datanavigator

Interactive data visualization for signals, videos, and complex data objects.

datanavigator is a matplotlib-based toolkit for interactive data visualization that handles signals, videos, and complex data objects. It provides both simple tools for navigating data with minimal programming and a user-friendly API for building sophisticated data interaction applications. This versatility makes it both powerful and accessible, regardless of a user’s programming expertise.

Installation

pip install datanavigator

If you encounter dependency issues and are using conda, set up your environment with conda using the requirements.yml file in this repository.

conda env create -n env-datanavigator -f https://github.com/praneethnamburi/datanavigator/raw/master/requirements.yml
conda activate env-datanavigator
pip install datanavigator

Quickstart

1. Browse video frames and extract a clip

import datanavigator as dnav

video_browser = dnav.VideoBrowser(dnav.get_example_video())
# Use the arrow keys to browse through frames.
# Press Ctrl+K to bring up a list of available keyboard shortcuts
# To extract a clip, 
#   1. navigate to the start frame and press 1
#   2. navigate to the end frame and press 2
#   3. press e to save the extracted clip
# run dnav.get_clip_folder() to find the saved video clip

# Or, you can extract a clip from the command line
clip_path = video_browser.extract_clip(start_frame=100, end_frame=200)
print(f"Extracted clip saved to: {clip_path}")

2. Browse time series data and mark events of interest

import datanavigator as dnav
signal_browser = dnav.EventPickerDemo()

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

Praneeth Namburi

Project Link: https://github.com/praneethnamburi/datanavigator

Acknowledgments

This tool was developed as part of the ImmersionToolbox initiative at the MIT.nano Immersion Lab. Thanks to NCSOFT for supporting this initiative.