Update paper.md #30

behinger · 2023-11-08T10:16:10Z

No description provided.

The argument `n_trials` does not exist for the function predef_eeg (at least in the current version of UnfoldSim.jl).

Correct mistake in README.md

multichannel

@behinger

All contributors should be added as a comment in a pull request or an issue. Eg : @all-contributors please add @behinger for <contributions> <contributions can be found in the emoji key in the Unfold.jl repo (needs to be merged)>

added the @all-contributors functionality

small cleanup changes

…to joss-paper

github-actions · 2024-01-03T15:17:11Z

docs/literate/HowTo/newComponent.jl

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Suggested change

basisfunction::Any

maxlength::Any

github-actions · 2024-01-03T15:17:12Z

docs/literate/reference/basistypes.jl

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Suggested change

ax = f[1, 1] = Axis(f)

for b in [p100, n170, p300, n400]

lines!(ax, b(), label = string(b))

scatter!(ax, b(), label = string(b))

github-actions · 2024-01-03T15:17:13Z

docs/literate/reference/basistypes.jl

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Suggested change

plotConfig = (:n => 5:3:15, :tmax => 0.5:0.2:1.1)

github-actions · 2024-01-03T15:17:14Z

docs/literate/tutorials/quickstart.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

design =

SingleSubjectDesign(; conditions = Dict(:condA => ["levelA", "levelB"])) |>

x -> RepeatDesign(x, 10);

github-actions · 2024-01-03T15:17:15Z

docs/literate/tutorials/quickstart.jl

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Suggested change

basis = [0, 0, 0, 0.5, 1, 1, 0.5, 0, 0],

formula = @formula(0 ~ 1 + condA),

β = [1, 0.5],

);

github-actions · 2024-01-03T15:17:16Z

docs/make.jl

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Suggested change

repo = Documenter.Remotes.GitHub("unfoldtoolbox", "UnfoldSim.jl"),

sitename = "UnfoldSim.jl",

format = Documenter.HTML(;

prettyurls = get(ENV, "CI", "false") == "true",

canonical = "https://unfoldtoolbox.github.io/UnfoldSim.jl",

edit_link = "main",

assets = String[],

github-actions · 2024-01-03T15:17:17Z

src/UnfoldSim.jl

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Suggested change

using DSP

using Random

using DataFrames

using Distributions # for LogNormal Onset

using Parameters

using StatsModels

using MixedModels

using ImageFiltering # for Noise-filter (can be replaced maybe?)

using MixedModelsSim

using SignalAnalysis

using LinearAlgebra

using ToeplitzMatrices # for AR Expo. Noise "Circulant"

using StatsModels

using HDF5, Artifacts, FileIO

github-actions · 2024-01-03T15:17:18Z

src/UnfoldSim.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

import DSP.hanning

import Base.length

import Base.size

import Base.show

include("types.jl")

include("design.jl")

include("component.jl")

include("noise.jl")

include("simulation.jl")

include("onset.jl")

include("predefinedSimulations.jl")

include("headmodel.jl")

include("helper.jl")

include("bases.jl")

github-actions · 2024-01-03T15:17:18Z

src/predefinedSimulations.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

predef_2x2(; kwargs...) = predef_2x2(MersenneTwister(1); kwargs...) # without rng always call same one

predef_eeg(; kwargs...) = predef_eeg(MersenneTwister(1); kwargs...) # without rng always call same one

predef_eeg(nsubjects::Int; kwargs...) = predef_eeg(MersenneTwister(1), nsubjects; kwargs...) # without rng always call same one

github-actions · 2024-01-03T15:17:19Z

src/predefinedSimulations.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

function predef_eeg(

rng;

# design

n_repeats = 100,

tableModifyFun = x -> shuffle(deepcopy(rng), x),

# component / signal

sfreq = 100,

p1 = (p100(; sfreq = sfreq), @formula(0 ~ 1), [5], Dict()),

n1 = (n170(; sfreq = sfreq), @formula(0 ~ 1 + condition), [5, -3], Dict()),

p3 = (p300(; sfreq = sfreq), @formula(0 ~ 1 + continuous), [5, 1], Dict()),

kwargs...,

)

design =

SingleSubjectDesign(;

conditions = Dict(

:condition => ["car", "face"],

:continuous => range(-5, 5, length = 10),

),

tableModifyFun = tableModifyFun,

) |> x -> RepeatDesign(x, n_repeats)

return predef_eeg(rng, design, LinearModelComponent, [p1, n1, p3]; sfreq, kwargs...)

github-actions · 2024-01-03T15:17:20Z

src/predefinedSimulations.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

function predef_eeg(

rng::AbstractRNG,

n_subjects;

