Package index • eyeris

🧠 Core Pipeline

Start here with the full pipeline wrapper to quickly and easily call and customize the opinionated glassbox pipeline in eyeris.

glassbox(): The opinionated "glass box" eyeris pipeline
eyelogger(): Run eyeris commands with automatic logging of R console's stdout and stderr

⏱️ Epoching Pupil Data

Conveniently extract tidy trial-based epochs with optional baseline correction.

epoch(): Epoch (and baseline) pupil data based on custom event message structure

📤 Export & Visualize

Save out BIDS-style derivatives, generate diagnostic HTML reports, and interactively plot and explore your pupil data.

bidsify(): Save out pupil time series data in a BIDS-like structure
summarize_confounds(): Extract confounding variables calculated separately for each pupil data file
plot(<eyeris>): Plot pre-processed pupil data from eyeris
plot_gaze_heatmap(): Create gaze heatmap of eye coordinates
plot_binocular_correlation(): Plot binocular correlation between left and right eye data
eyeris_color_palette(): Default color palette for eyeris plotting functions

🗄 Database Storage & Analysis

High-performance database storage and querying powered by DuckDB. Scalable alternative to CSV files for large studies, cloud computing, and collaborative research.

eyeris_db_collect(): Extract and aggregate eyeris data across subjects from database
eyeris_db_summary(): Get summary statistics for eyeris database
eyeris_db_connect(): Connect to eyeris project database (user-facing)
eyeris_db_disconnect(): Disconnect from eyeris database (user-facing)
eyeris_db_read(): Read eyeris data from database
eyeris_db_list_tables(): List available tables in eyeris database
eyeris_db_to_chunked_files(): Export eyeris database to chunked files
eyeris_db_to_parquet(): Split eyeris database into N parquet files by data type
read_eyeris_parquet(): Read parquet files back into R
process_chunked_query(): Process large database query in chunks
eyeris_db_split_for_sharing(): Split eyerisdb for data sharing and distribution
eyeris_db_reconstruct_from_chunks(): Reconstruct eyerisdb from chunked files

🔧 Preprocessing Steps

Modular functions used by the glassbox pipeline for cleaning and transforming pupil data.

load_asc(): Load and parse SR Research EyeLink .asc files
deblink(): NA-pad blink events / missing data
detransient(): Remove pupil samples that are physiologically unlikely
interpolate(): Interpolate missing pupil samples
lpfilt(): Lowpass filtering of time series data
downsample(): Downsample pupil time series with anti-aliasing filtering
bin(): Bin pupil time series by averaging within time bins
detrend(): Detrend the pupil time series
zscore(): Z-score pupil time series data

🧩 Build Your Own Extensions

Advanced tools for creating custom steps that plug into the glassbox pipeline.

pipeline_handler(): Build a generic operation (extension) for the eyeris pipeline

📈 Demo Datasets

Example eye-tracking / pupil datasets for testing and demonstrating pipeline functionality.

eyelink_asc_demo_dataset(): Access example EyeLink .asc demo dataset file provided by the eyeris package.
eyelink_asc_binocular_demo_dataset(): Access example EyeLink .asc binocular mock dataset file provided by the eyeris package.