Welcome to extended-wdm package documentation!
EWDM (Extended Wavelet Directional Method) is a Python toolkit for a wavelet-based estimation of the directional wave spectra
The wavelet-based method for estimating directional wave spectra have emerged as a practical alternative to the conventional Fourier-based techniques.
This package implements a wavelet-based technique to obtain a robust estimation of the directional wave spectrum from diverse source of data such as GPS buoys, pitch-roll buoys, arrays of wave staffs and ADCPs.
For spatial arrays of wave staffs, the original Donelan’s WDM (Wavelet Directional Method) is implemented.
For single-point triplet data, such as wave buoys and ADCPs, the methods presented by Pelaez-Zapata et al. (2024) and Krogstad et al. (2006) are implemented.
So, the package, “Extended Wavelet Directional Method,” extends the original WDM to incorporate single-point triplet data in addition to wave arrays
Note
Key features of the EWDM include:
Implementation of the wavelet-based algorithms for extracting directional information from wave time series.
Improve estimation of wave directional distribution using KDE (Kernel Density Estimation).
Tools for processing and visualising directional wave data.
Powered by xarray labelled multi-dimensional arrays.
Helper functions to handle commonly used data sources such as SOFAR Spotter buoys and CDIP database.
Documentation, examples, and comparison with conventional methods.
Whether you are a researcher, student, or engineer in physical oceanography, the EWDM provides a powerful, user-friendly toolkit for estimating the directional wave spectra. We welcome contributions, feedback, and collaboration from the community to further enhance the capabilities of the Extended Wavelet Directional Method.