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Unfold.jl

# [![Unfold.jl EEG toolbox](https://github.com/unfoldtoolbox/Unfold.jl/assets/10183650/3cbe57c1-e1a7-4150-817a-ce3dcc844485)](https://github.com/unfoldtoolbox/Unfold.jl) [![Stable Documentation](https://img.shields.io/badge/docs-stable-blue.svg)](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/stable/) [![In development documentation](https://img.shields.io/badge/docs-dev-blue.svg)](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/dev/) [![Test workflow status](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Test.yml/badge.svg?branch=main)](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Test.yml?query=branch%3Amain) [![Lint workflow Status](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Lint.yml/badge.svg?branch=main)](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Lint.yml?query=branch%3Amain) [![Docs workflow Status](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Docs.yml/badge.svg?branch=main)](https://github.com/unfoldtoolbox/Unfold.jl/actions/workflows/Docs.yml?query=branch%3Amain) [![Coverage](https://codecov.io/gh/unfoldtoolbox/Unfold.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/unfoldtoolbox/Unfold.jl) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5759066.svg)](https://doi.org/10.5281/zenodo.5759066) [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](CODE_OF_CONDUCT.md) [![All Contributors](https://img.shields.io/github/all-contributors/unfoldtoolbox/Unfold.jl?labelColor=5e1ec7&color=c0ffee&style=flat-square)](#contributors) |Estimation|Visualisation|Simulation|BIDS pipeline|Decoding|Statistics|MixedModelling| |---|---|---|---|---|---|---| |<a href="https://github.com/unfoldtoolbox/Unfold.jl/tree/main"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623787-757575d0-aeb9-4d94-a5f8-832f13dcd2dd.png" alt="Unfold.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldMakie.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623793-37af35a0-c99c-4374-827b-40fc37de7c2b.png" alt="UnfoldMakie.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldSim.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623795-328a4ccd-8860-4b13-9fb6-64d3df9e2091.png" alt="UnfoldSim.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldBIDS.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277622460-2956ca20-9c48-4066-9e50-c5d25c50f0d1.png" alt="UnfoldBIDS.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldDecode.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277622487-802002c0-a1f2-4236-9123-562684d39dcf.png" alt="UnfoldDecode.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldStats.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623799-4c8f2b5a-ea84-4ee3-82f9-01ef05b4f4c6.png" alt="UnfoldStats.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldMixedModels.jl"><img src="https://github.com/user-attachments/assets/ffb2bba6-3a30-48b7-9849-7d4e7195b297" alt="UnfoldMixedModels.jl logo"></a>| Package (-family) to perform linear / GAM / hierarchical / deconvolution regression on biological signals. This kind of modelling is also known as encoding modeling, linear deconvolution, Temporal Response Functions (TRFs), linear system identification, and probably under other names. fMRI models with HRF-basis functions and pupil-dilation bases are also supported. ## Getting started ### 🐍Python User? We clearly recommend Julia 😉 - but [Python users can use juliacall/Unfold directly from python!](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/dev/generated/HowTo/juliacall_unfold/) ### Julia installation <details> <summary>Click to expand</summary> The recommended way to install julia is [juliaup](https://github.com/JuliaLang/juliaup). It allows you to, e.g., easily update Julia at a later point, but also test out alpha/beta versions etc. TL:DR; If you dont want to read the explicit instructions, just copy the following command #### Windows AppStore -> JuliaUp, or `winget install julia -s msstore` in CMD #### Mac & Linux `curl -fsSL https://install.julialang.org | sh` in any shell </details> ### Unfold.jl installation ```julia using Pkg Pkg.add("Unfold") ``` ## Usage Please check out [the documentation](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/dev) for extensive tutorials, explanations and more! ### Tipp on Docs You can read the docs online: [![Stable Documentation](https://img.shields.io/badge/docs-stable-blue.svg)](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/stable) - or use the `?fit`, `?effects` julia-REPL feature. To filter docs, use e.g. `?fit(::UnfoldModel)` Here is a quick