From 6811cb0a6b44ee44cfd672630a228875eca10b92 Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Thu, 16 Nov 2023 18:52:28 +0000 Subject: [PATCH] build based on ca00f27 --- dev/.documenter-siteinfo.json | 2 +- dev/api/index.html | 20 +++++++++---------- dev/generated/reference/positions/index.html | 2 +- dev/generated/tutorials/circTopo/index.html | 12 +++++------ dev/generated/tutorials/erp/index.html | 16 +++++++-------- dev/helper/index.html | 4 ++-- dev/how_to/fix_pcp/index.html | 2 +- dev/how_to/hide_deco/index.html | 2 +- dev/how_to/mult_vis_in_fig/index.html | 17 ++++++++-------- dev/how_to/position2color/6d76388c-001.png | Bin 211163 -> 0 bytes dev/how_to/position2color/6d76388c-002.png | Bin 211163 -> 0 bytes dev/how_to/position2color/6d76388c-003.png | Bin 211163 -> 0 bytes dev/how_to/position2color/bba4123c.png | Bin 0 -> 143640 bytes dev/how_to/position2color/f1d27af4.png | Bin 0 -> 214610 bytes dev/how_to/position2color/f8de3e8a.png | Bin 0 -> 226051 bytes dev/how_to/position2color/index.html | 6 ++++-- dev/how_to/show_oob_labels/index.html | 2 +- dev/index.html | 2 +- dev/search_index.js | 2 +- dev/tutorials/butterfly/index.html | 4 ++-- dev/tutorials/designmatrix/index.html | 4 ++-- dev/tutorials/erpimage/1406632e.png | Bin 0 -> 148771 bytes dev/tutorials/erpimage/index.html | 19 +++++++++++++----- dev/tutorials/installation/index.html | 2 +- dev/tutorials/parallelcoordinates/index.html | 4 ++-- dev/tutorials/topoplot/index.html | 2 +- dev/tutorials/topoplotseries/index.html | 6 +++--- 27 files changed, 71 insertions(+), 59 deletions(-) delete mode 100644 dev/how_to/position2color/6d76388c-001.png delete mode 100644 dev/how_to/position2color/6d76388c-002.png delete mode 100644 dev/how_to/position2color/6d76388c-003.png create mode 100644 dev/how_to/position2color/bba4123c.png create mode 100644 dev/how_to/position2color/f1d27af4.png create mode 100644 dev/how_to/position2color/f8de3e8a.png create mode 100644 dev/tutorials/erpimage/1406632e.png diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index f3ef33590..920466587 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.9.3","generation_timestamp":"2023-11-14T16:28:28","documenter_version":"1.1.2"}} \ No newline at end of file +{"documenter":{"julia_version":"1.9.4","generation_timestamp":"2023-11-16T18:52:23","documenter_version":"1.1.2"}} \ No newline at end of file diff --git a/dev/api/index.html b/dev/api/index.html index baa1cd713..f4d7bf2d8 100644 --- a/dev/api/index.html +++ b/dev/api/index.html @@ -1,13 +1,13 @@ -API · UnfoldMakie.jl
UnfoldMakie.df_timebin — Method

function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins

  • df AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;
  • Δbin bin size in :time units;
  • col_y default :erp, the column to combine over (with fun);
  • fun function to combine, default is mean;
  • grouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.
source
UnfoldMakie.eeg_topoplot_series — Method

function eegtopoplotseries(data::DataFrame, Δbin; y=:estimate, label=:label, col=:time, row=nothing, figure = NamedTuple(), combinefun=mean, rowlabels = false, collabels = false, topoplot_attributes... )

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

  • The data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).
  • Δbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.
  • The col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful

to split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.

  • The figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).
  • row_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).

Examples

Desc

julia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data
+API · UnfoldMakie.jl
UnfoldMakie.df_timebin — Method
function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins
  • df AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;
  • Δbin bin size in :time units;
  • col_y default :erp, the column to combine over (with fun);
  • fun function to combine, default is mean;
  • grouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.
source
UnfoldMakie.eeg_topoplot_series — Method
function eegtopoplotseries(data::DataFrame,     Δbin;     y=:estimate,     label=:label,     col=:time,     row=nothing,     figure = NamedTuple(),     combinefun=mean,     rowlabels = false,     collabels = false,     topoplot_attributes...     )
Plot a series of topoplots. The function automatically takes the combinefun=mean over the :time column of data in Δbin steps.
  • The data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).
  • Δbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.
  • The col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful
to split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.
  • The figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).
  • row_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).
Examples
Desc
julia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data
 julia > pos = [(1:63) ./ 63 .* (sin.(range(-2 * pi, 2 * pi, 63))) (1:63) ./ 63 .* cos.(range(-2 * pi, 2 * pi, 63))] .* 0.5 .+ 0.5 # fake electrode positions
 julia > pos = [Point2.(pos[k, 1], pos[k, 2]) for k in 1:size(pos, 1)]
-julia > eeg_topoplot_series(df, 5; positions=pos)
source
UnfoldMakie.plot_butterfly — Method
Plot Butterfly
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = NamedTuple() - use kwargs... of  Makie.Axis 
layout = (showLegend = false, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t))  
mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:channel, :channels, :trial, :trials), positions = (:pos, :positions, :position, :topoPositions, :x, nothing), labels = (:labels, :label, :topoLabels, :sensor, nothing))  
visual = (colormap = :roma,) - use kwargs... of $Makie.lines$ 
legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  AlgebraOfGraphics.colobar! 
key-word arguments
  • topomarkersize (Real, 10) - change the size of the markers, topoplot-inlay electrodes
  • topowidth (Real, 0.25) - change the size of the inlay topoplot width
  • topoheigth (Real, 0.25) - change the size of the inlay topoplot height
see also plot_erp
source
UnfoldMakie.plot_circulareegtopoplot — Method
plot_circulareegtopoplot(plotData::DataFrame; kwargs...)
-plot_circulareegtopoplot!(figlike, plotData::DataFrame; kwargs...)
Plot a circular EEG topoplot.
Arguments:
  • figlike::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into
  • plotData::DataFrame: Dataframe with keys for data (looks for :y,:yhat, :estimate, and :position (looks for :pos, :positions, :position), 
  • predictor (optional; default :predictor) the circular predictor value, defines position of topoplot, is mapped around predictorBounds
  • predictorBounds: Default: [0,360] - The bounds of the predictor. This is relevant for the axis labels.
  • centerlabel: default "", the text in the center of the cricle
  • positions (nothing) - positions for the plot_topoplot
  • labels (nothing) - labels for the plot_topoplot
  • kwargs...: Additional styling behavior, see below.
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = (aspect = Makie.DataAspect(), label = "") - use kwargs... of  Makie.Axis 
layout = (showLegend = false, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ())  
mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing))  
visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* 
legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false, label = "Voltage [µV]", colormap = Makie.Reverse{Symbol}(:RdBu)) - use kwargs... of  Makie.Colorbar 
Return Value:
A figure containing the circular topoplot at given layout position
source
UnfoldMakie.plot_designmatrix — Method
plot_designmatrix!(f::Union{GridPosition, GridLayout, Figure}, plotData::Unfold.DesignMatrix; kwargs...)
-plot_designmatrix(plotData::Unfold.DesignMatrix; kwargs...)
Plot a designmatrix. 
Arguments:
  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.
  • plotData::Unfold.DesignMatrix: Data for the plot visualization.
kwargs
  • standardizeData: (bool,true) - Indicating whether the data is standardized by pointwise division of the data with its sampled standard deviation.
  • sortData: (bool, true) - Indicating whether the data is sorted; using sortslices() of Base Julia. 
  • xTicks: (nothing) 
Indicating the number of labels on the x-axis. Behavior if specified in configuration:
  • xTicks = 0: no labels are placed.
  • xTicks = 1: first possible label is placed.
  • xTicks = 2: first and last possible labels are placed.
  • 2 < xTicks < number of labels: Equally distribute the labels.
  • xTicks ≥ number of labels: all labels are placed.
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = (xticklabelrotation = 0.39269908169872414,) - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true)  
mapping = (x = (:time,), y = (:estimate, :yhat, :y))  
visual = (colormap = :roma,) - use kwargs... of $Makie.heatmap$ 
legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Colorbar 
Return Value:
A figure displaying the designmatrix. 
source
UnfoldMakie.plot_erp — Method
plot_erp!(f::Union{GridPosition, GridLayout, Figure}, plotData::DataFrame; kwargs...)
-plot_erp(plotData::DataFrame; kwargs...)
Plot an ERP plot.
Arguments:
  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into
  • plotData::DataFrame: Data for the line plot visualization.
  • kwargs...: Additional styling behavior. Often used: plot_erp(df; mapping=(; color=:coefname, col=:conditionA))
kwargs (...; ...):
  • categoricalColor (bool, true) - Indicates whether the column referenced in mapping.color should be used nonnumerically.
  • categoricalGroup (bool, true) - Indicates whether the column referenced in mapping.group should be used nonnumerically.
  • topoLegend (bool, false) - Indicating whether a topo plot is used as a legend.
  • stderror (bool, false) - Indicating whether the plot should show a colored band showing lower and higher estimates based on the stderror. 
  • pvalue (Array, []) - example: DataFrame(from=[0.1,0.3], to=[0.5,0.7], coefname=["(Intercept)", "condition:face"]) -  if coefname not specified, the lines will be black
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = NamedTuple() - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t))  
mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing))  
visual = (colormap = :roma,) - use kwargs... of $Makie.lines$ 
legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  AlgebraOfGraphics.colobar! 
Return Value:
  • f - Figure() or the inputed f
source
UnfoldMakie.plot_new — Method
plot_new() -> String
-
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = NamedTuple() - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t))  
mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing))  
visual = (colormap = :roma,) - use kwargs... of $Makie.lines$ 
legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  AlgebraOfGraphics.colobar! 
source
UnfoldMakie.plot_parallelcoordinates — Method
plot_parallelcoordinates!(f::Union{GridPosition, GridLayout, Figure}, 
-    plotData::DataFrame, config::PlotConfig; channels::Vector{Int64})
Plot a PCP (parallel coordinates plot).
Arguments:
  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into
  • plotData::DataFrame: Data for the plot visualization.
  • config::PlotConfig: Instance of PlotConfig being applied to the visualization.
  • channels::Vector{Int64}: vector with all the channels representing an axis used in the PCP in given order.
PCP has problems with size changes of the view window. By adapting the padding, aspect ratio and tick label size in px for a new use case, the PCP can even be added into a Coordinated Multiple Views System
  • pc_aspect_ratio  Default : 0.55
  • pc_right_padding  Default : 15
  • pc_left_padding  Default : 25
  • pc_top_padding  Default : 26
  • pc_bottom_padding  Default : 16
  • pc_tick_label_size  Default : 14
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = NamedTuple() - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :channel, ylabelFromMapping = :y, useColorbar = false, hidespines = (), hidedecorations = (label = false,))  
mapping = (x = (:time,), y = (:estimate, :yhat, :y), channel = :channel, category = :category, time = :time)  
visual = (colormap = :roma,) - use kwargs... of $Makie.lines$ 
legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Colorbar 
Return Value:
The input f
source
UnfoldMakie.plot_topoplot — Method
plot_topoplot!(f::Union{GridPosition, GridLayout, Figure}, plotData, ; positions=nothing, labels=nothing,kwargs...)
-plot_topoplot(plotData,; positions=nothing, labels=nothing, kwargs...)
Plot a topo plot.
Arguments:
  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.
  • plotData::Union{DataFrame, Vector{Float32}}: Data for the plot visualization.
  • positions::Vector{Point{2, Float32}}=nothing: positions used if plotData is no DataFrame. If this is the case and positions=nothing then positions is generated from labels.
  • labels::Vector{String}=nothing: labels used if plotData is no DataFrame.
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = (aspect = Makie.DataAspect(),) - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ())  
mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing))  
visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* 
legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Colorbar 
Return Value:
A figure displaying the topo plot.
source
UnfoldMakie.plot_topoplotseries — Method
plot_topoplotseries!(f::Union{GridPosition, GridLayout, Figure}, plotData::DataFrame, Δbin::Real; kwargs...)
-plot_topoplotseries!(plotData::DataFrame, Δbin::Real; kwargs...)
Multiple miniature topoplots in regular distances 
Arguments:
  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into
  • plotData::DataFrame: DataFrame with data, needs a time column
  • Δbin::Real: A number for how large one bin should be. Δbin is in units of the plotData.time column
  • combinefun (default mean) can be used to specify how the samples within Δbin are combined.
  • rasterize_heatmaps (deault true) - enforce rasterization of the plot heatmap when saving in svg format.
This has the benefit that all lines/points are vectors, except the interpolated heatmap.   This is typically what you want, because else you get ~500x500 vectors per topoplot, which makes everything super slow.
  • col_labels, row_labels - shows column and row labels. 
Shared plot configuration options
The shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.
figure = NamedTuple() - use kwargs... of Makie.Figure 
axis = (aspect = Makie.DataAspect(),) - use kwargs... of  Makie.Axis 
layout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ())  
mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing), col = (:time,), row = (nothing,))  
visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = false, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* 
legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of  Makie.Legend 
colorbar = (vertical = true, tellwidth = true, tellheight = false, height = 300, flipaxis = true, labelrotation = 4.7, label = "Voltage [µV]") - use kwargs... of  Makie.Colorbar 
Return Value:
The input f
source
UnfoldMakie.to_positions — Method
topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.
The matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.
Tipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension
source
Internally, we use a PlotConfig struct to keep track of common plot options, in order to have a similar API to all functions
UnfoldMakie.PlotConfig — Type
PlotConfig(<plotname>)
-holds various different fields, that can modify various different plotting aspects.
source

+julia > eeg_topoplot_series(df, 5; positions=pos)
source
UnfoldMakie.plot_butterfly — Method

Plot a butterfly plot

kwargs (...; ...):

  • butterfly (bool, true): create a butterfly plot.
  • topolegend (bool, true): show an inlay topoplot with corresponding electrodes.
  • topomarkersize (Real, 10): change the size of the markers, topoplot-inlay electrodes.
  • topowidth (Real, 0.25): change the size of the inlay topoplot width.
  • topoheigth (Real, 0.25): change the size of the inlay topoplot height.
  • topopositions_to_color (function, ´x -> posToColorRomaO(x)´).

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = NamedTuple() - use kwargs... of Makie.Axis

layout = (showlegend = false, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t))

mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:channel, :channels, :trial, :trials), positions = (:pos, :positions, :position, :topo_positions, :x, nothing), labels = (:labels, :label, :topoLabels, :sensor, nothing))

visual = (colormap = :roma,) - use kwargs... of $Makie.lines$

legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar!

see also plot_erp

source
UnfoldMakie.plot_circulareegtopoplot — Method
plot_circulareegtopoplot(data::DataFrame; kwargs...)
+plot_circulareegtopoplot!(f, data::DataFrame; kwargs...)

Plot a circular EEG topoplot.

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure, GridLayout or GridPosition that the plot should be drawn into

  • data::DataFrame: DataFrame with keys for data (looks for :y, :yhat, :estimate), and :position (looks for :pos, :position, :positions),

  • predictor (optional; default: predictor): the circular predictor value, defines position of topoplot, is mapped around predictor_bounds

  • predictor_bounds (default: [0,360]): the bounds of the predictor. This is relevant for the axis labels.

  • positions (default: nothing): positions for the plot_topoplot

  • center_label (default: ""): the text in the center of the cricle

  • labels (default: nothing): labels for the plot_topoplot

  • kwargs...: additional styling behavior, see below.

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = (aspect = Makie.DataAspect(), label = "") - use kwargs... of Makie.Axis

layout = (showlegend = false, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ())

mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing))

visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)*

legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false, label = "Voltage [µV]", colormap = Makie.Reverse{Symbol}(:RdBu)) - use kwargs... of Makie.Colorbar

Return Value:

A figure containing the circular topoplot at given layout position

source
UnfoldMakie.plot_designmatrix — Method
plot_designmatrix!(f::Union{GridPosition, GridLayout, Figure}, data::Unfold.DesignMatrix; kwargs...)
+plot_designmatrix(data::Unfold.DesignMatrix; kwargs...)

Plot a designmatrix.

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) in which the plot will be placed into. A new axis is created.
  • data::Unfold.DesignMatrix: data for the plot visualization.

kwargs

  • standardize_data (bool,true): indicates whether the data is standardized by pointwise division of the data with its sampled standard deviation.
  • sort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia.
  • xticks (nothing): returns the number of labels on the x-axis. Behavior is set in the configuration:
    • xticks = 0: no labels are placed.
    • xticks = 1: first possible label is placed.
    • xticks = 2: first and last possible labels are placed.
    • 2 < xticks < number of labels: equally distribute the labels.
    • xticks ≥ number of labels: all labels are placed.

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = (xticklabelrotation = 0.39269908169872414,) - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true)

mapping = (x = (:time,), y = (:estimate, :yhat, :y))

visual = (colormap = :roma,) - use kwargs... of $Makie.heatmap$

legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar

Return Value:

A figure displaying the designmatrix.

source
UnfoldMakie.plot_erp — Method
plot_erp!(f::Union{GridPosition, GridLayout, Figure}, plot_data::DataFrame; kwargs...)
+plot_erp(plot_data::DataFrame; kwargs...)

Plot an ERP plot.

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure, GridLayout or GridPosition that the plot should be drawn into.
  • plot_data::DataFrame: Data for the line plot visualization.
  • kwargs...: Additional styling behavior. Often used: plot_erp(df; mapping=(; color=:coefname, col=:conditionA)).

kwargs (...; ...):

  • categorical_color (bool, true): in case of numeric :color column, treat :color as continuous or categorical variable.
  • categorical_group (bool, true): in case of numeric :group column, treat :group as categorical variable by default.
  • topolegend (bool, false): add an inlay topoplot with corresponding electrodes.
  • stderror (bool, false): add an error ribbon, with lower and upper limits based on the :stderror column.
  • pvalue (Array, []): show a pvalue.
    • example: DataFrame(from=[0.1, 0.3], to=[0.5, 0.7], coefname=["(Intercept)", "condition:face"]) - if coefname is not specified, the lines will be black

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = NamedTuple() - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t))

mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing))

visual = (colormap = :roma,) - use kwargs... of $Makie.lines$

legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar!

Return Value:

  • f - Figure() or the inputed f
source
UnfoldMakie.plot_new — Method
plot_new() -> String
+

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = NamedTuple() - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t))

mapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing))

visual = (colormap = :roma,) - use kwargs... of $Makie.lines$

legend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar!

source
UnfoldMakie.plot_parallelcoordinates — Method
plot_parallelcoordinates!(f::Union{GridPosition, GridLayout, Figure}, 
+    data::DataFrame, config::PlotConfig; channels::Vector{Int64})

Plot a PCP (parallel coordinates plot).

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.
  • data::DataFrame: data for the plot visualization.
  • config::PlotConfig: instance of PlotConfig being applied to the visualization.
  • channels::Vector{Int64}: vector with all the channels representing an axis used in the PCP in given order.

PCP has problems with size changes of the view window. By adapting the padding, aspect ratio and tick label size in px for a new use case, the PCP can even be added into a complex figures.

