# Sample of 3D point coordinates (semilandmarks) acquired with `eigensound` function This sample file was acquired using `eigensound(analysis.type = "threeDshape")` and features 3D point coordinates (i.e. semilandmarks) from the calls of three frog species: **Physalaemus centralis**, **P. cuvieri** and **P. kroyeri** (Amphibia, Anura, Leptodactylidae). data ## Format An object of the class `"array"` (`base` package). `"array"` is a special type of `"list"` that can be thought as a filing cabinet, in which the `array` is the cabinet and each element is an arquive. This special `list` can be used in the subsequent steps of the eigensound protocol (MacLeod et al., 2013; Rocha & Romano **in prep**). ## Source Sample data of `"Wave"` objects employed on `eigensound` analysis: * `centralis`: Advertisement call of **Physalaemus centralis**; original recording housed at Fonoteca Neotropical Jacques Vielliard (FNJV-0031188). Recorded by Adão José Cardoso. * `cuvieri`: Advertisement call of **Physalaemus cuvieri**; original recording housed at Coleção Bioacústica da Universidade Federal de Minas Gerais (CBUFMG-00196). Recorded by Pedro Rocha. * `kroyeri`: Advertisement call of **Physalaemus kroyeri**; Original recording housed at Fonoteca Neotropical Jacques Vielliard (FNJV-0032047). Recorded by Werner Bokermann. ```r data(eig.sample) ``` ## Details Each species is represented by three stereotyped acoustic units (i.e. notes from their advertisement calls), which are available as sample data from `SoundShape` (`"Wave"` objects: `centralis`, `cuvieri` and `kroyeri`). See Rocha & Romano (**in prep**) for details. Prior to `eigensound` analysis, each of the sample calls had the acoustic units selected, stored as separate `".wav"` files, and aligned at beggining of sound window using `align.wave` (see `Examples` section). `eig.sample` is composed of 9 elements (i.e. three species, each represented by three acoustic units). Each element is a matrix with 3200 rows and 3 columns (i.e. X, Y and Z coordinates of 3200 semilandmarks). The number of semilandmarks acquired will depend on the number of cells per side on the sound window (i.e. `x.length` and `y.length` arguments from `eigensound` function). The analysis itself (`eigensound` function) featured relative amplitude backgroud at 25 dB (`dBlevel = 25`), sampling grid of 70 cells on the time (X-axis) and 47 cells on the frequency (Y-axis) (`x.length = 70`, `y.length = 47`, respectively). Sound window ranged from 0 to 0.8 s (X-axis), and from 0 to 4 kHz (Y-axis) (`tlim = c(0, 0.8)`, `flim = c(0, 4)`, respectively). Spectrogram parameters were the same as `eigensound` default: `f = 44100`, `wl = 512`, `ovlp = 70`. ## Examples ```r data(eig.sample) # PCA using 3D semilandmark coordinates pca.eig.sample <- stats::prcomp(geomorph::two.d.array(eig.sample)) # Verify names for each acoustic unit and the order in which they appear dimnames(eig.sample)[[3]] # Create factor to use as groups in subsequent ordination plot sample.gr <- factor(c(rep("centralis", 3), rep("cuvieri", 3), rep("kroyeri", 3))) # Plot result of Principal Components Analysis pca.plot(PCA.out = pca.eig.sample, groups = sample.gr, conv.hulls = sample.gr, main="PCA of 3D coordinates", leg=TRUE, leg.pos = "top") # Verify hypothetical sound surfaces for each Principal Component hypo.surf(threeD.out=eig.sample, PC=1, flim=c(0, 4), tlim=c(0, 0.8), x.length=70, y.length=47, plot.exp = FALSE) #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# # Recreate eig.sample object # #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# library(seewave) library(tuneR) # Create temporary folder to store ".wav" files wav.at <- file.path(base::tempdir(), "eig.sample") if(!dir.exists(wav.at)) dir.create(wav.at) # Create temporary folder to store results store.at <- file.path(base::tempdir(), "eig.sample-output") if(!dir.exists(store.at)) dir.create(store.at) # Select three acoustic units within each sound data data(cuvieri) spectro(cuvieri, flim = c(0,4)) cut.cuvieri1 <- cutw(cuvieri, f=44100, from=0, to=0.5, output = "Wave") cut.cuvieri2 <- cutw(cuvieri, f=44100, from=0.7, to=1.2, output = "Wave") cut.cuvieri3 <- cutw(cuvieri, f=44100, from=1.4, to=1.9, output = "Wave") data("centralis") spectro(centralis, flim = c(0,4)) cut.centralis1 <- cutw(centralis, f=44100, from=0.1, to=0.8, output = "Wave") cut.centralis2 <- cutw(centralis, f=44100, from=1.05, to=1.75, output = "Wave") cut.centralis3 <- cutw(centralis, f=44100, from=2.1, to=2.8, output = "Wave") data("kroyeri") spectro(kroyeri, flim = c(0,4)) cut.kroyeri1 <- cutw(kroyeri, f=44100, from=0.1, to=1, output = "Wave") cut.kroyeri2 <- cutw(kroyeri, f=44100, from=1.5, to=2.3, output = "Wave") cut.kroyeri3 <- cutw(kroyeri, f=44100, from=2.9, to=3.8, output = "Wave") # Export new wave files containing acoustic units and store on previosly created folder writeWave(cut.cuvieri1, filename = file.path(wav.at, "cut.cuvieri1.wav"), extensible = FALSE) writeWave(cut.cuvieri2, filename = file.path(wav.at, "cut.cuvieri2.wav"), extensible = FALSE) writeWave(cut.cuvieri3, filename = file.path(wav.at, "cut.cuvieri3.wav"), extensible = FALSE) writeWave(cut.centralis1, filename = file.path(wav.at, "cut.centralis1.wav"), extensible = FALSE) writeWave(cut.centralis2, filename = file.path(wav.at, "cut.centralis2.wav"), extensible = FALSE) writeWave(cut.centralis3, filename = file.path(wav.at, "cut.centralis3.wav"), extensible = FALSE) writeWave(cut.kroyeri1, filename = file.path(wav.at, "cut.kroyeri1.wav"), extensible = FALSE) writeWave(cut.kroyeri2, filename = file.path(wav.at, "cut.kroyeri2.wav"), extensible = FALSE) writeWave(cut.kroyeri3, filename = file.path(wav.at, "cut.kroyeri3.wav"), extensible = FALSE) # Place sounds at beggining of sound window before analysis align.wave(wav.at = wav.at, wav.to = "Aligned", time.length = 0.8, time.perc = 0.005, dBlevel = 25) # Verify alignment using analysis.type = "twoDshape" eigensound(analysis.type = "twoDshape", wav.at = file.path(wav.at, "Aligned"), store.at = store.at, flim=c(0, 4), tlim=c(0, 0.8), plot.exp = TRUE, plot.as = "jpeg", dBlevel = 25) # Go to folder specified by store.at and check jpeg files created # Run eigensound function using analysis.type = "threeDshape" on aligned wave files # Store results as R object eig.sample <- eigensound(analysis.type="threeDshape", wav.at = file.path(wav.at, "Aligned"), flim=c(0, 4), tlim=c(0, 0.8), dBlevel=25, plot.exp = FALSE, x.length=70, y.length = 47, log.scale = TRUE) ``` ## References MacLeod, N., Krieger, J. & Jones, K. E. (2013). Geometric morphometric approaches to acoustic signal analysis in mammalian biology. **Hystrix, the Italian Journal of Mammalogy, 24**(1), 110-125. Rocha, P. & Romano, P. (2021) The shape of sound: A new `R` package that crosses the bridge between Bioacoustics and Geometric Morphometrics. **Methods in Ecology and Evolution, 12**(6), 1115-1121.

eig.sample dataset