Plotting Functions

All public plotting functions in EegFun.jl.

Index

EegFun.plot_artifact_components
EegFun.plot_artifact_detection
EegFun.plot_artifact_rejection
EegFun.plot_artifact_repair
EegFun.plot_channel_spectrum
EegFun.plot_channel_summary
EegFun.plot_channel_summary!
EegFun.plot_confusion_matrix
EegFun.plot_correlation_heatmap
EegFun.plot_correlation_heatmap!
EegFun.plot_databrowser
EegFun.plot_databrowser
EegFun.plot_databrowser
EegFun.plot_databrowser
EegFun.plot_decoding
EegFun.plot_ecg_component_features
EegFun.plot_eog_component_features
EegFun.plot_epochs
EegFun.plot_erp
EegFun.plot_erp!
EegFun.plot_erp_errorbar
EegFun.plot_erp_errorbar
EegFun.plot_erp_errorbar
EegFun.plot_erp_errorbar!
EegFun.plot_erp_errorbar!
EegFun.plot_erp_filter_gui
EegFun.plot_erp_filter_gui
EegFun.plot_erp_filter_gui
EegFun.plot_erp_filter_gui
EegFun.plot_erp_image
EegFun.plot_erp_measurement_gui
EegFun.plot_erp_measurement_gui
EegFun.plot_erp_measurement_gui
EegFun.plot_erp_measurements
EegFun.plot_erp_stats
EegFun.plot_filter_response
EegFun.plot_gfp
EegFun.plot_gui
EegFun.plot_ica_component_activation
EegFun.plot_ica_component_spectrum
EegFun.plot_joint_probability
EegFun.plot_joint_probability!
EegFun.plot_layout
EegFun.plot_layout!
EegFun.plot_layout_2d
EegFun.plot_layout_2d!
EegFun.plot_layout_3d
EegFun.plot_layout_3d!
EegFun.plot_line_noise_components
EegFun.plot_model_correlations
EegFun.plot_rdm_heatmap
EegFun.plot_rdm_timecourse
EegFun.plot_rsa
EegFun.plot_spatial_kurtosis_components
EegFun.plot_stat_heatmap
EegFun.plot_tf
EegFun.plot_tf_stats
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography
EegFun.plot_topography!
EegFun.plot_topography!
EegFun.plot_topography_3d
EegFun.plot_topography_3d
EegFun.plot_topography_stats
EegFun.plot_topography_stats
EegFun.plot_trigger_overview
EegFun.plot_trigger_timing

Functions

julia

plot_artifact_components(ica::InfoIca, artifacts::ArtifactComponents; kwargs...)

Plot topoplots for all artifact components organized by type (vEOG, hEOG, ECG, Line Noise, Channel Noise).

This is a convenience function that takes the output of combine_artifact_components and creates a comprehensive visualization showing all identified artifact components with clear labels.

Arguments

ica::InfoIca: The ICA result object
artifacts::ArtifactComponents: The artifact components structure from combine_artifact_components

Keyword Arguments

All keyword arguments from plot_topography are supported, including:

method::Symbol: Interpolation method (see plot_topography for supported methods)
gridscale::Int: Grid resolution for interpolation
colormap: Colormap for the topography
display_plot::Bool: Whether to display the plot

Returns

Figure: The Makie Figure containing all topoplots

Examples

julia

# Identify artifact components
eog_comps, _ = identify_eog_components(dat, ica)
ecg_comps, _ = identify_ecg_components(dat, ica)
line_noise_comps, _ = identify_line_noise_components(dat, ica)
channel_noise_comps, _ = identify_spatial_kurtosis_components(ica)

# Combine them
artifacts = combine_artifact_components(eog_comps, ecg_comps, line_noise_comps, channel_noise_comps)

# Plot all artifact components
fig = plot_artifact_components(ica, artifacts)

source

EegFun.plot_artifact_detection Method

julia

plot_artifact_detection(epochs::EpochData, artifacts::EpochRejectionInfo; channel_selection::Function=channels(), kwargs...)

Interactive plot of artifact detection results with Previous/Next buttons for epoch navigation.

Arguments

epochs::EpochData: The epoch data
artifacts::EpochRejectionInfo: Artifact detection results
channel_selection::Function: Channel predicate for selecting channels to plot (default: all layout channels)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Whether to add origin lines at x=0 and y=0
alpha_normal::Float64 = 0.2: Transparency for normal channels.
alpha_rejected::Float64 = 1.0: Transparency for rejected channels.
colormap_name::Nothing = nothing: Colormap name (e.g., :Set1_9, :tab20).
display_plot::Bool = true: Display plot.
linewidth_normal::Int64 = 1: Line width for normal channels.
linewidth_rejected::Int64 = 2: Line width for rejected channels.
selection_threshold::Int64 = 50: Distance threshold for channel selection.
xgrid::Bool = false: Whether to show x-axis grid
xlim::Nothing = nothing: X-axis limits as (min, max) tuple or nothing for auto-scaling
xminorgrid::Bool = false: Whether to show x-axis minor grid
ygrid::Bool = false: Whether to show y-axis grid
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple or nothing for auto-scaling
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

Figure: Interactive Makie figure with navigation buttons

Examples

julia

# Basic interactive plot
fig = plot_artifact_detection(epochs, artifacts)

# With specific channels
fig = plot_artifact_detection(epochs, artifacts, 
                            channel_selection = channels([:Fp1, :Fp2, :Cz]))

# With custom axis limits
fig = plot_artifact_detection(epochs, artifacts, xlim = (-0.2, 0.8), ylim = (-100, 100))

source

EegFun.plot_artifact_rejection Method

julia

plot_artifact_rejection(epochs_raw::EpochData, epochs_rejected::EpochData, artifacts::EpochRejectionInfo; channel_selection::Function=channels(), kwargs...)

Interactive plot comparison between original and rejected epochs with navigation buttons. Epochs are aligned by epoch number from the dataframe. If an epoch was rejected (doesn't exist in epochs_rejected), both plots show a blank plot with red spines.

Arguments

epochs_raw::EpochData: Original epoch data (before rejection)
epochs_rejected::EpochData: Epoch data after rejection (may have fewer epochs)
artifacts::EpochRejectionInfo: Artifact detection results
channel_selection::Function: Channel predicate for selecting channels to plot (default: all layout channels)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Whether to add origin lines at x=0 and y=0
alpha_normal::Float64 = 0.2: Transparency for normal channels.
alpha_rejected::Float64 = 1.0: Transparency for rejected channels.
colormap_name::Nothing = nothing: Colormap name (e.g., :Set1_9, :tab20).
display_plot::Bool = true: Display plot.
linewidth_normal::Int64 = 1: Line width for normal channels.
linewidth_rejected::Int64 = 2: Line width for rejected channels.
selection_threshold::Int64 = 50: Distance threshold for channel selection.
xgrid::Bool = false: Whether to show x-axis grid
xlim::Nothing = nothing: X-axis limits as (min, max) tuple or nothing for auto-scaling
xminorgrid::Bool = false: Whether to show x-axis minor grid
ygrid::Bool = false: Whether to show y-axis grid
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple or nothing for auto-scaling
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

Figure: Interactive Makie figure with navigation buttons showing before/after comparison

Examples

julia

# Basic interactive rejection comparison
fig = plot_artifact_rejection(epochs_orig, epochs_rejected, artifacts)

# With specific channels
fig = plot_artifact_rejection(epochs_orig, epochs_rejected, artifacts,
                            channel_selection = channels([:Fp1, :Fp2, :Cz]))

# With custom axis limits
fig = plot_artifact_rejection(epochs_orig, epochs_rejected, artifacts, xlim = (-0.2, 0.8), ylim = (-100, 100))

source

EegFun.plot_artifact_repair Method

julia

plot_artifact_repair(epochs_raw::EpochData, epochs_repaired::EpochData, artifacts::EpochRejectionInfo; channel_selection::Function=channels(), kwargs...)

Interactive plot comparison between original and repaired epochs with navigation buttons.

Arguments

epochs_raw::EpochData: Original epoch data
epochs_repaired::EpochData: Repaired epoch data
artifacts::EpochRejectionInfo: Artifact detection results
channel_selection::Function: Channel predicate for selecting channels to plot (default: all layout channels)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Whether to add origin lines at x=0 and y=0
alpha_normal::Float64 = 0.2: Transparency for normal channels.
alpha_rejected::Float64 = 1.0: Transparency for rejected channels.
colormap_name::Nothing = nothing: Colormap name (e.g., :Set1_9, :tab20).
display_plot::Bool = true: Display plot.
linewidth_normal::Int64 = 1: Line width for normal channels.
linewidth_rejected::Int64 = 2: Line width for rejected channels.
selection_threshold::Int64 = 50: Distance threshold for channel selection.
xgrid::Bool = false: Whether to show x-axis grid
xlim::Nothing = nothing: X-axis limits as (min, max) tuple or nothing for auto-scaling
xminorgrid::Bool = false: Whether to show x-axis minor grid
ygrid::Bool = false: Whether to show y-axis grid
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple or nothing for auto-scaling
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

Figure: Interactive Makie figure with navigation buttons showing before/after comparison

Examples

julia

# Basic interactive repair comparison
fig = plot_artifact_repair(epochs_orig, epochs_repaired, artifacts)

# With specific channels
fig = plot_artifact_repair(epochs_orig, epochs_repaired, artifacts,
                          channel_selection = channels([:Fp1, :Fp2, :Cz]))

# With custom axis limits
fig = plot_artifact_repair(epochs_orig, epochs_repaired, artifacts, xlim = (-0.2, 0.8), ylim = (-100, 100))

source

EegFun.plot_channel_spectrum Method

julia

plot_channel_spectrum(dat::SpectrumData; kwargs...)

Plot a pre-computed power spectrum with interactive controls.

source

EegFun.plot_channel_summary! Method

julia

plot_channel_summary!(fig::Figure, ax::Axis, dat::DataFrame, col::Symbol; kwargs...)
plot_channel_summary(dat::DataFrame, col::Symbol; kwargs...)

Plot a bar chart summarizing a specific metric per channel from a DataFrame.

