_load_results(files_df; generate_Xs::Bool = true)

Internal function to load Unfold models into memory. Can also be used to load data after file information was loaded lazily (lazy=true) using load_results()

add_event_files!(layoutDF)

Function to find and load all events file-paths into Layout-DataFrame.

bids_coeftable(model_df)

Turns all models found in model_df into tydy DataFrames and aggregates them in a new DataFrame.

bids_layout(bidsPath::AbstractString;
    derivatives::Bool=true,
    specific_folder::Union{Nothing,AbstractString}=nothing,
    exclude_folder::Union{Nothing,AbstractString}=nothing,
    ses::Union{Nothing,AbstractString}=nothing,
    task::Union{Nothing,AbstractString}=nothing,
    run::Union{Nothing,AbstractString}=nothing)

Main function to load paths of all subjects in one bidsroot folder. Will return a DataFrame containing all found paths with specific subject information. Used before loading data into memore using @Ref(`loadbidseegdata`)

Keywords

• derivatives::Bool = true
  Look for data in the derivatives folder
• specific_folder::Union{Nothing,AbstractString} = nothing
  Specify a specific folder name in either derivatives or bids_root to look for data.
• exclude_folder::Union{Nothing,AbstractString} = nothing
  Exclude a specific folder from data detection.
• ses:Union{Nothing,AbstractString} = nothing
  Which session to load; loads all if nothing
• task::Union{Nothing,AbstractString} = nothing
  Which task to load; loads all if nothing
• run::Union{Nothing,AbstractString} = nothing
  Which run to load; loads all if nothing

check_df(files_df, ses, task, run)

Internal; Checks if the multiple sessions/task/runs are found if none of these are provided

extract_subject_id!(files_df, file)

Internal function to get subject information from dataframe.

list_all_paths(path)

Internal function to find pathfiles

load_bids_eeg_data(layout_df; verbose::Bool=true, kwargs...)

Load data found with @Ref('bids_layout') into memory.

• verbose::Bool = true
  Show ProgressBar
• kwargs...
  kwargs for CSV.read to load events from .tsv file; e.g. to specify delimeter

load_events(layoutDF::DataFrame; kwargs...)

Internal function to load events based on paths in the layout Df

load_results(bids_root::String;
    derivatives_subfolder::String="Unfold",
    lazy::Bool=false,
    generate_Xs::Bool = true,
    ses::Union{Nothing,AbstractString}=nothing,
    task::Union{Nothing,AbstractString}=nothing,
    run::Union{Nothing,AbstractString}=nothing)

Load Unfold models existing in a derivatives_subfolder in your BIDS root folder.

Keywords

• derivatives_subfolder::String = "Unfold"
  Defines in which subfolder of bids_root/derivatives to look for Unfold models.
• lazy::Bool = false
  Do not actually load the dataset into memore if true, only return a dataframe with paths
• generate_Xs::Bool = true
  Do not recreate the designmatrix; improves loading time.
• ses::Union{Nothing,AbstractString} = nothing
  Which session to load; loads all if nothing
• task::Union{Nothing,AbstractString} = nothing
  Which task to load; loads all if nothing
• run::Union{Nothing,AbstractString} = nothing
  Which run to load; loads all if nothing

raw_to_data(raw; channels::AbstractVector{<:Union{String,Integer}}=[])

Function to get data from MNE raw object. Can choose specific channels; default loads all channels.

rename_to_latency(data_df)

This is a convenience function to add a :latency collumn (needed by Unfold) based on another variable in the events_df (e.g. sample)

run_unfold(dataDF, bfDict; 
	eventcolumn="event",
	remove_time_expanded_Xs=true, 
	extract_data = raw_to_data, 
	verbose::Bool=true, 
	kwargs...)

Run Unfold analysis on all data in dataDF.

Keywords

• eventcolumn::String = "event"
  Which collumn Unfold should use during the analysis.
• remove_time_expanded_Xs::Bool = true
  Removes the timeexpanded designmatrix which significantly reduces the memory-consumption. This Xs is rarely needed, but can be recovered (look into the Unfold.load function)
• extract_data::function = raw_to_data
  Specify the function that translate the MNE Raw object to an data array. Default is raw_to_data which uses get_data and allows to pick channels - see @Ref(raw_to_data). The optional kw- arguments (e.g. channels) need to be specified directly in the run_unfold function as kw-args
• verbose::Bool = true)
  Show ProgressBar or not.

save_results(results::DataFrame, bids_root::String; 
    derivatives_subfolder::String="Unfold",
    overwrite::Bool=false)

Function to save unfold models in your BIDS root folder. Automatically creates a derivatives_subfolder (default = "Unfold") in the derivatives and subsequentely safes each model in results according to BIDS. Example of path so saved file: bids_root/derivatives/Unfold/sub-XXX/eeg/sub-XXX_ses-XX_task-XXX_run-XX_unfold.jld2

Keywords

• derivatives_subfolder::String = "Unfold"
  Creates the named subfolder and saves Unfold models according to BIDS.
• overwrite::Bool = false
  Does not overwrite existing datasets; can be set to true.

unpack_events(df::DataFrame)

Unpack events into tidy data frame; useful with AlgebraOfGraphics.jl

df is expected to be a UnfoldBIDS DataFrame where events are loaded already.

unpack_results(results_df)

Unpack all results into one tidy dataframe/ coeftable.