A re-implementation of the RIDE algorithm in Julia with an extension to replace the RIDEs iterative decomposition with an Unfold deconvolution.
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The recommended way to install julia is 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
AppStore -> JuliaUp, or winget install julia -s msstore in CMD
curl -fsSL https://install.julialang.org | sh in any shell
using Pkg
Pkg.add("UnfoldRIDE")#config for ride algorithm
cfg = RideConfig(
#sfreq is the sampling frequency of the data
sfreq = 100,
#ranges for the individual components have to be determined through manual inspection of the data
s_range = [-0.1, 0.3],
r_range = [0, 0.4],
c_range = [-0.4, 0.4],
#the range in which the initial peak estimation for the C component is performed
c_estimation_range = [0, 0.9],
#the range for one epoch
epoch_range = [-0.1, 1]
)
#run the ride algorithm
resultsClassic = ride_algorithm(ClassicMode, data_noisy, evts_without_c, cfg)
resultsUnfold = ride_algorithm(UnfoldMode, data_noisy, evts_without_c, cfg)If you use UnfoldRIDE.jl in your work, please cite using the reference given in CITATION.cff.
Contributions are very welcome. These could be typos, bugreports, feature-requests, speed-optimization, new solvers, better code, better documentation.
You are very welcome to raise issues and start pull requests!
- We recommend to write a Literate.jl document and place it in
docs/literate/FOLDER/FILENAME.jlwithFOLDERbeingHowTo,Explanation,TutorialorReference(recommended reading on the 4 categories). - Literate.jl converts the
.jlfile to a.mdautomatically and places it indocs/src/generated/FOLDER/FILENAME.md. - Edit make.jl with a reference to
docs/src/generated/FOLDER/FILENAME.md.