Assumes the DataFrame dat contains at least two columns:

:channel: Containing channel names or identifiers (will be used for x-axis labels).
col: The column specified by the col argument, containing the values to plot.

julia

plot_channel_summary!(
    fig,
    ax,
    dat,
    col;
    channel_selection,
    kwargs...
)

Arguments

fig::Figure: The Makie Figure object to plot on (mutating version only)
ax::Axis: The Makie Axis object to plot on (mutating version only)
dat::DataFrame: DataFrame containing channel summary data.
col::Symbol: The symbol representing the column in dat to plot on the y-axis.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

average_over::Nothing = nothing: Column to average over (e.g., :epoch). If specified, will compute mean ± 95% CI.
bar_alpha::Float64 = 0.7: Bar alpha.
bar_color::Symbol = :steelblue: Bar color.
bar_width::Float64 = 0.8: Bar width.
dims::Nothing = nothing: Tuple (rows, cols) for grid layout. default = _best_rect(n_columns).
display_plot::Bool = true: Display plot.
error_color::Symbol = :black: Error bar color.
error_linewidth::Int64 = 2: Error bar linewidth.
label_fontsize::Int64 = 14: Font size for axis labels.
plot_title::Nothing = nothing: Plot title.
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for title.
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
sort_values::Bool = false: Sort the bars by the values in the col column in descending order.
tick_fontsize::Int64 = 12: Font size for tick labels.
xgrid::Bool = false: Whether to show x-axis grid
xlabel::String = "Electrode": x-axis label.
xminorgrid::Bool = false: Whether to show x-axis minor grid
xtick_rotation::Float64 = 0.7853981633974483: Rotation angle for x-axis tick labels.
ygrid::Bool = false: Whether to show y-axis grid
ylabel::String = "": y-axis label
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

Mutating version: nothing (modifies the provided figure and axis in-place)
Non-mutating version: (fig::Figure, ax::Axis) - The created figure and axis objects

Examples

julia

# Non-mutating version (creates new figure)
fig, ax = plot_channel_summary(summary_df, :kurtosis)

# Mutating version (plots on existing figure)
fig = Figure()
ax = Axis(fig[1, 1])
plot_channel_summary!(fig, ax, summary_df, :kurtosis)

# Customize appearance
fig, ax = plot_channel_summary(summary_df, :kurtosis, 
    bar_color = :red, 
    title = "Custom Title",
    sort_values = true)

# With averaging and error bars
fig, ax = plot_channel_summary(summary_df, :kurtosis,
    average_over = :epoch,
    error_color = :blue,
    error_linewidth = 3)

source

EegFun.plot_channel_summary Method

julia

plot_channel_summary(dat::DataFrame, col::Symbol; kwargs...)

Plot a bar chart summarizing a specific metric per channel. Creates a new figure.

See plot_channel_summary! for full documentation of arguments and keyword arguments.

Returns

(fig::Figure, ax::Axis) - The created figure and axis objects

source

EegFun.plot_confusion_matrix Method

julia

plot_confusion_matrix(decoded::DecodedData; time_point::Union{Float64, Int, Nothing} = nothing, kwargs...)

Plot confusion matrix for decoding results.

Arguments

decoded::DecodedData: DecodedData object containing confusion matrices
time_point::Union{Float64, Int, Nothing}: Time point to plot (in seconds or index). If nothing, plots average across all time points
kwargs: Additional keyword arguments

Examples

julia

# Plot confusion matrix at a specific time point
plot_confusion_matrix(decoded, time_point=0.3)

# Plot average confusion matrix
plot_confusion_matrix(decoded)

source

EegFun.plot_correlation_heatmap! Method

julia

plot_correlation_heatmap!(fig::Figure, ax::Axis, corr_df::DataFrame; kwargs...)

Plot a heatmap of a correlation matrix stored in a DataFrame on the provided figure and axis.

This is the mutating version that plots directly on the provided fig and ax objects.

Arguments

fig::Figure: The Makie Figure object to plot on
ax::Axis: The Makie Axis object to plot on
corr_df::DataFrame: DataFrame containing the correlation matrix. First column for row labels, rest for correlation values.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "Correlation": Label for the colorbar
colorbar_plot::Bool = true: Whether to display the colorbar
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the heatmap
colorrange::Tuple{Int64, Int64} = (-1, 1): Color range for the heatmap and colorbar (should be -1 to 1 for correlations)
display_plot::Bool = true: Whether to display the plot
label_fontsize::Int64 = 14: Font size for axis labels
mask_range::Nothing = nothing: Optional tuple (min_val, max_val) to mask correlations within this range
nan_color::Symbol = :transparent: Color for NaN values
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
tick_fontsize::Int64 = 12: Font size for tick labels
xgrid::Bool = false: Whether to show x-axis grid
xlabel::String = "": Label for x-axis
xminorgrid::Bool = false: Whether to show x-axis minor grid
xtick_rotation::Float64 = 0.7853981633974483: Rotation angle for x-axis tick labels
ygrid::Bool = false: Whether to show y-axis grid
ylabel::String = "": Label for y-axis
yminorgrid::Bool = false: Whether to show y-axis minor grid
ytick_rotation::Int64 = 0: Rotation angle for y-axis tick labels

Returns

Mutating version: nothing (modifies the provided figure and axis in-place)
Non-mutating version: (fig::Figure, ax::Axis) - The created figure and axis objects

Examples

julia

# Generate sample correlation data
labels = ["Ch1", "Ch2", "Ch3", "Ch4"]
matrix = cor(rand(100, 4))
corr_df = DataFrame(matrix, labels)
insertcols!(corr_df, 1, :row => labels) # Add row label column

# Non-mutating version (creates new figure)
fig, ax = plot_correlation_heatmap(corr_df)

# Mutating version (plots on existing figure)
fig = Figure()
ax = Axis(fig[1, 1])
plot_correlation_heatmap!(fig, ax, corr_df)

# Customize appearance
fig, ax = plot_correlation_heatmap(corr_df; 
    mask_range = (-0.3, 0.3),
    colormap = :plasma,
    colorbar_label = "Custom Label")

source

EegFun.plot_correlation_heatmap Method

julia

plot_correlation_heatmap(corr_df::DataFrame; kwargs...)

Plot a heatmap of a correlation matrix. Creates a new figure.

See plot_correlation_heatmap! for full documentation of arguments and keyword arguments.

Returns

(fig::Figure, ax::Axis) - The created figure and axis objects

source

EegFun.plot_databrowser Function

Open a separate data browser window for each dataset in the vector.

source

EegFun.plot_databrowser Function

Launch the interactive data browser for a single EEG dataset.

source

EegFun.plot_databrowser Function

Load data from a .jld2 file or pattern and open the data browser.

source

EegFun.plot_databrowser Method

julia

plot_databrowser(; kwargs...)

Open a file-selector window that lets you drag-and-drop EEG files. Selected files are opened in a full interactive data browser via plot_databrowser(dat::EegData). The launcher stays open so you can load additional files.

Supported formats: .jld2, .set, .bdf, .edf, .vhdr, .fif, .xdf.

source

EegFun.plot_decoding Method

julia

plot_decoding(decoded::DecodedData; kwargs...)

Plot decoding accuracy over time.

Creates a line plot showing classification accuracy at each time point, with optional error bars and chance level reference line.

Arguments

decoded::DecodedData: DecodedData object containing decoding results
kwargs: Additional keyword arguments (see PLOT_DECODING_KWARGS)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Add origin lines at x=0 and y=chance (true/false)
chance_color::Symbol = :gray: Color for chance level line
chance_linestyle::Symbol = :dash: Line style for chance level
chance_linewidth::Int64 = 1: Line width for chance level
color::Nothing = nothing: Color for decoding curve
display_plot::Bool = true: Display the plot (true/false)
error_alpha::Float64 = 0.3: Transparency for error shading
error_color::Symbol = :blue: Color for error bars
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
interactive::Bool = true: Enable interactive features (true/false)
linestyle::Nothing = nothing: Line style
linewidth::Int64 = 2: Line width for decoding curve
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
show_error::Bool = true: Show standard error bars (true/false)
sig_alpha::Float64 = 0.5: Transparency for significance markers
sig_color::Symbol = :black: Color for significance markers
xgrid::Bool = true: Show x-axis grid (true/false)
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
ygrid::Bool = true: Show y-axis grid (true/false)
ylabel::String = "Classification Accuracy": Label for y-axis
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple. If nothing, automatically determined

Examples

julia

# Basic plot
plot_decoding(decoded)

# Custom styling
plot_decoding(decoded, color=:red, linewidth=3, show_error=false)

# With custom title
plot_decoding(decoded, title="Face vs. Object Decoding")

julia

plot_decoding(filepath::String; input_dir=pwd(), participant_selection=participants(), kwargs...)

Load decoded data and plot. Accepts either a .jld2 filepath or a pattern to discover and plot all matching files (one plot per file).

Examples

julia

plot_decoding("decoded.jld2")
plot_decoding("decoded")

source

EegFun.plot_ecg_component_features Method

julia

plot_ecg_component_features(identified_comps::Vector{Int64}, metrics_df::DataFrame)

Create a simplified visualization of ECG component detection metrics.

Arguments

identified_comps::Vector{Int64}: Vector of component indices identified as ECG artifacts
metrics_df::DataFrame: DataFrame with component metrics

Returns

fig::Figure: The Makie Figure containing the plot

source

EegFun.plot_eog_component_features Method

julia

plot_eog_component_features(identified_comps::Dict, metrics_df::DataFrame; kwargs...)

Plot z-scores of EOG correlations from the metrics DataFrame and highlight identified components.

Uses the results from identify_eye_components.

Arguments

identified_comps::Dict: Dictionary returned by identify_eye_components (containing :vEOG, :hEOG).
metrics_df::DataFrame: DataFrame returned by identify_eye_components. Expected to have columns :vEOG_zscore, :hEOG_zscore, and :Component.

Keyword Arguments

z_threshold::Float64: Z-score threshold to draw lines on the plot (default: 3.0).
display_plot::Bool: Whether to display the plot (default: true).

Returns

Named tuple (fig, axes) where axes = (ax_v, ax_h).

source

EegFun.plot_epochs Method

julia

plot_epochs(filename::String; 
           input_dir::String = pwd(),
           participant_selection::Function = participants(),
           channel_selection::Function = channels(),
           sample_selection::Function = samples(),
interval_selection::Interval = times(), 
           epoch_selection::Function = epochs(),
           include_extra::Bool = false,
           layout = :single,
           kwargs...)

