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Ruido is an R package that aims to provide
a simple and accessible framework for calculating less common soundscape
metrics that describes noise dynamics. It provides accessible tools for
calculating less common, but ecologically meaningful soundscape metrics,
helping researchers move beyond standard and classic indices.
These metrics can be used to explore acoustic complexity, biotic
activity, and environmental disturbance, making Ruido
useful for ecological monitoring, bioacoustic surveys, or experimental
soundscape studies.
install.packages("Ruido")
library(Ruido)devtools::install_github("Arthurigorr/Ruido")
library(Ruido)To illustrate the package’s use, we are going to use the recordings
available at: https://zenodo.org/records/17243660.
Use https://zenodo.org/records/17575795 to use lighter
recordings.
If you wish to temporary download the files using R to follow the examples, run:
options(timeout = 500)
dir <- tempdir()
recName <- paste0("GAL24576_20250401_", sprintf("%06d", seq(0, 230000, by = 10000)), ".wav")
recDir <- paste(dir, recName, sep = "/")
for (rec in recName) {
print(rec)
url <- paste0("https://zenodo.org/records/17243660/files/",
rec,
"?download=1")
download.file(url, destfile = paste(dir, rec, sep = "/"), mode = "wb")
}These examples use ggplot2 and patchwork to plot their results. Before running them, first run:
library(ggplot2)
library(patchwork)BGN_POW <- lapply(recDir, bgNoise)
time <- sapply(strsplit(recName, "_"), function(x)
paste(substr(x[3], 1, 2), substr(x[3], 3, 4), substr(x[3], 5, 6), sep = ":"))
date <- sapply(strsplit(recName, "_"), function(x)
paste(substr(x[2], 1, 4), substr(x[2], 5, 6), substr(x[2], 7, 8), sep = "-"))
dateTime <- as.POSIXct(paste(date, time))
sampRate <- BGN_POW[[1]]$sampRate
kHz <- cumsum(c(0, rep(sampRate / 6, 6))) / 1000
breaks <- round(c(1, cumsum(rep(256 / 6, 6))))
timeLabels <- time[c(1, 7, 13, 19, 24)]
timeBreaks <- as.character(dateTime[c(1, 7, 13, 19, 24)])
plotList <- list()
plotN <- 1
for (ind in c("BGN", "POW")) {
for (cha in c("left", "right")) {
core <- do.call(cbind, lapply(BGN_POW, function(x) {
x[[cha]][[ind]]
}))
dim(BGNLEFT)
coreDf <- data.frame(
TIME = as.character(rep(dateTime, each = sDim[1] * 3) + rep(rep(c(0, 60, 120), each = sDim[1]), sDim[2] / 3)),
SPEC = rep(seq(sDim[1]), sDim[2]), VAL = c(unlist(core))
)
plotList[[plotN]] <- ggplot(coreDf, aes(x = TIME, y = SPEC, fill = VAL)) +
geom_tile() +
theme_classic() +
scale_y_continuous(expand = c(0, 0), labels = kHz, breaks = breaks) +
scale_x_discrete(expand = c(0, 0), labels = timeLabels, breaks = timeBreaks) +
scale_fill_viridis_c(option = "magma", name = ind) +
labs( x = "Time of Day", y = "Frequency (kHz)", title = paste(ind, "in the", cha, "channel")
)
plotN <- plotN + 1
}
}
plotList[[1]] + plotList[[2]] + plotList[[3]] + plotList[[4]]
sat <- soundSat(dir)
SAT <- sat$values
satForPlot <- cbind(
aggregate(SAT ~ AUDIO + CHANNEL, data = SAT, sd),
aggregate(SAT ~ AUDIO + CHANNEL, data = SAT, mean)$SAT,
TIME = rep(substr(time, 1, 5), 2)
)
colnames(satForPlot)[c(3, 4)] <- c("sdSAT", "meanSAT")
ggplot(
satForPlot,
aes(x = TIME, y = meanSAT * 100, group = CHANNEL, fill = CHANNEL,
ymin = pmax(meanSAT - sdSAT, 0) * 100, ymax = pmin(meanSAT + sdSAT, 100) * 100
)
) +
geom_ribbon(alpha = 0.5) +
geom_line() +
geom_point() +
theme_classic() +
scale_y_continuous(limits = c(0, 100), expand = c(0, 0)) +
scale_x_discrete( expand = c(0, 0), breaks = c("00:00", "06:00", "12:00", "18:00", "23:00")
) +
labs(y = "Soundscape Saturation (%)") +
theme(
axis.title.x = element_blank(), axis.text = element_text(size = 15),
axis.title = element_text(size = 18, face = "bold"),
legend.title = element_text(size = 15, face = "bold"),
legend.text = element_text(size = 15)
) +
guides(fill = guide_legend(title = "Side"))
act <- multActivity(dir, powthr = sat$powthresh, bgnthr = sat$bgntresh / 100)
time <- sapply(strsplit(recName, "_"), function(x)
paste(substr(x[3], 1, 2), substr(x[3], 3, 4), substr(x[3], 5, 6), sep = ":"))
date <- sapply(strsplit(recName, "_"), function(x)
paste(substr(x[2], 1, 4), substr(x[2], 5, 6), substr(x[2], 7, 8), sep = "-"))
dateTime <- as.POSIXct(paste(date, time))
sampRate <- act$info$SAMPRATE[[1]]
kHz <- cumsum(c(0, rep(sampRate / 6, 6))) / 1000
breaks <- round(c(1, cumsum(rep(256 / 6, 6))))
timeLabels <- time[c(1, 7, 13, 19, 24)]
timeBreaks <- as.character(dateTime[c(1, 7, 13, 19, 24)])
plotList <- list()
plotN <- 1
for (cha in c("left", "right")) {
actCurrent <- act$values[, act$info$CHANNEL == cha]
actCurrentDF <- data.frame(
TIME = as.character(rep(dateTime, each = sDim[1] * 3) + rep(rep(c(0, 60, 120), each = sDim[1]), sDim[2] / 3)),
SPEC = rep(seq(sDim[1]), sDim[2]),
VAL = factor(c(unlist(actCurrent)), levels = c(0, 1))
)
plotList[[plotN]] <- ggplot(actCurrentDF, aes(x = TIME, y = SPEC, fill = VAL)) +
geom_tile() +
theme_classic() +
scale_y_continuous(expand = c(NA, NA), labels = kHz, breaks = breaks) +
scale_x_discrete(expand = c(0, 0), labels = timeLabels, breaks = timeBreaks) +
scale_fill_manual(values = c("white", "black"), labels = c("Inactive", "Active")) +
guides(fill = guide_legend(title = "Acoustic Activity")) +
labs(
x = "Time of Day",
y = "Frequency (kHz)",
title = paste("Acoustic Activity in the", cha, "channel")
)
plotN <- plotN + 1
}
plotList[[1]] + plotList[[2]] +
plot_layout(guides = "collect")
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.