FishDiveR (version 1.1.0)

pca_scores: Calculate Principal Component Analysis Scores not including depth statistics

Description

This function extracts the PCA scores from the PCA results and plots the loadings. This function is to be use on output from the pca_data() function not including depth statistics.

Usage

pca_scores(
  pc_results = results,
  plot_loadings = TRUE,
  every_nth = 12,
  output = FALSE,
  output_folder = NULL,
  verbose = FALSE
)

Value

A data frame of pc scores containing one column for each Principal Component kept. If processing just one tag, the attribute 'unique_tag_ID' is given to the data frame with the tag_ID. Plots the PC loadings for each row of pc_data

Arguments

pc_results

PCA class object containing the output from the 'pca_results()' function.

plot_loadings

TRUE or FALSE. Plot PC loadings figures. Default TRUE.

every_nth

Numeric. Sequence of labels to show on mean power plot. Default is 12.

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")

# Load pc_results
pc_results <- readRDS(file.path(filepath, "data/4_PCA/pc_results.rds"))

# Run pca_scores function
pc_scores <- pca_scores(
  pc_results = pc_results,
  plot_loadings = FALSE,
  every_nth = 12,
  output = TRUE,
  output_folder = tempdir(),
  verbose = TRUE
)