  • pc_aspect_ratio (default: 0.55) -
  • pc_right_padding (default: 15) -
  • pc_left_padding (default: 25) -
  • pc_top_padding (default: 26) -
  • pc_bottom_padding (default: 16) -
  • pc_tick_label_size (default: 14) -

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = NamedTuple() - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = :channel, ylabelFromMapping = :y, use_colorbar = false, hidespines = (), hidedecorations = (label = false,))

mapping = (x = (:time,), y = (:estimate, :yhat, :y), channel = :channel, category = :category, time = :time)

visual = (colormap = :roma,) - use kwargs... of $Makie.lines$

legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar

Return Value:

The input f

source
UnfoldMakie.plot_topoplot — Method
plot_topoplot!(f::Union{GridPosition, GridLayout, Figure}, data, ; positions=nothing, labels=nothing,kwargs...)
+plot_topoplot(data,; positions=nothing, labels=nothing, kwargs...)

Plot a topo plot.

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.
  • data::Union{DataFrame, Vector{Float32}}: data for the plot visualization.
  • positions::Vector{Point{2, Float32}}=nothing: positions used if data is not a DataFrame. If this is the case and positions=nothing then positions are generated from labels.
  • labels::Vector{String} = nothing: labels used if data is not a DataFrame.

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ())

mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing))

visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)*

legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar

Return Value:

A figure displaying the topo plot.

source
UnfoldMakie.plot_topoplotseries — Method
plot_topoplotseries!(f::Union{GridPosition, GridLayout, Figure}, data::DataFrame, Δbin::Real; kwargs...)
+plot_topoplotseries!(data::DataFrame, Δbin::Real; kwargs...)

Multiple miniature topoplots in regular distances

Arguments:

  • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.
  • data::DataFrame: DataFrame with data, needs a time column.
  • Δbin::Real: A number for how large one time bin should be. Δbin is in units of the data.time column.
  • combinefun (default: mean) - can be used to specify how the samples within Δbin are combined.
  • rasterize_heatmaps (default: true) - enforce rasterization of the plot heatmap when saving in svg format. This has the benefit that all lines/points are vectors, except the interpolated heatmap. This is typically what you want, otherwise you get ~500x500 vectors per topoplot, which makes everything super slow.
  • col_labels, row_labels - shows column and row labels.
  • labels (default: nothing) - .
  • positions (default: nothing) - .

Shared plot configuration options

The shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.

figure = NamedTuple() - use kwargs... of Makie.Figure

axis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis

layout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ())

mapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing), col = (:time,), row = (nothing,))

visual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = false, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)*

legend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend

colorbar = (vertical = true, tellwidth = true, tellheight = false, height = 300, flipaxis = true, labelrotation = 4.7, label = "Voltage [µV]") - use kwargs... of Makie.Colorbar

Return Value:

The input f

source
UnfoldMakie.to_positions — Method

topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.

The matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.

Tipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension

source

Internally, we use a PlotConfig struct to keep track of common plot options, in order to have a similar API to all functions

UnfoldMakie.PlotConfig — Type
PlotConfig(<plotname>)
+holds various different fields, that can modify various different plotting aspects.
source
diff --git a/dev/generated/reference/positions/index.html b/dev/generated/reference/positions/index.html index 0740eee89..ce4a4771e 100644 --- a/dev/generated/reference/positions/index.html +++ b/dev/generated/reference/positions/index.html @@ -39,4 +39,4 @@ f = Figure(resolution=(600,300)) scatter(f[1,1],pos3d[1:2,:]) scatter(f[1,2],pos2) -fExample block output

as one can see, the "naive" transform of just dropping the third dimension doesnt really work (left). We rather have to project the chanels to a sphere and unfold it (right)

This page was generated using Literate.jl.

+fExample block output

as one can see, the "naive" transform of just dropping the third dimension doesnt really work (left). We rather have to project the chanels to a sphere and unfold it (right)

This page was generated using Literate.jl.

diff --git a/dev/generated/tutorials/circTopo/index.html b/dev/generated/tutorials/circTopo/index.html index 545a06ffa..5e0ed91f6 100644 --- a/dev/generated/tutorials/circTopo/index.html +++ b/dev/generated/tutorials/circTopo/index.html @@ -7,18 +7,18 @@ dat = data[:, 240, 1] df = DataFrame( :estimate => eachcol(Float64.(data[:, 100:40:300, 1])), - :circularVariable => [0, 50, 80, 120, 180, 210], + :circular_variable => [0, 50, 80, 120, 180, 210], :time => 100:40:300, ) -df = flatten(df, :estimate);

Our first plot!

note how the plots are at the angles of circularVariable`

plot_circulareegtopoplot(
+df = flatten(df, :estimate);

Our first plot!

note how the plots are at the angles of circular_variable`

plot_circulareegtopoplot(
     df;
     positions = pos,
-    axis = (; label = "Sac Incoming"),
-    predictor = :circularVariable,
+    axis = (; label = "Incoming saccade"),
+    predictor = :circular_variable,
 )
Example block output

In case the bounding variable is not between 0 and 360, as here we use actually time, we have to specify it. e.g.

plot_circulareegtopoplot(
     df;
     positions = pos,
     axis = (; label = "Time?!"),
     predictor = :time,
-    predictorBounds = [80, 320],
-)
Example block output

This page was generated using Literate.jl.

+ predictor_bounds = [80, 320], +)Example block output

This page was generated using Literate.jl.

diff --git a/dev/generated/tutorials/erp/index.html b/dev/generated/tutorials/erp/index.html index 5edeecc57..e1ea6aa7d 100644 --- a/dev/generated/tutorials/erp/index.html +++ b/dev/generated/tutorials/erp/index.html @@ -1,11 +1,11 @@ -ERP plot · UnfoldMakie.jl

Line Plot Visualization

Here we discuss line plot visualization. Make sure you have looked into the installation instructions.

Include used Modules

The following modules are necessary for following this tutorial:

using Unfold
+ERP plot · UnfoldMakie.jl
Line Plot Visualization
Here we discuss ERP plot visualization. Make sure you have looked into the installation instructions.
Include used Modules
The following modules are necessary for following this tutorial:
using Unfold
 using UnfoldMakie
 using DataFrames
 using CairoMakie
 using DataFramesMeta
 using UnfoldSim
-using UnfoldMakie
Setup
Let's generate some data and fit a model of a 2-level categorical and a continuous predictor with interaction.
data, evts = UnfoldSim.predef_eeg(; noiselevel = 12, return_epoched = true)
+using UnfoldMakie
Setup
Let's generate some data. We'll fit a model with a 2 level categorical predictor and a continuous predictor with interaction.
data, evts = UnfoldSim.predef_eeg(; noiselevel = 12, return_epoched = true)
 data = reshape(data, (1, size(data)...))
 f = @formula 0 ~ 1 + condition + continuous
 se_solver = (x, y) -> Unfold.solver_default(x, y, stderror = true);
@@ -19,15 +19,15 @@
 )
 results = coeftable(m)
 res_effects = effects(Dict(:continuous => -5:0.5:5), m);
┌ Warning: Autocorrelation was NOT taken into account. Therefore SE are UNRELIABLE. Use at your own discretion
-└ @ Unfold ~/.julia/packages/Unfold/LwbaS/src/solver.jl:75
Plot the results
plot_erp(results; :stderror => true,)
Example block output
Column Mappings for Line Plots
plot_erp use a DataFrame as an input, the library needs to know the names of the columns used for plotting.
There are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name can be chosen using plot_erp(...;mapping=(; :y=:myEstimate)
:x Default is (:x, :time). :y Default is (:y, :estimate, :yhat). :color Default is (:color, :coefname).
Configuration for Line Plots
key values
plot_erp(...; <name>=<value>,...).
  • categoricalColor (boolean, true) - in case of numeric :color column, is color a continuous or categorical variable?
  • categoricalGroup (boolean, true) - in case of numeric :group column, treat :group as categorical variable by default
  • stderror (boolean, false) - add an error-ribbon based on the :stderror column
  • pvalue (see below)
Using some general configurations we can pretty up the default visualization. Here we use the following configuration:
plot_erp(
+└ @ Unfold ~/.julia/packages/Unfold/LwbaS/src/solver.jl:75
Plot the results
plot_erp(results; :stderror => true,)
Example block output
Column Mappings for Line Plots
plot_erp use a DataFrame as an input, the library needs to know the names of the columns used for plotting.
There are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name can be chosen using plot_erp(...; mapping=(; :y=:my_estimate)
:x Default is (:x, :time). :y Default is (:y, :estimate, :yhat). :color Default is (:color, :coefname).
Configuration for Line Plots
key values
plot_erp(...; <name>=<value>,...).
  • categorical_color (boolean, true) - in case of numeric :color column, treat :color as continuous or categorical variable.
  • categorical_group (boolean, true) - in case of numeric :group column, treat :group as categorical variable by default.
  • topolegend (bool, false): add an inlay topoplot with corresponding electrodes.
  • stderror (bool, false): add an error ribbon, with lower and upper limits based on the :stderror column.
  • pvalue (Array, []): show a pvalue (see below).
Using some general configurations we can pretty up the default visualization. Here we use the following configuration:
plot_erp(
     res_effects;
     mapping = (; y = :yhat, color = :continuous, group = :continuous),
     legend = (; nbanks = 2),
-    layout = (; showLegend = true, legendPosition = :right),
-    categoricalColor = false, categoricalGroup = true,
-)
Example block output
In the following we will use this "pretty" line plot as a basis for looking into configuration options.
pvalue (array)
Important
this is currently broken!
Is an array of p-values. If array not empty, plot shows colored lines under the plot representing the p-values. Default is [] (an empty array). Shown below is an example in which pvalue are given: pvals = DataFrame(
#		from=[0.1,0.3],
+    layout = (; showLegend = true, legend_position = :right),
+    categorical_color = false, categorical_group = true,
+)
Example block output
In the following we will use this "pretty" line plot as a basis for looking into configuration options.
pvalue (array)
Important
this is currently broken!
Is an array of p-values. If array not empty, plot shows colored lines under the plot representing the p-values. Default is [] (an empty array). Below is an example in which pvalue are given: pvals = DataFrame(
#		from=[0.1,0.3],
 #		to=[0.5,0.7],
-#		coefname=["(Intercept)","condition: face"] # if coefname not specified, line should be black
+#		coefname=["(Intercept)", "condition: face"] # if coefname not specified, line should be black
 #	)
plot_erp(results; :pvalue=>pvals)
stderror (boolean)
Indicating whether the plot should show a colored band showing lower and higher estimates based on the stderror. Default is false.
previously we showed :stderror- but low/high is possible as well`
results.se_low = results.estimate .- 0.5
 results.se_high = results.estimate .+ 0.15
-plot_erp(select(results, Not(:stderror)); stderror = true)
Example block output
Note
as in the above code,:stderror has precedence over :se_low/:se_high
This page was generated using Literate.jl.

+plot_erp(select(results, Not(:stderror)); stderror = true)
Example block output
Note

as in the above code,:stderror has precedence over :se_low/:se_high

This page was generated using Literate.jl.

diff --git a/dev/helper/index.html b/dev/helper/index.html index 5e6813142..008c27f9c 100644 --- a/dev/helper/index.html +++ b/dev/helper/index.html @@ -1,5 +1,5 @@ -Utilities · UnfoldMakie.jl
UnfoldMakie.RelativeAxis — Type

ax = RelativeAxis(figlike, p::NTuple{4, Float64}; kwargs...)

Returns an axis which's position is relative to a GridLayout Element (via BBox) and not relative to the Scene (default Axis(..., bbox=BBox()) behavior)

p::NTuple{4,Float64}: Give the relative position to the GridPosition, left:right; bottom:up, typical numbers betwen 0 and 1. E.g. (0.25, 0.75, 0.25, 0.75) would center an Axis inside that GridPosition

kwargs... are pasted into Axis

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

source
UnfoldMakie.eeg_topoplot_series — Function

function eegtopoplotseries(data::DataFrame, Δbin; y=:estimate, label=:label, col=:time, row=nothing, figure = NamedTuple(), combinefun=mean, rowlabels = false, collabels = false, topoplot_attributes... )

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

  • The data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).
  • Δbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.
  • The col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful

to split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.

  • The figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).
  • row_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).

Examples

Desc

julia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data
+Utilities · UnfoldMakie.jl
UnfoldMakie.RelativeAxis — Type
ax = RelativeAxis(figlike, p::NTuple{4, Float64}; kwargs...)
Returns an axis which's position is relative to a GridLayout Element (via BBox) and not  relative to the Scene (default Axis(..., bbox=BBox()) behavior)
p::NTuple{4,Float64}: Give the relative position to the GridPosition, left:right; bottom:up,  typical numbers betwen 0 and 1. E.g. (0.25, 0.75, 0.25, 0.75) would center an Axis inside that GridPosition
kwargs... are pasted into Axis
f = Figure() ax = RelativeAxis(f[1,2], (0.25, 0.75, 0.25, 0.75))	 # returns Axis centered within f[1,2]
source
UnfoldMakie.eeg_topoplot_series — Function
function eegtopoplotseries(data::DataFrame,     Δbin;     y=:estimate,     label=:label,     col=:time,     row=nothing,     figure = NamedTuple(),     combinefun=mean,     rowlabels = false,     collabels = false,     topoplot_attributes...     )
Plot a series of topoplots. The function automatically takes the combinefun=mean over the :time column of data in Δbin steps.
  • The data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).
  • Δbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.
  • The col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful
to split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.
  • The figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).
  • row_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).
Examples
Desc
julia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data
 julia > pos = [(1:63) ./ 63 .* (sin.(range(-2 * pi, 2 * pi, 63))) (1:63) ./ 63 .* cos.(range(-2 * pi, 2 * pi, 63))] .* 0.5 .+ 0.5 # fake electrode positions
 julia > pos = [Point2.(pos[k, 1], pos[k, 2]) for k in 1:size(pos, 1)]
-julia > eeg_topoplot_series(df, 5; positions=pos)
source
UnfoldMakie.to_positions — Function
topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.
The matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.
Tipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension
source
UnfoldMakie.df_timebin — Function
function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins
  • df AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;
  • Δbin bin size in :time units;
  • col_y default :erp, the column to combine over (with fun);
  • fun function to combine, default is mean;
  • grouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.
source

+julia > eeg_topoplot_series(df, 5; positions=pos)
source
UnfoldMakie.to_positions — Function

topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.

The matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.

Tipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension

source
UnfoldMakie.df_timebin — Function

function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins

  • df AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;
  • Δbin bin size in :time units;
  • col_y default :erp, the column to combine over (with fun);
  • fun function to combine, default is mean;
  • grouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.
source
diff --git a/dev/how_to/fix_pcp/index.html b/dev/how_to/fix_pcp/index.html index 1676120c5..e89e7ca2d 100644 --- a/dev/how_to/fix_pcp/index.html +++ b/dev/how_to/fix_pcp/index.html @@ -8,4 +8,4 @@ pc_bottom_padding = 27, ...

Furthermore, if the tick-number size becomes too big or small it can be changed with:

...
 pc_tick_label_size = 25,
-...

By setting these manually through trial and error we can fix the visualization issues

+...

By setting these manually through trial and error we can fix the visualization issues

diff --git a/dev/how_to/hide_deco/index.html b/dev/how_to/hide_deco/index.html index da790b824..524ce40cf 100644 --- a/dev/how_to/hide_deco/index.html +++ b/dev/how_to/hide_deco/index.html @@ -13,4 +13,4 @@ layout=(; hidespines = nothing, hidedecorations = nothing - ),)Example block output + ),)Example block output diff --git a/dev/how_to/mult_vis_in_fig/index.html b/dev/how_to/mult_vis_in_fig/index.html index 40043a265..c89bad86e 100644 --- a/dev/how_to/mult_vis_in_fig/index.html +++ b/dev/how_to/mult_vis_in_fig/index.html @@ -14,7 +14,7 @@ d_singletrial, _ = UnfoldSim.predef_eeg(; return_epoched=true) times = -0.099609375:0.001953125:1.0 data, positions = TopoPlots.example_data()
┌ Warning: Autocorrelation was NOT taken into account. Therefore SE are UNRELIABLE. Use at your own discretion
-└ @ Unfold ~/.julia/packages/Unfold/LwbaS/src/solver.jl:75

This section discusses how users can incorporate multiple plots into a single figure.

By using the !-version of the plotting function and inserting a grid position instead of an entire figure, we can create multiple coordinated views.

We start by creating a figure with Makie.Figure.

f = Figure()

Now any plot can be added to f by placing a grid position, such as f[1, 1].

f = Figure()
+└ @ Unfold ~/.julia/packages/Unfold/LwbaS/src/solver.jl:75

This section discusses how users can incorporate multiple plots into a single figure.

By using the !-version of the plotting function and inserting a grid position instead of an entire figure, we can create multiple coordinated views.

We will start by creating a figure with Makie.Figure.

f = Figure()

Now any plot can be added to f by placing a grid position, such as f[1, 1].

f = Figure()
 plot_erp!(f[1, 1], coeftable(uf_deconv))
 plot_erp!(f[1, 2], effects(Dict(:condition => ["car", "face"]), uf_deconv),
     mapping=(; color=:condition))
@@ -31,8 +31,8 @@
     coefname=["(Intercept)", "category: face"]
 )
 plot_erp!(f[2, 1:2], results,
-    categoricalColor=false,
-    categoricalGroup=false,
+    categorical_color=false,
+    categorical_group=false,
     pvalue=pvals,
     stderror=true)
 
@@ -44,15 +44,16 @@
 
 res_effects = effects(Dict(:continuous => -5:0.5:5), uf_deconv)
 
-plot_erp!(f[2, 4:5], res_effects; categoricalColor=false, categoricalGroup=true,
+plot_erp!(f[2, 4:5], res_effects; categorical_color=false, categorical_group=true,
     mapping=(; y=:yhat, color=:continuous, group=:continuous),
     legend=(; nbanks=2),
-    layout=(; showLegend=true, legendPosition=:right))
+    layout=(; show_legend=true, legend_position=:right))
 
-plot_parallelcoordinates!(f[3, 2:3], uf_5chan, [1, 2, 3, 4, 5]; mapping=(; color=:coefname), layout=(; legendPosition=:bottom))
+plot_parallelcoordinates!(f[3, 2:3], uf_5chan, [1, 2, 3, 4, 5]; mapping=(; color=:coefname),
+    layout=(; legend_position=:bottom))
 
 plot_erpimage!(f[1, 4:5], times, d_singletrial)
 plot_circulareegtopoplot!(f[3:4, 4:5], d_topo[in.(d_topo.time, Ref(-0.3:0.1:0.5)), :];
-    positions=positions, predictor=:time, predictorBounds=[-0.3, 0.5])
+    positions=positions, predictor=:time, predictor_bounds=[-0.3, 0.5])
 
-f
Example block output +fExample block output diff --git a/dev/how_to/position2color/6d76388c-001.png b/dev/how_to/position2color/6d76388c-001.png deleted file mode 100644 index 1f4e8f90b159382d360cd18561925d8c6049af2d..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 211163 zcmce7Wmg?d)MXR$0KwfoxH|-QcXxMpx8M$eAVEWLcMt9m+}(n^J51-DHEaIBths!+ z+)L42RekEn-upx<%1a=?;=%#|fFLC)stf>-!~pO?6XpZ>4F);}CHMwqEF&Qby#M?8 z*=E<6ypsE%YaB*E2jblh9)ZcfeY1=0_&oJv|*Dqi0HaDSdayss& zr`M*pu-woF2`MIwVufw!t?wHE-^0X)$ke=lkL9xAcfKZsk9eQ$!O+bFPaJ|Q3_~(% zlzapH`z54<9ovxP-*;NrP@3RpWMRxO2+V(fNeDFx4E;C8)ad{1khBJ9O&fJO{W@bO zsrV27ZdnX)k@E%eeuQpkI3)R>8DhjVO#JV8C3FA3z5D;SWr8<)cY_V>+1N11Rs4P< zh%EeNT4^?R0%gitO$zBF$#(;6!`C8ebXX#yoNy$fr-ui_n9u|_SQ#b!PyW{w%x~L+ zldA0<`QgFHBUtd&Z*7T5Njz>xv%kHrixhIaeSDg178sbBYx1E(kw-*j5>r3(7fV6L zkIg6keMBPhPNz8(A_=()gP0Fcb#|_ek5{NOADge#g9AoW=#Lj`Ou`Wfmxq#ix-uq(US~d61UjY$xt5Tv_qTKebfC90 zC1J+e(C~jikFp~>QLZuoS^l1Rb6`D|&Tbx_!e|i3j43?-nN2H~0>Rz)YepXwuxe+D 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b/dev/how_to/position2color/index.html @@ -4,5 +4,7 @@ using DataFramesMeta using Colors

By default the plot looks like this:

include("../../example_data.jl")
 results, positions = example_data("TopoPlots.jl")
-plot_butterfly(results; positions=positions)
Example block output

We can switch the colorscale of the position-map, by giving a function that maps from a (x,y) tuple to a color. UnfoldMakie currently provides three different ones pos2colorRGB (same as MNE-Python), pos2colorHSV (HSV colorspace), pos2colorRomaO. Whereas RGB & HSV have the benefits of being 2D colormaps, Roma0 has the benefit of being perceptualy uniform.

