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==========================================
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Wave Analysis for Fatigue and Oceanography
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==========================================
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.. image:: https://badge.fury.io/py/wafo.png
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:target: https://pypi.python.org/pypi/wafo/
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.. image:: https://travis-ci.org/wafo-project/pywafo.svg?branch=master
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:target: https://travis-ci.org/wafo-project/pywafo
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.. image:: https://readthedocs.org/projects/pip/badge/?version=latest
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:target: http://pywafo.readthedocs.org/en/latest/
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.. image:: https://landscape.io/github/wafo-project/pywafo/master/landscape.svg?style=flat
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:target: https://landscape.io/github/wafo-project/pywafo/master
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:alt: Code Health
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.. image:: https://coveralls.io/repos/wafo-project/pywafo/badge.svg?branch=master
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:target: https://coveralls.io/github/wafo-project/pywafo?branch=master
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.. image:: https://img.shields.io/pypi/pyversions/pywafo.svg
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:target: https://github.com/wafo-project/pywafo
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Description
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===========
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WAFO is a toolbox Python routines for statistical analysis and simulation of
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random waves and random loads. WAFO is freely redistributable software, see WAFO
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icence, cf. the GNU General Public License (GPL) and contain tools for:
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Fatigue Analysis
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----------------
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- Fatigue life prediction for random loads
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- Theoretical density of rainflow cycles
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Sea modelling
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-------------
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- Simulation of linear and non-linear Gaussian waves
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- Estimation of seamodels (spectrums)
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- Joint wave height, wave steepness, wave period distributions
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Statistics
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------------
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- Extreme value analysis
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- Kernel density estimation
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- Hidden markov models
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Classes
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-------
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* TimeSeries:
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Data analysis of time series. Example: extraction of turning points,
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estimation of spectrum and covariance function. Estimation transformation
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used in transformed Gaussian model.
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* CovData:
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Computation of spectral functions, linear and non-linear time series
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simulation.
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* SpecData:
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Computation of spectral moments and covariance functions, linear and
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non-linear time series simulation. Ex: common spectra implemented,
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directional spectra, bandwidth measures, exact distributions for wave
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characteristics.
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* CyclePairs:
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Cycle counting, discretization, and crossings, calculation of damage.
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Simulation of discrete Markov chains, switching Markov chains,
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harmonic oscillator. Ex: Rainflow cycles and matrix, discretization of
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loads. Damage of a rainflow count or matrix, damage matrix, S-N plot.
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Subpackages
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-----------
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* TRANSFORM
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Modelling with linear or transformed Gaussian waves.
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* STATS
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Statistical tools and extreme-value distributions. Ex: generation of random
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numbers, estimation of parameters, evaluation of pdf and cdf
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* KDETOOLS
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Kernel-density estimation.
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* MISC
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Miscellaneous routines.
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* DOCS
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Documentation of toolbox, definitions. An overview is given in the routine
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wafomenu.
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* DATA
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Measurements from marine applications.
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WAFO homepage: <http://www.maths.lth.se/matstat/wafo/>
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On the WAFO home page you will find:
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- The WAFO Tutorial
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- List of publications related to WAFO.
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Unit tests
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==========
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To test if the toolbox is working paste the following in an interactive
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python session::
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import wafo as wf
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wf.test(coverage=True, doctests=True)
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Note
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====
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This project has been set up using PyScaffold 2.4.2. For details and usage
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information on PyScaffold see http://pyscaffold.readthedocs.org/.
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