Package: PupillometryR 0.0.5

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_0.0.5.tar.gz
PupillometryR_0.0.5.zip(r-4.5)PupillometryR_0.0.5.zip(r-4.4)PupillometryR_0.0.5.zip(r-4.3)
PupillometryR_0.0.5.tgz(r-4.4-any)PupillometryR_0.0.5.tgz(r-4.3-any)
PupillometryR_0.0.5.tar.gz(r-4.5-noble)PupillometryR_0.0.5.tar.gz(r-4.4-noble)
PupillometryR_0.0.5.tgz(r-4.4-emscripten)PupillometryR_0.0.5.tgz(r-4.3-emscripten)
PupillometryR.pdf |PupillometryR.html✨
PupillometryR/json (API)
NEWS

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

Peer review:

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

Datasets:
  • pupil_data - Data collected in a pupillometry study by Sylvain Sirois

On CRAN:

7.53 score 42 stars 1 packages 266 scripts 663 downloads 20 exports 60 dependencies

Last updated 1 years agofrom:278ef3235f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-winNOTENov 14 2024
R-4.5-linuxNOTENov 14 2024
R-4.4-winNOTENov 14 2024
R-4.4-macNOTENov 14 2024
R-4.3-winNOTENov 14 2024
R-4.3-macNOTENov 14 2024

Exports:baseline_datacalculate_mean_pupil_sizecalculate_missing_dataclean_missing_datacreate_difference_datacreate_functional_datacreate_time_windowscreate_window_datadetect_blinks_by_columndetect_blinks_by_sizedetect_blinks_by_velocitydownsample_time_datafilter_datageom_flat_violininterpolate_datamake_pupillometryr_dataregress_datareplace_missing_datarun_functional_t_testsubset_data

Dependencies:ashbitopscliclustercolorspacecpp11deSolvedplyrfansifarverfdafdsFNNgenericsggplot2gluegtablehdrcdeisobanditsadugkernlabKernSmoothkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmepcaPPpillarpkgconfigplotfunctionspracmapurrrR6rainbowRColorBrewerRcppRCurlrlangscalessignalstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrzoo

PupillometryR

Rendered fromPupillometryR.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-09-14
Started: 2020-06-02

Readme and manuals

Help Manual

Help pageTopics
Baseline pupil data to the average pupil size within a windowbaseline_data
Calculate a mean size across two pupils over timecalculate_mean_pupil_size
Calculate the missing data amountcalculate_missing_data
Clean missing data above an acceptable thresholdclean_missing_data
Create a difference data frame when dealing with a condition column with 2 levelscreate_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 analysiscreate_time_windows
Make PupillometryR dataframe into a single collapsed window for easy analysiscreate_window_data
detect blinks by a pre-existing labelled blink column that comes from the eyetrackerdetect_blinks_by_column
detect blinks by a change in pupil sizedetect_blinks_by_size
detect blinks by a change in velocitydetect_blinks_by_velocity
Downsample frequency to reduce number of samples and data sizedownsample_time_data
Run a filter on the data to smooth it out.filter_data
ggplot Flat Violingeom_flat_violin
geom_flat_violin_HELPER2GeomFlatViolin
geom_flat_violin_HELPER1%||% gfv_helper1
Interpolate across the gaps in datainterpolate_data
Prepare data for pre-processing in PupillometryRmake_pupillometryr_data
Helper function mean2mean2
Pre-prepared plots of PupillometryR dataplot.Pupil_difference_data
Pre-prepared plots of PupillometryR dataplot.Pupil_test_data
Pre-prepared plots of PupillometryR dataplot.Pupil_window_data
Pre-prepared plots of PupillometryR dataplot.PupillometryR
Data collected in a pupillometry study by Sylvain Siroispupil_data
Regress one pupil against another for extra smoothingregress_data
replaces missing observations if you have some degree of incomplete observationsreplace_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 windowssubset_data