Similar to MNE

plot_butterfly(results; positions=positions, extra=(; topoPositionToColorFunction = pos -> UnfoldMakie.posToColorRGB(pos)))
Example block output

HSV-Space

plot_butterfly(results; positions=positions, extra=(; topoPositionToColorFunction=UnfoldMakie.posToColorHSV))
Example block output

Uniform Color

To highlight the flexibility, we can also make all lines gray, or any other arbitrary color, or function of electrode-position.

using Colors
-plot_butterfly(results; positions=positions, extra=(; topoPositionToColorFunction = x -> Colors.RGB(0.5)))
Example block output +plot_butterfly(results; positions=positions)Example block output

We can switch the colorscale of the position-map, by giving a function that maps from a (x,y) tuple to a color. UnfoldMakie currently provides three different ones pos2colorRGB (same as MNE-Python), pos2colorHSV (HSV colorspace), pos2colorRomaO. Whereas RGB & HSV have the benefits of being 2D colormaps, Roma0 has the benefit of being perceptualy uniform.

Similar to MNE

plot_butterfly(results;
+    positions=positions,
+    topopositions_to_color = pos -> UnfoldMakie.posToColorRGB(pos)
+)
Example block output

HSV-Space

plot_butterfly(results; positions=positions, topopositions_to_color=UnfoldMakie.posToColorHSV)
Example block output

Uniform Color

To highlight the flexibility, we can also make all lines gray, or any other arbitrary color, or function of electrode-position.

plot_butterfly(results; positions=positions, topopositions_to_color = x -> Colors.RGB(0.5))
Example block output diff --git a/dev/how_to/show_oob_labels/index.html b/dev/how_to/show_oob_labels/index.html index cddea937b..64daccb3b 100644 --- a/dev/how_to/show_oob_labels/index.html +++ b/dev/how_to/show_oob_labels/index.html @@ -2,4 +2,4 @@ Show out of Bounds Label · UnfoldMakie.jl

Show out of Bounds Label

When visualizing a design matrix, it can happen that the labels on the y-axis get cut off to the left (especially if they are quite long). In the following, we will discuss a possible quick solution to this problem.

We start with the "label-limited" time-expanded designmatrix from the corresponding Tutorial section, which describes in detail how to generate it.

plot_designmatrix(designmatrix!(ufCont,evts), cDesign; xTicks=10, sortData=false)

While the plot automatically sets its height according to the labels, the labels are cut off on the left side.

A quick fix would be to place an empty plot to the left of the designmatrix.

By creating your own figure with Makie.Figure and then giving the designmatrix only a certain grid position, we get white space next to the plot.

The plot! function inside the plot config instance can take any grid position, and the figure f will contain the plot and enough white space next to it.

The exact numbers in the grid position can be guessed from the overlap ratio, or just tried.

f = Figure()
 plot_design(f[1,2:6], designmatrix!(ufCont, evts), cDesign; setExtraValues=(xTicks=10, sortData=false))
 
-f
+f diff --git a/dev/index.html b/dev/index.html index 3ed29fd61..8ccf8c002 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -UnfoldMakie Documentation · UnfoldMakie.jl

UnfoldMakie Documentation

This is the documentation of the UnfoldMakie module for the Julia programming language.

About

UnfoldMakie aims to allow users to create different types of visualizations. These include line plots, butterfly plots, design matrices, parallel coordinate plots, ERP images, and topo plots. Building on the Unfold and Makie Modules, it also allows users to customize the plots through an input configuration.

As can be seen from the types of visualizations possible, these configuration options try to enable the user to create plots that are helpful in the field of computational EEG. One such example is the ability to use a topo plot as a legend for a line plot by allowing multiple visualizations within a figure.

Coordinated Multiple Views

+UnfoldMakie Documentation · UnfoldMakie.jl

UnfoldMakie Documentation

This is the documentation of the UnfoldMakie module for the Julia programming language.

About

UnfoldMakie aims to allow users to create different types of visualizations. These include line plots, butterfly plots, design matrices, parallel coordinate plots, ERP images, and topo plots. Building on the Unfold and Makie Modules, it also allows users to customize the plots through an input configuration.

As can be seen from the types of visualizations possible, these configuration options try to enable the user to create plots that are helpful in the field of computational EEG. One such example is the ability to use a topo plot as a legend for a line plot by allowing multiple visualizations within a figure.

