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Merge branch 'main' into unify_landingpage
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.pre-commit-config.yaml

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@@ -40,7 +40,7 @@ repos:
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types_or: [yaml, json]
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exclude: ".copier-answers.yml"
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- repo: https://github.com/adrienverge/yamllint
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rev: v1.35.1
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rev: v1.37.0
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hooks:
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- id: yamllint
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- repo: https://github.com/domluna/JuliaFormatter.jl

Project.toml

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name = "Unfold"
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uuid = "181c99d8-e21b-4ff3-b70b-c233eddec679"
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authors = ["Benedikt Ehinger <[email protected]>"]
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version = "0.8.1"
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version = "0.8.4"
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[deps]
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AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
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JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
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Krylov = "ba0b0d4f-ebba-5204-a429-3ac8c609bfb7"
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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<<<<<<< HEAD
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=======
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Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
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LiveServer = "16fef848-5104-11e9-1b77-fb7a48bbb589"
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>>>>>>> 7f44b0a (Update doc links to the respective UnfoldDocs pages)
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Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
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MLBase = "f0e99cf1-93fa-52ec-9ecc-5026115318e0"
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Missings = "e1d29d7a-bbdc-5cf2-9ac0-f12de2c33e28"
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[compat]
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AlgebraOfGraphics = "0.9.4"
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BSplineKit = "0.16,0.17, 0.18"
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BSplineKit = "0.16,0.17"
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CUDA = "4,5"
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DSP = "0.7, 0.8"
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DataFrames = "1"
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JLD2 = "0.5"
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Krylov = "0.9"
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LinearAlgebra = "1"
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<<<<<<< HEAD
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=======
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Literate = "2.20.1"
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LiveServer = "1.4.0"
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>>>>>>> 7f44b0a (Update doc links to the respective UnfoldDocs pages)
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Logging = "1"
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MLBase = "0.9"
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Missings = "1"

docs/literate/explanations/nonlinear_effects.jl

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using BSplineKit, Unfold
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import BSplineKit
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using Unfold
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using CairoMakie
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using DataFrames
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using Random

docs/src/index.md

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# Unfold.jl Documentation
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Welcome to [Unfold.jl](https://unfoldtoolbox.github.io/UnfoldDocs/Unfold.jl/stable/): a Julia Package for regression and event-based time series analysis, with a focus on regression ERPs for EEG analysis. The modular approach allows for easy modification to other context, like iEEG, pupil dilation, fMRI etc. - while maintaining the speed of Julia!
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```@raw html
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<div style="width:100%; margin: auto;">
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docs/src/references/extensions.md

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To use robust (outlier-"safe") solvers support as described in @Ref(custom_solvers) you have to:
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```julia
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using RobustSolvers
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import RobustSolvers
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using Unfold
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```
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Finally to use non-linear effects/splines like in `@formula 0~1+spl(continuous,5)` you have to use:
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```julia
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using BSplineKit
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import BSplineKit
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using Unfold
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```
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ext/UnfoldBSplineKitExt/UnfoldBSplineKitExt.jl

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module UnfoldBSplineKitExt
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using Unfold
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using BSplineKit
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import BSplineKit:
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BSplineOrder,
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BSplineBasis,
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boundaries,
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period,
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PeriodicBSplineBasis,
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basis_to_array_index
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using StatsModels
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import StatsModels: termvars, width, coefnames, modelcols, apply_schema
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import Base: show

ext/UnfoldBSplineKitExt/basisfunctions.jl

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function splinekernel(e, times, nsplines)
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breakpoints = spl_breakpoints(times, nsplines)
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basis = BSplineKit.BSplineBasis(BSplineOrder(4), breakpoints) # 4= cubic
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basis = BSplineBasis(BSplineOrder(4), breakpoints) # 4= cubic
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return sparse(splFunction(times, basis))
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end
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ext/UnfoldBSplineKitExt/splinepredictors.jl

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end
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function splFunction(x::AbstractVector, spl::BSplineTerm)
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basis = BSplineKit.BSplineBasis(BSplineOrder(spl.order), deepcopy(spl.breakpoints))
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basis = BSplineBasis(BSplineOrder(spl.order), deepcopy(spl.breakpoints))
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_splFunction(x, basis)
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end
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#spl(x,df) = Splines2.bs(x,df=df,intercept=true) # assumes intercept

test/Project.toml

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StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
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StatsModels = "3eaba693-59b7-5ba5-a881-562e759f1c8d"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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Unfold = "181c99d8-e21b-4ff3-b70b-c233eddec679"
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UnfoldSim = "ed8ae6d2-84d3-44c6-ab46-0baf21700804"

test/setup.jl

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using Missings
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using StableRNGs
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using RobustModels, BSplineKit # extensionTriggers
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import RobustModels, BSplineKit # extensionTriggers
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using SparseArrays
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using UnfoldSim
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using Interpolations

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