LAMTA#

LAMTA (LAgrangian Manifolds Tracking Algorithm) is a Python code designed to compute numerical particle trajectories within ocean current 2‑D fields and to derive a range of Lagrangian diagnostics for detecting and tracking (sub)mesoscale ocean features.

Manuscript and code#

A dedicated manuscript is currently under development to describe the theoretical background, numerical methods, and applications of LAMTA in detail.

The source code is openly developed and maintained, with a focus on reproducible Lagrangian analyses in oceanography.

Using LAMTA with the examples#

Tutorials and example workflows are provided as Jupyter notebooks and are documented separately in the LAMTA Examples documentation.

These examples are designed to run against a local installation of LAMTA and are not a standalone package.s To run the tutorials make sure that:

  • LAMTA is installed in the same Python environment (preferably in editable mode)

  • that environment is selected as the active Python kernel (Jupyter, VS Code, etc.)

This setup ensures that the examples always run against your local version of LAMTA. The examples include:

  • Initialising and advecting particles in analytical flows

  • Working with ParticleSet

  • Configuring advection schemes and parameters

  • Handling periodic boundary conditions

  • Applying LAMTA to realistic ocean current fields

Installation#

LAMTA is currently not distributed as a packaged release on PyPI. As a result, the command:

pip install lamta

will not work at this stage.

LAMTA must therefore be installed from source, either for local use or for development.

Development environment#

Recommended local setup (both repositories side-by-side):

lamta_dev/
├─ LAMTA/           # core package
└─ LAMTA_examples/  # notebooks

This keeps the library and the examples aligned during development.

VS Code#

We recommend using Visual Studio Code and opening the parent folder (e.g. lamta_dev/) so both repositories are available in a single workspace. This makes it easy to edit the LAMTA source code and immediately test changes in the example notebooks, while keeping navigation and Git operations clear.

Step 1 — Clone the repository#

Warning

If you only want to run the notebooks, cloning the repository is sufficient. If you plan to contribute to the code or documentation, we recommend forking the repository first and cloning your fork instead.

# Users
git clone https://github.com/OceanCruises/LAMTA_examples

# Contributors
# git clone https://github.com/<your-username>/LAMTA_examples

cd LAMTA

Step 2 — Create and activate a Python environment#

Using Conda (recommended):

conda create -n lamta python=3.12
conda activate lamta

Step 3 — Install LAMTA in editable mode#

From the root of the cloned repository:

pip install -e .

This links LAMTA to your local source directory. Any modification to the code will be immediately reflected when importing LAMTA in Python, scripts, or notebooks.

Future packaging#

A standard packaged release (e.g. via PyPI) is planned for the future. Until then, installing LAMTA from source as described above is the supported and recommended approach.

Funding and support#

The development of LAMTA has been supported by the following organisations:

  • LOCEAN — Laboratoire d’Océanographie et du Climat: Expérimentations et Approches Numériques, Sorbonne University

  • CNES — Centre National d’Études Spatiales

Acknowledgements#

The development of LAMTA has benefited from the remarkable coding efforts and scientific contributions of:

  • Louise Rousselet

  • Francesco d’Ovidio

  • Gina Fifani