Coordinated Multiple Views

diff --git a/dev/search_index.js b/dev/search_index.js index ed8beb9b3..1475a51c7 100644 --- a/dev/search_index.js +++ b/dev/search_index.js @@ -1,3 +1,3 @@ var documenterSearchIndex = {"docs": -[{"location":"how_to/show_oob_labels/#ht_soobl","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"","category":"section"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"When visualizing a design matrix, it can happen that the labels on the y-axis get cut off to the left (especially if they are quite long). 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This leads to truncated edges of the PCP and unused space.","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Since the plot could have more space above and below, we can change the aspect ratio of the plot with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_aspect_ratio = 1,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"The cut off or overlap at each side can be fixed with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_right_padding = 15,\npc_left_padding = 45,\npc_top_padding = 50,\npc_bottom_padding = 27,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Furthermore, if the tick-number size becomes too big or small it can be changed with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_tick_label_size = 25,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"By setting these manually through trial and error we can fix the visualization issues","category":"page"},{"location":"helper/","page":"Utilities","title":"Utilities","text":"UnfoldMakie.RelativeAxis\nUnfoldMakie.eeg_topoplot_series\nUnfoldMakie.eeg_topoplot_series!\nUnfoldMakie.config_kwargs!\nUnfoldMakie.eeg_matrix_to_dataframe\nUnfoldMakie.rel_to_abs_bbox\nUnfoldMakie.to_positions\nUnfoldMakie.df_timebin\nUnfoldMakie.cart3d_to_spherical\nUnfoldMakie.valType_to_symbol","category":"page"},{"location":"helper/#UnfoldMakie.RelativeAxis","page":"Utilities","title":"UnfoldMakie.RelativeAxis","text":"ax = RelativeAxis(figlike, p::NTuple{4, Float64}; kwargs...)\n\nReturns an axis which's position is relative to a GridLayout Element (via BBox) and not relative to the Scene (default Axis(..., bbox=BBox()) behavior)\n\np::NTuple{4,Float64}: Give the relative position to the GridPosition, left:right; bottom:up, typical numbers betwen 0 and 1. 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In place plotting of topoplot series see eegtopoplotseries(data, Δbin) for help\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.config_kwargs!","page":"Utilities","title":"UnfoldMakie.config_kwargs!","text":"Takes a kwargs named tuple of Key => NamedTuple and merges the fields with the defaults\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.eeg_matrix_to_dataframe","page":"Utilities","title":"UnfoldMakie.eeg_matrix_to_dataframe","text":"Helper function converting a matrix (channel x times) to a tidy dataframe with columns :estimate, :time and :label\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.rel_to_abs_bbox","page":"Utilities","title":"UnfoldMakie.rel_to_abs_bbox","text":"reltoabs_bbox(org,rel)\n\nTakes a rectangle org and applies the relative transformation tuple rel Returns a Makie.BBox\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.to_positions","page":"Utilities","title":"UnfoldMakie.to_positions","text":"topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.\n\nThe matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.\n\nTipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.df_timebin","page":"Utilities","title":"UnfoldMakie.df_timebin","text":"function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins\n\ndf AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;\nΔbin bin size in :time units;\ncol_y default :erp, the column to combine over (with fun);\nfun function to combine, default is mean;\ngrouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.cart3d_to_spherical","page":"Utilities","title":"UnfoldMakie.cart3d_to_spherical","text":"convert x/y/z electrode montage positions to spherical coordinate representation. output is a matrix\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.valType_to_symbol","page":"Utilities","title":"UnfoldMakie.valType_to_symbol","text":"Val{:bu}() to => :bu\n\n\n\n\n\n","category":"function"},{"location":"api/","page":"API","title":"API","text":"Modules = [UnfoldMakie]\nOrder = [:function]","category":"page"},{"location":"api/#UnfoldMakie.cart3d_to_spherical-Tuple{Any, Any, Any}","page":"API","title":"UnfoldMakie.cart3d_to_spherical","text":"convert x/y/z electrode montage positions to spherical coordinate representation. output is a matrix\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.config_kwargs!-Tuple{PlotConfig}","page":"API","title":"UnfoldMakie.config_kwargs!","text":"Takes a kwargs named tuple of Key => NamedTuple and merges the fields with the defaults\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.df_timebin-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.df_timebin","text":"function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins\n\ndf AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;\nΔbin bin size in :time units;\ncol_y default :erp, the column to combine over (with fun);\nfun function to combine, default is mean;\ngrouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_matrix_to_dataframe-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.eeg_matrix_to_dataframe","text":"Helper function converting a matrix (channel x times) to a tidy dataframe with columns :estimate, :time and :label\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_topoplot_series!-Tuple{Any, DataFrame, Any}","page":"API","title":"UnfoldMakie.eeg_topoplot_series!","text":"eegtopoplotseries!(fig, data::DataFrame, Δbin; kwargs..) In place plotting of topoplot series see eegtopoplotseries(data, Δbin) for help\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_topoplot_series-Tuple{DataFrame, Any}","page":"API","title":"UnfoldMakie.eeg_topoplot_series","text":"function eegtopoplotseries(data::DataFrame, Δbin; y=:estimate, label=:label, col=:time, row=nothing, figure = NamedTuple(), combinefun=mean, rowlabels = false, collabels = false, topoplot_attributes... )\n\nPlot a series of topoplots. The function automatically takes the combinefun=mean over the :time column of data in Δbin steps.\n\nThe data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).\nΔbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.\nThe col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful\n\nto split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.\n\nThe figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).\nrow_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).\n\nExamples\n\nDesc\n\njulia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data\njulia > pos = [(1:63) ./ 63 .* (sin.(range(-2 * pi, 2 * pi, 63))) (1:63) ./ 63 .* cos.(range(-2 * pi, 2 * pi, 63))] .* 0.5 .+ 0.5 # fake electrode positions\njulia > pos = [Point2.(pos[k, 1], pos[k, 2]) for k in 1:size(pos, 1)]\njulia > eeg_topoplot_series(df, 5; positions=pos)\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_butterfly-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_butterfly","text":"Plot Butterfly\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showLegend = false, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:channel, :channels, :trial, :trials), positions = (:pos, :positions, :position, :topoPositions, :x, nothing), labels = (:labels, :label, :topoLabels, :sensor, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\nkey-word arguments\n\ntopomarkersize (Real, 10) - change the size of the markers, topoplot-inlay electrodes\ntopowidth (Real, 0.25) - change the size of the inlay topoplot width\ntopoheigth (Real, 0.25) - change the size of the inlay topoplot height\n\nsee also plot_erp\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_circulareegtopoplot-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_circulareegtopoplot","text":"plot_circulareegtopoplot(plotData::DataFrame; kwargs...)\nplot_circulareegtopoplot!(figlike, plotData::DataFrame; kwargs...)\n\nPlot a circular EEG topoplot.\n\nArguments:\n\nfiglike::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into\nplotData::DataFrame: Dataframe with keys for data (looks for :y,:yhat, :estimate, and :position (looks for :pos, :positions, :position), \npredictor (optional; default :predictor) the circular predictor value, defines position of topoplot, is mapped around predictorBounds\npredictorBounds: Default: [0,360] - The bounds of the predictor. This is relevant for the axis labels.\ncenterlabel: default \"\", the text in the center of the cricle\npositions (nothing) - positions for the plot_topoplot\nlabels (nothing) - labels for the plot_topoplot\nkwargs...: Additional styling behavior, see below.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(), label = \"\") - use kwargs... of Makie.Axis \n\nlayout = (showLegend = false, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false, label = \"Voltage [µV]\", colormap = Makie.Reverse{Symbol}(:RdBu)) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure containing the circular topoplot at given layout position\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_designmatrix-Tuple{Unfold.DesignMatrix}","page":"API","title":"UnfoldMakie.plot_designmatrix","text":"plot_designmatrix!(f::Union{GridPosition, GridLayout, Figure}, plotData::Unfold.DesignMatrix; kwargs...)\nplot_designmatrix(plotData::Unfold.DesignMatrix; kwargs...)\n\nPlot a designmatrix. \n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.\nplotData::Unfold.DesignMatrix: Data for the plot visualization.\n\nkwargs\n\nstandardizeData: (bool,true) - Indicating whether the data is standardized by pointwise division of the data with its sampled standard deviation.\nsortData: (bool, true) - Indicating whether the data is sorted; using sortslices() of Base Julia. \nxTicks: (nothing) \n\nIndicating the number of labels on the x-axis. Behavior if specified in configuration:\n\nxTicks = 0: no labels are placed.\nxTicks = 1: first possible label is placed.\nxTicks = 2: first and last possible labels are placed.\n2 < xTicks < number of labels: Equally distribute the labels.\nxTicks ≥ number of labels: all labels are placed.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (xticklabelrotation = 0.39269908169872414,) - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makieheatmap \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure displaying the designmatrix. \n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_erp-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_erp","text":"plot_erp!(f::Union{GridPosition, GridLayout, Figure}, plotData::DataFrame; kwargs...)\nplot_erp(plotData::DataFrame; kwargs...)\n\nPlot an ERP plot.\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into\nplotData::DataFrame: Data for the line plot visualization.\nkwargs...: Additional styling behavior. Often used: plot_erp(df; mapping=(; color=:coefname, col=:conditionA))\n\nkwargs (...; ...):\n\ncategoricalColor (bool, true) - Indicates whether the column referenced in mapping.color should be used nonnumerically.\ncategoricalGroup (bool, true) - Indicates whether the column referenced in mapping.group should be used nonnumerically.\ntopoLegend (bool, false) - Indicating whether a topo plot is used as a legend.\nstderror (bool, false) - Indicating whether the plot should show a colored band showing lower and higher estimates based on the stderror. \npvalue (Array, []) - example: DataFrame(from=[0.1,0.3], to=[0.5,0.7], coefname=[\"(Intercept)\", \"condition:face\"]) - if coefname not specified, the lines will be black\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\nReturn Value:\n\nf - Figure() or the inputed f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_new-Tuple{}","page":"API","title":"UnfoldMakie.plot_new","text":"plot_new() -> String\n\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, useColorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_parallelcoordinates-Tuple{DataFrame, Vector{Int64}}","page":"API","title":"UnfoldMakie.plot_parallelcoordinates","text":"plot_parallelcoordinates!(f::Union{GridPosition, GridLayout, Figure}, \n plotData::DataFrame, config::PlotConfig; channels::Vector{Int64})\n\nPlot a PCP (parallel coordinates plot).\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into\nplotData::DataFrame: Data for the plot visualization.\nconfig::PlotConfig: Instance of PlotConfig being applied to the visualization.\nchannels::Vector{Int64}: vector with all the channels representing an axis used in the PCP in given order.\n\nPCP has problems with size changes of the view window. By adapting the padding, aspect ratio and tick label size in px for a new use case, the PCP can even be added into a Coordinated Multiple Views System\n\npc_aspect_ratio Default : 0.55\npc_right_padding Default : 15\npc_left_padding Default : 25\npc_top_padding Default : 26\npc_bottom_padding Default : 16\npc_tick_label_size Default : 14\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = :channel, ylabelFromMapping = :y, useColorbar = false, hidespines = (), hidedecorations = (label = false,)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), channel = :channel, category = :category, time = :time) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nThe input f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_topoplot-Tuple{Union{DataFrame, Vector{Float32}}}","page":"API","title":"UnfoldMakie.plot_topoplot","text":"plot_topoplot!(f::Union{GridPosition, GridLayout, Figure}, plotData, ; positions=nothing, labels=nothing,kwargs...)\nplot_topoplot(plotData,; positions=nothing, labels=nothing, kwargs...)\n\nPlot a topo plot.\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.\nplotData::Union{DataFrame, Vector{Float32}}: Data for the plot visualization.\npositions::Vector{Point{2, Float32}}=nothing: positions used if plotData is no DataFrame. If this is the case and positions=nothing then positions is generated from labels.\nlabels::Vector{String}=nothing: labels used if plotData is no DataFrame.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure displaying the topo plot.\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_topoplotseries-Tuple{DataFrame, Real}","page":"API","title":"UnfoldMakie.plot_topoplotseries","text":"plot_topoplotseries!(f::Union{GridPosition, GridLayout, Figure}, plotData::DataFrame, Δbin::Real; kwargs...)\nplot_topoplotseries!(plotData::DataFrame, Δbin::Real; kwargs...)\n\nMultiple miniature topoplots in regular distances \n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into\nplotData::DataFrame: DataFrame with data, needs a time column\nΔbin::Real: A number for how large one bin should be. Δbin is in units of the plotData.time column\ncombinefun (default mean) can be used to specify how the samples within Δbin are combined.\nrasterize_heatmaps (deault true) - enforce rasterization of the plot heatmap when saving in svg format.\n\nThis has the benefit that all lines/points are vectors, except the interpolated heatmap. This is typically what you want, because else you get ~500x500 vectors per topoplot, which makes everything super slow.\n\ncol_labels, row_labels - shows column and row labels. \n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(;key=value,...)) - for example plot_x(...,layout=(showLegend=true,legendPosition=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis \n\nlayout = (showLegend = true, legendPosition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, useColorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing), col = (:time,), row = (nothing,)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = false, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false, height = 300, flipaxis = true, labelrotation = 4.7, label = \"Voltage [µV]\") - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nThe input f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.rel_to_abs_bbox-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.rel_to_abs_bbox","text":"reltoabs_bbox(org,rel)\n\nTakes a rectangle org and applies the relative transformation tuple rel Returns a Makie.BBox\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.to_positions-Tuple{AbstractMatrix}","page":"API","title":"UnfoldMakie.to_positions","text":"topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.\n\nThe matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.\n\nTipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.valType_to_symbol-Tuple{Any}","page":"API","title":"UnfoldMakie.valType_to_symbol","text":"Val{:bu}() to => :bu\n\n\n\n\n\n","category":"method"},{"location":"api/","page":"API","title":"API","text":"Internally, we use a PlotConfig struct to keep track of common plot options, in order to have a similar API to all functions","category":"page"},{"location":"api/","page":"API","title":"API","text":"PlotConfig","category":"page"},{"location":"api/#UnfoldMakie.PlotConfig","page":"API","title":"UnfoldMakie.PlotConfig","text":"PlotConfig()\nholds various different fields, that can modify various different plotting aspects.\n\n\n\n\n\n","category":"type"},{"location":"how_to/mult_vis_in_fig/#ht_mvf","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"","category":"section"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"using UnfoldMakie\nusing CairoMakie\nusing DataFramesMeta\nusing UnfoldSim\nusing Unfold\nusing MakieThemes\nset_theme!(theme_ggthemr(:fresh)) # nicer defaults - should maybe be default?\n","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"include(\"../../example_data.jl\")\nd_topo, positions = example_data(\"TopoPlots.jl\")\nuf_deconv = example_data(\"UnfoldLinearModelContinuousTime\")\nuf = example_data(\"UnfoldLinearModel\")\nresults = coeftable(uf)\nuf_5chan = example_data(\"UnfoldLinearModelMultiChannel\")\nd_singletrial, _ = UnfoldSim.predef_eeg(; return_epoched=true)\ntimes = -0.099609375:0.001953125:1.0\ndata, positions = TopoPlots.example_data()\nnothing #hide","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"This section discusses how users can incorporate multiple plots into a single figure.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"By using the !-version of the plotting function and inserting a grid position instead of an entire figure, we can create multiple coordinated views.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"We start by creating a figure with Makie.Figure. ","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"f = Figure()","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"Now any plot can be added to f by placing a grid position, such as f[1, 1].","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"\nf = Figure()\nplot_erp!(f[1, 1], coeftable(uf_deconv))\nplot_erp!(f[1, 2], effects(Dict(:condition => [\"car\", \"face\"]), uf_deconv), \n mapping=(; color=:condition))\nplot_butterfly!(f[2, 1:2], d_topo; positions=positions)\n\nf","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"Using the data from the tutorials, we can create a large image with any type of plot.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"With so many plots at once, it's tempting to set a fixed resolution in your image to order the plots evenly (code below).","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"\nf = Figure(resolution=(2000, 2000))\n\nplot_butterfly!(f[1, 1:3], d_topo; positions=positions)\n\npvals = DataFrame(\n from=[0.1, 0.15],\n to=[0.2, 0.5],\n # if coefname not specified, line should be black\n coefname=[\"(Intercept)\", \"category: face\"]\n)\nplot_erp!(f[2, 1:2], results, \n categoricalColor=false,\n categoricalGroup=false,\n pvalue=pvals,\n stderror=true)\n\n\nplot_designmatrix!(f[2, 3], designmatrix(uf))\n\nplot_topoplot!(f[3, 1], data[:, 150, 1]; positions=positions)\nplot_topoplotseries!(f[4, 1:3], d_topo, 0.1; positions=positions, mapping=(; label=:channel))\n\nres_effects = effects(Dict(:continuous => -5:0.5:5), uf_deconv)\n\nplot_erp!(f[2, 4:5], res_effects; categoricalColor=false, categoricalGroup=true,\n mapping=(; y=:yhat, color=:continuous, group=:continuous),\n legend=(; nbanks=2),\n layout=(; showLegend=true, legendPosition=:right))\n\nplot_parallelcoordinates!(f[3, 2:3], uf_5chan, [1, 2, 3, 4, 5]; mapping=(; color=:coefname), layout=(; legendPosition=:bottom))\n\nplot_erpimage!(f[1, 4:5], times, d_singletrial)\nplot_circulareegtopoplot!(f[3:4, 4:5], d_topo[in.(d_topo.time, Ref(-0.3:0.1:0.5)), :];\n positions=positions, predictor=:time, predictorBounds=[-0.3, 0.5])\n\nf","category":"page"},{"location":"tutorials/topoplotseries/#tpseries_vis","page":"Topo Plot Series","title":"Topo Plot SeriesVisualization","text":"","category":"section"},{"location":"tutorials/topoplotseries/#Include-used-Modules","page":"Topo Plot Series","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing TopoPlots","category":"page"},{"location":"tutorials/topoplotseries/#Plot-Topo-Plots-Series","page":"Topo Plot Series","title":"Plot Topo Plots Series","text":"","category":"section"},{"location":"tutorials/topoplotseries/#Giving-the-Data","page":"Topo Plot Series","title":"Giving the Data","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"In case you do not already have data, you can get example data from the TopoPlots module. You can do it like this:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"data, positions = TopoPlots.example_data()\ndf = UnfoldMakie.eeg_matrix_to_dataframe(data[:,:,1], string.(1:length(positions)));\nnothing #hide","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"Δbin = 80\nplot_topoplotseries(df, Δbin; positions = positions)","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"Without colorbar:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"plot_topoplotseries(df, Δbin; positions=positions, layout = (; useColorbar=false))","category":"page"},{"location":"tutorials/topoplotseries/#Positions","page":"Topo Plot Series","title":"Positions","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"You can give either positions, or labels. If both are provided, positions have priority","category":"page"},{"location":"tutorials/topoplotseries/#plot_toposeries(...;-mapping(;-keyvalue))","page":"Topo Plot Series","title":"plot_toposeries(...; mapping=(; key=value))","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"mapping=(: y=(:estimate, :yhat, :y))","category":"page"},{"location":"tutorials/topoplotseries/#visual(;)","page":"Topo Plot Series","title":"visual=(;)","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"label_text (boolean, false) Indicates whether label should drawn next to their position. The labels have to be given into the function seperately:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"important: Important\ncurrently bugged","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"label_scatter (boolean, true) - Indicates whether the dots should be drawn at the given positions.","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"EditURL = \"../../../literate/reference/positions.jl\"","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"using UnfoldMakie\nusing CairoMakie\nusing TopoPlots\nusing PyMNE","category":"page"},{"location":"generated/reference/positions/#get-MNE-positions","page":"Convert 3D positions / montages to 2D layouts","title":"get MNE-positions","text":"","category":"section"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"Generate a fake MNE structure taken from mne documentation","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"biosemi_montage = PyMNE.channels.make_standard_montage(\"biosemi64\")\nn_channels = length(biosemi_montage.ch_names)\nfake_info = PyMNE.create_info(ch_names=biosemi_montage.ch_names, sfreq=250.,\n ch_types=\"eeg\")\ndata = rand(n_channels,1) * 1e-6\nfake_evoked = PyMNE.EvokedArray(data, fake_info)\nfake_evoked.set_montage(biosemi_montage)\n\npos = to_positions(fake_evoked)","category":"page"},{"location":"generated/reference/positions/#project-from-3D-electrode-locations-to-2D","page":"Convert 3D positions / montages to 2D layouts","title":"project from 3D electrode locations to 2D","text":"","category":"section"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"pos3d = hcat(values(pyconvert(Dict,biosemi_montage.get_positions()[\"ch_pos\"]))...)\n\npos2 = to_positions(pos3d)\n\nf = Figure(resolution=(600,300))\nscatter(f[1,1],pos3d[1:2,:])\nscatter(f[1,2],pos2)\nf","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"as one can see, the \"naive\" transform of just dropping the third dimension doesnt really work (left). We rather have to project the chanels to a sphere and unfold it (right)","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"This page was generated using Literate.jl.","category":"page"},{"location":"tutorials/parallelcoordinates/#pcp_vis","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Here we discuss parallel coordinates plot (PCP) visualization. ","category":"page"},{"location":"tutorials/parallelcoordinates/#Include-used-Modules","page":"Parallel Coordinates Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie","category":"page"},{"location":"tutorials/parallelcoordinates/#Data","page":"Parallel Coordinates Plot","title":"Data","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"We use the test data of erpcore-N170.jld2.","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"include(\"../../example_data.jl\")\nresults_plot, positions = example_data();","category":"page"},{"location":"tutorials/parallelcoordinates/#Plot-PCPs","page":"Parallel Coordinates Plot","title":"Plot PCPs","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"plot_parallelcoordinates(results_plot, [5,3,2]; # this selects channel 5,3 & 2 \n mapping = (color = :coefname, y = :estimate))","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"important: Important\nthe following is still outdated...","category":"page"},{"location":"tutorials/parallelcoordinates/#Column-Mappings-for-PCPs","page":"Parallel Coordinates Plot","title":"Column Mappings for PCPs","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Since PCPs use a DataFrame as an input, the library needs to know the names of the columns used for plotting.","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"While there are multiple default values that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:","category":"page"},{"location":"tutorials/parallelcoordinates/#y","page":"Parallel Coordinates Plot","title":"y","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is (:y, :estimate, :yhat).","category":"page"},{"location":"tutorials/parallelcoordinates/#channel","page":"Parallel Coordinates Plot","title":"channel","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is :channel.","category":"page"},{"location":"tutorials/parallelcoordinates/#color","page":"Parallel Coordinates Plot","title":"color","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"XXX Default is :coef.","category":"page"},{"location":"tutorials/parallelcoordinates/#time","page":"Parallel Coordinates Plot","title":"time","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is :time.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"EditURL = \"../../../literate/tutorials/erp.jl\"","category":"page"},{"location":"generated/tutorials/erp/#lp_vis","page":"ERP plot","title":"Line Plot Visualization","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Here we discuss line plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"generated/tutorials/erp/#Include-used-Modules","page":"ERP plot","title":"Include used Modules","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing DataFramesMeta\nusing UnfoldSim\nusing UnfoldMakie","category":"page"},{"location":"generated/tutorials/erp/#Setup","page":"ERP plot","title":"Setup","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Let's generate some data and fit a model of a 2-level categorical and a continuous predictor with interaction.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"data, evts = UnfoldSim.predef_eeg(; noiselevel = 12, return_epoched = true)\ndata = reshape(data, (1, size(data)...))\nf = @formula 0 ~ 1 + condition + continuous\nse_solver = (x, y) -> Unfold.solver_default(x, y, stderror = true);\n\nm = fit(\n UnfoldModel,\n Dict(Any => (f, range(0, step = 1 / 100, length = size(data, 2)))),\n evts,\n data,\n solver = se_solver,\n)\nresults = coeftable(m)\nres_effects = effects(Dict(:continuous => -5:0.5:5), m);\nnothing #hide","category":"page"},{"location":"generated/tutorials/erp/#Plot-the-results","page":"ERP plot","title":"Plot the results","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(results; :stderror => true,)","category":"page"},{"location":"generated/tutorials/erp/#Column-Mappings-for-Line-Plots","page":"ERP plot","title":"Column Mappings for Line Plots","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp use a DataFrame as an input, the library needs to know the names of the columns used for plotting.