# design

n_items = 100,

tableModifyFun = x -> shuffle(deepcopy(rng), x),

conditions = Dict(

:condition => ["car", "face"],

:continuous => range(-5, 5, length = 10),

),

# component / signal

sfreq = 100,

p1 = (;

s = p100(; sfreq = sfreq),

f = @formula(0 ~ 1 + (1 | subject) + (1 | item)),

β = [5],

σs = Dict(:subject => [1], :item => [1]),

c = Dict(),

),

n1 = (;

s = n170(; sfreq = sfreq),

f = @formula(

0 ~ 1 + condition + (1 + condition | subject) + (1 + condition | item)

),

β = [5, -3],

σs = Dict(:subject => [1, 1], :item => [0.5, 0.5]),

c = Dict(),

),

p3 = (;

s = p300(; sfreq = sfreq),

f = @formula(

0 ~ 1 + continuous + (1 + continuous | subject) + (1 + continuous | item)

),

β = [5, 1],

σs = Dict(:subject => [1, 1], :item => [0.5, 0.5]),

c = Dict(),

),

kwargs...,

)

github-actions · 2024-01-03T15:17:21Z

src/predefinedSimulations.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

github-actions · 2024-01-03T15:17:22Z

src/simulation.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

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function simulate(rng, simulation::Simulation; return_epoched::Bool = false)

github-actions · 2024-01-03T15:17:23Z

test/helper.jl

[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test padarray([2, 2], (-3, 2), -1) == [-1, -1, -1, 2, 2, -1, -1]

@test padarray([2, 2], -2, -1) == [-1, -1, 2, 2]

@test padarray([2, 2], 2, -1) == [2, 2, -1, -1]

@test padarray([2, 2], 2, -1) == [2, 2, -1, -1]

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github-actions · 2024-01-03T15:17:24Z

docs/literate/HowTo/multichannel.jl

+# ## Specifying a design
+
+# We are using a one-level design for testing here.
+design = SingleSubjectDesign(conditions=Dict(:condA=>["levelA"]))


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

design = SingleSubjectDesign(conditions=Dict(:condA=>["levelA"]))

design = SingleSubjectDesign(conditions = Dict(:condA => ["levelA"]))

github-actions · 2024-01-03T15:17:24Z

docs/literate/HowTo/multichannel.jl

+c = LinearModelComponent(;basis=p100(),formula = @formula(0~1),β = [1]);
+c2 = LinearModelComponent(;basis=p300(),formula = @formula(0~1),β = [1]);


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

c = LinearModelComponent(;basis=p100(),formula = @formula(0~1),β = [1]);

c2 = LinearModelComponent(;basis=p300(),formula = @formula(0~1),β = [1]);

c = LinearModelComponent(; basis = p100(), formula = @formula(0 ~ 1), β = [1]);

c2 = LinearModelComponent(; basis = p300(), formula = @formula(0 ~ 1), β = [1]);

github-actions · 2024-01-03T15:17:24Z

docs/literate/HowTo/multichannel.jl

+
+# ## The multichannel component
+# next similar to the nested design above, we can nest the component in a `MultichannelComponent`. We could either provide the projection marix manually, e.g.:
+mc = UnfoldSim.MultichannelComponent(c, [1,2,-1,3,5,2.3,1])


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

mc = UnfoldSim.MultichannelComponent(c, [1,2,-1,3,5,2.3,1])

mc = UnfoldSim.MultichannelComponent(c, [1, 2, -1, 3, 5, 2.3, 1])

github-actions · 2024-01-03T15:17:25Z

docs/literate/HowTo/multichannel.jl

+hart = headmodel(type="hartmut")
+mc = UnfoldSim.MultichannelComponent(c, hart=>"Left Postcentral Gyrus")
+mc2 = UnfoldSim.MultichannelComponent(c2, hart=>"Right Occipital Pole")


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

hart = headmodel(type="hartmut")

mc = UnfoldSim.MultichannelComponent(c, hart=>"Left Postcentral Gyrus")

mc2 = UnfoldSim.MultichannelComponent(c2, hart=>"Right Occipital Pole")

hart = headmodel(type = "hartmut")

mc = UnfoldSim.MultichannelComponent(c, hart => "Left Postcentral Gyrus")

mc2 = UnfoldSim.MultichannelComponent(c2, hart => "Right Occipital Pole")

github-actions · 2024-01-03T15:17:25Z

docs/literate/HowTo/multichannel.jl

+#     You could also specify a noise-specific component which is applied prior to projection & summing with other components
+# 
+# finally we need to define the onsets of the signal
+onset = UniformOnset(;width=20,offset=4);


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

onset = UniformOnset(;width=20,offset=4);

onset = UniformOnset(; width = 20, offset = 4);

github-actions · 2024-01-03T15:17:27Z

docs/run_liveserver.jl

+dr = filter(isdir,readdir(joinpath("src","generated"),join=true))
+push!(dr,"./build")
+servedocs(skip_dirs=dr,literate_dir=joinpath("literate"),foldername=".",host="0.0.0.0")
+
+


