Getting Started
Welcome to GraFT-App Wiki, home of the Graph Filtered Temporal Dictionary GUI. GraFT algorithm utilizes dictionary learning techniques to learn time traces with spatial maps acting as the presence coefficients encoding for active pixels determined by time-traces. This in turn redefines connectivity between pixels in terms of their shared temporal activity, rather than spatial proximity. To read more about GraFT algorithm, start by reading the published paper from PubMed.
GraFT-App is the implementation of the GraFT algorithm in an easy-to-use GUI. This guide will walk you through the basic steps to set up and use GraFT-App in both stand-alone and MATLAB app forms.
For more information about the GraFT code, visit the public GraFT-Analysis GitHub repository to learn more.
Download
Download our latest stand-alone or MATLAB App available here. Currently, we only have support for Windows Stand-Alone application.
To download or view past versions, visit our GitHub Releases Page.
Tutorials
Check out our Tutorials section for step-by-step guides on how to use GraFT-App for common tasks and workflows. Tutorials are short and geared towards app functionality rather than full guided examples. For example, tutorial material in section covers the following main topics.
- Downloading and Installing GraFT-App
- Loading Data
- Pre-processing Techniques (e.g. motion correction, creating masks, wavelet denoising)
- Setting Parameters
- Running GraFT Algorithm
- Analysing Results
- App Settings
Examples
We've compiled a list of Examples that demonstrate various use cases for GraFT-App. These examples are designed to help you get started with using GraFT algorithm in your own projects with varying data types.
API Reference
For detailed information about the GraFT-App API, refer to our API Reference. This section provides an overview of all the classes and functions in the GraFT-App package, along with detailed descriptions.
Contributing
We welcome contributions from the community! If you have an idea for a new feature or improvement, or if you've found a bug, please open an issue on our GitHub repository. If you're interested in contributing code, create a fork using Git and create a pull request with your changes. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
License
GraFT-App is released under the MIT License. Feel free to use, modify, and distribute GraFT-App in your own projects.