fSTG Toolkit: an Open-Source Software for Spatio-Temporal Graph Analysis of fMRI data
Overview
fSTG Toolkit is an open-source software dedicated to longitudinal analysis of brain connectivity, modeling data as spatio-temporal graphs. It enables the study of dynamics and reorganization of brain regions, primarily using functional MRI (fMRI) data, but is also compatible with any type of connectivity data.
Current main features:
- Building of spatio-temporal graphs from correlation matrices and region definitions.
- Advanced graph metrics computation.
- Interactive visualization of results via a web dashboard.
- Simulation of connectivity patterns and sequences.
- Frequent subgraph pattern mining via SPMiner integration.
Installation
Installation from PyPI
The easiest way to get started is to install the package from PyPI. Make sure you have a Python environment ready with a supported version (see the badge above), then run:
pip install fSTG-Toolkit
To install optional feature sets:
pip install "fSTG-Toolkit[dashboard]" # web dashboard
pip install "fSTG-Toolkit[plot]" # matplotlib plots
pip install "fSTG-Toolkit[frequent]" # frequent pattern mining (requires Docker)
pip install "fSTG-Toolkit[dashboard,plot,frequent]" # everything
Installation from Source
To install from source, create a new environment with the required Python and Poetry binaries. Using conda:
conda env create -n <env_name> -f environment.yml
conda activate <env_name>
Then in the project's root folder, install the dependencies:
poetry install
To install optional feature sets:
poetry install --extras dashboard # web dashboard
poetry install --extras plot # matplotlib plots
poetry install --extras frequent # frequent pattern mining (requires Docker)
poetry install --all-extras # everything
Quick Start
# Build graphs from a correlation matrix file and an areas CSV
python -m fstg_toolkit graph build -o my_graphs.zip areas.csv matrices.npz
# Compute graph metrics
python -m fstg_toolkit graph metrics my_graphs.zip
# Open the interactive dashboard
python -m fstg_toolkit dashboard show my_graphs.zip
The areas CSV must contain Id_Area, Name_Area, and Name_Region columns. Correlation matrices must be NumPy files (.npz or .npy) with shape (T, N, N).
Use --help on any command for full options:
python -m fstg_toolkit --help
python -m fstg_toolkit graph build --help
Full usage documentation, tutorials, and API reference are available at fstg-toolkit.readthedocs.io.
Community
- Questions about using the toolkit? Ask in the discussions, in the Q&A category.
- Found a bug? Open an issue with the bug report form.
- Want to contribute? Bug fixes, new features, and documentation improvements are welcome: see CONTRIBUTING.md for the development setup, the test suites, and the pull request process.
Everyone taking part in the project is expected to follow the Code of Conduct.
License
The fSTG Toolkit is distributed under the CeCILL Free Software Agreement v2.1. See LICENSE for more information. The Multi-SPMiner sources bundled under src/fstg_toolkit/spminer/ are an exception: see src/fstg_toolkit/spminer/NOTICE.md for their provenance and status.
Metadata
Release files for fSTG-Toolkit 1.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fstg_toolkit-1.3.0.tar.gz | 1.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fstg_toolkit-1.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.3 MB
Release files / fstg_toolkit-1.3.0.tar.gz
| Download URL | fstg_toolkit-1.3.0.tar.gz |
|---|---|
| Size | 1.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
521c7a1bf67cae5bf05861f77a09ddd34f64079c910891722765f135c9bf1db0
|
|
BLAKE2b-256 checksum How to use checksums |
44a88215fdb070fdef93d60cfd8e30e4066c4608ee7642c8a33f466849b4ea04
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 25, 2026.
Transparency logRelease files / fstg_toolkit-1.3.0-py3-none-any.whl
| Download URL | fstg_toolkit-1.3.0-py3-none-any.whl |
|---|---|
| Size | 1.7 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8efc09e0e51a72cc498db05466d4abf670282d57c05334a4175cda47a68c87c3
|
|
BLAKE2b-256 checksum How to use checksums |
aee220abf07eb37896f1c8c46511da1c486157aabfacb6ab7675256f1d8ddef9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 25, 2026.
Transparency log