Record Details

Title:
Teetool – A Probabilistic Trajectory Analysis Tool
Affiliation(s):
EuXFEL staff, Other
Keyword(s):
Topic:
Scientific area:
Abstract:
Teetool is a Python package which models and visualises motion patterns found in two- and three-dimensional trajectory data. It models the trajectories as a Gaussian process and uses the mean and covariance of the trajectory data to produce a confidence region, an area (or volume) through which a given percentage of trajectories travel. The confidence region is useful in obtaining an understanding of, or quantifying, dispersion in trajectory data. Furthermore, by modelling the trajectories as a Gaussian process, missing data can be recovered and noisy measurements can be corrected. Teetool is available as a Python package on GitHub, and includes Jupyter Notebooks, showing examples for two- and three-dimensional trajectory data.
Imprint:
2017
Journal Information:
Journal of Open Research Software, 5 (1), 14 (2017)
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Language(s):
English


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 Record created 2018-01-11, last modified 2019-02-19

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