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% Readme file explaining the data
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% This directory contains the relevant data published to accompany the
% publication "Extending Horsetail Matching for Optimization Under
% Probabilistic, Interval and Mixed Uncertainties" in AIAA Journal.

% The funding source of this work, the UK Engineering and Physical Sciences
% Research Council (EPSRC), gives Open Access requirements such that the data
% supporting the publication is made available.

% The data provided here is intended to be sufficient for recreation of the
% results in the publication. The results in the publication arose from
% performing horsetail matching optimizations on various test problems.
% This data is therefore the python module that implements the horsetail
% matching method, and thus can perform the optimizations detailed in the
% publication to recreate the results.

% The test cases whose results are presented in the publication make
% use of third party software that is openly available and so is not
% archived here. The non-linear optimization toolbox NLopt is available from
% http://ab-initio.mit.edu/wiki/index.php/NLopt. The low fidelity wing design
% problem, uses code available from: https://github.com/mdolab/OpenAeroStruct.
% The 3D wing design problem uses the open source CFD software SU2, which is
% available from su2.stanford.edu.

% The publication contains sufficient information such that the results can
% be recreated using the python package stored here by anyone with access to
% this third party software.

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% Requirements
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% The code is written in python (v2.7.6).
% Additionally it uses numpy (v1.12.1)

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% User Guide
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% The python package contains extensive documentatoion and examples.

% For installation guidelines refer to the README.md file within the package.

% The "examples" folder contains comprehensive usage examples of the package.
% Instructions related to these examples are provided in the "notebooks"
% folder in the form of Jupyter notebooks.