FishDiveR (version 1.1.0)

pca_data: Prepare all data for Principal Component Analysis

Description

pca_data loads the wavelet statistics for each of the tags listed in 'tag_vector'. Performs various checks to ensure compatibility of wavelets, and combines them into a data frame containing only the chosen statistics.

Usage

pca_data(
  tag_vector,
  data_folder = data_dir,
  phase_mean = FALSE,
  phase_variance = FALSE,
  power_mean = TRUE,
  power_variance = TRUE,
  mean_sq_power = FALSE,
  amplitude_mean = TRUE,
  amplitude_variance = FALSE,
  output = FALSE,
  output_folder = NULL,
  verbose = FALSE
)

Value

A data frame with the combined data for all tag ID's listed, containing the wavelet statistics to be used in Principal Component Analysis.

Arguments

tag_vector

A character vector of tag IDs. E.g. 'c("123456", "456283", "AB98XJ").

data_folder

Parent folder path with separate folders for each tag data. E.g. "C:/Tag data". Defaults to 'data_dir'

phase_mean

TRUE or FALSE to include this wavelet statistic. Default FALSE

phase_variance

TRUE or FALSE to include this wavelet statistic. Default FALSE

power_mean

TRUE or FALSE to include this wavelet statistic. Default TRUE

power_variance

TRUE or FALSE to include this wavelet statistic. Default TRUE

mean_sq_power

TRUE or FALSE to include this wavelet statistic. Default FALSE

amplitude_mean

TRUE or FALSE to include this wavelet statistic. Default TRUE

amplitude_variance

TRUE or FALSE to include this wavelet statistic. Default FALSE

output

Logical. If TRUE, output is saved to output_folder. Defaults to FALSE.

output_folder

Output folder path. If output = TRUE, output_folder must be provided. Defaults to NULL.

verbose

Logical. If TRUE, progress messages are shown. Defaults to FALSE.

Examples

# Set file path
filepath <- system.file("extdata", package = "FishDiveR")

# Run pca_data function
pc_data <- pca_data(
  tag_vector = c("data"),
  data_folder = filepath,
  phase_mean = FALSE,
  phase_variance = FALSE,
  power_mean = TRUE,
  power_variance = TRUE,
  mean_sq_power = FALSE,
  amplitude_mean = TRUE,
  amplitude_variance = FALSE,
  output = TRUE,
  output_folder = tempdir(),
  verbose = TRUE
)