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

dr = filter(isdir,readdir(joinpath("src","generated"),join=true))

push!(dr,"./build")

servedocs(skip_dirs=dr,literate_dir=joinpath("literate"),foldername=".",host="0.0.0.0")

dr = filter(isdir, readdir(joinpath("src", "generated"), join = true))

push!(dr, "./build")

servedocs(

skip_dirs = dr,

literate_dir = joinpath("literate"),

foldername = ".",

host = "0.0.0.0",

)

github-actions · 2024-01-03T15:17:27Z

src/UnfoldSim.jl

-
+   using HDF5,Artifacts,FileIO
+
+   using LinearAlgebra # headmodel


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

using LinearAlgebra # headmodel

using LinearAlgebra # headmodel

github-actions · 2024-01-03T15:17:27Z

src/UnfoldSim.jl

   # export bases
   export p100,n170,p300,n400,hrf


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

# export bases

export p100,n170,p300,n400,hrf

# noise functions

export PinkNoise, RedNoise, WhiteNoise, NoNoise, ExponentialNoise #,RealNoise (not implemented yet)

github-actions · 2024-01-03T15:17:27Z

src/UnfoldSim.jl

+   # headmodel
+   export AbstractHeadmodel,Hartmut,headmodel,leadfield,orientation,magnitude


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

# headmodel

export AbstractHeadmodel,Hartmut,headmodel,leadfield,orientation,magnitude

# UnfoldSim functions

export simulate, gen_noise, generate

github-actions · 2024-01-03T15:17:27Z

src/UnfoldSim.jl

+   # multichannel
+   export MultichannelComponent


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

# multichannel

export MultichannelComponent

# utilities

export padarray, convert

# export Offsets

export UniformOnset, LogNormalOnset

# re-export StatsModels

export DummyCoding, EffectsCoding

# export bases

export p100, n170, p300, n400, hrf

# headmodel

export AbstractHeadmodel, Hartmut, headmodel, leadfield, orientation, magnitude

# multichannel

export MultichannelComponent

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github-actions · 2024-01-03T15:27:00Z

docs/literate/HowTo/newComponent.jl



 erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)
-heatmap(hcat(erp...))
+plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)

heatmap(hcat(erp...))

\ No newline at end of file

plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)

erp = UnfoldSim.simulate(

MersenneTwister(1),

TimeVaryingComponent(basis_shiftduration, 50),

design,

)

plot_erpimage(hcat(erp...), sortvalues = generate(design).shift)

github-actions · 2024-01-03T15:27:01Z

src/component.jl

+"""
+Wrapper for an `AbstractComponent` to project it to multiple target-channels via `projection`. optional adds `noise` to the source prior to projection.
+"""
+@with_kw struct MultichannelComponent <:AbstractComponent


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@with_kw struct MultichannelComponent <:AbstractComponent

@with_kw struct MultichannelComponent <: AbstractComponent

github-actions · 2024-01-03T15:27:01Z

src/component.jl

+    noise::AbstractNoise # optional
+end
+
+MultichannelComponent(c::AbstractComponent,p) = MultichannelComponent(c::AbstractComponent,p,NoNoise())


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

MultichannelComponent(c::AbstractComponent,p) = MultichannelComponent(c::AbstractComponent,p,NoNoise())

MultichannelComponent(c::AbstractComponent, p) =

MultichannelComponent(c::AbstractComponent, p, NoNoise())

github-actions · 2024-01-03T15:27:01Z

src/component.jl

+function MultichannelComponent(c::AbstractComponent,p::Pair{<:AbstractHeadmodel,String},n::AbstractNoise)
+    ix = closest_src(p[1],p[2])


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

function MultichannelComponent(c::AbstractComponent,p::Pair{<:AbstractHeadmodel,String},n::AbstractNoise)

ix = closest_src(p[1],p[2])

function MultichannelComponent(

c::AbstractComponent,

p::Pair{<:AbstractHeadmodel,String},

n::AbstractNoise,

)

ix = closest_src(p[1], p[2])

github-actions · 2024-01-03T15:27:01Z

src/component.jl

+function MultichannelComponent(c::AbstractComponent,p::Pair{<:AbstractHeadmodel,String},n::AbstractNoise)
+    ix = closest_src(p[1],p[2])
+    mg = magnitude(p[1])
+    return MultichannelComponent(c,mg[:,ix],n)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

return MultichannelComponent(c,mg[:,ix],n)

return MultichannelComponent(c, mg[:, ix], n)

github-actions · 2024-01-03T15:27:03Z

src/helper.jl

+pos = closest_src(hartmut=>"Left Middle Temporal Gyrus, posterior division")
+```
+"""
+function closest_src(head::Hartmut,label::String)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

function closest_src(head::Hartmut,label::String)

function closest_src(head::Hartmut, label::String)

github-actions · 2024-01-03T15:27:03Z

src/helper.jl

+	pos = head.cortical["pos"]
+	ix = findall(head.cortical["label"] .== label)
+	@assert sum(ix)>0 """could not find label $label in hartmut.cortical["label"] - try unique(hartmut.cortical["label"]) for a list"""