Load epoch data and create plots. Accepts either a direct .jld2 filepath or a pattern string to discover and plot all matching files (one plot per file).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Whether to add origin lines at x=0 and y=0
average_channels::Bool = false: Whether to average across channels
avg_linewidth_multiplier::Float64 = 2.0: Multiplier for average line width.
axis_type::Symbol = :standard: Type of axis to draw (:standard or :origin)
color::Nothing = nothing: Color for epoch traces (can be a single color or a vector of colors, one per condition)
colormap::Nothing = nothing: Colormap for multi-condition plots
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
interactive::Bool = true: Whether to enable interactive features
layout::Symbol = :single: Layout type: :single, :grid, or :topo
linewidth::Nothing = nothing: Line width for epoch traces
plot_avg_trials::Bool = true: Whether to draw ERP average overlay
plot_title::Nothing = nothing: Plot title. If nothing, automatically determined
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
scale_x_value::Nothing = nothing: X-axis scale value/step size (e.g. 0.1 for 100 ms)
scale_y_value::Nothing = nothing: Y-axis scale value/step size (e.g. 50.0 for 50 μV)
selection_alpha::Float64 = 0.3: Alpha (transparency) for interactive selection rectangles
selection_color::Symbol = :blue: Color for interactive selection rectangles
theme_fontsize::Nothing = nothing: Font size for theme
trial_alpha::Float64 = 0.25: Alpha (transparency) for individual trial traces
xgrid::Bool = false: Whether to show x-axis grid
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Whether to show x-axis minor grid
ygrid::Bool = false: Whether to show y-axis grid
ylabel::String = "μV": Label for y-axis
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple. If nothing, automatically determined
yminorgrid::Bool = false: Whether to show y-axis minor grid
yreversed::Bool = false: Whether to reverse the y-axis
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Layout Options

layout_kwargs::@NamedTuple{} = NamedTuple(): Additional parameters to configure grid or topographical layouts (e.g., grid_dims, topo_plot_width, grid_rowgap)

Legend Options

legend::Bool = true: Whether to show the legend
legend_channel::Vector{Any} = Any[]: If plotting multiple plots, within channel to put the legend on.
legend_label::String = "": Title for the legend
legend_nbanks::Nothing = nothing: Number of columns for the legend. If nothing, automatically determined.
legend_position::Symbol = :lt: Position of the legend for axislegend() (symbol like :lt, :rt, :lb, :rb, or tuple like (:left, :top), or (0.5, 0.5))

Examples

julia

plot_epochs("epochs_raw.jld2")
plot_epochs("epochs_raw")
plot_epochs("epochs_raw", participant_selection = participants(1))

source

EegFun.plot_erp! Method

julia

plot_erp!(fig::Figure, ax::Axis, dat::ErpData; kwargs...)

Plot ERP data on an existing axis, mutating the figure and axis.

Arguments

fig::Figure: The figure to plot on
ax::Axis: The axis to plot on
dat::ErpData: The ERP data to plot
kwargs...: Additional plotting arguments (see PLOT_ERP_KWARGS)

Returns

ax::Axis: The axis that was plotted on

source

EegFun.plot_erp Method

julia

plot_erp(filepath::String; 
         input_dir::String = pwd(),
         participant_selection::Function = participants(),
         layout::Union{Symbol, PlotLayout} = :single,
         condition_selection::Function = conditions(),
         channel_selection::Function = channels(),
         channel_plot_order::Union{Nothing, Vector{Symbol}} = nothing,
         sample_selection::Function = samples(),
         interval_selection::Interval = times(),
         baseline_interval::Interval = nothing,
         kwargs...)

Load ERP data and create plots. Accepts either a direct .jld2 filepath or a filename pattern to discover and plot all matching files.

Arguments

filepath::String: Either a .jld2 file path, or a pattern string (e.g. "erps_final") to match against files in input_dir
input_dir::String: Directory to search for pattern-matched files (default: pwd())
participant_selection::Function: Participant filter for pattern mode (default: participants())
layout: Layout specification (see main plot_erp documentation)
channel_selection::Function: Function that returns boolean vector for channel filtering
sample_selection::Function: Function that returns boolean vector for sample filtering
kwargs: Additional keyword arguments

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Add origin lines at x=0 and y=0 (true/false)
average_channels::Bool = false: Average across channels (true/false)
axis_type::Symbol = :standard: Type of axis to draw (:standard or :origin)
color::Nothing = nothing: Color for ERPs (single color or a vector of colors, one per dataset)
colormap::Nothing = nothing: Colormap for multi-channel plots
display_plot::Bool = true: Display the plot (true/false)
error_bars::Symbol = :none: Error bars type to plot: :none, :sem, :within_sem, :ci95
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
highlight_regions::Nothing = nothing: Highlight regions as a NamedTuple or Vector of NamedTuples. Each region: (x1, x2, y1=-Inf, y2=Inf, color=:gray, alpha=0.3)
interactive::Bool = true: Enable interactive features (true/false)
linestyle::Nothing = nothing: Line style for ERPs (single style or a vector of styles, one per dataset)
linewidth::Nothing = nothing: Line width for ERPs
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
scale_x_value::Nothing = nothing: X-axis scale value/step size (e.g. 0.1 for 100 ms)
scale_y_value::Nothing = nothing: Y-axis scale value/step size (e.g. 5.0 for 5 μV)
selection_alpha::Float64 = 0.3: Alpha (transparency) for interactive selection rectangles
selection_color::Symbol = :blue: Color for interactive selection rectangles
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for x-axis display (😒 or :ms). Only affects axis labels and tick formatting — all intervals remain in seconds.
window_title::String = "": Title for the OS plot window. If empty, it's generated automatically.
xgrid::Bool = false: Show x-axis grid (true/false)
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Show x-axis minor grid (true/false)
xticks::Nothing = nothing: X-axis tick positions (e.g., -0.1:0.1:0.8 or [0, 0.2, 0.4]). If nothing, automatically determined
ygrid::Bool = false: Show y-axis grid (true/false)
ylabel::String = "μV": Label for y-axis
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple. If nothing, automatically determined
yminorgrid::Bool = false: Show y-axis minor grid (true/false)
yreversed::Bool = false: Whether to reverse the y-axis
yticks::Nothing = nothing: Y-axis tick positions (e.g., -4:2:4 or [-2, 0, 2]). If nothing, automatically determined
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Layout Options

layout_kwargs::@NamedTuple{} = NamedTuple(): Additional parameters to configure grid or topographical layouts (e.g., grid_dims, topo_plot_width, grid_rowgap)

Legend Options

legend::Bool = true: Show the legend (true/false)
legend_channel::Vector{Any} = Any[]: Which channel to put the legend on.
legend_label::String = "": Title for the legend
legend_nbanks::Nothing = nothing: Number of legend columns.
legend_position::Symbol = :lt: Legend position (:lt, :rt, :lb, :rb, or tuple like (:left, :top), or (0.5, 0.5))

Examples

julia

# Load and plot from file
plot_erp("grand_average_erps_final.jld2")

# Plot all files matching pattern in current directory
plot_erp("erps_final")

# Plot specific participant
plot_erp("erps_final", participant_selection = participants(1))

# With channel selection
plot_erp("erps_final", channel_selection = channels([:PO7, :PO8]), layout = :grid)

source

EegFun.plot_erp_errorbar! Method

julia

plot_erp_errorbar!(fig::Figure, ax::Axis, datasets::Vector{ErpData}; kwargs...)

Plot grand-averaged ERP data with error ribbons on an existing axis, mutating the figure and axis.

source

EegFun.plot_erp_errorbar! Method

julia

plot_erp_errorbar!(fig::Figure, ax::Axis, datasets::Vector{ErpData}; kwargs...)

Plot ERP errorbars for multiple datasets into an existing figure and axis.

source

EegFun.plot_erp_errorbar Method

julia

plot_erp_errorbar(dataset::ErpData; kwargs...)

Plot ERP errorbars for a single dataset.

source

EegFun.plot_erp_errorbar Method

julia

plot_erp_errorbar(datasets::Vector{ErpData}; kwargs...)

Plot ERP errorbars for multiple datasets.

source

EegFun.plot_erp_errorbar Method

julia

plot_erp_errorbar(datasets::Vector{ErpData}; kwargs...)

Plot ERP errorbars for multiple datasets.

source

EegFun.plot_erp_filter_gui Method

julia

plot_erp_filter_gui(filepath::String; kwargs...)

Launch a GUI for interactively filtering ERP data from a file.

source

EegFun.plot_erp_filter_gui Method

julia

plot_erp_filter_gui(erp::Union{ErpData,ContinuousData}; channel::Union{Symbol,Nothing} = nothing)

Launch a GUI for interactively filtering a single dataset.

source

EegFun.plot_erp_filter_gui Method

julia

plot_erp_filter_gui(erps::Vector{<:Union{ErpData,ContinuousData}}; channel::Union{Symbol,Nothing} = nothing)

Launch a GUI for interactively filtering multiple datasets.

source

EegFun.plot_erp_filter_gui Method

julia

plot_erp_filter_gui(; kwargs...)

Launch a GUI for interactively filtering ERP data.

source

EegFun.plot_erp_image Method

julia

plot_erp_image(dat::EpochData; 
               layout::Union{Symbol, PlotLayout} = :single,
               channel_selection::Function = channels(),
               channel_plot_order::Union{Nothing, Vector{Symbol}} = nothing,
               sample_selection::Function = samples(),
interval_selection::Interval = times(),
               kwargs...)

Plot ERP image for specified channels and samples with flexible layout options.

