Skip to main content

Wave Analysis for Fatigue and Oceanography

Project description

Wave Analysis for Fatigue and Oceanography

pkg_img tests_img docs_img Code Climate coverage_img versions_img depsy_img


WAFO is a toolbox Python routines for statistical analysis and simulation of random waves and random loads. WAFO is freely redistributable software, see WAFO icence, cf. the GNU General Public License (GPL) and contain tools for:

Fatigue Analysis

  • Fatigue life prediction for random loads

  • Theoretical density of rainflow cycles

Sea modelling

  • Simulation of linear and non-linear Gaussian waves

  • Estimation of seamodels (spectrums)

  • Joint wave height, wave steepness, wave period distributions


  • Extreme value analysis

  • Kernel density estimation

  • Hidden markov models


  • TimeSeries:

    Data analysis of time series. Example: extraction of turning points, estimation of spectrum and covariance function. Estimation transformation used in transformed Gaussian model.

  • CovData:

    Computation of spectral functions, linear and non-linear time series simulation.

  • SpecData:

    Computation of spectral moments and covariance functions, linear and non-linear time series simulation. Ex: common spectra implemented, directional spectra, bandwidth measures, exact distributions for wave characteristics.

  • CyclePairs:

    Cycle counting, discretization, and crossings, calculation of damage. Simulation of discrete Markov chains, switching Markov chains, harmonic oscillator. Ex: Rainflow cycles and matrix, discretization of loads. Damage of a rainflow count or matrix, damage matrix, S-N plot.



    Modelling with linear or transformed Gaussian waves.


    Statistical tools and extreme-value distributions. Ex: generation of random numbers, estimation of parameters, evaluation of pdf and cdf


    Kernel-density estimation.

  • MISC

    Miscellaneous routines.

  • DOCS

    Documentation of toolbox, definitions. An overview is given in the routine wafomenu.

  • DATA

    Measurements from marine applications.

WAFO homepage: <> On the WAFO home page you will find: - The WAFO Tutorial - List of publications related to WAFO.


WAFO contains some Fortran and C extensions that require a properly configured compiler and NumPy/f2py.

Create a binary wheel package and place it in the dist folder as follows:

python bdist_wheel -d dist

And install the wheel package with:

pip install dist/wafo-X.Y.Z+abcd123-os_platform.whl

Unit tests

To test if the toolbox is working paste the following in an interactive python session:

import wafo as wf
wf.test(coverage=True, doctests=True)


This project has been set up using PyScaffold 2.4.2. For details and usage information on PyScaffold see

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wafo-0.2.1.tar.gz (4.0 MB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page