{ "_id": "6a232b89530b9bc726bcf415", "Package": "eyeris", "Type": "Package", "Title": "Flexible, Extensible, & Reproducible Pupillometry Preprocessing", "Version": "3.1.0", "Date": "2026-06-05", "Language": "en-US", "Authors@R": "c(\nperson(given = \"Shawn\", family = \"Schwartz\", role = c(\"aut\", \"cre\"),\nemail = \"shawn.t.schwartz@gmail.com\",\ncomment = c(ORCID = \"0000-0001-6444-8451\")),\nperson(given = \"Mingjian\", family = \"He\", role = \"ctb\"),\nperson(given = \"Haopei\", family = \"Yang\", role = \"ctb\"),\nperson(given = \"Alice\", family = \"Xue\", role = \"ctb\"),\nperson(given = \"Gustavo\", family = \"Santiago-Reyes\", role = \"ctb\")\n)", "Description": "Pupillometry offers a non-invasive window into the mind\nand has been used extensively as a psychophysiological readout\nof arousal signals linked with cognitive processes like\nattention, stress, and emotional states [Clewett et al. (2020)\n; Kret & Sjak-Shie (2018)\n; Strauch (2024)\n]. Yet, despite decades of\npupillometry research, many established packages and workflows\nto date lack design patterns based on Findability,\nAccessibility, Interoperability, and Reusability (FAIR)\nprinciples [see Wilkinson et al. (2016)\n]. 'eyeris' provides a modular,\nperformant, and extensible preprocessing framework for\npupillometry data with BIDS-like organization and interactive\noutput reports [Esteban et al. (2019)\n; Gorgolewski et al. (2016)\n]. Development was supported, in\npart, by the Stanford Wu Tsai Human Performance Alliance,\nStanford Ric Weiland Graduate Fellowship, Stanford Center for\nMind, Brain, Computation and Technology, NIH National Institute\non Aging Grants (R01-AG065255, R01-AG079345), NSF GRFP\n(DGE-2146755), McKnight Brain Research Foundation Clinical\nTranslational Research Scholarship in Cognitive Aging and\nAge-Related Memory Loss, American Brain Foundation, and the\nAmerican Academy of Neurology.", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "License": "MIT + file LICENSE", "Config/testthat/edition": "3", "URL": "https://shawnschwartz.com/eyeris/,\nhttps://github.com/shawntz/eyeris/", "BugReports": "https://github.com/shawntz/eyeris/issues", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libx11-dev", "Repository": "https://shawntz.r-universe.dev", "Date/Publication": "2026-06-05 14:54:57 UTC", "RemoteUrl": "https://github.com/shawntz/eyeris", "RemoteRef": "HEAD", "RemoteSha": "8a20de2154d0c26493a118b7417835b0d74027be", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-05 19:55:31 UTC", "User": "root" }, "Author": "Shawn Schwartz [aut, cre] (ORCID:\n),\nMingjian He [ctb],\nHaopei Yang [ctb],\nAlice Xue [ctb],\nGustavo Santiago-Reyes [ctb]", "Maintainer": "Shawn Schwartz ", "MD5sum": "2a0ab0abae72344a6e7c3cdc252909d0", "_user": "shawntz", "_type": "src", "_file": "eyeris_3.1.0.tar.gz", "_fileid": "87c4d02a643ae9148633dee5ee1959bea7627af25232160dcec0d1e504244777", "_filesize": 4082957, "_sha256": "87c4d02a643ae9148633dee5ee1959bea7627af25232160dcec0d1e504244777", "_created": "2026-06-05T19:55:31.000Z", "_published": "2026-06-05T20:03:21.178Z", "_distro": "noble", "_jobs": [ { "job": 79803177418, "time": 196, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7445644075" }, { "job": 79803177424, "time": 230, "config": "linux-release-x86_64", "r": "4.6.0", 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"eyeris_db_reconstruct_from_chunks" ] }, { "page": "eyeris_db_split_for_sharing", "title": "Split eyerisdb for data sharing and distribution", "topics": [ "eyeris_db_split_for_sharing" ] }, { "page": "eyeris_db_summary", "title": "Get summary statistics for eyeris database", "topics": [ "eyeris_db_summary" ] }, { "page": "eyeris_db_to_chunked_files", "title": "Export eyeris database to chunked files", "topics": [ "eyeris_db_to_chunked_files" ] }, { "page": "eyeris_db_to_parquet", "title": "Split eyeris database into N parquet files by data type", "topics": [ "eyeris_db_to_parquet" ] }, { "page": "glassbox", "title": "The opinionated \"glass box\" 'eyeris' pipeline", "topics": [ "glassbox" ] }, { "page": "interpolate", "title": "Interpolate missing pupil samples", "topics": [ "interpolate" ] }, { "page": "load_asc", "title": "Load and parse SR Research EyeLink '.asc' files", "topics": [ "load_asc" ] }, { "page": "lpfilt", "title": "Lowpass filtering of time series data", "topics": [ "lpfilt" ] }, { "page": "pipeline_handler", "title": "Build a generic operation (extension) for the 'eyeris' pipeline", "topics": [ "pipeline_handler" ] }, { "page": "plot_binocular_correlation", "title": "Plot binocular correlation between left and right eye data", "topics": [ "plot_binocular_correlation" ] }, { "page": "plot_gaze_heatmap", "title": "Create gaze heatmap of eye coordinates", "topics": [ "plot_gaze_heatmap" ] }, { "page": "plot.eyeris", "title": "Plot pre-processed pupil data from 'eyeris'", "topics": [ "plot.eyeris" ] }, { "page": "process_chunked_query", "title": "Process large database query in chunks", "topics": [ "process_chunked_query" ] }, { "page": "read_eyeris_parquet", "title": "Read parquet files back into R", "topics": [ "read_eyeris_parquet" ] }, { "page": "summarize_confounds", "title": "Extract confounding variables calculated separately for each pupil data file", "topics": [ "summarize_confounds" ] }, { "page": "zscore", "title": "Z-score pupil time 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Gaze Heatmaps", "Standalone Gaze Heatmaps", "Manual Gaze Heatmap Creation", "Epoch-Level Gaze Heatmaps", "📚 Citing eyeris" ], "created": "2025-03-24 23:52:52", "modified": "2025-07-25 23:21:48", "commits": 9 }, { "source": "database-guide.Rmd", "filename": "database-guide.html", "title": "Working with eyeris Databases: A Complete Guide", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Why Use Databases Instead of CSV Files?", "The Case for Database Storage", "When to Use CSV vs a Database", "Getting Started: Creating Your First eyeris Database", "Basic Database Creation", "Database-Only Workflow (Cloud Optimized)", "Batch Processing Multiple Subjects", "Connecting to and Exploring eyeris Databases", "Basic Database Connection", "eyeris Database Overview and Exploration", "Data Extraction: From Simple to Advanced", "Simple Data Extraction", "Targeted Data Extraction", "Working with Binocular Data", "Epoch-Specific Extraction", "Output Format Options", "Advanced Database Operations", "Direct SQL Queries", "Reading Individual Tables", "Real-World Analysis Examples", "Example 1: Pupil Response Analysis Across Subjects", "Example 2: Quality Control and Confounds Analysis", "Performance Comparison: Database vs CSV", "Speed and Memory Benchmarks", "Best Practices and Tips", "Database Management", "Cloud Computing Optimization", "Error Handling and Debugging", "Migration and Interoperability", "Converting Existing CSV Data to Database", "Exporting Database Data Back to CSV", "Conclusion", "Session Information" ], "created": "2025-08-03 08:36:57", "modified": "2026-06-05 14:54:57", "commits": 4 } ], "_score": 7.6674529528899535, "_indexed": true, "_nocasepkg": "eyeris", "_universes": [ "shawntz" ], "_previous": "3.0.1", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "3.1.0", "date": "2026-06-05T19:58:10.000Z", "distro": "noble", "commit": "8a20de2154d0c26493a118b7417835b0d74027be", "fileid": 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