Arguments

dat::EpochData: Epoch data structure
layout: Layout specification:
- :single (default): Single ERP image plot
- :grid: Auto-calculated grid layout for multiple channels
- :topo: Topographic layout based on channel positions
- PlotLayout: Custom layout object
- Vector{Int}: Custom grid dimensions [rows, cols]
channel_selection::Function: Function that returns boolean vector for channel filtering (default: channels() - all channels)
sample_selection::Function: Function that returns boolean vector for sample filtering (default: samples() - all samples)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Add origin lines at x=0 and y=0 (true/false)
boxcar_average::Int64 = 1: Boxcar average window size for smoothing the ERP image (1 = no smoothing)
colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "μV": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the image
colorrange::Nothing = nothing: Color range for the image. If nothing, automatically determined
display_plot::Bool = true: Display the plot (true/false)
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
interactive::Bool = true: Enable interactive features (true/false)
interpolate::Bool = false: Whether to interpolate the heatmap pixels for smoother appearance
plot_erp::Bool = true: Whether to plot ERP average overlay
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
selection_alpha::Float64 = 0.3: Alpha (transparency) for interactive selection rectangles
selection_color::Symbol = :blue: Color for interactive selection rectangles
xgrid::Bool = false: Show x-axis grid (true/false)
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Show x-axis minor grid (true/false)
ygrid::Bool = false: Show y-axis grid (true/false)
ylabel::String = "Epoch": Label for y-axis
ylim::Nothing = nothing: Y-axis limits for ERP waveform as (min, max) tuple. If nothing, automatically determined
yminorgrid::Bool = false: Show y-axis minor grid (true/false)
yreversed::Bool = false: Whether to reverse the y-axis
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Layout Options

layout_kwargs::@NamedTuple{} = NamedTuple(): Additional parameters to configure grid or topographical layouts (e.g., grid_dims, topo_plot_width, grid_rowgap)

Returns

Figure: The Makie Figure object
Vector{Axis}: Vector of axes for the ERP images

Examples

julia

# Plot all channels and samples
plot_erp_image(dat)

# Plot specific channels
plot_erp_image(dat, channel_selection = channels([:Fp1, :Fp2]))

# Exclude reference channels
plot_erp_image(dat, channel_selection = channels_not([:M1, :M2]))

# Plot frontal channels only
plot_erp_image(dat, channel_selection = channels(1:10))

# Custom predicates
plot_erp_image(dat, 
    channel_selection = x -> startswith.(string.(x), "F"),
    sample_selection = x -> x .> 0.0  # Only positive time points
)

source

EegFun.plot_erp_measurement_gui Method

julia

plot_erp_measurement_gui(erp::Union{ErpData,EpochData}; kwargs...)

Launch a GUI for interacting with ERP measurements for a single dataset.

source

EegFun.plot_erp_measurement_gui Method

julia

plot_erp_measurement_gui(filepath::String; kwargs...)

Launch a GUI for interacting with ERP measurements from a file.

source

EegFun.plot_erp_measurement_gui Method

julia

plot_erp_measurement_gui(erps::Vector{<:Union{ErpData,EpochData}}; kwargs...)

Launch a GUI for interacting with ERP measurements for multiple datasets.

source

EegFun.plot_erp_measurements Method

julia

plot_erp_measurements(erp_data, analysis_type;
                      analysis_interval, baseline_interval,
                      layout, channel_selection, condition_selection, kwargs...)

Plot ERP data with measurement overlays computed inline.

Computes a single measurement type across all selected channels and conditions, then overlays the results on the ERP waveforms. Combines measurement computation and visualization in one call.

Arguments

erp_data::Union{String, ErpData, Vector{ErpData}}: ERP data (filepath or data object)
analysis_type::String: Measurement type (e.g. "mean_amplitude", "max_peak_latency")

Keyword Arguments

analysis_interval::Tuple{Real,Real}: Time interval for measurement (default: full range)
baseline_interval::Union{Tuple{Real,Real},Nothing}: Baseline interval for correction (default: nothing)
layout::Union{Symbol, PlotLayout}: Plot layout — :single, :grid, or :topo (default: :single)
channel_selection::Function: Channel selection predicate (default: all channels)
condition_selection::Function: Condition selection predicate (default: all conditions)
average_channels::Bool: Evaluate measurement across a spatially pooled ROI waveform instead of discrete individual channels (default: false).
kwargs...: Additional arguments passed to plot_erp and erp_measurements

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

fractional_area_fraction::Float64 = 0.5: Fraction for fractional area latency (0.0-1.0). Finds latency where this fraction of area is to the left.
fractional_peak_direction::Symbol = :onset: Direction for fractional peak latency: :onset (before peak) or :offset (after peak)
fractional_peak_fraction::Float64 = 0.5: Fraction for fractional peak latency (0.0-1.0). Finds latency where amplitude is this fraction of peak.
local_interval::Int64 = 3: Number of samples on each side of peak (total interval = 2*local_interval + 1). Peak must be larger than neighbors and local averages within this window.

Overlay Types

Peak amplitude → vertical line at peak time, amplitude label
Peak latency → vertical line at latency, time label
Peak-to-peak → vertical lines at both peaks
Mean amplitude → shaded analysis interval + horizontal mean line
Area/integral → shaded analysis interval
Fractional latency → vertical line at fractional latency point

Examples

julia

dat = EegFun.read_data("erps_final.jld2")

# Mean amplitude in 300-500ms interval
plot_erp_measurements(dat, "mean_amplitude",
    analysis_interval = (0.3, 0.5),
    baseline_interval = (-0.2, 0.0))

# Peak latency
plot_erp_measurements(dat, "max_peak_latency",
    analysis_interval = (0.0, 0.8),
    baseline_interval = (-0.2, 0.0),
    channel_selection = channels([:Cz, :Pz]))

# Load from file path
plot_erp_measurements("erps_final.jld2", "max_peak_amplitude",
    analysis_interval = (0.1, 0.3))

source

EegFun.plot_erp_stats Method

julia

plot_erp_stats(result::StatsResult;
                layout::Union{Symbol, PlotLayout} = :single,
                channel_selection::Function = channels(),
                channel_plot_order::Union{Nothing, Vector{Symbol}} = nothing,
                plot_erp::Bool = true,
                plot_difference::Bool = false,
                plot_tvalues::Bool = false,
                plot_significance::Bool = false,
                plot_critical_t::Bool = false,
                plot_se::Bool = false,
                colors::Vector = [:blue, :red, :black, :purple],
                difference_offset::Real = 0.0,
                significance_position::Union{Symbol, Real} = :auto,
                significance_color = (:gray, 0.6),
                kwargs...)

Plot ERP waveforms and statistical results for analytic or permutation tests with flexible layout support.

Works with both AnalyticResult (from analytic_test) and PermutationResult (from permutation_test).

Arguments

result::StatsResult: Results from analytic_test or permutation_test
layout: Layout specification:
- :single (default): Single plot with selected channels overlaid
- :grid: Grid layout with one subplot per selected channel
- :topo: Topographic layout based on channel positions
- PlotLayout: Custom layout object
channel_selection::Function: Predicate to select channels (default: channels() - all channels)
channel_plot_order::Union{Nothing, Vector{Symbol}}: Override the plotting order of selected channels (default: nothing — data order). When provided, channels are plotted in the specified order. Only channels present in both channel_plot_order and the selection are plotted
plot_erp::Bool: Whether to plot ERP waveforms (condition averages) (default: true)
plot_difference::Bool: Whether to plot difference wave (A-B) (default: false)
plot_tvalues::Bool: Whether to plot t-statistics (default: false)
plot_significance::Bool: Whether to highlight significant time points (default: false)
plot_critical_t::Bool: Whether to plot critical t-values (default: false). Only relevant when plot_tvalues=true
difference_offset::Real: Vertical offset for difference wave (default: 0.0). Set to non-zero to shift for visibility
plot_se::Bool: Whether to plot ±1 SEM bands around waveforms (default: false). Bands are drawn around condition ERPs and difference wave
significance_position::Union{Symbol, Real}: Position for significance bars (default: :auto). Options:
- :auto - Automatically place at y=0 if visible, otherwise at bottom (default)
- :zero - Always place at y=0
- :bottom - Always place at bottom of plot/spine
- Real - Custom y-position (e.g., -5.0 to place at -5 μV)
significance_color: Color for significance bars (default: (:gray, 0.6)). Can be any Makie color specification

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_xy_origin::Bool = true: Add origin lines at x=0 and y=0 (true/false)
average_channels::Bool = false: Average across channels (true/false)
axis_type::Symbol = :standard: Type of axis to draw (:standard or :origin)
color::Nothing = nothing: Color for ERPs (single color or a vector of colors, one per dataset)
colormap::Nothing = nothing: Colormap for multi-channel plots
display_plot::Bool = true: Display the plot (true/false)
error_bars::Symbol = :none: Error bars type to plot: :none, :sem, :within_sem, :ci95
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
highlight_regions::Nothing = nothing: Highlight regions as a NamedTuple or Vector of NamedTuples. Each region: (x1, x2, y1=-Inf, y2=Inf, color=:gray, alpha=0.3)
interactive::Bool = true: Enable interactive features (true/false)
linestyle::Nothing = nothing: Line style for ERPs (single style or a vector of styles, one per dataset)
linewidth::Nothing = nothing: Line width for ERPs
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
scale_x_value::Nothing = nothing: X-axis scale value/step size (e.g. 0.1 for 100 ms)
scale_y_value::Nothing = nothing: Y-axis scale value/step size (e.g. 5.0 for 5 μV)
selection_alpha::Float64 = 0.3: Alpha (transparency) for interactive selection rectangles
selection_color::Symbol = :blue: Color for interactive selection rectangles
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for x-axis display (😒 or :ms). Only affects axis labels and tick formatting — all intervals remain in seconds.
window_title::String = "": Title for the OS plot window. If empty, it's generated automatically.
xgrid::Bool = false: Show x-axis grid (true/false)
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Show x-axis minor grid (true/false)
xticks::Nothing = nothing: X-axis tick positions (e.g., -0.1:0.1:0.8 or [0, 0.2, 0.4]). If nothing, automatically determined
ygrid::Bool = false: Show y-axis grid (true/false)
ylabel::String = "μV": Label for y-axis
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple. If nothing, automatically determined
yminorgrid::Bool = false: Show y-axis minor grid (true/false)
yreversed::Bool = false: Whether to reverse the y-axis
yticks::Nothing = nothing: Y-axis tick positions (e.g., -4:2:4 or [-2, 0, 2]). If nothing, automatically determined
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Layout Options

layout_kwargs::@NamedTuple{} = NamedTuple(): Additional parameters to configure grid or topographical layouts (e.g., grid_dims, topo_plot_width, grid_rowgap)

Legend Options

legend::Bool = true: Show the legend (true/false)
legend_channel::Vector{Any} = Any[]: Which channel to put the legend on.
legend_label::String = "": Title for the legend
legend_nbanks::Nothing = nothing: Number of legend columns.
legend_position::Symbol = :lt: Legend position (:lt, :rt, :lb, :rb, or tuple like (:left, :top), or (0.5, 0.5))

Returns

Named tuple (fig, axes)

Examples

julia

# With analytic test results - single channel
result = analytic_test(prepared, correction_method=:no)
plot_erp_stats(result, channel_selection=channels(:PO7), 
               plot_erp=true, plot_difference=true, plot_significance=true)

# Grid layout with multiple channels
plot_erp_stats(result, channel_selection=channels([:PO7, :PO8, :Oz, :Pz]),
               layout=:grid, plot_significance=true)

# With permutation test results
result_perm = permutation_test(prepared, n_permutations=1000)
plot_erp_stats(result_perm, channel_selection=channels(:PO7),
               plot_erp=true, plot_significance=true, plot_critical_t=true)

source

EegFun.plot_filter_response Method

julia

plot_filter_response(filter_info::FilterInfo; kwargs...)

