run.spcc {callsync}

run.spcc

Description

Runs spectrographic cross correlation on multiple wave objects.

Usage

run.spcc(
  waves,
  freq_range = c(700, 3500),
  thr_low = 0.45,
  thr_high = 0.6,
  wl = 256,
  ovl = 250,
  method = "sd",
  sum_one = TRUE,
  mc.cores = 1,
  step_size = 10
)

Arguments

waves

a list of wave objects, e.g., from 'lapply' in combination with 'load.wave' or 'readWave'.

freq_range

numeric vector of length 2, the frequency range in Hz to return.

thr_low

numeric, the lower range (see 'method'). Pixels with lower values are set to 0 for noise reduction.

thr_high

numeric, the upper range (see 'method'). Pixels with higher values are set to 'thr_high'.

wl

numeric, window length in samples. Default is '512'.

ovl

numeric, overlap in samples. Default is '450'.

method

character, either 'sd' or 'max'. If 'sd', pixels are standardised. If 'max', pixels are normalised.

sum_one

logical, if 'TRUE' pixels are divided by the sum of all pixels, such that they sum to one.

mc.cores

numeric, how many threads to run in parallel. For Windows only one can be used.

step_size

numeric, argument for 'sliding.pixel.comparison' how many pixels should be moved for each step. Default is '10'.

Value

Matrix with row and columns names equal to the names of the wave list. Diagonal is zeroes. Other values are the normalised pairwise distances from 'sliding.pixel.comparison'.

Examples

require(callsync)
require(seewave)
require(tuneR)
path_git = 'https://raw.githubusercontent.com'
path_repo = '/simeonqs/callsync/master/tests/testthat/files'
file_1 = '/wave_1.wav'
file_2 = '/wave_2.wav'
url_1 = paste0(path_git, path_repo, file_1)
url_2 = paste0(path_git, path_repo, file_2)
local_file_1 = paste(tempdir(), file_1, sep = '/')
local_file_2 = paste(tempdir(), file_2, sep = '/')
if(!file.exists(local_file_1))
  download.file(url_1, destfile = local_file_1, mode = 'wb',)
if(!file.exists(local_file_2))
  download.file(url_2, destfile = local_file_2, mode = 'wb')
all_files = c(local_file_1, local_file_2)
waves = lapply(all_files, load.wave)
spcc_out = run.spcc(waves)