Measure wavelet packet decomposition features (EXPERIMENTAL)

wpd_features Measure wavelet packet decomposition features.

Usage

wpd_features(X, normalize = TRUE, threshold1 = 6,
threshold2 = 0.5, path = NULL, pb = TRUE, parallel = 1)

Arguments

X: object of class 'selection_table', 'extended_selection_table' or data frame with the following columns: 1) "sound.files": name of the sound files, 2) "sel": number of the selections, 3) "start": start time of selections, 4) "end": end time of selections. The output of auto_detec can also be used as the input data frame.
normalize: Logical to determine if features are normalized by signal duration.
threshold1: Threshold (%) for wavelet coefficient detection. Equivalent to denominator of equation 6 in Selin et al (2007). Must be a value between 0 and 1.
threshold2: Threshold for width detection. Equivalent to threshold 2 (th2) in equation 7 in Selin et al (2007).
path: Character string containing the directory path where the sound files are located. If NULL (default) then the current working directory is used.
pb: Logical argument to control progress bar and messages. 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).

Value

A data frame with rows for each of the selections in 'X' in addition to four wavelet packet decomposition features: max.energy, position, spread and width.

Details

Measures wavelet packet decomposition features. STILL UNDER DEVELOPMENT. USE IT UNDER YOUR OWN RISK.

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.Selin A., J. Turunen, and J. T. Tanttu, 2007. Wavelets in recognition of bird sounds. EURASIP Journal on Advances in Signal Processing.

Author

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

Examples

{
  data(list = c("Phae.long1", "Phae.long2", "lbh_selec_table"))
  writeWave(Phae.long1, file.path(tempdir(), "Phae.long1.wav"))
  writeWave(Phae.long2, file.path(tempdir(), "Phae.long2.wav"))

  # not normalize
  wpd_features(lbh_selec_table[1:5, ], threshold2 = 0.3, nor = FALSE, path = tempdir())
}
#>      sound.files selec max.energy position    spread width
#> 1 Phae.long1.wav     1 3819085942     3413 0.5333922    18
#> 2 Phae.long1.wav     2 4566803930     3371 0.5617731    15
#> 3 Phae.long1.wav     3 1710652669     3332 4.4784859    31
#> 4 Phae.long2.wav     1  123488775     3872 1.0150520   125
#> 5 Phae.long2.wav     2  347589172     3364 1.2633529    41