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"There are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name can be chosen using plot_erp(...;mapping=(; :y=:myEstimate)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":":x Default is (:x, :time). :y Default is (:y, :estimate, :yhat). :color Default is (:color, :coefname).","category":"page"},{"location":"generated/tutorials/erp/#Configuration-for-Line-Plots","page":"ERP plot","title":"Configuration for Line Plots","text":"","category":"section"},{"location":"generated/tutorials/erp/#key-values","page":"ERP plot","title":"key values","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(...; =,...).","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"categoricalColor (boolean, true) - in case of numeric :color column, is color a continuous or categorical variable?\ncategoricalGroup (boolean, true) - in case of numeric :group column, treat :group as categorical variable by default\nstderror (boolean, false) - add an error-ribbon based on the :stderror column\npvalue (see below)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Using some general configurations we can pretty up the default visualization. Here we use the following configuration:","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(\n res_effects;\n mapping = (; y = :yhat, color = :continuous, group = :continuous),\n legend = (; nbanks = 2),\n layout = (; showLegend = true, legendPosition = :right),\n categoricalColor = false, categoricalGroup = true,\n)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"In the following we will use this \"pretty\" line plot as a basis for looking into configuration options.","category":"page"},{"location":"generated/tutorials/erp/#pvalue-(array)","page":"ERP plot","title":"pvalue (array)","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"important: Important\nthis is currently broken!","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Is an array of p-values. If array not empty, plot shows colored lines under the plot representing the p-values. Default is [] (an empty array). Shown below is an example in which pvalue are given: pvals = DataFrame(","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"#\t\tfrom=[0.1,0.3],\n#\t\tto=[0.5,0.7],\n#\t\tcoefname=[\"(Intercept)\",\"condition: face\"] # if coefname not specified, line should be black\n#\t)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(results; :pvalue=>pvals)","category":"page"},{"location":"generated/tutorials/erp/#stderror-(boolean)","page":"ERP plot","title":"stderror (boolean)","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Indicating whether the plot should show a colored band showing lower and higher estimates based on the stderror. Default is false.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"previously we showed :stderror- but low/high is possible as well`","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"results.se_low = results.estimate .- 0.5\nresults.se_high = results.estimate .+ 0.15\nplot_erp(select(results, Not(:stderror)); stderror = true)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"note: Note\nas in the above code,:stderror has precedence over :se_low/:se_high","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"This page was generated using Literate.jl.","category":"page"},{"location":"tutorials/erpimage/#erpi_vis","page":"ERP Image","title":"ERP Image Visualization","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"Here we discuss ERP image visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/erpimage/#Include-used-Modules","page":"ERP Image","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"using Unfold\nusing UnfoldMakie\nusing CairoMakie\nusing UnfoldSim\ninclude(\"../../example_data.jl\")","category":"page"},{"location":"tutorials/erpimage/#Plot-ERP-Images","page":"ERP Image","title":"Plot ERP Images","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"The following code will result in the default configuration. ","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"data, evts = UnfoldSim.predef_eeg(; noiselevel=10, return_epoched=true)\nplot_erpimage(data)","category":"page"},{"location":"tutorials/erpimage/#Column-Mappings-for-ERP-Images","page":"ERP Image","title":"Column Mappings for ERP Images","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"Since ERP images use a Matrix as an input, the library does not need any informations about the mapping.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"erpBlur (number, 10) - Is a number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module. Negative values deactivate the blur.\nsortvalues - Indicating whether the data is sorted; using sortperm() of Base Julia ","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"(sortperm() computes a permutation of the array's indices that puts the array into sorted order). ","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"meanPlot (bool, false) - Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data. If limits are set in the axis values both plots will be aligned.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"plot_erpimage(data;\n meanPlot = true,\n colorbar = (label = \"Voltage [µV]\",),\n visual = (colormap = :viridis, colorrange = (-40, 40)))\n","category":"page"},{"location":"tutorials/butterfly/#bfp_vis","page":"Butterfly Plot","title":"Butterfly Plot Visualization","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Here we discuss butterfly plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/butterfly/#Include-used-Modules","page":"Butterfly Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"using UnfoldMakie\nusing Unfold\nusing CairoMakie\nusing DataFrames","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Note that DataFramesMeta is also used here in order to be able to use @subset for testing (filtering).","category":"page"},{"location":"tutorials/butterfly/#Data","page":"Butterfly Plot","title":"Data","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"We filter the data to make it more clearly represented:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"include(\"../../example_data.jl\")\ndf, pos = example_data(\"TopoPlots.jl\")\nfirst(df, 3)","category":"page"},{"location":"tutorials/butterfly/#Plot-Butterfly-Plots","page":"Butterfly Plot","title":"Plot Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"The following code will plot the default butterfly plot","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"plot_butterfly(df)","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"or if you provide the channel positions:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"plot_butterfly(df; positions=pos)","category":"page"},{"location":"tutorials/butterfly/#Column-Mappings-for-Butterfly-Plots","page":"Butterfly Plot","title":"Column Mappings for Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Since butterfly plots use a DataFrame as input, the library needs to know the names of the columns used for plotting. You can set these mapping values by calling plot_butterfly(...; mapping=(; :x=:time,)), that is, by specifying a NamedTuple (note the ; right after the opening parentheses).","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"While there are several default values that will be checked in that order if they exist in the DataFrame, a custom name may need to be chosen:","category":"page"},{"location":"tutorials/butterfly/#x","page":"Butterfly Plot","title":"x","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:x, :time).","category":"page"},{"location":"tutorials/butterfly/#y","page":"Butterfly Plot","title":"y","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:y, :estimate, :yhat).","category":"page"},{"location":"tutorials/butterfly/#labels","page":"Butterfly Plot","title":"labels","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:labels, :label, :topoLabels, :sensor, :nothing)","category":"page"},{"location":"tutorials/butterfly/#Configurations-for-Butterfly-Plots","page":"Butterfly Plot","title":"Configurations for Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Here we look into possible options for configuring the butterfly plot visualization using (...; =, ...). This is the list of unique configuration (key values):","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"topoLegend (boolean)","category":"page"},{"location":"tutorials/butterfly/#topoLegend-(boolean)","page":"Butterfly Plot","title":"topoLegend (boolean)","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Indicating whether the topo legend is displayed. Default is true.","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"For more general options look into the Plot Configuration section of the documentation.","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Since the configurations for line plots can be applied to butterfly plots as well. Here you can find the configurations for line plots, ","category":"page"},{"location":"tutorials/topoplot/#tp_vis","page":"Topo Plot","title":"Topo Plot Visualization","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Here we discuss topo plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/topoplot/#Include-used-Modules","page":"Topo Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing TopoPlots","category":"page"},{"location":"tutorials/topoplot/#Plot-Topo-Plots","page":"Topo Plot","title":"Plot Topo Plots","text":"","category":"section"},{"location":"tutorials/topoplot/#Providing-the-Data","page":"Topo Plot","title":"Providing the Data","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"data, positions = TopoPlots.example_data()","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"We select one datapoint, and the first enry of dimension 3 (the mean estimate, the others are p-value and std)","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(data[:,340,1]; positions = positions)","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"using DataFrames\ndf = DataFrame(:estimate => data[:,340,1])\nplot_topoplot(df; positions = positions)","category":"page"},{"location":"tutorials/topoplot/#Giving-the-Positions","page":"Topo Plot","title":"Giving the Positions","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Since the topo plot needs the positions of the sensors they have to be put into the drawing function. But there are multiple options (In order of prioritization):","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Giving the positions directly: plot_topoplot(...; positions=[...])\nGiving the labels of the sensors: plot_topoplot(...; labels=[...])","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"To get the positions from the labels we use a database.","category":"page"},{"location":"tutorials/topoplot/#Column-Mappings-for-Topo-Plots","page":"Topo Plot","title":"Column Mappings for Topo Plots","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"When using topo plots with a DataFrame as an input, the library needs to know the names of the columns used for plotting. This is specified using the mapping=(;) kwargs.","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"While there are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Note that only one of positions or labels have to be set to draw a topo plot. If both are set, positions takes precedence, labels might be used for labelling electrodes in TopoPlots.jl","category":"page"},{"location":"tutorials/topoplot/#(...,mapping(;))","page":"Topo Plot","title":"(...,mapping=(;))","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":":y plotting function looks in the default columns of mapping","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"cfgDefault = UnfoldMakie.PlotConfig()\ncfgDefault.mapping.y","category":"page"},{"location":"tutorials/topoplot/#label_text-(boolean)","page":"Topo Plot","title":"label_text (boolean)","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Indicates whether label should drawn next to their position. Obviously the labels have to be provided: plot_topoplot(...; labels=[...])","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(...; visual=(; label_text=true))","category":"page"},{"location":"tutorials/topoplot/#label_scatter-(boolean)","page":"Topo Plot","title":"label_scatter (boolean)","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Indicates whether the dots should be drawn at the given positions.","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(...; visual=(; label_scatter=true))","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"data, positions = TopoPlots.example_data()\nplot_topoplot(data[1:4,340,1]; visual = (; label_scatter = false), labels=[\"O1\", \"F2\", \"F3\", \"P4\"])","category":"page"},{"location":"tutorials/designmatrix/#dm_vis","page":"Designmatrix","title":"Designmatrix Visualization","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"Here we discuss designmatrix visualization. Make sure you have looked into the installation instructions section. ","category":"page"},{"location":"tutorials/designmatrix/#Include-used-Modules","page":"Designmatrix","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie","category":"page"},{"location":"tutorials/designmatrix/#Data","page":"Designmatrix","title":"Data","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"include(\"../../example_data.jl\")\nuf = example_data(\"UnfoldLinearModel\")\n","category":"page"},{"location":"tutorials/designmatrix/#Plot-Designmatrices","page":"Designmatrix","title":"Plot Designmatrices","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"The following code will result in the default configuration. ","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"plot_designmatrix(designmatrix(uf))","category":"page"},{"location":"tutorials/designmatrix/#kwargs-plot_designmatrix(...;-...).","page":"Designmatrix","title":"kwargs plot_designmatrix(...; ...).","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"sortData (boolean,false) - Indicating whether the data is sorted; using sortslices() of Base Julia. ","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"In order to make the designmatrix easier to read, you may want to sort it.","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"plot_designmatrix(designmatrix(uf); sortData=true)","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"standardizeData (boolean, false) - Indicating whether the data is standardized, mapping the values between 0 and 1. \nxTicks (number, nothing)","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"Indicating the number of labels on the x-axis. Behavior if specified in configuration: - xTicks = 0: no labels are placed. - xTicks = 1: first possible label is placed. - xTicks = 2: first and last possible labels are placed. - 2 < xTicks < number of labels: xTicks-2 labels are placed between the first and last. - xTicks ≥ number of labels: all labels are placed.","category":"page"},{"location":"how_to/hide_deco/#ht_hide_deco","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"","category":"section"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"This section discusses how users can efficiently hide axis spines and decorations in their plots.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"While it's possible to hide these axis decorations by setting the axis settings with axis=(;...), Makie.Axis provides multiple variables for different aspects of the plot. This means that removing all decorations is only possible by setting many variables each time.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Makie does provide methods like hidespines! and hidedecorations!, but the user may not have easy access to the axis their plot is drawn in.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Instead, these functions can be called by setting variables with layout = (;):","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"... layout = (\n ...\n hidespines = (),\n hidedecorations = ()\n)","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Since these values reflect the input to the function, we can use an empty tuple to remove all decorations and spines, respectively","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"And using hidespines = (:r, :t) will remove the top and right borders.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"For more information on the input of these functions refer to the Makie dokumentation on Axis.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Since some plots hide features by default, the hiding can be reverted by setting the variables to nothing","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"using TopoPlots\nusing UnfoldMakie\nusing CairoMakie\n\ndata, positions = TopoPlots.example_data()\nplot_topoplot(data[:,340,1]; \n positions = positions, \n layout=(;\n hidespines = nothing,\n hidedecorations = nothing\n ),)","category":"page"},{"location":"#UnfoldMakie-Documentation","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"","category":"section"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"This is the documentation of the UnfoldMakie module for the Julia programming language. ","category":"page"},{"location":"#About","page":"UnfoldMakie Documentation","title":"About","text":"","category":"section"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"UnfoldMakie aims to allow users to create different types of visualizations. These include line plots, butterfly plots, design matrices, parallel coordinate plots, ERP images, and topo plots. Building on the Unfold and Makie Modules, it also allows users to customize the plots through an input configuration.","category":"page"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"As can be seen from the types of visualizations possible, these configuration options try to enable the user to create plots that are helpful in the field of computational EEG. One such example is the ability to use a topo plot as a legend for a line plot by allowing multiple visualizations within a figure.","category":"page"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"(Image: Coordinated Multiple Views)","category":"page"},{"location":"tutorials/installation/#install_instruct","page":"Installation","title":"Installation","text":"","category":"section"},{"location":"tutorials/installation/#Getting-Julia","page":"Installation","title":"Getting Julia","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"You can install Julia by following the instructions from the official website. ","category":"page"},{"location":"tutorials/installation/#Setup-UnfoldMakie.jl","page":"Installation","title":"Setup UnfoldMakie.jl","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"After installing Julia, you can execute the julia.exe. ","category":"page"},{"location":"tutorials/installation/#Generate-a-Project","page":"Installation","title":"Generate a Project","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"If you do not yet have a project you can generate one. First you type ] into the Julia console to switch from julia to (@VERSION) pkg. Here you can generate a project by using the command: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"generate \"FOLDER_PATH\"","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Note that the specific folder in which you want to generate the project does not already exist.","category":"page"},{"location":"tutorials/installation/#Activate-your-Project","page":"Installation","title":"Activate your Project","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Before you can add the necessary modules to use UnfoldMakie you have to activate your project in the (@VERSION) pkg environment. The command is: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"activate \"FOLDER_PATH\"","category":"page"},{"location":"tutorials/installation/#Install-the-UnfoldMakie-Module","page":"Installation","title":"Install the UnfoldMakie Module","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"When your project is activated you can add the module. The command is: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"add UnfoldMakie","category":"page"},{"location":"tutorials/installation/#Using-the-Project-in-a-Notebook","page":"Installation","title":"Using the Project in a Notebook","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"In case you want to use this generated project in a notebook (e.g. Pluto or Jupyter), you can activate this in the notebook in the following manner:","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"begin\n using Pkg\n Pkg.activate(\"FOLDER_PATH\")\n Pkg.resolve()\nend","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Use slash / for the folder path. ","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"EditURL = \"../../../literate/tutorials/circTopo.jl\"","category":"page"},{"location":"generated/tutorials/circTopo/#Circular-Topoplot-Arrangement","page":"Circular TopoPlot","title":"Circular Topoplot Arrangement","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"using UnfoldMakie\nusing CairoMakie\nusing TopoPlots # for example data\nusing Random\nusing DataFrames","category":"page"},{"location":"generated/tutorials/circTopo/#Generate-data","page":"Circular TopoPlot","title":"Generate data","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"Generate a Dataframe. We need to specify the TopoPlot Positions either via position, or via labels (according to TopoPlots.jl)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"data, pos = TopoPlots.example_data();\ndat = data[:, 240, 1]\ndf = DataFrame(\n :estimate => eachcol(Float64.(data[:, 100:40:300, 1])),\n :circularVariable => [0, 50, 80, 120, 180, 210],\n :time => 100:40:300,\n)\ndf = flatten(df, :estimate);\nnothing #hide","category":"page"},{"location":"generated/tutorials/circTopo/#Our-first-plot!","page":"Circular TopoPlot","title":"Our first plot!","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"note how the plots are at the angles of circularVariable`","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"plot_circulareegtopoplot(\n df;\n positions = pos,\n axis = (; label = \"Sac Incoming\"),\n predictor = :circularVariable,\n)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"In case the bounding variable is not between 0 and 360, as here we use actually time, we have to specify it. e.g.","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"plot_circulareegtopoplot(\n df;\n positions = pos,\n axis = (; label = \"Time?!\"),\n predictor = :time,\n predictorBounds = [80, 320],\n)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"This page was generated using Literate.jl.","category":"page"}] +[{"location":"how_to/show_oob_labels/#ht_soobl","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"","category":"section"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"When visualizing a design matrix, it can happen that the labels on the y-axis get cut off to the left (especially if they are quite long). In the following, we will discuss a possible quick solution to this problem.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"We start with the \"label-limited\" time-expanded designmatrix from the corresponding Tutorial section, which describes in detail how to generate it.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"plot_designmatrix(designmatrix!(ufCont,evts), cDesign; xTicks=10, sortData=false)","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"While the plot automatically sets its height according to the labels, the labels are cut off on the left side.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"A quick fix would be to place an empty plot to the left of the designmatrix.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"By creating your own figure with Makie.Figure and then giving the designmatrix only a certain grid position, we get white space next to the plot.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"The plot! function inside the plot config instance can take any grid position, and the figure f will contain the plot and enough white space next to it.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"The exact numbers in the grid position can be guessed from the overlap ratio, or just tried.","category":"page"},{"location":"how_to/show_oob_labels/","page":"Show out of Bounds Label","title":"Show out of Bounds Label","text":"f = Figure()\nplot_design(f[1,2:6], designmatrix!(ufCont, evts), cDesign; setExtraValues=(xTicks=10, sortData=false))\n\nf","category":"page"},{"location":"how_to/position2color/#ht_p2c","page":"Butterfly Colormap","title":"Change Butterfly Channel Position Color","text":"","category":"section"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"In this section we discuss how users are able change the position to colorscale of the legendtopo in the butterfly plot.","category":"page"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"using UnfoldMakie\nusing CairoMakie\nusing DataFramesMeta\nusing Colors","category":"page"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"By default the plot looks like this:","category":"page"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"include(\"../../example_data.jl\")\nresults, positions = example_data(\"TopoPlots.jl\")\nplot_butterfly(results; positions=positions)","category":"page"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"We can switch the colorscale of the position-map, by giving a function that maps from a (x,y) tuple to a color. UnfoldMakie currently provides three different ones pos2colorRGB (same as MNE-Python), pos2colorHSV (HSV colorspace), pos2colorRomaO. Whereas RGB & HSV have the benefits of being 2D colormaps, Roma0 has the benefit of being perceptualy uniform.","category":"page"},{"location":"how_to/position2color/#Similar-to-MNE","page":"Butterfly Colormap","title":"Similar to MNE","text":"","category":"section"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"plot_butterfly(results; \n positions=positions, \n topopositions_to_color = pos -> UnfoldMakie.posToColorRGB(pos)\n)","category":"page"},{"location":"how_to/position2color/#HSV-Space","page":"Butterfly Colormap","title":"HSV-Space","text":"","category":"section"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"plot_butterfly(results; positions=positions, topopositions_to_color=UnfoldMakie.posToColorHSV)","category":"page"},{"location":"how_to/position2color/#Uniform-Color","page":"Butterfly Colormap","title":"Uniform Color","text":"","category":"section"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"To highlight the flexibility, we can also make all lines gray, or any other arbitrary color, or function of electrode-position.","category":"page"},{"location":"how_to/position2color/","page":"Butterfly Colormap","title":"Butterfly Colormap","text":"plot_butterfly(results; positions=positions, topopositions_to_color = x -> Colors.RGB(0.5))","category":"page"},{"location":"how_to/fix_pcp/#ht_fpcp","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"","category":"section"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Since Makie doesn't have a native function to draw PCPs, our version is somewhat experimental for general use.","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Under certain circumstances the PCP is not visualized correctly. This leads to truncated edges of the PCP and unused space.","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Since the plot could have more space above and below, we can change the aspect ratio of the plot with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_aspect_ratio = 1,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"The cut off or overlap at each side can be fixed with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_right_padding = 15,\npc_left_padding = 45,\npc_top_padding = 50,\npc_bottom_padding = 27,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"Furthermore, if the tick-number size becomes too big or small it can be changed with:","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"...\npc_tick_label_size = 25,\n...","category":"page"},{"location":"how_to/fix_pcp/","page":"Fix Parallel Coordinates Plot","title":"Fix Parallel Coordinates Plot","text":"By setting these manually through trial and error we can fix the visualization issues","category":"page"},{"location":"helper/","page":"Utilities","title":"Utilities","text":"UnfoldMakie.RelativeAxis\nUnfoldMakie.eeg_topoplot_series\nUnfoldMakie.eeg_topoplot_series!\nUnfoldMakie.config_kwargs!\nUnfoldMakie.eeg_matrix_to_dataframe\nUnfoldMakie.rel_to_abs_bbox\nUnfoldMakie.to_positions\nUnfoldMakie.df_timebin\nUnfoldMakie.cart3d_to_spherical\nUnfoldMakie.valType_to_symbol","category":"page"},{"location":"helper/#UnfoldMakie.RelativeAxis","page":"Utilities","title":"UnfoldMakie.RelativeAxis","text":"ax = RelativeAxis(figlike, p::NTuple{4, Float64}; kwargs...)