Metadata-Version: 1.1
Name: ezyrb
Version: 0.2
Summary: Easy Reduced Basis method
Home-page: https://github.com/mathLab/EZyRB
Author: Nicola Demo, Marco Tezzele
Author-email: demo.nicola@gmail.com, marcotez@gmail.com
License: MIT
Description: <p align="center">
          <a href="http://github.com/mathLab/PyDMD/" target="_blank" >
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        </p>
        <p align="center">
            <a href=" https://doi.org/10.21105/joss.00661" target="_blank">
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        **EZyRB**: Easy Reduced Basis method
        
        ## Table of contents
        * [Description](#description)
        * [Dependencies and installation](#dependencies-and-installation)
        * [Documentation](#documentation)
        * [Testing](#testing)
        * [Examples](#examples)
        * [How to cite](#how-to-cite)
        	* [Recent works with EZyRB](#recent-works-with-ezyrb)
        * [Authors and contributors](#authors-and-contributors)
        * [How to contribute](#how-to-contribute)
        	* [Submitting a patch](#submitting-a-patch) 
        * [License](#license)
        
        ## Description
        **EZyRB** is a python library for the Model Order Reduction based on **baricentric triangulation** for the selection of the parameter points and on **Proper Orthogonal Decomposition** for the selection of the modes. It is ideally suited for actual industrial problems, since its structure can interact with several simulation software simply providing the output file of the simulations. Up to now, it handles files in the vtk and mat formats. It has been used for the model order reduction of problems solved with matlab and openFOAM.
        
        See the [**Examples**](#examples) section below and the [**Tutorials**](tutorials/README.md) to have an idea of the potential of this package.
        
        ## Dependencies and installation
        **EZyRB** requires `numpy`, `scipy`, `matplotlib`, `vtk`, `nose` (for local
                test) and `sphinx` (to generate the documentation). They can be easily
        installed via `pip`. The code is compatible with Python 2.7.
        
        The official distribution is on GitHub, and you can clone the repository using
        
        ```bash
        > git clone https://github.com/mathLab/EZyRB
        ```
        
        To install the package just type:
        
        ```bash
        > python setup.py install
        ```
        
        To uninstall the package you have to rerun the installation and record the installed files in order to remove them:
        
        ```bash
        > python setup.py install --record installed_files.txt
        > cat installed_files.txt | xargs rm -rf
        ```
        
        
        ## Documentation
        **EZyRB** uses [Sphinx](http://www.sphinx-doc.org/en/stable/) for code documentation. To build the html versions of the docs simply:
        
        ```bash
        > cd docs
        > make html
        ```
        
        The generated html can be found in `docs/build/html`. Open up the `index.html` you find there to browse.
        
        
        ## Testing
        We are using Travis CI for continuous intergration testing. You can check out the current status [here](https://travis-ci.org/mathLab/EZyRB).
        
        To run tests locally:
        
        ```bash
        > python test.py
        ```
        
        
        
        ## Examples
        
        You can find useful tutorials on how to use the package in the [tutorials](tutorials/README.md) folder.
        Here we show an application taken from the **automotive** engineering field
        
        <p align="center">
        <img src="readme/pod_modes.png" alt>
        </p>
        <p align="center">
        <em>The first POD modes of the pressure field on the DrivAer model.</em>
        </p>
        
        <p align="center">
        <img src="readme/errors.png" alt>
        </p>
        <p align="center">
        <em>DrivAer model online evaluation: pressure (left) and wall shear stress (right) fields and errors.</em>
        </p>
        
        
        ## How to cite
        If you use this package in your publications please cite the package as follows:
        
        Demo et al., (2018). EZyRB: Easy Reduced Basis method. Journal of Open Source Software, 3(24), 661, [https://doi.org/10.21105/joss.00661](https://doi.org/10.21105/joss.00661)
        
        Or if you use LaTeX:
        
        ```tex
        @article{demo18ezyrb,
          Author = {Demo, Nicola and Tezzele, Marco and Rozza, Gianluigi},
          Title = {{EZyRB: Easy Reduced Basis method}},
          Journal = {The Journal of Open Source Software},
          Volume = {3},
          Number = {24},
          Pages = {661},
          Year = {2018},
          Doi = {https://doi.org/10.21105/joss.00661}
        }
        ```
        
        ### Recent works with EZyRB
        Here there is a list of the scientific works involving **EZyRB** you can consult and/or cite. If you want to add one, please open a PR.
        
        * Salmoiraghi, Scardigli, Telib, Rozza. *Free Form Deformation, mesh morphing and reduced order methods: enablers for efficient aerodynamic shape optimization*. 2018. [[arXiv](https://arxiv.org/abs/1803.04688)].
        
        * Demo, Tezzele, Gustin, Lavini, Rozza. *Shape Optimization by means of Proper Orthogonal Decomposition and Dynamic Mode Decomposition*. 2018. [[arXiv](https://arxiv.org/abs/1803.07368)].
        
        
        ## Authors and contributors
        **EZyRB** is currently developed and mantained at [SISSA mathLab](http://mathlab.sissa.it/) by
        * [Nicola Demo](mailto:demo.nicola@gmail.com)
        * [Marco Tezzele](mailto:marcotez@gmail.com)
        
        under the supervision of [Prof. Gianluigi Rozza](mailto:gianluigi.rozza@sissa.it). We thank [Filippo Salmoiraghi](mailto:filippo.salmoiraghi@gmail.com) for the original idea behind this package and the major contributions.
        
        Contact us by email for further information or questions about **EZyRB**, or suggest pull requests. **EZyRB** is at an early development stage, so contributions improving either the code or the documentation are welcome!
        
        
        ## How to contribute
        We'd love to accept your patches and contributions to this project. There are
        just a few small guidelines you need to follow.
        
        ### Submitting a patch
        
          1. It's generally best to start by opening a new issue describing the bug or
             feature you're intending to fix.  Even if you think it's relatively minor,
             it's helpful to know what people are working on.  Mention in the initial
             issue that you are planning to work on that bug or feature so that it can
             be assigned to you.
        
          2. Follow the normal process of [forking][] the project, and setup a new
             branch to work in.  It's important that each group of changes be done in
             separate branches in order to ensure that a pull request only includes the
             commits related to that bug or feature.
        
          3. To ensure properly formatted code, please make sure to use 4
             spaces to indent the code. The easy way is to run on your bash the provided
             script: ./code_formatter.sh. You should also run [pylint][] over your code.
             It's not strictly necessary that your code be completely "lint-free",
             but this will help you find common style issues.
        
          4. Any significant changes should almost always be accompanied by tests.  The
             project already has good test coverage, so look at some of the existing
             tests if you're unsure how to go about it. We're using [coveralls][] that
             is an invaluable tools for seeing which parts of your code aren't being
             exercised by your tests.
        
          5. Do your best to have [well-formed commit messages][] for each change.
             This provides consistency throughout the project, and ensures that commit
             messages are able to be formatted properly by various git tools.
        
          6. Finally, push the commits to your fork and submit a [pull request][]. Please,
             remember to rebase properly in order to maintain a clean, linear git history.
        
        [forking]: https://help.github.com/articles/fork-a-repo
        [pylint]: https://www.pylint.org/
        [coveralls]: https://coveralls.io
        [well-formed commit messages]: http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html
        [pull request]: https://help.github.com/articles/creating-a-pull-request
        
        
        ## License
        
        See the [LICENSE](LICENSE.rst) file for license rights and limitations (MIT).
        
Keywords: dimension_reduction mathematics vtk pod podi
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
