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Analysis Settings ​

This demo shows how to save and replay preprocessing settings using AnalysisSettings.

What are Analysis Settings? ​

AnalysisSettings stores a preprocessing recipe that can be applied to data in one step. This is useful for:

  • Reproducing the same preprocessing across multiple datasets

  • Storing settings from interactive exploration (e.g., databrowser GUI)

  • Standardising processing across participants in a study

Tracked Settings ​

An AnalysisSettings object can contain:

  • hp_filter: High-pass filter cutoff frequency

  • lp_filter: Low-pass filter cutoff frequency

  • reference: Re-referencing scheme (e.g., :avg, :Cz)

  • repaired_channels: Channels to interpolate

  • repair_method: Interpolation method

  • removed_ica_components: ICA components to remove

  • selected_regions: ROI definitions

Applying Settings ​

  • apply_analysis_settings!(dat, settings): Apply in-place (mutating)

  • apply_analysis_settings(dat, settings): Return a processed copy (non-mutating)

  • apply_analysis_settings!(dat, ica, settings): Apply with ICA component removal

Analysis Info Tracking ​

Every EegFun data object automatically tracks its preprocessing history via analysis_info. This records what filters, references, and other operations have been applied.

Workflow Summary ​

This demo covers:

  • Inspecting analysis info on data objects

  • Creating AnalysisSettings with filter and reference parameters

  • Applying settings to data (both mutating and non-mutating)

Code Examples ​

Show Code
julia
# Demo: Analysis Settings
# Shows how to save and replay preprocessing settings
# (filter, rereference, ICA) using AnalysisSettings.

# 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")

using EegFun
using GLMakie

#######################################################################
# SETUP
#######################################################################

dat = EegFun.read_raw_data(EegFun.example_path("data/bdf/example1.bdf"))
layout = EegFun.read_layout(EegFun.example_path("layouts/biosemi/biosemi72.csv"))
EegFun.polar_to_cartesian_xy!(layout)
dat = EegFun.create_eegfun_data(dat, layout)


#######################################################################
# INSPECTING ANALYSIS INFO
#######################################################################

# Every EegFun data object tracks its preprocessing state
dat.analysis_info  # shows reference, filter info

# Apply some preprocessing
EegFun.highpass_filter!(dat, 0.1)
EegFun.rereference!(dat, :avg)

# Check that analysis info is updated
dat.analysis_info  # now shows hp_filter = 0.1, reference = :avg


#######################################################################
# USING ANALYSIS SETTINGS
#######################################################################

# AnalysisSettings stores a recipe for preprocessing
settings = EegFun.AnalysisSettings(1.0, 30.0, :avg, Symbol[], :none, Tuple{Float64,Float64}[], Int[])

# Apply settings to fresh data (non-mutating — returns a processed copy)
dat_fresh = EegFun.read_raw_data(EegFun.example_path("data/bdf/example1.bdf"))
dat_fresh = EegFun.create_eegfun_data(dat_fresh, layout)

dat_processed = EegFun.apply_analysis_settings(dat_fresh, settings)
dat_processed.analysis_info

# Or apply in-place (mutating)
# EegFun.apply_analysis_settings!(dat_fresh, settings)

See Also ​