warbleR (version 1.1.17)

song_param: Calculates acoustic parameters at the song level

Description

song_param calculates descriptive statistics of songs or other higher levels of organization in the signals.

Usage

song_param(X = NULL, song_colm = "song",mean_colm = NULL, min_colm = NULL, 
max_colm = NULL, elm_colm = NULL, elm_fun = NULL, sd = FALSE, parallel = 1, pb = TRUE, 
na.rm = FALSE, weight = NULL)

Arguments

X

'selection_table', 'extended_selection_table' (created 'by.song') or data frame with the following columns: 1) "sound.files": name of the .wav files, 2) "selec": number of the selections, 3) "start": start time of selections, 4) "end": end time of selections. The ouptut of manualoc or autodetec can be used as the input data frame. Other data frames can be used as input, but must have at least the 4 columns mentioned above.

song_colm

Character string with the column name containing song labels. It can be used to label any hierarchical level at which parameters need to be calculated (e.g. syllables, phrases). Note that the function assumes that song labels are not repeated within a sound file.

mean_colm

Numeric vector with the index of the columns that will be averaged. If NULL the mean of all numeric columns in 'X' is returned.

min_colm

Character vector with the name(s) of the columns for which the minimum value is needed. Default is NULL.

max_colm

Character vector with the name(s) of the columns for which the maximum value is needed. Default is NULL.

elm_colm

Character vector with the name(s) of the columns identifying the element labels (i.e. element types). If supplied 'unq.elms' and 'mean.elm.count' are returned. Default is NULL.

elm_fun

Function to be applied to the sequence of elements composing a song. Default is NULL. Ignored if 'elm_colm' is not supplied. The name of the column containing the function's output is "elm_fun'.

sd

Logical value indicating whether standard deviaton is also returned for variables in which averages are reported. Default is FALSE.

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).

pb

Logical argument to control progress bar and messages. Default is TRUE.

na.rm

Logical value indicating whether 'NA' values should be ignored for calculations.

weight

Character vector defining 1 or more numeric vectors to weight average measurements (i.e. song parameters). Names of numeric columns in 'X' can also be used. See weighted.mean. for more details. Default is NULL (unweighted average).

Value

A data frame similar to the input 'X' data frame, but in this case each row corresponds to a single song. The data frame contains the mean or extreme values for numeric columns for each song. Columns that will be averaged can be defined with 'mean_colm' (otherwhise all numeric columns are used). Columns can be weighted by other columns in the data set (e.g. duration, frequency range). In addition, the function returns the following song level parameters:

• elm.duration: mean length of elements (in s)

• song.duration: length of song (in s)

• num.elms: number of elements (or song units)

• start: start time of song (in s)

• end: end time of song (in s)

• bottom.freq: lowest 'bottom.freq' from all song elements (in kHz)

• top.freq: highest 'top.freq' from all song elements (in kHz)

• freq.range: difference between song's 'top.freq' and 'bottom.freq' (in kHz)

• song.rate: number of elements per second (NA if only 1 element)

• gap.duration: average length of gaps (i.e. silences) in between elements (in s, NA if only 1 element)

• elm.types: number of element types (i.e. number of unique types, only if 'elm_colm' is supplied)

• mean.elm.count: mean number of times element types are found (only if 'elm_colm' is supplied)

This function assumes that song labels are not repeated within a sound file.

Details

The function calculates average or extreme values of acoustic parameters of elements in a song or other level of organization in the signals.

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.

See Also

specan

Examples

# NOT RUN {
{
# get warbleR sound file examples
data(list = c("Phae.long1", "Phae.long2", "Phae.long3", "Phae.long4", "lbh_selec_table"))
writeWave(Phae.long1, file.path(tempdir(), "Phae.long1.wav"))
writeWave(Phae.long2, file.path(tempdir(), "Phae.long2.wav"))
writeWave(Phae.long3, file.path(tempdir(), "Phae.long3.wav"))

# add a 'song' column
lbh_selec_table$song <- rep(1:4, each = 3)[1:11]

# measure acoustic parameters
sp <- specan(lbh_selec_table[1:8, ], bp = c(1, 11), 300, fast = TRUE, path = tempdir())

# add song data
sp <- merge(sp, lbh_selec_table[1:8, ], by = c("sound.files", "selec"))

# caculate song-level parameters for all numeric parameters
song_param(X = sp, song_colm = "song", parallel = 1, pb = TRUE)

# caculate song-level parameters selecting parameters with mean_colm
song_param(X = sp, song_colm = "song",mean_colm = c("dfrange", "duration"), parallel = 1, pb = TRUE)

# caculate song-level parameters for selecting parameters with mean_colm, max_colm
# and min_colm and weighted by duration
song_param(X = sp, weight = "duration", song_colm = "song",
mean_colm =  c("dfrange", "duration"), min_colm =  "mindom", max_colm = "maxdom", 
  parallel = 1, pb = TRUE)

# with two weights 
song_param(X = sp, weight = c("duration", "dfrange"), song_colm = "song",
mean_colm = c("kurt", "sp.ent"), parallel = 1, pb = TRUE)

# with two weights no progress bar
song_param(X = sp, weight = c("duration", "dfrange"), song_colm = "song",
mean_colm = c("kurt", "sp.ent"), parallel = 1, pb = FALSE)
}

# }