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            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
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        "description": "[![Build Status](https://travis-ci.org/qiqi/fds.svg?branch=master)](https://travis-ci.org/qiqi/fds?branch=master)\n[![Coverage Status](https://coveralls.io/repos/github/qiqi/fds/badge.svg?branch=master)](https://coveralls.io/github/qiqi/fds?branch=master)\n[![Dependency Status](https://dependencyci.com/github/qiqi/fds/badge)](https://dependencyci.com/github/qiqi/fds)\n[![Documentation Status](https://readthedocs.org/projects/fds/badge/?version=latest)](http://fds.readthedocs.io/en/latest/?badge=latest)\n[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)\n\n# What's it for\n\nfds is a research tool for computational simulations that exhibis\nchaotic dynamics. It computes sensitivity derivatives of time averaged\nquantities, a.k.a. statistics, with respect simulation parameters.\n\nFor an introduction of chaotic dynamics, I highly recommend [Strogatz's\nexcellent book](https://www.amazon.com/gp/product/0813349109). For a\nstatistical view of chaotic dynamical systems, please refer to\n[Berlinger's article](http://www.uvm.edu/~pdodds/files/papers/others/1992/berliner1992a.pdf).\nAlgorithm used in this software is described in [the upcoming AIAA\npaper](https://dl.dropbox.com/s/2e9jxjmwh375i01/fds.pdf)\n\n# Download and use\n\nThe best way to download fds is using pip. Pip is likely included in\nyour Python installation. If not, see [instruction\nhere](https://pip.pypa.io/en/stable/installing/). To install fds\nusing pip, simply type\n\n```\nsudo pip install fds\n```\n\n# Tutorials\n\n-  [First example -- Van der Pol oscillator in Python](http://fds.readthedocs.io/en/latest/tutorials/vanderpol.html)\n-  [Lorenz attractor in C](http://fds.readthedocs.io/en/latest/tutorials/lorenz_c.html)\n-  [Lorenz 96 in MPI and C](http://fds.readthedocs.io/en/latest/tutorials/lorenz96_mpi.html)\n\n# Guides\n\n-  [Chaos and statistical convergence](http://fds.readthedocs.io/en/latest/guides/statistics.html)\n-  [Lyapunov exponents and time\n   segmentation](http://fds.readthedocs.io/en/latest/guides/lyapunov.html)\n-  [Save and restart](http://fds.readthedocs.io/en/latest/guides/save_restart.html)\n\n# Reference\n\n-  [The least squares shadowing algorithm](http://fds.readthedocs.io/en/latest/ref/lss_algorithm.html)\n-  [Function reference](http://fds.readthedocs.io/en/latest/ref/function_ref.html)\n-  [License](https://www.gnu.org/licenses/gpl-3.0.en.html)\n\n\n",
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