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

pos = head.cortical["pos"]

ix = findall(head.cortical["label"] .== label)

@assert sum(ix)>0 """could not find label $label in hartmut.cortical["label"] - try unique(hartmut.cortical["label"]) for a list"""

pos = head.cortical["pos"]

ix = findall(head.cortical["label"] .== label)

@assert sum(ix) > 0 """could not find label $label in hartmut.cortical["label"] - try unique(hartmut.cortical["label"]) for a list"""

github-actions · 2024-01-03T15:27:04Z

src/helper.jl

+	ix = UnfoldSim.closest_src(mean(pos[ix,:],dims=1)[1,:],pos)
+	return ix
+end


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

ix = UnfoldSim.closest_src(mean(pos[ix,:],dims=1)[1,:],pos)

return ix

end

ix = UnfoldSim.closest_src(mean(pos[ix, :], dims = 1)[1, :], pos)

return ix

end

github-actions · 2024-01-03T15:27:04Z

src/predefinedSimulations.jl

@@ -74,12 +79,6 @@ function predef_eeg(rng::AbstractRNG,design::AbstractDesign,T::Type{<:AbstractCo
    return simulate(rng,design, components,  onset, noise;kwargs...);


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

return simulate(rng,design, components, onset, noise;kwargs...);

return simulate(rng, design, components, onset, noise; kwargs...)

github-actions · 2024-01-03T15:27:04Z

src/simulation.jl

@@ -2,70 +2,117 @@
 # helper to move input ::Component to ::Vector{Component}
 Simulation(design::AbstractDesign,component::AbstractComponent,onset::AbstractOnset,noisetype::AbstractNoise) = Simulation(design,[component],onset,noisetype)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

Simulation(design::AbstractDesign,component::AbstractComponent,onset::AbstractOnset,noisetype::AbstractNoise) = Simulation(design,[component],onset,noisetype)

Simulation(

design::AbstractDesign,

component::AbstractComponent,

onset::AbstractOnset,

noisetype::AbstractNoise,

) = Simulation(design, [component], onset, noisetype)

github-actions

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github-actions · 2024-01-05T11:04:20Z

docs/literate/HowTo/newComponent.jl



 erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)
-heatmap(hcat(erp...))
+plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)

heatmap(hcat(erp...))

\ No newline at end of file

plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)

erp = UnfoldSim.simulate(

MersenneTwister(1),

TimeVaryingComponent(basis_shiftduration, 50),

design,

)

plot_erpimage(hcat(erp...), sortvalues = generate(design).shift)

github-actions · 2024-01-05T11:04:20Z

src/simulation.jl

@@ -2,70 +2,117 @@
 # helper to move input ::Component to ::Vector{Component}
 Simulation(design::AbstractDesign,component::AbstractComponent,onset::AbstractOnset,noisetype::AbstractNoise) = Simulation(design,[component],onset,noisetype)

+# by default no noise
+Simulation(design::AbstractDesign,component,onset::AbstractOnset) = Simulation(design,component,onset,NoNoise())


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

Simulation(design::AbstractDesign,component,onset::AbstractOnset) = Simulation(design,component,onset,NoNoise())

Simulation(design::AbstractDesign, component, onset::AbstractOnset) =

Simulation(design, component, onset, NoNoise())

github-actions · 2024-01-05T11:04:20Z

src/simulation.jl

 """
 Simulate eeg data given a simulation design, effect sizes and variances

 make use of `return_epoched=true` to skip the Onset-calculation + conversion to continuous data and get the epoched data directly
 """
-simulate(rng,design, signal,  onset, noise;kwargs...) = simulate(rng,Simulation(design, signal,  onset, noise);kwargs...)
+
+simulate(rng, design::AbstractDesign, signal, onset::AbstractOnset, noise::AbstractNoise=NoNoise(); kwargs...) = simulate(rng, Simulation(design, signal, onset, noise); kwargs...)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

simulate(rng, design::AbstractDesign, signal, onset::AbstractOnset, noise::AbstractNoise=NoNoise(); kwargs...) = simulate(rng, Simulation(design, signal, onset, noise); kwargs...)

simulate(

rng,

design::AbstractDesign,

signal,

onset::AbstractOnset,

noise::AbstractNoise = NoNoise();

kwargs...,

) = simulate(rng, Simulation(design, signal, onset, noise); kwargs...)

github-actions · 2024-01-05T11:04:20Z

src/simulation.jl

 	# create epoch data / erps
 	erps = simulate(deepcopy(rng), components,simulation)
+#	@debug size(erps)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

# create epoch data / erps

erps = simulate(deepcopy(rng), components,simulation)

