freq_DTW: Acoustic dissimilarity using dynamic time warping on dominant...
In maRce10/warbleR: Streamline Bioacoustic Analysis

freq_DTW

R Documentation

Acoustic dissimilarity using dynamic time warping on dominant frequency contours

Description

freq_DTW calculates acoustic dissimilarity of frequency contours using dynamic time warping. Internally it applies the dtwDist function from the dtw package.

Usage

freq_DTW(X = NULL, type = "dominant", wl = 512, wl.freq = 512, length.out = 20,
wn = "hanning", ovlp = 70, bp = NULL, threshold = 15, threshold.time = NULL,
threshold.freq = NULL, img = TRUE, parallel = 1, path = NULL, ts.df = NULL,
img.suffix = "dfDTW", pb = TRUE, clip.edges = TRUE, window.type = "none",
open.end = FALSE, scale = FALSE, frange.detec = FALSE,  fsmooth = 0.1,
adjust.wl = TRUE, ...)

Arguments

`X`	object of class 'selection_table', 'extended_selection_table' or data frame containing columns for sound file name (sound.files), selection number (selec), and start and end time of signal (start and end). The output of `auto_detec` can be used as the input data frame.
`type`	Character string to determine the type of contour to be detected. Three options are available, "dominant" (default), "fundamental" and "entropy".
`wl`	A numeric vector of length 1 specifying the window length of the spectrogram, default is 512.
`wl.freq`	A numeric vector of length 1 specifying the window length of the spectrogram for measurements on the frequency spectrum. Default is 512. Higher values would provide more accurate measurements.
`length.out`	A numeric vector of length 1 giving the number of measurements of frequency desired (the length of the time series).
`wn`	Character vector of length 1 specifying window name. Default is "hanning". See function `ftwindow` for more options.
`ovlp`	Numeric vector of length 1 specifying % of overlap between two consecutive windows, as in `spectro`. Default is 70.
`bp`	A numeric vector of length 2 for the lower and upper limits of a frequency bandpass filter (in kHz). Default is `NULL`.
`threshold`	amplitude threshold (%) for frequency detection. Default is 15.
`threshold.time`	amplitude threshold (%) for the time domain. Use for frequency detection. If `NULL` (default) then the 'threshold' value is used.
`threshold.freq`	amplitude threshold (%) for the frequency domain. Use for frequency range detection from the spectrum (see 'frange.detec'). If `NULL` (default) then the 'threshold' value is used.
`img`	Logical argument. If `FALSE`, image files are not produced. Default is `TRUE`.
`parallel`	Numeric. Controls whether parallel computing is applied. It specifies the number of cores to be used. Default is 1 (i.e. no parallel computing).
`path`	Character string containing the directory path where the sound files are located. If `NULL` (default) then the current working directory is used.
`ts.df`	Optional. Data frame with frequency contour time series of signals to be compared. If provided "X" is ignored.
`img.suffix`	A character vector of length 1 with a suffix (label) to add at the end of the names of image files. Default is `NULL`.
`pb`	Logical argument to control progress bar. Default is `TRUE`.
`clip.edges`	Logical argument to control whether edges (start or end of signal) in which amplitude values above the threshold were not detected will be removed. If `TRUE` (default) this edges will be excluded and contours will be calculated on the remaining values. Note that DTW cannot be applied if missing values (e.i. when amplitude is not detected).
`window.type`	`dtw` windowing control parameter. Character: "none", "itakura", or a function (see `dtw`).
`open.end`	`dtw` control parameter. Performs open-ended alignments (see `dtw`).
`scale`	Logical. If `TRUE` frequency values are z-transformed using the `scale` function, which "ignores" differences in absolute frequencies between the signals in order to focus the comparison in the frequency contour, regardless of the pitch of signals. Default is `TRUE`.
`frange.detec`	DEPRECATED.
`fsmooth`	A numeric vector of length 1 to smooth the frequency spectrum with a mean sliding window (in kHz) used for frequency range detection (when `frange.detec = TRUE`). This help to average amplitude "hills" to minimize the effect of amplitude modulation. Default is 0.1.
`adjust.wl`	Logical. If `TRUE` 'wl' (window length) is reset to be lower than the number of samples in a selection if the number of samples is less than 'wl'. Default is `TRUE`.
`...`	Additional arguments to be passed to `track_freq_contour` for customizing graphical output.

Details

This function extracts the dominant frequency values as a time series and then calculates the pairwise acoustic dissimilarity using dynamic time warping. The function uses the approx function to interpolate values between dominant frequency measures. If 'img' is TRUE the function also produces image files with the spectrograms of the signals listed in the input data frame showing the location of the dominant frequencies.

Value

A matrix with the pairwise dissimilarity values. If img is FALSE it also produces image files with the spectrograms of the signals listed in the input data frame showing the location of the dominant frequencies.

Author(s)

Marcelo Araya-Salas (marcelo.araya@ucr.ac.cr)

References

Araya-Salas, M., & Smith-Vidaurre, G. (2017). warbleR: An R package to streamline analysis of animal acoustic signals. Methods in Ecology and Evolution, 8(2), 184-191.

Examples

{
  # load data
  data(list = c("Phae.long1", "Phae.long2", "lbh_selec_table"))
  writeWave(Phae.long2, file.path(tempdir(), "Phae.long2.wav")) # save sound files
  writeWave(Phae.long1, file.path(tempdir(), "Phae.long1.wav"))

  # dominant frequency
  freq_DTW(lbh_selec_table,
    length.out = 30, flim = c(1, 12), bp = c(2, 9),
    wl = 300, path = tempdir()
  )

  # fundamental frequency
  freq_DTW(lbh_selec_table,
    type = "fundamental", length.out = 30, flim = c(1, 12),
    bp = c(2, 9), wl = 300, path = tempdir()
  )
}

maRce10/warbleR documentation built on April 8, 2024, 11:08 p.m.