Metadata-Version: 2.4
Name: hipersim
Version: 0.1.14
Summary: A collection of wind energy simulation tools
Author-email: Nikolay Dimitrov <nkdi@dtu.dk>
Project-URL: Homepage, https://gitlab.windenergy.dtu.dk/HiperSim/hipersim
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: xarray
Requires-Dist: netcdf4
Requires-Dist: h5netcdf
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: matplotlib
Requires-Dist: wetb
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Requires-Dist: python-docs-theme; extra == "docs"
Requires-Dist: numpydoc; extra == "docs"
Requires-Dist: nbsphinx; extra == "docs"
Requires-Dist: sphinx_copybutton; extra == "docs"
Requires-Dist: sphinx_sitemap; extra == "docs"
Requires-Dist: ipympl; extra == "docs"
Requires-Dist: ipykernel; extra == "docs"
Provides-Extra: tests
Requires-Dist: h2lib; extra == "tests"

# Hipersim

## Introduction
Hipersim is a collection of tools for computationally-efficient simulation of Wind Energy problems using statistical and machine learning methods. Currently, the package contains the following submodules:

- **turbgen**: 
    - Generation of 3D frozen turbulence fields ("turbulence boxes") with the Mann turbulence spectrum
    - Constrained turbulence field generation and application of constraints on pre-generated turbulence fields

- **surrogates**:
    - A feedforward neural network toolbox, training and evaluation of feedforward neural networks. 
	- A set of tools for surrogate-based modeling and analysis of wind farms

## How to cite
If you use this code for academic research, you are encouraged to cite our paper:
### Text format:
Nikolay Dimitrov and Mads Pedersen and Ásta Hannesdóttir
An open-source Python-based tool for Mann turbulence generation with constraints and non-Gaussian capabilities,
The Science of Making Torque from Wind (TORQUE 2024): Modeling and simulation technology,
Journal of Physics: Conference Series 5,
IOP Publishing,
2024,
DOI: 10.1088/1742-6596/2767/5/052058

### BibTeX format:
```
@inproceedings{Dimitrov2024,
title = "An open-source Python-based tool for Mann turbulence generation with constraints and non-Gaussian capabilities",
author = "Nikolay Dimitrov and Mads Pedersen and {\'A}sta Hannesd{\'o}ttir",
year = "2024",
doi = "10.1088/1742-6596/2767/5/052058",
language = "English",
series = "Journal of Physics: Conference Series",
publisher = "IOP Publishing",
number = "5",
booktitle = "The Science of Making Torque from Wind (TORQUE 2024): Modeling and simulation technology",
address = "United Kingdom",
note = Conference date: 29-05-2024 Through 31-05-2024",
}
```

## Links

- [Online documentation of new interface](https://hipersim.pages.windenergy.dtu.dk/hipersim/)
- [Manual describing old interface + theory references]( https://gitlab.windenergy.dtu.dk/HiperSim/hipersim/-/blob/master/doc/Turbgen_Manual_0.0.24.pdf?ref_type=heads)
- [MIT License](https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake/blob/master/LICENSE)

