When using this content PLEASE CITE the preprint and this repository.
Data:
- Fig_4c.csv: source data provided by Alam et al. (2024, Nature)
- rebuttal_fig_2.csv: source data provided by Alam et al. (2024, Nature) and data measured by us from their Extended Data Fig. 6 (green versus black bars during playback)
R-scripts used in the analysis:
- Fig_point_1.r uses Fig_4c.csv and generates our Fig. 1; columns: tutor - unique tutor ID, pupil - unique pupil ID for the given tutor, tutor_path - song path length of the tutor, pupil_path - song path length of the pupil
- Fig_point_2.r uses rebuttal_fig_2.csv and generates our Fig. 2; columns: trial_id - unique trial ID, side_bias - was the long-path song during the trial played in the preferred arm or non-preferred arm by the female during the baseline period?, song_pair - unique song-pair ID; long - path length of the long path song, short - path length of the short path song, pre - the percentage of pre-trial time spent in the arm where long path song would be played during the trial, trial - the percentage of trial time spent in the arm with long path song, post - the percentage of post-trial time spent in the arm where long path song was played during the trial, trial_long - trial time spent in the arm with long path song, trial_short - trial time spent in the arm with short path song
Output: contains the generated figures in PNG format
LICENSE: terms of reuse
The figures were generated using the below indicated version of R and its related packages, running on the below indicated macOS. The installation of R and related R-packages takes only a few mintues. How to install R and R-packages is described here and here
R version 4.2.0 (2022-04-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Mojave 10.14.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale: en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages: grid, stats, graphics, grDevices, utils, datasets, methods, base
other attached packages: patchwork_1.1.3, ggpubr_0.6.0, ggpmisc_0.5.4-1, ggpp_0.5.5, ggplot2_3.5.1, data.table_1.14.8
packages loaded via a namespace (and not attached): pillar_1.9.0, compiler_4.2.0, tools_4.2.0, lifecycle_1.0.4, tibble_3.2.1, gtable_0.3.4, lattice_0.22-5, pkgconfig_2.0.3, rlang_1.1.2, Matrix_1.6-2, cli_3.6.1, polynom_1.4-1, SparseM_1.81, withr_2.5.2, dplyr_1.1.3, generics_0.1.3, vctrs_0.6.4, MatrixModels_0.5-3, tidyselect_1.2.0, glue_1.6.2, R6_2.5.1, rstatix_0.7.2, fansi_1.0.5, survival_3.5-7, carData_3.0-5, car_3.1-2, tidyr_1.3.0, purrr_1.0.2, magrittr_2.0.3, backports_1.4.1, scales_1.3.0, MASS_7.3-60, splines_4.2.0, abind_1.4-5, colorspace_2.1-0, ggsignif_0.6.4
We do not provide any demo data, because the two csv files used in the analyses are small and already contain all the data used in the analyses.
To generate Fig. 1 and/or Fig. 2, download the two csv files into Data folder of your project's root directory and create a folder Output. Open R software and the Fig_point_1.r or Fig_point_2.r R-script, install the R-packages indicated under the tools by running install.packages(c('data.table', 'ggplot2', 'ggpmisc', 'ggpubr', 'grid', 'patchwork') and run the script. The pngs of the figures will be generated in Output.