to quantify characteristics of an (unknown) optimization problem's landscape.
Features, which used to be spread over different packages and platforms (R, Matlab, Python, etc.), are now combined within this single package.
Amongst others, this package contains feature sets, such as ELA, Information Content, Dispersion, (General) Cell Mapping or Barrier Trees.
Furthermore, the package provides a unified interface for all features -- using a so-called feature object and (if required) control arguments.
In total, the current release (1.7) consists of 17 different feature sets, which sum up to approximately 300 features.
In addition to the features themselves, this package also provides visualizations, e.g. of the cell mappings, barrier trees or information content
The calculation procedure and further background information of ELA features is given in
Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems Using the R-Package flacco.

Contents#

Indices and tables#