\n\nReturns an axis which's position is relative to a GridLayout Element (via BBox) and not relative to the Scene (default Axis(..., bbox=BBox()) behavior)\n\np::NTuple{4,Float64}: Give the relative position to the GridPosition, left:right; bottom:up, typical numbers betwen 0 and 1. E.g. (0.25, 0.75, 0.25, 0.75) would center an Axis inside that GridPosition\n\nkwargs... are pasted into Axis\n\nf = Figure() ax = RelativeAxis(f[1,2], (0.25, 0.75, 0.25, 0.75))\t # returns Axis centered within f[1,2]\n\n\n\n\n\n","category":"type"},{"location":"helper/#UnfoldMakie.eeg_topoplot_series","page":"Utilities","title":"UnfoldMakie.eeg_topoplot_series","text":"function eegtopoplotseries(data::DataFrame, Δbin; y=:estimate, label=:label, col=:time, row=nothing, figure = NamedTuple(), combinefun=mean, rowlabels = false, collabels = false, topoplot_attributes... )\n\nPlot a series of topoplots. The function automatically takes the combinefun=mean over the :time column of data in Δbin steps.\n\nThe data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).\nΔbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.\nThe col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful\n\nto split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.\n\nThe figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).\nrow_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).\n\nExamples\n\nDesc\n\njulia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data\njulia > pos = [(1:63) ./ 63 .* (sin.(range(-2 * pi, 2 * pi, 63))) (1:63) ./ 63 .* cos.(range(-2 * pi, 2 * pi, 63))] .* 0.5 .+ 0.5 # fake electrode positions\njulia > pos = [Point2.(pos[k, 1], pos[k, 2]) for k in 1:size(pos, 1)]\njulia > eeg_topoplot_series(df, 5; positions=pos)\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.eeg_topoplot_series!","page":"Utilities","title":"UnfoldMakie.eeg_topoplot_series!","text":"eegtopoplotseries!(fig, data::DataFrame, Δbin; kwargs..) In place plotting of topoplot series see eegtopoplotseries(data, Δbin) for help\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.config_kwargs!","page":"Utilities","title":"UnfoldMakie.config_kwargs!","text":"Takes a kwargs named tuple of Key => NamedTuple and merges the fields with the defaults\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.eeg_matrix_to_dataframe","page":"Utilities","title":"UnfoldMakie.eeg_matrix_to_dataframe","text":"Helper function converting a matrix (channel x times) to a tidy dataframe with columns :estimate, :time and :label\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.rel_to_abs_bbox","page":"Utilities","title":"UnfoldMakie.rel_to_abs_bbox","text":"reltoabs_bbox(org,rel)\n\nTakes a rectangle org and applies the relative transformation tuple rel Returns a Makie.BBox\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.to_positions","page":"Utilities","title":"UnfoldMakie.to_positions","text":"topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.\n\nThe matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.\n\nTipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.df_timebin","page":"Utilities","title":"UnfoldMakie.df_timebin","text":"function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins\n\ndf AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;\nΔbin bin size in :time units;\ncol_y default :erp, the column to combine over (with fun);\nfun function to combine, default is mean;\ngrouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.cart3d_to_spherical","page":"Utilities","title":"UnfoldMakie.cart3d_to_spherical","text":"convert x/y/z electrode montage positions to spherical coordinate representation. output is a matrix\n\n\n\n\n\n","category":"function"},{"location":"helper/#UnfoldMakie.valType_to_symbol","page":"Utilities","title":"UnfoldMakie.valType_to_symbol","text":"Val{:bu}() to => :bu\n\n\n\n\n\n","category":"function"},{"location":"api/","page":"API","title":"API","text":"Modules = [UnfoldMakie]\nOrder = [:function]","category":"page"},{"location":"api/#UnfoldMakie.cart3d_to_spherical-Tuple{Any, Any, Any}","page":"API","title":"UnfoldMakie.cart3d_to_spherical","text":"convert x/y/z electrode montage positions to spherical coordinate representation. output is a matrix\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.config_kwargs!-Tuple{PlotConfig}","page":"API","title":"UnfoldMakie.config_kwargs!","text":"Takes a kwargs named tuple of Key => NamedTuple and merges the fields with the defaults\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.df_timebin-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.df_timebin","text":"function dftimebin(df, Δbin; coly=:erp, fun=mean, grouping=[]) Split or combine dataframe according to equally spaced time bins\n\ndf AbstractTable with columns :time and col_y (default :erp), and all columns in grouping;\nΔbin bin size in :time units;\ncol_y default :erp, the column to combine over (with fun);\nfun function to combine, default is mean;\ngrouping (vector of symbols/strings) default empty vector, columns to group the data by before aggregating. Values of nothing are ignored.\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_matrix_to_dataframe-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.eeg_matrix_to_dataframe","text":"Helper function converting a matrix (channel x times) to a tidy dataframe with columns :estimate, :time and :label\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_topoplot_series!-Tuple{Any, DataFrame, Any}","page":"API","title":"UnfoldMakie.eeg_topoplot_series!","text":"eegtopoplotseries!(fig, data::DataFrame, Δbin; kwargs..) In place plotting of topoplot series see eegtopoplotseries(data, Δbin) for help\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.eeg_topoplot_series-Tuple{DataFrame, Any}","page":"API","title":"UnfoldMakie.eeg_topoplot_series","text":"function eegtopoplotseries(data::DataFrame, Δbin; y=:estimate, label=:label, col=:time, row=nothing, figure = NamedTuple(), combinefun=mean, rowlabels = false, collabels = false, topoplot_attributes... )\n\nPlot a series of topoplots. The function automatically takes the combinefun=mean over the :time column of data in Δbin steps.\n\nThe data frame data needs the columns :time and y(=:erp), and label(=:label). If data is a matrix, it is automatically cast to a dataframe, time bins are in samples, labels are string.(1:size(data,1)).\nΔbin in :time units, specifying the time steps. All other keyword arguments are passed to the EEG_TopoPlot recipe. In most cases, the user should specify the electrode positions with positions=pos.\nThe col and row arguments specify the field to be divided into columns and rows. The default is col=:time to split by the time field and row=nothing. Useful\n\nto split by a condition, e.g. ...(..., col=:time, row=:condition) would result in multiple (as many as different values in df.condition) rows of topoplot series.\n\nThe figure option allows you to include information for plotting the figure. Alternatively, you can pass a fig object eeg_topoplot_series!(fig, data::DataFrame, Δbin; kwargs..).\nrow_labels and col_labels indicate whether there should be labels in the plots in the first column to indicate the row value and in the last row to indicate the time (typically timerange).\n\nExamples\n\nDesc\n\njulia > df = DataFrame(:erp => repeat(1:63, 100), :time => repeat(1:20, 5 * 63), :label => repeat(1:63, 100)) # fake data\njulia > pos = [(1:63) ./ 63 .* (sin.(range(-2 * pi, 2 * pi, 63))) (1:63) ./ 63 .* cos.(range(-2 * pi, 2 * pi, 63))] .* 0.5 .+ 0.5 # fake electrode positions\njulia > pos = [Point2.(pos[k, 1], pos[k, 2]) for k in 1:size(pos, 1)]\njulia > eeg_topoplot_series(df, 5; positions=pos)\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_butterfly-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_butterfly","text":"Plot a butterfly plot\n\nkwargs (...; ...):\n\nbutterfly (bool, true): create a butterfly plot.\ntopolegend (bool, true): show an inlay topoplot with corresponding electrodes.\ntopomarkersize (Real, 10): change the size of the markers, topoplot-inlay electrodes.\ntopowidth (Real, 0.25): change the size of the inlay topoplot width.\ntopoheigth (Real, 0.25): change the size of the inlay topoplot height.\ntopopositions_to_color (function, ´x -> posToColorRomaO(x)´).\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showlegend = false, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:channel, :channels, :trial, :trials), positions = (:pos, :positions, :position, :topo_positions, :x, nothing), labels = (:labels, :label, :topoLabels, :sensor, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\nsee also plot_erp\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_circulareegtopoplot-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_circulareegtopoplot","text":"plot_circulareegtopoplot(data::DataFrame; kwargs...)\nplot_circulareegtopoplot!(f, data::DataFrame; kwargs...)\n\nPlot a circular EEG topoplot.\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure, GridLayout or GridPosition that the plot should be drawn into\ndata::DataFrame: DataFrame with keys for data (looks for :y, :yhat, :estimate), and :position (looks for :pos, :position, :positions), \npredictor (optional; default: predictor): the circular predictor value, defines position of topoplot, is mapped around predictor_bounds\npredictor_bounds (default: [0,360]): the bounds of the predictor. This is relevant for the axis labels.\npositions (default: nothing): positions for the plot_topoplot\ncenter_label (default: \"\"): the text in the center of the cricle\nlabels (default: nothing): labels for the plot_topoplot\nkwargs...: additional styling behavior, see below.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(), label = \"\") - use kwargs... of Makie.Axis \n\nlayout = (showlegend = false, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false, label = \"Voltage [µV]\", colormap = Makie.Reverse{Symbol}(:RdBu)) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure containing the circular topoplot at given layout position\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_designmatrix-Tuple{Unfold.DesignMatrix}","page":"API","title":"UnfoldMakie.plot_designmatrix","text":"plot_designmatrix!(f::Union{GridPosition, GridLayout, Figure}, data::Unfold.DesignMatrix; kwargs...)\nplot_designmatrix(data::Unfold.DesignMatrix; kwargs...)\n\nPlot a designmatrix. \n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) in which the plot will be placed into. A new axis is created.\ndata::Unfold.DesignMatrix: data for the plot visualization.\n\nkwargs\n\nstandardize_data (bool,true): indicates whether the data is standardized by pointwise division of the data with its sampled standard deviation.\nsort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia. \nxticks (nothing): returns the number of labels on the x-axis. Behavior is set in the configuration:\nxticks = 0: no labels are placed.\nxticks = 1: first possible label is placed.\nxticks = 2: first and last possible labels are placed.\n2 < xticks < number of labels: equally distribute the labels.\nxticks ≥ number of labels: all labels are placed.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (xticklabelrotation = 0.39269908169872414,) - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makieheatmap \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure displaying the designmatrix. \n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_erp-Tuple{DataFrame}","page":"API","title":"UnfoldMakie.plot_erp","text":"plot_erp!(f::Union{GridPosition, GridLayout, Figure}, plot_data::DataFrame; kwargs...)\nplot_erp(plot_data::DataFrame; kwargs...)\n\nPlot an ERP plot.\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure, GridLayout or GridPosition that the plot should be drawn into.\nplot_data::DataFrame: Data for the line plot visualization.\nkwargs...: Additional styling behavior. Often used: plot_erp(df; mapping=(; color=:coefname, col=:conditionA)).\n\nkwargs (...; ...):\n\ncategorical_color (bool, true): in case of numeric :color column, treat :color as continuous or categorical variable.\ncategorical_group (bool, true): in case of numeric :group column, treat :group as categorical variable by default.\ntopolegend (bool, false): add an inlay topoplot with corresponding electrodes.\nstderror (bool, false): add an error ribbon, with lower and upper limits based on the :stderror column.\npvalue (Array, []): show a pvalue.\nexample: DataFrame(from=[0.1, 0.3], to=[0.5, 0.7], coefname=[\"(Intercept)\", \"condition:face\"]) - if coefname is not specified, the lines will be black\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\nReturn Value:\n\nf - Figure() or the inputed f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_new-Tuple{}","page":"API","title":"UnfoldMakie.plot_new","text":"plot_new() -> String\n\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = :x, ylabelFromMapping = :y, use_colorbar = false, hidespines = (:r, :t)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), color = (:color, :coefname, nothing)) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false, framevisible = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of AlgebraOfGraphics.colobar! \n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_parallelcoordinates-Tuple{DataFrame, Vector{Int64}}","page":"API","title":"UnfoldMakie.plot_parallelcoordinates","text":"plot_parallelcoordinates!(f::Union{GridPosition, GridLayout, Figure}, \n data::DataFrame, config::PlotConfig; channels::Vector{Int64})\n\nPlot a PCP (parallel coordinates plot).\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.\ndata::DataFrame: data for the plot visualization.\nconfig::PlotConfig: instance of PlotConfig being applied to the visualization.\nchannels::Vector{Int64}: vector with all the channels representing an axis used in the PCP in given order.\n\nPCP has problems with size changes of the view window. By adapting the padding, aspect ratio and tick label size in px for a new use case, the PCP can even be added into a complex figures.\n\npc_aspect_ratio (default: 0.55) -\npc_right_padding (default: 15) -\npc_left_padding (default: 25) -\npc_top_padding (default: 26) -\npc_bottom_padding (default: 16) -\npc_tick_label_size (default: 14) - \n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = NamedTuple() - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = :channel, ylabelFromMapping = :y, use_colorbar = false, hidespines = (), hidedecorations = (label = false,)) \n\nmapping = (x = (:time,), y = (:estimate, :yhat, :y), channel = :channel, category = :category, time = :time) \n\nvisual = (colormap = :roma,) - use kwargs... of Makielines \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nThe input f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_topoplot-Tuple{Union{DataFrame, Vector{Float32}}}","page":"API","title":"UnfoldMakie.plot_topoplot","text":"plot_topoplot!(f::Union{GridPosition, GridLayout, Figure}, data, ; positions=nothing, labels=nothing,kwargs...)\nplot_topoplot(data,; positions=nothing, labels=nothing, kwargs...)\n\nPlot a topo plot.\n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition (e.g. f[2, 3]) that the plot should be drawn into. New axis is created.\ndata::Union{DataFrame, Vector{Float32}}: data for the plot visualization.\npositions::Vector{Point{2, Float32}}=nothing: positions used if data is not a DataFrame. If this is the case and positions=nothing then positions are generated from labels.\nlabels::Vector{String} = nothing: labels used if data is not a DataFrame.\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = true, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false) - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nA figure displaying the topo plot.\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.plot_topoplotseries-Tuple{DataFrame, Real}","page":"API","title":"UnfoldMakie.plot_topoplotseries","text":"plot_topoplotseries!(f::Union{GridPosition, GridLayout, Figure}, data::DataFrame, Δbin::Real; kwargs...)\nplot_topoplotseries!(data::DataFrame, Δbin::Real; kwargs...)\n\nMultiple miniature topoplots in regular distances \n\nArguments:\n\nf::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.\ndata::DataFrame: DataFrame with data, needs a time column.\nΔbin::Real: A number for how large one time bin should be. Δbin is in units of the data.time column.\ncombinefun (default: mean) - can be used to specify how the samples within Δbin are combined.\nrasterize_heatmaps (default: true) - enforce rasterization of the plot heatmap when saving in svg format. This has the benefit that all lines/points are vectors, except the interpolated heatmap. This is typically what you want, otherwise you get ~500x500 vectors per topoplot, which makes everything super slow.\ncol_labels, row_labels - shows column and row labels. \nlabels (default: nothing) - .\npositions (default: nothing) - .\n\nShared plot configuration options\n\nThe shared plot options can be used as follows: type=(; key=value,...)) - for example plot_x(..., layout=(show_legend=true, legend_position=:right)). Multiple defaults will be cycled until match.\n\nfigure = NamedTuple() - use kwargs... of Makie.Figure \n\naxis = (aspect = Makie.DataAspect(),) - use kwargs... of Makie.Axis \n\nlayout = (showlegend = true, legendposition = :right, xlabelFromMapping = nothing, ylabelFromMapping = nothing, use_colorbar = true, hidespines = (), hidedecorations = ()) \n\nmapping = (x = (nothing,), y = (:estimate, :yhat, :y), positions = (:pos, :positions, :position, nothing), labels = (:labels, :label, :sensor, nothing), col = (:time,), row = (nothing,)) \n\nvisual = (colormap = Makie.Reverse{Symbol}(:RdBu), contours = (color = :white, linewidth = 2), labelscatter = true, labeltext = false, boundinggeometry = GeometryBasics.Circle) - *use kwargs... of [``Topoplot.eegtopoplot``](@ref)* \n\nlegend = (orientation = :vertical, tellwidth = true, tellheight = false) - use kwargs... of Makie.Legend \n\ncolorbar = (vertical = true, tellwidth = true, tellheight = false, height = 300, flipaxis = true, labelrotation = 4.7, label = \"Voltage [µV]\") - use kwargs... of Makie.Colorbar \n\nReturn Value:\n\nThe input f\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.rel_to_abs_bbox-Tuple{Any, Any}","page":"API","title":"UnfoldMakie.rel_to_abs_bbox","text":"reltoabs_bbox(org,rel)\n\nTakes a rectangle org and applies the relative transformation tuple rel Returns a Makie.BBox\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.to_positions-Tuple{AbstractMatrix}","page":"API","title":"UnfoldMakie.to_positions","text":"topositions(x,y,z;sphere=[0,0,0.]) topositions(pos::AbstractMatrix;sphere=[0,0,0.]) Projects 3D electrode positions to a 2D layout.\n\nThe matrix case, assumes size(pos) = (3,nChannels) Re-implementation of the MNE algorithm.\n\nTipp: You can directly get positions from an MNE object after loading PyMNE and thus activating the UnfoldMakie PyMNE extension\n\n\n\n\n\n","category":"method"},{"location":"api/#UnfoldMakie.valType_to_symbol-Tuple{Any}","page":"API","title":"UnfoldMakie.valType_to_symbol","text":"Val{:bu}() to => :bu\n\n\n\n\n\n","category":"method"},{"location":"api/","page":"API","title":"API","text":"Internally, we use a PlotConfig struct to keep track of common plot options, in order to have a similar API to all functions","category":"page"},{"location":"api/","page":"API","title":"API","text":"PlotConfig","category":"page"},{"location":"api/#UnfoldMakie.PlotConfig","page":"API","title":"UnfoldMakie.PlotConfig","text":"PlotConfig()\nholds various different fields, that can modify various different plotting aspects.\n\n\n\n\n\n","category":"type"},{"location":"how_to/mult_vis_in_fig/#ht_mvf","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"","category":"section"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"using UnfoldMakie\nusing CairoMakie\nusing DataFramesMeta\nusing UnfoldSim\nusing Unfold\nusing MakieThemes\nset_theme!(theme_ggthemr(:fresh)) # nicer defaults - should maybe be default?\n","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"include(\"../../example_data.jl\")\nd_topo, positions = example_data(\"TopoPlots.jl\")\nuf_deconv = example_data(\"UnfoldLinearModelContinuousTime\")\nuf = example_data(\"UnfoldLinearModel\")\nresults = coeftable(uf)\nuf_5chan = example_data(\"UnfoldLinearModelMultiChannel\")\nd_singletrial, _ = UnfoldSim.predef_eeg(; return_epoched=true)\ntimes = -0.099609375:0.001953125:1.0\ndata, positions = TopoPlots.example_data()\nnothing #hide","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"This section discusses how users can incorporate multiple plots into a single figure.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"By using the !-version of the plotting function and inserting a grid position instead of an entire figure, we can create multiple coordinated views.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"We will start by creating a figure with Makie.Figure. ","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"f = Figure()","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"Now any plot can be added to f by placing a grid position, such as f[1, 1].","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"\nf = Figure()\nplot_erp!(f[1, 1], coeftable(uf_deconv))\nplot_erp!(f[1, 2], effects(Dict(:condition => [\"car\", \"face\"]), uf_deconv), \n mapping=(; color=:condition))\nplot_butterfly!(f[2, 1:2], d_topo; positions=positions)\n\nf","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"Using the data from the tutorials, we can create a large image with any type of plot.","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"With so many plots at once, it's tempting to set a fixed resolution in your image to order the plots evenly (code below).","category":"page"},{"location":"how_to/mult_vis_in_fig/","page":"Include multiple Visualizations in one Figure","title":"Include multiple Visualizations in one Figure","text":"\nf = Figure(resolution=(2000, 2000))\n\nplot_butterfly!(f[1, 1:3], d_topo; positions=positions)\n\npvals = DataFrame(\n from=[0.1, 0.15],\n to=[0.2, 0.5],\n # if coefname not specified, line should be black\n coefname=[\"(Intercept)\", \"category: face\"]\n)\nplot_erp!(f[2, 1:2], results, \n categorical_color=false,\n categorical_group=false,\n pvalue=pvals,\n stderror=true)\n\n\nplot_designmatrix!(f[2, 3], designmatrix(uf))\n\nplot_topoplot!(f[3, 1], data[:, 150, 1]; positions=positions)\nplot_topoplotseries!(f[4, 1:3], d_topo, 0.1; positions=positions, mapping=(; label=:channel))\n\nres_effects = effects(Dict(:continuous => -5:0.5:5), uf_deconv)\n\nplot_erp!(f[2, 4:5], res_effects; categorical_color=false, categorical_group=true,\n mapping=(; y=:yhat, color=:continuous, group=:continuous),\n legend=(; nbanks=2),\n layout=(; show_legend=true, legend_position=:right))\n\nplot_parallelcoordinates!(f[3, 2:3], uf_5chan, [1, 2, 3, 4, 5]; mapping=(; color=:coefname), \n layout=(; legend_position=:bottom))\n\nplot_erpimage!(f[1, 4:5], times, d_singletrial)\nplot_circulareegtopoplot!(f[3:4, 4:5], d_topo[in.(d_topo.time, Ref(-0.3:0.1:0.5)), :];\n positions=positions, predictor=:time, predictor_bounds=[-0.3, 0.5])\n\nf","category":"page"},{"location":"tutorials/topoplotseries/#tpseries_vis","page":"Topo Plot Series","title":"Topoplot Series Visualization","text":"","category":"section"},{"location":"tutorials/topoplotseries/#Include-used-Modules","page":"Topo Plot Series","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing TopoPlots","category":"page"},{"location":"tutorials/topoplotseries/#Plot-Topoplot-Series","page":"Topo Plot Series","title":"Plot Topoplot Series","text":"","category":"section"},{"location":"tutorials/topoplotseries/#Example-data","page":"Topo Plot Series","title":"Example data","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"In case you do not already have data, you can get example data from the TopoPlots module. You can do it like this:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"data, positions = TopoPlots.example_data()\ndf = UnfoldMakie.eeg_matrix_to_dataframe(data[:,:,1], string.(1:length(positions)));\nnothing #hide","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"Δbin = 80\nplot_topoplotseries(df, Δbin; positions = positions)","category":"page"},{"location":"tutorials/topoplotseries/#Arguments-usage","page":"Topo Plot Series","title":"Arguments usage","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.\ndata::DataFrame: DataFrame with data, needs a time column.\nΔbin::Real: A number for how large one time bin should be. Δbin is in units of the data.time column.","category":"page"},{"location":"tutorials/topoplotseries/#Key-arguments","page":"Topo Plot Series","title":"Key arguments","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"combinefun (default: mean) - can be used to specify how the samples within Δbin are combined.\nrasterize_heatmaps (default: true) - enforce rasterization of the plot heatmap when saving in svg format. This has the benefit that all lines/points are vectors, except the interpolated heatmap. This is typically what you want, otherwise you get ~500x500 vectors per topoplot, which makes everything super slow.\ncol_labels, row_labels - shows column and row labels. \nlabels (default: nothing) - .\npositions (default: nothing) - .","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"Disabling colorbar:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"plot_topoplotseries(df, Δbin; positions=positions, layout = (; use_colorbar=false))","category":"page"},{"location":"tutorials/topoplotseries/#Positions","page":"Topo Plot Series","title":"Positions","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"You can give either positions, or labels. If both are provided, positions have priority","category":"page"},{"location":"tutorials/topoplotseries/#plot_toposeries(...;-mapping(;-keyvalue))","page":"Topo Plot Series","title":"plot_toposeries(...; mapping=(; key=value))","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"mapping=(: y=(:estimate, :yhat, :y))","category":"page"},{"location":"tutorials/topoplotseries/#visual(;)","page":"Topo Plot Series","title":"visual=(;)","text":"","category":"section"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"label_text (boolean, false) Indicates whether label should drawn next to their position. The labels have to be given into the function seperately:","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"important: Important\ncurrently bugged","category":"page"},{"location":"tutorials/topoplotseries/","page":"Topo Plot Series","title":"Topo Plot Series","text":"label_scatter (boolean, true) - Indicates whether the dots should be drawn at the given positions.","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"EditURL = \"../../../literate/reference/positions.jl\"","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"using UnfoldMakie\nusing CairoMakie\nusing TopoPlots\nusing PyMNE","category":"page"},{"location":"generated/reference/positions/#get-MNE-positions","page":"Convert 3D positions / montages to 2D layouts","title":"get MNE-positions","text":"","category":"section"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"Generate a fake MNE structure taken from mne documentation","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"biosemi_montage = PyMNE.channels.make_standard_montage(\"biosemi64\")\nn_channels = length(biosemi_montage.ch_names)\nfake_info = PyMNE.create_info(ch_names=biosemi_montage.ch_names, sfreq=250.,\n ch_types=\"eeg\")\ndata = rand(n_channels,1) * 1e-6\nfake_evoked = PyMNE.EvokedArray(data, fake_info)\nfake_evoked.set_montage(biosemi_montage)\n\npos = to_positions(fake_evoked)","category":"page"},{"location":"generated/reference/positions/#project-from-3D-electrode-locations-to-2D","page":"Convert 3D positions / montages to 2D layouts","title":"project from 3D electrode locations to 2D","text":"","category":"section"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"pos3d = hcat(values(pyconvert(Dict,biosemi_montage.get_positions()[\"ch_pos\"]))...)