pydfc

An implementation of several well-known dynamic Functional Connectivity (dFC) assessment methods.

Installation

Simply install pydfc using the following steps:

conda create --name pydfc_env python=3.11
conda activate pydfc_env
pip install pydfc

Examples

The following example scripts illustrate how to use the toolbox:

• examples/dFC_methods_demo.py Demonstrates how to load data and apply each of the implemented dFC methods individually.
• examples/multi_analysis_demo.py Demonstrates how to apply multiple dFC methods on a dataset and compare their results.

For more details about the implemented methods and the comparison analysis, see our paper:

On the variability of dynamic functional connectivity assessment methods

Mohammad Torabi, Georgios D Mitsis, Jean-Baptiste Poline, GigaScience, Volume 13, 2024, giae009.

AI-Assisted Tutorial Experience (Optional)

In addition to the example scripts and documentation, pydfc provides optional AI-assisted learning workflows that can help you explore the toolbox, understand dynamic functional connectivity methods, and generate minimal working examples.

These options are entirely optional and do not affect the core functionality of the toolbox.

Using GitHub Copilot Prompts

If you use GitHub Copilot in VS Code or Visual Studio, you can access guided prompts that walk you through installing pydfc, loading demo data, and running key dFC methods.

How to use:

1. Open the repository in VS Code.

2. Open Copilot Chat.

3. Run one of the available prompts, for example:

   /01_install
   /02_state_free_quickstart
   /03_state_based_quickstart
   /04_choose_method
   /05_troubleshoot
   

These prompts provide a structured, step-by-step tutorial experience and generate copy-paste code tailored to common workflows.

We encourage users with Copilot access to try this interactive experience to quickly become familiar with the toolbox.

Using Codex, Claude, or Other AI Coding Assistants

If you use Codex, Claude, or another AI coding assistant, the repository includes guidance files designed for AI-assisted workflows:

• docs/SKILL.md — comprehensive usage guidance and tutorial flow
• agents.md — concise agent instructions (if present)

You can point your AI assistant to these files or ask it to follow them when guiding you through pydfc.

Example prompt:

Use the instructions in docs/SKILL.md to guide me through a minimal PydFC workflow.

Using Any LLM Chat (Copy-Paste Method)

If you do not use Copilot, Codex, or Claude, you can still benefit from AI guidance.

Steps:

1. Open docs/SKILL.md.
2. Copy its contents.
3. Paste it into your preferred LLM chat (e.g., ChatGPT, Claude, Gemini).
4. Ask questions such as:
   • "Guide me through the state-free quickstart."
   • "Which dFC method should I use for my dataset?"
   • "Generate a minimal Sliding Window example."

This provides a portable, copy-paste tutorial experience.

Notes on Privacy and Offline Use

• The AI-assisted workflows described above operate within your chosen AI environment.
• No data is sent by pydfc itself.
• Users working with sensitive data should follow their institutional policies when using external AI services.

Recommended First Step

If you are new to pydfc, we recommend starting with:

1. examples/dFC_methods_demo.py
2. The Copilot prompt /02_state_free_quickstart (if available)
3. Or the copy-paste method using docs/SKILL.md

This optional AI-assisted workflow is designed to complement — not replace — the documentation and example scripts.