Lagrangian Trajectories Toolbox

The Lagrangian Trajectories Toolbox is a Python library dedicated to the post-processing, visualisation and analysis of Lagrangian particle trajectories.

The toolbox introduces the Trajectory Frames (TrajFrames) data structure to work with Lagrangian particle trajectories. TrajFrames make use of the blazingly fast polars DataFrame library to store attribute variables in a tabular format. Traditionally, the data structure used to store trajectories has been determined by the Lagrangian trajectory code used to evaluate particle trajectories. However, TrajFrames are well suited for working with both large .csv files generated from TRACMASS and .zarr files output from OceanParcels.

Beyond simply storing Lagrangian data, TrajFrames contain a wide range of built-in methods to enable the efficient post-processing and visualisation of particle trajectories with plotly, matplotlib and Cartopy.

Current Features of the LT Toolbox:

• Store the attribute variables of Lagrangian trajectories in a TrajFrame object.

• Add new variables, such as transit times and seeding levels, to your TrajFrame.

• Filter trajectories using any attribute variable contained in your TrajFrame.

• Get existing features, including trajectory start/end times, start/end locations and durations.

• Compute metrics, such as distance travelled, binned-statistics and Lagrangian probabilities from trajectories.

• Plot trajectories, properties and probability distributions in the form of maps, time series, temperature-salinity diagrams and more.