STUDY Workflows

Group-level STUDY functions for design, clustering, measures, and plotting.

Study Setup and Validation

eegprep.std_addvarlevel(STUDY[, designind])	Return STUDY with one/two design-variable levels.
eegprep.std_builddesignmat(design, trialinfo)	Build a design matrix from a STUDY design and trial metadata.
eegprep.std_checkconsist(STUDY, *args[, ...])	Check whether each value of a STUDY factor has the same subject count.
eegprep.std_checkdatasession(STUDY[, ...])	Check dataset/session alignment for a STUDY and loaded ALLEEG.
eegprep.std_checkdatasetinfo(STUDY, ALLEEG)	Return STUDY.datasetinfo consistency checks for loaded datasets.
eegprep.std_checkdesign(STUDY[, designind])	Return 1 when a design has no continuous variables or multi-valued extras.
eegprep.std_checkfiles(STUDY[, ALLEEG, ...])	Check loaded STUDY data and cached measures for standalone EEGPrep.
eegprep.std_checkset(STUDY, ALLEEG, *[, ...])	Normalize a STUDY dict and refresh dataset/design consistency metadata.
eegprep.std_combtrialinfo(datasetinfo, inds)	Return trial rows enriched with selected datasetinfo fields.
eegprep.std_editset(STUDY, ALLEEG, *args[, ...])	Modify STUDY metadata and datasetinfo entries.
eegprep.std_findgroupvars(STUDY)	Return dataset variables that are constant within each subject.
eegprep.std_maketrialinfo(STUDY, ALLEEG)	Populate STUDY and EEG trial information from each time-locking event.
eegprep.std_rebuilddesign(STUDY[, ALLEEG, ...])	Refresh STUDY design variables after dataset metadata changes.
eegprep.std_selectdataset(STUDY, ALLEEG[, ...])	Return selected 1-based dataset indices and trial indices.
eegprep.std_uniformfiles(STUDY, ALLEEG)	Return 1 for uniform channels, 0 for mismatch, -1 for missing files.
eegprep.std_uniformsetinds(STUDY)	Return 1 when STUDY channel group set indices are uniform.

Clustering

corrmap performs two-pass, polarity-invariant component matching against a template scalp map. Its average templates are RMS-normalized so arbitrary ICA column scale cannot bias which components are selected on the second pass. Datasets must use the same labelled montage; use std_interp first when montages differ. pop_corrmap is the history-producing scripted wrapper.

eegprep.corrmap(STUDY, ALLEEG, n_tmp, index, ...)	Find ICA maps correlated with one template component.
eegprep.pop_corrmap(STUDY, ALLEEG, n_tmp, ...)	Run noninteractive CORRMAP matching and optionally return history.
eegprep.std_apcluster(clustdata, *[, ...])	Cluster rows using deterministic affinity propagation updates.
eegprep.std_centroid(data[, labels])	Return centroids for all rows or for each positive label.
eegprep.std_clustplot(STUDY, ALLEEG[, ...])	Plot a compact cluster summary for GUI and console workflows.
eegprep.std_createclust(STUDY, ALLEEG, *, ...)	Create child clusters from one cluster label per preclustering row.
eegprep.std_dipoleclusters(*args, **kwargs)	Report the standalone boundary for STUDY dipole-cluster workflows.
eegprep.std_findoutlierclust(data[, labels, ...])	Return 1-based row indices farther than threshold cluster spreads.
eegprep.std_mergeclust(STUDY, ALLEEG, mrg_cls)	Merge two or more 1-based STUDY clusters into a new child cluster.
eegprep.std_moveoutlier(STUDY, ALLEEG, ...)	Move component positions from a cluster into its outlier cluster.
eegprep.std_preclust(STUDY, ALLEEG[, ...])	Build the PCA-reduced matrix used by pop_clust.
eegprep.std_readtopo(STUDY[, ALLEEG, ...])	Read cached STUDY component scalp topographies.
eegprep.std_rejectoutliers(STUDY, ALLEEG[, ...])	Move components farther than th cluster-distance stds to outliers.
eegprep.std_renameclust(STUDY, ALLEEG, cls, ...)	Rename one 1-based STUDY cluster and update parent/child links.

