v1.0.2

🔧 Release v1.0.2 — Plot customization options added

This update introduces two new optional parameters to enhance the configurability and readability of the velocity plots:

• ylim: Allows the user to define a fixed y-axis limit for velocity plots (e.g. ylim = 1000) to improve comparability across animals or sessions. Can be set to None for automatic scaling.
• bodypart_not_to_plot: Enables selective exclusion of specific body parts (e.g. ['center', 'tail']) from the velocity plots for clarity or focus.

Both options are optional and can be adjusted at the top of the script. These enhancements improve the interpretability and visual comparability of the generated figures.

v1.0.1

• added the Zenodo DOI

v1.0.0

🐍 DeepLabCut Analysis Toolbox — Release v1.0.0

We are pleased to announce the initial public release of the DeepLabCut Analysis Toolbox (v1.0.0), a modular Python-based utility designed for post-processing of DeepLabCut (DLC) tracking data. This release establishes the toolbox as a standardized workflow for behavioral movement analysis in neuroscience research.

🧠 Overview

The toolbox provides:

• automated velocity computation from DLC-tracked points,
• detection of movement vs. non-movement periods using a customizable velocity threshold,
• grouping of body parts for selective or combined analysis (e.g., head-only tracking in freezing behavior),
• interval-based analysis over defined time windows (in frames), and
• publication-ready visualizations of movement traces and periods of activity.

📁 Outputs

For each analyzed DLC .csv file, the toolbox automatically generates:

• a .csv file with all computed velocities and movement flags,
• one .pdf plot visualizing position, velocity, and movement indicators over time,
• additional result files for each time interval if specified, and
• a global .csv containing the average velocities across all DLC files in the dataset.

🛠️ User-defined Parameters

Users can configure the following key parameters:

• pixel_size, time_step, movement_threshold (unit conversions and thresholding),
• bodypart_groups (for grouped analyses),
• time_intervals (for interval-based sub-analyses),
• and path definitions for data input/output.

A detailed table of parameters and their descriptions is provided in the updated README.

📜 Citation

If you use this toolbox in your work, please cite it as:

Musacchio, Fabrizio. DeepLabCut Analysis Toolbox. Version 1.0.0. 2025. https://github.com/FabrizioMusacchio/MotilA

A CITATION.cff file is included for automated citation parsing. You may also use the Zenodo record once archived.