# @debug size(erps)

# unpacking fields

(; design, components, onset, noisetype) = simulation

github-actions · 2024-01-05T11:04:20Z

src/simulation.jl

+	n_subj = length(size(design))==1 ? 1 : size(design)[2]
+	n_trial = size(design)[1]
+	n_ch = n_channels(components)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

n_subj = length(size(design))==1 ? 1 : size(design)[2]

n_trial = size(design)[1]

n_ch = n_channels(components)

# create epoch data / erps

erps = simulate(deepcopy(rng), components, simulation)

# @debug size(erps)

n_subj = length(size(design)) == 1 ? 1 : size(design)[2]

n_trial = size(design)[1]

n_ch = n_channels(components)

github-actions · 2024-01-05T11:04:22Z

test/headmodel.jl

@@ -0,0 +1,23 @@
+hart = UnfoldSim.headmodel()
+@testset "hartmut" begin
+    @test length(hart.electrodes["label"]) == 231-4


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test length(hart.electrodes["label"]) == 231-4

@test length(hart.electrodes["label"]) == 231 - 4

github-actions · 2024-01-05T11:04:22Z

test/headmodel.jl

+    @test isa(lf,AbstractArray)
+    mg = magnitude(hart,type="norm")


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test isa(lf,AbstractArray)

mg = magnitude(hart,type="norm")

@test isa(lf, AbstractArray)

mg = magnitude(hart, type = "norm")

github-actions · 2024-01-05T11:04:23Z

test/headmodel.jl

+
+    @test isa(lf,AbstractArray)
+    mg_man = magnitude(lf,or)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test isa(lf,AbstractArray)

mg_man = magnitude(lf,or)

@test isa(lf, AbstractArray)

mg_man = magnitude(lf, or)

github-actions · 2024-01-05T11:04:23Z

test/headmodel.jl

+    @test size(mg) == (231-4,2004)
+
+
+end


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test size(mg) == (231-4,2004)

end

@test size(mg) == (231 - 4, 2004)

end

github-actions · 2024-01-05T11:04:23Z

test/helper.jl

+        @test UnfoldSim.closest_src([0,0,1],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == 1
+        @test UnfoldSim.closest_src([[0,0,1],[-1,-1,0]],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == [1,2]


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

@test UnfoldSim.closest_src([0,0,1],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == 1

@test UnfoldSim.closest_src([[0,0,1],[-1,-1,0]],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == [1,2]

@test UnfoldSim.closest_src([0, 0, 1], [0 0 0.5; -1 -1 -1; -3 -3 -3]) == 1

@test UnfoldSim.closest_src(

[[0, 0, 1], [-1, -1, 0]],

[0 0 0.5; -1 -1 -1; -3 -3 -3],

) == [1, 2]

github-actions · 2024-01-16T08:38:00Z

docs/literate/HowTo/newComponent.jl



 erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)
-heatmap(hcat(erp...))
+plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)

heatmap(hcat(erp...))

\ No newline at end of file

plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)

erp = UnfoldSim.simulate(

MersenneTwister(1),

TimeVaryingComponent(basis_shiftduration, 50),

design,

)

plot_erpimage(hcat(erp...), sortvalues = generate(design).shift)

github-actions · 2024-01-16T08:38:00Z

docs/literate/reference/onsettypes.jl

+#        - if `offset` > `length(signal.basis)` -> no overlap
+#        - if `offset` < `length(signal.basis)` -> there might be overlap, depending on the other parameters of the onset distribution
+
+


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

# [^1]: Wikipedia contributors. (2023, December 5). Log-normal distribution. In Wikipedia, The Free Encyclopedia. Retrieved 12:27, December 7, 2023, from https://en.wikipedia.org/w/index.php?title=Log-normal_distribution&oldid=1188400077#

github-actions · 2024-01-16T08:38:00Z

test/helper.jl

+        @test UnfoldSim.closest_src([0,0,1],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == 1
+        @test UnfoldSim.closest_src([[0,0,1],[-1,-1,0]],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == [1,2]
+
+


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

github-actions · 2024-01-16T08:38:01Z

test/helper.jl

+        @test UnfoldSim.closest_src([[0,0,1],[-1,-1,0]],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == [1,2]
+
+
+    end
 end


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

end

end

github-actions · 2024-01-16T08:38:01Z

test/multichannel.jl

+design = SingleSubjectDesign(conditions=Dict(:condA=>["levelA","levelB"])) |> x->RepeatDesign(x,5);
+signal = LinearModelComponent(;basis=[0,1,2,3,0],formula = @formula(0~1+condA),β = [2,5]);
+onset = UniformOnset(;width=20,offset=4);