Plot the frequency response and impulse response of a digital filter.

Arguments

filter_info::FilterInfo: Filter information struct
kwargs...: Additional keyword arguments

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

color::Nothing = nothing: Color for response curves
display_plot::Bool = true: Whether to display the plot
label_fontsize::Int64 = 22: Font size for axis labels
linewidth::Int64 = 4: Line width for response curves
n_points::Int64 = 2000: Number of frequency points for response calculation
plot_title::String = "Filter Frequency Response": Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 24: Font size for title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
reference_color::Symbol = :gray: Color for reference lines
reference_lines::Vector{Int64} = [-3, -6]: Reference lines in dB to display
reference_linestyle::Symbol = :dash: Line style for reference lines
tick_fontsize::Int64 = 20: Font size for tick labels
xgrid::Bool = false: Whether to show x-axis grid
xlabel::String = "Frequency (Hz)": X-axis label
xlim::Nothing = nothing: X-axis limits in Hz as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Whether to show x-axis minor grid
xscale::Makie.Symlog10{Makie.ReversibleScale{Makie.var"#forward#1209"{Int64, Float64, Float64}, Makie.var"#inverse#1210"{Int64, Float64, Float64}, IntervalSets.OpenInterval{Float32}}} = Symlog10(-10.0, 10.0; linscale = 1.0): X-axis scale type
ygrid::Bool = false: Whether to show y-axis grid
ylabel::String = "Magnitude (dB)": Y-axis label
ylim::Tuple{Int64, Int64} = (-100, 5): Y-axis limits in dB as (min, max) tuple
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

fig: Makie Figure object
ax: Tuple of Makie Axis objects (dB, impulse)

source

EegFun.plot_gfp Method

julia

plot_gfp(dat::ErpData;
         channel_selection::Function = channels(),
         normalize::Bool = true,
         kwargs...)

Plot Global Field Power (GFP) for ERP data.

Arguments

dat::ErpData: ERP data structure
channel_selection::Function: Channel predicate for selecting channels (default: all channels)
normalize::Bool: If true, normalize GFP to 0-100% (default: true)
kwargs: Additional keyword arguments

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

add_x_origin::Bool = true: Whether to add vertical line at x=0
color::Nothing = nothing: Color for traces
display_plot::Bool = true: Whether to display the plot
linestyle::Nothing = nothing: Line style for traces
linewidth::Int64 = 2: Line width for GFP/dissimilarity traces
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
show_dissimilarity::Bool = false: Whether to include Global Dissimilarity panel
show_erp_traces::Bool = false: Whether to show individual ERP channel traces in top panel
xgrid::Bool = false: Whether to show x-axis grid
xlabel::String = "Time (s)": Label for x-axis
xlim::Nothing = nothing: X-axis limits as (min, max) tuple. If nothing, automatically determined
xminorgrid::Bool = false: Whether to show x-axis minor grid
ygrid::Bool = false: Whether to show y-axis grid
ylabel::Nothing = nothing: Label for y-axis (auto-determined based on normalize flag)
ylim::Nothing = nothing: Y-axis limits as (min, max) tuple. If nothing, automatically determined
yminorgrid::Bool = false: Whether to show y-axis minor grid

Examples

julia

using EegFun, JLD2

# Load and plot GFP
erp_data = load("participant_1_erps.jld2", "erps")[1]
plot_gfp(erp_data)

# Plot with individual channel traces
plot_gfp(erp_data, show_erp_traces = true)

# Plot with Global Dissimilarity
plot_gfp(erp_data, show_dissimilarity = true)

# Plot all three panels
plot_gfp(erp_data, show_erp_traces = true, show_dissimilarity = true)

# Custom styling
plot_gfp(erp_data, 
         color = :blue,
         linewidth = 3,
         xlim = (-0.2, 0.8))

Plot Layout

By default, shows only the GFP trace. With show_erp_traces=true, adds a top panel with all channel traces. With show_dissimilarity=true, adds a bottom panel with Global Dissimilarity.

julia

plot_gfp(filepath::String; input_dir=pwd(), participant_selection=participants(), kwargs...)

Load ERP data and plot GFP. Accepts either a .jld2 filepath or a pattern to discover and plot all matching files (one plot per file).

Examples

julia

plot_gfp("erps_final.jld2")
plot_gfp("erps_final")

source

EegFun.plot_gui Method

julia

plot_gui()

Interactive GUI for quick data plotting and visualization.

GUI Structure

Column 1: File & Plot Selection

Directory and file browser
Plot type dropdown with hierarchical submenus:
- Common plots: Data Browser, Epochs, ERP, ERP Image, Topography
- Time-Frequency >: Time-Frequency, Power Spectrum
- ICA > : Components, Activation
- ERP Analysis > : ERP GUI
- Diagnostic Plots >: Artifact Detection, Triggers, Channel Summary, Joint Probability, Correlation Heatmap, Global Field Power, Layout View, Filter Response

Column 2: Data Selection & Layout

Participant, Condition, Epoch filters (integers, space/comma-separated)
Layout type: Single, Single Avg, Grid, Topo
Channel selection with multi-select support

Column 3: Axis Settings

X, Y, Z axis limits (validated numeric input with range checking)
Baseline correction window and type
Display options (invert Y-axis)

Supported Plot Types

See EegFun.jl documentation for complete plot type details and data requirements.

Examples

julia

# Launch GUI
EegFun.plot_gui()

# Navigate to data directory, select file and plot type
# Configure channels and axis limits as needed
# Click "Plot" to generate visualization

source

EegFun.plot_ica_component_activation Method

julia

plot_ica_component_activation(dat::ContinuousData, ica::InfoIca; ...)

Interactive Viewer for ICA Component Activation

Arguments

dat::ContinuousData: Continuous EEG data object.
ica::InfoIca: ICA results object.

Keyword Arguments

artifacts::Union{Nothing,ArtifactComponents}=nothing: Optional artifact detection results. When provided, adds category checkboxes for filtering components.
component_selection::Function=components(:all): Predicate to select which components to display.
n_visible_components::Int=10: Number of components visible at once (auto-adjusted for selected components).
window_size::Int=2000: Initial time window size in samples.
topo_kwargs::Dict=Dict(): Keyword arguments passed down for topography plots (see _plot_topo_on_axis!).
head_kwargs::Dict=Dict(): Keyword arguments passed down for head outlines.
point_kwargs::Dict=Dict(): Keyword arguments passed down for channel markers.
label_kwargs::Dict=Dict(): Keyword arguments passed down for channel labels.

Returns

fig::Figure: The Makie Figure object containing the interactive plot.

source

EegFun.plot_ica_component_spectrum Method

julia

plot_ica_component_spectrum(data::ContinuousData, ica::InfoIca, components::Union{Int,Vector{Int}})

Plot the power spectrum of specified ICA components.

source

EegFun.plot_joint_probability! Method

julia

plot_joint_probability!(fig::Figure, ax::Axis, dat::DataFrame; kwargs...)

Plot a bar chart of joint probability values per channel on the provided figure and axis.

This is the mutating version that plots directly on the provided fig and ax objects.

Assumes the DataFrame dat contains at least two columns:

:channel: Containing channel names or identifiers (will be used for x-axis labels).
:jp: Containing the joint probability values to plot.

Arguments

fig::Figure: The Makie Figure object to plot on
ax::Axis: The Makie Axis object to plot on
dat::DataFrame: DataFrame with channel and joint probability data.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

bar_alpha::Float64 = 0.7: Transparency of bars
bar_color::Symbol = :steelblue: Color of the bars
bar_width::Float64 = 0.8: Width of bars
display_plot::Bool = true: Whether to display the plot
label_fontsize::Int64 = 14: Font size for axis labels
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
sort_values::Bool = false: If true, sort the bars by joint probability values in descending order
tick_fontsize::Int64 = 12: Font size for tick labels
xgrid::Bool = true: Whether to show x-axis grid
xlabel::String = "Electrode": Label for x-axis
xminorgrid::Bool = false: Whether to show x-axis minor grid
xtick_rotation::Float64 = 0.7853981633974483: Rotation angle for x-axis tick labels
ygrid::Bool = true: Whether to show y-axis grid
ylabel::String = "Joint Probability": Label for y-axis
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

nothing (modifies the provided figure and axis in-place)

Example

julia

# Basic usage
fig = Figure()
ax = Axis(fig[1, 1])
plot_joint_probability!(fig, ax, jp_df)

# Custom styling
plot_joint_probability!(fig, ax, jp_df;
    title = "Custom Joint Probability",
    bar_color = :orange,
    sort_values = true)

source

EegFun.plot_joint_probability Method

julia

plot_joint_probability(dat::DataFrame; kwargs...)

Plot a bar chart of joint probability values per channel.

Assumes the DataFrame dat contains at least two columns:

:channel: Containing channel names or identifiers (will be used for x-axis labels).
:jp: Containing the joint probability values to plot.

Arguments

dat::DataFrame: DataFrame with channel and joint probability data.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

bar_alpha::Float64 = 0.7: Transparency of bars
bar_color::Symbol = :steelblue: Color of the bars
bar_width::Float64 = 0.8: Width of bars
display_plot::Bool = true: Whether to display the plot
label_fontsize::Int64 = 14: Font size for axis labels
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
sort_values::Bool = false: If true, sort the bars by joint probability values in descending order
tick_fontsize::Int64 = 12: Font size for tick labels
xgrid::Bool = true: Whether to show x-axis grid
xlabel::String = "Electrode": Label for x-axis
xminorgrid::Bool = false: Whether to show x-axis minor grid
xtick_rotation::Float64 = 0.7853981633974483: Rotation angle for x-axis tick labels
ygrid::Bool = true: Whether to show y-axis grid
ylabel::String = "Joint Probability": Label for y-axis
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

Figure: The Makie Figure object.
Axis: The Makie Axis object for the bar plot.