\n\npos2 = to_positions(pos3d)\n\nf = Figure(resolution=(600,300))\nscatter(f[1,1],pos3d[1:2,:])\nscatter(f[1,2],pos2)\nf","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"as one can see, the \"naive\" transform of just dropping the third dimension doesnt really work (left). We rather have to project the chanels to a sphere and unfold it (right)","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"","category":"page"},{"location":"generated/reference/positions/","page":"Convert 3D positions / montages to 2D layouts","title":"Convert 3D positions / montages to 2D layouts","text":"This page was generated using Literate.jl.","category":"page"},{"location":"tutorials/parallelcoordinates/#pcp_vis","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Here we discuss parallel coordinates plot (PCP) visualization. ","category":"page"},{"location":"tutorials/parallelcoordinates/#Include-used-Modules","page":"Parallel Coordinates Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie","category":"page"},{"location":"tutorials/parallelcoordinates/#Data","page":"Parallel Coordinates Plot","title":"Data","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"We use the test data of erpcore-N170.jld2.","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"include(\"../../example_data.jl\")\nresults_plot, positions = example_data();","category":"page"},{"location":"tutorials/parallelcoordinates/#Plot-PCPs","page":"Parallel Coordinates Plot","title":"Plot PCPs","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"plot_parallelcoordinates(results_plot, [5,3,2]; # this selects channel 5,3 & 2 \n mapping = (color = :coefname, y = :estimate))","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"important: Important\nthe following is still outdated...","category":"page"},{"location":"tutorials/parallelcoordinates/#Column-Mappings-for-PCPs","page":"Parallel Coordinates Plot","title":"Column Mappings for PCPs","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Since PCPs use a DataFrame as an input, the library needs to know the names of the columns used for plotting.","category":"page"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"While there are multiple default values that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:","category":"page"},{"location":"tutorials/parallelcoordinates/#y","page":"Parallel Coordinates Plot","title":"y","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is (:y, :estimate, :yhat).","category":"page"},{"location":"tutorials/parallelcoordinates/#channel","page":"Parallel Coordinates Plot","title":"channel","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is :channel.","category":"page"},{"location":"tutorials/parallelcoordinates/#color","page":"Parallel Coordinates Plot","title":"color","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"XXX Default is :coef.","category":"page"},{"location":"tutorials/parallelcoordinates/#time","page":"Parallel Coordinates Plot","title":"time","text":"","category":"section"},{"location":"tutorials/parallelcoordinates/","page":"Parallel Coordinates Plot","title":"Parallel Coordinates Plot","text":"Default is :time.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"EditURL = \"../../../literate/tutorials/erp.jl\"","category":"page"},{"location":"generated/tutorials/erp/#lp_vis","page":"ERP plot","title":"Line Plot Visualization","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Here we discuss ERP plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"generated/tutorials/erp/#Include-used-Modules","page":"ERP plot","title":"Include used Modules","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing DataFramesMeta\nusing UnfoldSim\nusing UnfoldMakie","category":"page"},{"location":"generated/tutorials/erp/#Setup","page":"ERP plot","title":"Setup","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Let's generate some data. We'll fit a model with a 2 level categorical predictor and a continuous predictor with interaction.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"data, evts = UnfoldSim.predef_eeg(; noiselevel = 12, return_epoched = true)\ndata = reshape(data, (1, size(data)...))\nf = @formula 0 ~ 1 + condition + continuous\nse_solver = (x, y) -> Unfold.solver_default(x, y, stderror = true);\n\nm = fit(\n UnfoldModel,\n Dict(Any => (f, range(0, step = 1 / 100, length = size(data, 2)))),\n evts,\n data,\n solver = se_solver,\n)\nresults = coeftable(m)\nres_effects = effects(Dict(:continuous => -5:0.5:5), m);\nnothing #hide","category":"page"},{"location":"generated/tutorials/erp/#Plot-the-results","page":"ERP plot","title":"Plot the results","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(results; :stderror => true,)","category":"page"},{"location":"generated/tutorials/erp/#Column-Mappings-for-Line-Plots","page":"ERP plot","title":"Column Mappings for Line Plots","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp use a DataFrame as an input, the library needs to know the names of the columns used for plotting.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"There are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name can be chosen using plot_erp(...; mapping=(; :y=:my_estimate)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":":x Default is (:x, :time). :y Default is (:y, :estimate, :yhat). :color Default is (:color, :coefname).","category":"page"},{"location":"generated/tutorials/erp/#Configuration-for-Line-Plots","page":"ERP plot","title":"Configuration for Line Plots","text":"","category":"section"},{"location":"generated/tutorials/erp/#key-values","page":"ERP plot","title":"key values","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(...; =,...).","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"categorical_color (boolean, true) - in case of numeric :color column, treat :color as continuous or categorical variable.\ncategorical_group (boolean, true) - in case of numeric :group column, treat :group as categorical variable by default.\ntopolegend (bool, false): add an inlay topoplot with corresponding electrodes.\nstderror (bool, false): add an error ribbon, with lower and upper limits based on the :stderror column.\npvalue (Array, []): show a pvalue (see below).","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Using some general configurations we can pretty up the default visualization. Here we use the following configuration:","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(\n res_effects;\n mapping = (; y = :yhat, color = :continuous, group = :continuous),\n legend = (; nbanks = 2),\n layout = (; showLegend = true, legend_position = :right),\n categorical_color = false, categorical_group = true,\n)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"In the following we will use this \"pretty\" line plot as a basis for looking into configuration options.","category":"page"},{"location":"generated/tutorials/erp/#pvalue-(array)","page":"ERP plot","title":"pvalue (array)","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"important: Important\nthis is currently broken!","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Is an array of p-values. If array not empty, plot shows colored lines under the plot representing the p-values. Default is [] (an empty array). Below is an example in which pvalue are given: pvals = DataFrame(","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"#\t\tfrom=[0.1,0.3],\n#\t\tto=[0.5,0.7],\n#\t\tcoefname=[\"(Intercept)\", \"condition: face\"] # if coefname not specified, line should be black\n#\t)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"plot_erp(results; :pvalue=>pvals)","category":"page"},{"location":"generated/tutorials/erp/#stderror-(boolean)","page":"ERP plot","title":"stderror (boolean)","text":"","category":"section"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"Indicating whether the plot should show a colored band showing lower and higher estimates based on the stderror. Default is false.","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"previously we showed :stderror- but low/high is possible as well`","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"results.se_low = results.estimate .- 0.5\nresults.se_high = results.estimate .+ 0.15\nplot_erp(select(results, Not(:stderror)); stderror = true)","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"note: Note\nas in the above code,:stderror has precedence over :se_low/:se_high","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"","category":"page"},{"location":"generated/tutorials/erp/","page":"ERP plot","title":"ERP plot","text":"This page was generated using Literate.jl.","category":"page"},{"location":"tutorials/erpimage/#erpi_vis","page":"ERP Image","title":"ERP Image Visualization","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"Here we discuss ERP image visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/erpimage/#Include-used-Modules","page":"ERP Image","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"using Unfold\nusing UnfoldMakie\nusing CairoMakie\nusing UnfoldSim\ninclude(\"../../example_data.jl\")","category":"page"},{"location":"tutorials/erpimage/#Plot-ERP-image","page":"ERP Image","title":"Plot ERP image","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"The following code will result in the default configuration. ","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"data, evts = UnfoldSim.predef_eeg(; noiselevel=10, return_epoched=true)\nplot_erpimage(data)","category":"page"},{"location":"tutorials/erpimage/#Column-Mappings-for-ERP-image","page":"ERP Image","title":"Column Mappings for ERP image","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"Since ERP images use a Matrix as an input, the library does not need any informations about the mapping.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"erpblur (Number, 10): number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"Non-Positive values deactivate the blur.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"sortvalues (bool, false): parameter over which plot will be sorted. Using sortperm() of Base Julia. \nsortperm() computes a permutation of the array's indices that puts the array into sorted order. \nmeanplot (bool, false): Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data.","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"plot_erpimage(data;\n meanplot = true,\n colorbar = (label = \"Voltage [µV]\",),\n visual = (colormap = :viridis, colorrange = (-40, 40)))\n","category":"page"},{"location":"tutorials/erpimage/#Sorted-ERP-image","page":"ERP Image","title":"Sorted ERP image","text":"","category":"section"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":"First, generate a data. Second, specify the necessary sorting parameter. ","category":"page"},{"location":"tutorials/erpimage/","page":"ERP Image","title":"ERP Image","text":" dat, evts = UnfoldSim.predef_eeg(; \n onset=LogNormalOnset(μ=3.5, σ=0.4), \n noiselevel=5\n )\n dat_e, times = Unfold.epoch(dat, evts, [-0.1,1], 100)\n evts, dat_e = Unfold.dropMissingEpochs(evts, dat_e)\n evts.Δlatency = diff(vcat(evts.latency, 0))\n dat_e = dat_e[1,:,:]\n\n plot_erpimage(times, dat_e; sortvalues=evts.Δlatency)","category":"page"},{"location":"tutorials/butterfly/#bfp_vis","page":"Butterfly Plot","title":"Butterfly Plot Visualization","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Here we discuss butterfly plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/butterfly/#Include-used-Modules","page":"Butterfly Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"using UnfoldMakie\nusing Unfold\nusing CairoMakie\nusing DataFrames","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Note that DataFramesMeta is also used here in order to be able to use @subset for testing (filtering).","category":"page"},{"location":"tutorials/butterfly/#Data","page":"Butterfly Plot","title":"Data","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"We filter the data to make it more clearly represented:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"include(\"../../example_data.jl\")\ndf, pos = example_data(\"TopoPlots.jl\")\nfirst(df, 3)","category":"page"},{"location":"tutorials/butterfly/#Plot-Butterfly-Plots","page":"Butterfly Plot","title":"Plot Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"The following code will plot the default butterfly plot","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"plot_butterfly(df)","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"or if you provide the channel positions:","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"plot_butterfly(df; positions=pos)","category":"page"},{"location":"tutorials/butterfly/#Column-Mappings-for-Butterfly-Plots","page":"Butterfly Plot","title":"Column Mappings for Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Since butterfly plots use a DataFrame as input, the library needs to know the names of the columns used for plotting. You can set these mapping values by calling plot_butterfly(...; mapping=(; :x=:time)), that is, by specifying a NamedTuple (note the ; right after the opening parentheses).","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"While there are several default values that will be checked in that order if they exist in the DataFrame, a custom name may need to be chosen:","category":"page"},{"location":"tutorials/butterfly/#x","page":"Butterfly Plot","title":"x","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:x, :time).","category":"page"},{"location":"tutorials/butterfly/#y","page":"Butterfly Plot","title":"y","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:y, :estimate, :yhat).","category":"page"},{"location":"tutorials/butterfly/#labels","page":"Butterfly Plot","title":"labels","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Default is (:labels, :label, :topoLabels, :sensor, :nothing)","category":"page"},{"location":"tutorials/butterfly/#Configurations-for-Butterfly-Plots","page":"Butterfly Plot","title":"Configurations for Butterfly Plots","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Here we look into possible options for configuring the butterfly plot visualization using (...; =, ...).","category":"page"},{"location":"tutorials/butterfly/#key-values","page":"Butterfly Plot","title":"key values","text":"","category":"section"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"butterfly (bool, true): create a butterfly plot.\ntopolegend (bool, true): show an inlay topoplot with corresponding electrodes.\ntopomarkersize (Real, 10): change the size of the markers, topoplot-inlay electrodes.\ntopowidth (Real, 0.25): change the size of the inlay topoplot width.\ntopoheigth (Real, 0.25): change the size of the inlay topoplot height.\ntopopositions_to_color (function, ´x -> posToColorRomaO(x)´).","category":"page"},{"location":"tutorials/butterfly/","page":"Butterfly Plot","title":"Butterfly Plot","text":"Since the configurations for ERP plots can be applied to butterfly plots as well. Here you can find the configurations for ERP plots.","category":"page"},{"location":"tutorials/topoplot/#tp_vis","page":"Topo Plot","title":"Topo Plot Visualization","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Here we discuss topo plot visualization. Make sure you have looked into the installation instructions.","category":"page"},{"location":"tutorials/topoplot/#Include-used-Modules","page":"Topo Plot","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie\nusing TopoPlots","category":"page"},{"location":"tutorials/topoplot/#Plot-Topo-Plots","page":"Topo Plot","title":"Plot Topo Plots","text":"","category":"section"},{"location":"tutorials/topoplot/#Providing-the-Data","page":"Topo Plot","title":"Providing the Data","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"data, positions = TopoPlots.example_data()","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"We select one datapoint, and the first enry of dimension 3 (the mean estimate, the others are p-value and std)","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(data[:,340,1]; positions = positions)","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"using DataFrames\ndf = DataFrame(:estimate => data[:,340,1])\nplot_topoplot(df; positions = positions)","category":"page"},{"location":"tutorials/topoplot/#Giving-the-Positions","page":"Topo Plot","title":"Giving the Positions","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Since the topo plot needs the positions of the sensors they have to be put into the drawing function. But there are multiple options (In order of prioritization):","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Giving the positions directly: plot_topoplot(...; positions=[...])\nGiving the labels of the sensors: plot_topoplot(...; labels=[...])","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"To get the positions from the labels we use a database.","category":"page"},{"location":"tutorials/topoplot/#Column-Mappings-for-Topo-Plots","page":"Topo Plot","title":"Column Mappings for Topo Plots","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"When using topo plots with a DataFrame as an input, the library needs to know the names of the columns used for plotting. This is specified using the mapping=(;) kwargs.","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"While there are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Note that only one of positions or labels have to be set to draw a topo plot. If both are set, positions takes precedence, labels might be used for labelling electrodes in TopoPlots.jl","category":"page"},{"location":"tutorials/topoplot/#(...,mapping(;))","page":"Topo Plot","title":"(...,mapping=(;))","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":":y plotting function looks in the default columns of mapping","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"cfgDefault = UnfoldMakie.PlotConfig()\ncfgDefault.mapping.y","category":"page"},{"location":"tutorials/topoplot/#label_text-(boolean)","page":"Topo Plot","title":"label_text (boolean)","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Indicates whether label should drawn next to their position. Obviously the labels have to be provided: plot_topoplot(...; labels=[...])","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(...; visual=(; label_text=true))","category":"page"},{"location":"tutorials/topoplot/#label_scatter-(boolean)","page":"Topo Plot","title":"label_scatter (boolean)","text":"","category":"section"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"Indicates whether the dots should be drawn at the given positions.","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"plot_topoplot(...; visual=(; label_scatter=true))","category":"page"},{"location":"tutorials/topoplot/","page":"Topo Plot","title":"Topo Plot","text":"data, positions = TopoPlots.example_data()\nplot_topoplot(data[1:4,340,1]; visual = (; label_scatter = false), labels=[\"O1\", \"F2\", \"F3\", \"P4\"])","category":"page"},{"location":"tutorials/designmatrix/#dm_vis","page":"Designmatrix","title":"Designmatrix Visualization","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"Here we discuss design matrix visualization. Make sure you have looked into the installation instructions section. ","category":"page"},{"location":"tutorials/designmatrix/#Include-used-Modules","page":"Designmatrix","title":"Include used Modules","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"The following modules are necessary for following this tutorial:","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"using Unfold\nusing UnfoldMakie\nusing DataFrames\nusing CairoMakie","category":"page"},{"location":"tutorials/designmatrix/#Data","page":"Designmatrix","title":"Data","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"include(\"../../example_data.jl\")\nuf = example_data(\"UnfoldLinearModel\")\n","category":"page"},{"location":"tutorials/designmatrix/#Plot-Designmatrices","page":"Designmatrix","title":"Plot Designmatrices","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"The following code will result in the default configuration. ","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"plot_designmatrix(designmatrix(uf))","category":"page"},{"location":"tutorials/designmatrix/#kwargs-plot_designmatrix(...;-...).","page":"Designmatrix","title":"kwargs plot_designmatrix(...; ...).","text":"","category":"section"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"sort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia. ","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"To make the design matrix easier to read, you may want to sort it.","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"plot_designmatrix(designmatrix(uf); sortData=true)","category":"page"},{"location":"tutorials/designmatrix/","page":"Designmatrix","title":"Designmatrix","text":"standardize_data (bool,true): indicates whether the data is standardized by pointwise division of the data with its sampled standard deviation.\nsort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia. \nxticks (nothing): returns the number of labels on the x-axis. Behavior is set in the configuration:\nxticks = 0: no labels are placed.\nxticks = 1: first possible label is placed.\nxticks = 2: first and last possible labels are placed.\n2 < xticks < number of labels: equally distribute the labels.\nxticks ≥ number of labels: all labels are placed.","category":"page"},{"location":"how_to/hide_deco/#ht_hide_deco","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"","category":"section"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"This section discusses how users can efficiently hide axis spines and decorations in their plots.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"While it's possible to hide these axis decorations by setting the axis settings with axis=(;...), Makie.Axis provides multiple variables for different aspects of the plot. This means that removing all decorations is only possible by setting many variables each time.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Makie does provide methods like hidespines! and hidedecorations!, but the user may not have easy access to the axis their plot is drawn in.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Instead, these functions can be called by setting variables with layout = (;):","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"... layout = (\n ...\n hidespines = (),\n hidedecorations = ()\n)","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Since these values reflect the input to the function, we can use an empty tuple to remove all decorations and spines, respectively","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"And using hidespines = (:r, :t) will remove the top and right borders.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"For more information on the input of these functions refer to the Makie dokumentation on Axis.","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"Since some plots hide features by default, the hiding can be reverted by setting the variables to nothing","category":"page"},{"location":"how_to/hide_deco/","page":"Hide Axis Spines and Decorations","title":"Hide Axis Spines and Decorations","text":"using TopoPlots\nusing UnfoldMakie\nusing CairoMakie\n\ndata, positions = TopoPlots.example_data()\nplot_topoplot(data[:,340,1]; \n positions = positions, \n layout=(;\n hidespines = nothing,\n hidedecorations = nothing\n ),)","category":"page"},{"location":"#UnfoldMakie-Documentation","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"","category":"section"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"This is the documentation of the UnfoldMakie module for the Julia programming language. ","category":"page"},{"location":"#About","page":"UnfoldMakie Documentation","title":"About","text":"","category":"section"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"UnfoldMakie aims to allow users to create different types of visualizations. These include line plots, butterfly plots, design matrices, parallel coordinate plots, ERP images, and topo plots. Building on the Unfold and Makie Modules, it also allows users to customize the plots through an input configuration.","category":"page"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"As can be seen from the types of visualizations possible, these configuration options try to enable the user to create plots that are helpful in the field of computational EEG. One such example is the ability to use a topo plot as a legend for a line plot by allowing multiple visualizations within a figure.","category":"page"},{"location":"","page":"UnfoldMakie Documentation","title":"UnfoldMakie Documentation","text":"(Image: Coordinated Multiple Views)","category":"page"},{"location":"tutorials/installation/#install_instruct","page":"Installation","title":"Installation","text":"","category":"section"},{"location":"tutorials/installation/#Getting-Julia","page":"Installation","title":"Getting Julia","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"You can install Julia by following the instructions from the official website. ","category":"page"},{"location":"tutorials/installation/#Setup-UnfoldMakie.jl","page":"Installation","title":"Setup UnfoldMakie.jl","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"After installing Julia, you can execute the julia.exe. ","category":"page"},{"location":"tutorials/installation/#Generate-a-Project","page":"Installation","title":"Generate a Project","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"If you do not yet have a project you can generate one. First you type ] into the Julia console to switch from julia to (@VERSION) pkg. Here you can generate a project by using the command: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"generate \"FOLDER_PATH\"","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Note that the specific folder in which you want to generate the project does not already exist.","category":"page"},{"location":"tutorials/installation/#Activate-your-Project","page":"Installation","title":"Activate your Project","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Before you can add the necessary modules to use UnfoldMakie you have to activate your project in the (@VERSION) pkg environment. The command is: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"activate \"FOLDER_PATH\"","category":"page"},{"location":"tutorials/installation/#Install-the-UnfoldMakie-Module","page":"Installation","title":"Install the UnfoldMakie Module","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"When your project is activated you can add the module. The command is: ","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"add UnfoldMakie","category":"page"},{"location":"tutorials/installation/#Using-the-Project-in-a-Notebook","page":"Installation","title":"Using the Project in a Notebook","text":"","category":"section"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"In case you want to use this generated project in a notebook (e.g. Pluto or Jupyter), you can activate this in the notebook in the following manner:","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"begin\n using Pkg\n Pkg.activate(\"FOLDER_PATH\")\n Pkg.resolve()\nend","category":"page"},{"location":"tutorials/installation/","page":"Installation","title":"Installation","text":"Use slash / for the folder path. ","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"EditURL = \"../../../literate/tutorials/circTopo.jl\"","category":"page"},{"location":"generated/tutorials/circTopo/#Circular-Topoplot-Arrangement","page":"Circular TopoPlot","title":"Circular Topoplot Arrangement","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"using UnfoldMakie\nusing CairoMakie\nusing TopoPlots # for example data\nusing Random\nusing DataFrames","category":"page"},{"location":"generated/tutorials/circTopo/#Generate-data","page":"Circular TopoPlot","title":"Generate data","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"Generate a Dataframe. We need to specify the TopoPlot Positions either via position, or via labels (according to TopoPlots.jl)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"data, pos = TopoPlots.example_data();\ndat = data[:, 240, 1]\ndf = DataFrame(\n :estimate => eachcol(Float64.(data[:, 100:40:300, 1])),\n :circular_variable => [0, 50, 80, 120, 180, 210],\n :time => 100:40:300,\n)\ndf = flatten(df, :estimate);\nnothing #hide","category":"page"},{"location":"generated/tutorials/circTopo/#Our-first-plot!","page":"Circular TopoPlot","title":"Our first plot!","text":"","category":"section"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"note how the plots are at the angles of circular_variable`","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"plot_circulareegtopoplot(\n df;\n positions = pos,\n axis = (; label = \"Incoming saccade\"),\n predictor = :circular_variable,\n)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"In case the bounding variable is not between 0 and 360, as here we use actually time, we have to specify it. e.g.","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"plot_circulareegtopoplot(\n df;\n positions = pos,\n axis = (; label = \"Time?!\"),\n predictor = :time,\n predictor_bounds = [80, 320],\n)","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"","category":"page"},{"location":"generated/tutorials/circTopo/","page":"Circular TopoPlot","title":"Circular TopoPlot","text":"This page was generated using Literate.jl.","category":"page"}] } diff --git a/dev/tutorials/butterfly/index.html b/dev/tutorials/butterfly/index.html index 9da0070f9..7e4477841 100644 --- a/dev/tutorials/butterfly/index.html +++ b/dev/tutorials/butterfly/index.html @@ -1,7 +1,7 @@ -Butterfly Plot · UnfoldMakie.jl

