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powerfulbean / mTRFpy

a python3 version of matlab mTRF-Toolbox by Lalor Lab https://mtrfpy.readthedocs.io/
BSD 3-Clause "New" or "Revised" License
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eeg lalorlab python temporal-response-function

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Package Maintenance Documentation Status PyPI pyversions PyPI license PyPI version DOI

mTRFpy - multivariate linear modeling

This is an adaptation of the matlab mTRF-toolbox using only basic Python and Numpy. It aims to implement the same methods as the original toolbox and advance them. This documentation provides tutorial-like demonstrations of the core functionalities like model fitting, visualization and optimization as well as a comprehensive reference documentation.

Installation

You can get the stable release from PyPI:

    pip install mtrf

Or get the latest version from this repo:

    pip install git+https://github.com/powerfulbean/mTRFpy.git

While mTRFpy only depends on numpy, matplotlib is an optional dependency used to visualize models. It can also be installed via pip:

    pip install matplotlib

We also provide an optional interface to MNE-Python so it might be useful to install mne as well.

Getting started

For a little tutorial on the core features of mTRFpy, have a look at our online documentation

Found a bug?

  1. Please use the issue search to check if the issue has already been reportet.
  2. Try to reproduce problem using the latestmaster branch.
  3. Create an issue with a minimal example that reproduces the problem.

Missing a feature?

Feature requests are welcome. But take a moment to find out whether your idea fits with the scope and aims of the project. It's up to you to make a strong case to convince the project's developers of the merits of this feature. Please provide as much detail and context as possible.

Want to contribute to the project?

Great! Please take a moment to read the contribution guidelines before you do.

Citing mTRFpy

Bialas et al., (2023). mTRFpy: A Python package for temporal response function analysis. Journal of Open Source Software, 8(89), 5657, https://doi.org/10.21105/joss.05657

@article{Bialas2023,
    doi = {10.21105/joss.05657},
    url = {https://doi.org/10.21105/joss.05657},
    year = {2023}, publisher = {The Open Journal},
    volume = {8},
    number = {89},
    pages = {5657},
    author = {Ole Bialas and Jin Dou and Edmund C. Lalor},
    title = {mTRFpy: A Python package for temporal response function analysis},
    journal = {Journal of Open Source Software} }