Example

julia

# Basic usage
fig, ax = plot_joint_probability(jp_df)

# Custom styling
fig, ax = plot_joint_probability(jp_df;
    title = "Joint Probability Analysis",
    bar_color = :red,
    sort_values = true,
    grid_visible = false)

source

EegFun.plot_layout! Method

julia

plot_layout!(args...; kwargs...)

Plot a 2D sensor layout in an existing Makie axis.

source

EegFun.plot_layout Method

julia

plot_layout(args...; kwargs...)
plot_layout!(args...; kwargs...)

Aliases for plot_layout_2d and plot_layout_2d! to maintain backwards compatibility and consistency with plot_topography (which is 2D by default).

source

EegFun.plot_layout_2d! Method

julia

plot_layout_2d!(fig::Figure, ax::Axis, layout::Layout; neighbours::Bool=false, correlation_matrix::Union{DataFrame, Nothing}=nothing, kwargs...)

Plot a 2D EEG electrode layout with customizable head shape, electrode points, and labels.

Arguments

fig: The figure to plot on
ax: The axis to plot on
layout: Layout containing electrode positions with columns x2, y2, and label
neighbours: Boolean to show interactive neighbour connections (default: false). Ignored if correlation_matrix is provided.
correlation_matrix: Optional DataFrame from correlation_matrix() to show correlation values on hover (default: nothing). When provided, neighbours is ignored.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Int64 = 1: Radius of the head shape (normalized units).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

label_align::Tuple{Symbol, Symbol} = (:left, :bottom): Text alignment for electrode labels (e.g., (:center, :center)).
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
label_zoffset::Int64 = 0: Z-axis offset for electrode labels (3D only).

Returns

nothing (modifies the provided figure and axis in-place)

Example

julia

layout = Layout("biosemi64.csv")
polar_to_cartesian_xy!(layout)
fig = Figure()
ax = Axis(fig[1, 1])
plot_layout_2d!(fig, ax, layout)

# With correlation matrix
cm = correlation_matrix(dat)
plot_layout_2d!(fig, ax, layout, correlation_matrix=cm)

source

EegFun.plot_layout_2d Method

julia

plot_layout_2d(layout::Layout; neighbours::Bool=false, correlation_matrix::Union{DataFrame, Nothing}=nothing, display_plot::Bool=true, kwargs...)

Create a new figure and plot a 2D EEG electrode layout.

Arguments

layout: Layout containing electrode positions
neighbours: Boolean to show interactive neighbour connections (default: false). Ignored if correlation_matrix is provided.
correlation_matrix: Optional DataFrame from correlation_matrix() to show correlation values on hover (default: nothing). When provided, neighbours is ignored.
display_plot: Boolean to display the plot (default: true)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Int64 = 1: Radius of the head shape (normalized units).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

label_align::Tuple{Symbol, Symbol} = (:left, :bottom): Text alignment for electrode labels (e.g., (:center, :center)).
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
label_zoffset::Int64 = 0: Z-axis offset for electrode labels (3D only).

Returns

The figure and axis objects

Example

julia

layout = read_layout("./layouts/biosemi64.csv")
polar_to_cartesian_xy!(layout)
plot_layout_2d(layout)
# With neighbour interactivity
plot_layout_2d(layout, neighbours=true)
# With correlation matrix
cm = correlation_matrix(dat)
plot_layout_2d(layout, correlation_matrix=cm)

source

EegFun.plot_layout_3d! Method

julia

plot_layout_3d!(fig::Figure, ax::Axis3, layout::Layout; neighbours::Bool=false, kwargs...)

Plot a 3D EEG electrode layout with customizable head shape, electrode points, and labels.

Arguments

fig: The figure to plot on
ax: The axis to plot on
layout: Layout containing electrode positions with columns x3, y3, z3, and label
neighbours: Boolean to show interactive neighbour connections (default: false)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Int64 = 1: Radius of the head shape (normalized units).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

label_align::Tuple{Symbol, Symbol} = (:left, :bottom): Text alignment for electrode labels (e.g., (:center, :center)).
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
label_zoffset::Int64 = 0: Z-axis offset for electrode labels (3D only).

Returns

nothing (modifies the provided figure and axis in-place)

Example

julia

layout = Layout("biosemi64.csv")
polar_to_cartesian_xyz!(layout)
fig = Figure()
ax = Axis3(fig[1, 1])
plot_layout_3d!(fig, ax, layout)

source

EegFun.plot_layout_3d Method

julia

plot_layout_3d(layout::Layout; neighbours::Bool=false, display_plot::Bool=true, kwargs...)

Create a new figure and plot a 3D EEG electrode layout.

Arguments

layout: Layout containing electrode positions
neighbours: Boolean to show interactive neighbour connections (default: false)
display_plot: Boolean to display the plot (default: true)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Int64 = 1: Radius of the head shape (normalized units).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

label_align::Tuple{Symbol, Symbol} = (:left, :bottom): Text alignment for electrode labels (e.g., (:center, :center)).
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
label_zoffset::Int64 = 0: Z-axis offset for electrode labels (3D only).

Returns

The figure and axis objects

Example

julia

layout = read_layout("./layouts/biosemi64.csv")
polar_to_cartesian_xyz!(layout)
plot_layout_3d(layout)
# With neighbour interactivity
plot_layout_3d(layout, neighbours=true)

source

EegFun.plot_line_noise_components Method

julia

plot_line_noise_components(line_noise_comps::Vector{Int}, metrics_df::DataFrame; kwargs...)

Plot spectral metrics used for line noise component identification.

Arguments

line_noise_comps::Vector{Int}: Vector of component indices identified as line noise.
metrics_df::DataFrame: DataFrame containing line noise metrics. Expected to have columns :Component, :power_ratio_zscore, and :harmonic_ratio.

Keyword Arguments

z_threshold::Float64: Z-score threshold for the reference line (default: 3.0).
min_harmonic_power::Real: Minimum harmonic power reference line (default: 0.5).
display_plot::Bool: Whether to display the plot (default: true).

Returns

Named tuple (fig, axes) where axes = (ax1, ax2).

source

EegFun.plot_model_correlations Method

julia

plot_model_correlations(rsa_data::RsaData; kwargs...)

Plot model correlations over time.

Arguments

rsa_data::RsaData: RSA results with model comparisons
kwargs: Additional keyword arguments

Examples

julia

# Plot correlations with models
plot_model_correlations(rsa_result)

# Custom styling
plot_model_correlations(rsa_result, colors=[:red, :blue], title="Model Comparison")

source

EegFun.plot_rdm_heatmap Method

julia

plot_rdm_heatmap(rsa_data::RsaData; time_point::Union{Float64, Int, Nothing} = nothing, kwargs...)

Plot Representational Dissimilarity Matrix (RDM) as a heatmap.

Shows a matrix visualization of pairwise dissimilarities between conditions at a specific time point or averaged across time.

Arguments

rsa_data::RsaData: RSA results
time_point::Union{Float64, Int, Nothing}: Time point to plot (Float64 = time in seconds, Int = index, nothing = average across time)
kwargs: Additional keyword arguments

Examples

julia

# Plot RDM at a specific time point
plot_rdm_heatmap(rsa_result, time_point=0.3)

# Plot average RDM across all time points
plot_rdm_heatmap(rsa_result)

# Plot RDM at time index 50
plot_rdm_heatmap(rsa_result, time_point=50)

source

EegFun.plot_rdm_timecourse Method

julia

plot_rdm_timecourse(
    rsa_data::RsaData;
    condition_pairs::Union{Vector{Tuple{Int,Int}}, Symbol, Nothing} = :all,
    kwargs...
)

Plot dissimilarity timecourse for condition pairs.

Shows how dissimilarity between conditions evolves over time as lines. This helps visualize when conditions become distinguishable.

Arguments

rsa_data::RsaData: RSA results
condition_pairs: Which condition pairs to plot
- :all - All pairwise comparisons (default)
- :upper - Upper triangle only (same as :all, no duplicates)
- Vector{Tuple{Int,Int}} - Specific pairs, e.g., [(1,2), (1,3)]
kwargs: Additional keyword arguments

Examples

julia

# Plot all condition pairs
plot_rdm_timecourse(rsa_result)

# Plot only specific pairs
plot_rdm_timecourse(rsa_result, condition_pairs=[(1,2), (1,3)])

# Custom styling
plot_rdm_timecourse(rsa_result, title="Dissimilarity Over Time")

source

EegFun.plot_rsa Method

julia

plot_rsa(rsa_data::RsaData; kwargs...)

Main plotting function for RSA results.

If model correlations are available, plots them. Otherwise, plots RDM heatmap at average time.

Arguments

rsa_data::RsaData: RSA results
kwargs: Additional keyword arguments (passed to plot_model_correlations or plot_rdm_heatmap)

Examples

julia

# Plot RSA results (automatically chooses best visualization)
plot_rsa(rsa_result)

# Force RDM heatmap plot
plot_rsa(rsa_result, plot_type=:rdm, time_point=0.3)

julia

plot_rsa(filepath::String; input_dir=pwd(), participant_selection=participants(), kwargs...)

Load RSA data and plot. Accepts either a .jld2 filepath or a pattern to discover and plot all matching files (one plot per file).

Examples

julia

plot_rsa("rsa_results.jld2")
plot_rsa("rsa_results")

source

EegFun.plot_spatial_kurtosis_components Method

julia

plot_spatial_kurtosis_components(kurtosis_comps::Vector{Int}, metrics_df::DataFrame; kwargs...)

Plot spatial kurtosis z-scores for all ICA components and highlight those exceeding the threshold.

Arguments

kurtosis_comps::Vector{Int}: Vector of component indices identified as having high spatial kurtosis.
metrics_df::DataFrame: DataFrame containing spatial kurtosis metrics. Expected to have columns :Component and :z_spatial_kurtosis.

Keyword Arguments

z_threshold::Float64: Z-score threshold for the reference line (default: 3.0).
display_plot::Bool: Whether to display the plot (default: true).

Returns

Named tuple (fig, axis).

source

EegFun.plot_stat_heatmap Method

julia

plot_stat_heatmap(result::StatsResult; kwargs...)

