https://github.com/dspelaez/extended-wdm
Python toolkit for estimating directional wave spectra of ocean waves based on wavelet transform
https://github.com/dspelaez/extended-wdm
adcps directional-spectrum spotter wavelets waves wavestaffs wdm
Last synced: 2 months ago
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Python toolkit for estimating directional wave spectra of ocean waves based on wavelet transform
- Host: GitHub
- URL: https://github.com/dspelaez/extended-wdm
- Owner: dspelaez
- License: gpl-3.0
- Created: 2024-06-25T07:55:42.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-03T10:12:34.000Z (10 months ago)
- Last Synced: 2025-11-27T12:53:41.602Z (3 months ago)
- Topics: adcps, directional-spectrum, spotter, wavelets, waves, wavestaffs, wdm
- Language: Jupyter Notebook
- Homepage: https://extended-wdm.readthedocs.io/
- Size: 5.02 MB
- Stars: 14
- Watchers: 1
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
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- open-sustainable-technology - EWDM - Python toolkit for estimating directional wave spectra of ocean waves based on wavelet transform. (Hydrosphere / Waves and Currents)
README
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# EWDM: Extended Wavelet Directional Method
Welcome to the GitHub repository for the **Extended Wavelet Directional Method (EWDM)** - a toolkit for estimating directional spectra of ocean waves using the Continuous Wavelet Transform (CWT).
This package implements the algorithms of the original WDM proposed by [Donelan et al. (1985)](10.1175/1520-0485(1996)026<1901:naotdp>2.0.co;2) that are suitable for spatially-distributed arrays of wave staffs; as well as the algorithms presented by [Peláez-Zapata et al. (2024)](https://doi.org/10.1175/JTECH-D-23-0058.1) for single-point triplets of wave-induced displacements, velocities, accelerations or slopes (see also [Krogstad et al., 2006](https://onepetro.org/IJOPE/article-abstract/28936/Wavelet-And-Local-Directional-Analysis-of-Ocean?redirectedFrom=fulltext)).
Therefore, **EWDM** allows the estimation of the directional wave spectrum for a variety of sources, including GPS-based buoys, pitch-roll-heave buoys, acoustic Doppler current profilers (ADCPs) and sampled points from stereo-imaging recordings.
**Key features** of the **EWDM** include:
* Implementation of the wavelet-based algorithms for extracting directional
information from wave time series.
* 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
[Spotter buoys](https://www.sofarocean.com/products/spotter) and
[CDIP](https://cdip.ucsd.edu/).
* Documentation, examples, and comparison with conventional methods.
Whether you are a researcher, student, or engineer in physical oceanography, **EWDM** provides a powerful, user-friendly toolkit for in-depth analysis of directional ocean wave spectra. We welcome contributions, feedback, and collaboration from the community to further enhance the capabilities of **EWDM**.
# Getting Started
## Installation
### Stable release
You can install EWDM using `pip`. First, make sure you have Python 3.8 or higher installed.
```bash
pip install ewdm
```
This is the preferred method to install EWDM, as it will always install the most recent stable release.
If you don't have `pip` installed, these [Python installation instructions](http://docs.python-guide.org/en/latest/starting/installation/) can guide
you through the process.
### From sources
The sources for EWDM can be downloaded from the [Github repo](https://github.com/dspelaez/extended-wdm).
You can either clone the public repository:
```bash
git clone git://github.com/dspelaez/extended-wdm
```
Or download the [tarball](https://github.com/dspelaez/extended-wdm/tarball/master):
```bash
curl -OJL https://github.com/dspelaez/extended-wdm/tarball/master
```
Once you have a copy of the source, you can install it with:
```bash
python setup.py install
```
Or using `pip`:
```bash
pip install .
```
## Running tests
To install the necessary packages for development and testing, you can run the following command:
```bash
pip install -e '.[test]'
```
To run the tests, you can use the `pytest` framework by executing the following command:
```bash
pytest tests
```
## Usage
After installation, you can import and use the `ewdm` package in your Python code:
```python
import ewdm
```
## Quick example
This example uses a CDIP buoy time series of wave-induced displacements to estimate the directional wave spectrum.
```python
import numpy as np
import xarray as xr
from matplotlib import pyplot as plt
import ewdm
from ewdm.sources import CDIPDataSourceRealTime
from ewdm.plots import plot_directional_spectrum
plt.ion()
cdip = CDIPDataSourceRealTime(166)
dataset = cdip.read_dataset(time_start='2024-06-09T08:30')
spec = ewdm.Triplets(dataset)
output = spec.compute()
fig, ax = plt.subplots()
plot_directional_spectrum(
output["directional_spectrum"], ax=ax, levels=None
)
```
This will produce a plot like this:
## Further examples
For a curated collection of examples, please refer to the [Gallery](https://extended-wdm.readthedocs.io/en/latest/gallery.html) in the documentation.
## Related projects
Several tools complement the functionality of **EWDM** in the analysis of ocean
wave data. Some of the most relevant projects are:
- [`WAFO`](https://www.maths.lth.se/matstat/wafo/) provides advanced statistical
and engineering analysis of wave fields and wave-induced loads.
- [`FOWD`](https://github.com/dionhaefner/FOWD) offers a rich dataset of wave
parameters tailored for machine learning applications. It also provides
routines to compute frequently used wave parameters.
- [`DIWASP`](https://github.com/metocean/diwasp) implements classical
Fourier-based methods for directional spectrum estimation.
- Special mention to modern Python packages like
[`wavespectra`](https://github.com/wavespectra/wavespectra) and
[`oceanwaves-python`](https://github.com/openearth/oceanwaves-python), that
support spectral data manipulation and visualization. While these tools do not
estimate directional spectra from raw measurements, they can be integrated
with **EWDM** to enhance wave data processing workflows.
## How to cite this work
If you find this software useful, please cite it using the DOI: [`10.21105/joss.07942`](https://doi.org/10.21105/joss.07942) or copy the following `bibtex` entry:
```
@article{Pelaez-Zapata2025,
doi = {10.21105/joss.07942},
url = {https://doi.org/10.21105/joss.07942},
year = {2025},
publisher = {The Open Journal},
volume = {10},
number = {109},
pages = {7942},
author = {Daniel Peláez-Zapata and Frédéric Dias},
title = {EWDM: A wavelet-based method for estimating directional spectra of ocean waves},
journal = {Journal of Open Source Software}
}
```
## How to contribute
EWDM is an open-source package and we welcome feedback and contributions.
You can open an issue in the GitHub issues page if you:
- find a bug in the package;
- need some new features;
- want some supports;
- show your own examples.
Please refer to the [Contributing guide](https://extended-wdm.readthedocs.io/en/latest/contribute.html) in the documentation for further information.