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Extract frequency contours as time series

Source: R/freq_ts.R
freq_ts.Rd

freq_ts extracts the fundamental frequency values as a time series.

Usage

freq_ts(
  X,
  type = "dominant",
  wl = 512,
  length.out = 20,
  wn = "hanning",
  ovlp = 70,
  bp = NULL,
  threshold = 15,
  img = TRUE,
  parallel = 1,
  path = NULL,
  img.suffix = "frequency.ts",
  pb = TRUE,
  clip.edges = FALSE,
  leglab = "frequency.ts",
  track.harm = FALSE,
  raw.contour = FALSE,
  adjust.wl = TRUE,
  ff.method = "seewave",
  entropy.range = c(2, 10),
  ...
)

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).

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.

length.out

A numeric vector of length 1 giving the number of measurements of fundamental 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 fundamental frequency detection. Default is 15.

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.

img.suffix

A character vector of length 1 with a suffix (label) to add at the end of the names of image files.

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 this edges will be excluded and signal contour will be calculated on the remaining values. Default is FALSE. #' @param leglab A character vector of length 1 or 2 containing the label(s) of the frequency contour legend in the output image.

leglab

A character vector of length 1 or 2 containing the label(s) of the frequency contour legend in the output image.

track.harm

Logical. If TRUE warbleR's track_harmonic function is used to track dominant frequency contours. Otherwise seewave's dfreq is used by default. Default is FALSE.

raw.contour

Logical. If TRUE then a list with the original contours (i.e. without interpolating values to make all contours of equal length) is returned (and no images are produced).

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. Used only for dominant frequency detection.

ff.method

Character. Selects the method used to detect fundamental frequency contours. Either 'tuneR' (using FF) or 'seewave' (using fund). Default is 'seewave'. 'tuneR' performs faster (and seems to be more accurate) than 'seewave'.

entropy.range

Numeric vector of length 2. Range of frequency in which to display the entropy values on the spectrogram (when img = TRUE). Default is c(2, 10). Negative values can be used in order to stretch more the range.

...

Additional arguments to be passed to track_freq_contour. for customizing graphical output.

Value

A data frame with the fundamental frequency values measured across the signals. If img is TRUE it also produces image files with the spectrograms of the signals listed in the input data frame showing the location of the fundamental frequencies (see track_freq_contour description for more details).

Details

This function extracts the dominant frequency, fundamental frequency or spectral entropy contours as time series. The function uses the approx function to interpolate values between frequency measures. If there are no frequencies above the amplitude threshold (for dominant and fundamental) at the beginning or end of the signals then NAs will be generated. On the other hand, if there are no frequencies above the amplitude theshold in between signal segments in which amplitude was detected then the values of this adjacent segments will be interpolated to fill out the missing values (e.g. no NAs in between detected amplitude segments).

See also

sig2noise, track_freq_contour, freq_ts, freq_DTW

Author

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

Examples

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

# run function with dominant frequency
freq_ts(X = lbh_selec_table, length.out = 30, flim = c(1, 12), bp = c(2, 9),
wl = 300, pb = FALSE, path = tempdir())

# note a NA in the row 4 column 3 (dfreq-1)
# this can be removed by clipping edges (removing NAs at the start and/or end
# when no freq was detected)

freq_ts(X = lbh_selec_table, length.out = 30, flim = c(1, 12), bp = c(2, 9),
wl = 300, pb = FALSE, clip.edges = TRUE, path = tempdir())

# run function with fundamental frequency
freq_ts(lbh_selec_table, type = "fundamental", length.out = 50,
flim = c(1, 12),  bp = c(2, 9), wl = 300, path = tempdir())

# run function with spectral entropy
# without clip edges
freq_ts(X = lbh_selec_table, type = "entropy", threshold = 10,
clip.edges = FALSE, length.out = 10, sp.en.range = c(-25, 10), path = tempdir(),
 img = FALSE)

# with clip edges and length.out 10
freq_ts(X = lbh_selec_table, type = "entropy", threshold = 10, bp = c(2, 12),
clip.edges = TRUE, length.out = 10, path = tempdir(), img = FALSE)
}
#>       sound.files selec ffreq-1 ffreq-2 ffreq-3 ffreq-4 ffreq-5 ffreq-6 ffreq-7
#> 1  Phae.long1.wav     1  0.8954  0.8428  0.8594  0.8910  0.8402  0.8801  0.8608
#> 2  Phae.long1.wav     2  0.9015  0.8020  0.8867  0.9032  0.8525  0.8418  0.9016
#> 3  Phae.long1.wav     3  0.9453  0.8812  0.8756  0.9307  0.8591  0.8781  0.9305
#> 4  Phae.long2.wav     1  0.9292  0.8915  0.9211  0.9203  0.8966  0.8790  0.8832
#> 5  Phae.long2.wav     2  0.9200  0.9000  0.9225  0.9245  0.8980  0.8786  0.8748
#> 6  Phae.long3.wav     1  0.9317  0.9047  0.8522  0.8797  0.8587  0.8638  0.8494
#> 7  Phae.long3.wav     2  0.9325  0.9040  0.8836  0.8730  0.8540  0.8670  0.8633
#> 8  Phae.long3.wav     3  0.9161  0.9012  0.8321  0.8720  0.8539  0.8622  0.8657
#> 9  Phae.long4.wav     1  0.9245  0.8420  0.8154  0.8248  0.8346  0.8837  0.8812
#> 10 Phae.long4.wav     2  0.9309  0.8351  0.8344  0.8342  0.8491  0.9000  0.8446
#> 11 Phae.long4.wav     3  0.9489  0.8281  0.8178  0.8389  0.8546  0.8864  0.8680
#>    ffreq-8 ffreq-9 ffreq-10
#> 1   0.7787  0.8262   0.9335
#> 2   0.7977  0.8135   0.9227
#> 3   0.7821  0.8256   0.8622
#> 4   0.8718  0.8937   0.9275
#> 5   0.8774  0.8726   0.9095
#> 6   0.8543  0.8618   0.9335
#> 7   0.8450  0.8472   0.8607
#> 8   0.8406  0.8502   0.8941
#> 9   0.7762  0.8041   0.9012
#> 10  0.7699  0.8185   0.9032
#> 11  0.8041  0.8307   0.9120