Plots a 2D heatmap of the t-statistics (Channels x Time).

source

EegFun.plot_tf Method

julia

plot_tf(filepath::String; kwargs...)
plot_tf(tf::TimeFreqData; channel_selection, baseline_interval, kwargs...)
plot_tf(tfs::Vector{TimeFreqData}; channel_selection, baseline_interval, kwargs...)

Plot time-frequency data as a heatmap (time × frequency). Supports single condition, multi-condition grid, and topographic layouts.

Arguments

filepath::String: Path to a .jld2 file, or a TimeFreqData / Vector{TimeFreqData} object
channel_selection::Function: Channel filter (default: all channels)
baseline_interval: Baseline window as (start, stop) in seconds (default: nothing)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

baseline_method::Symbol = :db: Baseline correction method: :db, :absolute, :relative, :relchange, :percent, :zscore
colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::Nothing = nothing: Custom colorbar label. If nothing, automatically determined
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the heatmap
colorrange::Nothing = nothing: Color range as (min, max) tuple. If nothing, automatically determined from data
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
interpolate::Bool = false: Whether to interpolate the heatmap for a smoother appearance
layout::Symbol = :single: Layout type: :single, :grid, or :topo
plot_title::Nothing = nothing: Plot title. If nothing, automatically determined from condition name and channel
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for plot titles
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for x-axis display (😒 or :ms). Only affects axis labels and tick formatting — all intervals remain in seconds.
xlim::Nothing = nothing: X-axis time limits as (min, max) tuple in seconds. If nothing, shows all time points
xticks::Nothing = nothing: Custom x-axis ticks (e.g., -0.2:0.2:1.0)
ylogscale::Bool = false: Whether to use logarithmic scale for the frequency (y) axis
yticks::Nothing = nothing: Custom y-axis ticks (e.g., [2, 10, 20, 40, 80])

Layout Options

layout_kwargs::@NamedTuple{} = NamedTuple(): Additional parameters to configure grid or topographical layouts (e.g., grid_dims, topo_plot_width, grid_rowgap)

Examples

julia

plot_tf("tf_morlet_result.jld2")
plot_tf("tf_morlet_result.jld2"; layout=:grid, channel_selection=channels([:Cz, :Pz]))
plot_tf(tf; colormap=:RdBu, ylogscale=true, baseline_interval=(-0.3, 0.0))

source

EegFun.plot_tf_stats Method

julia

plot_tf_stats(result::TFStatsResult;
              channel_selection::Function = channels(),
              channel_plot_order::Union{Nothing, Vector{Symbol}} = nothing,
              content::Symbol = :tvalues,
              significance::Symbol = :contour,
              colormap = nothing,
              colorrange = nothing,
              ylogscale::Bool = false,
              colorbar::Bool = true,
              significance_color = :black,
              significance_linewidth::Real = 2.0,
              stipple_alpha::Real = 0.4,
              opacity_alpha::Real = 0.3,
              figure_size = nothing,
              display_plot::Bool = true)

Plot TF statistical results as heatmaps with significance overlays.

Works with both TFClusterPermutationResult (from permutation_test) and TFAnalyticResult (from analytic_test).

Arguments

result::TFStatsResult: Statistical result to plot
channel_selection::Function: Channel selection predicate (default: all channels)
content::Symbol: What to plot as the heatmap:
- :tvalues (default) - t-statistic values
- :difference - power difference (condition A - B)
- :power_a - grand average power for condition A
- :power_b - grand average power for condition B
significance::Symbol: How to visualize significant regions:
- :contour (default) - black contour lines around significant regions
- :stipple - semi-transparent dots over non-significant regions
- :opacity - dim non-significant regions
- :none - no significance overlay
colormap: Colormap (default: :RdBu)
colorrange: Color range tuple or nothing for auto (auto-symmetric for t-values)
ylogscale::Bool: Log scale for frequencies (default: false)
colorbar::Bool: Show colorbar (default: true)
significance_color: Color for contour lines (default: :black)
significance_linewidth::Real: Width of contour lines (default: 2.0)
stipple_alpha::Real: Alpha for stipple dots (default: 0.4)
opacity_alpha::Real: Alpha for dimming non-significant regions (default: 0.3)
figure_size: Figure size tuple or nothing for auto
display_plot::Bool: Display the plot (default: true)

Returns

Named tuple (fig, axes) with Makie Figure and vector of Axes.

Examples

julia

# Basic t-value heatmap with contour significance
result = permutation_test(prepared; n_permutations=1000, cluster_type=:temporal)
plot_tf_stats(result, channel_selection=channels(:Cz))

# Power difference with stipple overlay
plot_tf_stats(result, content=:difference, significance=:stipple)

# Multiple channels in grid
plot_tf_stats(result, channel_selection=channels([:Cz, :Fz, :Pz, :Oz]))

# With analytic test results
result_analytic = analytic_test(prepared)
plot_tf_stats(result_analytic, significance=:opacity, colormap=:viridis)

source

EegFun.plot_topography! Method

In-place topographic plot for a specific epoch of multi-epoch data.

source

EegFun.plot_topography! Method

In-place topographic plot: subset data and render onto an existing figure/axis.

source

EegFun.plot_topography Method

julia

plot_topography(ica::InfoIca; ...)

Plot multiple ICA component topographies in a grid layout within a new Figure.

Arguments

ica::InfoIca: The ICA result object (contains layout information).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Returns

fig::Figure: The generated Makie Figure containing the grid of topoplots.

Examples

Basic Usage

julia

# Plot first 10 components (default)
fig = plot_topography(ica)

# Plot specific range of components
fig = plot_topography(ica, component_selection = components(5:15))

# Plot specific components
fig = plot_topography(ica, component_selection = components([1, 3, 5, 7]))

# Plot all components (if screen can handle it)
fig = plot_topography(ica, component_selection = components())

Advanced Selection

julia

# Plot components with custom selection
fig = plot_topography(ica, 
    component_selection = components(1:10)  # First 10 components
)

# Plot even-numbered components
fig = plot_topography(ica, 
    component_selection = components(2:2:20)  # Even components 2, 4, 6, ..., 20
)

source

EegFun.plot_topography Method

Create a topographic plot for a specific epoch of MultiDataFrameEeg data.

source

EegFun.plot_topography Method

Create a topographic plot for a single SingleDataFrameEeg; supports n_topo time bins.

source

EegFun.plot_topography Method

julia

plot_topography(tf::TimeFreqData;
                 freq_range::Tuple{Real, Real},
                 interval_selection::Interval = times(),
                 baseline_interval = nothing,
                 baseline_method::Symbol = :db,
                 kwargs...)

Plot a topographic map of average power within a frequency band and time window.

Arguments

tf::TimeFreqData: Time-frequency data
freq_range::Tuple{Real, Real}: Frequency range to average over (e.g., (8.0, 12.0) for alpha)
interval_selection::Interval: Time window (default: all time points)
baseline_interval: Baseline window as (start, stop) in seconds (e.g., (-0.3, 0.0)). Default: nothing
baseline_method::Symbol: Baseline method (default: :db). Options: :db, :absolute, :relative, :relchange, :percent, :zscore

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Returns

Named tuple (fig, ax)

Examples

julia

# Alpha-band power (8-12 Hz) in 300-500ms window with dB baseline
plot_topography(tf, freq_range=(8.0, 12.0), interval_selection=times(0.3, 0.5),
                baseline_interval=(-0.3, 0.0))

# Theta-band power across full time window
plot_topography(tf, freq_range=(4.0, 7.0))

source

EegFun.plot_topography Method

julia

plot_topography(filepath::String; input_dir=pwd(), participant_selection=participants(), kwargs...)

Load data and create topographic plots. Accepts either a .jld2 filepath or a pattern to discover and plot all matching files (one plot per file).

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Examples

julia

plot_topography("grand_average_erps_final.jld2")
plot_topography("erps_final")
plot_topography("erps_final", participant_selection = participants(1))

source

EegFun.plot_topography Method

Create a multi-panel topographic plot for a vector of datasets, one subplot per condition.

source

EegFun.plot_topography Method

Plot a single epoch from each EpochData in the vector.

source

EegFun.plot_topography Method

Average epochs per condition, then delegate to the Vector{ErpData} topography method.

source

EegFun.plot_topography_3d Method

julia

plot_topography_3d(dat::MultiDataFrameEeg, epoch::Int; kwargs...)

Create a 3D topographic plot for a specific epoch of MultiDataFrameEeg data.

source

EegFun.plot_topography_3d Method

julia

plot_topography_3d(dat::SingleDataFrameEeg; kwargs...)

Plot a perfectly smooth 3D interpolation of EEG data mapped onto a realistically proportioned head mesh.

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

camera_azimuth::Nothing = nothing: Initial camera azimuth angle (degrees) for 3D plots. (nothing for auto)
camera_elevation::Nothing = nothing: Initial camera elevation angle (degrees) for 3D plots. (nothing for auto)
colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

source

EegFun.plot_topography_stats Method

julia

plot_topography_stats(result::StatsResult;
                 n_topos::Int = 10,
                 interval_selection::Interval = times(),
                 topo_data::Symbol = :tvalues,
                 highlight_significant::Bool = true,
                 highlight_color = :white,
                 highlight_marker::Symbol = :circle,
                 highlight_size::Real = 8,
                 highlight_threshold::Real = 0.5,
                 kwargs...)

Plot a grid of topographic maps showing statistical results across time windows.

Each panel shows the spatial distribution of t-statistics (or difference amplitudes) averaged within a time window, with significant channels highlighted as markers.