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

design = SingleSubjectDesign(conditions=Dict(:condA=>["levelA","levelB"])) |> x->RepeatDesign(x,5);

signal = LinearModelComponent(;basis=[0,1,2,3,0],formula = @formula(0~1+condA),β = [2,5]);

onset = UniformOnset(;width=20,offset=4);

design =

SingleSubjectDesign(conditions = Dict(:condA => ["levelA", "levelB"])) |>

x -> RepeatDesign(x, 5);

signal = LinearModelComponent(;

basis = [0, 1, 2, 3, 0],

formula = @formula(0 ~ 1 + condA),

β = [2, 5],

);

onset = UniformOnset(; width = 20, offset = 4);

github-actions · 2024-01-16T08:38:02Z

test/simulation.jl

+    @testset "single_subject-multiple_channels" begin
+
+        ## Simulate data
+        data, events = simulate(MersenneTwister(42), design_single_subject, signal_linear_multichannel, onset, noise)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

data, events = simulate(MersenneTwister(42), design_single_subject, signal_linear_multichannel, onset, noise)

data, events = simulate(

MersenneTwister(42),

design_single_subject,

signal_linear_multichannel,

onset,

noise,

)

github-actions · 2024-01-16T08:38:02Z

test/simulation.jl

+
+        # channels x eeg
+        @test size(data) == (n_channels_exp, eeg_length_exp)
+


[JuliaFormatter] _{reported by reviewdog 🐶}

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github-actions · 2024-01-16T08:38:02Z

test/simulation.jl

+    @testset "multiple_subjects-single_channel" begin
+
+        ## Simulate data
+        data, events = simulate(MersenneTwister(42), design_multiple_subjects, signal_mixed, onset, noise)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

data, events = simulate(MersenneTwister(42), design_multiple_subjects, signal_mixed, onset, noise)

data, events = simulate(

MersenneTwister(42),

design_multiple_subjects,

signal_mixed,

onset,

noise,

)

github-actions · 2024-01-16T08:38:02Z

test/simulation.jl

+    end
+
+    @testset "multiple_subjects-multiple_channels" begin
+


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

github-actions · 2024-01-16T08:38:02Z

test/simulation.jl

+    @testset "multiple_subjects-multiple_channels" begin
+
+        ## Simulate data
+        data, events = simulate(MersenneTwister(42), design_multiple_subjects, signal_mixed_multichannel, onset, noise)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

data, events = simulate(MersenneTwister(42), design_multiple_subjects, signal_mixed_multichannel, onset, noise)

data, events = simulate(

MersenneTwister(42),

design_multiple_subjects,

signal_mixed_multichannel,

onset,

noise,

)

github-actions · 2024-01-16T08:45:12Z

docs/literate/HowTo/newComponent.jl



 erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)
-heatmap(hcat(erp...))
+plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)

heatmap(hcat(erp...))

\ No newline at end of file

plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)

erp = UnfoldSim.simulate(

MersenneTwister(1),

TimeVaryingComponent(basis_shiftduration, 50),

design,

)

plot_erpimage(hcat(erp...), sortvalues = generate(design).shift)

github-actions · 2024-01-16T08:47:06Z

docs/literate/HowTo/newComponent.jl



 erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)
-heatmap(hcat(erp...))
+plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)


[JuliaFormatter] _{reported by reviewdog 🐶}

Suggested change

erp = UnfoldSim.simulate(MersenneTwister(1),TimeVaryingComponent(basis_shiftduration,50),design)

heatmap(hcat(erp...))

\ No newline at end of file

plot_erpimage(hcat(erp...),sortvalues=generate(design).shift)

erp = UnfoldSim.simulate(

MersenneTwister(1),

TimeVaryingComponent(basis_shiftduration, 50),

design,

)

plot_erpimage(hcat(erp...), sortvalues = generate(design).shift)

behinger and others added 30 commits November 6, 2023 17:45

headmodel better tests

8c605f3

fix closestsrc test

2e52583

Merge branch 'main' into multichannel

a9060b2

multichannel support

4b90b92

Update paper.md

b8207c4

add label/helper

433cc6c

added tutorial, fix some bug, scaling 1000

8e05d42

fix docs

bda44f5

forgot to add package Random

58e502c

actually added Random...

146bd0b

Update paper.md

3aa7ad8

fix MultiChannel, new Overview doc

3cd06bc

Export MultichannelComponent

cf04383

Correct mistake in README.md

aa460dc

The argument `n_trials` does not exist for the function predef_eeg (at least in the current version of UnfoldSim.jl).