overview on what to expect. ### What you need ```julia using Unfold events::DataFrame # formula with or without random effects f = @formula 0~1+condA fLMM = @formula 0~1+condA+(1|subject) + (1|item) # in case of [overlap-correction] we need continuous data plus per-eventtype one basisfunction (typically firbasis) data::Array{Float64,2} basis = firbasis(τ=(-0.3,0.5),srate=250) # for "timeexpansion" / deconvolution # in case of [mass univariate] we need to epoch the data into trials, and a accompanying time vector epochs::Array{Float64,3} # channel x time x epochs (n-epochs == nrows(events)) times = range(0,length=size(epochs,3),step=1/sampling_rate) ``` To fit any of the models, Unfold.jl offers a unified syntax: |Overlap-Correction|Mixed Modelling|julia syntax| |:---:|:---:|---| |||`fit(UnfoldModel,[Any=>(f,times)),evts,data_epoch]`| |x||`fit(UnfoldModel,[Any=>(f,basis)),evts,data]`| ||x|`fit(UnfoldModel,[Any=>(fLMM,times)),evts,data_epoch]`| |x|x|`fit(UnfoldModel,[Any=>(fLMM,basis)),evts,data]`| ## Comparison to Unfold (matlab) <details> <summary>Click to expand</summary> The matlab version is still maintained, but active development happens in Julia. | Feature | Unfold | Unfold.jl | | --- | --- | --- | | overlap correction | x | x | | non-linear splines | x | x | | speed | | ⚡ 2-100x | | GPU support | | 🚀 | | plotting tools | x | [UnfoldMakie.jl](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldMakie.jl/) | | Interactive plotting | | ERPExplorer.jl | | simulation tools | x | [UnfoldSim.jl](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldSim.jl) | | BIDS support | x | [UnfoldBIDS.jl](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldBIDS.jl)) | | tutorials | x | x | | unittests | x | x | | Alternative bases e.g. HRF (fMRI) | | x | | Duration modelling (e.g. Hassal style) | | x | | mix different basisfunctions | | x | | different timewindows per event | | x | | linear mixed models | | x | | decoding | | [UnfoldDecode.jl](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldDecode.jl) | | outlier-robust fits | | [many options (but slower)](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/dev/HowTo/custom_solvers/#Robust-Solvers) | | 🐍Python support | | [via juliacall](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/dev/generated/HowTo/juliacall_unfold/) | </details> ## Contributions Contributions are very welcome. These could be typos, bugreports, feature-requests, speed-optimization, new solvers, better code, better documentation. ### How-to Contribute You are very welcome to raise issues and start pull requests! ### Adding Documentation 1. We recommend to write a Literate.jl document and place it in `docs/literate/FOLDER/FILENAME.jl` with `FOLDER` being `HowTo`, `Explanation`, `Tutorial` or `Reference` ([recommended reading on the 4 categories](https://documentation.divio.com/)). 2. Literate.jl converts the `.jl` file to a `.md` automatically and places it in `docs/src/generated/FOLDER/FILENAME.md`. 3. Edit [make.jl](https://github.com/unfoldtoolbox/Unfold.jl/blob/main/docs/make.jl) with a reference to `docs/src/generated/FOLDER/FILENAME.md`. ## Contributors    <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jschepers"><img src="https://avatars.githubusercontent.com/u/22366977?v=4?s=100" width="100px;" alt="Judith Schepers"/> Judith Schepers</a> <a href="#bug-jschepers" title="Bug reports">🐛</a> <a href="#code-jschepers" title="Code">💻</a> <a href="#doc-jschepers" title="Documentation">📖</a> <a href="#tutorial-jschepers" title="Tutorials">✅</a> <a href="#ideas-jschepers" title="Ideas, Planning, & Feedback">🤔</a> <a href="#test-jschepers" title="Tests">⚠️</a></td> <td align="center" valign="top" width="14.28%"><a href="http://www.benediktehinger.de"><img src="https://avatars.githubusercontent.com/u/10183650?v=4?s=100" width="100px;" alt="Benedikt Ehinger"/> Benedikt Ehinger</a> <a href="#bug-behinger" title="Bug reports">🐛</a> <a href="#code-behinger" title="Code">💻</a> <a href="#doc-behinger" title="Documentation">📖</a> <a href="#tutorial-behinger" title="Tutorials">✅</a> <a href="#ideas-behinger" title="Ideas, Planning, & Feedback">🤔</a> <a href="#test-behinger" title="Tests">⚠️</a> <a href="#infra-behinger" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="#test-behinger" title="Tests">⚠️</a> <a href="#maintenance-behinger" title="Maintenance">🚧</a> <a href="#review-behinger" title="Reviewed Pull Requests">👀</a> <a href="#question-behinger" title="Answering Questions">💬</a></td> <td align="center" valign="top" width="14.28%"><a href="https://reneskukies.de/"><img