Arguments

result::StatsResult: Results from analytic_test or permutation_test
n_topos::Int: Number of topographic panels (default: 10)
interval_selection::Interval: Time window to display (default: full range). Use times(start, stop) to specify
topo_data::Symbol: What to display on the topographic maps:
- :tvalues (default) — t-statistics from the statistical test
- :difference — difference wave amplitude (condition A − condition B)
highlight_significant::Bool: Whether to overlay markers on significant channels (default: true)
highlight_color: Color for significance markers (default: :white)
highlight_marker::Symbol: Marker symbol for significant channels (default: :circle). Options: :circle, :cross, :diamond, :star5, :xcross, :utriangle, :dtriangle, etc.
highlight_size::Real: Size of significance markers (default: 8)
highlight_threshold::Real: Proportion of time points within a window that must be significant to mark a channel (default: 0.5). 0.0 = any single time point (union), 0.5 = majority, 1.0 = all time points (intersection)

Additional keyword arguments from PLOT_TOPOGRAPHY_KWARGS are supported:

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Returns

Named tuple (fig, axes, colorbar)

Examples

julia

# Basic usage with analytic test
result = analytic_test(prepared, correction_method=:no)
plot_topography_stats(result)

# Show difference wave amplitudes instead of t-values
plot_topography_stats(result, topo_data=:difference)

# Focus on a specific time window with more panels
plot_topography_stats(result, interval_selection=times(0.1, 0.4), n_topos=15)

# Custom marker style for significant channels
plot_topography_stats(result, highlight_marker=:star5, highlight_color=:yellow, highlight_size=12)

source

EegFun.plot_topography_stats Method

julia

plot_topography_stats(result::TFStatsResult;
                 freq_range::Tuple{Real, Real},
                 n_topos::Int = 10,
                 interval_selection::Interval = times(),
                 topo_data::Symbol = :tvalues,
                 highlight_significant::Bool = true,
                 highlight_color = :white,
                 highlight_marker::Symbol = :circle,
                 highlight_size::Real = 8,
                 highlight_threshold::Real = 0.5,
                 kwargs...)

Plot a grid of topographic maps from TF statistical results across time windows for a selected frequency band.

Each panel shows the spatial distribution of t-statistics (or power difference) averaged within a time window and frequency band, with significant channels highlighted.

A channel is marked significant when the proportion of significant time×frequency bins within the panel's window meets or exceeds highlight_threshold.

Arguments

result::TFStatsResult: TF statistical result (from permutation_test or analytic_test)
freq_range::Tuple{Real, Real}: Frequency range to average over (e.g., (8.0, 12.0))
n_topos::Int: Number of topographic panels (default: 10)
interval_selection::Interval: Time window to display (default: full range). Use times(start, stop) to specify
topo_data::Symbol: :tvalues (default) or :difference
highlight_significant::Bool: Overlay markers on significant channels (default: true)
highlight_threshold::Real: Proportion of time×freq bins that must be significant to mark a channel (default: 0.5). 0.0 = any bin, 1.0 = all bins
highlight_color, highlight_marker, highlight_size: Marker styling

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

colorbar_kwargs::@NamedTuple{} = NamedTuple(): Additional kwargs passed directly to the Makie Colorbar block (see Makie's Colorbar documentation for available attributes).
colorbar_label::String = "": Label for the colorbar
colorbar_plot::Bool = true: Whether to show the colorbar
colorbar_plot_numbers::Vector{Any} = Any[]: Plot indices for which to show colorbars. Empty list shows colorbars for all plots.
colorbar_position::Symbol = :right: Position of the colorbar (:right, :left, :top, :bottom, or tuple)
colormap::Nothing = nothing: Colormap for the topography
component_selection::EegFun.var"#components##0#components##1" = EegFun.var"#components##0#components##1"(): Function that returns boolean vector for component filtering
dims::Nothing = nothing: Grid dimensions (rows, cols). If nothing, calculates best square-ish grid
display_plot::Bool = true: Whether to display the plot
figure_padding::NTuple{4, Int64} = (10, 30, 10, 10): Padding around entire figure as (left, right, bottom, top) tuple (in pixels)
figure_title::String = "": Title drawn at the top of the entire figure canvas
figure_title_fontsize::Int64 = 24: Font size for figure title
gridscale::Int64 = 75: Grid resolution for interpolation
head_color::Nothing = nothing: Color of the head shape outline.
head_linewidth::Int64 = 2: Line width of the head shape outline.
head_radius::Float64 = 1.0: Radius of the head shape in mm.
highlight_channels::Nothing = nothing: Highlight channel groups as a NamedTuple or Vector of NamedTuples. Each group: (channels=[:Cz, :Pz], color=:white, size=8, marker=:circle)
interactive::Bool = true: Whether to enable interactive features
label_color::Nothing = nothing: Color of electrode labels.
label_fontsize::Int64 = 20: Font size for electrode labels.
label_plot::Bool = true: Whether to plot electrode labels.
label_xoffset::Int64 = 0: X-axis offset for electrode labels.
label_yoffset::Int64 = 0: Y-axis offset for electrode labels.
method::Symbol = :thin_plate: Interpolation method: :multiquadratic, :inverse_multiquadratic, :gaussian, :inverse_quadratic, :thin_plate, :polyharmonic, :shepard, :nearest, :spherical_spline. See https://eljungsk.github.io/ScatteredInterpolation.jl/dev/methods/ for details on methods.
num_levels::Int64 = 20: Number of contour levels (for ICA plots). For standard plots, use ylim instead.
plot_title::Nothing = nothing: Plot title
plot_title_align::Tuple{Symbol, Symbol} = (:center, :top): Alignment of the inner plot title
plot_title_fontsize::Int64 = 16: Font size for the title
plot_title_position::Nothing = nothing: Relative (x, y) coordinates for the plot title (e.g., (0.5, 0.95)). If provided, the title is drawn inside the axis.
point_color::Nothing = nothing: Color of electrode points.
point_marker::Symbol = :circle: Marker style for electrode points.
point_markersize::Int64 = 12: Size of electrode point markers.
point_plot::Bool = true: Whether to plot electrode points.
theme_fontsize::Nothing = nothing: Font size for theme
time_unit::Symbol = :s: Time unit for display labels (😒 or :ms). Only affects title strings — all intervals and selections remain in seconds.
use_global_scale::Bool = false: Do multiple ICA topoplots share the same color scale based on min/max across all components?
ylim::Nothing = nothing: Y-axis limits (nothing for auto). For ICA plots, use num_levels instead.
zoom_step::Float64 = 0.2: Fractional zoom step for arrow keys (e.g. 0.2 means 20% zoom in/out)

Returns

Named tuple (fig, axes, colorbar)

Examples

julia

# Alpha-band statistics
plot_topography_stats(result, freq_range=(8.0, 12.0))

# Theta-band with more panels and lower threshold
plot_topography_stats(result, freq_range=(4.0, 7.0), n_topos=15, highlight_threshold=0.3)

# Specific time window
plot_topography_stats(result, freq_range=(8.0, 12.0), interval_selection=times(0.1, 0.5))

source

EegFun.plot_trigger_overview Method

julia

plot_trigger_overview(trigger_times, trigger_values, trigger_count)

Plot trigger events as a scatter plot with vertical lines.

Arguments

trigger_times: Vector of times when triggers occurred
trigger_values: Vector of trigger values at those times
trigger_count: OrderedDict mapping trigger values to their counts

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

display_plot::Bool = true: Whether to display the plot.
event_line_height::Float64 = 0.05: Height of event lines.
event_line_width::Int64 = 1: Line width for individual event lines.
font_size::Int64 = 24: Font size for text elements.
ignore_triggers::Vector{Int64} = Int64[]: Vector of trigger codes to ignore.
initial_position::Float64 = -2.0: Initial position of the time interval in seconds.
label_fontsize::Int64 = 20: Font size for labels.
line_offset::Float64 = 0.1: Offset for trigger vertical lines.
linewidth_trigger::Int64 = 1: Line width for trigger vertical lines.
marker_size::Int64 = 15: Size of markers in the trigger overview plot.
max_window_size::Float64 = 100.0: Maximum size of the time interval in seconds.
min_window_size::Float64 = 0.1: Minimum size of the time interval in seconds.
position_step::Float64 = 0.5: Step size for position slider.
time_label_offset::Float64 = -0.001: Vertical offset for time labels.
timeline_width::Int64 = 2: Line width for the main timeline.
window_size::Float64 = 10.0: Size of the time window to display in seconds.
window_size_step::Float64 = 1.0: Step size for window size slider.
xgrid::Bool = false: Whether to show x-axis grid
xminorgrid::Bool = false: Whether to show x-axis minor grid
y_max_limit::Float64 = 0.15: Maximum y-axis limit.
y_min_limit::Float64 = -0.1: Minimum y-axis limit.
ygrid::Bool = false: Whether to show y-axis grid
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

fig: The Makie Figure object
ax: The Axis object containing the plot

source

EegFun.plot_trigger_timing Method

julia

plot_trigger_timing(dat::ContinuousData; kwargs...)

Plot trigger timing with interactive x-axis sliders for scrolling and window size.

Arguments

dat::ContinuousData: The ContinuousData object containing the triggers
ignore_triggers: Vector of trigger codes to ignore (optional)
Other plotting parameters (window_size, display_plot, etc.)

Keyword Arguments

All keyword arguments below have sensible defaults. You can override any by passing the corresponding keyword argument.

General Plot Settings

display_plot::Bool = true: Whether to display the plot.
event_line_height::Float64 = 0.05: Height of event lines.
event_line_width::Int64 = 1: Line width for individual event lines.
font_size::Int64 = 24: Font size for text elements.
ignore_triggers::Vector{Int64} = Int64[]: Vector of trigger codes to ignore.
initial_position::Float64 = -2.0: Initial position of the time interval in seconds.
label_fontsize::Int64 = 20: Font size for labels.
line_offset::Float64 = 0.1: Offset for trigger vertical lines.
linewidth_trigger::Int64 = 1: Line width for trigger vertical lines.
marker_size::Int64 = 15: Size of markers in the trigger overview plot.
max_window_size::Float64 = 100.0: Maximum size of the time interval in seconds.
min_window_size::Float64 = 0.1: Minimum size of the time interval in seconds.
position_step::Float64 = 0.5: Step size for position slider.
time_label_offset::Float64 = -0.001: Vertical offset for time labels.
timeline_width::Int64 = 2: Line width for the main timeline.
window_size::Float64 = 10.0: Size of the time window to display in seconds.
window_size_step::Float64 = 1.0: Step size for window size slider.
xgrid::Bool = false: Whether to show x-axis grid
xminorgrid::Bool = false: Whether to show x-axis minor grid
y_max_limit::Float64 = 0.15: Maximum y-axis limit.
y_min_limit::Float64 = -0.1: Minimum y-axis limit.
ygrid::Bool = false: Whether to show y-axis grid
yminorgrid::Bool = false: Whether to show y-axis minor grid

Returns

fig::Figure: The Makie figure object
ax::Axis: The Makie axis object

Example

julia

# Plot all triggers
fig, ax = plot_trigger_timing(dat)

# Ignore specific trigger codes
fig, ax = plot_trigger_timing(dat; ignore_triggers=[1, 255])

source

Plotting Functions ​

Index ​

Functions ​

Plotting Functions

Index

Functions