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Sensitivity analysis of chaotic simulations

Project Description

[![Build Status](https://travis-ci.org/qiqi/fds.svg?branch=master)](https://travis-ci.org/qiqi/fds?branch=master) [![Coverage Status](https://coveralls.io/repos/github/qiqi/fds/badge.svg?branch=master)](https://coveralls.io/github/qiqi/fds?branch=master) [![Dependency Status](https://dependencyci.com/github/qiqi/fds/badge)](https://dependencyci.com/github/qiqi/fds) [![Documentation Status](https://readthedocs.org/projects/fds/badge/?version=latest)](http://fds.readthedocs.io/en/latest/?badge=latest) [![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)

# What’s it for

fds is a research tool for computational simulations that exhibis chaotic dynamics. It computes sensitivity derivatives of time averaged quantities, a.k.a. statistics, with respect simulation parameters.

For an introduction of chaotic dynamics, I highly recommend [Strogatz’s excellent book](https://www.amazon.com/gp/product/0813349109). For a statistical view of chaotic dynamical systems, please refer to [Berlinger’s article](http://www.uvm.edu/~pdodds/files/papers/others/1992/berliner1992a.pdf). Algorithm used in this software is described in [the upcoming AIAA paper](https://dl.dropbox.com/s/2e9jxjmwh375i01/fds.pdf)

# Download and use

The best way to download fds is using pip. Pip is likely included in your Python installation. If not, see [instruction here](https://pip.pypa.io/en/stable/installing/). To install fds using pip, simply type

` sudo pip install fds `

# Tutorials

# Guides

# Reference

Release History

This version
History Node

0.1.0.dev1

History Node

0.0.3.dev1

History Node

0.0.2.dev1

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Filename, Size & Hash SHA256 Hash Help File Type Python Version Upload Date
fds-0.1.0.dev1-py2.py3-none-any.whl
(25.3 kB) Copy SHA256 Hash SHA256
Wheel py2.py3 Sep 28, 2016

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