Butterfly Plot Visualization

Here we discuss butterfly plot visualization. Make sure you have looked into the installation instructions.

Include used Modules

The following modules are necessary for following this tutorial:

using UnfoldMakie
+Butterfly Plot · UnfoldMakie.jl
Butterfly Plot Visualization
Here we discuss butterfly plot visualization.  Make sure you have looked into the installation instructions.
Include used Modules
The following modules are necessary for following this tutorial:
using UnfoldMakie
 using Unfold
 using CairoMakie
 using DataFrames
Note that DataFramesMeta is also used here in order to be able to use @subset for testing (filtering).
Data
We filter the data to make it more clearly represented:
include("../../example_data.jl")
 df, pos = example_data("TopoPlots.jl")
-first(df, 3)
3×7 DataFrame
RowestimatetimechannelcoefnametopoPositionssepval
Float64Float64Int64StringAnyFloat64Float64
10.020321-0.31A(0.493714, 0.544031)0.1228750.266091
20.017548-0.2981A(0.493714, 0.544031)0.1243450.29664
30.0150747-0.2961A(0.493714, 0.544031)0.1248280.323592
Plot Butterfly Plots
The following code will plot the default butterfly plot
plot_butterfly(df)
Example block output
or if you provide the channel positions:
plot_butterfly(df; positions=pos)
Example block output
Column Mappings for Butterfly Plots
Since butterfly plots use a DataFrame as input, the library needs to know the names of the columns used for plotting. You can set these mapping values by calling plot_butterfly(...; mapping=(; :x=:time,)), that is, by specifying a NamedTuple (note the ; right after the opening parentheses).
While there are several default values that will be checked in that order if they exist in the DataFrame, a custom name may need to be chosen:
x
Default is (:x, :time).
y
Default is (:y, :estimate, :yhat).
labels
Default is (:labels, :label, :topoLabels, :sensor, :nothing)
Configurations for Butterfly Plots
Here we look into possible options for configuring the butterfly plot visualization using (...; <name>=<value>, ...). This is the list of unique configuration (key values):
  • topoLegend (boolean)
topoLegend (boolean)
Indicating whether the topo legend is displayed. Default is true.
For more general options look into the Plot Configuration section of the documentation.
Since the configurations for line plots can be applied to butterfly plots as well. Here you can find the configurations for line plots, 

+first(df, 3)
3×7 DataFrame
Rowestimatetimechannelcoefnametopo_positionssepval
Float64Float64Int64StringAnyFloat64Float64
10.020321-0.31A(0.493714, 0.544031)0.1228750.266091
20.017548-0.2981A(0.493714, 0.544031)0.1243450.29664
30.0150747-0.2961A(0.493714, 0.544031)0.1248280.323592

Plot Butterfly Plots

The following code will plot the default butterfly plot

plot_butterfly(df)
Example block output

or if you provide the channel positions:

plot_butterfly(df; positions=pos)
Example block output

Column Mappings for Butterfly Plots

Since butterfly plots use a DataFrame as input, the library needs to know the names of the columns used for plotting. You can set these mapping values by calling plot_butterfly(...; mapping=(; :x=:time)), that is, by specifying a NamedTuple (note the ; right after the opening parentheses).

While there are several default values that will be checked in that order if they exist in the DataFrame, a custom name may need to be chosen:

x

Default is (:x, :time).

y

Default is (:y, :estimate, :yhat).

labels

Default is (:labels, :label, :topoLabels, :sensor, :nothing)

Configurations for Butterfly Plots

Here we look into possible options for configuring the butterfly plot visualization using (...; <name>=<value>, ...).

key values

  • butterfly (bool, true): create a butterfly plot.
  • topolegend (bool, true): show an inlay topoplot with corresponding electrodes.
  • topomarkersize (Real, 10): change the size of the markers, topoplot-inlay electrodes.
  • topowidth (Real, 0.25): change the size of the inlay topoplot width.
  • topoheigth (Real, 0.25): change the size of the inlay topoplot height.
  • topopositions_to_color (function, ´x -> posToColorRomaO(x)´).

Since the configurations for ERP plots can be applied to butterfly plots as well. Here you can find the configurations for ERP plots.

diff --git a/dev/tutorials/designmatrix/index.html b/dev/tutorials/designmatrix/index.html index 6e1e547db..f0c26f467 100644 --- a/dev/tutorials/designmatrix/index.html +++ b/dev/tutorials/designmatrix/index.html @@ -1,5 +1,5 @@ -Designmatrix · UnfoldMakie.jl

Designmatrix Visualization

Here we discuss designmatrix visualization. Make sure you have looked into the installation instructions section.

Include used Modules

The following modules are necessary for following this tutorial:

using Unfold
+Designmatrix · UnfoldMakie.jl
Designmatrix Visualization
Here we discuss design matrix visualization.  Make sure you have looked into the installation instructions section. 
Include used Modules
The following modules are necessary for following this tutorial:
using Unfold
 using UnfoldMakie
 using DataFrames
 using CairoMakie
Data
include("../../example_data.jl")
@@ -16,4 +16,4 @@
 
     coeftable(uf) 		(returns tidy result dataframe) 
 
-
Plot Designmatrices
The following code will result in the default configuration. 
plot_designmatrix(designmatrix(uf))
Example block output
kwargs plot_designmatrix(...; ...).
  • sortData (boolean,false)  - Indicating whether the data is sorted; using sortslices() of Base Julia. 
In order to make the designmatrix easier to read, you may want to sort it.
plot_designmatrix(designmatrix(uf); sortData=true)
  • standardizeData (boolean, false) - Indicating whether the data is standardized, mapping the values between 0 and 1. 
  • xTicks (number, nothing)
Indicating the number of labels on the x-axis. Behavior if specified in configuration:     - xTicks = 0: no labels are placed.     - xTicks = 1: first possible label is placed.     - xTicks = 2: first and last possible labels are placed.     - 2 < xTicks < number of labels: xTicks-2 labels are placed between the first and last.     - xTicks ≥ number of labels: all labels are placed.

+

Plot Designmatrices

The following code will result in the default configuration. 

plot_designmatrix(designmatrix(uf))
Example block output

kwargs plot_designmatrix(...; ...).

  • sort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia.

To make the design matrix easier to read, you may want to sort it.

plot_designmatrix(designmatrix(uf); sortData=true)
  • standardize_data (bool,true): indicates whether the data is standardized by pointwise division of the data with its sampled standard deviation.
  • sort_data (bool, true): indicates whether the data is sorted; using sortslices() of Base Julia.
  • xticks (nothing): returns the number of labels on the x-axis. Behavior is set in the configuration:
    • xticks = 0: no labels are placed.
    • xticks = 1: first possible label is placed.
    • xticks = 2: first and last possible labels are placed.
    • 2 < xticks < number of labels: equally distribute the labels.
    • xticks ≥ number of labels: all labels are placed.
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    ERP Image Visualization

    Here we discuss ERP image visualization. Make sure you have looked into the installation instructions.

    Include used Modules

    The following modules are necessary for following this tutorial:

    using Unfold
+ERP Image · UnfoldMakie.jl
    ERP Image Visualization
    Here we discuss ERP image visualization.  Make sure you have looked into the installation instructions.
    Include used Modules
    The following modules are necessary for following this tutorial:
    using Unfold
 using UnfoldMakie
 using CairoMakie
 using UnfoldSim
-include("../../example_data.jl")
    example_data (generic function with 2 methods)
    Plot ERP Images
    The following code will result in the default configuration. 
    data, evts = UnfoldSim.predef_eeg(; noiselevel=10, return_epoched=true)
-plot_erpimage(data)
    Example block output
    Column Mappings for ERP Images
    Since ERP images use a Matrix as an input, the library does not need any informations about the mapping.
    • erpBlur (number, 10) - Is a number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module. Negative values deactivate the blur.
    • sortvalues - Indicating whether the data is sorted; using sortperm() of Base Julia 
    (sortperm() computes a permutation of the array's indices that puts the array into sorted order). 
    • meanPlot (bool, false) - Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data. If limits are set in the axis values both plots will be aligned.
    plot_erpimage(data;
-    meanPlot = true,
+include("../../example_data.jl")
    example_data (generic function with 2 methods)
    Plot ERP image
    The following code will result in the default configuration. 
    data, evts = UnfoldSim.predef_eeg(; noiselevel=10, return_epoched=true)
+plot_erpimage(data)
    Example block output
    Column Mappings for ERP image
    Since ERP images use a Matrix as an input, the library does not need any informations about the mapping.
    • erpblur (Number, 10): number indicating how much blur is applied to the image; using Gaussian blur of the ImageFiltering module.
    Non-Positive values deactivate the blur.
    • sortvalues (bool, false): parameter over which plot will be sorted. Using sortperm() of Base Julia. 
      • sortperm() computes a permutation of the array's indices that puts the array into sorted order. 
    • meanplot (bool, false): Indicating whether the plot should add a line plot below the ERP image, showing the mean of the data.
    plot_erpimage(data;
+    meanplot = true,
     colorbar = (label = "Voltage [µV]",),
-    visual = (colormap = :viridis, colorrange = (-40, 40)))
    Example block output
    
+    visual = (colormap = :viridis, colorrange = (-40, 40)))
    Example block output

    Sorted ERP image

    First, generate a data. Second, specify the necessary sorting parameter. 

        dat, evts = UnfoldSim.predef_eeg(;
+        onset=LogNormalOnset(μ=3.5, σ=0.4),
+        noiselevel=5
+    )
+    dat_e, times = Unfold.epoch(dat, evts, [-0.1,1], 100)
+    evts, dat_e = Unfold.dropMissingEpochs(evts, dat_e)
+    evts.Δlatency =  diff(vcat(evts.latency, 0))
+    dat_e = dat_e[1,:,:]
+
+    plot_erpimage(times, dat_e; sortvalues=evts.Δlatency)
    Example block output
    diff --git a/dev/tutorials/installation/index.html b/dev/tutorials/installation/index.html index fcd14dba5..ee95fa999 100644 --- a/dev/tutorials/installation/index.html +++ b/dev/tutorials/installation/index.html @@ -3,4 +3,4 @@ using Pkg Pkg.activate("FOLDER_PATH") Pkg.resolve() -end

    Use slash / for the folder path.

    +end

    Use slash / for the folder path.

    diff --git a/dev/tutorials/parallelcoordinates/index.html b/dev/tutorials/parallelcoordinates/index.html index 98dce88fc..35dbeac29 100644 --- a/dev/tutorials/parallelcoordinates/index.html +++ b/dev/tutorials/parallelcoordinates/index.html @@ -4,7 +4,7 @@ using DataFrames using CairoMakie

    Data

    We use the test data of erpcore-N170.jld2.

    include("../../example_data.jl")
 results_plot, positions = example_data();
    (25600×7 DataFrame
-   Row │ estimate      time     channel  coefname  topoPositions         se    ⋯
+   Row │ estimate      time     channel  coefname  topo_positions        se    ⋯
        │ Float64       Float64  Int64    String    Any                   Float ⋯
 ───────┼────────────────────────────────────────────────────────────────────────
      1 │  0.020321      -0.3          1  A         (0.493714, 0.544031)  0.122 ⋯
@@ -24,4 +24,4 @@
  25599 │  0.112385       0.496       64  A         (0.719221, 0.888091)  0.262
  25600 │  0.109979       0.498       64  A         (0.719221, 0.888091)  0.258
                                                 2 columns and 25585 rows omitted, Point{2, Float32}[[0.49371386, 0.5440313], [0.5630452, 0.50400287], [0.5630452, 0.4239459], [0.49371386, 0.38391745], [0.4243825, 0.4239459], [0.4243825, 0.50400287], [0.5378472, 0.6178857], [0.61455333, 0.56901854], [0.6522695, 0.4862579], [0.6388263, 0.39630732]  …  [0.93907887, 0.6439135], [0.9450873, 0.29968786], [0.8333667, 0.12432156], [0.61803544, 1.9428903f-16], [0.3693923, 2.7755576f-17], [0.15406103, 0.12432156], [0.029739477, 0.3396528], [0.04834886, 0.6439135], [0.26820713, 0.88809085], [0.7192206, 0.88809085]])

    Plot PCPs

    plot_parallelcoordinates(results_plot, [5,3,2]; # this selects channel 5,3 & 2
-    mapping = (color = :coefname, y = :estimate))
    Example block output
    Important

    the following is still outdated...

    Column Mappings for PCPs

    Since PCPs use a DataFrame as an input, the library needs to know the names of the columns used for plotting.

    While there are multiple default values that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:

    y

    Default is (:y, :estimate, :yhat).

    channel

    Default is :channel.

    color

    XXX Default is :coef.

    time

    Default is :time.

    + mapping = (color = :coefname, y = :estimate))Example block output
    Important

    the following is still outdated...

    Column Mappings for PCPs

    Since PCPs use a DataFrame as an input, the library needs to know the names of the columns used for plotting.

    While there are multiple default values that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:

    y

    Default is (:y, :estimate, :yhat).

    channel

    Default is :channel.

    color

    XXX Default is :coef.

    time

    Default is :time.

    diff --git a/dev/tutorials/topoplot/index.html b/dev/tutorials/topoplot/index.html index daf7c202d..4e6545e9e 100644 --- a/dev/tutorials/topoplot/index.html +++ b/dev/tutorials/topoplot/index.html @@ -7,4 +7,4 @@ df = DataFrame(:estimate => data[:,340,1]) plot_topoplot(df; positions = positions)Example block output

    Giving the Positions

    Since the topo plot needs the positions of the sensors they have to be put into the drawing function. But there are multiple options (In order of prioritization):

    • Giving the positions directly: plot_topoplot(...; positions=[...])
    • Giving the labels of the sensors: plot_topoplot(...; labels=[...])

    To get the positions from the labels we use a database.

    Column Mappings for Topo Plots

    When using topo plots with a DataFrame as an input, the library needs to know the names of the columns used for plotting. This is specified using the mapping=(;) kwargs.

    While there are multiple default values, that are checked in that order if they exist in the DataFrame, a custom name might need to be choosen for:

    Note that only one of positions or labels have to be set to draw a topo plot. If both are set, positions takes precedence, labels might be used for labelling electrodes in TopoPlots.jl

    (...,mapping=(;))

    :y plotting function looks in the default columns of mapping

    cfgDefault = UnfoldMakie.PlotConfig()
 cfgDefault.mapping.y
    (:estimate, :yhat, :y)

    label_text (boolean)

    Indicates whether label should drawn next to their position. Obviously the labels have to be provided: plot_topoplot(...; labels=[...])

    plot_topoplot(...; visual=(; label_text=true))

    label_scatter (boolean)

    Indicates whether the dots should be drawn at the given positions.

    plot_topoplot(...; visual=(; label_scatter=true))

    data, positions = TopoPlots.example_data()
-plot_topoplot(data[1:4,340,1]; visual = (; label_scatter = false), labels=["O1", "F2", "F3", "P4"])
    Example block output +plot_topoplot(data[1:4,340,1]; visual = (; label_scatter = false), labels=["O1", "F2", "F3", "P4"])Example block output diff --git a/dev/tutorials/topoplotseries/index.html b/dev/tutorials/topoplotseries/index.html index ba1a6681f..a77ef5846 100644 --- a/dev/tutorials/topoplotseries/index.html +++ b/dev/tutorials/topoplotseries/index.html @@ -1,8 +1,8 @@ -Topo Plot Series · UnfoldMakie.jl

    Topo Plot SeriesVisualization

    Include used Modules

    The following modules are necessary for following this tutorial:

    using Unfold
+Topo Plot Series · UnfoldMakie.jl
    Topoplot Series Visualization
    Include used Modules
    The following modules are necessary for following this tutorial:
    using Unfold
 using UnfoldMakie
 using DataFrames
 using CairoMakie
-using TopoPlots
    Plot Topo Plots Series
    Giving the Data
    In case you do not already have data, you can get example data from the TopoPlots module.  You can do it like this:
    data, positions = TopoPlots.example_data()
+using TopoPlots
    Plot Topoplot Series
    Example data
    In case you do not already have data, you can get example data from the TopoPlots module.  You can do it like this:
    data, positions = TopoPlots.example_data()
 df = UnfoldMakie.eeg_matrix_to_dataframe(data[:,:,1], string.(1:length(positions)));
    Δbin = 80
-plot_topoplotseries(df, Δbin; positions = positions)
    Example block output
    Without colorbar:
    plot_topoplotseries(df, Δbin; positions=positions, layout = (; useColorbar=false))
    Example block output
    Positions
    You can give either positions, or labels. If both are provided, positions have priority
    plot_toposeries(...; mapping=(; key=value))
    mapping=(: y=(:estimate, :yhat, :y))
    visual=(;)
    label_text (boolean, false) Indicates whether label should drawn next to their position. The labels have to be given into the function seperately:
    Important
    currently bugged
    label_scatter (boolean, true) - Indicates whether the dots should be drawn at the given positions.
    
+plot_topoplotseries(df, Δbin; positions = positions)
    Example block output

    Arguments usage

    • f::Union{GridPosition, GridLayout, Figure}: Figure or GridPosition that the plot should be drawn into.
    • data::DataFrame: DataFrame with data, needs a time column.
    • Δbin::Real: A number for how large one time bin should be. Δbin is in units of the data.time column.

    Key arguments

    • combinefun (default: mean) - can be used to specify how the samples within Δbin are combined.
    • rasterize_heatmaps (default: true) - enforce rasterization of the plot heatmap when saving in svg format. This has the benefit that all lines/points are vectors, except the interpolated heatmap. This is typically what you want, otherwise you get ~500x500 vectors per topoplot, which makes everything super slow.
    • col_labels, row_labels - shows column and row labels.
    • labels (default: nothing) - .
    • positions (default: nothing) - .

    Disabling colorbar:

    plot_topoplotseries(df, Δbin; positions=positions, layout = (; use_colorbar=false))
    Example block output

    Positions

    You can give either positions, or labels. If both are provided, positions have priority

    plot_toposeries(...; mapping=(; key=value))

    mapping=(: y=(:estimate, :yhat, :y))

    visual=(;)

    label_text (boolean, false) Indicates whether label should drawn next to their position. The labels have to be given into the function seperately:

    Important

    currently bugged

    label_scatter (boolean, true) - Indicates whether the dots should be drawn at the given positions.