Merge pull request #33 from unfoldtoolbox/README-mistake

8694f52

Correct mistake in README.md

Merge pull request #29 from unfoldtoolbox/multichannel

1aacd9c

multichannel

v0.1.7

b9ac5cc

fix a electrode scaling issue

ffe67ec

Merge branch 'multichannel'

4287d5e

moved literate to extra folder for compat with liveserver

dbd7b0c

added liveserver script

ef87b5d

Merge branch 'main' of https://github.com/unfoldtoolbox/UnfoldSim.jl

e65da17

Create .all-contributorsrc

8dc38bc

added markdown configuration for @all-contributors

1e7cd9c

All contributors should be added as a comment in a pull request or an issue. Eg : @all-contributors please add @behinger for <contributions> <contributions can be found in the emoji key in the Unfold.jl repo (needs to be merged)>

Merge pull request #34 from ReboreExplore/main

a2e4357

added the @all-contributors functionality

facelift of docs

12f614e

small cleanup changes

1daaec8

docs: update README.md

34bab0e

docs: update .all-contributorsrc

8699198

Merge pull request #36 from maanikmarathe/docs-2023-11

2b9cd37

small cleanup changes

behinger and others added 3 commits January 3, 2024 15:12

Update paper.md

5c12370

Create joss.yml

8951b47

Merge branch 'joss-paper' of github.com:unfoldtoolbox/UnfoldSim.jl in…

8a860ba

…to joss-paper

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created joss_paper folder and moved paper.md there

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behinger added 2 commits January 16, 2024 09:38

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behinger closed this Jan 16, 2024

+ax = f[1, 1] = Axis(f)
+for b in [p100, n170, p300, n400]
+    lines!(ax, b(), label = string(b))
+    scatter!(ax, b(), label = string(b))

+design =
+    SingleSubjectDesign(; conditions = Dict(:condA => ["levelA", "levelB"])) |>
+    x -> RepeatDesign(x, 10);

+    basis = [0, 0, 0, 0.5, 1, 1, 0.5, 0, 0],
+    formula = @formula(0 ~ 1 + condA),
+    β = [1, 0.5],
+);

+    repo = Documenter.Remotes.GitHub("unfoldtoolbox", "UnfoldSim.jl"),
+    sitename = "UnfoldSim.jl",
+    format = Documenter.HTML(;
+        prettyurls = get(ENV, "CI", "false") == "true",
+        canonical = "https://unfoldtoolbox.github.io/UnfoldSim.jl",
+        edit_link = "main",
+        assets = String[],

+using DSP
+using Random
+using DataFrames
+using Distributions # for LogNormal Onset
+using Parameters
+using StatsModels
+using MixedModels
+using ImageFiltering # for Noise-filter (can be replaced maybe?)
+using MixedModelsSim
+using SignalAnalysis
+using LinearAlgebra
+using ToeplitzMatrices # for AR Expo. Noise "Circulant"
+using StatsModels
+using HDF5, Artifacts, FileIO

+import DSP.hanning
+import Base.length
+import Base.size
+import Base.show
+include("types.jl")
+include("design.jl")
+include("component.jl")
+include("noise.jl")
+include("simulation.jl")
+include("onset.jl")
+include("predefinedSimulations.jl")
+include("headmodel.jl")
+include("helper.jl")
+include("bases.jl")

+predef_2x2(; kwargs...) = predef_2x2(MersenneTwister(1); kwargs...) # without rng always call same one
+predef_eeg(; kwargs...) = predef_eeg(MersenneTwister(1); kwargs...) # without rng always call same one
+predef_eeg(nsubjects::Int; kwargs...) = predef_eeg(MersenneTwister(1), nsubjects; kwargs...) # without rng always call same one

+function predef_eeg(
+    rng;
+    # design
+    n_repeats = 100,
+    tableModifyFun = x -> shuffle(deepcopy(rng), x),
+    # component / signal
+    sfreq = 100,
+    p1 = (p100(; sfreq = sfreq), @formula(0 ~ 1), [5], Dict()),
+    n1 = (n170(; sfreq = sfreq), @formula(0 ~ 1 + condition), [5, -3], Dict()),
+    p3 = (p300(; sfreq = sfreq), @formula(0 ~ 1 + continuous), [5, 1], Dict()),
+    kwargs...,
+)
+    design =
+        SingleSubjectDesign(;
+            conditions = Dict(
+                :condition => ["car", "face"],
+                :continuous => range(-5, 5, length = 10),
+            ),
+            tableModifyFun = tableModifyFun,
+        ) |> x -> RepeatDesign(x, n_repeats)
+    return predef_eeg(rng, design, LinearModelComponent, [p1, n1, p3]; sfreq, kwargs...)

+function predef_eeg(
+    rng::AbstractRNG,
+    n_subjects;
+    # design
+    n_items = 100,
+    tableModifyFun = x -> shuffle(deepcopy(rng), x),
+    conditions = Dict(
+        :condition => ["car", "face"],
+        :continuous => range(-5, 5, length = 10),
+    ),
+    # component / signal
+    sfreq = 100,
+    p1 = (;
+        s = p100(; sfreq = sfreq),
+        f = @formula(0 ~ 1 + (1 | subject) + (1 | item)),
+        β = [5],
+        σs = Dict(:subject => [1], :item => [1]),
+        c = Dict(),
+    ),
+    n1 = (;
+        s = n170(; sfreq = sfreq),
+        f = @formula(
+~ 1 + condition + (1 + condition | subject) + (1 + condition | item)
+        ),
+        β = [5, -3],
+        σs = Dict(:subject => [1, 1], :item => [0.5, 0.5]),
+        c = Dict(),
+    ),
+    p3 = (;
+        s = p300(; sfreq = sfreq),
+        f = @formula(
+~ 1 + continuous + (1 + continuous | subject) + (1 + continuous | item)
+        ),
+        β = [5, 1],
+        σs = Dict(:subject => [1, 1], :item => [0.5, 0.5]),
+        c = Dict(),
+    ),
+    kwargs...,
+)


	function simulate(rng, simulation::Simulation; return_epoched::Bool = false)

