Movatterモバイル変換

SqueakR 1.3.0

Addedanimal field for each added experiment data,which updates experiment metadata foranimals field.Updated compatibility to match semi-automatic and automatic SqueakRpipelines, as well asdescribe_experiment() function.Updated documentation to reflect the change
Added Plotly sunburst plot (to functions list and dashboard) tograph proportions of collected data done per experimenter, as well asdata collected per animal per group
Added Plotly 3D surface plot (plotSurface()) using 2Dkernel density estimation to represent call density against principalfrequency and call length
Added functions for unblinding experimenters to data
Added function —plotContours() — which rendersplotSurface() as a 2D rendering, flanked by histogramsdisplaying distributions of principal frequency and call length
Standardized some function naming (plotSurface instead ofplotCallDataSurface, etc)

Usedreport package for analyses: added functions forreporting descriptive statistics for grouped data in SqueakR Dashboardtab
Deprecated SqueakR Dashboard repository on GitHub and mergedfunctions into SqueakR
Added 3D cluster plot visualization functionplotClusters() against call length (z), principal frequency(x) and mean power (y) using plotly, available in base SqueakR and ondashboard

Merged SqueakR dashboard into SqueakR package! Dashboard can now berun after loading the package by runningsqueakRDashboard()
Added function for calculating ANOVA between groups
Added ANOVA tab on SqueakR Dashboard for determining statisticalsignificance between call features

Added fully-automatic pipeline function(autosqueakRpipeline()) which references Google Sheet toadd data without experimenter input for every file
Renamedexperiment_pipeline() tosemisqueakRpipeline()
Added function (remove_experiment_data()) to removedata from experiment object
Updatedvignette to reflect package changes

RecreatedNEWS.md file to track changes to thepackage.
Added functions for generating experiment and analyzing data betweenexperimental groups.
Added visualizations including ethnograms, histograms, box-plots,and correlation matrices.