Wave Analysis for Fatigue and Oceanography
Project description
Wave Analysis for Fatigue and Oceanography
Description
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
Statistics
Extreme value analysis
Kernel density estimation
Hidden markov models
Classes
- 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.
Subpackages
- TRANSFORM
Modelling with linear or transformed Gaussian waves.
- STATS
Statistical tools and extreme-value distributions. Ex: generation of random numbers, estimation of parameters, evaluation of pdf and cdf
- KDETOOLS
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: <http://www.maths.lth.se/matstat/wafo/> On the WAFO home page you will find: - The WAFO Tutorial - List of publications related to WAFO.
Installation
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 setup.py 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)
Note
This project has been set up using PyScaffold 2.4.2. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.
Project details
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