Ruido (version 1.0.2)

activity: Acoustic Activity Matrix

Description

Calculate the Acoustic Activity Matrix using the methodology proposed in Burivalova 2018

Usage

activity(
  soundfile,
  channel = "stereo",
  timeBin = 60,
  dbThreshold = -90,
  targetSampRate = NULL,
  wl = 512,
  window = signal::hamming(wl),
  overlap = ceiling(length(window)/2),
  histbreaks = "FD",
  powthr = 10,
  bgnthr = 0.8,
  beta = TRUE
)

Value

This function returns a 0 and 1 matrix containing the activity for all time bins of the inputted file. The matrix's number of rows will equal to half the set window lenght (wl) and number of columns will equal the number of bins. Cells with the value of 1 represent the acoustically active frequency of a bin.

Arguments

soundfile

tuneR Wave object or path to a valid audio

channel

channel where the saturation values will be extract from. Available channels are: "stereo", "mono", "left" or "right". Defaults to "stereo".

timeBin

size (in seconds) of the time bin. Set to NULL to use the entire audio as a single bin. Defaults to 60

dbThreshold

minimum allowed value of dB for the spectrograms. Defaults to -90, as set by Towsey 2017

targetSampRate

desired sample rate of the audios. This argument is only used to down sample the audio. If NULL, then audio's sample rate remains the same. Defaults to NULL

wl

window length of the spectrogram. Defaults to 512

window

window used to smooth the spectrogram. Switch to signal::hanning(wl) to use hanning instead. Defaults to signal::hammning(wl)

overlap

overlap between the spectrogram windows. Defaults to wl/2 (half the window length)

histbreaks

breaks used to calculate Background Noise. Available breaks are: "FD", "Sturges", "scott" or any numeric value (foe example = 100). Defaults to "FD"

powthr

single numeric value to calculate the activity matrix for soundscape power (in dB). Detauls to 10

bgnthr

single numeric value to calculate the activity matrix for background noise (in %). Detauls to 0.8

beta

how BGN thresholds are calculated. If TRUE, BGN thresholds are calculated using all recordings combined. If FALSE, BGN thresholds are calculated separately for each recording. Defaults to TRUE

Details

To calculate the activity matrix, we use the methodology proposed by Burivalova 2018. We begin by applying the following formula to each time bin of the recording:

$$a_{mf} = 1\ if (BGN_{mf} > \theta_{1})\ or\ (POW_{mf} > \theta_{2});\ otherwise,\ a_{mf} = 0,$$

Where \(\theta_{1}\) equals the threshold of BGN values and \(\theta_{2}\) equals the threshold of dB values. We set 1 to active and 0 to inactive frequency windows.

References

Burivalova, Z., Towsey, M., Boucher, T., Truskinger, A., Apelis, C., Roe, P., & Game, E. T. (2018). Using soundscapes to detect variable degrees of human influence on tropical forests in Papua New Guinea. Conservation Biology, 32(1), 205-215. https://doi.org/10.1111/cobi.12968

Examples

if (require("ggplot2")) {
### Generating an artificial audio for the example
## For this example we'll generate a sweep in a noisy soundscape
library(tuneR)
library(ggplot2)

# Define parameters for the artificial audio
samprate <- 12050
dur <- 60
n <- samprate * dur

# White noise
set.seed(413)
noise <- rnorm(n)

# Linear fade-out envelope
fade <- seq(1, 0, length.out = n)

# Apply fade
signal <- noise * fade

# Create Wave object
wave <- Wave(
  left = signal,
  samp.rate = samprate,
  bit = 16
)

# Running singleSat() on the artificial audio
time <- 10
sat <- activity(wave, timeBin = time)

# Now we can plot the results
satDim <- dim(sat)
numericTime <- seq(0, dur, by = time)
labels <- paste0(numericTime[-length(numericTime)], "-", numericTime[-1], "s")

satDF <- data.frame(BIN = rep(paste0("BIN", seq(satDim[2])), each = satDim[1]),
                    WIN = rep(seq(satDim[1]), satDim[2]),
                    ACT = factor(c(sat), levels = c(0,1)))

ggplot(satDF, aes(x = BIN, y = WIN, fill = ACT)) +
  geom_tile() +
  theme_bw() +
  scale_fill_manual(values = c("white", "black")) +
  scale_y_continuous(expand = c(0,0)) +
  scale_x_discrete(expand = c(0,0), labels = labels) +
  labs(x = "Time Bin", y = "Spectral Window") +
  guides(fill = guide_legend(title = "Activity"))

}