Metadata-Version: 2.4
Name: trackscan
Version: 0.0.1
Summary: Post-processing and analysis of cell track data
Author: Chris Viets
Project-URL: Homepage, https://github.com/cviets/trackscan
Project-URL: Bug Tracker, https://github.com/cviets/trackscan/issues
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: matplotlib

<h2 align="center">Track Scan</h2>
A Python package for post-processing and analyzing cell track data. Includes functionality for correcting automated tracking artifacts, measuring mean squared displacements, and measuring cell turning angles.

## Cite
```bibtex
@inbook{viets_measuring_2025,
author = {Viets, Chris and Stevens, Corey A.},
editor = {Brockhausen, Inka},
title = {Measuring and Analyzing Bacterial Movement in Mucus},
bookTitle = {Dynamics of Bacteria-Mucus Interactions},
year = {2025},
publisher = {Springer US},
address = {New York, NY},
pages = {187--197},
isbn = {978-1-0716-4627-4},
doi = {10.1007/978-1-0716-4627-4_16},
url = {https://doi.org/10.1007/978-1-0716-4627-4_16}
}

```

## Installation
```
pip install trackscan
```

## Usage
The first step to using `trackscan` is to read in a CSV file containing (note that the CSV file must contain columns labeled "Position_X", "Position_Y", "Frame", and "Track_ID -- not case-sensitive).
```
trackscan -i /path/to/track_data.csv
```
This command launches an interactive shell where the track data can be manipulated and measured. Once the interactive shell has appeared, simply type `?` to view the available commands. For example, the interactive shell contains commands to de-drift track data, correct artifacts arising from automated tracking, and measure mean squared displacement, turning angles, or mean cell speed.
