gibbonID: gibbonID

In DenaJGibbon/gibbonR: gibbonR: An R package for the detection and classification of acoustic signals using machine learning

gibbonID

Description

Function that extracts MFCCs as features from .wav files and plots them using UMAP. Points can be colored using affinity propagation clustering or by class labels. With the option to overlay spectrogram images.

Usage

gibbonID(
  input.dir,
  output.dir,
  min.freq,
  max.freq,
  pattern = ".wav",
  add.spectrograms = FALSE,
  class = "fixed",
  q.fixed = 0.1,
  win.avg = "standard",
  spec.ratio = 40
)

Arguments

input.dir	Directory where the .wav file clips are location
output.dir	Directory to save the spectrogram thumbnails.
min.freq	Minimum frequency (Hz) of signals of interest
max.freq	Maximum frequency (Hz) of signals of interest
pattern	Pattern to search fo rin input.dir; default is '.wav'
add.spectrograms	Logical; overlay spectrogram images
class	Option of 'affinity.adaptive', 'fixed.affinity' or 'no.clustering'; Specifies whether to do adaptive or fixed 'q' affinity propagation clustering, or to color points by class label.
q.fixed	If class=='fixed.affinity' specify value of 'q'. See ??apcluster for more details.
win.avg	Option of 'false','mean.sd' or 'standard'; whether to return MFCCs for each non-overlapping time window, calculate mean and SD over each MFCC or calculated MFCCs for a set number of time windows.
spec.ratio	Value to scale the spectrograms.

Examples

gibbonID(input.dir="/Users/denaclink/Desktop/RStudio Projects/gibbonR/data/MultipleSoundClasses/",output.dir="/Users/denaclink/Desktop/RStudio Projects/gibbonR/data/MultipleSoundClasses/Thumbnails/",win.avg='standard',add.spectrograms=TRUE,min.freq=400,max.freq=1600,class='no.clustering')

DenaJGibbon/gibbonR documentation built on Nov. 28, 2024, 2:52 a.m.