Skip to main content

Traja is a trajectory analysis and visualization tool

Project description

Colab

Traja is a Python library for trajectory analysis. It extends the capability of pandas DataFrame specific for animal trajectory analysis in 2D, and provides convenient interfaces to other geometric analysis packages (eg, R and shapely).

Introduction

The traja Python package is a toolkit for the numerical characterization and analysis of the trajectories of moving animals. Trajectory analysis is applicable in fields as diverse as optimal foraging theory, migration, and behavioral mimicry (e.g. for verifying similarities in locomotion). A trajectory is simply a record of the path followed by a moving animal. Traja operates on trajectories in the form of a series of locations (as x, y coordinates) with times. Trajectories may be obtained by any method which provides this information, including manual tracking, radio telemetry, GPS tracking, and motion tracking from videos.

The goal of this package (and this document) is to aid biological researchers, who may not have extensive experience with Python, to analyze trajectories without being handicapped by a limited knowledge of Python or programming. However, a basic understanding of Python is useful.

If you use traja in your publications, please cite the repo

@misc{justin_shenk_2019_3237827,
  author       = {Justin Shenk and
                  Rüdiger Busche},
  title        = {justinshenk/traja: v0.1.1},
  month        = jun,
  year         = 2019,
  doi          = {10.5281/zenodo.3237827},
  url          = {https://doi.org/10.5281/zenodo.3237827}
}

Installation and setup

To install traja with conda, run

conda install -c conda-forge traja

or with pip

pip install traja.

Import traja into your Python script or via the Python command-line with import traja.

Trajectories with traja

Traja stores trajectories in pandas DataFrames, allowing any pandas functions to be used.

Load trajectory with x, y and time coordinates:

import traja

df = traja.read_file('coords.csv')

Once a DataFrame is loaded, use the .traja accessor to access the visualization and analysis methods:

df.traja.plot(title='Cage trajectory')

Analyze Trajectory

The following functions are available via traja.trajectory.[method]
Function Description
calc_derivatives Calculate derivatives of x, y values
calc_turn_angles Calculate turn angles w.r.t. x-axis
transitions Calculate first-order Markov model for transitions between grid bins
generate Generate random walk
resample_time Resample to consistent step_time intervals
rediscretize_points Rediscretize points to given step length

For up-to-date documentation, see https://traja.readthedocs.io.

Random walk

Generate random walks with

df = traja.generate(n=1000, step_length=2)
df.traja.plot()
walk\_screenshot.png

Resample time

traja.trajectory.resample_time allows resampling trajectories by a step_time.

Flow Plotting

df = traja.generate()
traja.plot_surface(df)
3D plot
traja.plot_quiver(df, bins=32)
quiver plot
traja.plot_contour(df, filled=False, quiver=False, bins=32)
contour plot
traja.plot_contour(df, filled=False, quiver=False, bins=32)
contour plot filled
traja.plot_contour(df, bins=32, contourfplot_kws={'cmap':'coolwarm'})
streamplot

Acknowledgements

traja code implementation and analytical methods (particularly rediscretize_points) are heavily inspired by Jim McLean’s R package trajr. Many thanks to Jim for his feedback.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for traja, version 0.2.8
Filename, size File type Python version Upload date Hashes
Filename, size traja-0.2.8.tar.gz (79.5 kB) File type Source Python version None Upload date Hashes View
Filename, size traja-0.2.8-py3-none-any.whl (87.9 kB) File type Wheel Python version py3 Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page