src="https://avatars.githubusercontent.com/u/57703446?v=4?s=100" width="100px;" alt="René Skukies"/> René Skukies</a> <a href="#bug-ReneSkukies" title="Bug reports">🐛</a> <a href="#doc-ReneSkukies" title="Documentation">📖</a> <a href="#tutorial-ReneSkukies" title="Tutorials">✅</a> <a href="#code-ReneSkukies" title="Code">💻</a> <a href="#ideas-ReneSkukies" title="Ideas, Planning, & Feedback">🤔</a></td> <td align="center" valign="top" width="14.28%"><a href="https://reboreexplore.github.io/"><img src="https://avatars.githubusercontent.com/u/43548330?v=4?s=100" width="100px;" alt="Manpa Barman"/> Manpa Barman</a> <a href="#infra-ReboreExplore" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="https://www.phillipalday.com"><img src="https://avatars.githubusercontent.com/u/1677783?v=4?s=100" width="100px;" alt="Phillip Alday"/> Phillip Alday</a> <a href="#code-palday" title="Code">💻</a> <a href="#infra-palday" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="http://davekleinschmidt.com"><img src="https://avatars.githubusercontent.com/u/135920?v=4?s=100" width="100px;" alt="Dave Kleinschmidt"/> Dave Kleinschmidt</a> <a href="#doc-kleinschmidt" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ssaket"><img src="https://avatars.githubusercontent.com/u/27828189?v=4?s=100" width="100px;" alt="Saket Saurabh"/> Saket Saurabh</a> <a href="#bug-ssaket" title="Bug reports">🐛</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/suddha-bpn"><img src="https://avatars.githubusercontent.com/u/7974144?v=4?s=100" width="100px;" alt="suddha-bpn"/> suddha-bpn</a> <a href="#bug-suddha-bpn" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/vladdez"><img src="https://avatars.githubusercontent.com/u/33777074?v=4?s=100" width="100px;" alt="Vladimir Mikheev"/> Vladimir Mikheev</a> <a href="#bug-vladdez" title="Bug reports">🐛</a> <a href="#doc-vladdez" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/carmenamme"><img src="https://avatars.githubusercontent.com/u/100191854?v=4?s=100" width="100px;" alt="carmenamme"/> carmenamme</a> <a href="#doc-carmenamme" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/maxvanmigem"><img src="https://avatars.githubusercontent.com/u/115144441?v=4?s=100" width="100px;" alt="Maximilien Van Migem"/> Maximilien Van Migem</a> <a href="#bug-maxvanmigem" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Till223"><img src="https://avatars.githubusercontent.com/u/29772145?v=4?s=100" width="100px;" alt="Till Prölß"/> Till Prölß</a> <a href="#doc-Till223" title="Documentation">📖</a> <a href="#bug-Till223" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/LeonvonHaugwitz"><img src="https://avatars.githubusercontent.com/u/44725676?v=4?s=100" width="100px;" alt="Leon von Haugwitz"/> Leon von Haugwitz</a> <a href="#bug-LeonvonHaugwitz" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jordandeakin"><img src="https://avatars.githubusercontent.com/u/48567988?v=4?s=100" width="100px;" alt="Jordan Deakin"/> Jordan Deakin</a> <a href="#bug-jordandeakin" title="Bug reports">🐛</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/CherryClementine"><img src="https://avatars.githubusercontent.com/u/156665249?v=4?s=100" width="100px;" alt="Sanaz "/> Sanaz </a> <a href="#doc-CherryClementine" title="Documentation">📖</a></td> </tr> </tbody> </table>    This project follows the [all-contributors](https://allcontributors.org/specification) specification. Contributions of any kind welcome! ## Citation For now, please cite [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5759066.svg)](https://doi.org/10.5281/zenodo.5759066) and/or [Ehinger & Dimigen](https://peerj.com/articles/7838/) ## Acknowledgements This work was initially supported by the Center for Interdisciplinary Research, Bielefeld (ZiF) Cooperation Group "Statistical models for psychological and linguistic data". Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany´s Excellence Strategy – EXC 2075 – 390740016

ML Frameworks Geospatial & GIS

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Open Source

UnfoldSim.jl