Measures

eegprep.std_erpplot(STUDY, ALLEEG, *args, ...)	Plot precomputed ERPs grouped by the selected STUDY design.
eegprep.std_erspplot(STUDY, ALLEEG, *args, ...)	Plot precomputed ERSPs grouped by the selected STUDY design.
eegprep.std_interp(STUDY, ALLEEG[, chans, ...])	Interpolate selected missing channels into every STUDY dataset.
eegprep.std_itcplot(STUDY, ALLEEG, *args, ...)	Plot precomputed ITCs grouped by the selected STUDY design.
eegprep.std_precomp(STUDY, ALLEEG[, ...])	Precompute ERP, spectrum, ERSP, and ITC measures for a STUDY.
eegprep.std_readdata(STUDY[, ALLEEG, ...])	Read precomputed STUDY measures from EEGPrep's in-memory cache.
eegprep.std_readerp(STUDY[, ALLEEG])	Read cached STUDY ERP measures.
eegprep.std_readersp(STUDY[, ALLEEG])	Read cached STUDY ERSP measures.
eegprep.std_readfilelimo(source)	Load one or more EEGPrep LIMO .npz outputs.
eegprep.std_readitc(STUDY[, ALLEEG])	Read cached STUDY ITC measures.
eegprep.std_readspec(STUDY[, ALLEEG])	Read cached STUDY spectrum measures.
eegprep.std_specplot(STUDY, ALLEEG, *args, ...)	Plot precomputed spectra grouped by the selected STUDY design.
eegprep.std_topoplot(STUDY, ALLEEG, *args[, ...])	Plot polarity-aligned cluster centroids or their component maps.

Plot and Statistics Parameters

eegprep.pop_dipparams(STUDY, *args[, return_com])	Set defaults or named options in STUDY.etc.dipparams.
eegprep.pop_erpimparams(STUDY, *args[, ...])	Set defaults or named options in STUDY.etc.erpimparams.
eegprep.pop_erpparams(STUDY, *args[, return_com])	Set defaults or named options in STUDY.etc.erpparams.
eegprep.pop_erspparams(STUDY, *args[, ...])	Set defaults or named options in STUDY.etc.erspparams.
eegprep.pop_specparams(STUDY, *args[, ...])	Set defaults or named options in STUDY.etc.specparams.
eegprep.pop_statparams(STUDY, *args[, ...])	Set STUDY statistics options, including EEGLAB and FieldTrip sub-options.
eegprep.std_stat(data[, options, ...])	Compute EEGLAB-style condition, group, and interaction statistics.

Plotting

eegprep.std_dipplot(STUDY, ALLEEG, *args[, ...])	Select and plot localized components from one or more STUDY clusters.
eegprep.std_pacplot(STUDY, ALLEEG, *args[, ...])	Read and optionally plot precomputed STUDY PAC measures.

Other

eegprep.std_findsameica(ALLEEG[, icathreshold])	Group 1-based dataset indices with near-identical ICA weights*sphere.
eegprep.std_getindvar(STUDY[, mode, scandesign])	Return STUDY factor names, values, subject groupings, and pairing flags.
eegprep.std_gettrialsind(trialinfo, *args[, ...])	Return 1-based trial indices matching all requested trialinfo values.
eegprep.std_indvarmatch(value, valuelist)	Return 1-based indices where an independent-variable value matches.
eegprep.std_limo(data, design, *[, method, ...])	Fit a first-level mass-univariate linear model.
eegprep.std_limodesign(factors, trialinfo, *args)	Create LIMO-compatible categorical and continuous design matrices.
eegprep.std_limoresults(source[, analysis, ...])	Compute contrasts, group tests, regressions, or central tendencies.
eegprep.std_makedesign(STUDY, ALLEEG[, ...])	Create or replace a 1-based STUDY design.
eegprep.std_movecomp(STUDY, ALLEEG, ...[, ...])	Move component positions from one 1-based STUDY cluster to another.
eegprep.std_pac(EEG_or_STUDY[, ALLEEG, ...])	Compute phase-amplitude coupling for an EEG dataset or STUDY.
eegprep.std_prepare_neighbors(STUDY, ALLEEG, ...)	Prepare a FieldTrip-like neighbor list and LIMO adjacency matrix.
eegprep.std_readpac(STUDY[, ALLEEG, ...])	Read EEGPrep-owned cached STUDY PAC data when present.
eegprep.std_rmalldatafields(STUDY[, chanorcomp])	Return STUDY without cached measure/data fields for the requested target.
eegprep.std_rmdat(STUDY, ALLEEG, *args[, ...])	Remove datasets from STUDY/ALLEEG and return removed 1-based indices.
eegprep.std_savedat(tmpfile, structure)	Save a measure structure as JSON or MATLAB-compatible MAT data.
eegprep.std_saveindvar(STUDY, *[, return_com])	Save factor descriptors under STUDY.etc.eegprep.independent_variables.
eegprep.std_selectdesign(STUDY, ALLEEG, ...)	Select a 1-based STUDY design index.
eegprep.std_selsubject(data, subject, ...[, ...])	Return cached-measure cells with only the requested subject columns.
eegprep.std_substudy(STUDY, ALLEEG, *args[, ...])	Return a STUDY/ALLEEG subset using EEGLAB-facing 1-based selectors.