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Plot ERP Measurements ​

This demo shows how to plot ERP waveforms with measurement overlays using EegFun.plot_erp_measurements.

What Does It Do? ​

plot_erp_measurements combines ERP waveform visualization with quantified measurements in a single plot. It highlights the analysis interval and displays the computed measurement directly on the waveform, making it easy to see exactly what is being measured and where.

Supported Measurements ​

  • Mean amplitude — average voltage within the analysis interval

  • Peak amplitude — maximum or minimum voltage within the interval

  • Peak latency — time point of the peak within the interval

Key Options ​

ParameterPurpose
analysis_intervalTime window for measurement (seconds)
baseline_intervalBaseline correction window
channel_selectionWhich channels to plot
condition_selectionWhich conditions to include
layout:overlay (default) or :grid

Workflow Summary ​

This demo covers:

Mean Amplitude Overlay ​

  • Plot ERP with shaded analysis window and computed mean

Peak Latency ​

  • Show peak markers on specific channels

Grid Layout ​

  • Display each channel in its own panel with measurement annotations

File Path Input ​

  • Load data directly from JLD2 file path without pre-loading

Code Examples ​

Show Code
julia
# Demo: Plotting ERPs with Measurement Overlays
# Computes and visualizes ERP measurements in a single call.

using EegFun
# Note: EegFun.example_path() resolves bundled example data paths.
# When using your own data, simply pass the file path directly, e.g.:
# dat = EegFun.read_raw_data("/path/to/your/data.bdf")

dat = EegFun.read_data(EegFun.example_path("data/julia/erps/example1_erps_good.jld2"))

# Mean amplitude
# EegFun.plot_erp_measurements(dat, "mean_amplitude", analysis_interval = (0.3, 0.5), baseline_interval = (-0.2, 0.0)) # not really useful as too crowded!

# Peak latency with specific channels
EegFun.plot_erp_measurements(
    dat,
    "max_peak_latency",
    analysis_interval = (0.0, 1.0),
    baseline_interval = (-0.2, 0.0),
    channel_selection = EegFun.channels([:Cz, :Pz]),
)

# Grid layout
EegFun.plot_erp_measurements(dat, "max_peak_amplitude", analysis_interval = (0.0, 1.0), baseline_interval = (-0.2, 0.0), layout = :grid)

# Load from file path
EegFun.plot_erp_measurements(
    EegFun.example_path("data/julia/erps/example1_erps_good.jld2"),
    "max_peak_amplitude",
    analysis_interval = (0.0, 1.0),
    baseline_interval = (-0.2, 0.0),
    condition_selection = EegFun.conditions([1]),
    channel_selection = EegFun.channels([:Cz, :Pz]),
)

See Also ​