+        @test padarray([2, 2], (-3, 2), -1) == [-1, -1, -1, 2, 2, -1, -1]
+        @test padarray([2, 2], -2, -1) == [-1, -1, 2, 2]
+        @test padarray([2, 2], 2, -1) == [2, 2, -1, -1]
+        @test padarray([2, 2], 2, -1) == [2, 2, -1, -1]

	design = SingleSubjectDesign(conditions=Dict(:condA=>["levelA"]))
	design = SingleSubjectDesign(conditions = Dict(:condA => ["levelA"]))

		c = LinearModelComponent(;basis=p100(),formula = @formula(0~1),β = [1]);
		c2 = LinearModelComponent(;basis=p300(),formula = @formula(0~1),β = [1]);

	mc = UnfoldSim.MultichannelComponent(c, [1,2,-1,3,5,2.3,1])
	mc = UnfoldSim.MultichannelComponent(c, [1, 2, -1, 3, 5, 2.3, 1])

	onset = UniformOnset(;width=20,offset=4);
	onset = UniformOnset(; width = 20, offset = 4);

-dr = filter(isdir,readdir(joinpath("src","generated"),join=true))
-push!(dr,"./build")
-servedocs(skip_dirs=dr,literate_dir=joinpath("literate"),foldername=".",host="0.0.0.0")
+dr = filter(isdir, readdir(joinpath("src", "generated"), join = true))
+push!(dr, "./build")
+servedocs(
+    skip_dirs = dr,
+    literate_dir = joinpath("literate"),
+    foldername = ".",
+    host = "0.0.0.0",
+)

	using LinearAlgebra # headmodel
	using LinearAlgebra # headmodel

		# headmodel
		export AbstractHeadmodel,Hartmut,headmodel,leadfield,orientation,magnitude

-   # multichannel
-   export MultichannelComponent
+# utilities
+export padarray, convert
+# export Offsets
+export UniformOnset, LogNormalOnset
+# re-export StatsModels
+export DummyCoding, EffectsCoding
+# export bases
+export p100, n170, p300, n400, hrf
+# headmodel
+export AbstractHeadmodel, Hartmut, headmodel, leadfield, orientation, magnitude
+# multichannel
+export MultichannelComponent

	@with_kw struct MultichannelComponent <:AbstractComponent
	@with_kw struct MultichannelComponent <: AbstractComponent

Update paper.md #30

Update paper.md #30

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	MultichannelComponent(c::AbstractComponent,p) = MultichannelComponent(c::AbstractComponent,p,NoNoise())
	MultichannelComponent(c::AbstractComponent, p) =
	MultichannelComponent(c::AbstractComponent, p, NoNoise())

		function MultichannelComponent(c::AbstractComponent,p::Pair{<:AbstractHeadmodel,String},n::AbstractNoise)
		ix = closest_src(p[1],p[2])

	return MultichannelComponent(c,mg[:,ix],n)
	return MultichannelComponent(c, mg[:, ix], n)

	function closest_src(head::Hartmut,label::String)
	function closest_src(head::Hartmut, label::String)

		@@ -74,12 +79,6 @@ function predef_eeg(rng::AbstractRNG,design::AbstractDesign,T::Type{<:AbstractCo
		return simulate(rng,design, components, onset, noise;kwargs...);

	return simulate(rng,design, components, onset, noise;kwargs...);
	return simulate(rng, design, components, onset, noise; kwargs...)

		@@ -2,70 +2,117 @@
		# helper to move input ::Component to ::Vector{Component}
		Simulation(design::AbstractDesign,component::AbstractComponent,onset::AbstractOnset,noisetype::AbstractNoise) = Simulation(design,[component],onset,noisetype)

	Simulation(design::AbstractDesign,component,onset::AbstractOnset) = Simulation(design,component,onset,NoNoise())
	Simulation(design::AbstractDesign, component, onset::AbstractOnset) =
	Simulation(design, component, onset, NoNoise())

	@test length(hart.electrodes["label"]) == 231-4
	@test length(hart.electrodes["label"]) == 231 - 4

		@test UnfoldSim.closest_src([0,0,1],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == 1
		@test UnfoldSim.closest_src([[0,0,1],[-1,-1,0]],[0 0 0.5; -1 -1 -1; -3 -3 -3]) == [1,2]