UnfoldMixedModels

https://github.com/unfoldtoolbox/unfoldmixedmodels.jl

Science Score: 67.0%

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Last synced: 6 months ago · JSON representation ·

Repository

Basic Info

Host: GitHub
Owner: unfoldtoolbox
License: mit
Language: Julia
Default Branch: main
Size: 1.74 MB

Statistics

Stars: 1
Watchers: 2
Forks: 1
Open Issues: 5
Releases: 4

Created about 1 year ago · Last pushed 6 months ago

Metadata Files

Readme License Code of conduct Citation

README.md

|Estimation|Visualisation|Simulation|BIDS pipeline|Decoding|Statistics|MixedModelling| |---|---|---|---|---|---|---| | | ||||||

UnfoldMixedModels.jl is a package to perform hierarchical regression / linear mixed models on biological signals. As an experimental feature, it further allows to perform simultaneous overlap-correction / deconvolution.

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!

Julia installation

Click to expand

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

UnfoldMixedModels.jl installation

julia using Pkg Pkg.add("UnfoldMixedModels")

Usage

Please check out the documentation for extensive tutorials, explanations and more!

Tipp on Docs

You can read the docs online: - or use the ?fit, ?effects julia-REPL feature. To filter docs, use e.g. ?fit(::UnfoldMixedModel)

Here is a quick overview on what to expect.

What you need

```julia using UnfoldMixedModels

events::DataFrame

formula with or without random effects

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 | |:---:|:---:|---| | | x | fit(UnfoldModel,[Any=>(fLMM,times)),evts,data_epoch] | | x | x | fit(UnfoldModel,[Any=>(fLMM,basis)),evts,data] |

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

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).
Literate.jl converts the .jl file to a .md automatically and places it in docs/src/generated/FOLDER/FILENAME.md.
Edit make.jl with a reference to docs/src/generated/FOLDER/FILENAME.md.

Contributors

_{Alexandra M}
🐛

_{Phillip Alday}
💻

This project follows the all-contributors specification.

Contributions of any kind welcome!

Citation

For now, please cite

and/or Ehinger & Dimigen

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

Owner

Name: unfoldtoolbox
Login: unfoldtoolbox
Kind: organization
Email: info@unfoldtoolbox.org

Website: http://www.unfoldtoolbox.org
Repositories: 5
Profile: https://github.com/unfoldtoolbox

Unfold your potentials...

Citation (CITATION.cff)

# Go to https://citation-file-format.github.io/cff-initializer-javascript/#/ to finish this
cff-version: 1.2.0
title: UnfoldMixedModels.jl
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Benedikt Ehinger
    email: benedikt.ehinger@vis.uni-stuttgart.de

GitHub Events

Total

Create event: 11
Release event: 2
Issues event: 4
Watch event: 1
Delete event: 3
Issue comment event: 20
Push event: 61
Pull request review event: 1
Pull request review comment event: 1
Pull request event: 22
Fork event: 1

Last Year

Create event: 11
Release event: 2
Issues event: 4
Watch event: 1
Delete event: 3
Issue comment event: 20
Push event: 61
Pull request review event: 1
Pull request review comment event: 1
Pull request event: 22
Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 3
Total pull requests: 14
Average time to close issues: less than a minute
Average time to close pull requests: 6 days
Total issue authors: 3
Total pull request authors: 5
Average comments per issue: 0.0
Average comments per pull request: 0.07
Merged pull requests: 9
Bot issues: 0
Bot pull requests: 9

Past Year

Issues: 3
Pull requests: 14
Average time to close issues: less than a minute
Average time to close pull requests: 6 days
Issue authors: 3
Pull request authors: 5
Average comments per issue: 0.0
Average comments per pull request: 0.07
Merged pull requests: 9
Bot issues: 0
Bot pull requests: 9

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Top Authors

Issue Authors

behinger (1)
Alx-mor (1)
JuliaTagBot (1)

Pull Request Authors

github-actions[bot] (5)
behinger (4)
allcontributors[bot] (2)
dependabot[bot] (2)
xuyg16 (1)

Top Labels

Issue Labels

Pull Request Labels

chore (4) dependencies (2) github_actions (1)

Packages

Total packages: 1
Total downloads:
- julia 1 total

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 3

juliahub.com: UnfoldMixedModels

Documentation: https://docs.juliahub.com/General/UnfoldMixedModels/stable/
License: MIT
Latest release: 0.1.2
published 9 months ago

Versions: 3
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 1 Total

Rankings

Dependent repos count: 3.2%

Average: 9.8%

Dependent packages count: 16.3%

Last synced: 6 months ago

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