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169 lines
5.5 KiB
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169 lines
5.5 KiB
ReStructuredText
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==========================================
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Wave Analysis for Fatigue and Oceanography
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==========================================
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|pkg_img| |tests_img| |docs_img| |health_img| |coverage_img| |versions_img| |depsy_img|
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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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Installation
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============
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WAFO contains some Fortran and C extensions that require a properly configured
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compiler and NumPy/f2py.
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Create a binary wheel package and place it in the dist folder as follows::
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python setup.py bdist_wheel -d dist
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And install the wheel package with::
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pip install dist/wafo-X.Y.Z+abcd123-os_platform.whl
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Getting started
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===============
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A quick introduction to some of the many features of wafo can be found in the Tutorial IPython notebooks in the
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`tutorial scripts folder`_:
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* Chapter 1 - `Some applications of WAFO`_
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* Chapter 2 - `Modelling random loads and stochastic waves`_
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* Chapter 3 - `Demonstrates distributions of wave characteristics`_
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* Chapter 4 - `Fatigue load analysis and rain-flow cycles`_
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* Chapter 5 - `Extreme value analysis`_
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-- _tutorial scripts folder: http://nbviewer.jupyter.org/github/wafo-project/pywafo/tree/master/wafo/doc/tutorial_scripts/
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.. _Some applications of WAFO: http://nbviewer.jupyter.org/github/wafo-project/pywafo/blob/master/wafo/doc/tutorial_scripts/WAFO%20Chapter%201.ipynb
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.. _Modelling random loads and stochastic waves: http://nbviewer.jupyter.org/github/wafo-project/pywafo/blob/master/wafo/doc/tutorial_scripts/WAFO%20Chapter%202.ipynb
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.. _Demonstrates distributions of wave characteristics: http://nbviewer.jupyter.org/github/wafo-project/pywafo/blob/master/wafo/doc/tutorial_scripts/WAFO%20Chapter%203.ipynb
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.. _Fatigue load analysis and rain-flow cycles: http://nbviewer.jupyter.org/github/wafo-project/pywafo/blob/master/wafo/doc/tutorial_scripts/WAFO%20Chapter%204.ipynb
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.. _Extreme value analysis: http://nbviewer.jupyter.org/github/wafo-project/pywafo/blob/master/wafo/doc/tutorial_scripts/WAFO%20Chapter%205.ipynb
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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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.. |wafo_logo| image:: https://github.com/wafo-project/pywafo/blob/master/wafo/data/wafoLogoNewWithoutBorder.png
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:target: https://github.com/wafo-project/pywafo
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.. |pkg_img| image:: https://badge.fury.io/py/wafo.png
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:target: https://pypi.python.org/pypi/wafo/
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.. |tests_img| 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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.. |docs_img| image:: https://readthedocs.org/projects/pip/badge/?version=latest
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:target: http://pywafo.readthedocs.org/en/latest/
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.. |health_img| image:: https://codeclimate.com/github/wafo-project/pywafo/badges/gpa.svg
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:target: https://codeclimate.com/github/wafo-project/pywafo
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:alt: Code Climate
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.. |coverage_img| 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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.. |versions_img| image:: https://img.shields.io/pypi/pyversions/wafo.svg
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:target: https://github.com/wafo-project/pywafo
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.. |depsy_img| image:: http://depsy.org/api/package/pypi/wafo/badge.svg
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:target: http://depsy.org/package/python/wafo
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