Package: PupillometryR 0.0.7

PupillometryR: A Unified Pipeline for Pupillometry Data

Provides a unified pipeline to clean, prepare, plot, and run basic analyses on pupillometry experiments.

Authors:Samuel Forbes [aut, cre], David Robinson [ctb]

PupillometryR_0.0.7.tar.gz
PupillometryR_0.0.7.zip(r-4.7)PupillometryR_0.0.7.zip(r-4.6)PupillometryR_0.0.7.zip(r-4.5)
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PupillometryR/json (API)

# Install 'PupillometryR' in R:

install.packages('PupillometryR', repos = c('https://samhforbes.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/samhforbes/pupillometryr/issues

Datasets:

pupil_data - Data collected in a pupillometry study by Sylvain Sirois

On CRAN:

8.13 score 47 stars 1 packages 317 scripts 546 downloads 20 exports 57 dependencies

Last updated from:1fc24c80ef. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	143
source / vignettes	OK	202
linux-release-x86_64	NOTE	154
macos-release-arm64	NOTE	115
macos-oldrel-arm64	NOTE	104
windows-devel	NOTE	115
windows-release	NOTE	123
windows-oldrel	NOTE	103
wasm-release	OK	100

Exports:baseline_data calculate_mean_pupil_size calculate_missing_data clean_missing_data create_difference_data create_functional_data create_time_windows create_window_data detect_blinks_by_column detect_blinks_by_size detect_blinks_by_velocity downsample_time_data filter_data geom_flat_violin interpolate_data make_pupillometryr_data regress_data replace_missing_data run_functional_t_test subset_data

Dependencies:ash bitops cli cluster colorspace cpp11 deSolve dplyr farver fda fds FNN generics ggplot2 glue gtable hdrcde isoband kernlab KernSmooth ks labeling lattice lifecycle locfit magrittr MASS Matrix mclust mgcv multicool mvtnorm nlme pcaPP pillar pkgconfig pracma purrr R6 rainbow RColorBrewer Rcpp RCurl rlang S7 scales signal stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr zoo

PupillometryR

Rendered fromPupillometryR.Rmdusingknitr::rmarkdown

Last update: 2025-12-15
Started: 2020-06-02

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Baseline pupil data to the average pupil size within a window	baseline_data
Calculate a mean size across two pupils over time	calculate_mean_pupil_size
Calculate the missing data amount	calculate_missing_data
Clean missing data above an acceptable threshold	clean_missing_data
Create a difference data frame when dealing with a condition column with 2 levels	create_difference_data
Makes a functional data with splines from a Pupil_difference_data dataframe.	create_functional_data
Make PupillometryR dataframe into multiple time windows for easy analysis	create_time_windows
Make PupillometryR dataframe into a single collapsed window for easy analysis	create_window_data
detect blinks by a pre-existing labelled blink column that comes from the eyetracker	detect_blinks_by_column
detect blinks by a change in pupil size	detect_blinks_by_size
detect blinks by a change in velocity	detect_blinks_by_velocity
Downsample frequency to reduce number of samples and data size	downsample_time_data
Run a filter on the data to smooth it out.	filter_data
ggplot Flat Violin	geom_flat_violin
geom_flat_violin_HELPER2	GeomFlatViolin
geom_flat_violin_HELPER1	%\|\|% gfv_helper1
Interpolate across the gaps in data	interpolate_data
Prepare data for pre-processing in PupillometryR	make_pupillometryr_data
Helper function mean2	mean2
Pre-prepared plots of PupillometryR data	plot.Pupil_difference_data
Pre-prepared plots of PupillometryR data	plot.Pupil_test_data
Pre-prepared plots of PupillometryR data	plot.Pupil_window_data
Pre-prepared plots of PupillometryR data	plot.PupillometryR
Data collected in a pupillometry study by Sylvain Sirois	pupil_data
Regress one pupil against another for extra smoothing	regress_data
replaces missing observations if you have some degree of incomplete observations	replace_missing_data
Run a functional t-test on a dataframe previously fitted with b-splines.	run_functional_t_test
Subset data to provide start and finish time windows	subset_data