RelativeAxis(fig, p::NTuple{4, Float64}; kwargs...)

Returns an Axis whose position is relative to a GridLayout element (via BBox) and not relative to the Scene. Default behavior is Axis(..., bbox = BBox()).

• p::NTuple{4,Float64}: specify the position relative to the GridPosition left:right; bottom:top, typical numbers between 0 and 1, e.g. (0.25, 0.75, 0.25, 0.75) would center an Axis inside this GridPosition.

• kwargs... - inserted into the axis.

  f = Figure() ax = RelativeAxis(f[1, 2], (0.25, 0.75, 0.25, 0.75)# returns Axis centered within f[1, 2]

Return Value: Axis.

 eeg_topoplot_series(data::DataFrame,
    fig,
    data_inp::Union{<:Observable,<:AbstractMatrix};
    layout = nothing,
    xlabels = nothing,
    labels = nothing,
    rasterize_heatmaps = true,
    interactive_scatter = nothing,
    highlight_scatter = false,
    topo_axis = (;),
    topo_attributes = (;),
    positions,
)
eeg_topoplot_series!(fig, data::DataFrame; kwargs..)

Plot a series of topoplots. The function takes the combinefun = mean over the :time column of data.

• fig
  Figure object.
  
• data::Union{<:Observable,<:AbstractMatrix}
  Matrix with size = (nchannel, ntopoplots).
• layout::Vector{Tuple{Int64, Int64}}
  Vector of tuples with coordinates for each topoplot.
• xlabels::Vector{String}
  Vector of xlabels for each topoplot.
• topo_axis::NamedTuple = (;)
  Here you can flexibly change configurations of the topoplot axis.
  To see all options just type ?Axis in REPL.
  Defaults: (aspect = 1, title = "", xgridvisible = false, xminorgridvisible = false, xminorticksvisible = false, xticksvisible = false, xticklabelsvisible = false, xlabelvisible = true, ygridvisible = false, yminorgridvisible = false, yminorticksvisible = false, yticksvisible = false, yticklabelsvisible = false, ylabelvisible = false, leftspinevisible = false, rightspinevisible = false, topspinevisible = false, bottomspinevisible = false, xpanlock = true, ypanlock = true, xzoomlock = true, yzoomlock = true, xrectzoom = false, yrectzoom = false)
• topo_attributes::NamedTuple = (;)
  Here you can flexibly change configurations of the topoplot interoplation.
  To see all options just type ?Topoplot.topoplot in REPL.
  Defaults: interp_resolution = (128, 128), interpolation = CloughTocher().
• positions::Vector{Point{2, Float32}}
  Channel positions. The list of x and y positions for all unique electrodes.

Return Value: Tuple{Figure, Vector{Any}}.

config_kwargs!(cfg::PlotConfig; kwargs...)

Takes NamedTuple of Key => NamedTuple as kwargs and merges the fields with the defaults.

eeg_array_to_dataframe(data::AbstractMatrix, label_aliases::AbstractVector)
eeg_array_to_dataframe(data::AbstractVector, label_aliases::AbstractVector)
eeg_array_to_dataframe(data::Union{AbstractMatrix, AbstractVector{<:Number}})

Helper function converting an array (Matrix or Vector) to a tidy DataFrame with columns :estimate, :time and :label (with aliases :color, :group, :channel).

Format of Arrays:
- times x condition for plot_erp.
- channels x time for plot_butterfly, plot_topoplotseries.
- channels for plot_topoplot.
Return Value: DataFrame.

rel_to_abs_bbox(org, rel)

Takes a rectangle org consiting of coordinates of origins and applies the relative transformation tuple rel.

Return Value: Makie.BBox.

to_positions(x, y, z; sphere = [0, 0, 0.])
to_positions(pos::AbstractMatrix; sphere = [0, 0, 0.])

Projects 3D electrode positions to a 2D layout. Reimplementation of the MNE algorithm.

Assumes size(pos) = (3, nChannels) when input is AbstractMatrix.

Tip: You can get positions directly from an MNE object after loading PyMNE and enabling the UnfoldMakie PyMNE extension.

Return Value: Vector{Point2{Float64}}.

data_binning(df; col_y = :erp, fun = mean, grouping = [])

Group DataFrame according to topoplot coordinates and apply aggregation function.

Arguments:

• df::AbstractTable
  Requires columns :cont_cuts, col_y (default :erp), and all columns in grouping (col_coord, row_coord, label);
• col_y = :erp
  The column to combine over (with fun);
• fun = mean()
  Function to combine.
• grouping = []
  Vector of symbols or strings, columns to group by the data before aggregation. Values of nothing are ignored.

Return Value: DataFrame.

cart3d_to_spherical(x, y, z)

Convert x, y, z electrode positions on a scalp to spherical coordinate representation.

Return Value: Matrix.