# [![logo_UnfoldSim jl_120px](https://github.com/unfoldtoolbox/UnfoldSim.jl/assets/57703446/139a06c7-55c6-4c2e-8935-627a3c3bf036)](https://github.com/unfoldtoolbox/UnfoldSim.jl/tree/main) [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldSim.jl/stable/) [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldSim.jl/dev/) [![Build Status](https://github.com/unfoldtoolbox/UnfoldSim.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/unfoldtoolbox/UnfoldSim.jl/actions/workflows/CI.yml?query=branch%3Amain) [![Coverage](https://codecov.io/gh/unfoldtoolbox/UnfoldSim.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/unfoldtoolbox/UnfoldSim.jl) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15401704.svg)](https://doi.org/10.5281/zenodo.15401704) [![DOI](https://joss.theoj.org/papers/10.21105/joss.06641/status.svg)](https://doi.org/10.21105/joss.06641) |Estimation|Visualisation|Simulation|BIDS pipeline|Decoding|Statistics|MixedModelling| |---|---|---|---|---|---|---| | <a href="https://github.com/unfoldtoolbox/Unfold.jl/tree/main"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623787-757575d0-aeb9-4d94-a5f8-832f13dcd2dd.png" alt="Unfold.jl Logo"></a> | <a href="https://github.com/unfoldtoolbox/UnfoldMakie.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623793-37af35a0-c99c-4374-827b-40fc37de7c2b.png" alt="UnfoldMakie.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldSim.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623795-328a4ccd-8860-4b13-9fb6-64d3df9e2091.png" alt="UnfoldSim.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldBIDS.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277622460-2956ca20-9c48-4066-9e50-c5d25c50f0d1.png" alt="UnfoldBIDS.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldDecode.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277622487-802002c0-a1f2-4236-9123-562684d39dcf.png" alt="UnfoldDecode.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldStats.jl"><img src="https://github-production-user-asset-6210df.s3.amazonaws.com/10183650/277623799-4c8f2b5a-ea84-4ee3-82f9-01ef05b4f4c6.png" alt="UnfoldStats.jl Logo"></a>|<a href="https://github.com/unfoldtoolbox/UnfoldMixedModels.jl"><img src="https://github.com/user-attachments/assets/ffb2bba6-3a30-48b7-9849-7d4e7195b297" alt="UnfoldMixedModels.jl logo"></a>| A Julia package to simulate multivariate time series, e.g. model-based ERPs, fMRI activity, pupil dilation etc. UnfoldSim.jl provides multi-channel support via EEG-forward models. Moreover, it is possible to simulate overlapping event-related activity and to add noise of a certain type e.g. Pink noise. Many tutorials, guides, how-tos and references are available in the [documentation](https://unfoldtoolbox.github.io/UnfoldDocs/UnfoldSim.jl/)! ![unfoldsim_animation](https://github.com/unfoldtoolbox/UnfoldSim.jl/blob/assets/docs/src/assets/UnfoldSim_features_animation.gif) ## Installation ### Julia <details> <summary>Click to expand</summary> The recommended way to install julia is [juliaup](https://github.com/JuliaLang/juliaup). TL;DR: If you don't want to read the explicit instructions, just copy the following command: - Windows: `winget install julia -s msstore` - Mac/Linux: `curl -fsSL https://install.julialang.org | sh` </details> ### UnfoldSim.jl ```julia using Pkg Pkg.add("UnfoldSim") ``` ## Quickstart We offer some predefined (EEG) signals to get started. ```julia using UnfoldSim data, events = UnfoldSim.predef_eeg(; n_repeats = 1, noiselevel = 0.8) ``` Produces continuous "EEG" with PinkNoise and some overlap between 20 events (2 conditions * 10 levels of the continuous variable). ## Slightly longer All simulation ingredients (design, components, onsets, noise) can be easily modified and you can simply plugin your own! ```julia using UnfoldSim using Random # Start by defining the design / events data frame. design = SingleSubjectDesign(; conditions = Dict(:condA => ["levelA", "levelB"])) |> d -> RepeatDesign(d, 10) # Next define a ground truth signal + relation to events/design with Wilkinson formulas. signal = LinearModelComponent(; basis = [0, 0, 0, 0.5, 1, 1, 0.5, 0, 0], formula = @formula(0 ~ 1 + condA), β = [1, 0.5], ) # Finally, define some inter-onset distance distribution and noise, and simulate data! data, events = simulate( Random.MersenneTwister(1), design, signal, UniformOnset(; offset = 5, width = 4), PinkNoise(), ) ``` ## Statement of need EEG researchers often analyze data containing (temporally) overlapping events (e.g. stimulus onset and button press, or consecutive eye-fixations), non-linear effects, and complex experimental designs. For a multitude of reasons, we often need to simulate such kinds of data: Simulated EEG data is useful to test preprocessing and analysis tools, validate statistical methods, illustrate conceptual issues, test toolbox functionalities, and find limitations of traditional analysis workflows. For instance, such simulation tools allow for testing the assumptions of new analysis algorithms and testing their robustness against any violation of these assumptions.  ## Contributions Contributions of any kind are very welcome. Please have a look at [CONTRIBUTING.md](https://github.com/unfoldtoolbox/UnfoldSim.jl/blob/main/CONTRIBUTING.md) for guidance on contributing to UnfoldSim.jl. ## Contributors    <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="http://www.benediktehinger.de"><img src="https://avatars.githubusercontent.com/u/10183650?v=4?s=100" width="100px;" alt="Benedikt Ehinger"/> Benedikt Ehinger</a> <a href="#bug-behinger" title="Bug reports">🐛</a> <a href="#code-behinger" title="Code">💻</a> <a href="#doc-behinger" title="Documentation">📖</a> <a href="#ideas-behinger" title="Ideas, Planning, & Feedback">🤔</a> <a href="#infra-behinger" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="#maintenance-behinger" title="Maintenance">🚧</a> <a href="#review-behinger" title="Reviewed Pull Requests">👀</a> <a href="#test-behinger" title="Tests">⚠️</a> <a href="#tutorial-behinger" title="Tutorials">✅</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jschepers"><img src="https://avatars.githubusercontent.com/u/22366977?v=4?s=100" width="100px;" alt="Judith Schepers"/> Judith Schepers</a> <a href="#ideas-jschepers" title="Ideas, Planning, & Feedback">🤔</a> <a href="#bug-jschepers" title="Bug reports">🐛</a> <a href="#doc-jschepers" title="Documentation">📖</a> <a href="#tutorial-jschepers" title="Tutorials">✅</a> <a href="#code-jschepers" title="Code">💻</a> <a href="#test-jschepers" title="Tests">⚠️</a> <a href="#maintenance-jschepers" title="Maintenance">🚧</a> <a href="#review-jschepers" title="Reviewed Pull Requests">👀</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/llips"><img src="https://avatars.githubusercontent.com/u/38983684?v=4?s=100" width="100px;" alt="Luis"/> Luis</a> <a href="#bug-llips" title="Bug reports">🐛</a> <a href="#code-llips" title="Code">💻</a> <a href="#doc-llips" title="Documentation">📖</a> <a href="#ideas-llips" title="Ideas, Planning, & Feedback">🤔</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/maanikmarathe"><img src="https://avatars.githubusercontent.com/u/66105649?v=4?s=100" width="100px;" alt="Maanik Marathe"/> Maanik Marathe</a> <a href="#doc-maanikmarathe" title="Documentation">📖</a> <a href="#code-maanikmarathe" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://reneskukies.de/"><img src="https://avatars.githubusercontent.com/u/57703446?v=4?s=100" width="100px;" alt="René Skukies"/> René Skukies</a> <a href="#doc-ReneSkukies" title="Documentation">📖</a> <a href="#code-ReneSkukies" title="Code">💻</a> <a href="#test-ReneSkukies" title="Tests">⚠️</a> <a href="#ideas-ReneSkukies" title="Ideas, Planning, & Feedback">🤔</a> <a href="#tutorial-ReneSkukies" title="Tutorials">✅</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/vladdez"><img src="https://avatars.githubusercontent.com/u/33777074?v=4?s=100" width="100px;" alt="Vladimir Mikheev"/> Vladimir Mikheev</a> <a href="#bug-vladdez" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://reboreexplore.github.io/"><img src="https://avatars.githubusercontent.com/u/43548330?v=4?s=100" width="100px;" alt="Manpa Barman"/> Manpa Barman</a> <a href="#infra-ReboreExplore" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> </tr> </tbody> </table>    This project follows the [all-contributors](https://allcontributors.org/docs/en/specification) specification. Please reach out, if you have contributed to UnfoldSim.jl but we have not listed you as a contributor yet. ## Citation If you use UnfoldSim.jl, please acknowledge and support our work by citing **1\. Our [JOSS paper](https://doi.org/10.21105/joss.06641):** ``` Schepers et al., (2025). UnfoldSim.jl: Simulating continuous event-based time series data for EEG and beyond. Journal of Open Source Software, 10(107), 6641, https://doi.org/10.21105/joss.06641 ``` <details> <summary>BibTeX entry:</summary> ```bib @article{Schepers2025, doi = {10.21105/joss.06641}, url = {https://doi.org/10.21105/joss.06641}, year = {2025}, publisher = {The Open Journal}, volume = {10}, number = {107}, pages = {6641}, author = {Judith Schepers and Luis Lips and Maanik Marathe and Benedikt V. Ehinger}, title = {UnfoldSim.jl: Simulating continuous event-based time series data for EEG and beyond}, journal = {Journal of Open Source Software} } ``` </details> and **2\. The corresponding [Zenodo DOI](https://doi.org/10.5281/zenodo.7738651)** for the specific UnfoldSim.jl version that you are using in your work. ## Acknowledgements Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2075 – 390740016. Furthermore, the authors thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Judith Schepers.

Education & Learning ML Frameworks

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