cluster_candidate_motifs_plot: cluster_candidate_motifs_plot
In funMoDisco: Motif Discovery in Functional Data

View source: R/cluster_candidate_motifs_plot.R

cluster_candidate_motifs_plot

R Documentation

cluster_candidate_motifs_plot

Description

This function generates plots to visualize the results of the 'cluster_candidate_motifs' function. It provides insights into the distances between motifs and curves, group-specific radii, and displays aligned motifs for each cluster.

Usage

cluster_candidate_motifs_plot(
  cluster_candidate_motifs_results,
  ylab = "",
  R_all = cluster_candidate_motifs_results$R_all,
  R_m = NULL,
  ask = TRUE
)

Arguments

`cluster_candidate_motifs_results`	A list containing the output of the 'cluster_candidate_motifs' function, which includes clustering results and distances between motifs and curves.
`ylab`	A character string specifying the label for the y-axis in the plots. Default is an empty string.
`R_all`	A numeric value representing the global radius. This is used to cut the dendrogram, requiring groups to be more than twice 'R_all' apart. The default is set to the 'R_all' component of the input results.
`R_m`	A numeric vector with group-specific radii. The length of this vector must match the number of clusters obtained by cutting the dendrogram at height '2 * R_all'. If set to NULL, the radius 'R_m' is determined within each group based on the distances between motifs of the same group and all curves.
`ask`	A logical value indicating whether the user should be prompted before a new plot is drawn. Default is TRUE.

Details

This function produces: - Histograms of distances between all motifs and all curves, highlighting the global radius. - A dendrogram of motifs cut at '2 * R_all', which allows visualization of the clustering structure. - Histograms of distances for motifs within specific clusters, comparing motifs from curves with and without the motifs. - Plots of aligned motifs for each cluster, showing their positions and distributions. - A scatter plot displaying the approximate average distance against the approximate frequency for motifs in each cluster.